From 0160771e5961b85e935075cf39603976c7d57cee Mon Sep 17 00:00:00 2001
From: cacohe <2568545091@qq.com>
Date: Wed, 12 Aug 2026 19:06:53 +0800
Subject: [PATCH] feat: replace custom RAG pipeline with LlamaIndex

Use SimpleDirectoryReader and SentenceSplitter for loading/chunking,
and BM25 retrieval so indexing stays in-memory without a vector store.

Co-authored-by: Cursor <cursoragent@cursor.com>
---
 README.md                                     |   2 +-
 pyproject.toml                                |   2 +
 src/backend/infra/rag/loader.py               |  89 +--
 src/backend/infra/rag/retriever.py            |  68 +--
 src/backend/infra/rag/store.py                |   8 +-
 src/frontend/components/sidebar/sidebar.py    |  12 +-
 .../test_app/test_knowledge_service.py        |   4 +-
 .../test_infra/test_rag/test_rag.py           |   1 +
 uv.lock                                       | 508 ++++++++++++++++++
 9 files changed, 608 insertions(+), 86 deletions(-)

diff --git a/README.md b/README.md
index f2efe67..400fdac 100644
--- a/README.md
+++ b/README.md
@@ -7,7 +7,7 @@
 - **后端**: FastAPI
 - **前端**: Streamlit
 - **LLM**: LiteLLM 调用通义千问（`DEFAULT_LLM` 需为已登记模型）
-- **检索**: 进程内分块 + 关键字重叠检索（无向量库）
+- **检索**: LlamaIndex 句子分块 + BM25 检索（无向量库）
 
 ## 工作方式
 
diff --git a/pyproject.toml b/pyproject.toml
index 9905281..961fbed 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,6 +14,8 @@ dependencies = [
     "uvicorn~=0.24.0",
     "streamlit~=1.52.1",
     "requests~=2.32.5",
+    "llama-index-core>=0.14.23",
+    "llama-index-retrievers-bm25>=0.7.1",
 ]
 
 [dependency-groups]
diff --git a/src/backend/infra/rag/loader.py b/src/backend/infra/rag/loader.py
index 8f7a327..108d3f3 100644
--- a/src/backend/infra/rag/loader.py
+++ b/src/backend/infra/rag/loader.py
@@ -1,6 +1,8 @@
-import uuid
 from pathlib import Path
 
+from llama_index.core import Document, Settings, SimpleDirectoryReader
+from llama_index.core.node_parser import SentenceSplitter
+
 from src.backend.infra.rag.store import (
     DocumentChunk,
     KnowledgeStore,
@@ -12,23 +14,22 @@
 
 SUPPORTED_SUFFIXES = {".txt", ".md", ".markdown"}
 
+Settings.llm = None
+Settings.embed_model = None
+
+
+def _splitter(chunk_size: int, overlap: int) -> SentenceSplitter:
+    return SentenceSplitter(chunk_size=chunk_size, chunk_overlap=overlap)
+
 
 def chunk_text(text: str, chunk_size: int, overlap: int) -> list[str]:
     text = text.strip()
     if not text:
         return []
-    if len(text) <= chunk_size:
-        return [text]
-
-    chunks: list[str] = []
-    start = 0
-    while start < len(text):
-        end = start + chunk_size
-        chunks.append(text[start:end])
-        if end >= len(text):
-            break
-        start = max(end - overlap, start + 1)
-    return chunks
+    nodes = _splitter(chunk_size, overlap).get_nodes_from_documents(
+        [Document(text=text)]
+    )
+    return [node.get_content() for node in nodes]
 
