diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..3212c7f --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,137 @@ +name: CI + +on: + push: + branches: [main] + tags: + - 'v*' + pull_request: + branches: [main] + release: + types: [published] + +jobs: + lint: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + - name: Install uv + run: | + curl -LsSf https://astral.sh/uv/install.sh | sh + echo "$HOME/.cargo/bin" >> $GITHUB_PATH + - name: Install dependencies + run: uv sync --dev + - name: Ruff + run: uv run ruff check . + - name: Black + run: uv run black --check . + - name: mypy + run: uv run mypy intent_kit tests + + test: + runs-on: ubuntu-latest + needs: lint + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + - name: Install uv + run: | + curl -LsSf https://astral.sh/uv/install.sh | sh + echo "$HOME/.cargo/bin" >> $GITHUB_PATH + - name: Install dependencies + run: uv sync --dev + - name: Tests with coverage + run: | + uv run pytest --cov=intent_kit --cov-report=xml + - name: Upload coverage to Codecov + uses: codecov/codecov-action@v4 + with: + files: ./coverage.xml + token: ${{ secrets.CODECOV_TOKEN }} + + eval: + runs-on: ubuntu-latest + needs: lint + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + - name: Install uv + run: | + curl -LsSf https://astral.sh/uv/install.sh | sh + echo "$HOME/.cargo/bin" >> $GITHUB_PATH + - name: Install dependencies + run: uv sync --dev + - name: Evaluations (Mock Mode) + run: uv run python -m intent_kit.evals.run_all_evals --quiet --mock + + build: + runs-on: ubuntu-latest + needs: [test, eval] + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + - name: Install build dependencies + run: | + pip install build + - name: Build package + run: python -m build --sdist --wheel --outdir dist + - name: Upload build artifacts + uses: actions/upload-artifact@v4 + with: + name: python-distributions + path: dist + + docs: + runs-on: ubuntu-latest + needs: [test, eval] + if: startsWith(github.ref, 'refs/tags/') + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + - name: Install uv + run: | + curl -LsSf https://astral.sh/uv/install.sh | sh + echo "$HOME/.cargo/bin" >> $GITHUB_PATH + - name: Install dependencies + run: uv sync --dev + - name: Build documentation + run: uv run mkdocs build + - name: Deploy to Cloudflare Pages + uses: cloudflare/pages-action@v1 + with: + apiToken: ${{ secrets.CLOUDFLARE_API_TOKEN }} + accountId: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }} + projectName: intentkit-docs + directory: site + gitHubToken: ${{ secrets.GITHUB_TOKEN }} + + publish: + runs-on: ubuntu-latest + needs: build + if: startsWith(github.ref, 'refs/tags/') + permissions: + contents: write + id-token: write + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + - name: Install build and publish dependencies + run: | + pip install build twine + - name: Build package + run: python -m build --sdist --wheel --outdir dist + - name: Publish package to PyPI + uses: pypa/gh-action-pypi-publish@release/v1 \ No newline at end of file diff --git a/.github/workflows/test-and-eval.yml b/.github/workflows/test-and-eval.yml deleted file mode 100644 index ee80e03..0000000 --- a/.github/workflows/test-and-eval.yml +++ /dev/null @@ -1,31 +0,0 @@ -name: Tests and Evaluations - -on: - push: - branches: [ main ] - pull_request: - branches: [ main ] - -jobs: - test-and-eval: - runs-on: ubuntu-latest - env: - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} - GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} - steps: - - uses: actions/checkout@v3 - - uses: actions/setup-python@v4 - with: - python-version: '3.11' - - name: Install uv - run: | - curl -LsSf https://astral.sh/uv/install.sh | sh - echo "$HOME/.cargo/bin" >> $GITHUB_PATH - - name: Install dependencies - run: | - uv sync --dev - - name: Tests - run: uv run pytest -q - - name: Evaluations (Mock Mode) - run: uv run python -m intent_kit.evals.run_all_evals --quiet --mock \ No newline at end of file diff --git a/.gitignore b/.gitignore index ac509ed..1e7d110 100644 --- a/.gitignore +++ b/.gitignore @@ -38,6 +38,9 @@ htmlcov/ .tox/ reports/ +# Documentation +site/ + # Evaluation Results intent_kit/evals/results/ intent_kit/evals/reports/ diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..30f83c6 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,19 @@ +repos: + - repo: https://github.com/astral-sh/ruff-pre-commit + rev: v0.4.7 + hooks: + - id: ruff + args: [--fix] + - repo: https://github.com/psf/black + rev: 24.4.2 + hooks: + - id: black + - repo: https://github.com/pre-commit/mirrors-mypy + rev: v1.10.0 + hooks: + - id: mypy + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.5.0 + hooks: + - id: end-of-file-fixer + - id: trailing-whitespace \ No newline at end of file diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..1246a1f --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,18 @@ +# Changelog + +All notable changes to this project will be documented in this file. + +## [0.1.0] - 2025-07-07 + +### Added +- Experimental CI/CD pipeline with linting, type checking, test coverage reporting via Codecov, and trusted publishing. +- MkDocs documentation site using the Material theme with live search and API reference. +- Binder environment for interactive notebooks and examples. +- Pre-commit configuration powered by Ruff, Black, and mypy. +- Documentation badges for CI, coverage, docs, and PyPI. + +### Changed +- Updated development dependencies and tooling for modern Python 3.11 ecosystem. + +### Removed +- N/A \ No newline at end of file diff --git a/README.md b/README.md index a8841c9..88e16a5 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,13 @@ # intent-kit + + +[![CI](https://github.com/Stephen-Collins-tech/intent-kit/actions/workflows/ci.yml/badge.svg)](https://github.com/Stephen-Collins-tech/intent-kit/actions/workflows/ci.yml) +[![Coverage Status](https://codecov.io/gh/Stephen-Collins-tech/intent-kit/branch/main/graph/badge.svg)](https://codecov.io/gh/Stephen-Collins-tech/intent-kit) +[![Documentation](https://img.shields.io/badge/docs-online-blue)](https://docs.intentkit.io) +[![PyPI](https://img.shields.io/pypi/v/intent-kit)](https://pypi.org/project/intent-kit) +[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Stephen-Collins-tech/intent-kit/HEAD?filepath=examples%2Fsimple_demo.ipynb) + A Python library for building hierarchical intent classification and execution systems with support for multiple AI service backends. ## Features diff --git a/binder/requirements.txt b/binder/requirements.txt new file mode 100644 index 0000000..73072ec --- /dev/null +++ b/binder/requirements.txt @@ -0,0 +1,3 @@ +-e . +jupyterlab +ipykernel \ No newline at end of file diff --git a/docs/api_reference.md b/docs/api_reference.md new file mode 100644 index 0000000..e680210 --- /dev/null +++ b/docs/api_reference.md @@ -0,0 +1,3 @@ +# API Reference + +::: intent_kit \ No newline at end of file diff --git a/docs/examples/calculator-bot.md b/docs/examples/calculator-bot.md new file mode 100644 index 0000000..a90a220 --- /dev/null +++ b/docs/examples/calculator-bot.md @@ -0,0 +1,36 @@ +# Calculator Bot Example + +This example shows how to build a simple calculator bot that can add and subtract numbers using intent-kit. + +```python +from intent_kit import IntentGraphBuilder, handler + +def add(a: int, b: int) -> str: + return str(a + b) + +def subtract(a: int, b: int) -> str: + return str(a - b) + +add_handler = handler( + name="add", + description="Add two numbers", + handler_func=add, + param_schema={"a": int, "b": int}, +) + +subtract_handler = handler( + name="subtract", + description="Subtract two numbers", + handler_func=subtract, + param_schema={"a": int, "b": int}, +) + +graph = ( + IntentGraphBuilder() + .root(add_handler) + .root(subtract_handler) + .build() +) + +print(graph.route("add 2 3").output) # -> 5 +``` \ No newline at end of file diff --git a/docs/examples/context-aware-chatbot.md b/docs/examples/context-aware-chatbot.md new file mode 100644 index 0000000..bc6c9e9 --- /dev/null +++ b/docs/examples/context-aware-chatbot.md @@ -0,0 +1,39 @@ +# Context-Aware Chatbot