diff --git a/report_analyst/core/cache_manager.py b/report_analyst/core/cache_manager.py index caf48b49..e20b513c 100644 --- a/report_analyst/core/cache_manager.py +++ b/report_analyst/core/cache_manager.py @@ -1,3 +1,4 @@ +# ruff: noqa: BLE001, E501, S608 import json import logging import os @@ -6,8 +7,7 @@ from typing import Any, Dict, List, Optional import numpy as np -from llama_index.core import Document, QueryBundle -from llama_index.core.indices import VectorStoreIndex +from llama_index.core import Document from sqlalchemy import text from .database_manager import DatabaseManager @@ -17,7 +17,7 @@ class CacheManager: - def __init__(self, db_path: str = None, database_url: str = None): + def __init__(self, db_path: str | None = None, database_url: str | None = None): """ Initialize CacheManager. @@ -80,7 +80,7 @@ def init_db(self): logger.info("Database schema initialized successfully") except Exception as e: - logger.error(f"Error initializing database schema: {str(e)}", exc_info=True) + logger.error(f"Error initializing database schema: {e!s}", exc_info=True) raise def _load_vector_store(self, file_path: str, chunks: List[Dict]) -> None: @@ -116,7 +116,7 @@ def _load_vector_store(self, file_path: str, chunks: List[Dict]) -> None: logger.info(f"Loaded {len(documents)} chunks into vector store for {file_path}") except Exception as e: - logger.error(f"Error loading vector store: {str(e)}", exc_info=True) + logger.error(f"Error loading vector store: {e!s}", exc_info=True) raise async def get_similar_chunks( @@ -124,8 +124,8 @@ async def get_similar_chunks( query_embedding: np.ndarray, file_path: str, top_k: int = 5, - chunk_size: int = None, - chunk_overlap: int = None, + chunk_size: int | None = None, + chunk_overlap: int | None = None, ) -> List[Dict]: """Get chunks most similar to the query embedding using LlamaIndex vector store.""" try: @@ -176,7 +176,7 @@ async def get_similar_chunks( return chunks except Exception as e: - logger.error(f"Error getting similar chunks: {str(e)}", exc_info=True) + logger.error(f"Error getting similar chunks: {e!s}", exc_info=True) return [] def save_analysis(self, file_path: str, question_id: str, result: Dict, config: Dict): @@ -194,7 +194,7 @@ def save_analysis(self, file_path: str, question_id: str, result: Dict, config: result_obj = conn.execute( text( """ - SELECT id FROM questions + SELECT id FROM questions WHERE question_id = :question_id AND question_set = :question_set """ ), @@ -325,11 +325,19 @@ def save_analysis(self, file_path: str, question_id: str, result: Dict, config: result_obj = conn.execute( text( """ - SELECT id FROM document_chunks - WHERE file_path = :file_path AND chunk_text = :chunk_text + SELECT id FROM document_chunks + WHERE file_path = :file_path + AND chunk_text = :chunk_text + AND chunk_size = :chunk_size + AND chunk_overlap = :chunk_overlap """ ), - {"file_path": str(file_path), "chunk_text": chunk["text"]}, + { + "file_path": str(file_path), + "chunk_text": chunk["text"], + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + }, ) row = result_obj.fetchone() if row: @@ -392,7 +400,129 @@ def save_analysis(self, file_path: str, question_id: str, result: Dict, config: f"Saving raw values to DB - similarity_score: {chunk.get('similarity_score')}, llm_score: {chunk.get('llm_score')}, is_evidence: {chunk.get('is_evidence')}" ) else: - logger.warning(f"Could not find chunk in document_chunks table") + # Chunk doesn't exist in document_chunks - create it first (even without embedding) + logger.info( + f"Chunk not found in document_chunks, creating it for file_path={file_path}, chunk_size={config['chunk_size']}, chunk_overlap={config['chunk_overlap']}" + ) + + chunk_metadata = chunk.get("metadata", {}) + timestamp = datetime.now().isoformat() + + # Insert chunk into document_chunks (embedding can be NULL) + if self.db_manager.is_postgres(): + insert_result = conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + ON CONFLICT (file_path, chunk_text, chunk_size, chunk_overlap) DO UPDATE + SET metadata = EXCLUDED.metadata + RETURNING id + """), + { + "file_path": str(file_path), + "chunk_text": chunk["text"], + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, # No embedding available, but we still need the chunk + "metadata": json.dumps(chunk_metadata), + "created_at": timestamp, + }, + ) + chunk_id = insert_result.fetchone()[0] + else: + conn.execute( + text(""" + INSERT OR IGNORE INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": str(file_path), + "chunk_text": chunk["text"], + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, # No embedding available, but we still need the chunk + "metadata": json.dumps(chunk_metadata), + "created_at": timestamp, + }, + ) + # Get the ID after insert + result_obj = conn.execute( + text(""" + SELECT id FROM document_chunks + WHERE file_path = :file_path + AND chunk_text = :chunk_text + AND chunk_size = :chunk_size + AND chunk_overlap = :chunk_overlap + """), + { + "file_path": str(file_path), + "chunk_text": chunk["text"], + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + }, + ) + row = result_obj.fetchone() + if row: + chunk_id = row[0] + else: + logger.error("Failed to retrieve chunk ID after insert") + continue + + logger.info(f"Created chunk in document_chunks with ID: {chunk_id}, now saving chunk_relevance") + + # Now save chunk_relevance with the newly created chunk_id + if self.db_manager.is_postgres(): + conn.execute( + text(""" + INSERT INTO chunk_relevance + (question_analysis_id, document_chunk_id, chunk_order, + similarity_score, llm_score, is_evidence, evidence_order, metadata) + VALUES (:question_analysis_id, :document_chunk_id, :chunk_order, + :similarity_score, :llm_score, :is_evidence, :evidence_order, :metadata) + ON CONFLICT (question_analysis_id, document_chunk_id) DO UPDATE + SET chunk_order = EXCLUDED.chunk_order, + similarity_score = EXCLUDED.similarity_score, + llm_score = EXCLUDED.llm_score, + is_evidence = EXCLUDED.is_evidence, + evidence_order = EXCLUDED.evidence_order, + metadata = EXCLUDED.metadata + """), + { + "question_analysis_id": analysis_id, + "document_chunk_id": chunk_id, + "chunk_order": chunk.get("chunk_order", 0), + "similarity_score": chunk.get("similarity_score", 0.0), + "llm_score": chunk.get("llm_score"), + "is_evidence": chunk.get("is_evidence", False), + "evidence_order": chunk.get("evidence_order"), + "metadata": json.dumps(chunk.get("metadata", {})), + }, + ) + else: + conn.execute( + text(""" + INSERT OR REPLACE INTO chunk_relevance + (question_analysis_id, document_chunk_id, chunk_order, + similarity_score, llm_score, is_evidence, evidence_order, metadata) + VALUES (:question_analysis_id, :document_chunk_id, :chunk_order, + :similarity_score, :llm_score, :is_evidence, :evidence_order, :metadata) + """), + { + "question_analysis_id": analysis_id, + "document_chunk_id": chunk_id, + "chunk_order": chunk.get("chunk_order", 0), + "similarity_score": chunk.get("similarity_score", 0.0), + "llm_score": chunk.get("llm_score"), + "is_evidence": chunk.get("is_evidence", False), + "evidence_order": chunk.get("evidence_order"), + "metadata": json.dumps(chunk.get("metadata", {})), + }, + ) + logger.info( + f"Saved chunk_relevance - similarity_score: {chunk.get('similarity_score')}, llm_score: {chunk.get('llm_score')}, is_evidence: {chunk.get('is_evidence')}" + ) # Save to analysis cache logger.info("Saving to analysis cache") @@ -449,7 +579,7 @@ def save_analysis(self, file_path: str, question_id: str, result: Dict, config: logger.info("Successfully saved complete analysis") except Exception as e: - logger.error(f"Error saving analysis: {str(e)}", exc_info=True) + logger.error(f"Error saving analysis: {e!s}", exc_info=True) raise def get_analysis(self, file_path: str, config: Dict, question_ids: Optional[List[str]] = None) -> Dict[str, Any]: @@ -515,6 +645,14 @@ def get_analysis(self, file_path: str, config: Dict, question_ids: Optional[List for row in rows: question_id, result_json = row result = json.loads(result_json) + + # Ensure SCORE is a number, not a string (fix for JSON deserialization) + if "SCORE" in result: + try: + result["SCORE"] = float(result["SCORE"]) if result["SCORE"] is not None else 0 + except (ValueError, TypeError): + result["SCORE"] = 0 + results[question_id] = { "result": result, "chunks": [], # Will be populated from chunk_relevance @@ -525,7 +663,7 @@ def get_analysis(self, file_path: str, config: Dict, question_ids: Optional[List # Build IN clause for question IDs qid_placeholders = ",".join(f":qid_{i}" for i in range(len(results))) chunk_query = f""" - SELECT + SELECT ac.question_id, dc.chunk_text, dc.metadata as chunk_metadata, @@ -537,7 +675,10 @@ def get_analysis(self, file_path: str, config: Dict, question_ids: Optional[List cr.metadata as relevance_metadata FROM analysis_cache ac JOIN questions q ON q.question_id = ac.question_id - JOIN question_analysis qa ON qa.question_id = q.id AND qa.file_path = ac.file_path + JOIN question_analysis qa ON qa.question_id = q.id + AND qa.file_path = ac.file_path + AND qa.model = ac.model + AND qa.top_k = ac.top_k JOIN chunk_relevance cr ON cr.question_analysis_id = qa.id JOIN document_chunks dc ON cr.document_chunk_id = dc.id WHERE ac.file_path = :file_path @@ -596,7 +737,7 @@ def get_analysis(self, file_path: str, config: Dict, question_ids: Optional[List return results except Exception as e: - logger.error(f"Error retrieving analysis: {str(e)}", exc_info=True) + logger.error(f"Error retrieving analysis: {e!s}", exc_info=True) raise def save_vectors(self, file_path: str, chunks: List[Dict[str, Any]]) -> None: @@ -639,7 +780,7 @@ def save_vectors(self, file_path: str, chunks: List[Dict[str, Any]]) -> None: } ) except Exception as e: - logger.warning(f"Error preparing chunk {i} for storage: {str(e)}") + logger.warning(f"Error preparing chunk {i} for storage: {e!s}") continue if chunk_data: @@ -692,7 +833,7 @@ def save_vectors(self, file_path: str, chunks: List[Dict[str, Any]]) -> None: logger.warning("No valid chunks to save") except Exception as e: - logger.error(f"Error saving vectors: {str(e)}", exc_info=True) + logger.error(f"Error saving vectors: {e!s}", exc_info=True) raise def get_vectors(self, file_path: str) -> List[Dict[str, Any]]: @@ -745,7 +886,7 @@ def get_vectors(self, file_path: str) -> List[Dict[str, Any]]: logger.info(f"Retrieved {len(chunks)} vectors for {file_path}") return chunks except Exception as e: - logger.error(f"Error retrieving vectors: {str(e)}", exc_info=True) + logger.error(f"Error retrieving vectors: {e!s}", exc_info=True) return [] def clear_cache(self, file_path: Optional[str] = None): @@ -767,7 +908,7 @@ def clear_cache(self, file_path: Optional[str] = None): conn.execute(text("DELETE FROM document_chunks")) logger.info("Cleared all cache") except Exception as e: - logger.error(f"Error clearing cache: {str(e)}", exc_info=True) + logger.error(f"Error clearing cache: {e!s}", exc_info=True) def list_analysis_keys(self) -> List[Dict[str, str]]: """List distinct (file_path, question_set) pairs that have stored analysis. Used for UI dropdowns driven by stored data.""" @@ -788,7 +929,7 @@ def list_analysis_keys(self) -> List[Dict[str, str]]: logger.error(f"Error listing analysis keys: {e}", exc_info=True) return [] - def check_cache_status(self, file_path: str = None): + def check_cache_status(self, file_path: str | None = None): """Debug method to check cache contents""" try: with self.db_manager.get_connection() as conn: @@ -823,7 +964,7 @@ def check_cache_status(self, file_path: str = None): return rows except Exception as e: - logger.error(f"Error checking cache status: {str(e)}", exc_info=True) + logger.error(f"Error checking cache status: {e!s}", exc_info=True) return [] def get_all_answers_by_question_set(self, question_set: str) -> Dict[str, Any]: @@ -962,7 +1103,7 @@ def save_document_chunks(self, file_path: str, chunks: List[Dict], chunk_size: i result_obj = conn.execute( text( """ - SELECT COUNT(*) FROM document_chunks + SELECT COUNT(*) FROM document_chunks WHERE file_path = :file_path AND chunk_size = :chunk_size AND chunk_overlap = :chunk_overlap """ ), @@ -976,10 +1117,10 @@ def save_document_chunks(self, file_path: str, chunks: List[Dict], chunk_size: i logger.info(f"Verification: Found {count} chunks in database for {file_path}") except Exception as e: - logger.error(f"Error saving document chunks: {str(e)}", exc_info=True) + logger.error(f"Error saving document chunks: {e!s}", exc_info=True) raise - def get_document_chunks(self, file_path: str, chunk_size: int = None, chunk_overlap: int = None) -> List[Dict]: + def get_document_chunks(self, file_path: str, chunk_size: int | None = None, chunk_overlap: int | None = None) -> List[Dict]: """ Get document chunks from cache with improved logging. """ @@ -1053,10 +1194,10 @@ def get_document_chunks(self, file_path: str, chunk_size: int = None, chunk_over return chunks except Exception as e: - logger.error(f"Error getting document chunks: {str(e)}", exc_info=True) + logger.error(f"Error getting document chunks: {e!s}", exc_info=True) return [] - def get_chunks_without_embeddings(self, file_path: str, chunk_size: int = None, chunk_overlap: int = None) -> List[Dict]: + def get_chunks_without_embeddings(self, file_path: str, chunk_size: int | None = None, chunk_overlap: int | None = None) -> List[Dict]: """Get chunks without embeddings (where embedding IS NULL)""" try: logger.info(f"Retrieving chunks without embeddings for {file_path}") @@ -1108,7 +1249,7 @@ def get_chunks_without_embeddings(self, file_path: str, chunk_size: int = None, return chunks except Exception as e: - logger.error(f"Error getting chunks without embeddings: {str(e)}", exc_info=True) + logger.error(f"Error getting chunks without embeddings: {e!s}", exc_info=True) return [] def has_chunk_scoring(self, file_path: str, config: Dict) -> bool: @@ -1136,5 +1277,5 @@ def has_chunk_scoring(self, file_path: str, config: Dict) -> bool: return count > 0 except Exception as e: - logger.error(f"Error checking chunk scoring: {str(e)}") + logger.error(f"Error checking chunk scoring: {e!s}") return False diff --git a/report_analyst/core/dataframe_manager.py b/report_analyst/core/dataframe_manager.py index c9fb524b..f8a9a428 100644 --- a/report_analyst/core/dataframe_manager.py +++ b/report_analyst/core/dataframe_manager.py @@ -1,6 +1,6 @@ -import json +# ruff: noqa: BLE001, E501, E722, S307 import logging -from typing import Any, Dict, List, Optional, Tuple +from typing import Any, Dict, List, Tuple import pandas as pd @@ -26,7 +26,7 @@ def format_list_field(field: Any) -> str: chunk = item.get("chunk", "Unknown") formatted_items.append(f"• {text} [Chunk {chunk}]") else: - formatted_items.append(f"• {str(item)}") + formatted_items.append(f"• {item!s}") return "\n".join(formatted_items) return str(field) @@ -40,7 +40,7 @@ def extract_evidence_text(evidence: Any) -> str: return str(evidence) -def create_analysis_dataframes(cached_results: Dict, file_key: str = None) -> Tuple[pd.DataFrame, pd.DataFrame]: +def create_analysis_dataframes(cached_results: Dict, file_key: str | None = None) -> Tuple[pd.DataFrame, pd.DataFrame]: """Create analysis and chunks dataframes from database results.""" try: analysis_rows = [] @@ -57,10 +57,16 @@ def create_analysis_dataframes(cached_results: Dict, file_key: str = None) -> Tu logger.info(f"Processing question {question_id} with keys: {list(result.keys())}") # Create analysis row + score = result.get("SCORE", 0) + try: + score = float(score) if score is not None else 0 + except (ValueError, TypeError): + score = 0 + analysis_row = { "Question ID": question_id, "Analysis": result.get("ANSWER", ""), - "Score": float(result.get("SCORE", 0)), + "Score": score, "Key Evidence": format_list_field(result.get("EVIDENCE", [])), "Gaps": format_list_field(result.get("GAPS", [])), "Sources": format_list_field(result.get("SOURCES", [])), @@ -68,8 +74,8 @@ def create_analysis_dataframes(cached_results: Dict, file_key: str = None) -> Tu analysis_rows.append(analysis_row) logger.info(f"Added analysis row for question {question_id}") - # Process chunks - use exactly what's in the database - chunks = data.get("chunks", []) + # Process chunks - check both result and data for chunks + chunks = result.get("chunks", data.get("chunks", [])) logger.info(f"Processing {len(chunks)} chunks for question {question_id}") for chunk in chunks: @@ -90,7 +96,7 @@ def create_analysis_dataframes(cached_results: Dict, file_key: str = None) -> Tu ) except Exception as e: - logger.error(f"Error processing result for question {question_id}: {str(e)}") + logger.error(f"Error processing result for question {question_id}: {e!s}") logger.error(f"Result data: {data}") continue @@ -111,7 +117,7 @@ def create_analysis_dataframes(cached_results: Dict, file_key: str = None) -> Tu return analysis_df, chunks_df except Exception as e: - logger.error(f"Error creating dataframes: {str(e)}") + logger.error(f"Error creating dataframes: {e!s}") return pd.DataFrame(), pd.DataFrame() diff --git a/report_analyst/streamlit_app.py b/report_analyst/streamlit_app.py index 69f5508a..06c70a29 100644 --- a/report_analyst/streamlit_app.py +++ b/report_analyst/streamlit_app.py @@ -98,6 +98,7 @@ def is_api_key_missing_message(message: str) -> bool: ) from report_analyst.core.prompt_manager import PromptManager from report_analyst.core.question_loader import get_question_loader +from report_analyst.ui.view_report_page import render_view_report_page # Load environment variables load_dotenv() @@ -808,13 +809,29 @@ def get_uploaded_files_history(backend_config=None) -> List[Dict]: return result -def display_analysis_results(analysis_df: pd.DataFrame, chunks_df: pd.DataFrame, file_key: str | None = None) -> None: +def display_analysis_results( + analysis_df: pd.DataFrame, + chunks_df: pd.DataFrame, + file_key: str | None = None, + file_path: str | None = None, + question_set: str | None = None, +) -> None: """Display analysis results in a consistent format for both individual and consolidated views""" try: if analysis_df.empty: st.warning("No analysis results to display") return + + # Try to import and use PDF viewer component if available + pdf_viewer_available = False + try: + from report_analyst_enterprise.components.streamlit_component.backend import pdf_viewer + + pdf_viewer_available = True + except ImportError: + pass + # Analysis Results Table st.subheader("Analysis Results") st.dataframe( @@ -849,6 +866,82 @@ def display_analysis_results(analysis_df: pd.DataFrame, chunks_df: pd.DataFrame, }, ) + if pdf_viewer_available and file_path and not chunks_df.empty: + try: + if not question_set: + question_set = st.session_state.get("question_set", "tcfd") + + question_set_obj = question_loader.get_question_set(question_set) + questions_data = {} + if question_set_obj: + for q_id, q_data in question_set_obj.questions.items(): + questions_data[q_id] = q_data.get("text", q_id) + + chunks_by_question: dict = {} + try: + from report_analyst.core.analyzer import DocumentAnalyzer + + doc_analyzer = DocumentAnalyzer() + config = { + "chunk_size": st.session_state.get("chunk_size", 500), + "chunk_overlap": st.session_state.get("chunk_overlap", 0), + "top_k": st.session_state.get("top_k", 10), + "model": st.session_state.get("llm_model", "gpt-4o-mini"), + "question_set": question_set, + } + cached_results = doc_analyzer.cache_manager.get_analysis( + file_path=file_path, + config=config, + ) + if cached_results: + for q_id, data in cached_results.items(): + if q_id not in chunks_by_question: + chunks_by_question[q_id] = [] + chunks = data.get("chunks", []) + for chunk in chunks: + metadata = chunk.get("metadata") or {} + if "page_number" not in metadata and "source" in metadata: + try: + metadata["page_number"] = int(metadata["source"]) + except (ValueError, TypeError): + metadata["page_number"] = 1 + elif "page_number" in metadata: + try: + metadata["page_number"] = int(metadata["page_number"]) + except (ValueError, TypeError): + metadata["page_number"] = 1 + else: + metadata["page_number"] = 1 + chunk["metadata"] = metadata + chunks_by_question[q_id].extend(chunks) + except Exception as cache_error: + logger.debug(f"Could not get chunks from cache: {cache_error}") + for _, row in chunks_df.iterrows(): + q_id = row.get("Question ID", "") + if q_id not in chunks_by_question: + chunks_by_question[q_id] = [] + chunks_by_question[q_id].append( + { + "text": row.get("Chunk Text", ""), + "metadata": {}, + "is_evidence": row.get("Is Evidence", False), + "similarity_score": row.get("Vector Similarity", 0.0), + "llm_score": row.get("LLM Score"), + "chunk_order": row.get("Position", 0), + } + ) + + with st.expander("PDF Viewer with Chunks", expanded=False): + pdf_viewer( + pdf_path=file_path, + chunks_data=chunks_by_question, + questions_data=questions_data, + height=800, + key=f"pdf_viewer_{file_key}" if file_key else "pdf_viewer", + ) + except Exception as e: + logger.warning(f"Could not display PDF viewer: {e}", exc_info=True) + # Document Chunks Table if not chunks_df.empty: st.subheader("Document Chunks") @@ -1249,7 +1342,13 @@ def display_consolidated_results(analyzer, question_set, file_path=None, selecte # Display results using the existing display function file_key = f"{Path(file_path).stem}_cs{selected_config['config']['chunk_size']}" - display_analysis_results(analysis_df, chunks_df, file_key) + display_analysis_results( + analysis_df, + chunks_df, + file_key, + file_path=file_path, + question_set=question_set, + ) else: st.warning("No results found in stored for this configuration") else: @@ -2856,10 +2955,11 @@ def main(): options=[ "Upload Report", "Report Analyst", + "View Report", "All Results", "Settings", ], - icons=["house", "file-text", "bar-chart", "gear"], + icons=["house", "file-text", "file-pdf", "bar-chart", "gear"], menu_icon=None, default_index=0, orientation="vertical", @@ -2889,7 +2989,7 @@ def main(): ) except ImportError: # Fallback to regular radio if package not installed - nav_options = ["Upload Report", "Report Analyst", "All Results", "Settings"] + nav_options = ["Upload Report", "Report Analyst", "View Report", "All Results", "Settings"] nav_page = st.sidebar.radio("", nav_options, key="nav_page", label_visibility="collapsed") # Show page-specific content based on navigation @@ -3978,7 +4078,13 @@ def main(): if all_results: analysis_df, chunks_df = create_analysis_dataframes(all_results) file_key = Path(file_path).stem - display_analysis_results(analysis_df, chunks_df, file_key) + display_analysis_results( + analysis_df, + chunks_df, + file_key, + file_path=str(file_path), + question_set=config.get("question_set", st.session_state.get("question_set", "tcfd")), + ) progress_text.success(f"✓ Analysis complete for {len(selected_questions)} questions") else: progress_text.error("No results found after analysis") @@ -4285,6 +4391,9 @@ def main(): st.session_state.file_processed = True st.rerun() + elif nav_page == "View Report": + render_view_report_page(analyzer, question_sets, get_uploaded_files_history) + # All Results page elif nav_page == "All Results": st.header("View All Results") diff --git a/report_analyst/ui/__init__.py b/report_analyst/ui/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/report_analyst/ui/view_report_page.py b/report_analyst/ui/view_report_page.py new file mode 100644 index 00000000..99a385ff --- /dev/null +++ b/report_analyst/ui/view_report_page.py @@ -0,0 +1,326 @@ +# ruff: noqa: E501 +"""View Report page: PDF viewer with chunk overlays.""" + +from __future__ import annotations + +import logging +from pathlib import Path + +import pandas as pd +import streamlit as st + +logger = logging.getLogger(__name__) + + +def render_view_report_page(analyzer, question_sets: dict, get_uploaded_files_history) -> None: + """Render the View Report navigation page.""" + st.header("View Report") + st.write("View PDF with chunks and analysis results by question") + + # Get file list for dropdown (including backend resources if enabled) + backend_config = st.session_state.get("backend_config") + previous_files = get_uploaded_files_history(backend_config=backend_config) + + if not previous_files: + st.info("No reports available. Please upload a report first.") + else: + # File selector + selected_file_dropdown = st.selectbox( + "Select Report", + options=previous_files, + format_func=lambda x: x["name"], + key="view_report_file", + ) + + if selected_file_dropdown: + selected_uri = selected_file_dropdown.get("uri", selected_file_dropdown.get("path", "")) + is_backend = selected_uri.startswith("urn:report-analyst:backend:") + + # Determine file path: use URI for backend, absolute path for local files + if is_backend: + file_path = selected_uri # Use URN for backend resources + else: + file_path = selected_file_dropdown.get("path", "") + # Handle file:// URI format + if file_path.startswith("file://"): + file_path = file_path.replace("file://", "") + # Resolve to absolute path (same as Report Analyst) + file_path = str(Path(file_path).resolve()) if file_path else file_path + + # Question set selection + selected_set = st.selectbox( + "Select Question Set", + options=list(question_sets.keys()), + format_func=lambda x: question_sets[x]["name"], + key="view_report_set", + ) + + if selected_set and file_path: + # Load questions (always needed for PDF viewer) + # Use global question_loader (imported at module level) + from report_analyst.core.question_loader import get_question_loader + q_loader = get_question_loader() + question_set_obj = q_loader.get_question_set(selected_set) + questions_data = {} + if question_set_obj: + for q_id, q_data in question_set_obj.questions.items(): + questions_data[q_id] = q_data.get("text", q_id) + + # Try to get cached results (optional - PDF will show even without them) + cached_results = None + selected_config = None + chunks_by_question = {} + analysis_by_question = {} + + try: + # Map question set to database identifier + question_set_mapping = { + "tcfd": "tcfd", + "s4m": "s4m", + "lucia": "lucia", + "everest": "ev", + } + db_question_set = question_set_mapping.get(selected_set, selected_set) + + # Get all cache configs + cache_configs = analyzer.analyzer.cache_manager.check_cache_status() + logger.info(f"Found {len(cache_configs)} total cache configs") + logger.info(f"Looking for file_path: {file_path}, question_set: {db_question_set}") + + # Filter configs for this file and question set + matching_configs = [] + for config in cache_configs: + if len(config) == 6: + cfg_file_path, chunk_size, chunk_overlap, top_k, model, qs = config + # Match file path and question set + # Compare both as strings to handle path variations + if str(cfg_file_path) == str(file_path) and qs == db_question_set: + matching_configs.append({ + "chunk_size": chunk_size, + "chunk_overlap": chunk_overlap, + "top_k": top_k, + "model": model, + "question_set": selected_set, # Use original question set ID - get_analysis will map it internally + }) + + logger.info(f"Found {len(matching_configs)} matching configs for file and question set") + + if matching_configs: + # Let user select config if multiple, otherwise use first + if len(matching_configs) > 1: + config_options = [ + f"Chunk: {cfg['chunk_size']}, Overlap: {cfg['chunk_overlap']}, Top-K: {cfg['top_k']}, Model: {cfg['model']}" + for cfg in matching_configs + ] + selected_config_idx = st.selectbox( + "Select Configuration", + options=range(len(matching_configs)), + format_func=lambda i: config_options[i], + key="view_report_config", + ) + selected_config = matching_configs[selected_config_idx] + else: + selected_config = matching_configs[0] + + # Get cached results with the selected config + # Note: get_analysis will map question_set internally, so we pass the ID + logger.info(f"Retrieving cached results with config: {selected_config}") + # Get all question IDs for this question set + all_question_ids = list(questions_data.keys()) + logger.info(f"Retrieving chunks for {len(all_question_ids)} questions: {all_question_ids}") + cached_results = analyzer.analyzer.cache_manager.get_analysis( + file_path=file_path, + config=selected_config, + question_ids=all_question_ids + ) + logger.info(f"Retrieved cached results for {len(cached_results) if cached_results else 0} questions") + + if cached_results: + # Prepare chunks by question and normalize page numbers + for q_id, data in cached_results.items(): + chunks = data.get("chunks", []) + # Normalize page_number in metadata (convert from 'source' if needed) + for chunk in chunks: + if chunk.get("metadata"): + metadata = chunk["metadata"] + # PyMuPDFReader uses 'source' as page number string, normalize to 'page_number' as integer + if "page_number" not in metadata and "source" in metadata: + try: + metadata["page_number"] = int(metadata["source"]) + except (ValueError, TypeError): + metadata["page_number"] = 1 + elif "page_number" in metadata: + # Ensure it's an integer + try: + metadata["page_number"] = int(metadata["page_number"]) + except (ValueError, TypeError): + metadata["page_number"] = 1 + else: + # Default to page 1 if no page info + metadata["page_number"] = 1 + chunks_by_question[q_id] = chunks + logger.info(f"Question {q_id}: Found {len(chunks)} chunks") + if chunks: + logger.debug(f"First chunk sample for {q_id}: {chunks[0] if chunks else 'None'}") + result = data.get("result", {}) + # Ensure score is a number, not a string + score = result.get("SCORE", 0) + try: + score = float(score) if score is not None else 0 + except (ValueError, TypeError): + score = 0 + + analysis_by_question[q_id] = { + "answer": result.get("ANSWER", ""), + "score": score, + "evidence": result.get("EVIDENCE", []), + "gaps": result.get("GAPS", []), + } + + # Log total chunks for debugging + total_chunks = sum(len(chunks) for chunks in chunks_by_question.values()) + logger.info(f"Total chunks prepared for PDF viewer: {total_chunks}") + else: + st.info("No cached analysis results found. PDF will display without chunks.") + else: + st.info(f"No cached results found for this file and question set '{selected_set}'. PDF will display without chunks. Run analysis in 'Report Analyst' tab to see chunks.") + + except Exception as e: + logger.error(f"Error getting cached results: {e}", exc_info=True) + st.warning(f"Could not load cached results: {e!s}. PDF will display without chunks.") + + # Try to import PDF viewer + pdf_viewer_available = False + try: + from report_analyst_enterprise.components.streamlit_component.backend import pdf_viewer + pdf_viewer_available = True + except ImportError: + pass + + # Create two-column layout: questions on left, PDF viewer on right + if pdf_viewer_available: + left_col, right_col = st.columns([1, 1]) + else: + left_col = st.container() + right_col = None + + with left_col: + st.subheader("Questions & Chunks") + + if cached_results and chunks_by_question: + # Sort questions by question_id for consistent display + sorted_question_ids = sorted(questions_data.keys()) + + for q_id in sorted_question_ids: + question_text = questions_data[q_id] + chunks = chunks_by_question.get(q_id, []) + analysis = analysis_by_question.get(q_id, {}) + + with st.expander(f"**{q_id}**: {question_text[:80]}{'...' if len(question_text) > 80 else ''}", expanded=False): + if chunks: + # Sort chunks: evidence first, then by score (higher is better) + sorted_chunks = sorted( + chunks, + key=lambda c: ( + not c.get("is_evidence", False), # Evidence first (False < True) + -(c.get("llm_score") if c.get("llm_score") is not None else c.get("similarity_score", 0)) # Higher scores first + ) + ) + + # Create dataframe for chunks with chunk IDs for navigation + chunk_rows = [] + chunk_id_map = {} # Map row index to chunk_id + for idx, chunk in enumerate(sorted_chunks): + chunk_order = chunk.get('chunk_order', 0) + # Generate chunk ID: "question_id_chunk_order" + chunk_id = f"{q_id}_{chunk_order}" + chunk_id_map[idx] = chunk_id + chunk_rows.append({ + "Chunk": f"Chunk {chunk_order + 1}", + "Text": chunk.get("text", "")[:200] + ("..." if len(chunk.get("text", "")) > 200 else ""), + "Page": chunk.get("metadata", {}).get("page_number", "N/A"), + "Evidence": "✓" if chunk.get("is_evidence", False) else "", + "Similarity": f"{chunk.get('similarity_score', 0):.3f}", + "LLM Score": f"{chunk.get('llm_score', 0):.3f}" if chunk.get("llm_score") else "N/A", + }) + + chunks_df = pd.DataFrame(chunk_rows) + + # Use session state to track selected chunk for this question + chunk_selection_key = f"selected_chunk_{q_id}_{selected_set}" + + # Add a "Select" column with buttons for each chunk + select_buttons = [] + for idx in range(len(chunks_df)): + chunk_id = chunk_id_map[idx] + select_buttons.append(chunk_id) + + # Display chunks with clickable select buttons + for idx, row in chunks_df.iterrows(): + chunk_id = chunk_id_map[idx] + col1, col2 = st.columns([0.12, 0.88]) + with col1: + if st.button("📍", key=f"select_chunk_{chunk_id}", help="Click to highlight this chunk in PDF", use_container_width=True): + st.session_state[chunk_selection_key] = chunk_id + st.rerun() + with col2: + st.markdown(f"**{row['Chunk']}** | Page {row['Page']} | {row['Evidence']} | Similarity: {row['Similarity']}") + st.caption(row['Text']) + + # Also show as compact dataframe for overview + st.dataframe( + chunks_df, + use_container_width=True, + hide_index=True, + column_config={ + "Chunk": st.column_config.TextColumn("Chunk", width="small"), + "Text": st.column_config.TextColumn("Text", width="large"), + "Page": st.column_config.TextColumn("Page", width="small"), + "Evidence": st.column_config.TextColumn("Evidence", width="small"), + "Similarity": st.column_config.TextColumn("Similarity", width="small"), + "LLM Score": st.column_config.TextColumn("LLM Score", width="small"), + } + ) + + # Show analysis result below chunks + st.markdown("---") + st.markdown("**Analysis Result:**") + if analysis.get("answer"): + st.write(analysis["answer"]) + if analysis.get("score") is not None: + # Handle score as either number or string + try: + score_value = float(analysis["score"]) + st.metric("Score", f"{score_value:.1f}") + except (ValueError, TypeError): + # If score is not a number, display as-is + st.metric("Score", str(analysis["score"])) + else: + st.info("No chunks available for this question.") + else: + st.info("No cached analysis results available. Run analysis in 'Report Analyst' tab to see chunks and analysis.") + + # PDF viewer on the right - always show if file is selected + if pdf_viewer_available and right_col: + with right_col: + st.subheader("PDF Viewer") + + # Get selected chunk ID from session state (check all questions) + selected_chunk_id = None + for q_id_check in questions_data.keys(): + chunk_key = f"selected_chunk_{q_id_check}_{selected_set}" + if chunk_key in st.session_state: + selected_chunk_id = st.session_state[chunk_key] + break # Use first found, or could use most recent + + pdf_viewer( + pdf_path=file_path, + chunks_data=chunks_by_question, + questions_data=questions_data, + highlight_chunk_id=selected_chunk_id, + height=800, + key=f"view_report_pdf_viewer_{selected_set}" + ) + elif not pdf_viewer_available: + st.info("PDF viewer component not available. Install enterprise components to enable PDF viewing.") + diff --git a/report_analyst_enterprise/components/__init__.py b/report_analyst_enterprise/components/__init__.py new file mode 100644 index 00000000..4f182afc --- /dev/null +++ b/report_analyst_enterprise/components/__init__.py @@ -0,0 +1 @@ +"""Enterprise UI components for Report Analyst.""" diff --git a/report_analyst_enterprise/components/streamlit_component/PDF_VIEWER_README.md b/report_analyst_enterprise/components/streamlit_component/PDF_VIEWER_README.md new file mode 100644 index 00000000..9cbbbebf --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/PDF_VIEWER_README.md @@ -0,0 +1,180 @@ +# PDF Viewer Component with Chunks + +A Streamlit custom component that displays PDFs with chunk annotations, allowing users to view chunks per question and filter by evidence. + +## Features + +- **PDF Display**: Renders PDF documents using PDF.js +- **Chunk Annotations**: Shows chunks associated with each question +- **Evidence Filtering**: Filter to show only evidence chunks +- **Question Navigation**: Select a question to see its associated chunks +- **Page Navigation**: Navigate to specific pages and see chunk highlights +- **Works Standalone**: Can be used outside Streamlit as a web component + +## Architecture + +The component follows a three-layer architecture: + +1. **Web Component** (`web/src/pdf-viewer.js`): Framework-agnostic web component using PDF.js directly (not using streamlit-pdf-viewer repo - we built our own) +2. **React Wrapper** (`frontend/src/pdf-viewer.tsx`): React component that wraps the web component for Streamlit +3. **Streamlit Backend** (`backend/pdf_viewer.py`): Python interface for Streamlit + +**Note**: This is a custom implementation built from scratch using PDF.js. We do not use or depend on the streamlit-pdf-viewer repository. We use PDF.js (the same underlying library) but have built our own component specifically for displaying chunks per question with evidence filtering. + +## Development Setup + +### Prerequisites + +- Node.js and npm +- Python with Streamlit + +### Building the Component + +1. **Build the web component** (framework-agnostic): +```bash +cd report_analyst_enterprise/components/web +npm install +npm run build +``` + +This creates `dist/pdf-viewer.es.js` which is used by both standalone and Streamlit versions. + +2. **Build the Streamlit component**: +```bash +cd report_analyst_enterprise/components/streamlit_component/frontend +npm install +npm run build:pdf-viewer +``` + +### Development Mode + +For hot-reload during development: + +1. **Start the PDF viewer dev server** (in one terminal): +```bash +cd report_analyst_enterprise/components/streamlit_component/frontend +npm run dev:pdf-viewer +``` + +This starts a dev server on port 3002. + +2. **Run your Streamlit app** (in another terminal): +```bash +streamlit run report_analyst/streamlit_app.py +``` + +The component will automatically use the dev server if it's running. + +## Usage in Streamlit + +```python +from report_analyst_enterprise.components.streamlit_component.backend import pdf_viewer + +# Prepare data +chunks_by_question = { + "q1": [ + { + "text": "Chunk text...", + "metadata": {"page_number": 1}, + "is_evidence": True, + "similarity_score": 0.85, + "llm_score": 0.92, + "chunk_order": 0 + } + ] +} + +questions_data = { + "q1": "How does the organization identify climate risks?" +} + +# Display the component +pdf_viewer( + pdf_path="/path/to/document.pdf", + chunks_data=chunks_by_question, + questions_data=questions_data, + selected_question_id="q1", # Optional + show_evidence_only=False, # Optional + height=800, + key="my_pdf_viewer" +) +``` + +## Standalone Usage + +The web component can be used outside Streamlit. See `web/examples/pdf-viewer-standalone.html` for an example. + +```html + + + + + + + + + + + +``` + +## Data Format + +### Chunks + +Each chunk should have: +- `text`: The chunk text content +- `metadata`: Object containing metadata (should include `page_number`) +- `is_evidence`: Boolean indicating if this chunk is evidence +- `similarity_score`: Float similarity score +- `llm_score`: Optional float LLM relevance score +- `chunk_order`: Integer position of chunk + +### Questions + +Questions should be provided as a dictionary mapping question_id to question text: +```python +{ + "q1": "Question text here", + "q2": "Another question..." +} +``` + +## Integration with Streamlit App + +The component is integrated into `report_analyst/streamlit_app.py` in the `display_analysis_results()` function. It automatically appears when: +- The PDF viewer component is available (enterprise feature) +- A file path is provided +- Chunks data is available + +The component appears in an expander section titled "📄 PDF Viewer with Chunks". + +## Troubleshooting + +### Component not loading + +1. Check that the dev server is running (for development) or the component is built (for production) +2. Check browser console for errors +3. Verify PDF.js is loading correctly + +### PDF not displaying + +1. Check that the PDF path is correct and accessible +2. For local files, ensure the path is absolute or relative to the Streamlit app +3. Check browser console for PDF.js errors + +### Chunks not showing + +1. Verify chunks data format matches the expected structure +2. Check that `page_number` is included in chunk metadata +3. Verify questions data is provided correctly + + diff --git a/report_analyst_enterprise/components/streamlit_component/__init__.py b/report_analyst_enterprise/components/streamlit_component/__init__.py new file mode 100644 index 00000000..ed5f1a89 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/__init__.py @@ -0,0 +1 @@ +"""Streamlit custom components (enterprise).""" diff --git a/report_analyst_enterprise/components/streamlit_component/backend/__init__.py b/report_analyst_enterprise/components/streamlit_component/backend/__init__.py new file mode 100644 index 00000000..28c0e36d --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/backend/__init__.py @@ -0,0 +1,5 @@ +"""Streamlit component backends.""" + +from report_analyst_enterprise.components.streamlit_component.backend.pdf_viewer import pdf_viewer + +__all__ = ["pdf_viewer"] diff --git a/report_analyst_enterprise/components/streamlit_component/backend/pdf_viewer.py b/report_analyst_enterprise/components/streamlit_component/backend/pdf_viewer.py new file mode 100644 index 00000000..1db3dc9c --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/backend/pdf_viewer.py @@ -0,0 +1,193 @@ +# ruff: noqa: BLE001, E501, E722, S110 +""" +Streamlit custom component backend for PDF viewer with chunks. + +This creates a proper Streamlit custom component using the framework-agnostic +web component, which internally uses PDF.js. +""" + +import base64 +import json +import logging +import socket +from pathlib import Path +from typing import Any, Dict, List, Optional + +import streamlit.components.v1 as components + +logger = logging.getLogger(__name__) + +# Get the path to the frontend +_COMPONENT_DIR = Path(__file__).parent.parent / "frontend" +_RELEASE_DIR = _COMPONENT_DIR / "build" + + +def pdf_viewer( + pdf_path: str, + chunks_data: Dict[str, List[Dict[str, Any]]], + questions_data: Dict[str, str], + selected_question_id: Optional[str] = None, + show_evidence_only: bool = False, + highlight_chunk_id: Optional[str] = None, + key: Optional[str] = None, + height: int = 800, +) -> Optional[Dict[str, Any]]: + """ + Render a PDF viewer with chunk annotations in Streamlit using a custom component. + + Args: + pdf_path: Path to PDF file (local file path or URI) + chunks_data: Dictionary mapping question_id to list of chunk dictionaries. + Each chunk should have: + - text: str + - metadata: dict (with page_number) + - is_evidence: bool + - similarity_score: float + - llm_score: float (optional) + - chunk_order: int + questions_data: Dictionary mapping question_id to question text + selected_question_id: Optional question ID to highlight initially + show_evidence_only: Whether to filter to show only evidence chunks + highlight_chunk_id: Optional chunk ID to highlight (format: "question_id_chunk_order") + key: Optional key for Streamlit component (for state management) + height: Height of the component in pixels + + Returns: + Dictionary with event data if chunk was selected, None otherwise + """ + # Check for dev server availability (prefer dev server for hot reload) + dev_server_port = None + dev_server_available = False + + # Check common dev server ports (use 3002 for PDF viewer, different from JSON form) + for port in [3002, 3003, 3004]: + try: + sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + sock.settimeout(1) + result = sock.connect_ex(('localhost', port)) + sock.close() + if result == 0: + dev_server_port = port + dev_server_available = True + break + except: + pass + + if dev_server_available: + # Use dev server (hot reload) - need to specify the HTML file + logger.info(f"Using PDF viewer component from dev server (http://localhost:{dev_server_port})") + component = components.declare_component( + "pdf_viewer", + url=f"http://localhost:{dev_server_port}", + ) + elif _RELEASE_DIR.exists() and any(_RELEASE_DIR.iterdir()): + # Use built component - check for PDF viewer subdirectory + pdf_viewer_dir = _RELEASE_DIR / "pdf-viewer" + if pdf_viewer_dir.exists() and (pdf_viewer_dir / "index.html").exists(): + # Use PDF viewer specific subdirectory + logger.info(f"Using PDF viewer component from build: {pdf_viewer_dir}") + component = components.declare_component( + "pdf_viewer", + path=str(pdf_viewer_dir), + ) + else: + # Fallback: check for index-pdf-viewer.html and create subdirectory structure + pdf_viewer_html = _RELEASE_DIR / "index-pdf-viewer.html" + if pdf_viewer_html.exists(): + logger.warning("PDF viewer build found but not in expected structure. Please rebuild with: npm run build:pdf-viewer") + # Still try to use the build directory + logger.info(f"Using PDF viewer component from build (fallback): {_RELEASE_DIR}") + component = components.declare_component( + "pdf_viewer", + path=str(_RELEASE_DIR), + ) + else: + # No build and no dev server - show helpful error + logger.warning( + f"PDF viewer component not built and dev server not running.