 
 def validate_chunk_params(chunk_size: int, overlap: int) -> None:
@@ -58,21 +59,25 @@ def ingest_text(
     overlap: int,
 ) -> int:
     store.remove_document(doc_name)
-    parts = chunk_text(content, chunk_size, overlap)
-    doc_id = str(uuid.uuid4())
-    for idx, part in enumerate(parts):
+    nodes = _splitter(chunk_size, overlap).get_nodes_from_documents(
+        [Document(text=content.strip())]
+    )
+    for idx, node in enumerate(nodes):
+        node.metadata["doc_name"] = doc_name
+        node.metadata["chunk_index"] = idx
+        store.nodes.append(node)
         store.chunks.append(
             DocumentChunk(
-                doc_id=doc_id,
+                doc_id=node.node_id,
                 doc_name=doc_name,
-                content=part,
+                content=node.get_content(),
                 chunk_index=idx,
             )
         )
     store.document_names.append(doc_name)
     store.document_count += 1
-    logger.info(f"Ingested RAG doc: {doc_name} ({len(parts)} chunks)")
-    return len(parts)
+    logger.info(f"Ingested RAG doc: {doc_name} ({len(nodes)} chunks)")
+    return len(nodes)
 
 
 def load_docs(
@@ -81,7 +86,7 @@ def load_docs(
     chunk_size: int | None = None,
     overlap: int | None = None,
 ) -> KnowledgeStore:
-    """从目录加载全部文档到内存知识库。"""
+    """用 LlamaIndex 从目录加载文档并分块。"""
     size, ov = _resolve_chunk_params(chunk_size, overlap)
     path = Path(docs_path or settings.rag_settings.docs_path).expanduser().resolve()
     store = KnowledgeStore(
@@ -100,24 +105,34 @@ def load_docs(
         logger.warning(f"RAG docs path is not a directory: {path}")
         return store
 
-    files = sorted(
-        p
-        for p in path.rglob("*")
-        if p.is_file() and p.suffix.lower() in SUPPORTED_SUFFIXES
-    )
+    try:
+        documents = SimpleDirectoryReader(
+            input_dir=str(path),
+            required_exts=sorted(SUPPORTED_SUFFIXES),
+            recursive=True,
+            filename_as_id=True,
+        ).load_data()
+    except ValueError:
+        logger.warning(f"No supported documents found in: {path}")
+        return store
 
-    for file_path in files:
+    for document in documents:
+        file_path = Path(
+            document.metadata.get("file_path")
+            or document.metadata.get("file_name")
+            or ""
+        )
         try:
-            content = file_path.read_text(encoding="utf-8")
-        except UnicodeDecodeError:
-            content = file_path.read_text(encoding="utf-8", errors="ignore")
-            logger.warning(f"Decoded with errors ignored: {file_path}")
-        except Exception as e:
-            logger.exception(f"Failed to read {file_path}: {e}")
-            continue
-
-        doc_name = str(file_path.relative_to(path))
-        ingest_text(store, doc_name, content, chunk_size=size, overlap=ov)
+            doc_name = str(file_path.relative_to(path))
+        except ValueError:
+            doc_name = file_path.name or "document"
+        ingest_text(
+            store,
+            doc_name,
+            document.get_content(),
+            chunk_size=size,
+            overlap=ov,
+        )
 
     logger.info(
         f"RAG knowledge loaded: {store.document_count} docs, "
diff --git a/src/backend/infra/rag/retriever.py b/src/backend/infra/rag/retriever.py
index eb9bcc4..69579e1 100644
--- a/src/backend/infra/rag/retriever.py
+++ b/src/backend/infra/rag/retriever.py
@@ -1,53 +1,43 @@
-import re
+from llama_index.retrievers.bm25 import BM25Retriever
 
 from src.backend.infra.rag.store import DocumentChunk, get_knowledge_store
 from src.shared.config import settings
+from src.shared.logger import logger
 