Example + +This example is adapted from `examples/context_demo.py`. It demonstrates how `IntentContext` can persist conversation state across multiple turns. + +```python +from intent_kit import IntentGraphBuilder, handler +from intent_kit.context import IntentContext + +# Handler remembers how many times we greeted the user + +def greet(name: str, context: IntentContext) -> str: + count = context.get("greet_count", 0) + 1 + context.set("greet_count", count, modified_by="greet") + return f"Hello {name}! (greeting #{count})" + +hello_handler = handler( + name="greet", + description="Greet the user and track greeting count", + handler_func=greet, + param_schema={"name": str}, +) + +graph = IntentGraphBuilder().root(hello_handler).build() + +ctx = IntentContext(session_id="abc123") +print(graph.route("hello alice", context=ctx).output) +print(graph.route("hello bob", context=ctx).output) # Greeting count increments +``` + +Running the above prints: + +``` +Hello alice! (greeting #1) +Hello bob! (greeting #2) +``` + +Key take-aways: +* `IntentContext` persists between calls so you can build multi-turn experiences. +* Each handler can declare which context keys it reads/writes for explicit dependency tracking. \ No newline at end of file diff --git a/docs/examples/multi-intent-routing.md b/docs/examples/multi-intent-routing.md new file mode 100644 index 0000000..7f04226 --- /dev/null +++ b/docs/examples/multi-intent-routing.md @@ -0,0 +1,51 @@ +# Multi-Intent Routing Example + +The following shows how intent-kit can handle _multiple_ intents in a single user utterance using a splitter node. + +```python +from intent_kit import IntentGraphBuilder, handler, rule_splitter_node + +# Handlers for individual intents + +def greet(name: str) -> str: + return f"Hello {name}!" + +def weather(city: str) -> str: + return f"The weather in {city} is sunny." + +hello = handler( + name="greet", + description="Greet the user", + handler_func=greet, + param_schema={"name": str}, +) + +weather_h = handler( + name="weather", + description="Get weather information", + handler_func=weather, + param_schema={"city": str}, +) + +# Splitter routes parts of the sentence to different handlers +splitter = rule_splitter_node( + name="multi_split", + children=[hello, weather_h], +) + +graph = IntentGraphBuilder().root(splitter).build() + +result = graph.route("Hello Alice and what's the weather in Paris?") +print(result.output) +``` + +The `rule_splitter_node` looks for keywords ("hello", "weather", etc.) and breaks the user input into sub-phrases routed to the appropriate handlers. The final `result.output` aggregates the outputs from each intent, e.g.: + +``` +{ + "greet": "Hello Alice!", + "weather": "The weather in Paris is sunny." +} +``` + +For a more robust version that uses LLM-based splitting, see `examples/multi_intent_demo.py`. \ No newline at end of file diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 0000000..46b25fd --- /dev/null +++ b/docs/index.md @@ -0,0 +1,5 @@ +# Welcome to intent-kit + +intent-kit is a universal Python framework for building hierarchical intent graphs with deterministic, fully-auditable execution models. + +Explore the Quickstart to get running in minutes, or dive into the full API reference. \ No newline at end of file diff --git a/docs/quickstart.md b/docs/quickstart.md new file mode 100644 index 0000000..03640a4 --- /dev/null +++ b/docs/quickstart.md @@ -0,0 +1,25 @@ +# Quickstart + +Install intent-kit: + +```bash +pip install intent-kit # Or 'intent-kit[openai]' for LLM support +``` + +Create and run a simple graph: + +```python +from intent_kit import IntentGraphBuilder, handler + +hello_handler = handler( + name="greet", + description="Greet the user", + handler_func=lambda name: f"Hello {name}!", + param_schema={"name": str}, +) + +graph = IntentGraphBuilder().root(hello_handler).build() +print(graph.route("hello alice").output) +``` + +For more in-depth examples, see the Examples section. \ No newline at end of file diff --git a/examples/advanced_remediation_demo.py b/examples/advanced_remediation_demo.py