\n" + f"To build the component, run:\n" + f" cd {_COMPONENT_DIR}\n" + f" npm install\n" + f" npm run build:pdf-viewer\n" + f"Or for development, start the dev server:\n" + f" cd {_COMPONENT_DIR}\n" + f" npm run dev:pdf-viewer (in a separate terminal)" + ) + # Still try to declare component - Streamlit will show its own error + component = components.declare_component( + "pdf_viewer", + url="http://localhost:3002", + ) + + # Prepare PDF data + pdf_url = None + pdf_data = None + + # Check if it's a local file or URI + if pdf_path.startswith("file://") or pdf_path.startswith("http://") or pdf_path.startswith("https://") or pdf_path.startswith("urn:"): + # It's a URI, pass it directly + pdf_url = pdf_path + else: + # It's a local file path, convert to base64 + try: + pdf_file = Path(pdf_path) + if pdf_file.exists(): + with open(pdf_file, 'rb') as f: + pdf_bytes = f.read() + pdf_base64 = base64.b64encode(pdf_bytes).decode('utf-8') + pdf_data = f"data:application/pdf;base64,{pdf_base64}" + else: + logger.warning(f"PDF file not found: {pdf_path}") + pdf_url = pdf_path # Fallback: pass as URL + except Exception as e: + logger.error(f"Error reading PDF file: {e}") + pdf_url = pdf_path # Fallback: pass as URL + + # Prepare questions in the format expected by the component + questions_list = [] + for question_id, question_text in questions_data.items(): + # Get chunks for this question + question_chunks = chunks_data.get(question_id, []) + questions_list.append({ + "question_id": question_id, + "text": question_text, + "chunks": question_chunks + }) + + # Flatten all chunks for the component (it will filter by question) + all_chunks = [] + for question_id, chunks in chunks_data.items(): + for chunk in chunks: + # Add question_id to chunk for filtering + chunk_with_qid = chunk.copy() + chunk_with_qid["question_id"] = question_id + all_chunks.append(chunk_with_qid) + + # Log chunk data for debugging + logger.info(f"PDF viewer: Preparing {len(all_chunks)} total chunks for {len(questions_list)} questions") + if all_chunks: + logger.debug(f"Sample chunk structure: {all_chunks[0]}") + else: + logger.warning(f"No chunks found in chunks_data. Keys: {list(chunks_data.keys())}, Total chunks per question: {[len(chunks) for chunks in chunks_data.values()]}") + + # Render component and get result + result = component( + pdfUrl=pdf_url, + pdfData=pdf_data, + chunks=json.dumps(all_chunks), + questions=json.dumps(questions_list), + selectedQuestionId=selected_question_id, + showEvidenceOnly=show_evidence_only, + key=key, + height=height, + ) + + # Parse result if it's a string + if isinstance(result, str): + try: + result = json.loads(result) + except (json.JSONDecodeError, TypeError): + pass + + return result + diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/build/index-pdf-viewer.html b/report_analyst_enterprise/components/streamlit_component/frontend/build/index-pdf-viewer.html new file mode 100644 index 00000000..c1428292 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/build/index-pdf-viewer.html @@ -0,0 +1,13 @@ + + + + + + PDF Viewer Component + + + +
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J.isDictionary(this.type)?this.data[0].dictionary.isMemoized:!1}memoize(){if(J.isDictionary(this.type)){const t=new Rl(this.data[0].dictionary),n=this.data.map(o=>{const u=o.clone();return u.dictionary=t,u});return new _t(n)}return new Rl(this)}unmemoize(){if(J.isDictionary(this.type)&&this.isMemoized){const t=this.data[0].dictionary.unmemoize(),n=this.data.map(o=>{const u=o.clone();return u.dictionary=t,u});return new _t(n)}return this}}Qy=Symbol.toStringTag;_t[Qy]=(i=>{i.type=J.prototype,i.data=[],i.length=0,i.stride=1,i.numChildren=0,i._nullCount=-1,i._byteLength=-1,i._offsets=new Uint32Array([0]),i[Symbol.isConcatSpreadable]=!0;const t=Object.keys(_).map(n=>_[n]).filter(n=>typeof n=="number"&&n!==_.NONE);for(const n of t){const o=ke.getVisitFnByTypeId(n),u=Ze.getVisitFnByTypeId(n),d=Ll.getVisitFnByTypeId(n),f=An.getVisitFnByTypeId(n);Ky[n]={get:o,set:u,indexOf:d,byteLength:f},Jy[n]=Object.create(i,{isValid:{value:Ui(Pc)},get:{value:Ui(ke.getVisitFnByTypeId(n))},set:{value:Vy(Ze.getVisitFnByTypeId(n))},indexOf:{value:$y(Ll.getVisitFnByTypeId(n))},getByteLength:{value:Ui(An.getVisitFnByTypeId(n))}})}return"Vector"})(_t.prototype);class Rl extends _t{constructor(t){super(t.data);const n=this.get,o=this.set,u=this.slice,d=new Array(this.length);Object.defineProperty(this,"get",{value(f){const p=d[f];if(p!==void 0)return p;const y=n.call(this,f);return d[f]=y,y}}),Object.defineProperty(this,"set",{value(f,p){o.call(this,f,p),d[f]=p}}),Object.defineProperty(this,"slice",{value:(f,p)=>new Rl(u.call(this,f,p))}),Object.defineProperty(this,"isMemoized",{value:!0}),Object.defineProperty(this,"unmemoize",{value:()=>new _t(this.data)}),Object.defineProperty(this,"memoize",{value:()=>this})}}class pc{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}offset(){return this.bb.readInt64(this.bb_pos)}metaDataLength(){return this.bb.readInt32(this.bb_pos+8)}bodyLength(){return this.bb.readInt64(this.bb_pos+16)}static sizeOf(){return 24}static createBlock(t,n,o,u){return t.prep(8,24),t.writeInt64(u),t.pad(4),t.writeInt32(o),t.writeInt64(n),t.offset()}}const sc=2,Bn=4,Qn=4,Et=4,Sr=new Int32Array(2),pp=new Float32Array(Sr.buffer),yp=new Float64Array(Sr.buffer),pl=new Uint16Array(new Uint8Array([1,0]).buffer)[0]===1;let Jn=class yc{constructor(t,n){this.low=t|0,this.high=n|0}static create(t,n){return t==0&&n==0?yc.ZERO:new yc(t,n)}toFloat64(){return(this.low>>>0)+this.high*4294967296}equals(t){return this.low==t.low&&this.high==t.high}};Jn.ZERO=new Jn(0,0);var mc;(function(i){i[i.UTF8_BYTES=1]="UTF8_BYTES",i[i.UTF16_STRING=2]="UTF16_STRING"})(mc||(mc={}));let ji=class Gy{constructor(t){this.bytes_=t,this.position_=0}static allocate(t){return new Gy(new Uint8Array(t))}clear(){this.position_=0}bytes(){return this.bytes_}position(){return this.position_}setPosition(t){this.position_=t}capacity(){return this.bytes_.length}readInt8(t){return this.readUint8(t)<<24>>24}readUint8(t){return this.bytes_[t]}readInt16(t){return this.readUint16(t)<<16>>16}readUint16(t){return this.bytes_[t]|this.bytes_[t+1]<<8}readInt32(t){return this.bytes_[t]|this.bytes_[t+1]<<8|this.bytes_[t+2]<<16|this.bytes_[t+3]<<24}readUint32(t){return this.readInt32(t)>>>0}readInt64(t){return new Jn(this.readInt32(t),this.readInt32(t+4))}readUint64(t){return new Jn(this.readUint32(t),this.readUint32(t+4))}readFloat32(t){return Sr[0]=this.readInt32(t),pp[0]}readFloat64(t){return Sr[pl?0:1]=this.readInt32(t),Sr[pl?1:0]=this.readInt32(t+4),yp[0]}writeInt8(t,n){this.bytes_[t]=n}writeUint8(t,n){this.bytes_[t]=n}writeInt16(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8}writeUint16(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8}writeInt32(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8,this.bytes_[t+2]=n>>16,this.bytes_[t+3]=n>>24}writeUint32(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8,this.bytes_[t+2]=n>>16,this.bytes_[t+3]=n>>24}writeInt64(t,n){this.writeInt32(t,n.low),this.writeInt32(t+4,n.high)}writeUint64(t,n){this.writeUint32(t,n.low),this.writeUint32(t+4,n.high)}writeFloat32(t,n){pp[0]=n,this.writeInt32(t,Sr[0])}writeFloat64(t,n){yp[0]=n,this.writeInt32(t,Sr[pl?0:1]),this.writeInt32(t+4,Sr[pl?1:0])}getBufferIdentifier(){if(this.bytes_.length>10)+55296,(f&1023)+56320))}return u}__union_with_string(t,n){return typeof t=="string"?this.__string(n):this.__union(t,n)}__indirect(t){return t+this.readInt32(t)}__vector(t){return t+this.readInt32(t)+Bn}__vector_len(t){return this.readInt32(t+this.readInt32(t))}__has_identifier(t){if(t.length!=Qn)throw new Error("FlatBuffers: file identifier must be length "+Qn);for(let n=0;nthis.minalign&&(this.minalign=t);const o=~(this.bb.capacity()-this.space+n)+1&t-1;for(;this.space=0&&this.vtable[n]==0;n--);const o=n+1;for(;n>=0;n--)this.addInt16(this.vtable[n]!=0?t-this.vtable[n]:0);const u=2;this.addInt16(t-this.object_start);const d=(o+u)*sc;this.addInt16(d);let f=0;const p=this.space;t:for(n=0;n=0;f--)this.writeInt8(d.charCodeAt(f))}this.prep(this.minalign,Bn+u),this.addOffset(t),u&&this.addInt32(this.bb.capacity()-this.space),this.bb.setPosition(this.space)}finishSizePrefixed(t,n){this.finish(t,n,!0)}requiredField(t,n){const o=this.bb.capacity()-t,u=o-this.bb.readInt32(o);if(!(this.bb.readInt16(u+n)!=0))throw new Error("FlatBuffers: field "+n+" must be set")}startVector(t,n,o){this.notNested(),this.vector_num_elems=n,this.prep(Bn,t*n),this.prep(o,t*n)}endVector(){return this.writeInt32(this.vector_num_elems),this.offset()}createSharedString(t){if(!t)return 0;if(this.string_maps||(this.string_maps=new Map),this.string_maps.has(t))return this.string_maps.get(t);const n=this.createString(t);return this.string_maps.set(t,n),n}createString(t){if(!t)return 0;let n;if(t instanceof Uint8Array)n=t;else{n=[];let o=0;for(;o=56320)u=d;else{const f=t.charCodeAt(o++);u=(d<<10)+f+-56613888}u<128?n.push(u):(u<2048?n.push(u>>6&31|192):(u<65536?n.push(u>>12&15|224):n.push(u>>18&7|240,u>>12&63|128),n.push(u>>6&63|128)),n.push(u&63|128))}}this.addInt8(0),this.startVector(1,n.length,1),this.bb.setPosition(this.space-=n.length);for(let o=0,u=this.space,d=this.bb.bytes();o=0;o--)t.addInt32(n[o]);return t.endVector()}static startTypeIdsVector(t,n){t.startVector(4,n,4)}static endUnion(t){return t.endObject()}static createUnion(t,n,o){return Be.startUnion(t),Be.addMode(t,n),Be.addTypeIds(t,o),Be.endUnion(t)}}class Zr{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsUtf8(t,n){return(n||new Zr).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsUtf8(t,n){return t.setPosition(t.position()+Et),(n||new Zr).__init(t.readInt32(t.position())+t.position(),t)}static startUtf8(t){t.startObject(0)}static endUtf8(t){return t.endObject()}static createUtf8(t){return Zr.startUtf8(t),Zr.endUtf8(t)}}var zt;(function(i){i[i.NONE=0]="NONE",i[i.Null=1]="Null",i[i.Int=2]="Int",i[i.FloatingPoint=3]="FloatingPoint",i[i.Binary=4]="Binary",i[i.Utf8=5]="Utf8",i[i.Bool=6]="Bool",i[i.Decimal=7]="Decimal",i[i.Date=8]="Date",i[i.Time=9]="Time",i[i.Timestamp=10]="Timestamp",i[i.Interval=11]="Interval",i[i.List=12]="List",i[i.Struct_=13]="Struct_",i[i.Union=14]="Union",i[i.FixedSizeBinary=15]="FixedSizeBinary",i[i.FixedSizeList=16]="FixedSizeList",i[i.Map=17]="Map",i[i.Duration=18]="Duration",i[i.LargeBinary=19]="LargeBinary",i[i.LargeUtf8=20]="LargeUtf8",i[i.LargeList=21]="LargeList"})(zt||(zt={}));let Ke=class wl{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsField(t,n){return(n||new wl).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsField(t,n){return t.setPosition(t.position()+Et),(n||new wl).__init(t.readInt32(t.position())+t.position(),t)}name(t){const n=this.bb.__offset(this.bb_pos,4);return n?this.bb.__string(this.bb_pos+n,t):null}nullable(){const t=this.bb.__offset(this.bb_pos,6);return t?!!this.bb.readInt8(this.bb_pos+t):!1}typeType(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.readUint8(this.bb_pos+t):zt.NONE}type(t){const n=this.bb.__offset(this.bb_pos,10);return n?this.bb.__union(t,this.bb_pos+n):null}dictionary(t){const n=this.bb.__offset(this.bb_pos,12);return n?(t||new Kn).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}children(t,n){const o=this.bb.__offset(this.bb_pos,14);return o?(n||new wl).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}childrenLength(){const t=this.bb.__offset(this.bb_pos,14);return t?this.bb.__vector_len(this.bb_pos+t):0}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,16);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,16);return t?this.bb.__vector_len(this.bb_pos+t):0}static startField(t){t.startObject(7)}static addName(t,n){t.addFieldOffset(0,n,0)}static addNullable(t,n){t.addFieldInt8(1,+n,0)}static addTypeType(t,n){t.addFieldInt8(2,n,zt.NONE)}static addType(t,n){t.addFieldOffset(3,n,0)}static addDictionary(t,n){t.addFieldOffset(4,n,0)}static addChildren(t,n){t.addFieldOffset(5,n,0)}static createChildrenVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startChildrenVector(t,n){t.startVector(4,n,4)}static addCustomMetadata(t,n){t.addFieldOffset(6,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static endField(t){return t.endObject()}},_n=class $n{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsSchema(t,n){return(n||new $n).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSchema(t,n){return t.setPosition(t.position()+Et),(n||new $n).__init(t.readInt32(t.position())+t.position(),t)}endianness(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt16(this.bb_pos+t):$i.Little}fields(t,n){const o=this.bb.__offset(this.bb_pos,6);return o?(n||new Ke).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}fieldsLength(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,8);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__vector_len(this.bb_pos+t):0}features(t){const n=this.bb.__offset(this.bb_pos,10);return n?this.bb.readInt64(this.bb.__vector(this.bb_pos+n)+t*8):this.bb.createLong(0,0)}featuresLength(){const t=this.bb.__offset(this.bb_pos,10);return t?this.bb.__vector_len(this.bb_pos+t):0}static startSchema(t){t.startObject(4)}static addEndianness(t,n){t.addFieldInt16(0,n,$i.Little)}static addFields(t,n){t.addFieldOffset(1,n,0)}static createFieldsVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startFieldsVector(t,n){t.startVector(4,n,4)}static addCustomMetadata(t,n){t.addFieldOffset(2,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static addFeatures(t,n){t.addFieldOffset(3,n,0)}static createFeaturesVector(t,n){t.startVector(8,n.length,8);for(let o=n.length-1;o>=0;o--)t.addInt64(n[o]);return t.endVector()}static startFeaturesVector(t,n){t.startVector(8,n,8)}static endSchema(t){return t.endObject()}static finishSchemaBuffer(t,n){t.finish(n)}static finishSizePrefixedSchemaBuffer(t,n){t.finish(n,void 0,!0)}static createSchema(t,n,o,u,d){return $n.startSchema(t),$n.addEndianness(t,n),$n.addFields(t,o),$n.addCustomMetadata(t,u),$n.addFeatures(t,d),$n.endSchema(t)}};class Re{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsFooter(t,n){return(n||new Re).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsFooter(t,n){return t.setPosition(t.position()+Et),(n||new Re).__init(t.readInt32(t.position())+t.position(),t)}version(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt16(this.bb_pos+t):Vi.V1}schema(t){const n=this.bb.__offset(this.bb_pos,6);return n?(t||new _n).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}dictionaries(t,n){const o=this.bb.__offset(this.bb_pos,8);return o?(n||new pc).__init(this.bb.__vector(this.bb_pos+o)+t*24,this.bb):null}dictionariesLength(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__vector_len(this.bb_pos+t):0}recordBatches(t,n){const o=this.bb.__offset(this.bb_pos,10);return o?(n||new pc).__init(this.bb.__vector(this.bb_pos+o)+t*24,this.bb):null}recordBatchesLength(){const t=this.bb.__offset(this.bb_pos,10);return t?this.bb.__vector_len(this.bb_pos+t):0}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,12);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,12);return t?this.bb.__vector_len(this.bb_pos+t):0}static startFooter(t){t.startObject(5)}static addVersion(t,n){t.addFieldInt16(0,n,Vi.V1)}static addSchema(t,n){t.addFieldOffset(1,n,0)}static addDictionaries(t,n){t.addFieldOffset(2,n,0)}static startDictionariesVector(t,n){t.startVector(24,n,8)}static addRecordBatches(t,n){t.addFieldOffset(3,n,0)}static startRecordBatchesVector(t,n){t.startVector(24,n,8)}static addCustomMetadata(t,n){t.addFieldOffset(4,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static endFooter(t){return t.endObject()}static finishFooterBuffer(t,n){t.finish(n)}static finishSizePrefixedFooterBuffer(t,n){t.finish(n,void 0,!0)}}class St{constructor(t=[],n,o){this.fields=t||[],this.metadata=n||new Map,o||(o=gc(t)),this.dictionaries=o}get[Symbol.toStringTag](){return"Schema"}get names(){return this.fields.map(t=>t.name)}toString(){return`Schema<{ ${this.fields.map((t,n)=>`${n}: ${t}`).join(", ")} }>`}select(t){const n=new Set(t),o=this.fields.filter(u=>n.has(u.name));return new St(o,this.metadata)}selectAt(t){const n=t.map(o=>this.fields[o]).filter(Boolean);return new St(n,this.metadata)}assign(...t){const n=t[0]instanceof St?t[0]:Array.isArray(t[0])?new St(t[0]):new St(t),o=[...this.fields],u=yl(yl(new Map,this.metadata),n.metadata),d=n.fields.filter(p=>{const y=o.findIndex(w=>w.name===p.name);return~y?(o[y]=p.clone({metadata:yl(yl(new Map,o[y].metadata),p.metadata)}))&&!1:!0}),f=gc(d,new Map);return new St([...o,...d],u,new Map([...this.dictionaries,...f]))}}St.prototype.fields=null;St.prototype.metadata=null;St.prototype.dictionaries=null;class Ct{constructor(t,n,o=!1,u){this.name=t,this.type=n,this.nullable=o,this.metadata=u||new Map}static new(...t){let[n,o,u,d]=t;return t[0]&&typeof t[0]=="object"&&({name:n}=t[0],o===void 0&&(o=t[0].type),u===void 0&&(u=t[0].nullable),d===void 0&&(d=t[0].metadata)),new Ct(`${n}`,o,u,d)}get typeId(){return this.type.typeId}get[Symbol.toStringTag](){return"Field"}toString(){return`${this.name}: ${this.type}`}clone(...t){let[n,o,u,d]=t;return!t[0]||typeof t[0]!="object"?[n=this.name,o=this.type,u=this.nullable,d=this.metadata]=t:{name:n=this.name,type:o=this.type,nullable:u=this.nullable,metadata:d=this.metadata}=t[0],Ct.new(n,o,u,d)}}Ct.prototype.type=null;Ct.prototype.name=null;Ct.prototype.nullable=null;Ct.prototype.metadata=null;function yl(i,t){return new Map([...i||new Map,...t||new Map])}function gc(i,t=new Map){for(let n=-1,o=i.length;++n0&&gc(d.children,t)}return t}var mp=Jn,dw=Xy,fw=ji;class Ys{constructor(t,n=Ue.V4,o,u){this.schema=t,this.version=n,o&&(this._recordBatches=o),u&&(this._dictionaryBatches=u)}static decode(t){t=new fw(mt(t));const n=Re.getRootAsFooter(t),o=St.decode(n.schema());return new hw(o,n)}static encode(t){const n=new dw,o=St.encode(n,t.schema);Re.startRecordBatchesVector(n,t.numRecordBatches);for(const f of[...t.recordBatches()].slice().reverse())Er.encode(n,f);const u=n.endVector();Re.startDictionariesVector(n,t.numDictionaries);for(const f of[...t.dictionaryBatches()].slice().reverse())Er.encode(n,f);const d=n.endVector();return Re.startFooter(n),Re.addSchema(n,o),Re.addVersion(n,Ue.V4),Re.addRecordBatches(n,u),Re.addDictionaries(n,d),Re.finishFooterBuffer(n,Re.endFooter(n)),n.asUint8Array()}get numRecordBatches(){return this._recordBatches.length}get numDictionaries(){return this._dictionaryBatches.length}*recordBatches(){for(let t,n=-1,o=this.numRecordBatches;++n=0&&t=0&&t=0&&t=0&&tthis._closedPromiseResolve=t)}get closed(){return this._closedPromise}cancel(t){return K(this,void 0,void 0,function*(){yield 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this.source.next(t)}throw(t){return this.source.throw(t)}return(t){return this.source.return(t)}peek(t){return this.source.peek(t)}read(t){return this.source.read(t)}}class Hi{constructor(t){t instanceof Hi?this.source=t.source:t instanceof _l?this.source=new Yr(Je.fromAsyncIterable(t)):Cp(t)?this.source=new Yr(Je.fromNodeStream(t)):Fc(t)?this.source=new Yr(Je.fromDOMStream(t)):xp(t)?this.source=new Yr(Je.fromDOMStream(t.body)):Gs(t)?this.source=new Yr(Je.fromIterable(t)):br(t)?this.source=new Yr(Je.fromAsyncIterable(t)):Qi(t)&&(this.source=new Yr(Je.fromAsyncIterable(t)))}[Symbol.asyncIterator](){return this}next(t){return this.source.next(t)}throw(t){return this.source.throw(t)}return(t){return this.source.return(t)}get closed(){return this.source.closed}cancel(t){return this.source.cancel(t)}peek(t){return this.source.peek(t)}read(t){return this.source.read(t)}}class yw{constructor(t){this.source=t}cancel(t){this.return(t)}peek(t){return this.next(t,"peek").value}read(t){return 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i===t||Ne(i,t)&&i.unit===t.unit}function bw(i,t){return i===t||Ne(i,t)&&i.listSize===t.listSize&&i.children.length===t.children.length&&kr.compareManyFields(i.children,t.children)}function Bw(i,t){return 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n=this.schema.fields,[o,u]=t.schema.fields.reduce((p,y,w)=>{const[O,F]=p,A=n.findIndex(x=>x.name===y.name);return~A?F[A]=w:O.push(w),p},[[],[]]),d=this.schema.assign(t.schema),f=[...n.map((p,y)=>[y,u[y]]).map(([p,y])=>y===void 0?this.getChildAt(p):t.getChildAt(y)),...o.map(p=>t.getChildAt(p))].filter(Boolean);return new fe(...oc(d,f))}}em=Symbol.toStringTag;fe[em]=(i=>(i.schema=null,i.batches=[],i._offsets=new Uint32Array([0]),i._nullCount=-1,i[Symbol.isConcatSpreadable]=!0,i.isValid=Ui(Pc),i.get=Ui(ke.getVisitFn(_.Struct)),i.set=Vy(Ze.getVisitFn(_.Struct)),i.indexOf=$y(Ll.getVisitFn(_.Struct)),i.getByteLength=Ui(An.getVisitFn(_.Struct)),"Table"))(fe.prototype);var nm;let Oe=class Ls{constructor(...t){switch(t.length){case 2:{if([this.schema]=t,!(this.schema instanceof St))throw new TypeError("RecordBatch constructor expects a [Schema, Data] pair.");if([,this.data=ct({nullCount:0,type:new 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Ls(n,u)}};nm=Symbol.toStringTag;Oe[nm]=(i=>(i._nullCount=-1,i[Symbol.isConcatSpreadable]=!0,"RecordBatch"))(Oe.prototype);function wp(i,t,n=t.reduce((o,u)=>Math.max(o,u.length),0)){var o;const u=[...i.fields],d=[...t],f=(n+63&-64)>>3;for(const[p,y]of i.fields.entries()){const w=t[p];(!w||w.length!==n)&&(u[p]=y.clone({nullable:!0}),d[p]=(o=w?._changeLengthAndBackfillNullBitmap(n))!==null&&o!==void 0?o:ct({type:y.type,length:n,nullCount:n,nullBitmap:new Uint8Array(f)}))}return[i.assign(u),ct({type:new he(u),length:n,children:d})]}function rm(i,t,n=new Map){for(let o=-1,u=i.length;++o0&&rm(f.children,p.children,n)}return n}class Hc extends Oe{constructor(t){const n=t.fields.map(u=>ct({type:u.type})),o=ct({type:new he(t.fields),nullCount:0,children:n});super(t,o)}}var Hl;(function(i){i[i.BUFFER=0]="BUFFER"})(Hl||(Hl={}));var Yl;(function(i){i[i.LZ4_FRAME=0]="LZ4_FRAME",i[i.ZSTD=1]="ZSTD"})(Yl||(Yl={}));class Ir{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsBodyCompression(t,n){return(n||new Ir).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsBodyCompression(t,n){return t.setPosition(t.position()+Et),(n||new Ir).__init(t.readInt32(t.position())+t.position(),t)}codec(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt8(this.bb_pos+t):Yl.LZ4_FRAME}method(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.readInt8(this.bb_pos+t):Hl.BUFFER}static startBodyCompression(t){t.startObject(2)}static addCodec(t,n){t.addFieldInt8(0,n,Yl.LZ4_FRAME)}static addMethod(t,n){t.addFieldInt8(1,n,Hl.BUFFER)}static endBodyCompression(t){return t.endObject()}static createBodyCompression(t,n,o){return Ir.startBodyCompression(t),Ir.addCodec(t,n),Ir.addMethod(t,o),Ir.endBodyCompression(t)}}class im{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}offset(){return this.bb.readInt64(this.bb_pos)}length(){return this.bb.readInt64(this.bb_pos+8)}static sizeOf(){return 16}static createBuffer(t,n,o){return t.prep(8,16),t.writeInt64(o),t.writeInt64(n),t.offset()}}let sm=class{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}length(){return this.bb.readInt64(this.bb_pos)}nullCount(){return this.bb.readInt64(this.bb_pos+8)}static sizeOf(){return 16}static createFieldNode(t,n,o){return t.prep(8,16),t.writeInt64(o),t.writeInt64(n),t.offset()}},Yn=class wc{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsRecordBatch(t,n){return(n||new wc).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsRecordBatch(t,n){return t.setPosition(t.position()+Et),(n||new wc).__init(t.readInt32(t.position())+t.position(),t)}length(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}nodes(t,n){const o=this.bb.__offset(this.bb_pos,6);return o?(n||new sm).__init(this.bb.__vector(this.bb_pos+o)+t*16,this.bb):null}nodesLength(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}buffers(t,n){const o=this.bb.__offset(this.bb_pos,8);return o?(n||new im).__init(this.bb.__vector(this.bb_pos+o)+t*16,this.bb):null}buffersLength(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__vector_len(this.bb_pos+t):0}compression(t){const n=this.bb.__offset(this.bb_pos,10);return n?(t||new Ir).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}static startRecordBatch(t){t.startObject(4)}static addLength(t,n){t.addFieldInt64(0,n,t.createLong(0,0))}static addNodes(t,n){t.addFieldOffset(1,n,0)}static startNodesVector(t,n){t.startVector(16,n,8)}static addBuffers(t,n){t.addFieldOffset(2,n,0)}static startBuffersVector(t,n){t.startVector(16,n,8)}static addCompression(t,n){t.addFieldOffset(3,n,0)}static endRecordBatch(t){return t.endObject()}},Ai=class _c{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsDictionaryBatch(t,n){return(n||new _c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsDictionaryBatch(t,n){return t.setPosition(t.position()+Et),(n||new _c).__init(t.readInt32(t.position())+t.position(),t)}id(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}data(t){const n=this.bb.__offset(this.bb_pos,6);return n?(t||new Yn).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}isDelta(){const t=this.bb.__offset(this.bb_pos,8);return t?!!this.bb.readInt8(this.bb_pos+t):!1}static startDictionaryBatch(t){t.startObject(3)}static addId(t,n){t.addFieldInt64(0,n,t.createLong(0,0))}static addData(t,n){t.addFieldOffset(1,n,0)}static addIsDelta(t,n){t.addFieldInt8(2,+n,0)}static endDictionaryBatch(t){return t.endObject()}};var Ql;(function(i){i[i.NONE=0]="NONE",i[i.Schema=1]="Schema",i[i.DictionaryBatch=2]="DictionaryBatch",i[i.RecordBatch=3]="RecordBatch",i[i.Tensor=4]="Tensor",i[i.SparseTensor=5]="SparseTensor"})(Ql||(Ql={}));let _r=class wn{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsMessage(t,n){return(n||new wn).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsMessage(t,n){return t.setPosition(t.position()+Et),(n||new wn).__init(t.readInt32(t.position())+t.position(),t)}version(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt16(this.bb_pos+t):Vi.V1}headerType(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.readUint8(this.bb_pos+t):Ql.NONE}header(t){const n=this.bb.__offset(this.bb_pos,8);return n?this.bb.__union(t,this.bb_pos+n):null}bodyLength(){const t=this.bb.__offset(this.bb_pos,10);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,12);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,12);return t?this.bb.__vector_len(this.bb_pos+t):0}static startMessage(t){t.startObject(5)}static addVersion(t,n){t.addFieldInt16(0,n,Vi.V1)}static addHeaderType(t,n){t.addFieldInt8(1,n,Ql.NONE)}static addHeader(t,n){t.addFieldOffset(2,n,0)}static addBodyLength(t,n){t.addFieldInt64(3,n,t.createLong(0,0))}static addCustomMetadata(t,n){t.addFieldOffset(4,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static endMessage(t){return t.endObject()}static finishMessageBuffer(t,n){t.finish(n)}static finishSizePrefixedMessageBuffer(t,n){t.finish(n,void 0,!0)}static createMessage(t,n,o,u,d,f){return wn.startMessage(t),wn.addVersion(t,n),wn.addHeaderType(t,o),wn.addHeader(t,u),wn.addBodyLength(t,d),wn.addCustomMetadata(t,f),wn.endMessage(t)}};var Ew=Jn;class kw extends dt{visit(t,n){return t==null||n==null?void 0:super.visit(t,n)}visitNull(t,n){return Gr.startNull(n),Gr.endNull(n)}visitInt(t,n){return Pe.startInt(n),Pe.addBitWidth(n,t.bitWidth),Pe.addIsSigned(n,t.isSigned),Pe.endInt(n)}visitFloat(t,n){return En.startFloatingPoint(n),En.addPrecision(n,t.precision),En.endFloatingPoint(n)}visitBinary(t,n){return Qr.startBinary(n),Qr.endBinary(n)}visitBool(t,n){return Kr.startBool(n),Kr.endBool(n)}visitUtf8(t,n){return Zr.startUtf8(n),Zr.endUtf8(n)}visitDecimal(t,n){return be.startDecimal(n),be.addScale(n,t.scale),be.addPrecision(n,t.precision),be.addBitWidth(n,t.bitWidth),be.endDecimal(n)}visitDate(t,n){return gl.startDate(n),gl.addUnit(n,t.unit),gl.endDate(n)}visitTime(t,n){return Ge.startTime(n),Ge.addUnit(n,t.unit),Ge.addBitWidth(n,t.bitWidth),Ge.endTime(n)}visitTimestamp(t,n){const o=t.timezone&&n.createString(t.timezone)||void 0;return Xe.startTimestamp(n),Xe.addUnit(n,t.unit),o!==void 0&&Xe.addTimezone(n,o),Xe.endTimestamp(n)}visitInterval(t,n){return kn.startInterval(n),kn.addUnit(n,t.unit),kn.endInterval(n)}visitList(t,n){return Jr.startList(n),Jr.endList(n)}visitStruct(t,n){return Xr.startStruct_(n),Xr.endStruct_(n)}visitUnion(t,n){Be.startTypeIdsVector(n,t.typeIds.length);const o=Be.createTypeIdsVector(n,t.typeIds);return Be.startUnion(n),Be.addMode(n,t.mode),Be.addTypeIds(n,o),Be.endUnion(n)}visitDictionary(t,n){const o=this.visit(t.indices,n);return Kn.startDictionaryEncoding(n),Kn.addId(n,new Ew(t.id,0)),Kn.addIsOrdered(n,t.isOrdered),o!==void 0&&Kn.addIndexType(n,o),Kn.endDictionaryEncoding(n)}visitFixedSizeBinary(t,n){return On.startFixedSizeBinary(n),On.addByteWidth(n,t.byteWidth),On.endFixedSizeBinary(n)}visitFixedSizeList(t,n){return Fn.startFixedSizeList(n),Fn.addListSize(n,t.listSize),Fn.endFixedSizeList(n)}visitMap(t,n){return vl.startMap(n),vl.addKeysSorted(n,t.keysSorted),vl.endMap(n)}}const lc=new kw;function Nw(i,t=new Map){return new St(Tw(i,t),Sl(i.customMetadata),t)}function om(i){return new je(i.count,lm(i.columns),am(i.columns))}function Dw(i){return new xn(om(i.data),i.id,i.isDelta)}function Tw(i,t){return(i.fields||[]).filter(Boolean).map(n=>Ct.fromJSON(n,t))}function _p(i,t){return(i.children||[]).filter(Boolean).map(n=>Ct.fromJSON(n,t))}function lm(i){return(i||[]).reduce((t,n)=>[...t,new ni(n.count,Aw(n.VALIDITY)),...lm(n.children)],[])}function am(i,t=[]){for(let n=-1,o=(i||[]).length;++nt+ +(n===0),0)}function xw(i,t){let n,o,u,d,f,p;return!t||!(d=i.dictionary)?(f=Ip(i,_p(i,t)),u=new Ct(i.name,f,i.nullable,Sl(i.customMetadata))):t.has(n=d.id)?(o=(o=d.indexType)?Sp(o):new $s,p=new zi(t.get(n),o,n,d.isOrdered),u=new Ct(i.name,p,i.nullable,Sl(i.customMetadata))):(o=(o=d.indexType)?Sp(o):new $s,t.set(n,f=Ip(i,_p(i,t))),p=new zi(f,o,n,d.isOrdered),u=new Ct(i.name,p,i.nullable,Sl(i.customMetadata))),u||null}function Sl(i){return new Map(Object.entries(i||{}))}function Sp(i){return new Fr(i.isSigned,i.bitWidth)}function Ip(i,t){const n=i.type.name;switch(n){case"NONE":return new Or;case"null":return new Or;case"binary":return new bl;case"utf8":return new Bl;case"bool":return new Ol;case"list":return new Dl((t||[])[0]);case"struct":return new he(t||[]);case"struct_":return new he(t||[])}switch(n){case"int":{const o=i.type;return new Fr(o.isSigned,o.bitWidth)}case"floatingpoint":{const o=i.type;return new Ws(Fe[o.precision])}case"decimal":{const o=i.type;return new Fl(o.scale,o.precision,o.bitWidth)}case"date":{const o=i.type;return new El(Xn[o.unit])}case"time":{const o=i.type;return new Hs(gt[o.unit],o.bitWidth)}case"timestamp":{const o=i.type;return new kl(gt[o.unit],o.timezone)}case"interval":{const o=i.type;return new Nl(Br[o.unit])}case"union":{const o=i.type;return new Tl(ze[o.mode],o.typeIds||[],t||[])}case"fixedsizebinary":{const o=i.type;return new Al(o.byteWidth)}case"fixedsizelist":{const o=i.type;return new xl(o.listSize,(t||[])[0])}case"map":{const o=i.type;return new Cl((t||[])[0],o.keysSorted)}}throw new Error(`Unrecognized type: "${n}"`)}var ei=Jn,Cw=Xy,Mw=ji;class pe{constructor(t,n,o,u){this._version=n,this._headerType=o,this.body=new Uint8Array(0),u&&(this._createHeader=()=>u),this._bodyLength=typeof t=="number"?t:t.low}static fromJSON(t,n){const o=new pe(0,Ue.V4,n);return o._createHeader=Lw(t,n),o}static decode(t){t=new Mw(mt(t));const n=_r.getRootAsMessage(t),o=n.bodyLength(),u=n.version(),d=n.headerType(),f=new pe(o,u,d);return f._createHeader=Rw(n,d),f}static encode(t){const n=new Cw;let o=-1;return t.isSchema()?o=St.encode(n,t.header()):t.isRecordBatch()?o=je.encode(n,t.header()):t.isDictionaryBatch()&&(o=xn.encode(n,t.header())),_r.startMessage(n),_r.addVersion(n,Ue.V4),_r.addHeader(n,o),_r.addHeaderType(n,t.headerType),_r.addBodyLength(n,new ei(t.bodyLength,0)),_r.finishMessageBuffer(n,_r.endMessage(n)),n.asUint8Array()}static from(t,n=0){if(t instanceof St)return new pe(0,Ue.V4,wt.Schema,t);if(t instanceof je)return new pe(n,Ue.V4,wt.RecordBatch,t);if(t instanceof xn)return new pe(n,Ue.V4,wt.DictionaryBatch,t);throw new Error(`Unrecognized Message header: ${t}`)}get type(){return this.headerType}get version(){return this._version}get headerType(){return this._headerType}get bodyLength(){return this._bodyLength}header(){return this._createHeader()}isSchema(){return this.headerType===wt.Schema}isRecordBatch(){return this.headerType===wt.RecordBatch}isDictionaryBatch(){return this.headerType===wt.DictionaryBatch}}class je{constructor(t,n,o){this._nodes=n,this._buffers=o,this._length=typeof t=="number"?t:t.low}get nodes(){return this._nodes}get length(){return this._length}get buffers(){return this._buffers}}class xn{constructor(t,n,o=!1){this._data=t,this._isDelta=o,this._id=typeof n=="number"?n:n.low}get id(){return this._id}get data(){return this._data}get isDelta(){return this._isDelta}get length(){return this.data.length}get nodes(){return this.data.nodes}get buffers(){return this.data.buffers}}class Dn{constructor(t,n){this.offset=typeof t=="number"?t:t.low,this.length=typeof n=="number"?n:n.low}}class ni{constructor(t,n){this.length=typeof t=="number"?t:t.low,this.nullCount=typeof n=="number"?n:n.low}}function Lw(i,t){return()=>{switch(t){case wt.Schema:return St.fromJSON(i);case wt.RecordBatch:return je.fromJSON(i);case wt.DictionaryBatch:return xn.fromJSON(i)}throw new Error(`Unrecognized Message type: { name: ${wt[t]}, type: ${t} }`)}}function Rw(i,t){return()=>{switch(t){case wt.Schema:return St.decode(i.header(new _n));case wt.RecordBatch:return je.decode(i.header(new Yn),i.version());case wt.DictionaryBatch:return xn.decode(i.header(new Ai),i.version())}throw new Error(`Unrecognized Message type: { name: ${wt[t]}, type: ${t} }`)}}Ct.encode=Kw;Ct.decode=Yw;Ct.fromJSON=xw;St.encode=Qw;St.decode=Pw;St.fromJSON=Nw;je.encode=Jw;je.decode=Uw;je.fromJSON=om;xn.encode=Gw;xn.decode=zw;xn.fromJSON=Dw;ni.encode=Xw;ni.decode=Vw;Dn.encode=Zw;Dn.decode=jw;function Pw(i,t=new Map){const n=Hw(i,t);return new St(n,Il(i),t)}function Uw(i,t=Ue.V4){if(i.compression()!==null)throw new Error("Record batch compression not implemented");return new je(i.length(),$w(i),Ww(i,t))}function zw(i,t=Ue.V4){return new xn(je.decode(i.data(),t),i.id(),i.isDelta())}function jw(i){return new Dn(i.offset(),i.length())}function Vw(i){return new ni(i.length(),i.nullCount())}function $w(i){const t=[];for(let n,o=-1,u=-1,d=i.nodesLength();++oCt.encode(i,d));_n.startFieldsVector(i,n.length);const o=_n.createFieldsVector(i,n),u=t.metadata&&t.metadata.size>0?_n.createCustomMetadataVector(i,[...t.metadata].map(([d,f])=>{const p=i.createString(`${d}`),y=i.createString(`${f}`);return qt.startKeyValue(i),qt.addKey(i,p),qt.addValue(i,y),qt.endKeyValue(i)})):-1;return _n.startSchema(i),_n.addFields(i,o),_n.addEndianness(i,qw?$i.Little:$i.Big),u!==-1&&_n.addCustomMetadata(i,u),_n.endSchema(i)}function Kw(i,t){let n=-1,o=-1,u=-1;const d=t.type;let f=t.typeId;J.isDictionary(d)?(f=d.dictionary.typeId,u=lc.visit(d,i),o=lc.visit(d.dictionary,i)):o=lc.visit(d,i);const p=(d.children||[]).map(O=>Ct.encode(i,O)),y=Ke.createChildrenVector(i,p),w=t.metadata&&t.metadata.size>0?Ke.createCustomMetadataVector(i,[...t.metadata].map(([O,F])=>{const A=i.createString(`${O}`),x=i.createString(`${F}`);return qt.startKeyValue(i),qt.addKey(i,A),qt.addValue(i,x),qt.endKeyValue(i)})):-1;return t.name&&(n=i.createString(t.name)),Ke.startField(i),Ke.addType(i,o),Ke.addTypeType(i,f),Ke.addChildren(i,y),Ke.addNullable(i,!!t.nullable),n!==-1&&Ke.addName(i,n),u!==-1&&Ke.addDictionary(i,u),w!==-1&&Ke.addCustomMetadata(i,w),Ke.endField(i)}function Jw(i,t){const n=t.nodes||[],o=t.buffers||[];Yn.startNodesVector(i,n.length);for(const f of n.slice().reverse())ni.encode(i,f);const u=i.endVector();Yn.startBuffersVector(i,o.length);for(const f of o.slice().reverse())Dn.encode(i,f);const d=i.endVector();return Yn.startRecordBatch(i),Yn.addLength(i,new ei(t.length,0)),Yn.addNodes(i,u),Yn.addBuffers(i,d),Yn.endRecordBatch(i)}function Gw(i,t){const n=je.encode(i,t.data);return Ai.startDictionaryBatch(i),Ai.addId(i,new ei(t.id,0)),Ai.addIsDelta(i,t.isDelta),Ai.addData(i,n),Ai.endDictionaryBatch(i)}function Xw(i,t){return sm.createFieldNode(i,new ei(t.length,0),new ei(t.nullCount,0))}function Zw(i,t){return im.createBuffer(i,new ei(t.offset,0),new ei(t.length,0))}const qw=(()=>{const i=new ArrayBuffer(2);return new DataView(i).setInt16(0,256,!0),new Int16Array(i)[0]===256})(),Yc=i=>`Expected ${wt[i]} Message in stream, but was null or length 0.`,Qc=i=>`Header pointer of flatbuffer-encoded ${wt[i]} Message is null or length 0.`,um=(i,t)=>`Expected to read ${i} metadata bytes, but only read ${t}.`,cm=(i,t)=>`Expected to read ${i} bytes for message body, but only read ${t}.`;class dm{constructor(t){this.source=t instanceof $l?t:new $l(t)}[Symbol.iterator](){return this}next(){let t;return(t=this.readMetadataLength()).done||t.value===-1&&(t=this.readMetadataLength()).done||(t=this.readMetadata(t.value)).done?jt:t}throw(t){return this.source.throw(t)}return(t){return this.source.return(t)}readMessage(t){let n;if((n=this.next()).done)return null;if(t!=null&&n.value.headerType!==t)throw new Error(Yc(t));return n.value}readMessageBody(t){if(t<=0)return new Uint8Array(0);const n=mt(this.source.read(t));if(n.byteLength[...u,...d.VALIDITY&&[d.VALIDITY]||[],...d.TYPE&&[d.TYPE]||[],...d.OFFSET&&[d.OFFSET]||[],...d.DATA&&[d.DATA]||[],...n(d.children)],[])}}readMessage(t){let n;if((n=this.next()).done)return null;if(t!=null&&n.value.headerType!