-
-def _tokenize(text: str) -> set[str]:
-    # 中英文简单切词：连续中文/字母数字为一 token
-    tokens = re.findall(r"[\u4e00-\u9fff]+|[a-zA-Z0-9]+", text.lower())
-    result: set[str] = set()
-    for token in tokens:
-        if re.fullmatch(r"[\u4e00-\u9fff]+", token) and len(token) > 1:
-            # 中文再拆成字与 bigram，提高短查询命中率
-            result.update(token)
-            result.update(token[i : i + 2] for i in range(len(token) - 1))
-        else:
-            result.add(token)
-    return {t for t in result if t}
-
-
-def _score(query_tokens: set[str], chunk: DocumentChunk) -> float:
-    """
-    计算查询词与文档内容的相似度
-    """
-    if not query_tokens:
-        return 0.0
-    chunk_tokens = _tokenize(chunk.content)
-    if not chunk_tokens:
-        return 0.0
-    overlap = query_tokens & chunk_tokens
-    if not overlap:
-        # 退化为子串匹配
-        q = "".join(sorted(query_tokens, key=len, reverse=True)[:3])
-        if q and q in chunk.content.lower():
-            return 0.1
-        return 0.0
-    return len(overlap) / len(query_tokens)
+_BM25_TOKEN_PATTERN = r"(?u)[\u4e00-\u9fff]|[a-zA-Z0-9]+"
 
 
 def retrieve(query: str, top_k: int | None = None) -> list[DocumentChunk]:
     store = get_knowledge_store()
-    if not store.chunks:
+    if not store.nodes:
         return []
 
     k = top_k if top_k is not None else settings.rag_settings.top_k
-    query_tokens = _tokenize(query)
-    scored = [(_score(query_tokens, chunk), chunk) for chunk in store.chunks]
-    scored = [(s, c) for s, c in scored if s > 0]
-    scored.sort(key=lambda x: x[0], reverse=True)
-    return [c for _, c in scored[:k]]
+    try:
+        retriever = BM25Retriever.from_defaults(
+            nodes=store.nodes,
+            similarity_top_k=k,
+            skip_stemming=True,
+            language="zh",
+            token_pattern=_BM25_TOKEN_PATTERN,
+        )
+        results = retriever.retrieve(query)
+    except Exception:
+        logger.exception("LlamaIndex BM25 retrieve failed")
+        return []
+
+    chunks: list[DocumentChunk] = []
+    for result in results:
+        node = result.node
+        chunks.append(
+            DocumentChunk(
+                doc_id=node.node_id,
+                doc_name=str(node.metadata.get("doc_name") or ""),
+                content=node.get_content(),
+                chunk_index=int(node.metadata.get("chunk_index") or 0),
+            )
+        )
+    return chunks
 
 
 def format_context(chunks: list[DocumentChunk]) -> str:
diff --git a/src/backend/infra/rag/store.py b/src/backend/infra/rag/store.py
index 0c13c2e..8dccc19 100644
--- a/src/backend/infra/rag/store.py
+++ b/src/backend/infra/rag/store.py
@@ -1,4 +1,5 @@
 from dataclasses import dataclass, field
+from typing import Any
 
 
 @dataclass
@@ -11,7 +12,7 @@ class DocumentChunk:
 
 @dataclass
 class KnowledgeStore:
-    """进程内知识库"""
+    """进程内知识库（LlamaIndex nodes + 预览分块）"""
 
     docs_path: str = ""
     chunk_size: int = 500
@@ -19,17 +20,22 @@ class KnowledgeStore:
     document_count: int = 0
     document_names: list[str] = field(default_factory=list)
     chunks: list[DocumentChunk] = field(default_factory=list)
+    nodes: list[Any] = field(default_factory=list)
 
     def clear(self) -> None:
         self.document_count = 0
         self.document_names = []
         self.chunks = []
+        self.nodes = []
 
     def remove_document(self, doc_name: str) -> None:
         if doc_name in self.document_names:
             self.document_names.remove(doc_name)
             self.document_count = max(0, self.document_count - 1)
         self.chunks = [chunk for chunk in self.chunks if chunk.doc_name != doc_name]
+        self.nodes = [
+            node for node in self.nodes if node.metadata.get("doc_name") != doc_name
+        ]
 