==t)throw new Error(Yc(t));return n.value}readSchema(){const t=wt.Schema,n=this.readMessage(t),o=n?.header();if(!n||!o)throw new Error(Qc(t));return o}}const ea=4,Sc="ARROW1",Qs=new Uint8Array(Sc.length);for(let i=0;ithis):this}readRecordBatch(t){return this._impl.isFile()?this._impl.readRecordBatch(t):null}[Symbol.iterator](){return this._impl[Symbol.iterator]()}[Symbol.asyncIterator](){return this._impl[Symbol.asyncIterator]()}toDOMStream(){return Je.toDOMStream(this.isSync()?{[Symbol.iterator]:()=>this}:{[Symbol.asyncIterator]:()=>this})}toNodeStream(){return Je.toNodeStream(this.isSync()?{[Symbol.iterator]:()=>this}:{[Symbol.asyncIterator]:()=>this},{objectMode:!0})}static throughNode(t){throw new Error('"throughNode" not available in this environment')}static throughDOM(t,n){throw new Error('"throughDOM" not available in this environment')}static from(t){return t instanceof Gn?t:cc(t)?o_(t):Ap(t)?u_(t):br(t)?K(this,void 0,void 0,function*(){return yield Gn.from(yield t)}):xp(t)||Fc(t)||Cp(t)||Qi(t)?a_(new Hi(t)):l_(new $l(t))}static readAll(t){return t instanceof Gn?t.isSync()?Fp(t):Ep(t):cc(t)||ArrayBuffer.isView(t)||Gs(t)||Tp(t)?Fp(t):Ep(t)}}class Kl extends Gn{constructor(t){super(t),this._impl=t}readAll(){return[...this]}[Symbol.iterator](){return this._impl[Symbol.iterator]()}[Symbol.asyncIterator](){return Nn(this,arguments,function*(){yield it(yield*ml(qr(this[Symbol.iterator]())))})}}class Jl extends Gn{constructor(t){super(t),this._impl=t}readAll(){var t,n;return K(this,void 0,void 0,function*(){const o=new Array;try{for(var u=qr(this),d;d=yield u.next(),!d.done;){const f=d.value;o.push(f)}}catch(f){t={error:f}}finally{try{d&&!d.done&&(n=u.return)&&(yield n.call(u))}finally{if(t)throw t.error}}return o})}[Symbol.iterator](){throw new Error("AsyncRecordBatchStreamReader is not Iterable")}[Symbol.asyncIterator](){return this._impl[Symbol.asyncIterator]()}}class hm extends Kl{constructor(t){super(t),this._impl=t}}class r_ extends Jl{constructor(t){super(t),this._impl=t}}class pm{constructor(t=new Map){this.closed=!1,this.autoDestroy=!0,this._dictionaryIndex=0,this._recordBatchIndex=0,this.dictionaries=t}get numDictionaries(){return this._dictionaryIndex}get numRecordBatches(){return this._recordBatchIndex}isSync(){return!1}isAsync(){return!1}isFile(){return!1}isStream(){return!1}reset(t){return this._dictionaryIndex=0,this._recordBatchIndex=0,this.schema=t,this.dictionaries=new Map,this}_loadRecordBatch(t,n){const o=this._loadVectors(t,n,this.schema.fields),u=ct({type:new he(this.schema.fields),length:t.length,children:o});return new Oe(this.schema,u)}_loadDictionaryBatch(t,n){const{id:o,isDelta:u}=t,{dictionaries:d,schema:f}=this,p=d.get(o);if(u||!p){const y=f.dictionaries.get(o),w=this._loadVectors(t.data,n,[y]);return(p&&u?p.concat(new _t(w)):new _t(w)).memoize()}return p.memoize()}_loadVectors(t,n,o){return new tm(n,t.nodes,t.buffers,this.dictionaries).visitMany(o)}}class Gl extends pm{constructor(t,n){super(n),this._reader=cc(t)?new e_(this._handle=t):new dm(this._handle=t)}isSync(){return!0}isStream(){return!0}[Symbol.iterator](){return this}cancel(){!this.closed&&(this.closed=!0)&&(this.reset()._reader.return(),this._reader=null,this.dictionaries=null)}open(t){return this.closed||(this.autoDestroy=mm(this,t),this.schema||(this.schema=this._reader.readSchema())||this.cancel()),this}throw(t){return!this.closed&&this.autoDestroy&&(this.closed=!0)?this.reset()._reader.throw(t):jt}return(t){return!this.closed&&this.autoDestroy&&(this.closed=!0)?this.reset()._reader.return(t):jt}next(){if(this.closed)return jt;let t;const{_reader:n}=this;for(;t=this._readNextMessageAndValidate();)if(t.isSchema())this.reset(t.header());else if(t.isRecordBatch()){this._recordBatchIndex++;const o=t.header(),u=n.readMessageBody(t.bodyLength);return{done:!1,value:this._loadRecordBatch(o,u)}}else if(t.isDictionaryBatch()){this._dictionaryIndex++;const o=t.header(),u=n.readMessageBody(t.bodyLength),d=this._loadDictionaryBatch(o,u);this.dictionaries.set(o.id,d)}return this.schema&&this._recordBatchIndex===0?(this._recordBatchIndex++,{done:!1,value:new Hc(this.schema)}):this.return()}_readNextMessageAndValidate(t){return this._reader.readMessage(t)}}class Xl extends pm{constructor(t,n){super(n),this._reader=new t_(this._handle=t)}isAsync(){return!0}isStream(){return!0}[Symbol.asyncIterator](){return this}cancel(){return K(this,void 0,void 0,function*(){!this.closed&&(this.closed=!0)&&(yield this.reset()._reader.return(),this._reader=null,this.dictionaries=null)})}open(t){return K(this,void 0,void 0,function*(){return this.closed||(this.autoDestroy=mm(this,t),this.schema||(this.schema=yield this._reader.readSchema())||(yield this.cancel())),this})}throw(t){return K(this,void 0,void 0,function*(){return!this.closed&&this.autoDestroy&&(this.closed=!0)?yield this.reset()._reader.throw(t):jt})}return(t){return K(this,void 0,void 0,function*(){return!this.closed&&this.autoDestroy&&(this.closed=!0)?yield this.reset()._reader.return(t):jt})}next(){return K(this,void 0,void 0,function*(){if(this.closed)return jt;let t;const{_reader:n}=this;for(;t=yield this._readNextMessageAndValidate();)if(t.isSchema())yield this.reset(t.header());else if(t.isRecordBatch()){this._recordBatchIndex++;const o=t.header(),u=yield n.readMessageBody(t.bodyLength);return{done:!1,value:this._loadRecordBatch(o,u)}}else if(t.isDictionaryBatch()){this._dictionaryIndex++;const o=t.header(),u=yield n.readMessageBody(t.bodyLength),d=this._loadDictionaryBatch(o,u);this.dictionaries.set(o.id,d)}return this.schema&&this._recordBatchIndex===0?(this._recordBatchIndex++,{done:!1,value:new Hc(this.schema)}):yield this.return()})}_readNextMessageAndValidate(t){return K(this,void 0,void 0,function*(){return yield this._reader.readMessage(t)})}}class ym extends Gl{constructor(t,n){super(t instanceof vp?t:new vp(t),n)}get footer(){return this._footer}get numDictionaries(){return this._footer?this._footer.numDictionaries:0}get numRecordBatches(){return this._footer?this._footer.numRecordBatches:0}isSync(){return!0}isFile(){return!0}open(t){if(!this.closed&&!this._footer){this.schema=(this._footer=this._readFooter()).schema;for(const n of this._footer.dictionaryBatches())n&&this._readDictionaryBatch(this._dictionaryIndex++)}return super.open(t)}readRecordBatch(t){var n;if(this.closed)return null;this._footer||this.open();const o=(n=this._footer)===null||n===void 0?void 0:n.getRecordBatch(t);if(o&&this._handle.seek(o.offset)){const u=this._reader.readMessage(wt.RecordBatch);if(u?.isRecordBatch()){const d=u.header(),f=this._reader.readMessageBody(u.bodyLength);return this._loadRecordBatch(d,f)}}return null}_readDictionaryBatch(t){var n;const o=(n=this._footer)===null||n===void 0?void 0:n.getDictionaryBatch(t);if(o&&this._handle.seek(o.offset)){const u=this._reader.readMessage(wt.DictionaryBatch);if(u?.isDictionaryBatch()){const d=u.header(),f=this._reader.readMessageBody(u.bodyLength),p=this._loadDictionaryBatch(d,f);this.dictionaries.set(d.id,p)}}}_readFooter(){const{_handle:t}=this,n=t.size-fm,o=t.readInt32(n),u=t.readAt(n-o,o);return Ys.decode(u)}_readNextMessageAndValidate(t){var n;if(this._footer||this.open(),this._footer&&this._recordBatchIndexsuper.open}});return K(this,void 0,void 0,function*(){if(!this.closed&&!this._footer){this.schema=(this._footer=yield this._readFooter()).schema;for(const o of this._footer.dictionaryBatches())o&&(yield this._readDictionaryBatch(this._dictionaryIndex++))}return yield n.open.call(this,t)})}readRecordBatch(t){var n;return K(this,void 0,void 0,function*(){if(this.closed)return null;this._footer||(yield this.open());const o=(n=this._footer)===null||n===void 0?void 0:n.getRecordBatch(t);if(o&&(yield this._handle.seek(o.offset))){const u=yield this._reader.readMessage(wt.RecordBatch);if(u?.isRecordBatch()){const d=u.header(),f=yield this._reader.readMessageBody(u.bodyLength);return this._loadRecordBatch(d,f)}}return null})}_readDictionaryBatch(t){var n;return K(this,void 0,void 0,function*(){const o=(n=this._footer)===null||n===void 0?void 0:n.getDictionaryBatch(t);if(o&&(yield this._handle.seek(o.offset))){const u=yield this._reader.readMessage(wt.DictionaryBatch);if(u?.isDictionaryBatch()){const d=u.header(),f=yield this._reader.readMessageBody(u.bodyLength),p=this._loadDictionaryBatch(d,f);this.dictionaries.set(d.id,p)}}})}_readFooter(){return K(this,void 0,void 0,function*(){const{_handle:t}=this;t._pending&&(yield t._pending);const n=t.size-fm,o=yield t.readInt32(n),u=yield t.readAt(n-o,o);return Ys.decode(u)})}_readNextMessageAndValidate(t){return K(this,void 0,void 0,function*(){if(this._footer||(yield this.open()),this._footer&&this._recordBatchIndex=4?Kc(t)?new hm(new ym(i.read())):new Kl(new Gl(i)):new Kl(new Gl(function*(){}()))}function a_(i){return K(this,void 0,void 0,function*(){const t=yield i.peek(to+7&-8);return t&&t.byteLength>=4?Kc(t)?new hm(new ym(yield i.read())):new Jl(new Xl(i)):new Jl(new Xl(function(){return Nn(this,arguments,function*(){})}()))})}function u_(i){return K(this,void 0,void 0,function*(){const{size:t}=yield i.stat(),n=new Wl(i,t);return t>=n_&&Kc(yield n.readAt(0,to+7&-8))?new r_(new i_(n)):new Jl(new Xl(n))})}class Kt extends dt{constructor(){super(),this._byteLength=0,this._nodes=[],this._buffers=[],this._bufferRegions=[]}static assemble(...t){const n=u=>u.flatMap(d=>Array.isArray(d)?n(d):d instanceof Oe?d.data.children:d.data),o=new Kt;return o.visitMany(n(t)),o}visit(t){if(t instanceof _t)return this.visitMany(t.data),this;const{type:n}=t;if(!J.isDictionary(n)){const{length:o,nullCount:u}=t;if(o>2147483647)throw new RangeError("Cannot write arrays larger than 2^31 - 1 in length");J.isNull(n)||cn.call(this,u<=0?new Uint8Array(0):Mc(t.offset,o,t.nullBitmap)),this.nodes.push(new ni(o,u))}return super.visit(t)}visitNull(t){return this}visitDictionary(t){return this.visit(t.clone(t.type.indices))}get nodes(){return this._nodes}get buffers(){return this._buffers}get byteLength(){return this._byteLength}get bufferRegions(){return this._bufferRegions}}function cn(i){const t=i.byteLength+7&-8;return this.buffers.push(i),this.bufferRegions.push(new Dn(this._byteLength,t)),this._byteLength+=t,this}function c_(i){const{type:t,length:n,typeIds:o,valueOffsets:u}=i;if(cn.call(this,o),t.mode===ze.Sparse)return Ic.call(this,i);if(t.mode===ze.Dense){if(i.offset<=0)return cn.call(this,u),Ic.call(this,i);{const d=o.reduce((O,F)=>Math.max(O,F),o[0]),f=new Int32Array(d+1),p=new Int32Array(d+1).fill(-1),y=new Int32Array(n),w=kc(-u[0],n,u);for(let O,F,A=-1;++A=i.length?cn.call(this,new Uint8Array(0)):(t=i.values)instanceof Uint8Array?cn.call(this,Mc(i.offset,i.length,t)):cn.call(this,Ml(i.values))}function Tr(i){return cn.call(this,i.values.subarray(0,i.length*i.stride))}function gm(i){const{length:t,values:n,valueOffsets:o}=i,u=o[0],d=o[t],f=Math.min(d-u,n.byteLength-u);return cn.call(this,kc(-o[0],t,o)),cn.call(this,n.subarray(u,u+f)),this}function Jc(i){const{length:t,valueOffsets:n}=i;return n&&cn.call(this,kc(n[0],t,n)),this.visit(i.children[0])}function Ic(i){return this.visitMany(i.type.children.map((t,n)=>i.children[n]).filter(Boolean))[0]}Kt.prototype.visitBool=d_;Kt.prototype.visitInt=Tr;Kt.prototype.visitFloat=Tr;Kt.prototype.visitUtf8=gm;Kt.prototype.visitBinary=gm;Kt.prototype.visitFixedSizeBinary=Tr;Kt.prototype.visitDate=Tr;Kt.prototype.visitTimestamp=Tr;Kt.prototype.visitTime=Tr;Kt.prototype.visitDecimal=Tr;Kt.prototype.visitList=Jc;Kt.prototype.visitStruct=Ic;Kt.prototype.visitUnion=c_;Kt.prototype.visitInterval=Tr;Kt.prototype.visitFixedSizeList=Jc;Kt.prototype.visitMap=Jc;class vm extends zc{constructor(t){super(),this._position=0,this._started=!1,this._sink=new _l,this._schema=null,this._dictionaryBlocks=[],this._recordBatchBlocks=[],this._dictionaryDeltaOffsets=new Map,Ee(t)||(t={autoDestroy:!0,writeLegacyIpcFormat:!1}),this._autoDestroy=typeof t.autoDestroy=="boolean"?t.autoDestroy:!0,this._writeLegacyIpcFormat=typeof t.writeLegacyIpcFormat=="boolean"?t.writeLegacyIpcFormat:!1}static throughNode(t){throw new Error('"throughNode" not available in this environment')}static throughDOM(t,n){throw new Error('"throughDOM" not available in this environment')}toString(t=!1){return this._sink.toString(t)}toUint8Array(t=!1){return this._sink.toUint8Array(t)}writeAll(t){return br(t)?t.then(n=>this.writeAll(n)):Qi(t)?qc(this,t):Zc(this,t)}get closed(){return this._sink.closed}[Symbol.asyncIterator](){return this._sink[Symbol.asyncIterator]()}toDOMStream(t){return this._sink.toDOMStream(t)}toNodeStream(t){return this._sink.toNodeStream(t)}close(){return this.reset()._sink.close()}abort(t){return this.reset()._sink.abort(t)}finish(){return this._autoDestroy?this.close():this.reset(this._sink,this._schema),this}reset(t=this._sink,n=null){return t===this._sink||t instanceof _l?this._sink=t:(this._sink=new _l,t&&Av(t)?this.toDOMStream({type:"bytes"}).pipeTo(t):t&&xv(t)&&this.toNodeStream({objectMode:!1}).pipe(t)),this._started&&this._schema&&this._writeFooter(this._schema),this._started=!1,this._dictionaryBlocks=[],this._recordBatchBlocks=[],this._dictionaryDeltaOffsets=new Map,(!n||!vc(n,this._schema))&&(n==null?(this._position=0,this._schema=null):(this._started=!0,this._schema=n,this._writeSchema(n))),this}write(t){let n=null;if(this._sink){if(t==null)return this.finish()&&void 0;if(t instanceof fe&&!(n=t.schema))return this.finish()&&void 0;if(t instanceof Oe&&!(n=t.schema))return this.finish()&&void 0}else throw new Error("RecordBatchWriter is closed");if(n&&!vc(n,this._schema)){if(this._started&&this._autoDestroy)return this.close();this.reset(this._sink,n)}t instanceof Oe?t instanceof Hc||this._writeRecordBatch(t):t instanceof fe?this.writeAll(t.batches):Gs(t)&&this.writeAll(t)}_writeMessage(t,n=8){const o=n-1,u=pe.encode(t),d=u.byteLength,f=this._writeLegacyIpcFormat?4:8,p=d+f+o&~o,y=p-d-f;return t.headerType===wt.RecordBatch?this._recordBatchBlocks.push(new Er(p,t.bodyLength,this._position)):t.headerType===wt.DictionaryBatch&&this._dictionaryBlocks.push(new Er(p,t.bodyLength,this._position)),this._writeLegacyIpcFormat||this._write(Int32Array.of(-1)),this._write(Int32Array.of(p-f)),d>0&&this._write(u),this._writePadding(y)}_write(t){if(this._started){const n=mt(t);n&&n.byteLength>0&&(this._sink.write(n),this._position+=n.byteLength)}return this}_writeSchema(t){return this._writeMessage(pe.from(t))}_writeFooter(t){return this._writeLegacyIpcFormat?this._write(Int32Array.of(0)):this._write(Int32Array.of(-1,0))}_writeMagic(){return this._write(Qs)}_writePadding(t){return t>0?this._write(new Uint8Array(t)):this}_writeRecordBatch(t){const{byteLength:n,nodes:o,bufferRegions:u,buffers:d}=Kt.assemble(t),f=new je(t.numRows,o,u),p=pe.from(f,n);return this._writeDictionaries(t)._writeMessage(p)._writeBodyBuffers(d)}_writeDictionaryBatch(t,n,o=!1){this._dictionaryDeltaOffsets.set(n,t.length+(this._dictionaryDeltaOffsets.get(n)||0));const{byteLength:u,nodes:d,bufferRegions:f,buffers:p}=Kt.assemble(new _t([t])),y=new je(t.length,d,f),w=new xn(y,n,o),O=pe.from(w,u);return this._writeMessage(O)._writeBodyBuffers(p)}_writeBodyBuffers(t){let n,o,u;for(let d=-1,f=t.length;++d0&&(this._write(n),(u=(o+7&-8)-o)>0&&this._writePadding(u));return this}_writeDictionaries(t){for(let[n,o]of t.dictionaries){let u=this._dictionaryDeltaOffsets.get(n)||0;if(u===0||(o=o?.slice(u)).length>0)for(const d of o.data)this._writeDictionaryBatch(d,n,u>0),u+=d.length}return this}}class Gc extends vm{static writeAll(t,n){const o=new Gc(n);return br(t)?t.then(u=>o.writeAll(u)):Qi(t)?qc(o,t):Zc(o,t)}}class Xc extends vm{static writeAll(t){const n=new Xc;return br(t)?t.then(o=>n.writeAll(o)):Qi(t)?qc(n,t):Zc(n,t)}constructor(){super(),this._autoDestroy=!0}_writeSchema(t){return this._writeMagic()._writePadding(2)}_writeFooter(t){const n=Ys.encode(new Ys(t,Ue.V4,this._recordBatchBlocks,this._dictionaryBlocks));return super._writeFooter(t)._write(n)._write(Int32Array.of(n.byteLength))._writeMagic()}}function Zc(i,t){let n=t;t instanceof fe&&(n=t.batches,i.reset(void 0,t.schema));for(const o of n)i.write(o);return i.finish()}function qc(i,t){var n,o,u,d;return K(this,void 0,void 0,function*(){try{for(n=qr(t);o=yield n.next(),!o.done;){const f=o.value;i.write(f)}}catch(f){u={error:f}}finally{try{o&&!o.done&&(d=n.return)&&(yield d.call(n))}finally{if(u)throw u.error}}return i.finish()})}function Rs(i){const t=Gn.from(i);return br(t)?t.then(n=>Rs(n)):t.isAsync()?t.readAll().then(n=>new fe(n)):new fe(t.readAll())}function ac(i,t="stream"){return(t==="stream"?Gc:Xc).writeAll(i).toUint8Array(!0)}var kp=function(){function i(t,n,o,u){var d=this;this.getCell=function(f,p){var y=f=d.headerRows&&p=d.headerColumns;if(y){var F=["blank"];return p>0&&F.push("level"+f),{type:"blank",classNames:F.join(" "),content:""}}else if(O){var A=p-d.headerColumns,F=["col_heading","level"+f,"col"+A];return{type:"columns",classNames:F.join(" "),content:d.getContent(d.columnsTable,A,f)}}else if(w){var x=f-d.headerRows,F=["row_heading","level"+p,"row"+x];return{type:"index",id:"T_".concat(d.uuid,"level").concat(p,"_row").concat(x),classNames:F.join(" "),content:d.getContent(d.indexTable,x,p)}}else{var x=f-d.headerRows,A=p-d.headerColumns,F=["data","row"+x,"col"+A],j=d.styler?d.getContent(d.styler.displayValuesTable,x,A):d.getContent(d.dataTable,x,A);return{type:"data",id:"T_".concat(d.uuid,"row").concat(x,"_col").concat(A),classNames:F.join(" "),content:j}}},this.getContent=function(f,p,y){var w=f.getChildAt(y);if(w===null)return"";var O=d.getColumnTypeId(f,y);switch(O){case _.Timestamp:return d.nanosToDate(w.get(p));default:return w.get(p)}},this.dataTable=Rs(t),this.indexTable=Rs(n),this.columnsTable=Rs(o),this.styler=u?{caption:u.caption,displayValuesTable:Rs(u.displayValues),styles:u.styles,uuid:u.uuid}:void 0}return Object.defineProperty(i.prototype,"rows",{get:function(){return this.indexTable.numRows+this.columnsTable.numCols},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"columns",{get:function(){return this.indexTable.numCols+this.columnsTable.numRows},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"headerRows",{get:function(){return this.rows-this.dataRows},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"headerColumns",{get:function(){return this.columns-this.dataColumns},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"dataRows",{get:function(){return this.dataTable.numRows},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"dataColumns",{get:function(){return this.dataTable.numCols},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"uuid",{get:function(){return this.styler&&this.styler.uuid},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"caption",{get:function(){return this.styler&&this.styler.caption},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"styles",{get:function(){return this.styler&&this.styler.styles},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"table",{get:function(){return this.dataTable},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"index",{get:function(){return this.indexTable},enumerable:!1,configurable:!0}),Object.defineProperty(i.prototype,"columnTable",{get:function(){return this.columnsTable},enumerable:!1,configurable:!0}),i.prototype.serialize=function(){return{data:ac(this.dataTable),index:ac(this.indexTable),columns:ac(this.columnsTable)}},i.prototype.getColumnTypeId=function(t,n){return t.schema.fields[n].type.typeId},i.prototype.nanosToDate=function(t){return new Date(t/1e6)},i}(),Us=function(){return Us=Object.assign||function(i){for(var t,n=1,o=arguments.length;n0?i.argsDataframeToObject(t.dfs):{};n=Us(Us({},n),o);var u=!!t.disabled,d=t.theme;d&&f_(d);var f={disabled:u,args:n,theme:d},p=new CustomEvent(i.RENDER_EVENT,{detail:f});i.events.dispatchEvent(p)},i.argsDataframeToObject=function(t){var n=t.map(function(o){var u=o.key,d=o.value;return[u,i.toArrowTable(d)]});return Object.fromEntries(n)},i.toArrowTable=function(t){var n,o=(n=t.data,n.data),u=n.index,d=n.columns,f=n.styler;return new kp(o,u,d,f)},i.sendBackMsg=function(t,n){window.parent.postMessage(Us({isStreamlitMessage:!0,type:t},n),"*")},i}(),f_=function(i){var t=document.createElement("style");document.head.appendChild(t),t.innerHTML=` + :root { + --primary-color: `.concat(i.primaryColor,`; + --background-color: `).concat(i.backgroundColor,`; + --secondary-background-color: 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b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer.es.js @@ -0,0 +1,985 @@ +class B extends HTMLElement { + constructor() { + super(), this.attachShadow({ mode: "open" }), this._pdfUrl = null, this._pdfData = null, this._chunks = [], this._questions = [], this._selectedQuestionId = null, this._showEvidenceOnly = !1, this._pdfDoc = null, this._currentPage = 1, this._scale = 1.5, this._pdfjsLib = null, this._renderedPages = /* @__PURE__ */ new Map(), this._isLoading = !1, this._highlightedChunkId = null; + } + static get observedAttributes() { + return ["pdf-url", "pdf-data", "chunks", "questions", "selected-question-id", "show-evidence-only"]; + } + connectedCallback() { + this.loadPdfJs().then(() => { + this.render(); + }); + } + disconnectedCallback() { + this._renderedPages.clear(), this._pdfDoc && (this._pdfDoc.destroy(), this._pdfDoc = null); + } + attributeChangedCallback(e, t, s) { + if (t !== s) + try { + e === "pdf-url" ? (this._pdfUrl = s, this._pdfData = null) : e === "pdf-data" ? (this._pdfData = s, this._pdfUrl = null) : e === "chunks" ? this._chunks = s ? JSON.parse(s) : [] : e === "questions" ? this._questions = s ? JSON.parse(s) : [] : e === "selected-question-id" ? this._selectedQuestionId = s : e === "show-evidence-only" && (this._showEvidenceOnly = s === "true" || s === ""), this._skipAttributeRender || this.render(); + } catch (i) { + console.error(`Error parsing ${e}:`, i); + } + } + // Public API: Set PDF URL + setPdfUrl(e) { + this._pdfUrl = e, this._pdfData = null, this.setAttribute("pdf-url", e); + } + // Public API: Set PDF data (base64) + setPdfData(e) { + this._pdfData = e, this._pdfUrl = null, this.setAttribute("pdf-data", e); + } + // Public API: Set chunks + setChunks(e) { + this._chunks = e, this.setAttribute("chunks", JSON.stringify(e)); + } + // Public API: Set questions + setQuestions(e) { + this._questions = e, this.setAttribute("questions", JSON.stringify(e)); + } + // Public API: Set selected question + setSelectedQuestionId(e, t = !1) { + this._selectedQuestionId = e, t ? (this._skipAttributeRender = !0, this.setAttribute("selected-question-id", e || ""), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("selected-question-id", e || ""); + } + // Public API: Set evidence filter + setShowEvidenceOnly(e, t = !1) { + this._showEvidenceOnly = e, t ? (this._skipAttributeRender = !0, this.setAttribute("show-evidence-only", e ? "true" : "false"), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("show-evidence-only", e ? "true" : "false"); + } + // Update filter UI without full render + updateFilterUI() { + var s, i; + const e = (s = this.shadowRoot) == null ? void 0 : s.getElementById("question-select"); + e && (e.value = this._selectedQuestionId || ""); + const t = (i = this.shadowRoot) == null ? void 0 : i.getElementById("evidence-filter"); + t && (t.checked = this._showEvidenceOnly), this.renderChunkList(); + } + // Render only the chunk list without re-rendering PDF + renderChunkList() { + var s; + const e = (s = this.shadowRoot) == null ? void 0 : s.querySelector(".chunks-list"); + if (!e) return; + const t = this.getFilteredChunks(); + e.innerHTML = t.length === 0 ? '
No chunks to display
' : t.map((i, n) => { + var g, c; + let r = "?"; + i.metadata && (i.metadata.page_number !== void 0 ? r = parseInt(i.metadata.page_number) || "?" : i.metadata.source !== void 0 && (r = parseInt(i.metadata.source) || "?")); + const o = i.is_evidence === !0, l = ((g = i.similarity_score) == null ? void 0 : g.toFixed(3)) || "N/A", h = ((c = i.llm_score) == null ? void 0 : c.toFixed(3)) || "N/A", a = i.text || "", p = a.substring(0, 150) + (a.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${i.chunk_order !== void 0 ? i.chunk_order + 1 : n + 1} +
+ ${o ? 'Evidence' : ""} + Page ${r} +
+
+
${this.escapeHtml(p)}
+
+ Similarity: ${l} + ${i.llm_score !== null && i.llm_score !== void 0 ? `LLM: ${h}` : ""} +
+
+ `; + }).join(""), this.attachChunkListeners(); + } + // Attach click listeners to chunk items + attachChunkListeners() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.querySelectorAll(".chunk-item"); + e && e.forEach((s) => { + var n; + const i = s.cloneNode(!0); + (n = s.parentNode) == null || n.replaceChild(i, s), i.addEventListener("click", () => { + const r = parseInt(i.dataset.chunkIndex), o = this.getFilteredChunks()[r]; + o && this.navigateToChunk(o); + }); + }); + } + async loadPdfJs() { + if (!this._pdfjsLib) { + if (typeof pdfjsLib > "u") { + const e = document.createElement("script"); + e.src = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.min.js", e.async = !0, await new Promise((t, s) => { + e.onload = t, e.onerror = s, document.head.appendChild(e); + }); + } + this._pdfjsLib = window.pdfjsLib || pdfjsLib, this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.workerSrc = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.worker.min.js"), this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.cMapUrl = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", this._pdfjsLib.GlobalWorkerOptions.cMapPacked = !0); + } + } + async loadPdf() { + if (this._pdfjsLib || await this.loadPdfJs(), this._pdfDoc) + return this._pdfDoc; + this._isLoading = !0, this.updateLoadingDisplay(); + try { + let e; + const t = { + cMapUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", + cMapPacked: !0, + standardFontDataUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/standard_fonts/" + }; + if (this._pdfData) { + const s = this._pdfData.replace(/^data:application\/pdf;base64,/, ""), i = atob(s), n = new Uint8Array(i.length); + for (let r = 0; r < i.length; r++) + n[r] = i.charCodeAt(r); + e = this._pdfjsLib.getDocument({ + data: n, + ...t + }); + } else if (this._pdfUrl) + e = this._pdfjsLib.getDocument({ + url: this._pdfUrl, + ...t + }); + else + throw new Error("No PDF URL or data provided"); + return this._pdfDoc = await e.promise, this._pdfDoc; + } catch (e) { + throw console.error("Error loading PDF:", e), e; + } + } + updateLoadingDisplay() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.getElementById("viewer-content"); + e && this._isLoading && (e.innerHTML = ` +
+ +
Loading PDF...
+
+ `); + } + getFilteredChunks() { + let e = []; + if (this._selectedQuestionId) { + const t = this._questions.find((s) => s.question_id === this._selectedQuestionId); + t && t.chunks ? e = t.chunks : e = this._chunks.filter((s) => s.question_id === this._selectedQuestionId); + } else + e = this._chunks; + return this._showEvidenceOnly && (e = e.filter((t) => t.is_evidence === !0 || t.is_evidence === 1)), e; + } + async renderPage(e) { + if (this._renderedPages.has(e)) + return this._renderedPages.get(e); + try { + const s = await (await this.loadPdf()).getPage(e), i = s.getViewport({ scale: this._scale }), n = document.createElement("canvas"), r = n.getContext("2d"); + return n.height = i.height, n.width = i.width, await s.render({ + canvasContext: r, + viewport: i + }).promise, this._renderedPages.set(e, n), n; + } catch (t) { + return console.error(`Error rendering page ${e}:`, t), null; + } + } + /** + * Calculate log-likelihood keyness scores for words + * Identifies words that are unusually frequent in this chunk compared to other chunks + * Uses Dunning's log-likelihood (G²) statistic + * @param {string} chunkText - The chunk text to analyze + * @param {Array} allChunks - All chunk texts for comparison + * @returns {Map} Map of word to keyness score + */ + calculateKeyness(e, t = []) { + const s = (c) => c.toLowerCase().replace(/[^\w\s]/g, " ").split(/\s+/).filter((f) => f.length > 2), i = s(e), n = /* @__PURE__ */ new Map(); + if (i.forEach((c) => { + n.set(c, (n.get(c) || 0) + 1); + }), t.length === 0) { + const c = Array.from(n.entries()).sort((f, d) => d[1] - f[1]).slice(0, 10); + return new Map(c); + } + const r = [], o = /* @__PURE__ */ new Map(); + t.forEach((c) => { + s(c.text || c).forEach((d) => { + r.push(d), o.set(d, (o.get(d) || 0) + 1); + }); + }); + const l = /* @__PURE__ */ new Map(), h = i.length, a = r.length, p = h + a; + return (/* @__PURE__ */ new Set([...i, ...r])).forEach((c) => { + const f = n.get(c) || 0, d = o.get(c) || 0; + if (f === 0) + return; + const m = (f + d) * (h / p), v = (f + d) * (a / p); + let u = 0; + f > 0 && m > 0 && (u += 2 * f * Math.log(f / m)), d > 0 && v > 0 && (u += 2 * d * Math.log(d / v)), u > 0.01 && f > m && l.set(c, u); + }), l; + } + /** + * Get word-level importance scores for highlighting + * Uses log-likelihood keyness to identify words unusually frequent in this chunk + * @param {string} chunkText - The chunk text + * @param {Array} allChunks - All chunks for comparison + * @returns {Map} Word to keyness score + */ + getWordImportanceScores(e, t = []) { + return this.calculateKeyness(e, t); + } + /** + * Find text positions for a chunk in the PDF page + * Uses exact matching first, falls back to embedding-based semantic matching + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @param {Array} allChunks - All chunks for context (optional, for TF-IDF) + * @returns {Array} Array of bounding boxes {x, y, width, height, wordScores} in viewport coordinates + */ + async findChunkTextPositions(e, t, s, i = []) { + const n = await this.findChunkTextPositionsExact(e, t, s); + if (n.length > 0) { + const r = this.getWordImportanceScores(t, i); + return n.forEach((o) => { + o.wordScores = r; + }), n; + } + return []; + } + /** + * Exact text matching (original implementation) + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @returns {Array} Array of bounding boxes + */ + async findChunkTextPositionsExact(e, t, s) { + try { + const i = await e.getTextContent(); + if (!i || !i.items || i.items.length === 0) + return console.warn("No text content found on page"), []; + const n = (g) => g.toLowerCase().trim().replace(/\s+/g, " "), r = n(t); + if (!r || r.length < 10) + return console.warn("Chunk text too short for reliable matching"), []; + const o = i.items, l = o.map((g) => g.str).join(" "), h = n(l); + let a = h.indexOf(r), p = r; + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(20, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(10, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + return a === -1 ? (console.warn(`Chunk text not found on page: "${t.substring(0, 50)}..."`), []) : this.findTextItemPositions(o, p, a, h, s, n); + } catch (i) { + return console.error("Error finding chunk text positions:", i), []; + } + } + /** + * Find text item positions that match the search text + * @param {Array} textItems - Array of text items from PDF.js + * @param {string} searchText - Normalized text to search for + * @param {number} textIndex - Character index where searchText was found in normalized text + * @param {string} normalizedAllText - Full normalized text from all items + * @param {Object} viewport - PDF.js viewport object + * @param {Function} normalizeText - Text normalization function + * @returns {Array} Array of bounding boxes + */ + findTextItemPositions(e, t, s, i, n, r) { + const o = []; + let l = 0; + const h = []; + for (let a = 0; a < e.length; a++) { + const p = e[a], g = r(p.str), c = g.length + 1; + if (l + g.length >= s && l <= s + t.length && h.push(p), l += c, l > s + t.length) + break; + } + if (h.length === 0) { + const a = t.split(" ").slice(0, 5).join(" "); + let p = ""; + for (const g of e) { + const c = r(g.str); + if (p += c + " ", h.push(g), r(p).includes(a)) + break; + if (h.length > 50) { + h.length = 0; + break; + } + } + } + if (h.length > 0) { + const a = this.calculateBoundingBox(h, n); + a && a.width > 0 && a.height > 0 && o.push(a); + } + return o; + } + /** + * Calculate bounding box from text items and convert to viewport coordinates + * @param {Array} textItems - Array of text items that form the match + * @param {Object} viewport - PDF.js viewport object + * @returns {Object|null} Bounding box {x, y, width, height} in viewport coordinates, or null + */ + calculateBoundingBox(e, t) { + if (!e || e.length === 0) + return null; + let s = 1 / 0, i = 1 / 0, n = -1 / 0, r = -1 / 0; + for (const d of e) + if (d.transform && d.transform.length >= 6) { + const m = d.transform[4], v = d.transform[5], u = d.width || 0, y = d.height || Math.abs(d.transform[3]) || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } else if (d.x !== void 0 && d.y !== void 0) { + const m = d.x, v = d.y, u = d.width || 0, y = d.height || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } + if (s === 1 / 0 || i === 1 / 0) + return null; + let o, l, h, a; + if (t.convertToViewportPoint) + [o, l] = t.convertToViewportPoint(s, i), [h, a] = t.convertToViewportPoint(n, r); + else { + const d = t.height / t.scale; + o = s * t.scale, l = (d - r) * t.scale, h = n * t.scale, a = (d - i) * t.scale; + } + const p = Math.min(o, h), g = Math.min(l, a), c = Math.abs(h - o), f = Math.abs(a - l); + return c < 1 || f < 1 ? null : { x: p, y: g, width: c, height: f }; + } + /** + * Add word-level highlights based on TF-IDF scores + * Highlights individual words within the matched text region + * @param {HTMLElement} container - Container to add highlights to + * @param {Object} page - PDF.js page object + * @param {Object} bbox - Bounding box of matched text + * @param {Map} wordScores - Map of word to TF-IDF score + * @param {Object} viewport - PDF.js viewport + * @param {boolean} isEvidence - Whether this is an evidence chunk + */ + async addWordLevelHighlights(e, t, s, i, n, r) { + try { + const o = await t.getTextContent(); + if (!o || !o.items) + return; + const l = /* @__PURE__ */ new Set([ + "the", + "be", + "to", + "of", + "and", + "a", + "in", + "that", + "have", + "i", + "it", + "for", + "not", + "on", + "with", + "he", + "as", + "you", + "do", + "at", + "this", + "but", + "his", + "by", + "from", + "they", + "we", + "say", + "her", + "she", + "or", + "an", + "will", + "my", + "one", + "all", + "would", + "there", + "their", + "what", + "so", + "up", + "out", + "if", + "about", + "who", + "get", + "which", + "go", + "me", + "when", + "make", + "can", + "like", + "time", + "no", + "just", + "him", + "know", + "take", + "people", + "into", + "year", + "your", + "good", + "some", + "could", + "them", + "see", + "other", + "than", + "then", + "now", + "look", + "only", + "come", + "its", + "over", + "think", + "also", + "back", + "after", + "use", + "two", + "how", + "our", + "work", + "first", + "well", + "way", + "even", + "new", + "want", + "because", + "any", + "these", + "give", + "day", + "most", + "us", + "is", + "are", + "was", + "were", + "been", + "being", + "has", + "had", + "does", + "did", + "may", + "might", + "must", + "shall", + "should", + "could", + "would", + "can", + "cannot", + "will", + "shall" + ]); + let h = i; + i instanceof Map || (h = new Map(Object.entries(i || {}))); + const a = Array.from(h.entries()).sort((w, x) => x[1] - w[1]).slice(0, 10); + if (a.length === 0) { + console.warn("No key words found for highlighting - keyness scores may be empty. WordScores:", h); + return; + } + console.log(`Found ${a.length} key words for highlighting:`, a.map(([w, x]) => `${w}(${x.toFixed(3)})`)); + const p = a[0][1], g = a[a.length - 1][1], c = p - g || 1, f = (w) => w.toLowerCase().replace(/[^\w]/g, ""), d = /* @__PURE__ */ new Set(), m = /* @__PURE__ */ new Map(); + if (a.forEach(([w, x]) => { + const k = f(w); + k.length >= 3 && (d.add(k), m.set(k, x)); + }), d.size === 0) + return; + const v = 0.1, u = s.x - s.width * v, y = s.x + s.width + s.width * v, T = s.y - s.height * v, j = s.y + s.height + s.height * v, D = n.height / n.scale, O = (w, x, k, C) => { + if (n.convertToViewportPoint) { + const [L, q] = n.convertToViewportPoint(w, x), W = w + k, E = x + C, [P, I] = n.convertToViewportPoint(W, E); + return { + x: L, + y: q, + width: Math.abs(P - L), + height: Math.abs(I - q) + }; + } else + return { + x: w * n.scale, + y: (D - (x + C)) * n.scale, + width: k * n.scale, + height: C * n.scale + }; + }; + let S = 0; + const N = 50; + for (const w of o.items) { + if (S >= N) break; + if (!w.transform || w.transform.length < 6) continue; + const x = w.transform[4], k = w.transform[5], C = w.width || 0, L = w.height || Math.abs(w.transform[3]) || 12, q = x + C, W = k + L, E = O(x, k, C, L), P = E.x, I = E.y, F = E.width, R = E.height; + if (P < u || P + F > y || I < T || I + R > j) + continue; + const M = f(w.str); + if (d.has(M)) { + const $ = m.get(M), z = 0.5 + ($ - g) / c * 0.4, _ = document.createElement("div"); + _.className = `word-highlight ${r ? "evidence-word" : ""}`, _.style.left = `${P / n.width * 100}%`, _.style.top = `${I / n.height * 100}%`, _.style.width = `${F / n.width * 100}%`, _.style.height = `${R / n.height * 100}%`, _.style.opacity = z, _.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", _.style.borderRadius = "2px", _.title = `Important word: "${w.str}" (Keyness: ${$.toFixed(3)})`, e.appendChild(_), S++; + } else + for (const $ of d) + if (M.startsWith($) || M.endsWith($)) { + const A = m.get($), _ = 0.5 + (A - g) / c * 0.4, b = document.createElement("div"); + b.className = `word-highlight ${r ? "evidence-word" : ""}`, b.style.left = `${P / n.width * 100}%`, b.style.top = `${I / n.height * 100}%`, b.style.width = `${F / n.width * 100}%`, b.style.height = `${R / n.height * 100}%`, b.style.opacity = _, b.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", b.style.borderRadius = "2px", b.title = `Important word: "${w.str}" (Keyness: ${A.toFixed(3)})`, e.appendChild(b), S++; + break; + } + } + console.log(`Added ${S} word highlights for ${a.length} key words`); + } catch (o) { + console.error("Error adding word-level highlights:", o); + } + } + async navigateToPage(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + this._currentPage = e, await this.render(), this._selectedQuestionId = t, this._showEvidenceOnly = s, requestAnimationFrame(() => { + var r, o; + const i = (r = this.shadowRoot) == null ? void 0 : r.getElementById("question-select"); + i && (i.value = t || ""); + const n = (o = this.shadowRoot) == null ? void 0 : o.getElementById("evidence-filter"); + n && (n.checked = s); + }); + } + async navigateToChunk(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + let i = 1; + if (e.metadata && (e.metadata.page_number !== void 0 ? i = parseInt(e.metadata.page_number) || 1 : e.metadata.source !== void 0 && (i = parseInt(e.metadata.source) || 1)), this._pdfDoc) { + const n = this._pdfDoc.numPages; + i < 1 && (i = 1), i > n && (i = n); + } + await this.navigateToPage(i), this._selectedQuestionId = t, this._showEvidenceOnly = s, this.dispatchEvent(new CustomEvent("chunk-selected", { + detail: { chunk: e, pageNum: i }, + bubbles: !0, + composed: !0 + })); + } + // Public API: Navigate to chunk by ID (for Streamlit communication) + // chunkId format: "question_id_chunk_order" (e.g., "tcfd_1_0") + // Note: question_id may contain underscores, so we split from the right + async navigateToChunkById(e) { + if (!e) return; + const t = e.lastIndexOf("_"); + if (t === -1) { + console.warn(`Invalid chunk ID format: ${e}. Expected format: "question_id_chunk_order"`); + return; + } + const s = e.substring(0, t), i = e.substring(t + 1), n = parseInt(i); + if (isNaN(n)) { + console.warn(`Invalid chunk order in chunk ID: ${e} (parsed as: ${i})`); + return; + } + const r = this._chunks.find((l) => { + const h = l.question_id || "", a = l.chunk_order !== void 0 ? l.chunk_order : -1; + return h === s && (a === n || a === n - 1 || a === n + 1); + }); + if (!r) { + console.warn(`Chunk not found for ID: ${e} (question_id: ${s}, chunk_order: ${n})`), console.debug("Available chunks:", this._chunks.map((l) => ({ + question_id: l.question_id, + chunk_order: l.chunk_order + }))); + return; + } + const o = this._showEvidenceOnly; + this.setSelectedQuestionId(s), await new Promise((l) => setTimeout(l, 100)), await this.navigateToChunk(r), this._showEvidenceOnly = o, this._highlightedChunkId = e; + } + async render() { + if (!this.shadowRoot) return; + const e = this._selectedQuestionId, t = this._showEvidenceOnly, s = this.getFilteredChunks(), i = {}; + s.forEach((o) => { + let l = 1; + o.metadata && (o.metadata.page_number !== void 0 ? l = parseInt(o.metadata.page_number) || 1 : o.metadata.source !== void 0 && (l = parseInt(o.metadata.source) || 1)), i[l] || (i[l] = []), i[l].push(o); + }); + const n = ` + + `, r = ` +
+
+
+

Chunks by Question

+
+ +
+
+ + +
+
+
+ ${s.length === 0 ? '
No chunks to display
' : ""} + ${s.map((o, l) => { + var d, m; + let h = "?"; + o.metadata && (o.metadata.page_number !== void 0 ? h = parseInt(o.metadata.page_number) || "?" : o.metadata.source !== void 0 && (h = parseInt(o.metadata.source) || "?")); + const a = o.is_evidence === !0, p = ((d = o.similarity_score) == null ? void 0 : d.toFixed(3)) || "N/A", g = ((m = o.llm_score) == null ? void 0 : m.toFixed(3)) || "N/A", c = o.text || "", f = c.substring(0, 150) + (c.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${o.chunk_order !== void 0 ? o.chunk_order + 1 : l + 1} +
+ ${a ? 'Evidence' : ""} + Page ${h} +
+
+
${this.escapeHtml(f)}
+
+ Similarity: ${p} + ${o.llm_score !== null && o.llm_score !== void 0 ? `LLM: ${g}` : ""} +
+
+ `; + }).join("")} +
+
+
+
+ + + Page ${this._currentPage} of - + + +
+
+
Loading PDF...
+
+
+
+ `; + this.shadowRoot.innerHTML = n + r, this._selectedQuestionId = e, this._showEvidenceOnly = t, this.setupEventListeners(), setTimeout(() => { + const o = this.shadowRoot.getElementById("question-select"); + o && this._selectedQuestionId !== void 0 && (o.value = this._selectedQuestionId || ""); + const l = this.shadowRoot.getElementById("evidence-filter"); + l && this._showEvidenceOnly !== void 0 && (l.checked = this._showEvidenceOnly); + }, 0), this.loadAndRenderPdf(); + } + escapeHtml(e) { + const t = document.createElement("div"); + return t.textContent = e, t.innerHTML; + } + setupEventListeners() { + const e = this.shadowRoot.getElementById("question-select"); + e && e.addEventListener("change", (n) => { + this.setSelectedQuestionId(n.target.value || null, !0); + }); + const t = this.shadowRoot.getElementById("evidence-filter"); + t && t.addEventListener("change", (n) => { + this.setShowEvidenceOnly(n.target.checked, !0); + }), this.attachChunkListeners(); + const s = this.shadowRoot.getElementById("prev-page"), i = this.shadowRoot.getElementById("next-page"); + s && s.addEventListener("click", () => { + this._currentPage > 1 && this.navigateToPage(this._currentPage - 1); + }), i && i.addEventListener("click", async () => { + if (this._pdfDoc) { + const n = this._pdfDoc.numPages; + this._currentPage < n && await this.navigateToPage(this._currentPage + 1); + } + }); + } + async loadAndRenderPdf() { + try { + this._isLoading = !0, this.updateLoadingDisplay(); + const t = (await this.loadPdf()).numPages, s = this.shadowRoot.getElementById("total-pages"); + s && (s.textContent = t), await this.renderCurrentPage(), this._isLoading = !1; + } catch (e) { + this._isLoading = !1; + const t = this.shadowRoot.getElementById("viewer-content"); + t && (t.innerHTML = `
Error loading PDF: ${e.message}
`); + } + } + async renderCurrentPage() { + const e = this.shadowRoot.getElementById("viewer-content"); + if (e) + try { + const t = await this.loadPdf(), s = t.numPages; + this._currentPage < 1 && (this._currentPage = 1), this._currentPage > s && (this._currentPage = s); + const i = this.shadowRoot.getElementById("current-page"); + i && (i.textContent = this._currentPage); + const n = await this.renderPage(this._currentPage); + if (!n) { + e.innerHTML = '
Error rendering page
'; + return; + } + const r = await t.getPage(this._currentPage), o = r.getViewport({ scale: this._scale }), l = this.getFilteredChunks(), h = l.filter((c) => { + let f = 1; + return c.metadata && (c.metadata.page_number !== void 0 ? f = parseInt(c.metadata.page_number) || 1 : c.metadata.source !== void 0 && (f = parseInt(c.metadata.source) || 1)), f === this._currentPage; + }), a = document.createElement("div"); + a.className = "page-container"; + const p = document.createElement("canvas"); + if (p.className = "page-canvas", p.width = n.width, p.height = n.height, p.getContext("2d").drawImage(n, 0, 0), a.appendChild(p), h.length > 0) { + const c = document.createElement("div"); + c.className = "page-highlights"; + const f = l.map((d) => ({ text: d.text || "" })); + for (const d of h) { + const m = d.text || ""; + if (!m || m.trim().length === 0) + continue; + const v = await this.findChunkTextPositions( + r, + m, + o, + f + ); + if (v.length > 0) + v.forEach((u) => { + const y = document.createElement("div"); + y.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`; + const T = u.x / o.width * 100, j = u.y / o.height * 100, D = u.width / o.width * 100, O = u.height / o.height * 100; + y.style.left = `${T}%`, y.style.top = `${j}%`, y.style.width = `${D}%`, y.style.height = `${O}%`, y.title = d.is_evidence === !0 || d.is_evidence === 1 ? `Evidence chunk: ${m.substring(0, 50)}...` : `Chunk: ${m.substring(0, 50)}...`, c.appendChild(y), u.wordScores && (u.wordScores instanceof Map ? u.wordScores.size > 0 : Object.keys(u.wordScores || {}).length > 0) ? (console.log(`Adding word highlights for chunk with ${u.wordScores instanceof Map ? u.wordScores.size : Object.keys(u.wordScores || {}).length} word scores`), this.addWordLevelHighlights( + c, + r, + u, + u.wordScores, + o, + d.is_evidence === !0 || d.is_evidence === 1 + )) : console.warn("No wordScores found for chunk, skipping word highlights"); + }); + else { + console.warn(`Could not find text position for chunk on page ${this._currentPage}`); + const u = document.createElement("div"); + u.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`, u.style.top = "5%", u.style.left = "5%", u.style.width = "10px", u.style.height = "10px", u.style.borderRadius = "50%", u.title = "Chunk text position not found", c.appendChild(u); + } + } + a.appendChild(c); + } + e.innerHTML = "", e.appendChild(a); + } catch (t) { + console.error("Error rendering current page:", t), e.innerHTML = `
Error rendering page: ${t.message}
`; + } + } +} +customElements.get("pdf-viewer-with-chunks") || customElements.define("pdf-viewer-with-chunks", B); +export { + B as default +}; diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/index-pdf-viewer.js b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/index-pdf-viewer.js new file mode 100644 index 00000000..f4c3a862 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/index-pdf-viewer.js @@ -0,0 +1,63 @@ +(function(){const t=document.createElement("link").relList;if(t&&t.supports&&t.supports("modulepreload"))return;for(const u of document.querySelectorAll('link[rel="modulepreload"]'))o(u);new MutationObserver(u=>{for(const d of u)if(d.type==="childList")for(const f of d.addedNodes)f.tagName==="LINK"&&f.rel==="modulepreload"&&o(f)}).observe(document,{childList:!0,subtree:!0});function n(u){const d={};return 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Gy(new Uint8Array(t))}clear(){this.position_=0}bytes(){return this.bytes_}position(){return this.position_}setPosition(t){this.position_=t}capacity(){return this.bytes_.length}readInt8(t){return this.readUint8(t)<<24>>24}readUint8(t){return this.bytes_[t]}readInt16(t){return this.readUint16(t)<<16>>16}readUint16(t){return this.bytes_[t]|this.bytes_[t+1]<<8}readInt32(t){return this.bytes_[t]|this.bytes_[t+1]<<8|this.bytes_[t+2]<<16|this.bytes_[t+3]<<24}readUint32(t){return this.readInt32(t)>>>0}readInt64(t){return new Jn(this.readInt32(t),this.readInt32(t+4))}readUint64(t){return new Jn(this.readUint32(t),this.readUint32(t+4))}readFloat32(t){return Sr[0]=this.readInt32(t),pp[0]}readFloat64(t){return Sr[pl?0:1]=this.readInt32(t),Sr[pl?1:0]=this.readInt32(t+4),yp[0]}writeInt8(t,n){this.bytes_[t]=n}writeUint8(t,n){this.bytes_[t]=n}writeInt16(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8}writeUint16(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8}writeInt32(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8,this.bytes_[t+2]=n>>16,this.bytes_[t+3]=n>>24}writeUint32(t,n){this.bytes_[t]=n,this.bytes_[t+1]=n>>8,this.bytes_[t+2]=n>>16,this.bytes_[t+3]=n>>24}writeInt64(t,n){this.writeInt32(t,n.low),this.writeInt32(t+4,n.high)}writeUint64(t,n){this.writeUint32(t,n.low),this.writeUint32(t+4,n.high)}writeFloat32(t,n){pp[0]=n,this.writeInt32(t,Sr[0])}writeFloat64(t,n){yp[0]=n,this.writeInt32(t,Sr[pl?0:1]),this.writeInt32(t+4,Sr[pl?1:0])}getBufferIdentifier(){if(this.bytes_.length>10)+55296,(f&1023)+56320))}return u}__union_with_string(t,n){return typeof t=="string"?this.__string(n):this.__union(t,n)}__indirect(t){return t+this.readInt32(t)}__vector(t){return t+this.readInt32(t)+Bn}__vector_len(t){return this.readInt32(t+this.readInt32(t))}__has_identifier(t){if(t.length!=Qn)throw new Error("FlatBuffers: file identifier must be length "+Qn);for(let n=0;nthis.minalign&&(this.minalign=t);const o=~(this.bb.capacity()-this.space+n)+1&t-1;for(;this.space=0&&this.vtable[n]==0;n--);const o=n+1;for(;n>=0;n--)this.addInt16(this.vtable[n]!=0?t-this.vtable[n]:0);const u=2;this.addInt16(t-this.object_start);const d=(o+u)*sc;this.addInt16(d);let f=0;const p=this.space;t:for(n=0;n=0;f--)this.writeInt8(d.charCodeAt(f))}this.prep(this.minalign,Bn+u),this.addOffset(t),u&&this.addInt32(this.bb.capacity()-this.space),this.bb.setPosition(this.space)}finishSizePrefixed(t,n){this.finish(t,n,!0)}requiredField(t,n){const o=this.bb.capacity()-t,u=o-this.bb.readInt32(o);if(!(this.bb.readInt16(u+n)!=0))throw new Error("FlatBuffers: field "+n+" must be set")}startVector(t,n,o){this.notNested(),this.vector_num_elems=n,this.prep(Bn,t*n),this.prep(o,t*n)}endVector(){return this.writeInt32(this.vector_num_elems),this.offset()}createSharedString(t){if(!t)return 0;if(this.string_maps||(this.string_maps=new Map),this.string_maps.has(t))return this.string_maps.get(t);const n=this.createString(t);return this.string_maps.set(t,n),n}createString(t){if(!t)return 0;let n;if(t instanceof Uint8Array)n=t;else{n=[];let o=0;for(;o=56320)u=d;else{const f=t.charCodeAt(o++);u=(d<<10)+f+-56613888}u<128?n.push(u):(u<2048?n.push(u>>6&31|192):(u<65536?n.push(u>>12&15|224):n.push(u>>18&7|240,u>>12&63|128),n.push(u>>6&63|128)),n.push(u&63|128))}}this.addInt8(0),this.startVector(1,n.length,1),this.bb.setPosition(this.space-=n.length);for(let o=0,u=this.space,d=this.bb.bytes();o=0;o--)t.addInt32(n[o]);return t.endVector()}static startTypeIdsVector(t,n){t.startVector(4,n,4)}static endUnion(t){return t.endObject()}static createUnion(t,n,o){return Be.startUnion(t),Be.addMode(t,n),Be.addTypeIds(t,o),Be.endUnion(t)}}class Zr{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsUtf8(t,n){return(n||new Zr).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsUtf8(t,n){return t.setPosition(t.position()+Et),(n||new Zr).__init(t.readInt32(t.position())+t.position(),t)}static startUtf8(t){t.startObject(0)}static endUtf8(t){return t.endObject()}static createUtf8(t){return Zr.startUtf8(t),Zr.endUtf8(t)}}var zt;(function(i){i[i.NONE=0]="NONE",i[i.Null=1]="Null",i[i.Int=2]="Int",i[i.FloatingPoint=3]="FloatingPoint",i[i.Binary=4]="Binary",i[i.Utf8=5]="Utf8",i[i.Bool=6]="Bool",i[i.Decimal=7]="Decimal",i[i.Date=8]="Date",i[i.Time=9]="Time",i[i.Timestamp=10]="Timestamp",i[i.Interval=11]="Interval",i[i.List=12]="List",i[i.Struct_=13]="Struct_",i[i.Union=14]="Union",i[i.FixedSizeBinary=15]="FixedSizeBinary",i[i.FixedSizeList=16]="FixedSizeList",i[i.Map=17]="Map",i[i.Duration=18]="Duration",i[i.LargeBinary=19]="LargeBinary",i[i.LargeUtf8=20]="LargeUtf8",i[i.LargeList=21]="LargeList"})(zt||(zt={}));let Ke=class wl{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsField(t,n){return(n||new wl).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsField(t,n){return t.setPosition(t.position()+Et),(n||new wl).__init(t.readInt32(t.position())+t.position(),t)}name(t){const n=this.bb.__offset(this.bb_pos,4);return n?this.bb.__string(this.bb_pos+n,t):null}nullable(){const t=this.bb.__offset(this.bb_pos,6);return t?!!this.bb.readInt8(this.bb_pos+t):!1}typeType(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.readUint8(this.bb_pos+t):zt.NONE}type(t){const n=this.bb.__offset(this.bb_pos,10);return n?this.bb.__union(t,this.bb_pos+n):null}dictionary(t){const n=this.bb.__offset(this.bb_pos,12);return n?(t||new Kn).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}children(t,n){const o=this.bb.__offset(this.bb_pos,14);return o?(n||new wl).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}childrenLength(){const t=this.bb.__offset(this.bb_pos,14);return t?this.bb.__vector_len(this.bb_pos+t):0}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,16);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,16);return t?this.bb.__vector_len(this.bb_pos+t):0}static startField(t){t.startObject(7)}static addName(t,n){t.addFieldOffset(0,n,0)}static addNullable(t,n){t.addFieldInt8(1,+n,0)}static addTypeType(t,n){t.addFieldInt8(2,n,zt.NONE)}static addType(t,n){t.addFieldOffset(3,n,0)}static addDictionary(t,n){t.addFieldOffset(4,n,0)}static addChildren(t,n){t.addFieldOffset(5,n,0)}static createChildrenVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startChildrenVector(t,n){t.startVector(4,n,4)}static addCustomMetadata(t,n){t.addFieldOffset(6,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static endField(t){return t.endObject()}},_n=class $n{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsSchema(t,n){return(n||new $n).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsSchema(t,n){return t.setPosition(t.position()+Et),(n||new $n).__init(t.readInt32(t.position())+t.position(),t)}endianness(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt16(this.bb_pos+t):$i.Little}fields(t,n){const o=this.bb.__offset(this.bb_pos,6);return o?(n||new Ke).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}fieldsLength(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,8);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__vector_len(this.bb_pos+t):0}features(t){const n=this.bb.__offset(this.bb_pos,10);return n?this.bb.readInt64(this.bb.__vector(this.bb_pos+n)+t*8):this.bb.createLong(0,0)}featuresLength(){const t=this.bb.__offset(this.bb_pos,10);return t?this.bb.__vector_len(this.bb_pos+t):0}static startSchema(t){t.startObject(4)}static addEndianness(t,n){t.addFieldInt16(0,n,$i.Little)}static addFields(t,n){t.addFieldOffset(1,n,0)}static createFieldsVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startFieldsVector(t,n){t.startVector(4,n,4)}static addCustomMetadata(t,n){t.addFieldOffset(2,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static addFeatures(t,n){t.addFieldOffset(3,n,0)}static createFeaturesVector(t,n){t.startVector(8,n.length,8);for(let o=n.length-1;o>=0;o--)t.addInt64(n[o]);return t.endVector()}static startFeaturesVector(t,n){t.startVector(8,n,8)}static endSchema(t){return t.endObject()}static finishSchemaBuffer(t,n){t.finish(n)}static finishSizePrefixedSchemaBuffer(t,n){t.finish(n,void 0,!0)}static createSchema(t,n,o,u,d){return $n.startSchema(t),$n.addEndianness(t,n),$n.addFields(t,o),$n.addCustomMetadata(t,u),$n.addFeatures(t,d),$n.endSchema(t)}};class Re{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsFooter(t,n){return(n||new Re).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsFooter(t,n){return t.setPosition(t.position()+Et),(n||new Re).__init(t.readInt32(t.position())+t.position(),t)}version(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt16(this.bb_pos+t):Vi.V1}schema(t){const n=this.bb.__offset(this.bb_pos,6);return n?(t||new _n).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}dictionaries(t,n){const o=this.bb.__offset(this.bb_pos,8);return o?(n||new pc).__init(this.bb.__vector(this.bb_pos+o)+t*24,this.bb):null}dictionariesLength(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__vector_len(this.bb_pos+t):0}recordBatches(t,n){const o=this.bb.__offset(this.bb_pos,10);return o?(n||new pc).__init(this.bb.__vector(this.bb_pos+o)+t*24,this.bb):null}recordBatchesLength(){const t=this.bb.__offset(this.bb_pos,10);return t?this.bb.__vector_len(this.bb_pos+t):0}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,12);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,12);return t?this.bb.__vector_len(this.bb_pos+t):0}static startFooter(t){t.startObject(5)}static addVersion(t,n){t.addFieldInt16(0,n,Vi.V1)}static addSchema(t,n){t.addFieldOffset(1,n,0)}static addDictionaries(t,n){t.addFieldOffset(2,n,0)}static startDictionariesVector(t,n){t.startVector(24,n,8)}static addRecordBatches(t,n){t.addFieldOffset(3,n,0)}static startRecordBatchesVector(t,n){t.startVector(24,n,8)}static addCustomMetadata(t,n){t.addFieldOffset(4,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static endFooter(t){return t.endObject()}static finishFooterBuffer(t,n){t.finish(n)}static finishSizePrefixedFooterBuffer(t,n){t.finish(n,void 0,!0)}}class St{constructor(t=[],n,o){this.fields=t||[],this.metadata=n||new Map,o||(o=gc(t)),this.dictionaries=o}get[Symbol.toStringTag](){return"Schema"}get names(){return this.fields.map(t=>t.name)}toString(){return`Schema<{ ${this.fields.map((t,n)=>`${n}: ${t}`).join(", ")} }>`}select(t){const n=new Set(t),o=this.fields.filter(u=>n.has(u.name));return new St(o,this.metadata)}selectAt(t){const n=t.map(o=>this.fields[o]).filter(Boolean);return new St(n,this.metadata)}assign(...t){const n=t[0]instanceof St?t[0]:Array.isArray(t[0])?new St(t[0]):new St(t),o=[...this.fields],u=yl(yl(new Map,this.metadata),n.metadata),d=n.fields.filter(p=>{const y=o.findIndex(w=>w.name===p.name);return~y?(o[y]=p.clone({metadata:yl(yl(new Map,o[y].metadata),p.metadata)}))&&!1:!0}),f=gc(d,new Map);return new St([...o,...d],u,new Map([...this.dictionaries,...f]))}}St.prototype.fields=null;St.prototype.metadata=null;St.prototype.dictionaries=null;class Ct{constructor(t,n,o=!1,u){this.name=t,this.type=n,this.nullable=o,this.metadata=u||new Map}static new(...t){let[n,o,u,d]=t;return t[0]&&typeof t[0]=="object"&&({name:n}=t[0],o===void 0&&(o=t[0].type),u===void 0&&(u=t[0].nullable),d===void 0&&(d=t[0].metadata)),new Ct(`${n}`,o,u,d)}get typeId(){return this.type.typeId}get[Symbol.toStringTag](){return"Field"}toString(){return`${this.name}: ${this.type}`}clone(...t){let[n,o,u,d]=t;return!t[0]||typeof t[0]!="object"?[n=this.name,o=this.type,u=this.nullable,d=this.metadata]=t:{name:n=this.name,type:o=this.type,nullable:u=this.nullable,metadata:d=this.metadata}=t[0],Ct.new(n,o,u,d)}}Ct.prototype.type=null;Ct.prototype.name=null;Ct.prototype.nullable=null;Ct.prototype.metadata=null;function yl(i,t){return new Map([...i||new Map,...t||new Map])}function gc(i,t=new Map){for(let n=-1,o=i.length;++n0&&gc(d.children,t)}return t}var mp=Jn,dw=Xy,fw=ji;class Ys{constructor(t,n=Ue.V4,o,u){this.schema=t,this.version=n,o&&(this._recordBatches=o),u&&(this._dictionaryBatches=u)}static decode(t){t=new fw(mt(t));const n=Re.getRootAsFooter(t),o=St.decode(n.schema());return new hw(o,n)}static encode(t){const n=new dw,o=St.encode(n,t.schema);Re.startRecordBatchesVector(n,t.numRecordBatches);for(const f of[...t.recordBatches()].slice().reverse())Er.encode(n,f);const u=n.endVector();Re.startDictionariesVector(n,t.numDictionaries);for(const f of[...t.dictionaryBatches()].slice().reverse())Er.encode(n,f);const d=n.endVector();return Re.startFooter(n),Re.addSchema(n,o),Re.addVersion(n,Ue.V4),Re.addRecordBatches(n,u),Re.addDictionaries(n,d),Re.finishFooterBuffer(n,Re.endFooter(n)),n.asUint8Array()}get numRecordBatches(){return this._recordBatches.length}get numDictionaries(){return this._dictionaryBatches.length}*recordBatches(){for(let t,n=-1,o=this.numRecordBatches;++n=0&&t=0&&t=0&&t=0&&tthis._closedPromiseResolve=t)}get closed(){return this._closedPromise}cancel(t){return K(this,void 0,void 0,function*(){yield this.return(t)})}write(t){this._ensureOpen()&&(this.resolvers.length<=0?this._values.push(t):this.resolvers.shift().resolve({done:!1,value:t}))}abort(t){this._closedPromiseResolve&&(this.resolvers.length<=0?this._error={error:t}:this.resolvers.shift().reject({done:!0,value:t}))}close(){if(this._closedPromiseResolve){const{resolvers:t}=this;for(;t.length>0;)t.shift().resolve(jt);this._closedPromiseResolve(),this._closedPromiseResolve=void 0}}[Symbol.asyncIterator](){return this}toDOMStream(t){return Je.toDOMStream(this._closedPromiseResolve||this._error?this:this._values,t)}toNodeStream(t){return Je.toNodeStream(this._closedPromiseResolve||this._error?this:this._values,t)}throw(t){return K(this,void 0,void 0,function*(){return yield this.abort(t),jt})}return(t){return K(this,void 0,void 0,function*(){return yield this.close(),jt})}read(t){return K(this,void 0,void 0,function*(){return(yield this.next(t,"read")).value})}peek(t){return K(this,void 0,void 0,function*(){return(yield this.next(t,"peek")).value})}next(...t){return this._values.length>0?Promise.resolve({done:!1,value:this._values.shift()}):this._error?Promise.reject({done:!0,value:this._error.error}):this._closedPromiseResolve?new Promise((n,o)=>{this.resolvers.push({resolve:n,reject:o})}):Promise.resolve(jt)}_ensureOpen(){if(this._closedPromiseResolve)return!0;throw new Error("AsyncQueue is closed")}}class _l extends pw{write(t){if((t=mt(t)).byteLength>0)return super.write(t)}toString(t=!1){return t?uc(this.toUint8Array(!0)):this.toUint8Array(!1).then(uc)}toUint8Array(t=!1){return t?Tn(this._values)[0]:K(this,void 0,void 0,function*(){var n,o;const u=[];let d=0;try{for(var f=qr(this),p;p=yield f.next(),!p.done;){const y=p.value;u.push(y),d+=y.byteLength}}catch(y){n={error:y}}finally{try{p&&!p.done&&(o=f.return)&&(yield o.call(f))}finally{if(n)throw n.error}}return Tn(u,d)[0]})}}class $l{constructor(t){t&&(this.source=new yw(Je.fromIterable(t)))}[Symbol.iterator](){return this}next(t){return this.source.next(t)}throw(t){return this.source.throw(t)}return(t){return this.source.return(t)}peek(t){return this.source.peek(t)}read(t){return this.source.read(t)}}class Hi{constructor(t){t instanceof Hi?this.source=t.source:t instanceof _l?this.source=new Yr(Je.fromAsyncIterable(t)):Cp(t)?this.source=new Yr(Je.fromNodeStream(t)):Fc(t)?this.source=new Yr(Je.fromDOMStream(t)):xp(t)?this.source=new Yr(Je.fromDOMStream(t.body)):Gs(t)?this.source=new Yr(Je.fromIterable(t)):br(t)?this.source=new Yr(Je.fromAsyncIterable(t)):Qi(t)&&(this.source=new Yr(Je.fromAsyncIterable(t)))}[Symbol.asyncIterator](){return this}next(t){return this.source.next(t)}throw(t){return this.source.throw(t)}return(t){return this.source.return(t)}get closed(){return this.source.closed}cancel(t){return this.source.cancel(t)}peek(t){return this.source.peek(t)}read(t){return this.source.read(t)}}class yw{constructor(t){this.source=t}cancel(t){this.return(t)}peek(t){return this.next(t,"peek").value}read(t){return 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sm).__init(this.bb.__vector(this.bb_pos+o)+t*16,this.bb):null}nodesLength(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.__vector_len(this.bb_pos+t):0}buffers(t,n){const o=this.bb.__offset(this.bb_pos,8);return o?(n||new im).__init(this.bb.__vector(this.bb_pos+o)+t*16,this.bb):null}buffersLength(){const t=this.bb.__offset(this.bb_pos,8);return t?this.bb.__vector_len(this.bb_pos+t):0}compression(t){const n=this.bb.__offset(this.bb_pos,10);return n?(t||new Ir).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}static startRecordBatch(t){t.startObject(4)}static addLength(t,n){t.addFieldInt64(0,n,t.createLong(0,0))}static addNodes(t,n){t.addFieldOffset(1,n,0)}static startNodesVector(t,n){t.startVector(16,n,8)}static addBuffers(t,n){t.addFieldOffset(2,n,0)}static startBuffersVector(t,n){t.startVector(16,n,8)}static addCompression(t,n){t.addFieldOffset(3,n,0)}static endRecordBatch(t){return t.endObject()}},Ai=class _c{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsDictionaryBatch(t,n){return(n||new _c).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsDictionaryBatch(t,n){return t.setPosition(t.position()+Et),(n||new _c).__init(t.readInt32(t.position())+t.position(),t)}id(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}data(t){const n=this.bb.__offset(this.bb_pos,6);return n?(t||new Yn).__init(this.bb.__indirect(this.bb_pos+n),this.bb):null}isDelta(){const t=this.bb.__offset(this.bb_pos,8);return t?!!this.bb.readInt8(this.bb_pos+t):!1}static startDictionaryBatch(t){t.startObject(3)}static addId(t,n){t.addFieldInt64(0,n,t.createLong(0,0))}static addData(t,n){t.addFieldOffset(1,n,0)}static addIsDelta(t,n){t.addFieldInt8(2,+n,0)}static endDictionaryBatch(t){return t.endObject()}};var Ql;(function(i){i[i.NONE=0]="NONE",i[i.Schema=1]="Schema",i[i.DictionaryBatch=2]="DictionaryBatch",i[i.RecordBatch=3]="RecordBatch",i[i.Tensor=4]="Tensor",i[i.SparseTensor=5]="SparseTensor"})(Ql||(Ql={}));let _r=class wn{constructor(){this.bb=null,this.bb_pos=0}__init(t,n){return this.bb_pos=t,this.bb=n,this}static getRootAsMessage(t,n){return(n||new wn).__init(t.readInt32(t.position())+t.position(),t)}static getSizePrefixedRootAsMessage(t,n){return t.setPosition(t.position()+Et),(n||new wn).__init(t.readInt32(t.position())+t.position(),t)}version(){const t=this.bb.__offset(this.bb_pos,4);return t?this.bb.readInt16(this.bb_pos+t):Vi.V1}headerType(){const t=this.bb.__offset(this.bb_pos,6);return t?this.bb.readUint8(this.bb_pos+t):Ql.NONE}header(t){const n=this.bb.__offset(this.bb_pos,8);return n?this.bb.__union(t,this.bb_pos+n):null}bodyLength(){const t=this.bb.__offset(this.bb_pos,10);return t?this.bb.readInt64(this.bb_pos+t):this.bb.createLong(0,0)}customMetadata(t,n){const o=this.bb.__offset(this.bb_pos,12);return o?(n||new qt).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+o)+t*4),this.bb):null}customMetadataLength(){const t=this.bb.__offset(this.bb_pos,12);return t?this.bb.__vector_len(this.bb_pos+t):0}static startMessage(t){t.startObject(5)}static addVersion(t,n){t.addFieldInt16(0,n,Vi.V1)}static addHeaderType(t,n){t.addFieldInt8(1,n,Ql.NONE)}static addHeader(t,n){t.addFieldOffset(2,n,0)}static addBodyLength(t,n){t.addFieldInt64(3,n,t.createLong(0,0))}static addCustomMetadata(t,n){t.addFieldOffset(4,n,0)}static createCustomMetadataVector(t,n){t.startVector(4,n.length,4);for(let o=n.length-1;o>=0;o--)t.addOffset(n[o]);return t.endVector()}static startCustomMetadataVector(t,n){t.startVector(4,n,4)}static endMessage(t){return t.endObject()}static finishMessageBuffer(t,n){t.finish(n)}static finishSizePrefixedMessageBuffer(t,n){t.finish(n,void 0,!0)}static createMessage(t,n,o,u,d,f){return wn.startMessage(t),wn.addVersion(t,n),wn.addHeaderType(t,o),wn.addHeader(t,u),wn.addBodyLength(t,d),wn.addCustomMetadata(t,f),wn.endMessage(t)}};var Ew=Jn;class kw extends dt{visit(t,n){return t==null||n==null?void 0:super.visit(t,n)}visitNull(t,n){return Gr.startNull(n),Gr.endNull(n)}visitInt(t,n){return Pe.startInt(n),Pe.addBitWidth(n,t.bitWidth),Pe.addIsSigned(n,t.isSigned),Pe.endInt(n)}visitFloat(t,n){return En.startFloatingPoint(n),En.addPrecision(n,t.precision),En.endFloatingPoint(n)}visitBinary(t,n){return Qr.startBinary(n),Qr.endBinary(n)}visitBool(t,n){return Kr.startBool(n),Kr.endBool(n)}visitUtf8(t,n){return Zr.startUtf8(n),Zr.endUtf8(n)}visitDecimal(t,n){return be.startDecimal(n),be.addScale(n,t.scale),be.addPrecision(n,t.precision),be.addBitWidth(n,t.bitWidth),be.endDecimal(n)}visitDate(t,n){return gl.startDate(n),gl.addUnit(n,t.unit),gl.endDate(n)}visitTime(t,n){return Ge.startTime(n),Ge.addUnit(n,t.unit),Ge.addBitWidth(n,t.bitWidth),Ge.endTime(n)}visitTimestamp(t,n){const o=t.timezone&&n.createString(t.timezone)||void 0;return Xe.startTimestamp(n),Xe.addUnit(n,t.unit),o!==void 0&&Xe.addTimezone(n,o),Xe.endTimestamp(n)}visitInterval(t,n){return kn.startInterval(n),kn.addUnit(n,t.unit),kn.endInterval(n)}visitList(t,n){return Jr.startList(n),Jr.endList(n)}visitStruct(t,n){return Xr.startStruct_(n),Xr.endStruct_(n)}visitUnion(t,n){Be.startTypeIdsVector(n,t.typeIds.length);const o=Be.createTypeIdsVector(n,t.typeIds);return Be.startUnion(n),Be.addMode(n,t.mode),Be.addTypeIds(n,o),Be.endUnion(n)}visitDictionary(t,n){const o=this.visit(t.indices,n);return Kn.startDictionaryEncoding(n),Kn.addId(n,new Ew(t.id,0)),Kn.addIsOrdered(n,t.isOrdered),o!==void 0&&Kn.addIndexType(n,o),Kn.endDictionaryEncoding(n)}visitFixedSizeBinary(t,n){return On.startFixedSizeBinary(n),On.addByteWidth(n,t.byteWidth),On.endFixedSizeBinary(n)}visitFixedSizeList(t,n){return Fn.startFixedSizeList(n),Fn.addListSize(n,t.listSize),Fn.endFixedSizeList(n)}visitMap(t,n){return vl.startMap(n),vl.addKeysSorted(n,t.keysSorted),vl.endMap(n)}}const lc=new kw;function Nw(i,t=new Map){return new St(Tw(i,t),Sl(i.customMetadata),t)}function om(i){return new je(i.count,lm(i.columns),am(i.columns))}function Dw(i){return new xn(om(i.data),i.id,i.isDelta)}function Tw(i,t){return(i.fields||[]).filter(Boolean).map(n=>Ct.fromJSON(n,t))}function _p(i,t){return(i.children||[]).filter(Boolean).map(n=>Ct.fromJSON(n,t))}function lm(i){return(i||[]).reduce((t,n)=>[...t,new ni(n.count,Aw(n.VALIDITY)),...lm(n.children)],[])}function am(i,t=[]){for(let n=-1,o=(i||[]).length;++nt+ +(n===0),0)}function xw(i,t){let n,o,u,d,f,p;return!t||!(d=i.dictionary)?(f=Ip(i,_p(i,t)),u=new Ct(i.name,f,i.nullable,Sl(i.customMetadata))):t.has(n=d.id)?(o=(o=d.indexType)?Sp(o):new $s,p=new zi(t.get(n),o,n,d.isOrdered),u=new Ct(i.name,p,i.nullable,Sl(i.customMetadata))):(o=(o=d.indexType)?Sp(o):new $s,t.set(n,f=Ip(i,_p(i,t))),p=new zi(f,o,n,d.isOrdered),u=new Ct(i.name,p,i.nullable,Sl(i.customMetadata))),u||null}function Sl(i){return new Map(Object.entries(i||{}))}function Sp(i){return new Fr(i.isSigned,i.bitWidth)}function Ip(i,t){const n=i.type.name;switch(n){case"NONE":return new Or;case"null":return new Or;case"binary":return new bl;case"utf8":return new Bl;case"bool":return new Ol;case"list":return new Dl((t||[])[0]);case"struct":return new he(t||[]);case"struct_":return new he(t||[])}switch(n){case"int":{const o=i.type;return new Fr(o.isSigned,o.bitWidth)}case"floatingpoint":{const o=i.type;return new Ws(Fe[o.precision])}case"decimal":{const o=i.type;return new Fl(o.scale,o.precision,o.bitWidth)}case"date":{const o=i.type;return new El(Xn[o.unit])}case"time":{const o=i.type;return new Hs(gt[o.unit],o.bitWidth)}case"timestamp":{const o=i.type;return new kl(gt[o.unit],o.timezone)}case"interval":{const o=i.type;return new Nl(Br[o.unit])}case"union":{const o=i.type;return new Tl(ze[o.mode],o.typeIds||[],t||[])}case"fixedsizebinary":{const o=i.type;return new Al(o.byteWidth)}case"fixedsizelist":{const o=i.type;return new xl(o.listSize,(t||[])[0])}case"map":{const o=i.type;return new Cl((t||[])[0],o.keysSorted)}}throw new Error(`Unrecognized type: "${n}"`)}var ei=Jn,Cw=Xy,Mw=ji;class pe{constructor(t,n,o,u){this._version=n,this._headerType=o,this.body=new Uint8Array(0),u&&(this._createHeader=()=>u),this._bodyLength=typeof t=="number"?t:t.low}static fromJSON(t,n){const o=new pe(0,Ue.V4,n);return o._createHeader=Lw(t,n),o}static decode(t){t=new Mw(mt(t));const n=_r.getRootAsMessage(t),o=n.bodyLength(),u=n.version(),d=n.headerType(),f=new pe(o,u,d);return f._createHeader=Rw(n,d),f}static encode(t){const n=new Cw;let o=-1;return t.isSchema()?o=St.encode(n,t.header()):t.isRecordBatch()?o=je.encode(n,t.header()):t.isDictionaryBatch()&&(o=xn.encode(n,t.header())),_r.startMessage(n),_r.addVersion(n,Ue.V4),_r.addHeader(n,o),_r.addHeaderType(n,t.headerType),_r.addBodyLength(n,new ei(t.bodyLength,0)),_r.finishMessageBuffer(n,_r.endMessage(n)),n.asUint8Array()}static from(t,n=0){if(t instanceof St)return new pe(0,Ue.V4,wt.Schema,t);if(t instanceof je)return new pe(n,Ue.V4,wt.RecordBatch,t);if(t instanceof xn)return new pe(n,Ue.V4,wt.DictionaryBatch,t);throw new Error(`Unrecognized Message header: ${t}`)}get type(){return this.headerType}get version(){return this._version}get headerType(){return this._headerType}get bodyLength(){return this._bodyLength}header(){return this._createHeader()}isSchema(){return this.headerType===wt.Schema}isRecordBatch(){return this.headerType===wt.RecordBatch}isDictionaryBatch(){return this.headerType===wt.DictionaryBatch}}class je{constructor(t,n,o){this._nodes=n,this._buffers=o,this._length=typeof t=="number"?t:t.low}get nodes(){return this._nodes}get length(){return this._length}get buffers(){return this._buffers}}class xn{constructor(t,n,o=!1){this._data=t,this._isDelta=o,this._id=typeof n=="number"?n:n.low}get id(){return this._id}get data(){return this._data}get isDelta(){return this._isDelta}get length(){return this.data.length}get nodes(){return this.data.nodes}get buffers(){return this.data.buffers}}class Dn{constructor(t,n){this.offset=typeof t=="number"?t:t.low,this.length=typeof n=="number"?n:n.low}}class ni{constructor(t,n){this.length=typeof t=="number"?t:t.low,this.nullCount=typeof n=="number"?n:n.low}}function Lw(i,t){return()=>{switch(t){case wt.Schema:return St.fromJSON(i);case wt.RecordBatch:return je.fromJSON(i);case wt.DictionaryBatch:return xn.fromJSON(i)}throw new Error(`Unrecognized Message type: { name: ${wt[t]}, type: ${t} }`)}}function Rw(i,t){return()=>{switch(t){case wt.Schema:return St.decode(i.header(new _n));case wt.RecordBatch:return je.decode(i.header(new Yn),i.version());case wt.DictionaryBatch:return xn.decode(i.header(new Ai),i.version())}throw new Error(`Unrecognized Message type: { name: ${wt[t]}, type: ${t} }`)}}Ct.encode=Kw;Ct.decode=Yw;Ct.fromJSON=xw;St.encode=Qw;St.decode=Pw;St.fromJSON=Nw;je.encode=Jw;je.decode=Uw;je.fromJSON=om;xn.encode=Gw;xn.decode=zw;xn.fromJSON=Dw;ni.encode=Xw;ni.decode=Vw;Dn.encode=Zw;Dn.decode=jw;function Pw(i,t=new Map){const n=Hw(i,t);return new St(n,Il(i),t)}function Uw(i,t=Ue.V4){if(i.compression()!==null)throw new Error("Record batch compression not implemented");return new je(i.length(),$w(i),Ww(i,t))}function zw(i,t=Ue.V4){return new xn(je.decode(i.data(),t),i.id(),i.isDelta())}function jw(i){return new Dn(i.offset(),i.length())}function Vw(i){return new ni(i.length(),i.nullCount())}function $w(i){const t=[];for(let n,o=-1,u=-1,d=i.nodesLength();++oCt.encode(i,d));_n.startFieldsVector(i,n.length);const o=_n.createFieldsVector(i,n),u=t.metadata&&t.metadata.size>0?_n.createCustomMetadataVector(i,[...t.metadata].map(([d,f])=>{const p=i.createString(`${d}`),y=i.createString(`${f}`);return qt.startKeyValue(i),qt.addKey(i,p),qt.addValue(i,y),qt.endKeyValue(i)})):-1;return _n.startSchema(i),_n.addFields(i,o),_n.addEndianness(i,qw?$i.Little:$i.Big),u!==-1&&_n.addCustomMetadata(i,u),_n.endSchema(i)}function Kw(i,t){let n=-1,o=-1,u=-1;const d=t.type;let f=t.typeId;J.isDictionary(d)?(f=d.dictionary.typeId,u=lc.visit(d,i),o=lc.visit(d.dictionary,i)):o=lc.visit(d,i);const p=(d.children||[]).map(O=>Ct.encode(i,O)),y=Ke.createChildrenVector(i,p),w=t.metadata&&t.metadata.size>0?Ke.createCustomMetadataVector(i,[...t.metadata].map(([O,F])=>{const A=i.createString(`${O}`),x=i.createString(`${F}`);return qt.startKeyValue(i),qt.addKey(i,A),qt.addValue(i,x),qt.endKeyValue(i)})):-1;return t.name&&(n=i.createString(t.name)),Ke.startField(i),Ke.addType(i,o),Ke.addTypeType(i,f),Ke.addChildren(i,y),Ke.addNullable(i,!!t.nullable),n!==-1&&Ke.addName(i,n),u!==-1&&Ke.addDictionary(i,u),w!==-1&&Ke.addCustomMetadata(i,w),Ke.endField(i)}function Jw(i,t){const n=t.nodes||[],o=t.buffers||[];Yn.startNodesVector(i,n.length);for(const f of n.slice().reverse())ni.encode(i,f);const u=i.endVector();Yn.startBuffersVector(i,o.length);for(const f of o.slice().reverse())Dn.encode(i,f);const d=i.endVector();return Yn.startRecordBatch(i),Yn.addLength(i,new ei(t.length,0)),Yn.addNodes(i,u),Yn.addBuffers(i,d),Yn.endRecordBatch(i)}function Gw(i,t){const n=je.encode(i,t.data);return Ai.startDictionaryBatch(i),Ai.addId(i,new ei(t.id,0)),Ai.addIsDelta(i,t.isDelta),Ai.addData(i,n),Ai.endDictionaryBatch(i)}function Xw(i,t){return sm.createFieldNode(i,new ei(t.length,0),new ei(t.nullCount,0))}function Zw(i,t){return im.createBuffer(i,new ei(t.offset,0),new ei(t.length,0))}const qw=(()=>{const i=new ArrayBuffer(2);return new DataView(i).setInt16(0,256,!0),new Int16Array(i)[0]===256})(),Yc=i=>`Expected ${wt[i]} Message in stream, but was null or length 0.`,Qc=i=>`Header pointer of flatbuffer-encoded ${wt[i]} Message is null or length 0.`,um=(i,t)=>`Expected to read ${i} metadata bytes, but only read ${t}.`,cm=(i,t)=>`Expected to read ${i} bytes for message body, but only read ${t}.`;class dm{constructor(t){this.source=t instanceof $l?t:new $l(t)}[Symbol.iterator](){return this}next(){let t;return(t=this.readMetadataLength()).done||t.value===-1&&(t=this.readMetadataLength()).done||(t=this.readMetadata(t.value)).done?jt:t}throw(t){return this.source.throw(t)}return(t){return this.source.return(t)}readMessage(t){let n;if((n=this.next()).done)return null;if(t!=null&&n.value.headerType!==t)throw new Error(Yc(t));return n.value}readMessageBody(t){if(t<=0)return new Uint8Array(0);const n=mt(this.source.read(t));if(n.byteLength[...u,...d.VALIDITY&&[d.VALIDITY]||[],...d.TYPE&&[d.TYPE]||[],...d.OFFSET&&[d.OFFSET]||[],...d.DATA&&[d.DATA]||[],...n(d.children)],[])}}readMessage(t){let n;if((n=this.next()).done)return null;if(t!=null&&n.value.headerType!==t)throw new Error(Yc(t));return n.value}readSchema(){const t=wt.Schema,n=this.readMessage(t),o=n?.header();if(!n||!o)throw new Error(Qc(t));return o}}const ea=4,Sc="ARROW1",Qs=new Uint8Array(Sc.length);for(let i=0;ithis):this}readRecordBatch(t){return this._impl.isFile()?this._impl.readRecordBatch(t):null}[Symbol.iterator](){return this._impl[Symbol.iterator]()}[Symbol.asyncIterator](){return this._impl[Symbol.asyncIterator]()}toDOMStream(){return Je.toDOMStream(this.isSync()?{[Symbol.iterator]:()=>this}:{[Symbol.asyncIterator]:()=>this})}toNodeStream(){return Je.toNodeStream(this.isSync()?{[Symbol.iterator]:()=>this}:{[Symbol.asyncIterator]:()=>this},{objectMode:!0})}static throughNode(t){throw new Error('"throughNode" not available in this environment')}static throughDOM(t,n){throw new Error('"throughDOM" not available in this environment')}static from(t){return t instanceof Gn?t:cc(t)?o_(t):Ap(t)?u_(t):br(t)?K(this,void 0,void 0,function*(){return yield Gn.from(yield t)}):xp(t)||Fc(t)||Cp(t)||Qi(t)?a_(new Hi(t)):l_(new $l(t))}static readAll(t){return t instanceof Gn?t.isSync()?Fp(t):Ep(t):cc(t)||ArrayBuffer.isView(t)||Gs(t)||Tp(t)?Fp(t):Ep(t)}}class Kl extends Gn{constructor(t){super(t),this._impl=t}readAll(){return[...this]}[Symbol.iterator](){return this._impl[Symbol.iterator]()}[Symbol.asyncIterator](){return Nn(this,arguments,function*(){yield it(yield*ml(qr(this[Symbol.iterator]())))})}}class Jl extends Gn{constructor(t){super(t),this._impl=t}readAll(){var t,n;return K(this,void 0,void 0,function*(){const o=new Array;try{for(var u=qr(this),d;d=yield u.next(),!d.done;){const f=d.value;o.push(f)}}catch(f){t={error:f}}finally{try{d&&!d.done&&(n=u.return)&&(yield n.call(u))}finally{if(t)throw t.error}}return o})}[Symbol.iterator](){throw new Error("AsyncRecordBatchStreamReader is not Iterable")}[Symbol.asyncIterator](){return this._impl[Symbol.asyncIterator]()}}class hm extends Kl{constructor(t){super(t),this._impl=t}}class r_ extends Jl{constructor(t){super(t),this._impl=t}}class pm{constructor(t=new Map){this.closed=!1,this.autoDestroy=!0,this._dictionaryIndex=0,this._recordBatchIndex=0,this.dictionaries=t}get numDictionaries(){return this._dictionaryIndex}get numRecordBatches(){return this._recordBatchIndex}isSync(){return!1}isAsync(){return!1}isFile(){return!1}isStream(){return!1}reset(t){return this._dictionaryIndex=0,this._recordBatchIndex=0,this.schema=t,this.dictionaries=new Map,this}_loadRecordBatch(t,n){const o=this._loadVectors(t,n,this.schema.fields),u=ct({type:new he(this.schema.fields),length:t.length,children:o});return new Oe(this.schema,u)}_loadDictionaryBatch(t,n){const{id:o,isDelta:u}=t,{dictionaries:d,schema:f}=this,p=d.get(o);if(u||!p){const y=f.dictionaries.get(o),w=this._loadVectors(t.data,n,[y]);return(p&&u?p.concat(new _t(w)):new _t(w)).memoize()}return p.memoize()}_loadVectors(t,n,o){return new tm(n,t.nodes,t.buffers,this.dictionaries).visitMany(o)}}class Gl extends pm{constructor(t,n){super(n),this._reader=cc(t)?new e_(this._handle=t):new dm(this._handle=t)}isSync(){return!0}isStream(){return!0}[Symbol.iterator](){return this}cancel(){!this.closed&&(this.closed=!0)&&(this.reset()._reader.return(),this._reader=null,this.dictionaries=null)}open(t){return this.closed||(this.autoDestroy=mm(this,t),this.schema||(this.schema=this._reader.readSchema())||this.cancel()),this}throw(t){return!this.closed&&this.autoDestroy&&(this.closed=!0)?this.reset()._reader.throw(t):jt}return(t){return!this.closed&&this.autoDestroy&&(this.closed=!0)?this.reset()._reader.return(t):jt}next(){if(this.closed)return jt;let t;const{_reader:n}=this;for(;t=this._readNextMessageAndValidate();)if(t.isSchema())this.reset(t.header());else if(t.isRecordBatch()){this._recordBatchIndex++;const o=t.header(),u=n.readMessageBody(t.bodyLength);return{done:!1,value:this._loadRecordBatch(o,u)}}else if(t.isDictionaryBatch()){this._dictionaryIndex++;const o=t.header(),u=n.readMessageBody(t.bodyLength),d=this._loadDictionaryBatch(o,u);this.dictionaries.set(o.id,d)}return this.schema&&this._recordBatchIndex===0?(this._recordBatchIndex++,{done:!1,value:new Hc(this.schema)}):this.return()}_readNextMessageAndValidate(t){return this._reader.readMessage(t)}}class Xl extends pm{constructor(t,n){super(n),this._reader=new t_(this._handle=t)}isAsync(){return!0}isStream(){return!0}[Symbol.asyncIterator](){return this}cancel(){return K(this,void 0,void 0,function*(){!this.closed&&(this.closed=!0)&&(yield this.reset()._reader.return(),this._reader=null,this.dictionaries=null)})}open(t){return K(this,void 0,void 0,function*(){return this.closed||(this.autoDestroy=mm(this,t),this.schema||(this.schema=yield this._reader.readSchema())||(yield this.cancel())),this})}throw(t){return K(this,void 0,void 0,function*(){return!this.closed&&this.autoDestroy&&(this.closed=!0)?yield this.reset()._reader.throw(t):jt})}return(t){return K(this,void 0,void 0,function*(){return!this.closed&&this.autoDestroy&&(this.closed=!0)?yield this.reset()._reader.return(t):jt})}next(){return K(this,void 0,void 0,function*(){if(this.closed)return jt;let t;const{_reader:n}=this;for(;t=yield this._readNextMessageAndValidate();)if(t.isSchema())yield this.reset(t.header());else if(t.isRecordBatch()){this._recordBatchIndex++;const o=t.header(),u=yield n.readMessageBody(t.bodyLength);return{done:!1,value:this._loadRecordBatch(o,u)}}else if(t.isDictionaryBatch()){this._dictionaryIndex++;const o=t.header(),u=yield n.readMessageBody(t.bodyLength),d=this._loadDictionaryBatch(o,u);this.dictionaries.set(o.id,d)}return this.schema&&this._recordBatchIndex===0?(this._recordBatchIndex++,{done:!1,value:new Hc(this.schema)}):yield this.return()})}_readNextMessageAndValidate(t){return K(this,void 0,void 0,function*(){return yield this._reader.readMessage(t)})}}class ym extends Gl{constructor(t,n){super(t instanceof vp?t:new vp(t),n)}get footer(){return this._footer}get numDictionaries(){return this._footer?this._footer.numDictionaries:0}get numRecordBatches(){return this._footer?this._footer.numRecordBatches:0}isSync(){return!0}isFile(){return!0}open(t){if(!this.closed&&!this._footer){this.schema=(this._footer=this._readFooter()).schema;for(const n of this._footer.dictionaryBatches())n&&this._readDictionaryBatch(this._dictionaryIndex++)}return super.open(t)}readRecordBatch(t){var n;if(this.closed)return null;this._footer||this.open();const o=(n=this._footer)===null||n===void 0?void 0:n.getRecordBatch(t);if(o&&this._handle.seek(o.offset)){const u=this._reader.readMessage(wt.RecordBatch);if(u?.isRecordBatch()){const d=u.header(),f=this._reader.readMessageBody(u.bodyLength);return this._loadRecordBatch(d,f)}}return null}_readDictionaryBatch(t){var n;const o=(n=this._footer)===null||n===void 0?void 0:n.getDictionaryBatch(t);if(o&&this._handle.seek(o.offset)){const u=this._reader.readMessage(wt.DictionaryBatch);if(u?.isDictionaryBatch()){const d=u.header(),f=this._reader.readMessageBody(u.bodyLength),p=this._loadDictionaryBatch(d,f);this.dictionaries.set(d.id,p)}}}_readFooter(){const{_handle:t}=this,n=t.size-fm,o=t.readInt32(n),u=t.readAt(n-o,o);return Ys.decode(u)}_readNextMessageAndValidate(t){var n;if(this._footer||this.open(),this._footer&&this._recordBatchIndexsuper.open}});return K(this,void 0,void 0,function*(){if(!this.closed&&!this._footer){this.schema=(this._footer=yield this._readFooter()).schema;for(const o of this._footer.dictionaryBatches())o&&(yield this._readDictionaryBatch(this._dictionaryIndex++))}return yield n.open.call(this,t)})}readRecordBatch(t){var n;return K(this,void 0,void 0,function*(){if(this.closed)return null;this._footer||(yield this.open());const o=(n=this._footer)===null||n===void 0?void 0:n.getRecordBatch(t);if(o&&(yield this._handle.seek(o.offset))){const u=yield this._reader.readMessage(wt.RecordBatch);if(u?.isRecordBatch()){const d=u.header(),f=yield this._reader.readMessageBody(u.bodyLength);return this._loadRecordBatch(d,f)}}return null})}_readDictionaryBatch(t){var n;return K(this,void 0,void 0,function*(){const o=(n=this._footer)===null||n===void 0?void 0:n.getDictionaryBatch(t);if(o&&(yield this._handle.seek(o.offset))){const u=yield this._reader.readMessage(wt.DictionaryBatch);if(u?.isDictionaryBatch()){const d=u.header(),f=yield this._reader.readMessageBody(u.bodyLength),p=this._loadDictionaryBatch(d,f);this.dictionaries.set(d.id,p)}}})}_readFooter(){return K(this,void 0,void 0,function*(){const{_handle:t}=this;t._pending&&(yield t._pending);const n=t.size-fm,o=yield t.readInt32(n),u=yield t.readAt(n-o,o);return Ys.decode(u)})}_readNextMessageAndValidate(t){return K(this,void 0,void 0,function*(){if(this._footer||(yield this.open()),this._footer&&this._recordBatchIndex=4?Kc(t)?new hm(new ym(i.read())):new Kl(new Gl(i)):new Kl(new Gl(function*(){}()))}function a_(i){return K(this,void 0,void 0,function*(){const t=yield i.peek(to+7&-8);return t&&t.byteLength>=4?Kc(t)?new hm(new ym(yield i.read())):new Jl(new Xl(i)):new Jl(new Xl(function(){return Nn(this,arguments,function*(){})}()))})}function u_(i){return K(this,void 0,void 0,function*(){const{size:t}=yield i.stat(),n=new Wl(i,t);return t>=n_&&Kc(yield n.readAt(0,to+7&-8))?new r_(new i_(n)):new Jl(new Xl(n))})}class Kt extends dt{constructor(){super(),this._byteLength=0,this._nodes=[],this._buffers=[],this._bufferRegions=[]}static assemble(...t){const n=u=>u.flatMap(d=>Array.isArray(d)?n(d):d instanceof Oe?d.data.children:d.data),o=new Kt;return o.visitMany(n(t)),o}visit(t){if(t instanceof _t)return this.visitMany(t.data),this;const{type:n}=t;if(!J.isDictionary(n)){const{length:o,nullCount:u}=t;if(o>2147483647)throw new RangeError("Cannot write arrays larger than 2^31 - 1 in length");J.isNull(n)||cn.call(this,u<=0?new Uint8Array(0):Mc(t.offset,o,t.nullBitmap)),this.nodes.push(new ni(o,u))}return super.visit(t)}visitNull(t){return this}visitDictionary(t){return this.visit(t.clone(t.type.indices))}get nodes(){return this._nodes}get buffers(){return this._buffers}get byteLength(){return this._byteLength}get bufferRegions(){return this._bufferRegions}}function cn(i){const t=i.byteLength+7&-8;return this.buffers.push(i),this.bufferRegions.push(new Dn(this._byteLength,t)),this._byteLength+=t,this}function c_(i){const{type:t,length:n,typeIds:o,valueOffsets:u}=i;if(cn.call(this,o),t.mode===ze.Sparse)return Ic.call(this,i);if(t.mode===ze.Dense){if(i.offset<=0)return cn.call(this,u),Ic.call(this,i);{const d=o.reduce((O,F)=>Math.max(O,F),o[0]),f=new Int32Array(d+1),p=new Int32Array(d+1).fill(-1),y=new Int32Array(n),w=kc(-u[0],n,u);for(let O,F,A=-1;++A=i.length?cn.call(this,new Uint8Array(0)):(t=i.values)instanceof Uint8Array?cn.call(this,Mc(i.offset,i.length,t)):cn.call(this,Ml(i.values))}function Tr(i){return cn.call(this,i.values.subarray(0,i.length*i.stride))}function gm(i){const{length:t,values:n,valueOffsets:o}=i,u=o[0],d=o[t],f=Math.min(d-u,n.byteLength-u);return cn.call(this,kc(-o[0],t,o)),cn.call(this,n.subarray(u,u+f)),this}function Jc(i){const{length:t,valueOffsets:n}=i;return n&&cn.call(this,kc(n[0],t,n)),this.visit(i.children[0])}function Ic(i){return this.visitMany(i.type.children.map((t,n)=>i.children[n]).filter(Boolean))[0]}Kt.prototype.visitBool=d_;Kt.prototype.visitInt=Tr;Kt.prototype.visitFloat=Tr;Kt.prototype.visitUtf8=gm;Kt.prototype.visitBinary=gm;Kt.prototype.visitFixedSizeBinary=Tr;Kt.prototype.visitDate=Tr;Kt.prototype.visitTimestamp=Tr;Kt.prototype.visitTime=Tr;Kt.prototype.visitDecimal=Tr;Kt.prototype.visitList=Jc;Kt.prototype.visitStruct=Ic;Kt.prototype.visitUnion=c_;Kt.prototype.visitInterval=Tr;Kt.prototype.visitFixedSizeList=Jc;Kt.prototype.visitMap=Jc;class vm extends zc{constructor(t){super(),this._position=0,this._started=!1,this._sink=new _l,this._schema=null,this._dictionaryBlocks=[],this._recordBatchBlocks=[],this._dictionaryDeltaOffsets=new Map,Ee(t)||(t={autoDestroy:!0,writeLegacyIpcFormat:!1}),this._autoDestroy=typeof t.autoDestroy=="boolean"?t.autoDestroy:!0,this._writeLegacyIpcFormat=typeof t.writeLegacyIpcFormat=="boolean"?t.writeLegacyIpcFormat:!1}static throughNode(t){throw new Error('"throughNode" not available in this environment')}static throughDOM(t,n){throw new Error('"throughDOM" not available in this environment')}toString(t=!1){return this._sink.toString(t)}toUint8Array(t=!1){return this._sink.toUint8Array(t)}writeAll(t){return br(t)?t.then(n=>this.writeAll(n)):Qi(t)?qc(this,t):Zc(this,t)}get closed(){return this._sink.closed}[Symbol.asyncIterator](){return this._sink[Symbol.asyncIterator]()}toDOMStream(t){return this._sink.toDOMStream(t)}toNodeStream(t){return this._sink.toNodeStream(t)}close(){return this.reset()._sink.close()}abort(t){return this.reset()._sink.abort(t)}finish(){return this._autoDestroy?this.close():this.reset(this._sink,this._schema),this}reset(t=this._sink,n=null){return t===this._sink||t instanceof _l?this._sink=t:(this._sink=new _l,t&&Av(t)?this.toDOMStream({type:"bytes"}).pipeTo(t):t&&xv(t)&&this.toNodeStream({objectMode:!1}).pipe(t)),this._started&&this._schema&&this._writeFooter(this._schema),this._started=!1,this._dictionaryBlocks=[],this._recordBatchBlocks=[],this._dictionaryDeltaOffsets=new Map,(!n||!vc(n,this._schema))&&(n==null?(this._position=0,this._schema=null):(this._started=!0,this._schema=n,this._writeSchema(n))),this}write(t){let n=null;if(this._sink){if(t==null)return this.finish()&&void 0;if(t instanceof fe&&!(n=t.schema))return this.finish()&&void 0;if(t instanceof Oe&&!(n=t.schema))return this.finish()&&void 0}else throw new Error("RecordBatchWriter is closed");if(n&&!vc(n,this._schema)){if(this._started&&this._autoDestroy)return this.close();this.reset(this._sink,n)}t instanceof Oe?t instanceof Hc||this._writeRecordBatch(t):t instanceof fe?this.writeAll(t.batches):Gs(t)&&this.writeAll(t)}_writeMessage(t,n=8){const o=n-1,u=pe.encode(t),d=u.byteLength,f=this._writeLegacyIpcFormat?4:8,p=d+f+o&~o,y=p-d-f;return t.headerType===wt.RecordBatch?this._recordBatchBlocks.push(new Er(p,t.bodyLength,this._position)):t.headerType===wt.DictionaryBatch&&this._dictionaryBlocks.push(new Er(p,t.bodyLength,this._position)),this._writeLegacyIpcFormat||this._write(Int32Array.of(-1)),this._write(Int32Array.of(p-f)),d>0&&this._write(u),this._writePadding(y)}_write(t){if(this._started){const n=mt(t);n&&n.byteLength>0&&(this._sink.write(n),this._position+=n.byteLength)}return this}_writeSchema(t){return this._writeMessage(pe.from(t))}_writeFooter(t){return this._writeLegacyIpcFormat?this._write(Int32Array.of(0)):this._write(Int32Array.of(-1,0))}_writeMagic(){return this._write(Qs)}_writePadding(t){return t>0?this._write(new Uint8Array(t)):this}_writeRecordBatch(t){const{byteLength:n,nodes:o,bufferRegions:u,buffers:d}=Kt.assemble(t),f=new je(t.numRows,o,u),p=pe.from(f,n);return this._writeDictionaries(t)._writeMessage(p)._writeBodyBuffers(d)}_writeDictionaryBatch(t,n,o=!1){this._dictionaryDeltaOffsets.set(n,t.length+(this._dictionaryDeltaOffsets.get(n)||0));const{byteLength:u,nodes:d,bufferRegions:f,buffers:p}=Kt.assemble(new _t([t])),y=new je(t.length,d,f),w=new xn(y,n,o),O=pe.from(w,u);return this._writeMessage(O)._writeBodyBuffers(p)}_writeBodyBuffers(t){let n,o,u;for(let d=-1,f=t.length;++d0&&(this._write(n),(u=(o+7&-8)-o)>0&&this._writePadding(u));return this}_writeDictionaries(t){for(let[n,o]of t.dictionaries){let u=this._dictionaryDeltaOffsets.get(n)||0;if(u===0||(o=o?.slice(u)).length>0)for(const d of o.data)this._writeDictionaryBatch(d,n,u>0),u+=d.length}return this}}class Gc extends vm{static writeAll(t,n){const o=new Gc(n);return br(t)?t.then(u=>o.writeAll(u)):Qi(t)?qc(o,t):Zc(o,t)}}class Xc extends vm{static writeAll(t){const n=new Xc;return br(t)?t.then(o=>n.writeAll(o)):Qi(t)?qc(n,t):Zc(n,t)}constructor(){super(),this._autoDestroy=!0}_writeSchema(t){return this._writeMagic()._writePadding(2)}_writeFooter(t){const n=Ys.encode(new Ys(t,Ue.V4,this._recordBatchBlocks,this._dictionaryBlocks));return super._writeFooter(t)._write(n)._write(Int32Array.of(n.byteLength))._writeMagic()}}function Zc(i,t){let n=t;t instanceof fe&&(n=t.batches,i.reset(void 0,t.schema));for(const o of n)i.write(o);return i.finish()}function qc(i,t){var n,o,u,d;return K(this,void 0,void 0,function*(){try{for(n=qr(t);o=yield n.next(),!o.done;){const f=o.value;i.write(f)}}catch(f){u={error:f}}finally{try{o&&!o.done&&(d=n.return)&&(yield d.call(n))}finally{if(u)throw u.error}}return i.finish()})}function Rs(i){const t=Gn.from(i);return br(t)?t.then(n=>Rs(n)):t.isAsync()?t.readAll().then(n=>new fe(n)):new fe(t.readAll())}function ac(i,t="stream"){return(t==="stream"?Gc:Xc).writeAll(i).toUint8Array(!0)}var kp=function(){function i(t,n,o,u){var d=this;this.getCell=function(f,p){var y=f=d.headerRows&&p=d.headerColumns;if(y){var F=["blank"];return p>0&&F.push("level"+f),{type:"blank",classNames:F.join(" "),content:""}}else if(O){var A=p-d.headerColumns,F=["col_heading","level"+f,"col"+A];return{type:"columns",classNames:F.join(" "),content:d.getContent(d.columnsTable,A,f)}}else if(w){var x=f-d.headerRows,F=["row_heading","level"+p,"row"+x];return{type:"index",id:"T_".concat(d.uuid,"level").concat(p,"_row").concat(x),classNames:F.join(" "),content:d.getContent(d.indexTable,x,p)}}else{var x=f-d.headerRows,A=p-d.headerColumns,F=["data","row"+x,"col"+A],j=d.styler?d.getContent(d.styler.displayValuesTable,x,A):d.getContent(d.dataTable,x,A);return{type:"data",id:"T_".concat(d.uuid,"row").concat(x,"_col").concat(A),classNames:F.join(" "),content:j}}},this.getContent=function(f,p,y){var w=f.getChildAt(y);if(w===null)return"";var O=d.getColumnTypeId(f,y);switch(O){case _.Timestamp:return d.nanosToDate(w.get(p));default:return 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w(),t.current&&(i.pdfUrl?t.current.setPdfUrl(i.pdfUrl):i.pdfData&&t.current.setPdfData(i.pdfData),t.current.setChunks(f),t.current.setQuestions(p),i.selectedQuestionId&&t.current.setSelectedQuestionId(i.selectedQuestionId),t.current.setShowEvidenceOnly(i.showEvidenceOnly||!1),y()),()=>{o.current&&clearTimeout(o.current),d.current&&(d.current.disconnect(),d.current=null),t.current&&(t.current.remove(),t.current=null)}},[i.pdfUrl,i.pdfData,i.chunks,i.questions,i.selectedQuestionId,i.showEvidenceOnly,f,p,y]),In.useEffect(()=>{i.highlightChunkId&&t.current&&(t.current.navigateToChunkById(i.highlightChunkId),y())},[i.highlightChunkId,y]),Ci.jsx("div",{ref:n,style:{width:"100%",minHeight:"800px"}})};un.setComponentReady();function m_(){const[i,t]=In.useState({});return In.useEffect(()=>{const n=o=>{const u=o.detail||o;u&&u.args&&t(u.args)};return un.events.addEventListener(un.RENDER_EVENT,n),window.addEventListener(un.RENDER_EVENT,n),()=>{un.events.removeEventListener(un.RENDER_EVENT,n),window.removeEventListener(un.RENDER_EVENT,n)}},[]),!i||Object.keys(i).length===0?Ci.jsx("div",{style:{padding:"20px",textAlign:"center"},children:Ci.jsx("p",{children:"Loading PDF viewer..."})}):Ci.jsx(y_,{pdfUrl:i.pdfUrl,pdfData:i.pdfData,chunks:i.chunks||"[]",questions:i.questions||"[]",selectedQuestionId:i.selectedQuestionId,showEvidenceOnly:i.showEvidenceOnly||!1,highlightChunkId:i.highlightChunkId})}const g_=Bv.createRoot(document.getElementById("root"));g_.render(Ci.jsx(Bc.StrictMode,{children:Ci.jsx(m_,{})})); diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/index.html b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/index.html new file mode 100644 index 00000000..c1428292 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/index.html @@ -0,0 +1,13 @@ + + + + + + PDF Viewer Component + + + +
+ + + diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/pdf-viewer.es.js b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/pdf-viewer.es.js new file mode 100644 index 00000000..e90ea722 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/build/pdf-viewer/pdf-viewer.es.js @@ -0,0 +1,985 @@ +class B extends HTMLElement { + constructor() { + super(), this.attachShadow({ mode: "open" }), this._pdfUrl = null, this._pdfData = null, this._chunks = [], this._questions = [], this._selectedQuestionId = null, this._showEvidenceOnly = !1, this._pdfDoc = null, this._currentPage = 1, this._scale = 1.5, this._pdfjsLib = null, this._renderedPages = /* @__PURE__ */ new Map(), this._isLoading = !1, this._highlightedChunkId = null; + } + static get observedAttributes() { + return ["pdf-url", "pdf-data", "chunks", "questions", "selected-question-id", "show-evidence-only"]; + } + connectedCallback() { + this.loadPdfJs().then(() => { + this.render(); + }); + } + disconnectedCallback() { + this._renderedPages.clear(), this._pdfDoc && (this._pdfDoc.destroy(), this._pdfDoc = null); + } + attributeChangedCallback(e, t, s) { + if (t !== s) + try { + e === "pdf-url" ? (this._pdfUrl = s, this._pdfData = null) : e === "pdf-data" ? (this._pdfData = s, this._pdfUrl = null) : e === "chunks" ? this._chunks = s ? JSON.parse(s) : [] : e === "questions" ? this._questions = s ? JSON.parse(s) : [] : e === "selected-question-id" ? this._selectedQuestionId = s : e === "show-evidence-only" && (this._showEvidenceOnly = s === "true" || s === ""), this._skipAttributeRender || this.render(); + } catch (i) { + console.error(`Error parsing ${e}:`, i); + } + } + // Public API: Set PDF URL + setPdfUrl(e) { + this._pdfUrl = e, this._pdfData = null, this.setAttribute("pdf-url", e); + } + // Public API: Set PDF data (base64) + setPdfData(e) { + this._pdfData = e, this._pdfUrl = null, this.setAttribute("pdf-data", e); + } + // Public API: Set chunks + setChunks(e) { + this._chunks = e, this.setAttribute("chunks", JSON.stringify(e)); + } + // Public API: Set questions + setQuestions(e) { + this._questions = e, this.setAttribute("questions", JSON.stringify(e)); + } + // Public API: Set selected question + setSelectedQuestionId(e, t = !1) { + this._selectedQuestionId = e, t ? (this._skipAttributeRender = !0, this.setAttribute("selected-question-id", e || ""), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("selected-question-id", e || ""); + } + // Public API: Set evidence filter + setShowEvidenceOnly(e, t = !1) { + this._showEvidenceOnly = e, t ? (this._skipAttributeRender = !0, this.setAttribute("show-evidence-only", e ? "true" : "false"), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("show-evidence-only", e ? "true" : "false"); + } + // Update filter UI without full render + updateFilterUI() { + var s, i; + const e = (s = this.shadowRoot) == null ? void 0 : s.getElementById("question-select"); + e && (e.value = this._selectedQuestionId || ""); + const t = (i = this.shadowRoot) == null ? void 0 : i.getElementById("evidence-filter"); + t && (t.checked = this._showEvidenceOnly), this.renderChunkList(); + } + // Render only the chunk list without re-rendering PDF + renderChunkList() { + var s; + const e = (s = this.shadowRoot) == null ? void 0 : s.querySelector(".chunks-list"); + if (!e) return; + const t = this.getFilteredChunks(); + e.innerHTML = t.length === 0 ? '
No chunks to display
' : t.map((i, n) => { + var g, c; + let r = "?"; + i.metadata && (i.metadata.page_number !== void 0 ? r = parseInt(i.metadata.page_number) || "?" : i.metadata.source !== void 0 && (r = parseInt(i.metadata.source) || "?")); + const o = i.is_evidence === !0, l = ((g = i.similarity_score) == null ? void 0 : g.toFixed(3)) || "N/A", h = ((c = i.llm_score) == null ? void 0 : c.toFixed(3)) || "N/A", a = i.text || "", p = a.substring(0, 150) + (a.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${i.chunk_order !== void 0 ? i.chunk_order + 1 : n + 1} +
+ ${o ? 'Evidence' : ""} + Page ${r} +
+
+
${this.escapeHtml(p)}
+
+ Similarity: ${l} + ${i.llm_score !== null && i.llm_score !== void 0 ? `LLM: ${h}` : ""} +
+
+ `; + }).join(""), this.attachChunkListeners(); + } + // Attach click listeners to chunk items + attachChunkListeners() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.querySelectorAll(".chunk-item"); + e && e.forEach((s) => { + var n; + const i = s.cloneNode(!0); + (n = s.parentNode) == null || n.replaceChild(i, s), i.addEventListener("click", () => { + const r = parseInt(i.dataset.chunkIndex), o = this.getFilteredChunks()[r]; + o && this.navigateToChunk(o); + }); + }); + } + async loadPdfJs() { + if (!this._pdfjsLib) { + if (typeof pdfjsLib > "u") { + const e = document.createElement("script"); + e.src = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.min.js", e.async = !0, await new Promise((t, s) => { + e.onload = t, e.onerror = s, document.head.appendChild(e); + }); + } + this._pdfjsLib = window.pdfjsLib || pdfjsLib, this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.workerSrc = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.worker.min.js"), this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.cMapUrl = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", this._pdfjsLib.GlobalWorkerOptions.cMapPacked = !0); + } + } + async loadPdf() { + if (this._pdfjsLib || await this.loadPdfJs(), this._pdfDoc) + return this._pdfDoc; + this._isLoading = !0, this.updateLoadingDisplay(); + try { + let e; + const t = { + cMapUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", + cMapPacked: !0, + standardFontDataUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/standard_fonts/" + }; + if (this._pdfData) { + const s = this._pdfData.replace(/^data:application\/pdf;base64,/, ""), i = atob(s), n = new Uint8Array(i.length); + for (let r = 0; r < i.length; r++) + n[r] = i.charCodeAt(r); + e = this._pdfjsLib.getDocument({ + data: n, + ...t + }); + } else if (this._pdfUrl) + e = this._pdfjsLib.getDocument({ + url: this._pdfUrl, + ...t + }); + else + throw new Error("No PDF URL or data provided"); + return this._pdfDoc = await e.promise, this._pdfDoc; + } catch (e) { + throw console.error("Error loading PDF:", e), e; + } + } + updateLoadingDisplay() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.getElementById("viewer-content"); + e && this._isLoading && (e.innerHTML = ` +
+ +
Loading PDF...