 
 _store: KnowledgeStore | None = None
diff --git a/src/frontend/components/sidebar/sidebar.py b/src/frontend/components/sidebar/sidebar.py
index 9dca987..a0be0b3 100644
--- a/src/frontend/components/sidebar/sidebar.py
+++ b/src/frontend/components/sidebar/sidebar.py
@@ -28,28 +28,28 @@ def _render_knowledge_panel():
             f"{status['document_count']} 个文档 · {status['chunk_count']} 个分块"
         )
         chunk_size = st.number_input(
-            "分块大小（字符）",
+            "分块大小",
             min_value=50,
             max_value=10000,
             value=int(status.get("chunk_size", 500)),
             step=50,
-            help="每个分块最多包含多少字符",
+            help="每个分块的目标长度（按句子切分）",
         )
         chunk_overlap = st.number_input(
-            "重叠长度（字符）",
+            "重叠长度",
             min_value=0,
             max_value=5000,
             value=int(status.get("chunk_overlap", 50)),
             step=10,
-            help="相邻两个分块之间重复多少字符，需小于分块大小",
+            help="相邻两个分块之间重复的内容长度，需小于分块大小",
         )
     else:
         st.warning("无法连接后端知识库服务")
         chunk_size = st.number_input(
-            "分块大小（字符）", min_value=50, max_value=10000, value=500
+            "分块大小", min_value=50, max_value=10000, value=500
         )
         chunk_overlap = st.number_input(
-            "重叠长度（字符）", min_value=0, max_value=5000, value=50
+            "重叠长度", min_value=0, max_value=5000, value=50
         )
 
     uploaded_files = st.file_uploader(
diff --git a/tests/unittest/test_backend/test_app/test_knowledge_service.py b/tests/unittest/test_backend/test_app/test_knowledge_service.py
index ea4c0d4..a1a714c 100644
--- a/tests/unittest/test_backend/test_app/test_knowledge_service.py
+++ b/tests/unittest/test_backend/test_app/test_knowledge_service.py
@@ -29,10 +29,10 @@ def reset_store():
 
 class TestChunkHelpers:
     def test_chunk_text_with_overlap(self):
-        text = "a" * 100
+        text = "年假政策说明。" * 30
         chunks = chunk_text(text, chunk_size=40, overlap=10)
         assert len(chunks) >= 2
-        assert all(len(chunk) <= 40 for chunk in chunks)
+        assert all(chunk.strip() for chunk in chunks)
 
     def test_validate_chunk_params_rejects_large_overlap(self):
         with pytest.raises(ValueError, match="chunk_overlap"):
diff --git a/tests/unittest/test_backend/test_infra/test_rag/test_rag.py b/tests/unittest/test_backend/test_infra/test_rag/test_rag.py
index 6762703..64799dd 100644
--- a/tests/unittest/test_backend/test_infra/test_rag/test_rag.py
+++ b/tests/unittest/test_backend/test_infra/test_rag/test_rag.py
@@ -15,6 +15,7 @@ def test_load_docs_from_sample_dir():
     store = load_docs(str(docs_path))
     assert store.document_count >= 1
     assert len(store.chunks) >= 1
+    assert len(store.nodes) >= 1
 
 
 def test_retrieve_leave_policy():
diff --git a/uv.lock b/uv.lock
index c1e6c6d..7302ab4 100644
--- a/uv.lock
+++ b/uv.lock
@@ -124,6 +124,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490, upload-time = "2025-07-03T22:54:42.156Z" },
 ]
 
+[[package]]
+name = "aiosqlite"
+version = "0.22.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/4e/8a/64761f4005f17809769d23e518d915db74e6310474e733e3593cfc854ef1/aiosqlite-0.22.1.tar.gz", hash = "sha256:043e0bd78d32888c0a9ca90fc788b38796843360c855a7262a532813133a0650", size = 14821, upload-time = "2025-12-23T19:25:43.997Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/00/b7/e3bf5133d697a08128598c8d0abc5e16377b51465a33756de24fa7dee953/aiosqlite-0.22.1-py3-none-any.whl", hash = "sha256:21c002eb13823fad740196c5a2e9d8e62f6243bd9e7e4a1f87fb5e44ecb4fceb", size = 17405, upload-time = "2025-12-23T19:25:42.139Z" },
+]
+
 [[package]]
 name = "altair"
 version = "6.0.0"
@@ -180,6 +189,23 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373", size = 67615, upload-time = "2025-10-06T13:54:43.17Z" },
 ]
 
+[[package]]
+name = "banks"
+version = "2.5.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "deprecated" },
+    { name = "filetype" },
+    { name = "griffe" },
+    { name = "jinja2" },
+    { name = "platformdirs" },
+    { name = "pydantic" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/6d/f0/ce5b3105a8551fdcedb509ab5340066247b3cd1b28e79f9296be2d6d3bf4/banks-2.5.0.tar.gz", hash = "sha256:fdd4fd54b84dbe31cb51a1173c960697c73d683a52fb0b1d1957a557a8d6fcc8", size = 194585, upload-time = "2026-08-08T15:54:16.548Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/07/9c/7dc7b15cecc03baa47d413b2599487b1fab270169b00feaa5e74978845f3/banks-2.5.0-py3-none-any.whl", hash = "sha256:8804c58f23e41a5aabe9ecfdf64235cdf1d5f3b16ad95ec2a54b6dc738dc1dfc", size = 38620, upload-time = "2026-08-08T15:54:15.505Z" },
+]
+
 [[package]]
 name = "blinker"
 version = "1.9.0"
@@ -189,6 +215,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458, upload-time = "2024-11-08T17:25:46.184Z" },
 ]
 
+[[package]]
+name = "bm25s"
+version = "0.3.10"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/34/ab/8fac50e2095d26dd9ccaf3c35bddb96ff45a8cca9fc3ac0e98209971828f/bm25s-0.3.10.tar.gz", hash = "sha256:fafdfc45e6c064fc117b08de8f59b47564a3879d3ca593daa0b2a40b2c05da43", size = 80762, upload-time = "2026-07-22T20:54:28.824Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d4/06/7ec2175c185661a976589fffde16eb7c36d69eaa43eed26fe5ad0ce3cd25/bm25s-0.3.10-py3-none-any.whl", hash = "sha256:d271d4e1ad7ffdacb224f41bc54aba55159438ecf06439ffe929f088efa96858", size = 74687, upload-time = "2026-07-22T20:54:27.447Z" },
+]
+
 [[package]]
 name = "cachetools"
 version = "6.2.6"
@@ -271,6 +309,8 @@ source = { virtual = "." }
 dependencies = [
     { name = "fastapi" },
     { name = "litellm" },
+    { name = "llama-index-core" },
+    { name = "llama-index-retrievers-bm25" },
     { name = "pydantic" },
     { name = "pydantic-settings" },
     { name = "python-dotenv" },
@@ -292,6 +332,8 @@ dev = [
 requires-dist = [
     { name = "fastapi", specifier = "~=0.121.2" },
     { name = "litellm", specifier = ">=1.60.0" },
+    { name = "llama-index-core", specifier = ">=0.14.23" },
+    { name = "llama-index-retrievers-bm25", specifier = ">=0.7.1" },
     { name = "pydantic", specifier = "~=2.12.4" },
     { name = "pydantic-settings", specifier = "~=2.13.1" },
     { name = "python-dotenv", specifier = "~=1.0.0" },
@@ -330,6 +372,49 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" },
 ]
 
+[[package]]
+name = "dataclasses-json"
+version = "0.6.7"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "marshmallow" },
+    { name = "typing-inspect" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/64/a4/f71d9cf3a5ac257c993b5ca3f93df5f7fb395c725e7f1e6479d2514173c3/dataclasses_json-0.6.7.tar.gz", hash = "sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0", size = 32227, upload-time = "2024-06-09T16:20:19.103Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c3/be/d0d44e092656fe7a06b55e6103cbce807cdbdee17884a5367c68c9860853/dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a", size = 28686, upload-time = "2024-06-09T16:20:16.715Z" },
+]
+
+[[package]]
+name = "defusedxml"
+version = "0.7.1"
+source = { registry = "https://pypi.org/simple" }
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