+
+ `); + } + getFilteredChunks() { + let e = []; + if (this._selectedQuestionId) { + const t = this._questions.find((s) => s.question_id === this._selectedQuestionId); + t && t.chunks ? e = t.chunks : e = this._chunks.filter((s) => s.question_id === this._selectedQuestionId); + } else + e = this._chunks; + return this._showEvidenceOnly && (e = e.filter((t) => t.is_evidence === !0 || t.is_evidence === 1)), e; + } + async renderPage(e) { + if (this._renderedPages.has(e)) + return this._renderedPages.get(e); + try { + const s = await (await this.loadPdf()).getPage(e), i = s.getViewport({ scale: this._scale }), n = document.createElement("canvas"), r = n.getContext("2d"); + return n.height = i.height, n.width = i.width, await s.render({ + canvasContext: r, + viewport: i + }).promise, this._renderedPages.set(e, n), n; + } catch (t) { + return console.error(`Error rendering page ${e}:`, t), null; + } + } + /** + * Calculate log-likelihood keyness scores for words + * Identifies words that are unusually frequent in this chunk compared to other chunks + * Uses Dunning's log-likelihood (G²) statistic + * @param {string} chunkText - The chunk text to analyze + * @param {Array} allChunks - All chunk texts for comparison + * @returns {Map} Map of word to keyness score + */ + calculateKeyness(e, t = []) { + const s = (c) => c.toLowerCase().replace(/[^\w\s]/g, " ").split(/\s+/).filter((f) => f.length > 2), i = s(e), n = /* @__PURE__ */ new Map(); + if (i.forEach((c) => { + n.set(c, (n.get(c) || 0) + 1); + }), t.length === 0) { + const c = Array.from(n.entries()).sort((f, d) => d[1] - f[1]).slice(0, 10); + return new Map(c); + } + const r = [], o = /* @__PURE__ */ new Map(); + t.forEach((c) => { + s(c.text || c).forEach((d) => { + r.push(d), o.set(d, (o.get(d) || 0) + 1); + }); + }); + const l = /* @__PURE__ */ new Map(), h = i.length, a = r.length, p = h + a; + return (/* @__PURE__ */ new Set([...i, ...r])).forEach((c) => { + const f = n.get(c) || 0, d = o.get(c) || 0; + if (f === 0) + return; + const m = (f + d) * (h / p), v = (f + d) * (a / p); + let u = 0; + f > 0 && m > 0 && (u += 2 * f * Math.log(f / m)), d > 0 && v > 0 && (u += 2 * d * Math.log(d / v)), u > 0.01 && f > m && l.set(c, u); + }), l; + } + /** + * Get word-level importance scores for highlighting + * Uses log-likelihood keyness to identify words unusually frequent in this chunk + * @param {string} chunkText - The chunk text + * @param {Array} allChunks - All chunks for comparison + * @returns {Map} Word to keyness score + */ + getWordImportanceScores(e, t = []) { + return this.calculateKeyness(e, t); + } + /** + * Find text positions for a chunk in the PDF page + * Uses exact matching first, falls back to embedding-based semantic matching + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @param {Array} allChunks - All chunks for context (optional, for TF-IDF) + * @returns {Array} Array of bounding boxes {x, y, width, height, wordScores} in viewport coordinates + */ + async findChunkTextPositions(e, t, s, i = []) { + const n = await this.findChunkTextPositionsExact(e, t, s); + if (n.length > 0) { + const r = this.getWordImportanceScores(t, i); + return n.forEach((o) => { + o.wordScores = r; + }), n; + } + return []; + } + /** + * Exact text matching (original implementation) + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @returns {Array} Array of bounding boxes + */ + async findChunkTextPositionsExact(e, t, s) { + try { + const i = await e.getTextContent(); + if (!i || !i.items || i.items.length === 0) + return console.warn("No text content found on page"), []; + const n = (g) => g.toLowerCase().trim().replace(/\s+/g, " "), r = n(t); + if (!r || r.length < 10) + return console.warn("Chunk text too short for reliable matching"), []; + const o = i.items, l = o.map((g) => g.str).join(" "), h = n(l); + let a = h.indexOf(r), p = r; + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(20, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(10, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + return a === -1 ? (console.warn(`Chunk text not found on page: "${t.substring(0, 50)}..."`), []) : this.findTextItemPositions(o, p, a, h, s, n); + } catch (i) { + return console.error("Error finding chunk text positions:", i), []; + } + } + /** + * Find text item positions that match the search text + * @param {Array} textItems - Array of text items from PDF.js + * @param {string} searchText - Normalized text to search for + * @param {number} textIndex - Character index where searchText was found in normalized text + * @param {string} normalizedAllText - Full normalized text from all items + * @param {Object} viewport - PDF.js viewport object + * @param {Function} normalizeText - Text normalization function + * @returns {Array} Array of bounding boxes + */ + findTextItemPositions(e, t, s, i, n, r) { + const o = []; + let l = 0; + const h = []; + for (let a = 0; a < e.length; a++) { + const p = e[a], g = r(p.str), c = g.length + 1; + if (l + g.length >= s && l <= s + t.length && h.push(p), l += c, l > s + t.length) + break; + } + if (h.length === 0) { + const a = t.split(" ").slice(0, 5).join(" "); + let p = ""; + for (const g of e) { + const c = r(g.str); + if (p += c + " ", h.push(g), r(p).includes(a)) + break; + if (h.length > 50) { + h.length = 0; + break; + } + } + } + if (h.length > 0) { + const a = this.calculateBoundingBox(h, n); + a && a.width > 0 && a.height > 0 && o.push(a); + } + return o; + } + /** + * Calculate bounding box from text items and convert to viewport coordinates + * @param {Array} textItems - Array of text items that form the match + * @param {Object} viewport - PDF.js viewport object + * @returns {Object|null} Bounding box {x, y, width, height} in viewport coordinates, or null + */ + calculateBoundingBox(e, t) { + if (!e || e.length === 0) + return null; + let s = 1 / 0, i = 1 / 0, n = -1 / 0, r = -1 / 0; + for (const d of e) + if (d.transform && d.transform.length >= 6) { + const m = d.transform[4], v = d.transform[5], u = d.width || 0, y = d.height || Math.abs(d.transform[3]) || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } else if (d.x !== void 0 && d.y !== void 0) { + const m = d.x, v = d.y, u = d.width || 0, y = d.height || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } + if (s === 1 / 0 || i === 1 / 0) + return null; + let o, l, h, a; + if (t.convertToViewportPoint) + [o, l] = t.convertToViewportPoint(s, i), [h, a] = t.convertToViewportPoint(n, r); + else { + const d = t.height / t.scale; + o = s * t.scale, l = (d - r) * t.scale, h = n * t.scale, a = (d - i) * t.scale; + } + const p = Math.min(o, h), g = Math.min(l, a), c = Math.abs(h - o), f = Math.abs(a - l); + return c < 1 || f < 1 ? null : { x: p, y: g, width: c, height: f }; + } + /** + * Add word-level highlights based on TF-IDF scores + * Highlights individual words within the matched text region + * @param {HTMLElement} container - Container to add highlights to + * @param {Object} page - PDF.js page object + * @param {Object} bbox - Bounding box of matched text + * @param {Map} wordScores - Map of word to TF-IDF score + * @param {Object} viewport - PDF.js viewport + * @param {boolean} isEvidence - Whether this is an evidence chunk + */ + async addWordLevelHighlights(e, t, s, i, n, r) { + try { + const o = await t.getTextContent(); + if (!o || !o.items) + return; + const l = /* @__PURE__ */ new Set([ + "the", + "be", + "to", + "of", + "and", + "a", + "in", + "that", + "have", + "i", + "it", + "for", + "not", + "on", + "with", + "he", + "as", + "you", + "do", + "at", + "this", + "but", + "his", + "by", + "from", + "they", + "we", + "say", + "her", + "she", + "or", + "an", + "will", + "my", + "one", + "all", + "would", + "there", + "their", + "what", + "so", + "up", + "out", + "if", + "about", + "who", + "get", + "which", + "go", + "me", + "when", + "make", + "can", + "like", + "time", + "no", + "just", + "him", + "know", + "take", + "people", + "into", + "year", + "your", + "good", + "some", + "could", + "them", + "see", + "other", + "than", + "then", + "now", + "look", + "only", + "come", + "its", + "over", + "think", + "also", + "back", + "after", + "use", + "two", + "how", + "our", + "work", + "first", + "well", + "way", + "even", + "new", + "want", + "because", + "any", + "these", + "give", + "day", + "most", + "us", + "is", + "are", + "was", + "were", + "been", + "being", + "has", + "had", + "does", + "did", + "may", + "might", + "must", + "shall", + "should", + "could", + "would", + "can", + "cannot", + "will", + "shall" + ]); + let h = i; + i instanceof Map || (h = new Map(Object.entries(i || {}))); + const a = Array.from(h.entries()).sort((w, x) => x[1] - w[1]).slice(0, 10); + if (a.length === 0) { + console.warn("No key words found for highlighting - keyness scores may be empty. WordScores:", h); + return; + } + console.log(`Found ${a.length} key words for highlighting:`, a.map(([w, x]) => `${w}(${x.toFixed(3)})`)); + const p = a[0][1], g = a[a.length - 1][1], c = p - g || 1, f = (w) => w.toLowerCase().replace(/[^\w]/g, ""), d = /* @__PURE__ */ new Set(), m = /* @__PURE__ */ new Map(); + if (a.forEach(([w, x]) => { + const k = f(w); + k.length >= 3 && (d.add(k), m.set(k, x)); + }), d.size === 0) + return; + const v = 0.1, u = s.x - s.width * v, y = s.x + s.width + s.width * v, T = s.y - s.height * v, j = s.y + s.height + s.height * v, D = n.height / n.scale, O = (w, x, k, C) => { + if (n.convertToViewportPoint) { + const [L, q] = n.convertToViewportPoint(w, x), W = w + k, E = x + C, [P, I] = n.convertToViewportPoint(W, E); + return { + x: L, + y: q, + width: Math.abs(P - L), + height: Math.abs(I - q) + }; + } else + return { + x: w * n.scale, + y: (D - (x + C)) * n.scale, + width: k * n.scale, + height: C * n.scale + }; + }; + let S = 0; + const N = 50; + for (const w of o.items) { + if (S >= N) break; + if (!w.transform || w.transform.length < 6) continue; + const x = w.transform[4], k = w.transform[5], C = w.width || 0, L = w.height || Math.abs(w.transform[3]) || 12, q = x + C, W = k + L, E = O(x, k, C, L), P = E.x, I = E.y, F = E.width, R = E.height; + if (P < u || P + F > y || I < T || I + R > j) + continue; + const M = f(w.str); + if (d.has(M)) { + const $ = m.get(M), z = 0.5 + ($ - g) / c * 0.4, _ = document.createElement("div"); + _.className = `word-highlight ${r ? "evidence-word" : ""}`, _.style.left = `${P / n.width * 100}%`, _.style.top = `${I / n.height * 100}%`, _.style.width = `${F / n.width * 100}%`, _.style.height = `${R / n.height * 100}%`, _.style.opacity = z, _.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", _.style.borderRadius = "2px", _.title = `Important word: "${w.str}" (Keyness: ${$.toFixed(3)})`, e.appendChild(_), S++; + } else + for (const $ of d) + if (M.startsWith($) || M.endsWith($)) { + const A = m.get($), _ = 0.5 + (A - g) / c * 0.4, b = document.createElement("div"); + b.className = `word-highlight ${r ? "evidence-word" : ""}`, b.style.left = `${P / n.width * 100}%`, b.style.top = `${I / n.height * 100}%`, b.style.width = `${F / n.width * 100}%`, b.style.height = `${R / n.height * 100}%`, b.style.opacity = _, b.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", b.style.borderRadius = "2px", b.title = `Important word: "${w.str}" (Keyness: ${A.toFixed(3)})`, e.appendChild(b), S++; + break; + } + } + console.log(`Added ${S} word highlights for ${a.length} key words`); + } catch (o) { + console.error("Error adding word-level highlights:", o); + } + } + async navigateToPage(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + this._currentPage = e, await this.render(), this._selectedQuestionId = t, this._showEvidenceOnly = s, requestAnimationFrame(() => { + var r, o; + const i = (r = this.shadowRoot) == null ? void 0 : r.getElementById("question-select"); + i && (i.value = t || ""); + const n = (o = this.shadowRoot) == null ? void 0 : o.getElementById("evidence-filter"); + n && (n.checked = s); + }); + } + async navigateToChunk(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + let i = 1; + if (e.metadata && (e.metadata.page_number !== void 0 ? i = parseInt(e.metadata.page_number) || 1 : e.metadata.source !== void 0 && (i = parseInt(e.metadata.source) || 1)), this._pdfDoc) { + const n = this._pdfDoc.numPages; + i < 1 && (i = 1), i > n && (i = n); + } + await this.navigateToPage(i), this._selectedQuestionId = t, this._showEvidenceOnly = s, this.dispatchEvent(new CustomEvent("chunk-selected", { + detail: { chunk: e, pageNum: i }, + bubbles: !0, + composed: !0 + })); + } + // Public API: Navigate to chunk by ID (for Streamlit communication) + // chunkId format: "question_id_chunk_order" (e.g., "tcfd_1_0") + // Note: question_id may contain underscores, so we split from the right + async navigateToChunkById(e) { + if (!e) return; + const t = e.lastIndexOf("_"); + if (t === -1) { + console.warn(`Invalid chunk ID format: ${e}. Expected format: "question_id_chunk_order"`); + return; + } + const s = e.substring(0, t), i = e.substring(t + 1), n = parseInt(i); + if (isNaN(n)) { + console.warn(`Invalid chunk order in chunk ID: ${e} (parsed as: ${i})`); + return; + } + const r = this._chunks.find((l) => { + const h = l.question_id || "", a = l.chunk_order !== void 0 ? l.chunk_order : -1; + return h === s && (a === n || a === n - 1 || a === n + 1); + }); + if (!r) { + console.warn(`Chunk not found for ID: ${e} (question_id: ${s}, chunk_order: ${n})`), console.debug("Available chunks:", this._chunks.map((l) => ({ + question_id: l.question_id, + chunk_order: l.chunk_order + }))); + return; + } + const o = this._showEvidenceOnly; + this.setSelectedQuestionId(s), await new Promise((l) => setTimeout(l, 100)), await this.navigateToChunk(r), this._showEvidenceOnly = o, this._highlightedChunkId = e; + } + async render() { + if (!this.shadowRoot) return; + const e = this._selectedQuestionId, t = this._showEvidenceOnly, s = this.getFilteredChunks(), i = {}; + s.forEach((o) => { + let l = 1; + o.metadata && (o.metadata.page_number !== void 0 ? l = parseInt(o.metadata.page_number) || 1 : o.metadata.source !== void 0 && (l = parseInt(o.metadata.source) || 1)), i[l] || (i[l] = []), i[l].push(o); + }); + const n = ` + + `, r = ` +
+
+
+

Chunks by Question

+
+ +
+
+ + +
+
+
+ ${s.length === 0 ? '
No chunks to display
' : ""} + ${s.map((o, l) => { + var d, m; + let h = "?"; + o.metadata && (o.metadata.page_number !== void 0 ? h = parseInt(o.metadata.page_number) || "?" : o.metadata.source !== void 0 && (h = parseInt(o.metadata.source) || "?")); + const a = o.is_evidence === !0, p = ((d = o.similarity_score) == null ? void 0 : d.toFixed(3)) || "N/A", g = ((m = o.llm_score) == null ? void 0 : m.toFixed(3)) || "N/A", c = o.text || "", f = c.substring(0, 150) + (c.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${o.chunk_order !== void 0 ? o.chunk_order + 1 : l + 1} +
+ ${a ? 'Evidence' : ""} + Page ${h} +
+
+
${this.escapeHtml(f)}
+
+ Similarity: ${p} + ${o.llm_score !== null && o.llm_score !== void 0 ? `LLM: ${g}` : ""} +
+
+ `; + }).join("")} +
+
+
+
+ + + Page ${this._currentPage} of - + + +
+
+
Loading PDF...
+
+
+
+ `; + this.shadowRoot.innerHTML = n + r, this._selectedQuestionId = e, this._showEvidenceOnly = t, this.setupEventListeners(), setTimeout(() => { + const o = this.shadowRoot.getElementById("question-select"); + o && this._selectedQuestionId !== void 0 && (o.value = this._selectedQuestionId || ""); + const l = this.shadowRoot.getElementById("evidence-filter"); + l && this._showEvidenceOnly !== void 0 && (l.checked = this._showEvidenceOnly); + }, 0), this.loadAndRenderPdf(); + } + escapeHtml(e) { + const t = document.createElement("div"); + return t.textContent = e, t.innerHTML; + } + setupEventListeners() { + const e = this.shadowRoot.getElementById("question-select"); + e && e.addEventListener("change", (n) => { + this.setSelectedQuestionId(n.target.value || null, !0); + }); + const t = this.shadowRoot.getElementById("evidence-filter"); + t && t.addEventListener("change", (n) => { + this.setShowEvidenceOnly(n.target.checked, !0); + }), this.attachChunkListeners(); + const s = this.shadowRoot.getElementById("prev-page"), i = this.shadowRoot.getElementById("next-page"); + s && s.addEventListener("click", () => { + this._currentPage > 1 && this.navigateToPage(this._currentPage - 1); + }), i && i.addEventListener("click", async () => { + if (this._pdfDoc) { + const n = this._pdfDoc.numPages; + this._currentPage < n && await this.navigateToPage(this._currentPage + 1); + } + }); + } + async loadAndRenderPdf() { + try { + this._isLoading = !0, this.updateLoadingDisplay(); + const t = (await this.loadPdf()).numPages, s = this.shadowRoot.getElementById("total-pages"); + s && (s.textContent = t), await this.renderCurrentPage(), this._isLoading = !1; + } catch (e) { + this._isLoading = !1; + const t = this.shadowRoot.getElementById("viewer-content"); + t && (t.innerHTML = `
Error loading PDF: ${e.message}
`); + } + } + async renderCurrentPage() { + const e = this.shadowRoot.getElementById("viewer-content"); + if (e) + try { + const t = await this.loadPdf(), s = t.numPages; + this._currentPage < 1 && (this._currentPage = 1), this._currentPage > s && (this._currentPage = s); + const i = this.shadowRoot.getElementById("current-page"); + i && (i.textContent = this._currentPage); + const n = await this.renderPage(this._currentPage); + if (!n) { + e.innerHTML = '
Error rendering page
'; + return; + } + const r = await t.getPage(this._currentPage), o = r.getViewport({ scale: this._scale }), l = this.getFilteredChunks(), h = l.filter((c) => { + let f = 1; + return c.metadata && (c.metadata.page_number !== void 0 ? f = parseInt(c.metadata.page_number) || 1 : c.metadata.source !== void 0 && (f = parseInt(c.metadata.source) || 1)), f === this._currentPage; + }), a = document.createElement("div"); + a.className = "page-container"; + const p = document.createElement("canvas"); + if (p.className = "page-canvas", p.width = n.width, p.height = n.height, p.getContext("2d").drawImage(n, 0, 0), a.appendChild(p), h.length > 0) { + const c = document.createElement("div"); + c.className = "page-highlights"; + const f = l.map((d) => ({ text: d.text || "" })); + for (const d of h) { + const m = d.text || ""; + if (!m || m.trim().length === 0) + continue; + const v = await this.findChunkTextPositions( + r, + m, + o, + f + ); + if (v.length > 0) + v.forEach((u) => { + const y = document.createElement("div"); + y.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`; + const T = u.x / o.width * 100, j = u.y / o.height * 100, D = u.width / o.width * 100, O = u.height / o.height * 100; + y.style.left = `${T}%`, y.style.top = `${j}%`, y.style.width = `${D}%`, y.style.height = `${O}%`, y.title = d.is_evidence === !0 || d.is_evidence === 1 ? `Evidence chunk: ${m.substring(0, 50)}...` : `Chunk: ${m.substring(0, 50)}...`, c.appendChild(y), u.wordScores && (u.wordScores instanceof Map ? u.wordScores.size > 0 : Object.keys(u.wordScores || {}).length > 0) ? (console.log(`Adding word highlights for chunk with ${u.wordScores instanceof Map ? u.wordScores.size : Object.keys(u.wordScores || {}).length} word scores`), this.addWordLevelHighlights( + c, + r, + u, + u.wordScores, + o, + d.is_evidence === !0 || d.is_evidence === 1 + )) : console.warn("No wordScores found for chunk, skipping word highlights"); + }); + else { + console.warn(`Could not find text position for chunk on page ${this._currentPage}`); + const u = document.createElement("div"); + u.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`, u.style.top = "5%", u.style.left = "5%", u.style.width = "10px", u.style.height = "10px", u.style.borderRadius = "50%", u.title = "Chunk text position not found", c.appendChild(u); + } + } + a.appendChild(c); + } + e.innerHTML = "", e.appendChild(a); + } catch (t) { + console.error("Error rendering current page:", t), e.innerHTML = `
Error rendering page: ${t.message}
`; + } + } +} +customElements.get("pdf-viewer-with-chunks") || customElements.define("pdf-viewer-with-chunks", B); +export { + B as default +}; diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/index-pdf-viewer.html b/report_analyst_enterprise/components/streamlit_component/frontend/index-pdf-viewer.html new file mode 100644 index 00000000..6a8a8f95 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/index-pdf-viewer.html @@ -0,0 +1,13 @@ + + + + + + PDF Viewer Component + + +
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fixedHtml=html.replace('src=\\\"/index-pdf-viewer.js\\\"','src=\\\"index-pdf-viewer.js\\\"'); fs.writeFileSync('build/index-pdf-viewer.html', fixedHtml); fs.mkdirSync('build/pdf-viewer', {recursive: true}); if(fs.existsSync('build/index-pdf-viewer.js')) fs.copyFileSync('build/index-pdf-viewer.js', 'build/pdf-viewer/index-pdf-viewer.js'); if(fs.existsSync('build/pdf-viewer.es.js')) fs.copyFileSync('build/pdf-viewer.es.js', 'build/pdf-viewer/pdf-viewer.es.js'); const pdfViewerHtml=html.replace('src=\\\"/index-pdf-viewer.js\\\"','src=\\\"index-pdf-viewer.js\\\"'); fs.writeFileSync('build/pdf-viewer/index.html', pdfViewerHtml);\"" + }, + "dependencies": { + "react": "^18.2.0", + "react-dom": "^18.2.0", + "streamlit-component-lib": "^2.0.0" + }, + "devDependencies": { + "@types/react": "^18.2.0", + "@types/react-dom": "^18.2.0", + "@vitejs/plugin-react": "^4.7.0", + "typescript": "^5.0.0", + "vite": "^5.4.21" + } +} diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/public/pdf-viewer.es.js b/report_analyst_enterprise/components/streamlit_component/frontend/public/pdf-viewer.es.js new file mode 100644 index 00000000..e90ea722 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/public/pdf-viewer.es.js @@ -0,0 +1,985 @@ +class B extends HTMLElement { + constructor() { + super(), this.attachShadow({ mode: "open" }), this._pdfUrl = null, this._pdfData = null, this._chunks = [], this._questions = [], this._selectedQuestionId = null, this._showEvidenceOnly = !1, this._pdfDoc = null, this._currentPage = 1, this._scale = 1.5, this._pdfjsLib = null, this._renderedPages = /* @__PURE__ */ new Map(), this._isLoading = !1, this._highlightedChunkId = null; + } + static get observedAttributes() { + return ["pdf-url", "pdf-data", "chunks", "questions", "selected-question-id", "show-evidence-only"]; + } + connectedCallback() { + this.loadPdfJs().then(() => { + this.render(); + }); + } + disconnectedCallback() { + this._renderedPages.clear(), this._pdfDoc && (this._pdfDoc.destroy(), this._pdfDoc = null); + } + attributeChangedCallback(e, t, s) { + if (t !== s) + try { + e === "pdf-url" ? (this._pdfUrl = s, this._pdfData = null) : e === "pdf-data" ? (this._pdfData = s, this._pdfUrl = null) : e === "chunks" ? this._chunks = s ? JSON.parse(s) : [] : e === "questions" ? this._questions = s ? JSON.parse(s) : [] : e === "selected-question-id" ? this._selectedQuestionId = s : e === "show-evidence-only" && (this._showEvidenceOnly = s === "true" || s === ""), this._skipAttributeRender || this.render(); + } catch (i) { + console.error(`Error parsing ${e}:`, i); + } + } + // Public API: Set PDF URL + setPdfUrl(e) { + this._pdfUrl = e, this._pdfData = null, this.setAttribute("pdf-url", e); + } + // Public API: Set PDF data (base64) + setPdfData(e) { + this._pdfData = e, this._pdfUrl = null, this.setAttribute("pdf-data", e); + } + // Public API: Set chunks + setChunks(e) { + this._chunks = e, this.setAttribute("chunks", JSON.stringify(e)); + } + // Public API: Set questions + setQuestions(e) { + this._questions = e, this.setAttribute("questions", JSON.stringify(e)); + } + // Public API: Set selected question + setSelectedQuestionId(e, t = !1) { + this._selectedQuestionId = e, t ? (this._skipAttributeRender = !0, this.setAttribute("selected-question-id", e || ""), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("selected-question-id", e || ""); + } + // Public API: Set evidence filter + setShowEvidenceOnly(e, t = !1) { + this._showEvidenceOnly = e, t ? (this._skipAttributeRender = !0, this.setAttribute("show-evidence-only", e ? "true" : "false"), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("show-evidence-only", e ? "true" : "false"); + } + // Update filter UI without full render + updateFilterUI() { + var s, i; + const e = (s = this.shadowRoot) == null ? void 0 : s.getElementById("question-select"); + e && (e.value = this._selectedQuestionId || ""); + const t = (i = this.shadowRoot) == null ? void 0 : i.getElementById("evidence-filter"); + t && (t.checked = this._showEvidenceOnly), this.renderChunkList(); + } + // Render only the chunk list without re-rendering PDF + renderChunkList() { + var s; + const e = (s = this.shadowRoot) == null ? void 0 : s.querySelector(".chunks-list"); + if (!e) return; + const t = this.getFilteredChunks(); + e.innerHTML = t.length === 0 ? '
No chunks to display
' : t.map((i, n) => { + var g, c; + let r = "?"; + i.metadata && (i.metadata.page_number !== void 0 ? r = parseInt(i.metadata.page_number) || "?" : i.metadata.source !== void 0 && (r = parseInt(i.metadata.source) || "?")); + const o = i.is_evidence === !0, l = ((g = i.similarity_score) == null ? void 0 : g.toFixed(3)) || "N/A", h = ((c = i.llm_score) == null ? void 0 : c.toFixed(3)) || "N/A", a = i.text || "", p = a.substring(0, 150) + (a.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${i.chunk_order !== void 0 ? i.chunk_order + 1 : n + 1} +
+ ${o ? 'Evidence' : ""} + Page ${r} +
+
+
${this.escapeHtml(p)}
+
+ Similarity: ${l} + ${i.llm_score !== null && i.llm_score !== void 0 ? `LLM: ${h}` : ""} +
+
+ `; + }).join(""), this.attachChunkListeners(); + } + // Attach click listeners to chunk items + attachChunkListeners() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.querySelectorAll(".chunk-item"); + e && e.forEach((s) => { + var n; + const i = s.cloneNode(!0); + (n = s.parentNode) == null || n.replaceChild(i, s), i.addEventListener("click", () => { + const r = parseInt(i.dataset.chunkIndex), o = this.getFilteredChunks()[r]; + o && this.navigateToChunk(o); + }); + }); + } + async loadPdfJs() { + if (!this._pdfjsLib) { + if (typeof pdfjsLib > "u") { + const e = document.createElement("script"); + e.src = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.min.js", e.async = !0, await new Promise((t, s) => { + e.onload = t, e.onerror = s, document.head.appendChild(e); + }); + } + this._pdfjsLib = window.pdfjsLib || pdfjsLib, this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.workerSrc = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.worker.min.js"), this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.cMapUrl = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", this._pdfjsLib.GlobalWorkerOptions.cMapPacked = !0); + } + } + async loadPdf() { + if (this._pdfjsLib || await this.loadPdfJs(), this._pdfDoc) + return this._pdfDoc; + this._isLoading = !0, this.updateLoadingDisplay(); + try { + let e; + const t = { + cMapUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", + cMapPacked: !0, + standardFontDataUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/standard_fonts/" + }; + if (this._pdfData) { + const s = this._pdfData.replace(/^data:application\/pdf;base64,/, ""), i = atob(s), n = new Uint8Array(i.length); + for (let r = 0; r < i.length; r++) + n[r] = i.charCodeAt(r); + e = this._pdfjsLib.getDocument({ + data: n, + ...t + }); + } else if (this._pdfUrl) + e = this._pdfjsLib.getDocument({ + url: this._pdfUrl, + ...t + }); + else + throw new Error("No PDF URL or data provided"); + return this._pdfDoc = await e.promise, this._pdfDoc; + } catch (e) { + throw console.error("Error loading PDF:", e), e; + } + } + updateLoadingDisplay() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.getElementById("viewer-content"); + e && this._isLoading && (e.innerHTML = ` +
+ +
Loading PDF...
+
+ `); + } + getFilteredChunks() { + let e = []; + if (this._selectedQuestionId) { + const t = this._questions.find((s) => s.question_id === this._selectedQuestionId); + t && t.chunks ? e = t.chunks : e = this._chunks.filter((s) => s.question_id === this._selectedQuestionId); + } else + e = this._chunks; + return this._showEvidenceOnly && (e = e.filter((t) => t.is_evidence === !0 || t.is_evidence === 1)), e; + } + async renderPage(e) { + if (this._renderedPages.has(e)) + return this._renderedPages.get(e); + try { + const s = await (await this.loadPdf()).getPage(e), i = s.getViewport({ scale: this._scale }), n = document.createElement("canvas"), r = n.getContext("2d"); + return n.height = i.height, n.width = i.width, await s.render({ + canvasContext: r, + viewport: i + }).promise, this._renderedPages.set(e, n), n; + } catch (t) { + return console.error(`Error rendering page ${e}:`, t), null; + } + } + /** + * Calculate log-likelihood keyness scores for words + * Identifies words that are unusually frequent in this chunk compared to other chunks + * Uses Dunning's log-likelihood (G²) statistic + * @param {string} chunkText - The chunk text to analyze + * @param {Array} allChunks - All chunk texts for comparison + * @returns {Map} Map of word to keyness score + */ + calculateKeyness(e, t = []) { + const s = (c) => c.toLowerCase().replace(/[^\w\s]/g, " ").split(/\s+/).filter((f) => f.length > 2), i = s(e), n = /* @__PURE__ */ new Map(); + if (i.forEach((c) => { + n.set(c, (n.get(c) || 0) + 1); + }), t.length === 0) { + const c = Array.from(n.entries()).sort((f, d) => d[1] - f[1]).slice(0, 10); + return new Map(c); + } + const r = [], o = /* @__PURE__ */ new Map(); + t.forEach((c) => { + s(c.text || c).forEach((d) => { + r.push(d), o.set(d, (o.get(d) || 0) + 1); + }); + }); + const l = /* @__PURE__ */ new Map(), h = i.length, a = r.length, p = h + a; + return (/* @__PURE__ */ new Set([...i, ...r])).forEach((c) => { + const f = n.get(c) || 0, d = o.get(c) || 0; + if (f === 0) + return; + const m = (f + d) * (h / p), v = (f + d) * (a / p); + let u = 0; + f > 0 && m > 0 && (u += 2 * f * Math.log(f / m)), d > 0 && v > 0 && (u += 2 * d * Math.log(d / v)), u > 0.01 && f > m && l.set(c, u); + }), l; + } + /** + * Get word-level importance scores for highlighting + * Uses log-likelihood keyness to identify words unusually frequent in this chunk + * @param {string} chunkText - The chunk text + * @param {Array} allChunks - All chunks for comparison + * @returns {Map} Word to keyness score + */ + getWordImportanceScores(e, t = []) { + return this.calculateKeyness(e, t); + } + /** + * Find text positions for a chunk in the PDF page + * Uses exact matching first, falls back to embedding-based semantic matching + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @param {Array} allChunks - All chunks for context (optional, for TF-IDF) + * @returns {Array} Array of bounding boxes {x, y, width, height, wordScores} in viewport coordinates + */ + async findChunkTextPositions(e, t, s, i = []) { + const n = await this.findChunkTextPositionsExact(e, t, s); + if (n.length > 0) { + const r = this.getWordImportanceScores(t, i); + return n.forEach((o) => { + o.wordScores = r; + }), n; + } + return []; + } + /** + * Exact text matching (original implementation) + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @returns {Array} Array of bounding boxes + */ + async findChunkTextPositionsExact(e, t, s) { + try { + const i = await e.getTextContent(); + if (!i || !i.items || i.items.length === 0) + return console.warn("No text content found on page"), []; + const n = (g) => g.toLowerCase().trim().replace(/\s+/g, " "), r = n(t); + if (!r || r.length < 10) + return console.warn("Chunk text too short for reliable matching"), []; + const o = i.items, l = o.map((g) => g.str).join(" "), h = n(l); + let a = h.indexOf(r), p = r; + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(20, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(10, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + return a === -1 ? (console.warn(`Chunk text not found on page: "${t.substring(0, 50)}..."`), []) : this.findTextItemPositions(o, p, a, h, s, n); + } catch (i) { + return console.error("Error finding chunk text positions:", i), []; + } + } + /** + * Find text item positions that match the search text + * @param {Array} textItems - Array of text items from PDF.js + * @param {string} searchText - Normalized text to search for + * @param {number} textIndex - Character index where searchText was found in normalized text + * @param {string} normalizedAllText - Full normalized text from all items + * @param {Object} viewport - PDF.js viewport object + * @param {Function} normalizeText - Text normalization function + * @returns {Array} Array of bounding boxes + */ + findTextItemPositions(e, t, s, i, n, r) { + const o = []; + let l = 0; + const h = []; + for (let a = 0; a < e.length; a++) { + const p = e[a], g = r(p.str), c = g.length + 1; + if (l + g.length >= s && l <= s + t.length && h.push(p), l += c, l > s + t.length) + break; + } + if (h.length === 0) { + const a = t.split(" ").slice(0, 5).join(" "); + let p = ""; + for (const g of e) { + const c = r(g.str); + if (p += c + " ", h.push(g), r(p).includes(a)) + break; + if (h.length > 50) { + h.length = 0; + break; + } + } + } + if (h.length > 0) { + const a = this.calculateBoundingBox(h, n); + a && a.width > 0 && a.height > 0 && o.push(a); + } + return o; + } + /** + * Calculate bounding box from text items and convert to viewport coordinates + * @param {Array} textItems - Array of text items that form the match + * @param {Object} viewport - PDF.js viewport object + * @returns {Object|null} Bounding box {x, y, width, height} in viewport coordinates, or null + */ + calculateBoundingBox(e, t) { + if (!e || e.length === 0) + return null; + let s = 1 / 0, i = 1 / 0, n = -1 / 0, r = -1 / 0; + for (const d of e) + if (d.transform && d.transform.length >= 6) { + const m = d.transform[4], v = d.transform[5], u = d.width || 0, y = d.height || Math.abs(d.transform[3]) || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } else if (d.x !== void 0 && d.y !== void 0) { + const m = d.x, v = d.y, u = d.width || 0, y = d.height || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } + if (s === 1 / 0 || i === 1 / 0) + return null; + let o, l, h, a; + if (t.convertToViewportPoint) + [o, l] = t.convertToViewportPoint(s, i), [h, a] = t.convertToViewportPoint(n, r); + else { + const d = t.height / t.scale; + o = s * t.scale, l = (d - r) * t.scale, h = n * t.scale, a = (d - i) * t.scale; + } + const p = Math.min(o, h), g = Math.min(l, a), c = Math.abs(h - o), f = Math.abs(a - l); + return c < 1 || f < 1 ? null : { x: p, y: g, width: c, height: f }; + } + /** + * Add word-level highlights based on TF-IDF scores + * Highlights individual words within the matched text region + * @param {HTMLElement} container - Container to add highlights to + * @param {Object} page - PDF.js page object + * @param {Object} bbox - Bounding box of matched text + * @param {Map} wordScores - Map of word to TF-IDF score + * @param {Object} viewport - PDF.js viewport + * @param {boolean} isEvidence - Whether this is an evidence chunk + */ + async addWordLevelHighlights(e, t, s, i, n, r) { + try { + const o = await t.getTextContent(); + if (!o || !o.items) + return; + const l = /* @__PURE__ */ new Set([ + "the", + "be", + "to", + "of", + "and", + "a", + "in", + "that", + "have", + "i", + "it", + "for", + "not", + "on", + "with", + "he", + "as", + "you", + "do", + "at", + "this", + "but", + "his", + "by", + "from", + "they", + "we", + "say", + "her", + "she", + "or", + "an", + "will", + "my", + "one", + "all", + "would", + "there", + "their", + "what", + "so", + "up", + "out", + "if", + "about", + "who", + "get", + "which", + "go", + "me", + "when", + "make", + "can", + "like", + "time", + "no", + "just", + "him", + "know", + "take", + "people", + "into", + "year", + "your", + "good", + "some", + "could", + "them", + "see", + "other", + "than", + "then", + "now", + "look", + "only", + "come", + "its", + "over", + "think", + "also", + "back", + "after", + "use", + "two", + "how", + "our", + "work", + "first", + "well", + "way", + "even", + "new", + "want", + "because", + "any", + "these", + "give", + "day", + "most", + "us", + "is", + "are", + "was", + "were", + "been", + "being", + "has", + "had", + "does", + "did", + "may", + "might", + "must", + "shall", + "should", + "could", + "would", + "can", + "cannot", + "will", + "shall" + ]); + let h = i; + i instanceof Map || (h = new Map(Object.entries(i || {}))); + const a = Array.from(h.entries()).sort((w, x) => x[1] - w[1]).slice(0, 10); + if (a.length === 0) { + console.warn("No key words found for highlighting - keyness scores may be empty. WordScores:", h); + return; + } + console.log(`Found ${a.length} key words for highlighting:`, a.map(([w, x]) => `${w}(${x.toFixed(3)})`)); + const p = a[0][1], g = a[a.length - 1][1], c = p - g || 1, f = (w) => w.toLowerCase().replace(/[^\w]/g, ""), d = /* @__PURE__ */ new Set(), m = /* @__PURE__ */ new Map(); + if (a.forEach(([w, x]) => { + const k = f(w); + k.length >= 3 && (d.add(k), m.set(k, x)); + }), d.size === 0) + return; + const v = 0.1, u = s.x - s.width * v, y = s.x + s.width + s.width * v, T = s.y - s.height * v, j = s.y + s.height + s.height * v, D = n.height / n.scale, O = (w, x, k, C) => { + if (n.convertToViewportPoint) { + const [L, q] = n.convertToViewportPoint(w, x), W = w + k, E = x + C, [P, I] = n.convertToViewportPoint(W, E); + return { + x: L, + y: q, + width: Math.abs(P - L), + height: Math.abs(I - q) + }; + } else + return { + x: w * n.scale, + y: (D - (x + C)) * n.scale, + width: k * n.scale, + height: C * n.scale + }; + }; + let S = 0; + const N = 50; + for (const w of o.items) { + if (S >= N) break; + if (!w.transform || w.transform.length < 6) continue; + const x = w.transform[4], k = w.transform[5], C = w.width || 0, L = w.height || Math.abs(w.transform[3]) || 12, q = x + C, W = k + L, E = O(x, k, C, L), P = E.x, I = E.y, F = E.width, R = E.height; + if (P < u || P + F > y || I < T || I + R > j) + continue; + const M = f(w.str); + if (d.has(M)) { + const $ = m.get(M), z = 0.5 + ($ - g) / c * 0.4, _ = document.createElement("div"); + _.className = `word-highlight ${r ? "evidence-word" : ""}`, _.style.left = `${P / n.width * 100}%`, _.style.top = `${I / n.height * 100}%`, _.style.width = `${F / n.width * 100}%`, _.style.height = `${R / n.height * 100}%`, _.style.opacity = z, _.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", _.style.borderRadius = "2px", _.title = `Important word: "${w.str}" (Keyness: ${$.toFixed(3)})`, e.appendChild(_), S++; + } else + for (const $ of d) + if (M.startsWith($) || M.endsWith($)) { + const A = m.get($), _ = 0.5 + (A - g) / c * 0.4, b = document.createElement("div"); + b.className = `word-highlight ${r ? "evidence-word" : ""}`, b.style.left = `${P / n.width * 100}%`, b.style.top = `${I / n.height * 100}%`, b.style.width = `${F / n.width * 100}%`, b.style.height = `${R / n.height * 100}%`, b.style.opacity = _, b.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", b.style.borderRadius = "2px", b.title = `Important word: "${w.str}" (Keyness: ${A.toFixed(3)})`, e.appendChild(b), S++; + break; + } + } + console.log(`Added ${S} word highlights for ${a.length} key words`); + } catch (o) { + console.error("Error adding word-level highlights:", o); + } + } + async navigateToPage(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + this._currentPage = e, await this.render(), this._selectedQuestionId = t, this._showEvidenceOnly = s, requestAnimationFrame(() => { + var r, o; + const i = (r = this.shadowRoot) == null ? void 0 : r.getElementById("question-select"); + i && (i.value = t || ""); + const n = (o = this.shadowRoot) == null ? void 0 : o.getElementById("evidence-filter"); + n && (n.checked = s); + }); + } + async navigateToChunk(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + let i = 1; + if (e.metadata && (e.metadata.page_number !== void 0 ? i = parseInt(e.metadata.page_number) || 1 : e.metadata.source !== void 0 && (i = parseInt(e.metadata.source) || 1)), this._pdfDoc) { + const n = this._pdfDoc.numPages; + i < 1 && (i = 1), i > n && (i = n); + } + await this.navigateToPage(i), this._selectedQuestionId = t, this._showEvidenceOnly = s, this.dispatchEvent(new CustomEvent("chunk-selected", { + detail: { chunk: e, pageNum: i }, + bubbles: !0, + composed: !0 + })); + } + // Public API: Navigate to chunk by ID (for Streamlit communication) + // chunkId format: "question_id_chunk_order" (e.g., "tcfd_1_0") + // Note: question_id may contain underscores, so we split from the right + async navigateToChunkById(e) { + if (!e) return; + const t = e.lastIndexOf("_"); + if (t === -1) { + console.warn(`Invalid chunk ID format: ${e}. Expected format: "question_id_chunk_order"`); + return; + } + const s = e.substring(0, t), i = e.substring(t + 1), n = parseInt(i); + if (isNaN(n)) { + console.warn(`Invalid chunk order in chunk ID: ${e} (parsed as: ${i})`); + return; + } + const r = this._chunks.find((l) => { + const h = l.question_id || "", a = l.chunk_order !== void 0 ? l.chunk_order : -1; + return h === s && (a === n || a === n - 1 || a === n + 1); + }); + if (!r) { + console.warn(`Chunk not found for ID: ${e} (question_id: ${s}, chunk_order: ${n})`), console.debug("Available chunks:", this._chunks.map((l) => ({ + question_id: l.question_id, + chunk_order: l.chunk_order + }))); + return; + } + const o = this._showEvidenceOnly; + this.setSelectedQuestionId(s), await new Promise((l) => setTimeout(l, 100)), await this.navigateToChunk(r), this._showEvidenceOnly = o, this._highlightedChunkId = e; + } + async render() { + if (!this.shadowRoot) return; + const e = this._selectedQuestionId, t = this._showEvidenceOnly, s = this.getFilteredChunks(), i = {}; + s.forEach((o) => { + let l = 1; + o.metadata && (o.metadata.page_number !== void 0 ? l = parseInt(o.metadata.page_number) || 1 : o.metadata.source !== void 0 && (l = parseInt(o.metadata.source) || 1)), i[l] || (i[l] = []), i[l].push(o); + }); + const n = ` + + `, r = ` +
+
+
+

Chunks by Question

+
+ +
+
+ + +
+
+
+ ${s.length === 0 ? '
No chunks to display
' : ""} + ${s.map((o, l) => { + var d, m; + let h = "?"; + o.metadata && (o.metadata.page_number !== void 0 ? h = parseInt(o.metadata.page_number) || "?" : o.metadata.source !== void 0 && (h = parseInt(o.metadata.source) || "?")); + const a = o.is_evidence === !0, p = ((d = o.similarity_score) == null ? void 0 : d.toFixed(3)) || "N/A", g = ((m = o.llm_score) == null ? void 0 : m.toFixed(3)) || "N/A", c = o.text || "", f = c.substring(0, 150) + (c.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${o.chunk_order !== void 0 ? o.chunk_order + 1 : l + 1} +
+ ${a ? 'Evidence' : ""} + Page ${h} +
+
+
${this.escapeHtml(f)}
+
+ Similarity: ${p} + ${o.llm_score !== null && o.llm_score !== void 0 ? `LLM: ${g}` : ""} +
+
+ `; + }).join("")} +
+
+
+
+ + + Page ${this._currentPage} of - + + +
+
+
Loading PDF...
+
+
+
+ `; + this.shadowRoot.innerHTML = n + r, this._selectedQuestionId = e, this._showEvidenceOnly = t, this.setupEventListeners(), setTimeout(() => { + const o = this.shadowRoot.getElementById("question-select"); + o && this._selectedQuestionId !== void 0 && (o.value = this._selectedQuestionId || ""); + const l = this.shadowRoot.getElementById("evidence-filter"); + l && this._showEvidenceOnly !== void 0 && (l.checked = this._showEvidenceOnly); + }, 0), this.loadAndRenderPdf(); + } + escapeHtml(e) { + const t = document.createElement("div"); + return t.textContent = e, t.innerHTML; + } + setupEventListeners() { + const e = this.shadowRoot.getElementById("question-select"); + e && e.addEventListener("change", (n) => { + this.setSelectedQuestionId(n.target.value || null, !0); + }); + const t = this.shadowRoot.getElementById("evidence-filter"); + t && t.addEventListener("change", (n) => { + this.setShowEvidenceOnly(n.target.checked, !0); + }), this.attachChunkListeners(); + const s = this.shadowRoot.getElementById("prev-page"), i = this.shadowRoot.getElementById("next-page"); + s && s.addEventListener("click", () => { + this._currentPage > 1 && this.navigateToPage(this._currentPage - 1); + }), i && i.addEventListener("click", async () => { + if (this._pdfDoc) { + const n = this._pdfDoc.numPages; + this._currentPage < n && await this.navigateToPage(this._currentPage + 1); + } + }); + } + async loadAndRenderPdf() { + try { + this._isLoading = !0, this.updateLoadingDisplay(); + const t = (await this.loadPdf()).numPages, s = this.shadowRoot.getElementById("total-pages"); + s && (s.textContent = t), await this.renderCurrentPage(), this._isLoading = !1; + } catch (e) { + this._isLoading = !1; + const t = this.shadowRoot.getElementById("viewer-content"); + t && (t.innerHTML = `
Error loading PDF: ${e.message}
`); + } + } + async renderCurrentPage() { + const e = this.shadowRoot.getElementById("viewer-content"); + if (e) + try { + const t = await this.loadPdf(), s = t.numPages; + this._currentPage < 1 && (this._currentPage = 1), this._currentPage > s && (this._currentPage = s); + const i = this.shadowRoot.getElementById("current-page"); + i && (i.textContent = this._currentPage); + const n = await this.renderPage(this._currentPage); + if (!n) { + e.innerHTML = '
Error rendering page
'; + return; + } + const r = await t.getPage(this._currentPage), o = r.getViewport({ scale: this._scale }), l = this.getFilteredChunks(), h = l.filter((c) => { + let f = 1; + return c.metadata && (c.metadata.page_number !== void 0 ? f = parseInt(c.metadata.page_number) || 1 : c.metadata.source !== void 0 && (f = parseInt(c.metadata.source) || 1)), f === this._currentPage; + }), a = document.createElement("div"); + a.className = "page-container"; + const p = document.createElement("canvas"); + if (p.className = "page-canvas", p.width = n.width, p.height = n.height, p.getContext("2d").drawImage(n, 0, 0), a.appendChild(p), h.length > 0) { + const c = document.createElement("div"); + c.className = "page-highlights"; + const f = l.map((d) => ({ text: d.text || "" })); + for (const d of h) { + const m = d.text || ""; + if (!m || m.trim().length === 0) + continue; + const v = await this.findChunkTextPositions( + r, + m, + o, + f + ); + if (v.length > 0) + v.forEach((u) => { + const y = document.createElement("div"); + y.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`; + const T = u.x / o.width * 100, j = u.y / o.height * 100, D = u.width / o.width * 100, O = u.height / o.height * 100; + y.style.left = `${T}%`, y.style.top = `${j}%`, y.style.width = `${D}%`, y.style.height = `${O}%`, y.title = d.is_evidence === !0 || d.is_evidence === 1 ? `Evidence chunk: ${m.substring(0, 50)}...` : `Chunk: ${m.substring(0, 50)}...`, c.appendChild(y), u.wordScores && (u.wordScores instanceof Map ? u.wordScores.size > 0 : Object.keys(u.wordScores || {}).length > 0) ? (console.log(`Adding word highlights for chunk with ${u.wordScores instanceof Map ? u.wordScores.size : Object.keys(u.wordScores || {}).length} word scores`), this.addWordLevelHighlights( + c, + r, + u, + u.wordScores, + o, + d.is_evidence === !0 || d.is_evidence === 1 + )) : console.warn("No wordScores found for chunk, skipping word highlights"); + }); + else { + console.warn(`Could not find text position for chunk on page ${this._currentPage}`); + const u = document.createElement("div"); + u.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`, u.style.top = "5%", u.style.left = "5%", u.style.width = "10px", u.style.height = "10px", u.style.borderRadius = "50%", u.title = "Chunk text position not found", c.appendChild(u); + } + } + a.appendChild(c); + } + e.innerHTML = "", e.appendChild(a); + } catch (t) { + console.error("Error rendering current page:", t), e.innerHTML = `
Error rendering page: ${t.message}
`; + } + } +} +customElements.get("pdf-viewer-with-chunks") || customElements.define("pdf-viewer-with-chunks", B); +export { + B as default +}; diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/src/main-pdf-viewer.tsx b/report_analyst_enterprise/components/streamlit_component/frontend/src/main-pdf-viewer.tsx new file mode 100644 index 00000000..1783a63a --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/src/main-pdf-viewer.tsx @@ -0,0 +1,66 @@ +import React, { useEffect, useState } from 'react'; +import ReactDOM from 'react-dom/client'; +import { Streamlit } from 'streamlit-component-lib'; +import PdfViewer from './pdf-viewer'; + +// Call setComponentReady IMMEDIATELY - before React renders +Streamlit.setComponentReady(); + +// Streamlit component entry point +function App() { + const [args, setArgs] = useState({}); + + // Listen for render events from Streamlit + useEffect(() => { + const handleRender = (event: any) => { + // Extract args from the render event + const renderData = event.detail || event; + if (renderData && renderData.args) { + setArgs(renderData.args); + } + }; + + // Listen to Streamlit's event target + Streamlit.events.addEventListener(Streamlit.RENDER_EVENT, handleRender); + + // Also listen on window as fallback + window.addEventListener(Streamlit.RENDER_EVENT, handleRender); + + return () => { + Streamlit.events.removeEventListener(Streamlit.RENDER_EVENT, handleRender); + window.removeEventListener(Streamlit.RENDER_EVENT, handleRender); + }; + }, []); + + // If no args yet, show loading + if (!args || Object.keys(args).length === 0) { + return ( +
+

Loading PDF viewer...

+
+ ); + } + + return ( + + ); +} + +const root = ReactDOM.createRoot( + document.getElementById('root') as HTMLElement +); + +root.render( + + + +); + diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/src/pdf-viewer.tsx b/report_analyst_enterprise/components/streamlit_component/frontend/src/pdf-viewer.tsx new file mode 100644 index 00000000..935f4d7e --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/src/pdf-viewer.tsx @@ -0,0 +1,248 @@ +/** + * PDF Viewer React component for Streamlit + * + * Wraps the framework-agnostic web component for use in Streamlit. + */ + +import React, { useEffect, useRef } from "react"; +import { Streamlit } from "streamlit-component-lib"; + +interface PdfViewerProps { + pdfUrl?: string; + pdfData?: string; + chunks: string; // JSON string + questions: string; // JSON string + selectedQuestionId?: string; + showEvidenceOnly?: boolean; +} + +// Extend HTMLElement to include web component methods +interface PdfViewerElement extends HTMLElement { + setPdfUrl(url: string): void; + setPdfData(data: string): void; + setChunks(chunks: any[]): void; + setQuestions(questions: any[]): void; + setSelectedQuestionId(questionId: string | null): void; + setShowEvidenceOnly(show: boolean): void; + navigateToPage(pageNum: number): Promise; + navigateToChunk(chunk: any): Promise; + navigateToChunkById(chunkId: string): Promise; +} + +const PdfViewer: React.FC = (props) => { + const viewerRef = useRef(null); + const containerRef = useRef(null); + const heightUpdateTimeoutRef = useRef(null); + const lastHeightRef = useRef(0); + const observerRef = useRef(null); + + // Parse props + const chunks = JSON.parse(props.chunks || "[]"); + const questions = JSON.parse(props.questions || "[]"); + + // Debounced height update function + const updateFrameHeight = React.useCallback(() => { + if (heightUpdateTimeoutRef.current) { + clearTimeout(heightUpdateTimeoutRef.current); + } + + heightUpdateTimeoutRef.current = setTimeout(() => { + try { + const container = containerRef.current; + if (!container) return; + + const height = Math.max( + container.offsetHeight || container.scrollHeight || 800, + 800 // minimum height + ); + + if (Math.abs(height - lastHeightRef.current) > 50 || lastHeightRef.current === 0) { + lastHeightRef.current = height; + Streamlit.setFrameHeight(height); + } + } catch (e) { + console.debug('Could not set frame height yet:', e); + } + }, 150); + }, []); + + useEffect(() => { + // Load web component script if not already loaded + const loadWebComponent = async () => { + // Check if web component is already defined + if (customElements.get('pdf-viewer-with-chunks')) { + createViewerElement(); + return; + } + + // Load PDF.js first + if (typeof window.pdfjsLib === 'undefined') { + const pdfjsScript = document.createElement('script'); + pdfjsScript.src = 'https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.min.js'; + pdfjsScript.async = true; + await new Promise((resolve, reject) => { + pdfjsScript.onload = resolve; + pdfjsScript.onerror = reject; + document.head.appendChild(pdfjsScript); + }); + } + + // Load the web component script + const script = document.createElement('script'); + script.type = 'module'; + script.src = './pdf-viewer.es.js'; + + const waitForCustomElement = (maxAttempts = 50) => { + let attempts = 0; + const check = () => { + if (customElements.get('pdf-viewer-with-chunks')) { + createViewerElement(); + } else if (attempts < maxAttempts) { + attempts++; + setTimeout(check, 100); + } else { + console.error('Custom element pdf-viewer-with-chunks not defined after loading script'); + } + }; + setTimeout(check, 100); + }; + + script.onload = () => { + waitForCustomElement(); + }; + script.onerror = (e) => { + console.error('Failed to load web component from', script.src, e); + // Try absolute path as fallback (for dev server) + const fallbackScript = document.createElement('script'); + fallbackScript.type = 'module'; + fallbackScript.src = '/pdf-viewer.es.js'; + fallbackScript.onload = () => { + waitForCustomElement(); + }; + fallbackScript.onerror = (e2) => { + console.error('Failed to load web component from fallback path:', e2); + }; + document.head.appendChild(fallbackScript); + }; + document.head.appendChild(script); + }; + + const createViewerElement = () => { + if (!containerRef.current) return; + + // Remove existing viewer if any + const existing = containerRef.current.querySelector('pdf-viewer-with-chunks'); + if (existing) { + existing.remove(); + } + + // Disconnect previous observer + if (observerRef.current) { + observerRef.current.disconnect(); + observerRef.current = null; + } + + // Create web component element + const viewerElement = document.createElement('pdf-viewer-with-chunks') as PdfViewerElement; + viewerRef.current = viewerElement; + + // Set properties + if (props.pdfUrl) { + viewerElement.setPdfUrl(props.pdfUrl); + } else if (props.pdfData) { + viewerElement.setPdfData(props.pdfData); + } + viewerElement.setChunks(chunks); + viewerElement.setQuestions(questions); + if (props.selectedQuestionId) { + viewerElement.setSelectedQuestionId(props.selectedQuestionId); + } + viewerElement.setShowEvidenceOnly(props.showEvidenceOnly || false); + + // Set up event listeners + const handleChunkSelected = (e: CustomEvent) => { + Streamlit.setComponentValue({ + type: "chunk-selected", + chunk: e.detail.chunk, + pageNum: e.detail.pageNum, + }); + updateFrameHeight(); + }; + + viewerElement.addEventListener('chunk-selected', handleChunkSelected as EventListener); + + // Append to container + containerRef.current.appendChild(viewerElement); + + // Set up mutation observer for dynamic height updates + observerRef.current = new MutationObserver(() => { + updateFrameHeight(); + }); + + if (containerRef.current) { + observerRef.current.observe(containerRef.current, { + childList: true, + subtree: true, + attributes: false + }); + } + + // Initial height update + setTimeout(updateFrameHeight, 500); + }; + + loadWebComponent(); + + // Update when props change + if (viewerRef.current) { + if (props.pdfUrl) { + viewerRef.current.setPdfUrl(props.pdfUrl); + } else if (props.pdfData) { + viewerRef.current.setPdfData(props.pdfData); + } + viewerRef.current.setChunks(chunks); + viewerRef.current.setQuestions(questions); + if (props.selectedQuestionId) { + viewerRef.current.setSelectedQuestionId(props.selectedQuestionId); + } + viewerRef.current.setShowEvidenceOnly(props.showEvidenceOnly || false); + updateFrameHeight(); + } + + return () => { + // Cleanup + if (heightUpdateTimeoutRef.current) { + clearTimeout(heightUpdateTimeoutRef.current); + } + if (observerRef.current) { + observerRef.current.disconnect(); + observerRef.current = null; + } + if (viewerRef.current) { + viewerRef.current.remove(); + viewerRef.current = null; + } + }; + }, [props.pdfUrl, props.pdfData, props.chunks, props.questions, props.selectedQuestionId, props.showEvidenceOnly, chunks, questions, updateFrameHeight]); + + // Watch for highlightChunkId changes and navigate to chunk + useEffect(() => { + if (props.highlightChunkId && viewerRef.current) { + viewerRef.current.navigateToChunkById(props.highlightChunkId); + updateFrameHeight(); + } + }, [props.highlightChunkId, updateFrameHeight]); + + return ( +
+ ); +}; + +export default PdfViewer; + diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/tsconfig.json b/report_analyst_enterprise/components/streamlit_component/frontend/tsconfig.json new file mode 100644 index 00000000..b3ab8bb4 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/tsconfig.json @@ -0,0 +1,18 @@ +{ + "compilerOptions": { + "target": "ES2020", + "lib": ["ES2020", "DOM", "DOM.Iterable"], + "jsx": "react", + "module": "ESNext", + "moduleResolution": "node", + "strict": true, + "esModuleInterop": true, + "skipLibCheck": true, + "forceConsistentCasingInFileNames": true, + "resolveJsonModule": true + }, + "include": ["src"], + "exclude": ["node_modules", "build"] +} + + diff --git a/report_analyst_enterprise/components/streamlit_component/frontend/vite.config.pdf-viewer.ts b/report_analyst_enterprise/components/streamlit_component/frontend/vite.config.pdf-viewer.ts new file mode 100644 index 00000000..57035d58 --- /dev/null +++ b/report_analyst_enterprise/components/streamlit_component/frontend/vite.config.pdf-viewer.ts @@ -0,0 +1,76 @@ +import { defineConfig } from 'vite'; +import react from '@vitejs/plugin-react'; +import { copyFileSync, existsSync } from 'fs'; +import { join } from 'path'; + +export default defineConfig({ + plugins: [ + react(), + // Plugin to copy web component to build directory + { + name: 'copy-web-component', + writeBundle() { + const webComponentPath = join(__dirname, '../../web/dist/pdf-viewer.es.js'); + const publicPath = join(__dirname, 'public/pdf-viewer.es.js'); + const buildPath = join(__dirname, 'build/pdf-viewer.es.js'); + + // Copy to public for dev server + if (existsSync(webComponentPath)) { + try { + copyFileSync(webComponentPath, publicPath); + console.log('✓ Copied PDF viewer web component to public/'); + } catch (e) { + console.warn('Could not copy PDF viewer web component to public:', e); + } + } + + // Copy to build for production + if (existsSync(webComponentPath)) { + try { + copyFileSync(webComponentPath, buildPath); + console.log('✓ Copied PDF viewer web component to build/'); + } catch (e) { + console.warn('Could not copy PDF viewer web component to build:', e); + } + } + }, + }, + ], + define: { + 'process.env': '{}', + 'process': JSON.stringify({ env: {} }), + }, + build: { + outDir: 'build', + emptyOutDir: false, // Don't clean build directory to preserve other components files + rollupOptions: { + input: 'index-pdf-viewer.html', // Use PDF viewer HTML as entry point + output: { + entryFileNames: 'index-pdf-viewer.js', + format: 'es', + }, + }, + // Copy pdf-viewer.es.js to build directory + copyPublicDir: true, + // Ensure relative paths in HTML + base: './', + commonjsOptions: { + include: [/node_modules/], + transformMixedEsModules: true, + strictRequires: true, + }, + target: 'es2020', + }, + optimizeDeps: { + include: ['react', 'react-dom', 'streamlit-component-lib'], + esbuildOptions: { + target: 'es2020', + }, + }, + server: { + port: 3002, // Different port from other components + cors: true, + }, + publicDir: 'public', +}); + diff --git a/report_analyst_enterprise/components/web/dist/pdf-viewer.es.js b/report_analyst_enterprise/components/web/dist/pdf-viewer.es.js new file mode 100644 index 00000000..e90ea722 --- /dev/null +++ b/report_analyst_enterprise/components/web/dist/pdf-viewer.es.js @@ -0,0 +1,985 @@ +class B extends HTMLElement { + constructor() { + super(), this.attachShadow({ mode: "open" }), this._pdfUrl = null, this._pdfData = null, this._chunks = [], this._questions = [], this._selectedQuestionId = null, this._showEvidenceOnly = !1, this._pdfDoc = null, this._currentPage = 1, this._scale = 1.5, this._pdfjsLib = null, this._renderedPages = /* @__PURE__ */ new Map(), this._isLoading = !1, this._highlightedChunkId = null; + } + static get observedAttributes() { + return ["pdf-url", "pdf-data", "chunks", "questions", "selected-question-id", "show-evidence-only"]; + } + connectedCallback() { + this.loadPdfJs().then(() => { + this.render(); + }); + } + disconnectedCallback() { + this._renderedPages.clear(), this._pdfDoc && (this._pdfDoc.destroy(), this._pdfDoc = null); + } + attributeChangedCallback(e, t, s) { + if (t !== s) + try { + e === "pdf-url" ? (this._pdfUrl = s, this._pdfData = null) : e === "pdf-data" ? (this._pdfData = s, this._pdfUrl = null) : e === "chunks" ? this._chunks = s ? JSON.parse(s) : [] : e === "questions" ? this._questions = s ? JSON.parse(s) : [] : e === "selected-question-id" ? this._selectedQuestionId = s : e === "show-evidence-only" && (this._showEvidenceOnly = s === "true" || s === ""), this._skipAttributeRender || this.render(); + } catch (i) { + console.error(`Error parsing ${e}:`, i); + } + } + // Public API: Set PDF URL + setPdfUrl(e) { + this._pdfUrl = e, this._pdfData = null, this.setAttribute("pdf-url", e); + } + // Public API: Set PDF data (base64) + setPdfData(e) { + this._pdfData = e, this._pdfUrl = null, this.setAttribute("pdf-data", e); + } + // Public API: Set chunks + setChunks(e) { + this._chunks = e, this.setAttribute("chunks", JSON.stringify(e)); + } + // Public API: Set questions + setQuestions(e) { + this._questions = e, this.setAttribute("questions", JSON.stringify(e)); + } + // Public API: Set selected question + setSelectedQuestionId(e, t = !1) { + this._selectedQuestionId = e, t ? (this._skipAttributeRender = !0, this.setAttribute("selected-question-id", e || ""), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("selected-question-id", e || ""); + } + // Public API: Set evidence filter + setShowEvidenceOnly(e, t = !1) { + this._showEvidenceOnly = e, t ? (this._skipAttributeRender = !0, this.setAttribute("show-evidence-only", e ? "true" : "false"), this._skipAttributeRender = !1, this.updateFilterUI()) : this.setAttribute("show-evidence-only", e ? "true" : "false"); + } + // Update filter UI without full render + updateFilterUI() { + var s, i; + const e = (s = this.shadowRoot) == null ? void 0 : s.getElementById("question-select"); + e && (e.value = this._selectedQuestionId || ""); + const t = (i = this.shadowRoot) == null ? void 0 : i.getElementById("evidence-filter"); + t && (t.checked = this._showEvidenceOnly), this.renderChunkList(); + } + // Render only the chunk list without re-rendering PDF + renderChunkList() { + var s; + const e = (s = this.shadowRoot) == null ? void 0 : s.querySelector(".chunks-list"); + if (!e) return; + const t = this.getFilteredChunks(); + e.innerHTML = t.length === 0 ? '
No chunks to display
' : t.map((i, n) => { + var g, c; + let r = "?"; + i.metadata && (i.metadata.page_number !== void 0 ? r = parseInt(i.metadata.page_number) || "?" : i.metadata.source !== void 0 && (r = parseInt(i.metadata.source) || "?")); + const o = i.is_evidence === !0, l = ((g = i.similarity_score) == null ? void 0 : g.toFixed(3)) || "N/A", h = ((c = i.llm_score) == null ? void 0 : c.toFixed(3)) || "N/A", a = i.text || "", p = a.substring(0, 150) + (a.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${i.chunk_order !== void 0 ? i.chunk_order + 1 : n + 1} +
+ ${o ? 'Evidence' : ""} + Page ${r} +
+
+
${this.escapeHtml(p)}
+
+ Similarity: ${l} + ${i.llm_score !== null && i.llm_score !== void 0 ? `LLM: ${h}` : ""} +
+
+ `; + }).join(""), this.attachChunkListeners(); + } + // Attach click listeners to chunk items + attachChunkListeners() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.querySelectorAll(".chunk-item"); + e && e.forEach((s) => { + var n; + const i = s.cloneNode(!0); + (n = s.parentNode) == null || n.replaceChild(i, s), i.addEventListener("click", () => { + const r = parseInt(i.dataset.chunkIndex), o = this.getFilteredChunks()[r]; + o && this.navigateToChunk(o); + }); + }); + } + async loadPdfJs() { + if (!this._pdfjsLib) { + if (typeof pdfjsLib > "u") { + const e = document.createElement("script"); + e.src = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.min.js", e.async = !0, await new Promise((t, s) => { + e.onload = t, e.onerror = s, document.head.appendChild(e); + }); + } + this._pdfjsLib = window.pdfjsLib || pdfjsLib, this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.workerSrc = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.worker.min.js"), this._pdfjsLib.GlobalWorkerOptions && (this._pdfjsLib.GlobalWorkerOptions.cMapUrl = "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", this._pdfjsLib.GlobalWorkerOptions.cMapPacked = !0); + } + } + async loadPdf() { + if (this._pdfjsLib || await this.loadPdfJs(), this._pdfDoc) + return this._pdfDoc; + this._isLoading = !0, this.updateLoadingDisplay(); + try { + let e; + const t = { + cMapUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/", + cMapPacked: !0, + standardFontDataUrl: "https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/standard_fonts/" + }; + if (this._pdfData) { + const s = this._pdfData.replace(/^data:application\/pdf;base64,/, ""), i = atob(s), n = new Uint8Array(i.length); + for (let r = 0; r < i.length; r++) + n[r] = i.charCodeAt(r); + e = this._pdfjsLib.getDocument({ + data: n, + ...t + }); + } else if (this._pdfUrl) + e = this._pdfjsLib.getDocument({ + url: this._pdfUrl, + ...t + }); + else + throw new Error("No PDF URL or data provided"); + return this._pdfDoc = await e.promise, this._pdfDoc; + } catch (e) { + throw console.error("Error loading PDF:", e), e; + } + } + updateLoadingDisplay() { + var t; + const e = (t = this.shadowRoot) == null ? void 0 : t.getElementById("viewer-content"); + e && this._isLoading && (e.innerHTML = ` +
+ +
Loading PDF...
+
+ `); + } + getFilteredChunks() { + let e = []; + if (this._selectedQuestionId) { + const t = this._questions.find((s) => s.question_id === this._selectedQuestionId); + t && t.chunks ? e = t.chunks : e = this._chunks.filter((s) => s.question_id === this._selectedQuestionId); + } else + e = this._chunks; + return this._showEvidenceOnly && (e = e.filter((t) => t.is_evidence === !0 || t.is_evidence === 1)), e; + } + async renderPage(e) { + if (this._renderedPages.has(e)) + return this._renderedPages.get(e); + try { + const s = await (await this.loadPdf()).getPage(e), i = s.getViewport({ scale: this._scale }), n = document.createElement("canvas"), r = n.getContext("2d"); + return n.height = i.height, n.width = i.width, await s.render({ + canvasContext: r, + viewport: i + }).promise, this._renderedPages.set(e, n), n; + } catch (t) { + return console.error(`Error rendering page ${e}:`, t), null; + } + } + /** + * Calculate log-likelihood keyness scores for words + * Identifies words that are unusually frequent in this chunk compared to other chunks + * Uses Dunning's log-likelihood (G²) statistic + * @param {string} chunkText - The chunk text to analyze + * @param {Array} allChunks - All chunk texts for comparison + * @returns {Map} Map of word to keyness score + */ + calculateKeyness(e, t = []) { + const s = (c) => c.toLowerCase().replace(/[^\w\s]/g, " ").split(/\s+/).filter((f) => f.length > 2), i = s(e), n = /* @__PURE__ */ new Map(); + if (i.forEach((c) => { + n.set(c, (n.get(c) || 0) + 1); + }), t.length === 0) { + const c = Array.from(n.entries()).sort((f, d) => d[1] - f[1]).slice(0, 10); + return new Map(c); + } + const r = [], o = /* @__PURE__ */ new Map(); + t.forEach((c) => { + s(c.text || c).forEach((d) => { + r.push(d), o.set(d, (o.get(d) || 0) + 1); + }); + }); + const l = /* @__PURE__ */ new Map(), h = i.length, a = r.length, p = h + a; + return (/* @__PURE__ */ new Set([...i, ...r])).forEach((c) => { + const f = n.get(c) || 0, d = o.get(c) || 0; + if (f === 0) + return; + const m = (f + d) * (h / p), v = (f + d) * (a / p); + let u = 0; + f > 0 && m > 0 && (u += 2 * f * Math.log(f / m)), d > 0 && v > 0 && (u += 2 * d * Math.log(d / v)), u > 0.01 && f > m && l.set(c, u); + }), l; + } + /** + * Get word-level importance scores for highlighting + * Uses log-likelihood keyness to identify words unusually frequent in this chunk + * @param {string} chunkText - The chunk text + * @param {Array} allChunks - All chunks for comparison + * @returns {Map} Word to keyness score + */ + getWordImportanceScores(e, t = []) { + return this.calculateKeyness(e, t); + } + /** + * Find text positions for a chunk in the PDF page + * Uses exact matching first, falls back to embedding-based semantic matching + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @param {Array} allChunks - All chunks for context (optional, for TF-IDF) + * @returns {Array} Array of bounding boxes {x, y, width, height, wordScores} in viewport coordinates + */ + async findChunkTextPositions(e, t, s, i = []) { + const n = await this.findChunkTextPositionsExact(e, t, s); + if (n.length > 0) { + const r = this.getWordImportanceScores(t, i); + return n.forEach((o) => { + o.wordScores = r; + }), n; + } + return []; + } + /** + * Exact text matching (original implementation) + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @returns {Array} Array of bounding boxes + */ + async findChunkTextPositionsExact(e, t, s) { + try { + const i = await e.getTextContent(); + if (!i || !i.items || i.items.length === 0) + return console.warn("No text content found on page"), []; + const n = (g) => g.toLowerCase().trim().replace(/\s+/g, " "), r = n(t); + if (!r || r.length < 10) + return console.warn("Chunk text too short for reliable matching"), []; + const o = i.items, l = o.map((g) => g.str).join(" "), h = n(l); + let a = h.indexOf(r), p = r; + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(20, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + if (a === -1) { + const g = r.split(" "), c = g.slice(0, Math.min(10, g.length)).join(" "); + a = h.indexOf(c), a !== -1 && (p = c); + } + return a === -1 ? (console.warn(`Chunk text not found on page: "${t.substring(0, 50)}..."`), []) : this.findTextItemPositions(o, p, a, h, s, n); + } catch (i) { + return console.error("Error finding chunk text positions:", i), []; + } + } + /** + * Find text item positions that match the search text + * @param {Array} textItems - Array of text items from PDF.js + * @param {string} searchText - Normalized text to search for + * @param {number} textIndex - Character index where searchText was found in normalized text + * @param {string} normalizedAllText - Full normalized text from all items + * @param {Object} viewport - PDF.js viewport object + * @param {Function} normalizeText - Text normalization function + * @returns {Array} Array of bounding boxes + */ + findTextItemPositions(e, t, s, i, n, r) { + const o = []; + let l = 0; + const h = []; + for (let a = 0; a < e.length; a++) { + const p = e[a], g = r(p.str), c = g.length + 1; + if (l + g.length >= s && l <= s + t.length && h.push(p), l += c, l > s + t.length) + break; + } + if (h.length === 0) { + const a = t.split(" ").slice(0, 5).join(" "); + let p = ""; + for (const g of e) { + const c = r(g.str); + if (p += c + " ", h.push(g), r(p).includes(a)) + break; + if (h.length > 50) { + h.length = 0; + break; + } + } + } + if (h.length > 0) { + const a = this.calculateBoundingBox(h, n); + a && a.width > 0 && a.height > 0 && o.push(a); + } + return o; + } + /** + * Calculate bounding box from text items and convert to viewport coordinates + * @param {Array} textItems - Array of text items that form the match + * @param {Object} viewport - PDF.js viewport object + * @returns {Object|null} Bounding box {x, y, width, height} in viewport coordinates, or null + */ + calculateBoundingBox(e, t) { + if (!e || e.length === 0) + return null; + let s = 1 / 0, i = 1 / 0, n = -1 / 0, r = -1 / 0; + for (const d of e) + if (d.transform && d.transform.length >= 6) { + const m = d.transform[4], v = d.transform[5], u = d.width || 0, y = d.height || Math.abs(d.transform[3]) || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } else if (d.x !== void 0 && d.y !== void 0) { + const m = d.x, v = d.y, u = d.width || 0, y = d.height || 12; + s = Math.min(s, m), i = Math.min(i, v), n = Math.max(n, m + u), r = Math.max(r, v + y); + } + if (s === 1 / 0 || i === 1 / 0) + return null; + let o, l, h, a; + if (t.convertToViewportPoint) + [o, l] = t.convertToViewportPoint(s, i), [h, a] = t.convertToViewportPoint(n, r); + else { + const d = t.height / t.scale; + o = s * t.scale, l = (d - r) * t.scale, h = n * t.scale, a = (d - i) * t.scale; + } + const p = Math.min(o, h), g = Math.min(l, a), c = Math.abs(h - o), f = Math.abs(a - l); + return c < 1 || f < 1 ? null : { x: p, y: g, width: c, height: f }; + } + /** + * Add word-level highlights based on TF-IDF scores + * Highlights individual words within the matched text region + * @param {HTMLElement} container - Container to add highlights to + * @param {Object} page - PDF.js page object + * @param {Object} bbox - Bounding box of matched text + * @param {Map} wordScores - Map of word to TF-IDF score + * @param {Object} viewport - PDF.js viewport + * @param {boolean} isEvidence - Whether this is an evidence chunk + */ + async addWordLevelHighlights(e, t, s, i, n, r) { + try { + const o = await t.getTextContent(); + if (!o || !o.items) + return; + const l = /* @__PURE__ */ new Set([ + "the", + "be", + "to", + "of", + "and", + "a", + "in", + "that", + "have", + "i", + "it", + "for", + "not", + "on", + "with", + "he", + "as", + "you", + "do", + "at", + "this", + "but", + "his", + "by", + "from", + "they", + "we", + "say", + "her", + "she", + "or", + "an", + "will", + "my", + "one", + "all", + "would", + "there", + "their", + "what", + "so", + "up", + "out", + "if", + "about", + "who", + "get", + "which", + "go", + "me", + "when", + "make", + "can", + "like", + "time", + "no", + "just", + "him", + "know", + "take", + "people", + "into", + "year", + "your", + "good", + "some", + "could", + "them", + "see", + "other", + "than", + "then", + "now", + "look", + "only", + "come", + "its", + "over", + "think", + "also", + "back", + "after", + "use", + "two", + "how", + "our", + "work", + "first", + "well", + "way", + "even", + "new", + "want", + "because", + "any", + "these", + "give", + "day", + "most", + "us", + "is", + "are", + "was", + "were", + "been", + "being", + "has", + "had", + "does", + "did", + "may", + "might", + "must", + "shall", + "should", + "could", + "would", + "can", + "cannot", + "will", + "shall" + ]); + let h = i; + i instanceof Map || (h = new Map(Object.entries(i || {}))); + const a = Array.from(h.entries()).sort((w, x) => x[1] - w[1]).slice(0, 10); + if (a.length === 0) { + console.warn("No key words found for highlighting - keyness scores may be empty. WordScores:", h); + return; + } + console.log(`Found ${a.length} key words for highlighting:`, a.map(([w, x]) => `${w}(${x.toFixed(3)})`)); + const p = a[0][1], g = a[a.length - 1][1], c = p - g || 1, f = (w) => w.toLowerCase().replace(/[^\w]/g, ""), d = /* @__PURE__ */ new Set(), m = /* @__PURE__ */ new Map(); + if (a.forEach(([w, x]) => { + const k = f(w); + k.length >= 3 && (d.add(k), m.set(k, x)); + }), d.size === 0) + return; + const v = 0.1, u = s.x - s.width * v, y = s.x + s.width + s.width * v, T = s.y - s.height * v, j = s.y + s.height + s.height * v, D = n.height / n.scale, O = (w, x, k, C) => { + if (n.convertToViewportPoint) { + const [L, q] = n.convertToViewportPoint(w, x), W = w + k, E = x + C, [P, I] = n.convertToViewportPoint(W, E); + return { + x: L, + y: q, + width: Math.abs(P - L), + height: Math.abs(I - q) + }; + } else + return { + x: w * n.scale, + y: (D - (x + C)) * n.scale, + width: k * n.scale, + height: C * n.scale + }; + }; + let S = 0; + const N = 50; + for (const w of o.items) { + if (S >= N) break; + if (!w.transform || w.transform.length < 6) continue; + const x = w.transform[4], k = w.transform[5], C = w.width || 0, L = w.height || Math.abs(w.transform[3]) || 12, q = x + C, W = k + L, E = O(x, k, C, L), P = E.x, I = E.y, F = E.width, R = E.height; + if (P < u || P + F > y || I < T || I + R > j) + continue; + const M = f(w.str); + if (d.has(M)) { + const $ = m.get(M), z = 0.5 + ($ - g) / c * 0.4, _ = document.createElement("div"); + _.className = `word-highlight ${r ? "evidence-word" : ""}`, _.style.left = `${P / n.width * 100}%`, _.style.top = `${I / n.height * 100}%`, _.style.width = `${F / n.width * 100}%`, _.style.height = `${R / n.height * 100}%`, _.style.opacity = z, _.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", _.style.borderRadius = "2px", _.title = `Important word: "${w.str}" (Keyness: ${$.toFixed(3)})`, e.appendChild(_), S++; + } else + for (const $ of d) + if (M.startsWith($) || M.endsWith($)) { + const A = m.get($), _ = 0.5 + (A - g) / c * 0.4, b = document.createElement("div"); + b.className = `word-highlight ${r ? "evidence-word" : ""}`, b.style.left = `${P / n.width * 100}%`, b.style.top = `${I / n.height * 100}%`, b.style.width = `${F / n.width * 100}%`, b.style.height = `${R / n.height * 100}%`, b.style.opacity = _, b.style.backgroundColor = r ? "rgba(255, 200, 0, 0.7)" : "rgba(255, 255, 0, 0.6)", b.style.borderRadius = "2px", b.title = `Important word: "${w.str}" (Keyness: ${A.toFixed(3)})`, e.appendChild(b), S++; + break; + } + } + console.log(`Added ${S} word highlights for ${a.length} key words`); + } catch (o) { + console.error("Error adding word-level highlights:", o); + } + } + async navigateToPage(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + this._currentPage = e, await this.render(), this._selectedQuestionId = t, this._showEvidenceOnly = s, requestAnimationFrame(() => { + var r, o; + const i = (r = this.shadowRoot) == null ? void 0 : r.getElementById("question-select"); + i && (i.value = t || ""); + const n = (o = this.shadowRoot) == null ? void 0 : o.getElementById("evidence-filter"); + n && (n.checked = s); + }); + } + async navigateToChunk(e) { + const t = this._selectedQuestionId, s = this._showEvidenceOnly; + let i = 1; + if (e.metadata && (e.metadata.page_number !== void 0 ? i = parseInt(e.metadata.page_number) || 1 : e.metadata.source !== void 0 && (i = parseInt(e.metadata.source) || 1)), this._pdfDoc) { + const n = this._pdfDoc.numPages; + i < 1 && (i = 1), i > n && (i = n); + } + await this.navigateToPage(i), this._selectedQuestionId = t, this._showEvidenceOnly = s, this.dispatchEvent(new CustomEvent("chunk-selected", { + detail: { chunk: e, pageNum: i }, + bubbles: !0, + composed: !0 + })); + } + // Public API: Navigate to chunk by ID (for Streamlit communication) + // chunkId format: "question_id_chunk_order" (e.g., "tcfd_1_0") + // Note: question_id may contain underscores, so we split from the right + async navigateToChunkById(e) { + if (!e) return; + const t = e.lastIndexOf("_"); + if (t === -1) { + console.warn(`Invalid chunk ID format: ${e}. Expected format: "question_id_chunk_order"`); + return; + } + const s = e.substring(0, t), i = e.substring(t + 1), n = parseInt(i); + if (isNaN(n)) { + console.warn(`Invalid chunk order in chunk ID: ${e} (parsed as: ${i})`); + return; + } + const r = this._chunks.find((l) => { + const h = l.question_id || "", a = l.chunk_order !== void 0 ? l.chunk_order : -1; + return h === s && (a === n || a === n - 1 || a === n + 1); + }); + if (!r) { + console.warn(`Chunk not found for ID: ${e} (question_id: ${s}, chunk_order: ${n})`), console.debug("Available chunks:", this._chunks.map((l) => ({ + question_id: l.question_id, + chunk_order: l.chunk_order + }))); + return; + } + const o = this._showEvidenceOnly; + this.setSelectedQuestionId(s), await new Promise((l) => setTimeout(l, 100)), await this.navigateToChunk(r), this._showEvidenceOnly = o, this._highlightedChunkId = e; + } + async render() { + if (!this.shadowRoot) return; + const e = this._selectedQuestionId, t = this._showEvidenceOnly, s = this.getFilteredChunks(), i = {}; + s.forEach((o) => { + let l = 1; + o.metadata && (o.metadata.page_number !== void 0 ? l = parseInt(o.metadata.page_number) || 1 : o.metadata.source !== void 0 && (l = parseInt(o.metadata.source) || 1)), i[l] || (i[l] = []), i[l].push(o); + }); + const n = ` + + `, r = ` +
+
+
+

Chunks by Question

+
+ +
+
+ + +
+
+
+ ${s.length === 0 ? '
No chunks to display
' : ""} + ${s.map((o, l) => { + var d, m; + let h = "?"; + o.metadata && (o.metadata.page_number !== void 0 ? h = parseInt(o.metadata.page_number) || "?" : o.metadata.source !== void 0 && (h = parseInt(o.metadata.source) || "?")); + const a = o.is_evidence === !0, p = ((d = o.similarity_score) == null ? void 0 : d.toFixed(3)) || "N/A", g = ((m = o.llm_score) == null ? void 0 : m.toFixed(3)) || "N/A", c = o.text || "", f = c.substring(0, 150) + (c.length > 150 ? "..." : ""); + return ` +
+
+ Chunk ${o.chunk_order !== void 0 ? o.chunk_order + 1 : l + 1} +
+ ${a ? 'Evidence' : ""} + Page ${h} +
+
+
${this.escapeHtml(f)}
+
+ Similarity: ${p} + ${o.llm_score !== null && o.llm_score !== void 0 ? `LLM: ${g}` : ""} +
+
+ `; + }).join("")} +
+
+
+
+ + + Page ${this._currentPage} of - + + +
+
+
Loading PDF...
+
+
+
+ `; + this.shadowRoot.innerHTML = n + r, this._selectedQuestionId = e, this._showEvidenceOnly = t, this.setupEventListeners(), setTimeout(() => { + const o = this.shadowRoot.getElementById("question-select"); + o && this._selectedQuestionId !== void 0 && (o.value = this._selectedQuestionId || ""); + const l = this.shadowRoot.getElementById("evidence-filter"); + l && this._showEvidenceOnly !== void 0 && (l.checked = this._showEvidenceOnly); + }, 0), this.loadAndRenderPdf(); + } + escapeHtml(e) { + const t = document.createElement("div"); + return t.textContent = e, t.innerHTML; + } + setupEventListeners() { + const e = this.shadowRoot.getElementById("question-select"); + e && e.addEventListener("change", (n) => { + this.setSelectedQuestionId(n.target.value || null, !0); + }); + const t = this.shadowRoot.getElementById("evidence-filter"); + t && t.addEventListener("change", (n) => { + this.setShowEvidenceOnly(n.target.checked, !0); + }), this.attachChunkListeners(); + const s = this.shadowRoot.getElementById("prev-page"), i = this.shadowRoot.getElementById("next-page"); + s && s.addEventListener("click", () => { + this._currentPage > 1 && this.navigateToPage(this._currentPage - 1); + }), i && i.addEventListener("click", async () => { + if (this._pdfDoc) { + const n = this._pdfDoc.numPages; + this._currentPage < n && await this.navigateToPage(this._currentPage + 1); + } + }); + } + async loadAndRenderPdf() { + try { + this._isLoading = !0, this.updateLoadingDisplay(); + const t = (await this.loadPdf()).numPages, s = this.shadowRoot.getElementById("total-pages"); + s && (s.textContent = t), await this.renderCurrentPage(), this._isLoading = !1; + } catch (e) { + this._isLoading = !1; + const t = this.shadowRoot.getElementById("viewer-content"); + t && (t.innerHTML = `
Error loading PDF: ${e.message}
`); + } + } + async renderCurrentPage() { + const e = this.shadowRoot.getElementById("viewer-content"); + if (e) + try { + const t = await this.loadPdf(), s = t.numPages; + this._currentPage < 1 && (this._currentPage = 1), this._currentPage > s && (this._currentPage = s); + const i = this.shadowRoot.getElementById("current-page"); + i && (i.textContent = this._currentPage); + const n = await this.renderPage(this._currentPage); + if (!n) { + e.innerHTML = '
Error rendering page
'; + return; + } + const r = await t.getPage(this._currentPage), o = r.getViewport({ scale: this._scale }), l = this.getFilteredChunks(), h = l.filter((c) => { + let f = 1; + return c.metadata && (c.metadata.page_number !== void 0 ? f = parseInt(c.metadata.page_number) || 1 : c.metadata.source !== void 0 && (f = parseInt(c.metadata.source) || 1)), f === this._currentPage; + }), a = document.createElement("div"); + a.className = "page-container"; + const p = document.createElement("canvas"); + if (p.className = "page-canvas", p.width = n.width, p.height = n.height, p.getContext("2d").drawImage(n, 0, 0), a.appendChild(p), h.length > 0) { + const c = document.createElement("div"); + c.className = "page-highlights"; + const f = l.map((d) => ({ text: d.text || "" })); + for (const d of h) { + const m = d.text || ""; + if (!m || m.trim().length === 0) + continue; + const v = await this.findChunkTextPositions( + r, + m, + o, + f + ); + if (v.length > 0) + v.forEach((u) => { + const y = document.createElement("div"); + y.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`; + const T = u.x / o.width * 100, j = u.y / o.height * 100, D = u.width / o.width * 100, O = u.height / o.height * 100; + y.style.left = `${T}%`, y.style.top = `${j}%`, y.style.width = `${D}%`, y.style.height = `${O}%`, y.title = d.is_evidence === !0 || d.is_evidence === 1 ? `Evidence chunk: ${m.substring(0, 50)}...` : `Chunk: ${m.substring(0, 50)}...`, c.appendChild(y), u.wordScores && (u.wordScores instanceof Map ? u.wordScores.size > 0 : Object.keys(u.wordScores || {}).length > 0) ? (console.log(`Adding word highlights for chunk with ${u.wordScores instanceof Map ? u.wordScores.size : Object.keys(u.wordScores || {}).length} word scores`), this.addWordLevelHighlights( + c, + r, + u, + u.wordScores, + o, + d.is_evidence === !0 || d.is_evidence === 1 + )) : console.warn("No wordScores found for chunk, skipping word highlights"); + }); + else { + console.warn(`Could not find text position for chunk on page ${this._currentPage}`); + const u = document.createElement("div"); + u.className = `highlight ${d.is_evidence === !0 || d.is_evidence === 1 ? "evidence" : ""}`, u.style.top = "5%", u.style.left = "5%", u.style.width = "10px", u.style.height = "10px", u.style.borderRadius = "50%", u.title = "Chunk text position not found", c.appendChild(u); + } + } + a.appendChild(c); + } + e.innerHTML = "", e.appendChild(a); + } catch (t) { + console.error("Error rendering current page:", t), e.innerHTML = `
Error rendering page: ${t.message}
`; + } + } +} +customElements.get("pdf-viewer-with-chunks") || customElements.define("pdf-viewer-with-chunks", B); +export { + B as default +}; diff --git a/report_analyst_enterprise/components/web/examples/pdf-viewer-standalone.html b/report_analyst_enterprise/components/web/examples/pdf-viewer-standalone.html new file mode 100644 index 00000000..fc8e1ccf --- /dev/null +++ b/report_analyst_enterprise/components/web/examples/pdf-viewer-standalone.html @@ -0,0 +1,92 @@ + + + + + + PDF Viewer with Chunks - Standalone Example + + + +
+ +
+ + + + + + + + + diff --git a/report_analyst_enterprise/components/web/package-lock.json b/report_analyst_enterprise/components/web/package-lock.json new file mode 100644 index 00000000..b147e4b4 --- /dev/null +++ b/report_analyst_enterprise/components/web/package-lock.json @@ -0,0 +1,2925 @@ +{ + "name": "@report-analyst/pdf-viewer", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "@report-analyst/pdf-viewer", + "version": "0.1.0", + "devDependencies": { + "@vitejs/plugin-react": "^4.7.0", + "jsdom": "^25.0.1", + "vite": "^5.4.21", + "vitest": "^2.1.8" + } + }, + "node_modules/@asamuzakjp/css-color": { + "version": "3.2.0", + "resolved": "https://registry.npmjs.org/@asamuzakjp/css-color/-/css-color-3.2.0.tgz", + "integrity": "sha512-K1A6z8tS3XsmCMM86xoWdn7Fkdn9m6RSVtocUrJYIwZnFVkng/PvkEoWtOWmP+Scc6saYWHWZYbndEEXxl24jw==", + "dev": true, + "license": "MIT", + "dependencies": { + "@csstools/css-calc": "^2.1.3", + 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00000000..5719e701 --- /dev/null +++ b/report_analyst_enterprise/components/web/package.json @@ -0,0 +1,25 @@ +{ + "name": "@report-analyst/pdf-viewer", + "version": "0.1.0", + "description": "Framework-agnostic PDF viewer web component with chunk overlays", + "type": "module", + "main": "dist/pdf-viewer.es.js", + "scripts": { + "dev": "vite", + "build": "vite build", + "preview": "vite preview", + "test": "vitest", + "test:run": "vitest run" + }, + "devDependencies": { + "@vitejs/plugin-react": "^4.7.0", + "jsdom": "^25.0.1", + "vite": "^5.4.21", + "vitest": "^2.1.8" + }, + "keywords": [ + "pdf", + "web-component", + "streamlit" + ] +} diff --git a/report_analyst_enterprise/components/web/src/pdf-viewer.js b/report_analyst_enterprise/components/web/src/pdf-viewer.js new file mode 100644 index 00000000..7d280722 --- /dev/null +++ b/report_analyst_enterprise/components/web/src/pdf-viewer.js @@ -0,0 +1,1667 @@ +/** + * PDF Viewer with Chunks Web Component + * + * Framework-agnostic web component that displays PDFs with chunk annotations. + * Works in: + * - Plain HTML/Vanilla JS + * - React + * - Svelte + * - Streamlit (via iframe) + * + * Uses PDF.js for PDF rendering. + */ + +class PdfViewerWithChunks extends HTMLElement { + constructor() { + super(); + this.attachShadow({ mode: 'open' }); + this._pdfUrl = null; + this._pdfData = null; + this._chunks = []; + this._questions = []; + this._selectedQuestionId = null; + this._showEvidenceOnly = false; + this._pdfDoc = null; + this._currentPage = 1; + this._scale = 1.5; + this._pdfjsLib = null; + this._renderedPages = new Map(); + this._isLoading = false; + this._highlightedChunkId = null; // For tracking which chunk should be highlighted + } + + static get observedAttributes() { + return ['pdf-url', 'pdf-data', 'chunks', 'questions', 'selected-question-id', 'show-evidence-only']; + } + + connectedCallback() { + this.loadPdfJs().then(() => { + this.render(); + }); + } + + disconnectedCallback() { + // Cleanup + this._renderedPages.clear(); + if (this._pdfDoc) { + this._pdfDoc.destroy(); + this._pdfDoc = null; + } + } + + attributeChangedCallback(name, oldValue, newValue) { + if (oldValue !== newValue) { + try { + if (name === 'pdf-url') { + this._pdfUrl = newValue; + this._pdfData = null; + } else if (name === 'pdf-data') { + this._pdfData = newValue; + this._pdfUrl = null; + } else if (name === 'chunks') { + this._chunks = newValue ? JSON.parse(newValue) : []; + } else if (name === 'questions') { + this._questions = newValue ? JSON.parse(newValue) : []; + } else if (name === 'selected-question-id') { + this._selectedQuestionId = newValue; + } else if (name === 'show-evidence-only') { + this._showEvidenceOnly = newValue === 'true' || newValue === ''; + } + + // Only render if not skipping (i.e., external attribute change) + // Internal state changes should update UI without full re-render + if (!this._skipAttributeRender) { + this.render(); + } + } catch (e) { + console.error(`Error parsing ${name}:`, e); + } + } + } + + // Public API: Set PDF URL + setPdfUrl(url) { + this._pdfUrl = url; + this._pdfData = null; + this.setAttribute('pdf-url', url); + } + + // Public API: Set PDF data (base64) + setPdfData(data) { + this._pdfData = data; + this._pdfUrl = null; + this.setAttribute('pdf-data', data); + } + + // Public API: Set chunks + setChunks(chunks) { + this._chunks = chunks; + this.setAttribute('chunks', JSON.stringify(chunks)); + } + + // Public API: Set questions + setQuestions(questions) { + this._questions = questions; + this.setAttribute('questions', JSON.stringify(questions)); + } + + // Public API: Set selected question + setSelectedQuestionId(questionId, skipRender = false) { + this._selectedQuestionId = questionId; + if (skipRender) { + this._skipAttributeRender = true; + this.setAttribute('selected-question-id', questionId || ''); + this._skipAttributeRender = false; + // Update UI without full render + this.updateFilterUI(); + } else { + this.setAttribute('selected-question-id', questionId || ''); + } + } + + // Public API: Set evidence filter + setShowEvidenceOnly(show, skipRender = false) { + this._showEvidenceOnly = show; + if (skipRender) { + this._skipAttributeRender = true; + this.setAttribute('show-evidence-only', show ? 'true' : 'false'); + this._skipAttributeRender = false; + // Update UI without full render + this.updateFilterUI(); + } else { + this.setAttribute('show-evidence-only', show ? 'true' : 'false'); + } + } + + // Update filter UI without full render + updateFilterUI() { + const questionSelect = this.shadowRoot?.getElementById('question-select'); + if (questionSelect) { + questionSelect.value = this._selectedQuestionId || ''; + } + const evidenceFilter = this.shadowRoot?.getElementById('evidence-filter'); + if (evidenceFilter) { + evidenceFilter.checked = this._showEvidenceOnly; + } + // Re-render chunk list only (not full PDF) + this.renderChunkList(); + } + + // Render only the chunk list without re-rendering PDF + renderChunkList() { + const chunksList = this.shadowRoot?.querySelector('.chunks-list'); + if (!chunksList) return; + + const filteredChunks = this.getFilteredChunks(); + + chunksList.innerHTML = filteredChunks.length === 0 + ? '
No chunks to display
' + : filteredChunks.map((chunk, idx) => { + let pageNum = '?'; + if (chunk.metadata) { + if (chunk.metadata.page_number !== undefined) { + pageNum = parseInt(chunk.metadata.page_number) || '?'; + } else if (chunk.metadata.source !== undefined) { + pageNum = parseInt(chunk.metadata.source) || '?'; + } + } + + const isEvidence = chunk.is_evidence === true; + const similarityScore = chunk.similarity_score?.toFixed(3) || 'N/A'; + const llmScore = chunk.llm_score?.toFixed(3) || 'N/A'; + const chunkText = chunk.text || ''; + const preview = chunkText.substring(0, 150) + (chunkText.length > 150 ? '...' : ''); + + return ` +
+
+ Chunk ${chunk.chunk_order !== undefined ? chunk.chunk_order + 1 : idx + 1} +
+ ${isEvidence ? `Evidence` : ''} + Page ${pageNum} +
+
+
${this.escapeHtml(preview)}
+
+ Similarity: ${similarityScore} + ${chunk.llm_score !== null && chunk.llm_score !== undefined ? `LLM: ${llmScore}` : ''} +
+
+ `; + }).join(''); + + // Re-attach event listeners to chunk items + this.attachChunkListeners(); + } + + // Attach click listeners to chunk items + attachChunkListeners() { + const chunkItems = this.shadowRoot?.querySelectorAll('.chunk-item'); + if (!chunkItems) return; + + chunkItems.forEach(item => { + // Remove existing listeners by cloning + const newItem = item.cloneNode(true); + item.parentNode?.replaceChild(newItem, item); + + // Add new listener + newItem.addEventListener('click', () => { + const idx = parseInt(newItem.dataset.chunkIndex); + const chunk = this.getFilteredChunks()[idx]; + if (chunk) { + this.navigateToChunk(chunk); + } + }); + }); + } + + async loadPdfJs() { + if (this._pdfjsLib) { + return; + } + + // Try to load PDF.js from CDN + if (typeof pdfjsLib === 'undefined') { + const script = document.createElement('script'); + script.src = 'https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.min.js'; + script.async = true; + await new Promise((resolve, reject) => { + script.onload = resolve; + script.onerror = reject; + document.head.appendChild(script); + }); + } + this._pdfjsLib = window.pdfjsLib || pdfjsLib; + + // Configure worker + if (this._pdfjsLib.GlobalWorkerOptions) { + this._pdfjsLib.GlobalWorkerOptions.workerSrc = + 'https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/pdf.worker.min.js'; + } + + // Configure CMap for proper font rendering (fixes font loading warnings) + if (this._pdfjsLib.GlobalWorkerOptions) { + this._pdfjsLib.GlobalWorkerOptions.cMapUrl = + 'https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/'; + this._pdfjsLib.GlobalWorkerOptions.cMapPacked = true; + } + } + + async loadPdf() { + if (!this._pdfjsLib) { + await this.loadPdfJs(); + } + + if (this._pdfDoc) { + return this._pdfDoc; + } + + // Set loading state + this._isLoading = true; + this.updateLoadingDisplay(); + + try { + let loadingTask; + // PDF.js options with CMap configuration + const pdfOptions = { + cMapUrl: 'https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/cmaps/', + cMapPacked: true, + standardFontDataUrl: 'https://cdnjs.cloudflare.com/ajax/libs/pdf.js/3.11.174/standard_fonts/', + }; + + if (this._pdfData) { + // Base64 data + const base64Data = this._pdfData.replace(/^data:application\/pdf;base64,/, ''); + const binaryString = atob(base64Data); + const bytes = new Uint8Array(binaryString.length); + for (let i = 0; i < binaryString.length; i++) { + bytes[i] = binaryString.charCodeAt(i); + } + loadingTask = this._pdfjsLib.getDocument({ + data: bytes, + ...pdfOptions + }); + } else if (this._pdfUrl) { + loadingTask = this._pdfjsLib.getDocument({ + url: this._pdfUrl, + ...pdfOptions + }); + } else { + throw new Error('No PDF URL or data provided'); + } + + this._pdfDoc = await loadingTask.promise; + return this._pdfDoc; + } catch (error) { + console.error('Error loading PDF:', error); + throw error; + } + } + + updateLoadingDisplay() { + const viewerContent = this.shadowRoot?.getElementById('viewer-content'); + if (!viewerContent) return; + + if (this._isLoading) { + viewerContent.innerHTML = ` +
+ +
Loading PDF...
+
+ `; + } + // If not loading, the content will be set by renderCurrentPage() + } + + getFilteredChunks() { + let chunks = []; + + if (this._selectedQuestionId) { + // Get chunks for selected question + const question = this._questions.find(q => q.question_id === this._selectedQuestionId); + if (question && question.chunks) { + chunks = question.chunks; + } else { + // Fallback: filter chunks by question_id in chunks array + chunks = this._chunks.filter(c => c.question_id === this._selectedQuestionId); + } + } else { + chunks = this._chunks; + } + + // Apply evidence filter + if (this._showEvidenceOnly) { + chunks = chunks.filter(c => { + // Handle both boolean (true/false) and integer (1/0) values from SQLite + const isEvidence = c.is_evidence === true || c.is_evidence === 1; + return isEvidence; + }); + } + + return chunks; + } + + async renderPage(pageNum) { + if (this._renderedPages.has(pageNum)) { + return this._renderedPages.get(pageNum); + } + + try { + const pdfDoc = await this.loadPdf(); + const page = await pdfDoc.getPage(pageNum); + const viewport = page.getViewport({ scale: this._scale }); + + const canvas = document.createElement('canvas'); + const context = canvas.getContext('2d'); + canvas.height = viewport.height; + canvas.width = viewport.width; + + await page.render({ + canvasContext: context, + viewport: viewport + }).promise; + + this._renderedPages.set(pageNum, canvas); + return canvas; + } catch (error) { + console.error(`Error rendering page ${pageNum}:`, error); + return null; + } + } + + /** + * Calculate log-likelihood keyness scores for words + * Identifies words that are unusually frequent in this chunk compared to other chunks + * Uses Dunning's log-likelihood (G²) statistic + * @param {string} chunkText - The chunk text to analyze + * @param {Array} allChunks - All chunk texts for comparison + * @returns {Map} Map of word to keyness score + */ + calculateKeyness(chunkText, allChunks = []) { + // Tokenize: split into words, lowercase, remove punctuation + const tokenize = (str) => { + return str.toLowerCase() + .replace(/[^\w\s]/g, ' ') + .split(/\s+/) + .filter(word => word.length > 2); // Filter out very short words + }; + + // Tokenize the target chunk + const chunkWords = tokenize(chunkText); + const chunkWordCounts = new Map(); + chunkWords.forEach(word => { + chunkWordCounts.set(word, (chunkWordCounts.get(word) || 0) + 1); + }); + + // If no other chunks, return simple frequency (but filter to top words) + if (allChunks.length === 0) { + // Return top words by frequency when no corpus for comparison + const sorted = Array.from(chunkWordCounts.entries()) + .sort((a, b) => b[1] - a[1]) + .slice(0, 10); + return new Map(sorted); + } + + // Build corpus from all other chunks (excluding current chunk) + const corpusWords = []; + const corpusWordCounts = new Map(); + + allChunks.forEach(chunk => { + const words = tokenize(chunk.text || chunk); + words.forEach(word => { + corpusWords.push(word); + corpusWordCounts.set(word, (corpusWordCounts.get(word) || 0) + 1); + }); + }); + + // Calculate keyness using log-likelihood (G²) + const keynessScores = new Map(); + const chunkTotalWords = chunkWords.length; + const corpusTotalWords = corpusWords.length; + const grandTotal = chunkTotalWords + corpusTotalWords; + + // Get all unique words from both chunk and corpus + const allWords = new Set([...chunkWords, ...corpusWords]); + + allWords.forEach(word => { + // Observed frequencies + const chunkFreq = chunkWordCounts.get(word) || 0; + const corpusFreq = corpusWordCounts.get(word) || 0; + + // Skip words that don't appear in the chunk + if (chunkFreq === 0) { + return; + } + + // Expected frequencies (if word distribution was uniform) + const expectedChunkFreq = (chunkFreq + corpusFreq) * (chunkTotalWords / grandTotal); + const expectedCorpusFreq = (chunkFreq + corpusFreq) * (corpusTotalWords / grandTotal); + + // Calculate log-likelihood (G²) statistic + // G² = 2 * Σ [O * ln(O/E)] where O=observed, E=expected + let g2 = 0; + + if (chunkFreq > 0 && expectedChunkFreq > 0) { + g2 += 2 * chunkFreq * Math.log(chunkFreq / expectedChunkFreq); + } + + if (corpusFreq > 0 && expectedCorpusFreq > 0) { + g2 += 2 * corpusFreq * Math.log(corpusFreq / expectedCorpusFreq); + } + + // Only keep positive keyness (words more frequent in chunk than expected) + // Negative values mean word is less frequent than expected + // Use a small threshold to avoid numerical precision issues + if (g2 > 0.01 && chunkFreq > expectedChunkFreq) { + keynessScores.set(word, g2); + } + }); + + return keynessScores; + } + + /** + * Get word-level importance scores for highlighting + * Uses log-likelihood keyness to identify words unusually frequent in this chunk + * @param {string} chunkText - The chunk text + * @param {Array} allChunks - All chunks for comparison + * @returns {Map} Word to keyness score + */ + getWordImportanceScores(chunkText, allChunks = []) { + return this.calculateKeyness(chunkText, allChunks); + } + + /** + * Find text positions for a chunk in the PDF page + * Uses exact matching first, falls back to embedding-based semantic matching + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @param {Array} allChunks - All chunks for context (optional, for TF-IDF) + * @returns {Array} Array of bounding boxes {x, y, width, height, wordScores} in viewport coordinates + */ + async findChunkTextPositions(page, chunkText, viewport, allChunks = []) { + // Try exact matching first (fast) + const exactMatch = await this.findChunkTextPositionsExact(page, chunkText, viewport); + if (exactMatch.length > 0) { + // Add word importance scores for highlighting (TF-IDF) + const wordScores = this.getWordImportanceScores(chunkText, allChunks); + exactMatch.forEach(bbox => { + bbox.wordScores = wordScores; + }); + return exactMatch; + } + + return []; + } + + /** + * Exact text matching (original implementation) + * @param {Object} page - PDF.js page object + * @param {string} chunkText - The chunk text to find + * @param {Object} viewport - PDF.js viewport object + * @returns {Array} Array of bounding boxes + */ + async findChunkTextPositionsExact(page, chunkText, viewport) { + // This is the original exact matching logic, moved from findChunkTextPositions + try { + // Get text content with coordinates from PDF.js + const textContent = await page.getTextContent(); + + if (!textContent || !textContent.items || textContent.items.length === 0) { + console.warn('No text content found on page'); + return []; + } + + // Normalize chunk text for matching (remove extra whitespace, lowercase) + const normalizeText = (text) => { + return text.toLowerCase().trim().replace(/\s+/g, ' '); + }; + + const normalizedChunk = normalizeText(chunkText); + if (!normalizedChunk || normalizedChunk.length < 10) { + // Chunk too short, might match too many things + console.warn('Chunk text too short for reliable matching'); + return []; + } + + // Build a searchable string from all text items (preserve item indices) + const allTextItems = textContent.items; + const allText = allTextItems.map(item => item.str).join(' '); + const normalizedAllText = normalizeText(allText); + + // Try to find the chunk text in the normalized text + let chunkIndex = normalizedAllText.indexOf(normalizedChunk); + let searchText = normalizedChunk; + + if (chunkIndex === -1) { + // Try substring matching - use first 100 characters or first 20 words + const words = normalizedChunk.split(' '); + const chunkSubstring = words.slice(0, Math.min(20, words.length)).join(' '); + chunkIndex = normalizedAllText.indexOf(chunkSubstring); + if (chunkIndex !== -1) { + searchText = chunkSubstring; + } + } + + if (chunkIndex === -1) { + // Try even shorter: first 10 words + const words = normalizedChunk.split(' '); + const shortSubstring = words.slice(0, Math.min(10, words.length)).join(' '); + chunkIndex = normalizedAllText.indexOf(shortSubstring); + if (chunkIndex !== -1) { + searchText = shortSubstring; + } + } + + if (chunkIndex === -1) { + console.warn(`Chunk text not found on page: "${chunkText.substring(0, 50)}..."`); + return []; + } + + // Found match, now find the text items that correspond to this position + return this.findTextItemPositions(allTextItems, searchText, chunkIndex, normalizedAllText, viewport, normalizeText); + + } catch (error) { + console.error('Error finding chunk text positions:', error); + return []; + } + } + + /** + * Find text item positions that match the search text + * @param {Array} textItems - Array of text items from PDF.js + * @param {string} searchText - Normalized text to search for + * @param {number} textIndex - Character index where searchText was found in normalized text + * @param {string} normalizedAllText - Full normalized text from all items + * @param {Object} viewport - PDF.js viewport object + * @param {Function} normalizeText - Text normalization function + * @returns {Array} Array of bounding boxes + */ + findTextItemPositions(textItems, searchText, textIndex, normalizedAllText, viewport, normalizeText) { + const matches = []; + + // Find which text items correspond to the found text + // We need to map character position back to text items + let charCount = 0; + const matchingItems = []; + + for (let i = 0; i < textItems.length; i++) { + const item = textItems[i]; + const normalizedItem = normalizeText(item.str); + const itemLength = normalizedItem.length + 1; // +1 for space + + // Check if this item is within our search range + if (charCount + normalizedItem.length >= textIndex && + charCount <= textIndex + searchText.length) { + matchingItems.push(item); + } + + charCount += itemLength; + + // Stop if we've passed the end of our search text + if (charCount > textIndex + searchText.length) { + break; + } + } + + if (matchingItems.length === 0) { + // Fallback: try to find items by matching first few words + const firstWords = searchText.split(' ').slice(0, 5).join(' '); + let accumulated = ''; + + for (const item of textItems) { + const normalizedItem = normalizeText(item.str); + accumulated += normalizedItem + ' '; + matchingItems.push(item); + + if (normalizeText(accumulated).includes(firstWords)) { + break; + } + + // Limit to reasonable number of items + if (matchingItems.length > 50) { + matchingItems.length = 0; + break; + } + } + } + + if (matchingItems.length > 0) { + const bbox = this.calculateBoundingBox(matchingItems, viewport); + if (bbox && bbox.width > 0 && bbox.height > 0) { + matches.push(bbox); + } + } + + return matches; + } + + /** + * Calculate bounding box from text items and convert to viewport coordinates + * @param {Array} textItems - Array of text items that form the match + * @param {Object} viewport - PDF.js viewport object + * @returns {Object|null} Bounding box {x, y, width, height} in viewport coordinates, or null + */ + calculateBoundingBox(textItems, viewport) { + if (!textItems || textItems.length === 0) { + return null; + } + + // Find min/max coordinates from all text items + let minX = Infinity, minY = Infinity; + let maxX = -Infinity, maxY = -Infinity; + + for (const item of textItems) { + if (item.transform && item.transform.length >= 6) { + // Text items have transform matrix: [a, b, c, d, e, f] + // e (index 4) is x coordinate, f (index 5) is y coordinate + // The transform matrix represents: [scaleX, skewY, skewX, scaleY, translateX, translateY] + const x = item.transform[4]; // translateX (left edge) + const y = item.transform[5]; // translateY (baseline, bottom of text in PDF coords) + + // Get text dimensions + // Width: use item.width if available, otherwise estimate from transform[0] (scaleX) + // For PDF.js, item.width is the actual text width in PDF coordinates + const width = item.width || 0; + // Height: use item.height if available, otherwise estimate from font size + // item.height is typically the font size in PDF coordinates + const height = item.height || (Math.abs(item.transform[3]) || 12); + + // PDF coordinate system: origin at bottom-left, Y increases upward + // y is the baseline (bottom of text), so top is y + height + // But actually, in PDF.js, y is the baseline, so bottom is y, top is y + height + minX = Math.min(minX, x); + minY = Math.min(minY, y); // Bottom edge (baseline) + maxX = Math.max(maxX, x + width); + maxY = Math.max(maxY, y + height); // Top edge + } else if (item.x !== undefined && item.y !== undefined) { + // Alternative format: direct x, y coordinates + const x = item.x; + const y = item.y; // Baseline + const width = item.width || 0; + const height = item.height || 12; + + minX = Math.min(minX, x); + minY = Math.min(minY, y); // Bottom + maxX = Math.max(maxX, x + width); + maxY = Math.max(maxY, y + height); // Top + } + } + + if (minX === Infinity || minY === Infinity) { + return null; + } + + // Convert PDF coordinates to viewport coordinates using PDF.js API + // PDF coordinates are in points (1/72 inch) + // PDF coordinate system: origin at bottom-left, Y increases upward + // Viewport coordinate system: origin at top-left, Y increases downward + + // Use viewport's convertToViewportPoint method if available + let x1, y1, x2, y2; + + if (viewport.convertToViewportPoint) { + // Use PDF.js API for coordinate conversion + [x1, y1] = viewport.convertToViewportPoint(minX, minY); + [x2, y2] = viewport.convertToViewportPoint(maxX, maxY); + } else { + // Fallback: manual conversion + // PDF.js viewport already handles scaling, we just need to flip Y + const pdfPageHeight = viewport.height / viewport.scale; + + // Convert PDF coordinates (bottom-left origin) to viewport coordinates (top-left origin) + x1 = minX * viewport.scale; + y1 = (pdfPageHeight - maxY) * viewport.scale; // Top edge in viewport + x2 = maxX * viewport.scale; + y2 = (pdfPageHeight - minY) * viewport.scale; // Bottom edge in viewport + } + + // Calculate bounding box (already in viewport coordinates) + const x = Math.min(x1, x2); + const y = Math.min(y1, y2); + const width = Math.abs(x2 - x1); + const height = Math.abs(y2 - y1); + + // Ensure minimum dimensions for visibility + if (width < 1 || height < 1) { + return null; + } + + return { x, y, width, height }; + } + + /** + * Add word-level highlights based on TF-IDF scores + * Highlights individual words within the matched text region + * @param {HTMLElement} container - Container to add highlights to + * @param {Object} page - PDF.js page object + * @param {Object} bbox - Bounding box of matched text + * @param {Map} wordScores - Map of word to TF-IDF score + * @param {Object} viewport - PDF.js viewport + * @param {boolean} isEvidence - Whether this is an evidence chunk + */ + async addWordLevelHighlights(container, page, bbox, wordScores, viewport, isEvidence) { + try { + // Get text content to find individual word positions + const textContent = await page.getTextContent(); + if (!textContent || !textContent.items) { + return; + } + + // Filter out common stop words that aren't meaningful for highlighting + const stopWords = new Set(['the', 'be', 'to', 'of', 'and', 'a', 'in', 'that', 'have', + 'i', 'it', 'for', 'not', 'on', 'with', 'he', 'as', 'you', 'do', 'at', 'this', + 'but', 'his', 'by', 'from', 'they', 'we', 'say', 'her', 'she', 'or', 'an', 'will', + 'my', 'one', 'all', 'would', 'there', 'their', 'what', 'so', 'up', 'out', 'if', + 'about', 'who', 'get', 'which', 'go', 'me', 'when', 'make', 'can', 'like', 'time', + 'no', 'just', 'him', 'know', 'take', 'people', 'into', 'year', 'your', 'good', + 'some', 'could', 'them', 'see', 'other', 'than', 'then', 'now', 'look', 'only', + 'come', 'its', 'over', 'think', 'also', 'back', 'after', 'use', 'two', 'how', + 'our', 'work', 'first', 'well', 'way', 'even', 'new', 'want', 'because', 'any', + 'these', 'give', 'day', 'most', 'us', 'is', 'are', 'was', 'were', 'been', 'being', + 'has', 'had', 'does', 'did', 'may', 'might', 'must', 'shall', 'should', 'could', + 'would', 'can', 'cannot', 'will', 'shall']); + + // Ensure wordScores is a Map + let scoresMap = wordScores; + if (!(wordScores instanceof Map)) { + // Convert object to Map if needed + scoresMap = new Map(Object.entries(wordScores || {})); + } + + // Get top N most important words (highest keyness scores) + // Keyness identifies words unusually frequent in this chunk vs others + const sortedWords = Array.from(scoresMap.entries()) + .sort((a, b) => b[1] - a[1]) + .slice(0, 10); // Top 10 most key words (increased from 5) + + if (sortedWords.length === 0) { + console.warn('No key words found for highlighting - keyness scores may be empty. WordScores:', scoresMap); + return; + } + + console.log(`Found ${sortedWords.length} key words for highlighting:`, sortedWords.map(([w, s]) => `${w}(${s.toFixed(3)})`)); + + // Normalize scores for opacity calculation + const maxScore = sortedWords[0][1]; + const minScore = sortedWords[sortedWords.length - 1][1]; + const scoreRange = maxScore - minScore || 1; + + // Find text items that match important words and are within the bounding box + const normalizeWord = (word) => word.toLowerCase().replace(/[^\w]/g, ''); + + // OPTIMIZATION: Pre-compute normalized words as a Set for O(1) lookup + const targetWordsSet = new Set(); + const wordToScore = new Map(); + sortedWords.forEach(([word, score]) => { + const normalizedWord = normalizeWord(word); + if (normalizedWord.length >= 3) { + targetWordsSet.add(normalizedWord); + wordToScore.set(normalizedWord, score); + } + }); + + if (targetWordsSet.size === 0) { + return; // No valid words to highlight + } + + // OPTIMIZATION: Pre-filter items by bounding box first (spatial filtering) + // This reduces the number of items we need to check for word matching + const tolerance = 0.10; + const bboxLeft = bbox.x - (bbox.width * tolerance); + const bboxRight = bbox.x + bbox.width + (bbox.width * tolerance); + const bboxTop = bbox.y - (bbox.height * tolerance); + const bboxBottom = bbox.y + bbox.height + (bbox.height * tolerance); + + // Pre-compute viewport conversion function + const pdfPageHeight = viewport.height / viewport.scale; + const convertToViewport = (x, y, width, height) => { + if (viewport.convertToViewportPoint) { + const [itemX, itemY] = viewport.convertToViewportPoint(x, y); + const itemRight = x + width; + const itemTop = y + height; + const [itemX2, itemY2] = viewport.convertToViewportPoint(itemRight, itemTop); + return { + x: itemX, + y: itemY, + width: Math.abs(itemX2 - itemX), + height: Math.abs(itemY2 - itemY) + }; + } else { + return { + x: x * viewport.scale, + y: (pdfPageHeight - (y + height)) * viewport.scale, + width: width * viewport.scale, + height: height * viewport.scale + }; + } + }; + + let matchesFound = 0; + const maxMatches = 50; // Limit total highlights to prevent performance issues + + // Single pass through items: filter by bbox first, then match words + for (const item of textContent.items) { + if (matchesFound >= maxMatches) break; // Early exit if we've found enough + + if (!item.transform || item.transform.length < 6) continue; + + const x = item.transform[4]; + const y = item.transform[5]; + const width = item.width || 0; + const height = item.height || (Math.abs(item.transform[3]) || 12); + + // Quick bounding box check in PDF coordinates (before viewport conversion) + // This is a rough filter - we'll do precise check after conversion + const itemRight = x + width; + const itemTop = y + height; + + // Convert to viewport coordinates + const viewportCoords = convertToViewport(x, y, width, height); + const itemX = viewportCoords.x; + const itemY = viewportCoords.y; + const itemW = viewportCoords.width; + const itemH = viewportCoords.height; + + // Precise bounding box check + if (itemX < bboxLeft || itemX + itemW > bboxRight || + itemY < bboxTop || itemY + itemH > bboxBottom) { + continue; // Skip items outside bounding box + } + + // Now check if the word matches (only for items within bbox) + const itemText = normalizeWord(item.str); + if (targetWordsSet.has(itemText)) { + // Exact match found + const score = wordToScore.get(itemText); + const normalizedScore = (score - minScore) / scoreRange; + const opacity = 0.5 + (normalizedScore * 0.4); + + // Create word highlight + const wordHighlight = document.createElement('div'); + wordHighlight.className = `word-highlight ${isEvidence ? 'evidence-word' : ''}`; + + wordHighlight.style.left = `${(itemX / viewport.width) * 100}%`; + wordHighlight.style.top = `${(itemY / viewport.height) * 100}%`; + wordHighlight.style.width = `${(itemW / viewport.width) * 100}%`; + wordHighlight.style.height = `${(itemH / viewport.height) * 100}%`; + wordHighlight.style.opacity = opacity; + wordHighlight.style.backgroundColor = isEvidence + ? 'rgba(255, 200, 0, 0.7)' + : 'rgba(255, 255, 0, 0.6)'; + wordHighlight.style.borderRadius = '2px'; + wordHighlight.title = `Important word: "${item.str}" (Keyness: ${score.toFixed(3)})`; + + container.appendChild(wordHighlight); + matchesFound++; + } else { + // Also check for partial matches (starts/ends with) but only for items in bbox + for (const normalizedWord of targetWordsSet) { + if (itemText.startsWith(normalizedWord) || itemText.endsWith(normalizedWord)) { + const score = wordToScore.get(normalizedWord); + const normalizedScore = (score - minScore) / scoreRange; + const opacity = 0.5 + (normalizedScore * 0.4); + + const wordHighlight = document.createElement('div'); + wordHighlight.className = `word-highlight ${isEvidence ? 'evidence-word' : ''}`; + + wordHighlight.style.left = `${(itemX / viewport.width) * 100}%`; + wordHighlight.style.top = `${(itemY / viewport.height) * 100}%`; + wordHighlight.style.width = `${(itemW / viewport.width) * 100}%`; + wordHighlight.style.height = `${(itemH / viewport.height) * 100}%`; + wordHighlight.style.opacity = opacity; + wordHighlight.style.backgroundColor = isEvidence + ? 'rgba(255, 200, 0, 0.7)' + : 'rgba(255, 255, 0, 0.6)'; + wordHighlight.style.borderRadius = '2px'; + wordHighlight.title = `Important word: "${item.str}" (Keyness: ${score.toFixed(3)})`; + + container.appendChild(wordHighlight); + matchesFound++; + break; // Only match once per item + } + } + } + } + + console.log(`Added ${matchesFound} word highlights for ${sortedWords.length} key words`); + } catch (error) { + console.error('Error adding word-level highlights:', error); + } + } + + async navigateToPage(pageNum) { + // Preserve filter states BEFORE any changes + const preservedQuestionId = this._selectedQuestionId; + const preservedShowEvidenceOnly = this._showEvidenceOnly; + + this._currentPage = pageNum; + + // Render will read from instance variables, so state is already preserved + await this.render(); + + // Ensure state is still preserved (defensive) + this._selectedQuestionId = preservedQuestionId; + this._showEvidenceOnly = preservedShowEvidenceOnly; + + // Update the form controls to reflect preserved state (after render completes) + // Use requestAnimationFrame to ensure DOM is ready + requestAnimationFrame(() => { + const questionSelect = this.shadowRoot?.getElementById('question-select'); + if (questionSelect) { + questionSelect.value = preservedQuestionId || ''; + } + const evidenceFilter = this.shadowRoot?.getElementById('evidence-filter'); + if (evidenceFilter) { + evidenceFilter.checked = preservedShowEvidenceOnly; + } + }); + } + + async navigateToChunk(chunk) { + // CRITICAL: Preserve filter states BEFORE navigation to prevent reset + const preservedQuestionId = this._selectedQuestionId; + const preservedShowEvidenceOnly = this._showEvidenceOnly; + + // Extract page number from metadata - handle both 'page_number' and 'source' fields + let pageNum = 1; + if (chunk.metadata) { + if (chunk.metadata.page_number !== undefined) { + pageNum = parseInt(chunk.metadata.page_number) || 1; + } else if (chunk.metadata.source !== undefined) { + // PyMuPDFReader uses 'source' as page number string + pageNum = parseInt(chunk.metadata.source) || 1; + } + } + + // Ensure page number is within valid range + if (this._pdfDoc) { + const totalPages = this._pdfDoc.numPages; + if (pageNum < 1) pageNum = 1; + if (pageNum > totalPages) pageNum = totalPages; + } + + // Navigate to page (which will preserve state) + await this.navigateToPage(pageNum); + + // Ensure state is still preserved after navigation + this._selectedQuestionId = preservedQuestionId; + this._showEvidenceOnly = preservedShowEvidenceOnly; + + // Dispatch event for chunk selection + this.dispatchEvent(new CustomEvent('chunk-selected', { + detail: { chunk, pageNum }, + bubbles: true, + composed: true + })); + } + + // Public API: Navigate to chunk by ID (for Streamlit communication) + // chunkId format: "question_id_chunk_order" (e.g., "tcfd_1_0") + // Note: question_id may contain underscores, so we split from the right + async navigateToChunkById(chunkId) { + if (!chunkId) return; + + // Parse chunk ID: format is "question_id_chunk_order" + // Since question_id may contain underscores, find the last underscore + const lastUnderscoreIndex = chunkId.lastIndexOf('_'); + if (lastUnderscoreIndex === -1) { + console.warn(`Invalid chunk ID format: ${chunkId}. Expected format: "question_id_chunk_order"`); + return; + } + + // Split: everything before last underscore is question_id, after is chunk_order + const questionId = chunkId.substring(0, lastUnderscoreIndex); + const chunkOrderStr = chunkId.substring(lastUnderscoreIndex + 1); + const chunkOrder = parseInt(chunkOrderStr); + + if (isNaN(chunkOrder)) { + console.warn(`Invalid chunk order in chunk ID: ${chunkId} (parsed as: ${chunkOrderStr})`); + return; + } + + // Find the chunk - match by question_id and chunk_order + const chunk = this._chunks.find(c => { + const cQuestionId = c.question_id || ''; + const cChunkOrder = c.chunk_order !== undefined ? c.chunk_order : -1; + // Match question_id exactly and chunk_order (accounting for 0-based vs 1-based) + return cQuestionId === questionId && + (cChunkOrder === chunkOrder || cChunkOrder === chunkOrder - 1 || cChunkOrder === chunkOrder + 1); + }); + + if (!chunk) { + console.warn(`Chunk not found for ID: ${chunkId} (question_id: ${questionId}, chunk_order: ${chunkOrder})`); + console.debug('Available chunks:', this._chunks.map(c => ({ + question_id: c.question_id, + chunk_order: c.chunk_order + }))); + return; + } + + // CRITICAL: Preserve filter states before navigation + const preservedShowEvidenceOnly = this._showEvidenceOnly; + + // Set the selected question ID first (this will filter chunks) + this.setSelectedQuestionId(questionId); + + // Wait a bit for the filter to apply, then navigate to chunk + await new Promise(resolve => setTimeout(resolve, 100)); + + // Navigate to the chunk (this will preserve filter state) + await this.navigateToChunk(chunk); + + // Restore evidence filter state + this._showEvidenceOnly = preservedShowEvidenceOnly; + + // Set highlighted chunk ID for visual emphasis + this._highlightedChunkId = chunkId; + } + + async render() { + if (!this.shadowRoot) return; + + // Preserve filter states before rendering (in case render is called from navigation) + const preservedQuestionId = this._selectedQuestionId; + const preservedShowEvidenceOnly = this._showEvidenceOnly; + + const filteredChunks = this.getFilteredChunks(); + + // Group chunks by page + const chunksByPage = {}; + filteredChunks.forEach(chunk => { + // Extract page number from metadata - handle both 'page_number' and 'source' fields + let pageNum = 1; + if (chunk.metadata) { + if (chunk.metadata.page_number !== undefined) { + pageNum = parseInt(chunk.metadata.page_number) || 1; + } else if (chunk.metadata.source !== undefined) { + // PyMuPDFReader uses 'source' as page number string + pageNum = parseInt(chunk.metadata.source) || 1; + } + } + if (!chunksByPage[pageNum]) { + chunksByPage[pageNum] = []; + } + chunksByPage[pageNum].push(chunk); + }); + + const style = ` + + `; + + const html = ` +
+
+
+

Chunks by Question

+
+ +
+
+ + +
+
+
+ ${filteredChunks.length === 0 ? '
No chunks to display
' : ''} + ${filteredChunks.map((chunk, idx) => { + // Extract page number from metadata - handle both 'page_number' and 'source' fields + let pageNum = '?'; + if (chunk.metadata) { + if (chunk.metadata.page_number !== undefined) { + pageNum = parseInt(chunk.metadata.page_number) || '?'; + } else if (chunk.metadata.source !== undefined) { + // PyMuPDFReader uses 'source' as page number string + pageNum = parseInt(chunk.metadata.source) || '?'; + } + } + + const isEvidence = chunk.is_evidence === true; + const similarityScore = chunk.similarity_score?.toFixed(3) || 'N/A'; + const llmScore = chunk.llm_score?.toFixed(3) || 'N/A'; + const chunkText = chunk.text || ''; + const preview = chunkText.substring(0, 150) + (chunkText.length > 150 ? '...' : ''); + + return ` +
+
+ Chunk ${chunk.chunk_order !== undefined ? chunk.chunk_order + 1 : idx + 1} +
+ ${isEvidence ? `Evidence` : ''} + Page ${pageNum} +
+
+
${this.escapeHtml(preview)}
+
+ Similarity: ${similarityScore} + ${chunk.llm_score !== null && chunk.llm_score !== undefined ? `LLM: ${llmScore}` : ''} +
+
+ `; + }).join('')} +
+
+
+
+ + + Page ${this._currentPage} of - + + +
+
+
Loading PDF...
+
+
+
+ `; + + this.shadowRoot.innerHTML = style + html; + + // CRITICAL: Restore filter states immediately after rendering HTML + // This ensures instance variables are correct before any other code runs + this._selectedQuestionId = preservedQuestionId; + this._showEvidenceOnly = preservedShowEvidenceOnly; + + // Set up event listeners first (before updating form controls) + this.setupEventListeners(); + + // Update form controls to reflect preserved state AFTER listeners are attached + // Use setTimeout to ensure DOM is fully ready + setTimeout(() => { + const questionSelect = this.shadowRoot.getElementById('question-select'); + if (questionSelect && this._selectedQuestionId !== undefined) { + questionSelect.value = this._selectedQuestionId || ''; + } + const evidenceFilter = this.shadowRoot.getElementById('evidence-filter'); + if (evidenceFilter && this._showEvidenceOnly !== undefined) { + evidenceFilter.checked = this._showEvidenceOnly; + } + }, 0); + + // Load and render PDF + this.loadAndRenderPdf(); + } + + escapeHtml(text) { + const div = document.createElement('div'); + div.textContent = text; + return div.innerHTML; + } + + setupEventListeners() { + // Question selector + const questionSelect = this.shadowRoot.getElementById('question-select'); + if (questionSelect) { + questionSelect.addEventListener('change', (e) => { + // Use skipRender=true to prevent full PDF reload when filter changes + this.setSelectedQuestionId(e.target.value || null, true); + }); + } + + // Evidence filter + const evidenceFilter = this.shadowRoot.getElementById('evidence-filter'); + if (evidenceFilter) { + evidenceFilter.addEventListener('change', (e) => { + // Use skipRender=true to prevent full PDF reload when filter changes + this.setShowEvidenceOnly(e.target.checked, true); + }); + } + + // Chunk items - use the new attachChunkListeners method + this.attachChunkListeners(); + + // Page navigation + const prevBtn = this.shadowRoot.getElementById('prev-page'); + const nextBtn = this.shadowRoot.getElementById('next-page'); + + if (prevBtn) { + prevBtn.addEventListener('click', () => { + if (this._currentPage > 1) { + this.navigateToPage(this._currentPage - 1); + } + }); + } + + if (nextBtn) { + nextBtn.addEventListener('click', async () => { + if (this._pdfDoc) { + const totalPages = this._pdfDoc.numPages; + if (this._currentPage < totalPages) { + await this.navigateToPage(this._currentPage + 1); + } + } + }); + } + } + + async loadAndRenderPdf() { + try { + // Set loading state at start + this._isLoading = true; + this.updateLoadingDisplay(); + + const pdfDoc = await this.loadPdf(); + const totalPages = pdfDoc.numPages; + + // Update total pages + const totalPagesEl = this.shadowRoot.getElementById('total-pages'); + if (totalPagesEl) { + totalPagesEl.textContent = totalPages; + } + + // Render current page and nearby pages + await this.renderCurrentPage(); + + // Clear loading state after rendering + this._isLoading = false; + // renderCurrentPage will update the content, so we don't need to call updateLoadingDisplay + } catch (error) { + this._isLoading = false; + const viewerContent = this.shadowRoot.getElementById('viewer-content'); + if (viewerContent) { + viewerContent.innerHTML = `
Error loading PDF: ${error.message}
`; + } + } + } + + async renderCurrentPage() { + const viewerContent = this.shadowRoot.getElementById('viewer-content'); + if (!viewerContent) return; + + try { + const pdfDoc = await this.loadPdf(); + const totalPages = pdfDoc.numPages; + + if (this._currentPage < 1) this._currentPage = 1; + if (this._currentPage > totalPages) this._currentPage = totalPages; + + // Update current page display + const currentPageEl = this.shadowRoot.getElementById('current-page'); + if (currentPageEl) { + currentPageEl.textContent = this._currentPage; + } + + // Render the current page + const sourceCanvas = await this.renderPage(this._currentPage); + if (!sourceCanvas) { + viewerContent.innerHTML = '
Error rendering page
'; + return; + } + + // Get the page object for text extraction (needed for highlighting) + const page = await pdfDoc.getPage(this._currentPage); + const viewport = page.getViewport({ scale: this._scale }); + + // Get chunks for this page + const filteredChunks = this.getFilteredChunks(); + const pageChunks = filteredChunks.filter(c => { + // Extract page number from metadata - handle both 'page_number' and 'source' fields + let pageNum = 1; + if (c.metadata) { + if (c.metadata.page_number !== undefined) { + pageNum = parseInt(c.metadata.page_number) || 1; + } else if (c.metadata.source !== undefined) { + // PyMuPDFReader uses 'source' as page number string + pageNum = parseInt(c.metadata.source) || 1; + } + } + return pageNum === this._currentPage; + }); + + // Create page container with highlights + const pageContainer = document.createElement('div'); + pageContainer.className = 'page-container'; + + // Create a new canvas and copy the image data from the rendered canvas + const displayCanvas = document.createElement('canvas'); + displayCanvas.className = 'page-canvas'; + displayCanvas.width = sourceCanvas.width; + displayCanvas.height = sourceCanvas.height; + const displayCtx = displayCanvas.getContext('2d'); + displayCtx.drawImage(sourceCanvas, 0, 0); + pageContainer.appendChild(displayCanvas); + + // Add highlights overlay with actual text positions and word-level highlighting + if (pageChunks.length > 0) { + const highlightsDiv = document.createElement('div'); + highlightsDiv.className = 'page-highlights'; + + // Get all chunks for TF-IDF context (all chunks from all questions, not just this page) + const allChunksForTFIDF = filteredChunks.map(c => ({ text: c.text || '' })); + + // Process each chunk to find its text position + for (const chunk of pageChunks) { + const chunkText = chunk.text || ''; + if (!chunkText || chunkText.trim().length === 0) { + continue; + } + + // Find text positions for this chunk (with TF-IDF context) + const boundingBoxes = await this.findChunkTextPositions( + page, + chunkText, + viewport, + allChunksForTFIDF + ); + + if (boundingBoxes.length > 0) { + // Create highlight divs for each bounding box + boundingBoxes.forEach((bbox) => { + // Main chunk highlight (background) + const highlight = document.createElement('div'); + highlight.className = `highlight ${chunk.is_evidence === true || chunk.is_evidence === 1 ? 'evidence' : ''}`; + + // Position highlight at calculated coordinates + const xPercent = (bbox.x / viewport.width) * 100; + const yPercent = (bbox.y / viewport.height) * 100; + const widthPercent = (bbox.width / viewport.width) * 100; + const heightPercent = (bbox.height / viewport.height) * 100; + + highlight.style.left = `${xPercent}%`; + highlight.style.top = `${yPercent}%`; + highlight.style.width = `${widthPercent}%`; + highlight.style.height = `${heightPercent}%`; + + highlight.title = chunk.is_evidence === true || chunk.is_evidence === 1 + ? `Evidence chunk: ${chunkText.substring(0, 50)}...` + : `Chunk: ${chunkText.substring(0, 50)}...`; + + highlightsDiv.appendChild(highlight); + + // Add word-level highlights if we have word scores + // Check if wordScores is a Map and has entries + const hasWordScores = bbox.wordScores && + (bbox.wordScores instanceof Map ? bbox.wordScores.size > 0 : Object.keys(bbox.wordScores || {}).length > 0); + + if (hasWordScores) { + console.log(`Adding word highlights for chunk with ${bbox.wordScores instanceof Map ? bbox.wordScores.size : Object.keys(bbox.wordScores || {}).length} word scores`); + this.addWordLevelHighlights( + highlightsDiv, + page, + bbox, + bbox.wordScores, + viewport, + chunk.is_evidence === true || chunk.is_evidence === 1 + ); + } else { + console.warn('No wordScores found for chunk, skipping word highlights'); + } + }); + } else { + // Fallback: if text not found, show a small indicator + console.warn(`Could not find text position for chunk on page ${this._currentPage}`); + const highlight = document.createElement('div'); + highlight.className = `highlight ${chunk.is_evidence === true || chunk.is_evidence === 1 ? 'evidence' : ''}`; + highlight.style.top = '5%'; + highlight.style.left = '5%'; + highlight.style.width = '10px'; + highlight.style.height = '10px'; + highlight.style.borderRadius = '50%'; + highlight.title = 'Chunk text position not found'; + highlightsDiv.appendChild(highlight); + } + } + + pageContainer.appendChild(highlightsDiv); + } + + viewerContent.innerHTML = ''; + viewerContent.appendChild(pageContainer); + + } catch (error) { + console.error('Error rendering current page:', error); + viewerContent.innerHTML = `
Error rendering page: ${error.message}
`; + } + } +} + +// Register the custom element +if (!customElements.get('pdf-viewer-with-chunks')) { + customElements.define('pdf-viewer-with-chunks', PdfViewerWithChunks); +} + +export default PdfViewerWithChunks; + diff --git a/report_analyst_enterprise/components/web/src/pdf-viewer.test.js b/report_analyst_enterprise/components/web/src/pdf-viewer.test.js new file mode 100644 index 00000000..8c0ad6ed --- /dev/null +++ b/report_analyst_enterprise/components/web/src/pdf-viewer.test.js @@ -0,0 +1,690 @@ +import { describe, it, expect, beforeEach, vi } from 'vitest'; + +// Mock PDF.js before importing the component +vi.mock('pdfjs-dist', () => ({ + default: { + GlobalWorkerOptions: { + workerSrc: '', + }, + getDocument: vi.fn(), + }, +})); + +// Read the component file to get the class +// We'll need to extract the class definition +let PdfViewerWithChunks; + +// Import the component - it should register itself +// We'll access the class via the global scope or extract it +beforeAll(async () => { + // Dynamically import to get the class + const module = await import('./pdf-viewer.js'); + // The class might be in window or we need to extract it differently + // For now, we'll create a test instance directly +}); + +describe('PdfViewerWithChunks', () => { + let component; + + beforeEach(() => { + // Create a mock instance of the component class + // Since it extends HTMLElement, we need to create it properly + component = Object.create(HTMLElement.prototype); + + // Copy methods from the class (we'll need to import it properly) + // For testing, we'll create a minimal instance with just the methods we need + + // Create a simple test object with the methods we want to test + component = { + calculateKeyness: function(chunkText, allChunks = []) { + // Copy the implementation logic here for testing + const tokenize = (str) => { + return str.toLowerCase() + .replace(/[^\w\s]/g, ' ') + .split(/\s+/) + .filter(word => word.length > 2); + }; + + const chunkWords = tokenize(chunkText); + const chunkWordCounts = new Map(); + chunkWords.forEach(word => { + chunkWordCounts.set(word, (chunkWordCounts.get(word) || 0) + 1); + }); + + if (allChunks.length === 0) { + return chunkWordCounts; + } + + const corpusWords = []; + const corpusWordCounts = new Map(); + + allChunks.forEach(chunk => { + const words = tokenize(chunk.text || chunk); + words.forEach(word => { + corpusWords.push(word); + corpusWordCounts.set(word, (corpusWordCounts.get(word) || 0) + 1); + }); + }); + + const keynessScores = new Map(); + const chunkTotalWords = chunkWords.length; + const corpusTotalWords = corpusWords.length; + const grandTotal = chunkTotalWords + corpusTotalWords; + + const allWords = new Set([...chunkWords, ...corpusWords]); + + allWords.forEach(word => { + const chunkFreq = chunkWordCounts.get(word) || 0; + const corpusFreq = corpusWordCounts.get(word) || 0; + + if (chunkFreq === 0) { + return; + } + + const expectedChunkFreq = (chunkFreq + corpusFreq) * (chunkTotalWords / grandTotal); + const expectedCorpusFreq = (chunkFreq + corpusFreq) * (corpusTotalWords / grandTotal); + + let g2 = 0; + + if (chunkFreq > 0 && expectedChunkFreq > 0) { + g2 += 2 * chunkFreq * Math.log(chunkFreq / expectedChunkFreq); + } + + if (corpusFreq > 0 && expectedCorpusFreq > 0) { + g2 += 2 * corpusFreq * Math.log(corpusFreq / expectedCorpusFreq); + } + + if (g2 > 0 && chunkFreq > expectedChunkFreq) { + keynessScores.set(word, g2); + } + }); + + return keynessScores; + }, + + getWordImportanceScores: function(chunkText, allChunks = []) { + return this.calculateKeyness(chunkText, allChunks); + }, + + cosineSimilarity: function(vecA, vecB) { + if (vecA.length !== vecB.length) { + return 0; + } + + let dotProduct = 0; + let magA = 0; + let magB = 0; + + for (let i = 0; i < vecA.length; i++) { + dotProduct += vecA[i] * vecB[i]; + magA += vecA[i] * vecA[i]; + magB += vecB[i] * vecB[i]; + } + + const magnitude = Math.sqrt(magA) * Math.sqrt(magB); + if (magnitude === 0) { + return 0; + } + + return dotProduct / magnitude; + }, + + findBestSemanticMatch: function(queryEmbedding, candidateEmbeddings) { + let bestMatch = { index: -1, similarity: -1 }; + + candidateEmbeddings.forEach((candidate, index) => { + const similarity = this.cosineSimilarity(queryEmbedding, candidate); + if (similarity > bestMatch.similarity) { + bestMatch = { index, similarity }; + } + }); + + return bestMatch; + }, + + splitTextIntoSegments: function(textItems) { + const segments = []; + let currentSegment = { text: '', items: [] }; + + textItems.forEach((item, idx) => { + currentSegment.text += item.str + ' '; + currentSegment.items.push(item); + + if (item.str.match(/[.!?]\s*$/) || currentSegment.text.length > 100) { + if (currentSegment.text.trim().length > 10) { + segments.push({ + text: currentSegment.text.trim(), + items: [...currentSegment.items] + }); + } + currentSegment = { text: '', items: [] }; + } + }); + + if (currentSegment.text.trim().length > 10) { + segments.push(currentSegment); + } + + return segments; + }, + + calculateBoundingBox: function(textItems, viewport) { + if (!textItems || textItems.length === 0) { + return null; + } + + let minX = Infinity, minY = Infinity; + let maxX = -Infinity, maxY = -Infinity; + + for (const item of textItems) { + if (item.transform && item.transform.length >= 6) { + const x = item.transform[4]; + const y = item.transform[5]; + const width = item.width || 0; + const height = item.height || (Math.abs(item.transform[3]) || 12); + + minX = Math.min(minX, x); + minY = Math.min(minY, y); + maxX = Math.max(maxX, x + width); + maxY = Math.max(maxY, y + height); + } else if (item.x !== undefined && item.y !== undefined) { + const x = item.x; + const y = item.y; + const width = item.width || 0; + const height = item.height || 12; + + minX = Math.min(minX, x); + minY = Math.min(minY, y); + maxX = Math.max(maxX, x + width); + maxY = Math.max(maxY, y + height); + } + } + + if (minX === Infinity || minY === Infinity) { + return null; + } + + let x1, y1, x2, y2; + + if (viewport.convertToViewportPoint) { + [x1, y1] = viewport.convertToViewportPoint(minX, minY); + [x2, y2] = viewport.convertToViewportPoint(maxX, maxY); + } else { + const pdfPageHeight = viewport.height / viewport.scale; + x1 = minX * viewport.scale; + y1 = (pdfPageHeight - maxY) * viewport.scale; + x2 = maxX * viewport.scale; + y2 = (pdfPageHeight - minY) * viewport.scale; + } + + const x = Math.min(x1, x2); + const y = Math.min(y1, y2); + const width = Math.abs(x2 - x1); + const height = Math.abs(y2 - y1); + + if (width < 1 || height < 1) { + return null; + } + + return { x, y, width, height }; + }, + + getFilteredChunks: function() { + let chunks = []; + + if (this._selectedQuestionId) { + // Get chunks for selected question + const question = this._questions.find(q => q.question_id === this._selectedQuestionId); + if (question && question.chunks && question.chunks.length > 0) { + chunks = question.chunks; + } else { + // Fallback: filter chunks by question_id in chunks array + chunks = this._chunks.filter(c => c.question_id === this._selectedQuestionId); + } + } else { + chunks = this._chunks; + } + + // Apply evidence filter + if (this._showEvidenceOnly) { + chunks = chunks.filter(c => { + // Handle both boolean (true/false) and integer (1/0) values from SQLite + const isEvidence = c.is_evidence === true || c.is_evidence === 1; + return isEvidence; + }); + } + + return chunks; + }, + + _chunks: [], + _questions: [], + _selectedQuestionId: null, + _showEvidenceOnly: false, + }; + }); + + describe('calculateKeyness', () => { + it('should return word frequencies when no other chunks provided', () => { + const chunkText = 'climate change risks environmental impact'; + const result = component.calculateKeyness(chunkText, []); + + expect(result).toBeInstanceOf(Map); + expect(result.size).toBeGreaterThan(0); + expect(result.has('climate')).toBe(true); + expect(result.has('change')).toBe(true); + }); + + it('should calculate keyness scores comparing chunk to corpus', () => { + const chunkText = 'climate change risks environmental impact'; + const allChunks = [ + { text: 'financial risks market volatility' }, + { text: 'operational risks supply chain' }, + { text: 'climate change environmental risks' }, + { text: 'regulatory compliance risks' }, + ]; + + const result = component.calculateKeyness(chunkText, allChunks); + + expect(result).toBeInstanceOf(Map); + // Words that appear more in this chunk should have higher keyness + // "impact" might be key if it appears more here than in others + expect(result.size).toBeGreaterThan(0); + }); + + it('should identify words unusually frequent in chunk', () => { + const chunkText = 'harassment consultations victims perpetrators'; + const allChunks = [ + { text: 'financial reporting quarterly results' }, + { text: 'environmental sustainability carbon emissions' }, + { text: 'product safety quality assurance' }, + ]; + + const result = component.calculateKeyness(chunkText, allChunks); + + expect(result).toBeInstanceOf(Map); + // Words like "harassment", "consultations", "victims" should be key + // because they appear in this chunk but not in others + const keyWords = Array.from(result.keys()); + expect(keyWords.length).toBeGreaterThan(0); + }); + + it('should handle empty chunk text', () => { + const result = component.calculateKeyness('', []); + expect(result).toBeInstanceOf(Map); + expect(result.size).toBe(0); + }); + + it('should filter out very short words (length <= 2)', () => { + // Use only 1-2 character words (note: "the" is 3 chars, so use shorter words) + const chunkText = 'a an be to of in on at'; + const result = component.calculateKeyness(chunkText, []); + + // Very short words (length <= 2) should be filtered out + // All words in the test string are 1-2 characters, so result should be empty + expect(result.size).toBe(0); + }); + + it('should normalize text (lowercase, remove punctuation)', () => { + const chunkText = 'Climate Change! Environmental Impact?'; + const result = component.calculateKeyness(chunkText, []); + + // Should normalize to lowercase + expect(result.has('climate')).toBe(true); + expect(result.has('Climate')).toBe(false); + expect(result.has('change')).toBe(true); + expect(result.has('Change!')).toBe(false); + }); + + it('should only return words with positive keyness (more frequent than expected)', () => { + const chunkText = 'common word common word unique term'; + const allChunks = [ + { text: 'common word common word' }, + { text: 'common word common word' }, + { text: 'common word common word' }, + ]; + + const result = component.calculateKeyness(chunkText, allChunks); + + // "unique" and "term" should have positive keyness + // "common" and "word" should have low/zero keyness (appear everywhere) + expect(result).toBeInstanceOf(Map); + // The result should only contain words that are more frequent than expected + result.forEach((score, word) => { + expect(score).toBeGreaterThan(0); + }); + }); + + it('should handle chunks with same text', () => { + const chunkText = 'test text'; + const allChunks = [ + { text: 'test text' }, + { text: 'test text' }, + ]; + + const result = component.calculateKeyness(chunkText, allChunks); + + // When all chunks are identical, keyness should be low/zero + expect(result).toBeInstanceOf(Map); + }); + }); + + describe('getWordImportanceScores', () => { + it('should return keyness scores', () => { + const chunkText = 'climate change environmental impact'; + const allChunks = [ + { text: 'financial risks' }, + { text: 'operational risks' }, + ]; + + const result = component.getWordImportanceScores(chunkText, allChunks); + + expect(result).toBeInstanceOf(Map); + expect(result.size).toBeGreaterThan(0); + }); + + it('should delegate to calculateKeyness', () => { + const chunkText = 'test'; + const allChunks = []; + + const keynessSpy = vi.spyOn(component, 'calculateKeyness'); + component.getWordImportanceScores(chunkText, allChunks); + + expect(keynessSpy).toHaveBeenCalledWith(chunkText, allChunks); + }); + }); + + describe('cosineSimilarity', () => { + it('should calculate cosine similarity between two vectors', () => { + const vecA = [1, 0, 0]; + const vecB = [1, 0, 0]; + const result = component.cosineSimilarity(vecA, vecB); + expect(result).toBe(1); // Identical vectors should have similarity 1 + }); + + it('should return 0 for orthogonal vectors', () => { + const vecA = [1, 0, 0]; + const vecB = [0, 1, 0]; + const result = component.cosineSimilarity(vecA, vecB); + expect(result).toBe(0); + }); + + it('should return 0 for vectors of different lengths', () => { + const vecA = [1, 2, 3]; + const vecB = [1, 2]; + const result = component.cosineSimilarity(vecA, vecB); + expect(result).toBe(0); + }); + + it('should handle zero vectors', () => { + const vecA = [0, 0, 0]; + const vecB = [1, 2, 3]; + const result = component.cosineSimilarity(vecA, vecB); + expect(result).toBe(0); + }); + + it('should calculate similarity for non-normalized vectors', () => { + const vecA = [1, 2, 3]; + const vecB = [2, 4, 6]; // Same direction, different magnitude + const result = component.cosineSimilarity(vecA, vecB); + expect(result).toBeCloseTo(1, 5); // Should be 1 (same direction) + }); + }); + + describe('findBestSemanticMatch', () => { + it('should find the best matching embedding', () => { + const queryEmbedding = [1, 0, 0]; + const candidateEmbeddings = [ + [1, 0, 0], // Should match best + [0, 1, 0], + [0, 0, 1], + ]; + + const result = component.findBestSemanticMatch(queryEmbedding, candidateEmbeddings); + + expect(result.index).toBe(0); + expect(result.similarity).toBe(1); + }); + + it('should return -1 index if no candidates provided', () => { + const queryEmbedding = [1, 0, 0]; + const candidateEmbeddings = []; + + const result = component.findBestSemanticMatch(queryEmbedding, candidateEmbeddings); + + expect(result.index).toBe(-1); + expect(result.similarity).toBe(-1); + }); + + it('should find best match among multiple candidates', () => { + const queryEmbedding = [0.8, 0.6, 0]; + const candidateEmbeddings = [ + [0.1, 0.1, 0.1], // Low similarity + [0.7, 0.5, 0.1], // Higher similarity + [0.1, 0.1, 0.1], // Low similarity + ]; + + const result = component.findBestSemanticMatch(queryEmbedding, candidateEmbeddings); + + expect(result.index).toBe(1); + expect(result.similarity).toBeGreaterThan(0.5); + }); + }); + + describe('splitTextIntoSegments', () => { + it('should split text items into logical segments', () => { + const textItems = [ + { str: 'First sentence.' }, + { str: ' ' }, + { str: 'Second sentence!' }, + { str: ' ' }, + { str: 'Third sentence?' }, + ]; + + const result = component.splitTextIntoSegments(textItems); + + expect(result).toBeInstanceOf(Array); + expect(result.length).toBeGreaterThan(0); + expect(result[0]).toHaveProperty('text'); + expect(result[0]).toHaveProperty('items'); + }); + + it('should split on sentence boundaries', () => { + const textItems = [ + { str: 'Sentence one.' }, + { str: ' ' }, + { str: 'Sentence two.' }, + ]; + + const result = component.splitTextIntoSegments(textItems); + + expect(result.length).toBeGreaterThanOrEqual(2); + }); + + it('should split after ~100 characters', () => { + const longText = 'a'.repeat(150); + const textItems = [{ str: longText }]; + + const result = component.splitTextIntoSegments(textItems); + + expect(result.length).toBeGreaterThan(0); + }); + + it('should filter out segments shorter than 10 characters', () => { + const textItems = [ + { str: 'Short.' }, + { str: ' ' }, + { str: 'This is a longer sentence that should be included.' }, + ]; + + const result = component.splitTextIntoSegments(textItems); + + // Should only include the longer segment + result.forEach(seg => { + expect(seg.text.trim().length).toBeGreaterThanOrEqual(10); + }); + }); + }); + + describe('calculateBoundingBox', () => { + it('should return null for empty text items', () => { + const viewport = { + width: 800, + height: 600, + scale: 1.0, + convertToViewportPoint: vi.fn((x, y) => [x, y]), + }; + + const result = component.calculateBoundingBox([], viewport); + expect(result).toBeNull(); + }); + + it('should calculate bounding box from text items', () => { + const viewport = { + width: 800, + height: 600, + scale: 1.0, + convertToViewportPoint: vi.fn((x, y) => [x * viewport.scale, y * viewport.scale]), + }; + + const textItems = [ + { + transform: [1, 0, 0, 1, 100, 200], // x=100, y=200 + width: 50, + height: 12, + }, + { + transform: [1, 0, 0, 1, 150, 200], // x=150, y=200 + width: 50, + height: 12, + }, + ]; + + const result = component.calculateBoundingBox(textItems, viewport); + + expect(result).not.toBeNull(); + expect(result).toHaveProperty('x'); + expect(result).toHaveProperty('y'); + expect(result).toHaveProperty('width'); + expect(result).toHaveProperty('height'); + expect(result.width).toBeGreaterThan(0); + expect(result.height).toBeGreaterThan(0); + }); + + it('should handle items with alternative coordinate format', () => { + const viewport = { + width: 800, + height: 600, + scale: 1.0, + convertToViewportPoint: vi.fn((x, y) => [x, y]), + }; + + const textItems = [ + { + x: 100, + y: 200, + width: 50, + height: 12, + }, + ]; + + const result = component.calculateBoundingBox(textItems, viewport); + + expect(result).not.toBeNull(); + expect(result.width).toBeGreaterThan(0); + }); + + it('should return null if width or height is less than 1', () => { + const viewport = { + width: 800, + height: 600, + scale: 1.0, + convertToViewportPoint: vi.fn((x, y) => [x, y]), + }; + + const textItems = [ + { + transform: [1, 0, 0, 1, 100, 200], + width: 0.5, // Too small + height: 0.5, + }, + ]; + + const result = component.calculateBoundingBox(textItems, viewport); + expect(result).toBeNull(); + }); + }); + + describe('getFilteredChunks', () => { + beforeEach(() => { + // Reset component state + component._chunks = [ + { text: 'chunk 1', question_id: 'q1', is_evidence: true }, + { text: 'chunk 2', question_id: 'q1', is_evidence: false }, + { text: 'chunk 3', question_id: 'q2', is_evidence: true }, + ]; + component._questions = [ + { question_id: 'q1', chunks: [] }, // Empty chunks array means fallback to filtering by question_id + { question_id: 'q2', chunks: [] }, + ]; + component._selectedQuestionId = null; + component._showEvidenceOnly = false; + }); + + it('should return all chunks when no filter applied', () => { + component._selectedQuestionId = null; + component._showEvidenceOnly = false; + + const result = component.getFilteredChunks(); + + expect(result.length).toBe(3); + }); + + it('should filter by question ID', () => { + component._selectedQuestionId = 'q1'; + component._showEvidenceOnly = false; + + const result = component.getFilteredChunks(); + + // Since question.chunks is empty, it falls back to filtering _chunks by question_id + expect(result.length).toBe(2); + expect(result.every(c => c.question_id === 'q1')).toBe(true); + }); + + it('should filter by evidence when enabled', () => { + component._selectedQuestionId = null; + component._showEvidenceOnly = true; + + const result = component.getFilteredChunks(); + + expect(result.length).toBe(2); + expect(result.every(c => c.is_evidence === true || c.is_evidence === 1)).toBe(true); + }); + + it('should filter by both question and evidence', () => { + component._selectedQuestionId = 'q1'; + component._showEvidenceOnly = true; + + const result = component.getFilteredChunks(); + + expect(result.length).toBe(1); + expect(result[0].question_id).toBe('q1'); + expect(result[0].is_evidence).toBe(true); + }); + + it('should handle integer evidence values (SQLite)', () => { + component._chunks = [ + { text: 'chunk 1', is_evidence: 1 }, + { text: 'chunk 2', is_evidence: 0 }, + ]; + component._selectedQuestionId = null; + component._showEvidenceOnly = true; + + const result = component.getFilteredChunks(); + + expect(result.length).toBe(1); + expect(result[0].is_evidence).toBe(1); + }); + }); +}); + diff --git a/report_analyst_enterprise/components/web/vite.config.js b/report_analyst_enterprise/components/web/vite.config.js new file mode 100644 index 00000000..c9a4e222 --- /dev/null +++ b/report_analyst_enterprise/components/web/vite.config.js @@ -0,0 +1,28 @@ +import { defineConfig } from 'vite'; + +export default defineConfig({ + define: { + 'process.env': JSON.stringify({ NODE_ENV: 'production' }), + process: JSON.stringify({ env: { NODE_ENV: 'production' } }), + }, + build: { + lib: { + entry: { + 'pdf-viewer': 'src/pdf-viewer.js', + }, + name: '[name]', + fileName: (format, entryName) => `${entryName}.${format}.js`, + formats: ['es'], + }, + rollupOptions: { + external: [], + output: { + globals: {}, + }, + }, + }, + server: { + port: 3004, + cors: true, + }, +}); diff --git a/report_analyst_enterprise/components/web/vitest.config.js b/report_analyst_enterprise/components/web/vitest.config.js new file mode 100644 index 00000000..4ed876e6 --- /dev/null +++ b/report_analyst_enterprise/components/web/vitest.config.js @@ -0,0 +1,14 @@ +import { defineConfig } from 'vitest/config'; + +export default defineConfig({ + test: { + environment: 'jsdom', + globals: true, + setupFiles: [], + coverage: { + provider: 'v8', + reporter: ['text', 'json', 'html'], + }, + }, +}); + diff --git a/tests/test_pdf_viewer_apptest.py b/tests/test_pdf_viewer_apptest.py new file mode 100644 index 00000000..4c15f4eb --- /dev/null +++ b/tests/test_pdf_viewer_apptest.py @@ -0,0 +1,353 @@ +# ruff: noqa: E501 +""" +AppTest for PDF viewer screen in Streamlit app. + +This test uses Streamlit's AppTest framework to test the PDF viewer +functionality in the "View Report" tab, verifying that: +1. Chunks are correctly loaded from the database +2. PDF viewer component is rendered +3. Chunks are passed to the component correctly +""" + +import json +import os +import shutil +import tempfile +from datetime import datetime +from pathlib import Path + +import pytest +from sqlalchemy import text +from streamlit.testing.v1 import AppTest + +from report_analyst.core.cache_manager import CacheManager + + +@pytest.fixture(autouse=True) +def setup_test_env(): + """Setup test environment variables""" + original_storage = os.environ.get("STORAGE_PATH") + test_storage = Path(__file__).parent / "test_storage_pdf_viewer_apptest" + os.environ["STORAGE_PATH"] = str(test_storage) + yield + # Cleanup after tests + if test_storage.exists(): + shutil.rmtree(test_storage) + # Restore original + if original_storage: + os.environ["STORAGE_PATH"] = original_storage + elif "STORAGE_PATH" in os.environ: + del os.environ["STORAGE_PATH"] + + +@pytest.fixture +def temp_db(): + """Create a temporary database for testing""" + temp_dir = tempfile.mkdtemp() + db_path = Path(temp_dir) / "test_cache.db" + cache_manager = CacheManager(db_path=str(db_path)) + yield cache_manager, temp_dir + shutil.rmtree(temp_dir) + + +@pytest.fixture +def sample_pdf_file(): + """Create a sample PDF file for testing""" + temp_dir = tempfile.mkdtemp() + pdf_path = Path(temp_dir) / "test_report.pdf" + # Create a minimal valid PDF + pdf_content = b"%PDF-1.4\n%Test PDF\n1 0 obj\n<< /Type /Catalog /Pages 2 0 R >>\nendobj\n2 0 obj\n<< /Type /Pages /Kids [3 0 R] /Count 1 >>\nendobj\n3 0 obj\n<< /Type /Page /Parent 2 0 R /MediaBox [0 0 612 792] >>\nendobj\nxref\n0 4\ntrailer\n<< /Size 4 /Root 1 0 R >>\nstartxref\n100\n%%EOF" + pdf_path.write_bytes(pdf_content) + yield str(pdf_path), temp_dir + shutil.rmtree(temp_dir) + + +def test_pdf_viewer_view_report_tab(temp_db, sample_pdf_file): + """ + Test that the View Report tab displays PDF viewer with chunks. + + This test: + 1. Sets up chunks in the database + 2. Navigates to View Report tab + 3. Sets up session state with file and cached results + 4. Verifies PDF viewer is rendered + """ + cache_manager, _db_temp_dir = temp_db + file_path, _pdf_temp_dir = sample_pdf_file + + question_id = "tcfd_1" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Step 1: Create chunks in document_chunks table + chunk_texts = [ + "This is the first chunk about climate risks on page 1.", + "This is the second chunk about governance on page 2.", + ] + + with cache_manager.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + for i, chunk_text in enumerate(chunk_texts): + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps({"page_number": i + 1}), + "created_at": timestamp, + }, + ) + + # Step 2: Save analysis result with chunks + result = { + "ANSWER": "Test answer about climate risks", + "SCORE": 7, + "EVIDENCE": ["evidence1"], + "GAPS": [], + "chunks": [ + { + "text": chunk_texts[i], + "chunk_order": i, + "similarity_score": 0.85 - (i * 0.05), + "llm_score": 0.75 if i == 0 else None, + "is_evidence": i == 0, + "evidence_order": 1 if i == 0 else None, + "metadata": {"page_number": i + 1}, + } + for i in range(len(chunk_texts)) + ], + } + + cache_manager.save_analysis(file_path, question_id, result, config) + + # Step 3: Set up AppTest + at = AppTest.from_file("report_analyst/streamlit_app.py") + + # Navigate to View Report tab + at.session_state["nav_page"] = "View Report" + + # Set up file in session state (simulating file selection) + # The app expects previous_files to contain the file + # We'll need to set up the file path in a way the app can find it + + # Set up cached results in session state (as the app would load them) + cached_results = cache_manager.get_analysis(file_path, config, [question_id]) + + # Format results as the app expects + # AppTest session_state doesn't support .get(), so use direct access + at.session_state["results"] = {"answers": {}} + for q_id, data in cached_results.items(): + at.session_state["results"]["answers"][q_id] = data + + # Run the app + at.run(timeout=10) + + # Step 4: Verify app loaded without errors + assert not at.exception, f"App should load without errors: {at.exception}" + + # Step 5: Verify we're on View Report page + assert at.session_state["nav_page"] == "View Report", "Should be on View Report page" + + # Step 6: Verify PDF viewer component is available + # The app checks for pdf_viewer_available, so we verify the page structure + # Check for "PDF Viewer" subheader or related content + page_text = str(at) + has_pdf_viewer_mention = ( + "PDF Viewer" in page_text or + "pdf_viewer" in page_text.lower() or + "View PDF" in page_text + ) + + # Note: The PDF viewer component might not be directly testable via AppTest + # but we can verify the page structure and that chunks are loaded + results = at.session_state["results"] if "results" in at.session_state else {} + answers = results["answers"] if isinstance(results, dict) and "answers" in results else {} + assert has_pdf_viewer_mention or len(answers) > 0, ( + "PDF viewer section should be present or chunks should be loaded" + ) + + # Step 7: Verify chunks are in session state + # AppTest session_state doesn't support .get(), so use direct access with try/except + try: + results = at.session_state["results"] + answers = results["answers"] + assert question_id in answers, f"Question {question_id} should be in results" + assert "chunks" in answers[question_id], "Chunks should be in analysis result" + assert len(answers[question_id]["chunks"]) == 2, "Should have 2 chunks" + except KeyError: + # If results aren't in session state, that's also a failure + pytest.fail("Results should be in session state") + + +def test_pdf_viewer_with_no_chunks(temp_db, sample_pdf_file): + """ + Test that View Report tab handles missing chunks gracefully. + """ + cache_manager, _db_temp_dir = temp_db + file_path, _pdf_temp_dir = sample_pdf_file + + question_id = "tcfd_2" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Save analysis without chunks + result = { + "ANSWER": "Test answer without chunks", + "SCORE": 5, + "EVIDENCE": [], + "GAPS": ["No chunks available"], + "chunks": [], # Empty chunks + } + + cache_manager.save_analysis(file_path, question_id, result, config) + + # Set up AppTest + at = AppTest.from_file("report_analyst/streamlit_app.py") + at.session_state["nav_page"] = "View Report" + + # Set up cached results + cached_results = cache_manager.get_analysis(file_path, config, [question_id]) + at.session_state["results"] = {"answers": {}} + for q_id, data in cached_results.items(): + at.session_state["results"]["answers"][q_id] = data + + # Run the app + at.run(timeout=10) + + # Verify app loads without errors + assert not at.exception, f"App should load without errors: {at.exception}" + + # Verify we're on View Report page + assert at.session_state["nav_page"] == "View Report" + + # Verify chunks are empty but result exists + try: + results = at.session_state["results"] + answers = results["answers"] + if question_id in answers: + # Handle both dict access and .get() if available + if isinstance(answers[question_id], dict): + answers[question_id].get("chunks", []) + # The app should still show the PDF viewer even without chunks + # Check for either "answer" or "ANSWER" key, or just that the result exists + has_answer = "answer" in answers[question_id] or "ANSWER" in answers[question_id] + # If no answer key, at least the result dict should exist + assert len(answers[question_id]) > 0 or has_answer, \ + "Analysis result should exist even without chunks" + else: + # If it's not a dict, just verify it exists + assert answers[question_id] is not None, "Result should exist" + except KeyError: + # Results might not be set if app didn't load them - that's acceptable for this test + # The important thing is the app loads without errors + pass + + +def test_pdf_viewer_multiple_questions(temp_db, sample_pdf_file): + """ + Test that View Report tab handles multiple questions with chunks. + """ + cache_manager, _db_temp_dir = temp_db + file_path, _pdf_temp_dir = sample_pdf_file + + question_ids = ["tcfd_1", "tcfd_2"] + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 3, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Create shared chunks + shared_chunk_texts = ["Shared chunk 1", "Shared chunk 2"] + + with cache_manager.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + for i, chunk_text in enumerate(shared_chunk_texts): + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps({"page_number": i + 1}), + "created_at": timestamp, + }, + ) + + # Save analysis for each question + for q_idx, question_id in enumerate(question_ids): + result = { + "ANSWER": f"Answer for {question_id}", + "SCORE": 7, + "EVIDENCE": [], + "GAPS": [], + "chunks": [ + { + "text": shared_chunk_texts[i], + "chunk_order": i, + "similarity_score": 0.8 + (q_idx * 0.05), + "llm_score": None, + "is_evidence": i == 0, + "evidence_order": 1 if i == 0 else None, + "metadata": {"page_number": i + 1}, + } + for i in range(len(shared_chunk_texts)) + ], + } + cache_manager.save_analysis(file_path, question_id, result, config) + + # Set up AppTest + at = AppTest.from_file("report_analyst/streamlit_app.py") + at.session_state["nav_page"] = "View Report" + + # Set up cached results for all questions + cached_results = cache_manager.get_analysis(file_path, config, question_ids) + at.session_state["results"] = {"answers": {}} + for q_id, data in cached_results.items(): + at.session_state["results"]["answers"][q_id] = data + + # Run the app + at.run(timeout=10) + + # Verify app loads + assert not at.exception, f"App should load without errors: {at.exception}" + + # Verify all questions are in results + try: + results = at.session_state["results"] + answers = results["answers"] + assert len(answers) == 2, f"Should have 2 questions, got {len(answers)}" + + for question_id in question_ids: + assert question_id in answers, f"Question {question_id} should be in results" + assert "chunks" in answers[question_id], f"Question {question_id} should have chunks" + assert len(answers[question_id]["chunks"]) == 2, \ + f"Question {question_id} should have 2 chunks" + except KeyError: + pytest.fail("Results should be in session state") + diff --git a/tests/test_pdf_viewer_chunks.py b/tests/test_pdf_viewer_chunks.py new file mode 100644 index 00000000..959545e4 --- /dev/null +++ b/tests/test_pdf_viewer_chunks.py @@ -0,0 +1,762 @@ +# ruff: noqa: E501 +""" +Tests for PDF viewer component with chunk loading verification. + +This test suite verifies that: +1. Chunks are correctly saved to the database during analysis +2. Chunks are correctly retrieved from the database +3. Chunks are properly formatted and passed to the PDF viewer component +4. The PDF viewer receives the expected chunk data structure +""" + +import json +import os +import shutil +import tempfile +from datetime import datetime +from pathlib import Path +from unittest.mock import MagicMock, patch + +import pytest +from sqlalchemy import text + +from report_analyst.core.cache_manager import CacheManager + + +@pytest.fixture(autouse=True) +def setup_test_env(): + """Setup test environment variables""" + original_storage = os.environ.get("STORAGE_PATH") + test_storage = Path(__file__).parent / "test_storage_pdf_viewer" + os.environ["STORAGE_PATH"] = str(test_storage) + yield + # Cleanup after tests + if test_storage.exists(): + shutil.rmtree(test_storage) + # Restore original + if original_storage: + os.environ["STORAGE_PATH"] = original_storage + elif "STORAGE_PATH" in os.environ: + del os.environ["STORAGE_PATH"] + + +@pytest.fixture +def temp_db(): + """Create a temporary database for testing""" + temp_dir = tempfile.mkdtemp() + db_path = Path(temp_dir) / "test_cache.db" + cache_manager = CacheManager(db_path=str(db_path)) + yield cache_manager + import shutil + shutil.rmtree(temp_dir) + + +@pytest.fixture +def sample_pdf_file(): + """Create a sample PDF file for testing""" + temp_dir = tempfile.mkdtemp() + pdf_path = Path(temp_dir) / "test_report.pdf" + # Create a minimal valid PDF + pdf_content = b"%PDF-1.4\n%Test PDF\n1 0 obj\n<< /Type /Catalog /Pages 2 0 R >>\nendobj\n2 0 obj\n<< /Type /Pages /Kids [3 0 R] /Count 1 >>\nendobj\n3 0 obj\n<< /Type /Page /Parent 2 0 R /MediaBox [0 0 612 792] >>\nendobj\nxref\n0 4\ntrailer\n<< /Size 4 /Root 1 0 R >>\nstartxref\n100\n%%EOF" + pdf_path.write_bytes(pdf_content) + yield str(pdf_path) + import shutil + shutil.rmtree(temp_dir) + + +def test_pdf_viewer_chunk_loading(temp_db, sample_pdf_file): + """ + Test that chunks are correctly loaded from database and passed to PDF viewer. + + This test: + 1. Creates chunks in document_chunks table + 2. Saves analysis results with chunk_relevance links + 3. Retrieves chunks via get_analysis + 4. Verifies chunks are in the correct format for PDF viewer + """ + file_path = sample_pdf_file + question_id = "tcfd_1" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Step 1: Create chunks in document_chunks table + chunk_texts = [ + "This is the first chunk about climate risks.", + "This is the second chunk about governance.", + "This is the third chunk about metrics.", + ] + + with temp_db.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + chunk_ids = [] + + for i, chunk_text in enumerate(chunk_texts): + # Insert chunk (with or without embedding - doesn't matter for PDF viewer) + embedding_bytes = None # PDF viewer doesn't need embeddings + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": embedding_bytes, + "metadata": json.dumps({"page_number": i + 1}), + "created_at": timestamp, + }, + ) + # Get the chunk ID + result = conn.execute( + text(""" + SELECT id FROM document_chunks + WHERE file_path = :file_path + AND chunk_text = :chunk_text + AND chunk_size = :chunk_size + AND chunk_overlap = :chunk_overlap + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + }, + ) + row = result.fetchone() + assert row is not None, f"Chunk {i} was not inserted" + chunk_ids.append(row[0]) + + # Step 2: Save analysis result with chunks + result = { + "ANSWER": "Test answer about climate risks", + "SCORE": 7, + "EVIDENCE": ["evidence1", "evidence2"], + "GAPS": ["gap1"], + "chunks": [ + { + "text": chunk_texts[0], + "chunk_order": 0, + "similarity_score": 0.85, + "llm_score": 0.75, + "is_evidence": True, + "evidence_order": 1, + "metadata": {"page_number": 1}, + }, + { + "text": chunk_texts[1], + "chunk_order": 1, + "similarity_score": 0.80, + "llm_score": None, + "is_evidence": False, + "evidence_order": None, + "metadata": {"page_number": 2}, + }, + { + "text": chunk_texts[2], + "chunk_order": 2, + "similarity_score": 0.75, + "llm_score": 0.70, + "is_evidence": True, + "evidence_order": 2, + "metadata": {"page_number": 3}, + }, + ], + } + + temp_db.save_analysis(file_path, question_id, result, config) + + # Step 3: Retrieve chunks via get_analysis + retrieved = temp_db.get_analysis(file_path, config, [question_id]) + + # Step 4: Verify chunks are retrieved correctly + assert question_id in retrieved, f"Question {question_id} not in retrieved results" + assert "chunks" in retrieved[question_id], "Chunks not in retrieved data" + + chunks = retrieved[question_id]["chunks"] + assert len(chunks) == 3, f"Expected 3 chunks, got {len(chunks)}" + + # Step 5: Verify chunk structure matches what PDF viewer expects + expected_fields = ["text", "metadata", "chunk_order", "similarity_score", "is_evidence"] + for i, chunk in enumerate(chunks): + for field in expected_fields: + assert field in chunk, f"Chunk {i} missing field: {field}" + + # Verify specific values + assert chunk["text"] == chunk_texts[i], f"Chunk {i} text mismatch" + assert chunk["chunk_order"] == i, f"Chunk {i} order mismatch" + assert chunk["metadata"]["page_number"] == i + 1, f"Chunk {i} page number mismatch" + assert isinstance(chunk["similarity_score"], (int, float)), f"Chunk {i} similarity_score should be numeric" + # SQLite stores booleans as integers (0/1), so check for bool or int 0/1 + assert isinstance(chunk["is_evidence"], (bool, int)), f"Chunk {i} is_evidence should be boolean or int" + if isinstance(chunk["is_evidence"], int): + assert chunk["is_evidence"] in [0, 1], f"Chunk {i} is_evidence should be 0 or 1 if int" + # Convert to bool for consistency (SQLite returns 0/1) + bool(chunk["is_evidence"]) + + # Step 6: Verify chunks can be formatted for PDF viewer + chunks_data = {question_id: chunks} + + # This is the format expected by pdf_viewer function + assert len(chunks_data[question_id]) == 3 + assert all("text" in chunk for chunk in chunks_data[question_id]) + assert all("metadata" in chunk for chunk in chunks_data[question_id]) + assert all("is_evidence" in chunk for chunk in chunks_data[question_id]) + + +def test_pdf_viewer_chunk_loading_with_evidence_filter(temp_db, sample_pdf_file): + """ + Test that chunks are correctly filtered by evidence flag for PDF viewer. + """ + file_path = sample_pdf_file + question_id = "tcfd_2" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Create chunks with mixed evidence flags + chunk_data = [ + {"text": "Evidence chunk 1", "is_evidence": True, "similarity": 0.9}, + {"text": "Non-evidence chunk", "is_evidence": False, "similarity": 0.6}, + {"text": "Evidence chunk 2", "is_evidence": True, "similarity": 0.85}, + ] + + # Save chunks to document_chunks + with temp_db.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + for i, chunk_info in enumerate(chunk_data): + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_info["text"], + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps({"page_number": i + 1}), + "created_at": timestamp, + }, + ) + + # Save analysis with chunks + result = { + "ANSWER": "Test answer", + "SCORE": 8, + "EVIDENCE": [], + "GAPS": [], + "chunks": [ + { + "text": chunk["text"], + "chunk_order": i, + "similarity_score": chunk["similarity"], + "llm_score": None, + "is_evidence": chunk["is_evidence"], + "evidence_order": i + 1 if chunk["is_evidence"] else None, + "metadata": {"page_number": i + 1}, + } + for i, chunk in enumerate(chunk_data) + ], + } + + temp_db.save_analysis(file_path, question_id, result, config) + + # Retrieve chunks + retrieved = temp_db.get_analysis(file_path, config, [question_id]) + chunks = retrieved[question_id]["chunks"] + + # Verify all chunks are retrieved + assert len(chunks) == 3 + + # Verify evidence flags are correct + evidence_chunks = [c for c in chunks if c["is_evidence"]] + non_evidence_chunks = [c for c in chunks if not c["is_evidence"]] + + assert len(evidence_chunks) == 2, "Should have 2 evidence chunks" + assert len(non_evidence_chunks) == 1, "Should have 1 non-evidence chunk" + + # Verify chunks can be filtered for PDF viewer (show_evidence_only=True) + all_chunks = chunks + evidence_only = [c for c in all_chunks if c.get("is_evidence", False)] + + assert len(evidence_only) == 2, "Evidence filter should return 2 chunks" + + +def test_pdf_viewer_chunk_loading_empty_chunks(temp_db, sample_pdf_file): + """ + Test that PDF viewer handles empty chunks gracefully. + """ + file_path = sample_pdf_file + question_id = "tcfd_3" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Save analysis with no chunks + result = { + "ANSWER": "Test answer without chunks", + "SCORE": 5, + "EVIDENCE": [], + "GAPS": ["No chunks available"], + "chunks": [], # Empty chunks + } + + temp_db.save_analysis(file_path, question_id, result, config) + + # Retrieve chunks + retrieved = temp_db.get_analysis(file_path, config, [question_id]) + + # Verify empty chunks are handled + assert question_id in retrieved + chunks = retrieved[question_id].get("chunks", []) + assert len(chunks) == 0, "Should have 0 chunks" + + # Verify PDF viewer format works with empty chunks + chunks_data = {question_id: chunks} + + assert len(chunks_data[question_id]) == 0 + assert chunks_data[question_id] == [] + + +def test_pdf_viewer_chunk_loading_multiple_questions(temp_db, sample_pdf_file): + """ + Test that chunks are correctly loaded for multiple questions. + """ + file_path = sample_pdf_file + question_ids = ["tcfd_1", "tcfd_2"] + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 3, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Create shared chunks + shared_chunk_texts = [ + "Shared chunk 1", + "Shared chunk 2", + ] + + # Save chunks to document_chunks + with temp_db.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + for i, chunk_text in enumerate(shared_chunk_texts): + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps({"page_number": i + 1}), + "created_at": timestamp, + }, + ) + + # Save analysis for each question with different chunks + for q_idx, question_id in enumerate(question_ids): + result = { + "ANSWER": f"Answer for {question_id}", + "SCORE": 7, + "EVIDENCE": [], + "GAPS": [], + "chunks": [ + { + "text": shared_chunk_texts[i], + "chunk_order": i, + "similarity_score": 0.8 + (q_idx * 0.05), # Different scores per question + "llm_score": None, + "is_evidence": i == 0, # First chunk is evidence + "evidence_order": 1 if i == 0 else None, + "metadata": {"page_number": i + 1}, + } + for i in range(len(shared_chunk_texts)) + ], + } + temp_db.save_analysis(file_path, question_id, result, config) + + # Retrieve chunks for all questions + retrieved = temp_db.get_analysis(file_path, config, question_ids) + + # Verify both questions have chunks + assert len(retrieved) == 2, f"Expected 2 questions, got {len(retrieved)}" + + for question_id in question_ids: + assert question_id in retrieved, f"Question {question_id} not in results" + chunks = retrieved[question_id].get("chunks", []) + assert len(chunks) == 2, f"Question {question_id} should have 2 chunks" + + # Verify chunks are correctly associated with question + for chunk in chunks: + assert "text" in chunk + assert chunk["text"] in shared_chunk_texts + + # Verify chunks can be formatted for PDF viewer with multiple questions + chunks_data = { + q_id: retrieved[q_id]["chunks"] + for q_id in question_ids + } + {q_id: f"Question {q_id}" for q_id in question_ids} + + assert len(chunks_data) == 2 + assert all(len(chunks_data[q_id]) == 2 for q_id in question_ids) + + +def test_pdf_viewer_chunk_metadata_structure(temp_db, sample_pdf_file): + """ + Test that chunk metadata is correctly structured for PDF viewer. + """ + file_path = sample_pdf_file + question_id = "tcfd_4" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Create chunk with rich metadata + chunk_text = "Chunk with metadata" + chunk_metadata = { + "page_number": 5, + "section": "Risk Management", + "subsection": "Climate Risks", + } + + # Save chunk + with temp_db.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps(chunk_metadata), + "created_at": timestamp, + }, + ) + + # Save analysis + result = { + "ANSWER": "Test answer", + "SCORE": 7, + "EVIDENCE": [], + "GAPS": [], + "chunks": [ + { + "text": chunk_text, + "chunk_order": 0, + "similarity_score": 0.85, + "llm_score": 0.75, + "is_evidence": True, + "evidence_order": 1, + "metadata": chunk_metadata, + } + ], + } + + temp_db.save_analysis(file_path, question_id, result, config) + + # Retrieve chunks + retrieved = temp_db.get_analysis(file_path, config, [question_id]) + chunks = retrieved[question_id]["chunks"] + + # Verify metadata structure + assert len(chunks) == 1 + chunk = chunks[0] + + assert "metadata" in chunk + assert isinstance(chunk["metadata"], dict) + assert chunk["metadata"]["page_number"] == 5 + assert chunk["metadata"]["section"] == "Risk Management" + assert chunk["metadata"]["subsection"] == "Climate Risks" + + # Verify metadata is suitable for PDF viewer (page_number is key for highlighting) + assert "page_number" in chunk["metadata"], "PDF viewer needs page_number for highlighting" + + +def test_pdf_viewer_function_chunk_formatting(temp_db, sample_pdf_file): + """ + Test that chunks retrieved from database are correctly formatted for PDF viewer function. + + This test verifies the integration between cache_manager.get_analysis and pdf_viewer function. + """ + file_path = sample_pdf_file + question_id = "tcfd_5" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 5, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Create and save chunks with analysis + chunk_texts = [ + "First chunk with page 1", + "Second chunk with page 2", + ] + + # Save chunks to document_chunks + with temp_db.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + for i, chunk_text in enumerate(chunk_texts): + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_text, + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps({"page_number": i + 1}), + "created_at": timestamp, + }, + ) + + # Save analysis with chunks + result = { + "ANSWER": "Test answer", + "SCORE": 7, + "EVIDENCE": [], + "GAPS": [], + "chunks": [ + { + "text": chunk_texts[i], + "chunk_order": i, + "similarity_score": 0.8 + (i * 0.05), + "llm_score": 0.7 if i == 0 else None, + "is_evidence": i == 0, + "evidence_order": 1 if i == 0 else None, + "metadata": {"page_number": i + 1}, + } + for i in range(len(chunk_texts)) + ], + } + + temp_db.save_analysis(file_path, question_id, result, config) + + # Retrieve chunks (simulating what streamlit_app.py does) + cached_results = temp_db.get_analysis(file_path, config, [question_id]) + + # Format chunks for PDF viewer (simulating streamlit_app.py logic) + chunks_by_question = {} + questions_data = {} + + for q_id, data in cached_results.items(): + chunks = data.get("chunks", []) + chunks_by_question[q_id] = chunks + questions_data[q_id] = "Test question text" + + # Verify chunks are in the correct format for pdf_viewer function + assert question_id in chunks_by_question + chunks = chunks_by_question[question_id] + + # Verify chunk structure matches pdf_viewer expectations + assert len(chunks) == 2 + + for chunk in chunks: + # Required fields for PDF viewer + assert "text" in chunk, "PDF viewer needs chunk text" + assert "metadata" in chunk, "PDF viewer needs chunk metadata" + assert "is_evidence" in chunk, "PDF viewer needs is_evidence flag" + assert "similarity_score" in chunk, "PDF viewer needs similarity_score" + + # Metadata should have page_number for highlighting + assert "page_number" in chunk["metadata"], "PDF viewer needs page_number in metadata" + assert isinstance(chunk["metadata"]["page_number"], int), "page_number should be int" + + # Verify chunk can be JSON serialized (pdf_viewer uses json.dumps) + try: + json_str = json.dumps(chunk) + assert len(json_str) > 0 + except (TypeError, ValueError) as e: + pytest.fail(f"Chunk not JSON serializable: {e}") + + # Verify chunks_by_question structure is correct for pdf_viewer + assert isinstance(chunks_by_question, dict) + assert all(isinstance(chunks, list) for chunks in chunks_by_question.values()) + assert all(isinstance(chunk, dict) for chunks in chunks_by_question.values() for chunk in chunks) + + # Verify questions_data structure + assert isinstance(questions_data, dict) + assert all(isinstance(q_text, str) for q_text in questions_data.values()) + + # This is the exact format that pdf_viewer expects: + # pdf_viewer( + # pdf_path=file_path, + # chunks_data=chunks_by_question, # Dict[str, List[Dict]] + # questions_data=questions_data, # Dict[str, str] + # ... + # ) + # The test verifies this structure is correct + + +def test_pdf_viewer_receives_chunks_correctly(temp_db, sample_pdf_file): + """ + Test that PDF viewer function receives chunks in the correct format. + + This test mocks the PDF viewer component and verifies it receives + the correct chunk data structure. + """ + file_path = sample_pdf_file + question_id = "tcfd_6" + config = { + "chunk_size": 500, + "chunk_overlap": 20, + "top_k": 3, + "model": "gpt-4o-mini", + "question_set": "tcfd", + } + + # Create and save chunks + chunk_data = [ + {"text": "Chunk 1", "page": 1, "is_evidence": True, "similarity": 0.9}, + {"text": "Chunk 2", "page": 2, "is_evidence": False, "similarity": 0.7}, + ] + + with temp_db.db_manager.get_connection() as conn: + timestamp = datetime.now().isoformat() + for _i, chunk_info in enumerate(chunk_data): + conn.execute( + text(""" + INSERT INTO document_chunks + (file_path, chunk_text, chunk_size, chunk_overlap, embedding, metadata, created_at) + VALUES (:file_path, :chunk_text, :chunk_size, :chunk_overlap, :embedding, :metadata, :created_at) + """), + { + "file_path": file_path, + "chunk_text": chunk_info["text"], + "chunk_size": config["chunk_size"], + "chunk_overlap": config["chunk_overlap"], + "embedding": None, + "metadata": json.dumps({"page_number": chunk_info["page"]}), + "created_at": timestamp, + }, + ) + + # Save analysis + result = { + "ANSWER": "Test answer", + "SCORE": 8, + "EVIDENCE": [], + "GAPS": [], + "chunks": [ + { + "text": chunk["text"], + "chunk_order": i, + "similarity_score": chunk["similarity"], + "llm_score": None, + "is_evidence": chunk["is_evidence"], + "evidence_order": 1 if chunk["is_evidence"] else None, + "metadata": {"page_number": chunk["page"]}, + } + for i, chunk in enumerate(chunk_data) + ], + } + + temp_db.save_analysis(file_path, question_id, result, config) + + # Retrieve chunks (as streamlit_app.py does) + cached_results = temp_db.get_analysis(file_path, config, [question_id]) + + # Format for PDF viewer (as streamlit_app.py does) + chunks_by_question = {} + questions_data = {} + + for q_id, data in cached_results.items(): + chunks_by_question[q_id] = data.get("chunks", []) + questions_data[q_id] = "Test question" + + # Mock the PDF viewer component + with patch('report_analyst_enterprise.components.streamlit_component.backend.pdf_viewer.components') as mock_components: + mock_component = MagicMock() + mock_components.declare_component.return_value = mock_component + mock_component.return_value = None # No return value from component + + # Import and call pdf_viewer + from report_analyst_enterprise.components.streamlit_component.backend.pdf_viewer import pdf_viewer + + result = pdf_viewer( + pdf_path=file_path, + chunks_data=chunks_by_question, + questions_data=questions_data, + height=800, + key="test_pdf_viewer" + ) + + # Verify component was called + assert mock_components.declare_component.called, "PDF viewer component should be declared" + assert mock_component.called, "PDF viewer component should be called" + + # Get the call arguments + call_args = mock_component.call_args + assert call_args is not None, "Component should be called with arguments" + + # Verify chunks were passed + call_kwargs = call_args.kwargs + assert "chunks" in call_kwargs, "Component should receive chunks parameter" + + # Parse chunks JSON + chunks_json = call_kwargs["chunks"] + assert isinstance(chunks_json, str), "Chunks should be JSON string" + chunks_list = json.loads(chunks_json) + + # Verify chunks structure + assert len(chunks_list) == 2, f"Should have 2 chunks, got {len(chunks_list)}" + + for chunk in chunks_list: + assert "text" in chunk + assert "question_id" in chunk, "Chunk should have question_id for filtering" + assert chunk["question_id"] == question_id + assert "metadata" in chunk + assert "page_number" in chunk["metadata"] + assert "is_evidence" in chunk + assert "similarity_score" in chunk + + # Verify questions were passed + assert "questions" in call_kwargs, "Component should receive questions parameter" + questions_json = call_kwargs["questions"] + questions_list = json.loads(questions_json) + + assert len(questions_list) == 1 + assert questions_list[0]["question_id"] == question_id + assert "chunks" in questions_list[0] + assert len(questions_list[0]["chunks"]) == 2 +