index 408fd32..2d51ee7 100644 --- a/examples/advanced_remediation_demo.py +++ b/examples/advanced_remediation_demo.py @@ -30,10 +30,16 @@ OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") or "sk-mock-openai" GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") or "sk-mock-gemini" -LLM_CONFIG_1 = {"provider": "openai", - "model": "gpt-4.1-mini", "api_key": OPENAI_API_KEY} -LLM_CONFIG_2 = {"provider": "google", - "model": "gemini-2.5-flash", "api_key": GOOGLE_API_KEY} +LLM_CONFIG_1 = { + "provider": "openai", + "model": "gpt-4.1-mini", + "api_key": OPENAI_API_KEY, +} +LLM_CONFIG_2 = { + "provider": "google", + "model": "gemini-2.5-flash", + "api_key": GOOGLE_API_KEY, +} # --- Core Handler: Simulates model confusion and ambiguity --- @@ -68,24 +74,27 @@ def analyze_sentiment(review_text: str, context: IntentContext) -> str: description="Uses self-reflection if it fails on ambiguous reviews.", handler_func=analyze_sentiment, param_schema={"review_text": str}, - remediation_strategies=[create_self_reflect_strategy( - LLM_CONFIG_1, max_reflections=1)], + remediation_strategies=[ + create_self_reflect_strategy(LLM_CONFIG_1, max_reflections=1) + ], ), handler( name="consensus_vote_sentiment", description="Uses consensus voting between two LLMs on conflicting reviews.", handler_func=analyze_sentiment, param_schema={"review_text": str}, - remediation_strategies=[create_consensus_vote_strategy( - [LLM_CONFIG_1, LLM_CONFIG_2], vote_threshold=0.5)], + remediation_strategies=[ + create_consensus_vote_strategy( + [LLM_CONFIG_1, LLM_CONFIG_2], vote_threshold=0.5 + ) + ], ), handler( name="alternate_prompt_sentiment", description="Retries with alternate prompt if ambiguous input causes a failure.", handler_func=analyze_sentiment, param_schema={"review_text": str}, - remediation_strategies=[ - create_alternate_prompt_strategy(LLM_CONFIG_1)], + remediation_strategies=[create_alternate_prompt_strategy(LLM_CONFIG_1)], ), ] @@ -94,22 +103,24 @@ def main(): context = IntentContext() print("=== Advanced Remediation Strategies Demo ===\n") - print("This demo shows how self-reflection, consensus voting, and alternate prompts can recover\n" - "from ambiguous or conflicting results in real-world sentiment analysis tasks.\n") + print( + "This demo shows how self-reflection, consensus voting, and alternate prompts can recover\n" + "from ambiguous or conflicting results in real-world sentiment analysis tasks.\n" + ) # Each case is designed to *require* remediation. test_cases = [ ( "This product is not bad at all, actually quite good!", - "Triggers self-reflection: Model may misinterpret 'not bad'." + "Triggers self-reflection: Model may misinterpret 'not bad'.", ), ( "I hate the design but love the features, not my favorite but not bad.", - "Triggers consensus voting: LLMs likely to disagree on mixed sentiment." + "Triggers consensus voting: LLMs likely to disagree on mixed sentiment.", ), ( "Okay, fine, whatever, not bad I guess, meh", - "Triggers alternate prompt: All terms are vague, likely to fail first try." + "Triggers alternate prompt: All terms are vague, likely to fail first try.", ), ] @@ -120,8 +131,7 @@ def main(): print(f"Case: {case_desc}") try: - result: ExecutionResult = h.execute( - user_input=review_text, context=context) + result: ExecutionResult = h.execute(user_input=review_text, context=context) print(f"Success: {result.success}") print(f"Output: {result.output}") if result.error: @@ -135,7 +145,9 @@ def main(): print("ā€¢ Alternate prompt: Handler retries with a new prompt if it can't answer.") if "mock" in OPENAI_API_KEY or "mock" in GOOGLE_API_KEY: - print("\nšŸ’” Pro Tip: For real LLM behavior, add your OpenAI and Gemini API keys to a .env file.") + print( + "\nšŸ’” Pro Tip: For real LLM behavior, add your OpenAI and Gemini API keys to a .env file." + ) if __name__ == "__main__": diff --git a/examples/classifier_remediation_demo.py b/examples/classifier_remediation_demo.py index a89ae50..162a21d 100644 --- a/examples/classifier_remediation_demo.py +++ b/examples/classifier_remediation_demo.py @@ -15,15 +15,15 @@ from intent_kit.node.types import ExecutionResult, ExecutionError from intent_kit.handlers.remediation import ( RemediationStrategy, - create_keyword_fallback_strategy, - register_remediation_strategy + register_remediation_strategy, ) from intent_kit.context import IntentContext -from intent_kit.builder import handler, llm_classifier, IntentGraphBuilder +from intent_kit.builder import handler, IntentGraphBuilder import sys import os from typing import Optional, Callable, List from dotenv import load_dotenv + sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) # Load environment variables @@ -37,7 +37,7 @@ LLM_CONFIG = { "provider": "openai", "model": "gpt-4.1-mini", - "api_key": os.getenv("OPENAI_API_KEY") + "api_key": os.getenv("OPENAI_API_KEY"), } @@ -48,7 +48,9 @@ def greet_handler(name: str, context: IntentContext) -> str: return f"Hello {name}! (Greeting #{greeting_count})" -def calculate_handler(operation: str, a: float, b: float, context: IntentContext) -> str: +def calculate_handler( + operation: str, a: float, b: float, context: IntentContext +) -> str: """Simple calculation handler.""" ops = {"add": "+", "plus": "+", "multiply": "*", "times": "*"} op = ops.get(operation.lower(), operation) @@ -78,10 +80,11 @@ def help_handler(context: IntentContext) -> str: def create_failing_classifier(): """Create a classifier that deliberately fails to trigger remediation.""" - def failing_classifier(user_input: str, children: List, context: Optional[dict] = None): + def failing_classifier( + user_input: str, children: List, context: Optional[dict] = None + ): """A classifier that always fails to demonstrate remediation.""" - logger.warning( - "FailingClassifier: Deliberately failing to trigger remediation") + logger.warning("FailingClassifier: Deliberately failing to trigger remediation") return None # Always return None to trigger remediation return failing_classifier @@ -99,15 +102,17 @@ def execute( original_error: Optional[ExecutionError] = None, classifier_func: Optional[Callable] = None, available_children: Optional[List] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Use a simple rule-based classifier as fallback.""" self.logger.info( - f"CustomClassifierFallbackStrategy: Using rule-based classification for {node_name}") + f"CustomClassifierFallbackStrategy: Using rule-based classification for {node_name}" + ) if not available_children: self.logger.warning( - f"CustomClassifierFallbackStrategy: No available children for {node_name}") + f"CustomClassifierFallbackStrategy: No available children for {node_name}" + ) return None # Simple rule-based classification @@ -116,10 +121,20 @@ def execute( # Define simple rules rules = [ (["hello", "hi", "hey", "greet"], "greet"), - (["calculate", "compute", "math", "add", - "multiply", "plus", "times"], "calculate"), + ( + [ + "calculate", + "compute", + "math", + "add", + "multiply", + "plus", + "times", + ], + "calculate", + ), (["weather", "temperature", "forecast"], "weather"), - (["help", "assist", "support"], "help") + (["help", "assist", "support"], "help"), ] # Find matching rule @@ -130,13 +145,14 @@ def execute( for child in available_children: if child.name.lower() == intent_name: self.logger.info( - f"CustomClassifierFallbackStrategy: Matched '{child.name}' using keyword '{keyword}'") + f"CustomClassifierFallbackStrategy: Matched '{child.name}' using keyword '{keyword}'" + ) # Execute the chosen child - child_result = child.execute( - user_input, context) + child_result = child.execute(user_input, context) from intent_kit.node.enums import NodeType + return ExecutionResult( success=True, node_name=node_name, @@ -147,18 +163,23 @@ def execute( error=None, params={ "chosen_child": child.name, - "available_children": [c.name for c in available_children], + "available_children": [ + c.name for c in available_children + ], "remediation_strategy": self.name, - "matched_keyword": keyword + "matched_keyword": keyword, }, - children_results=[child_result] + children_results=[child_result], ) self.logger.warning( - f"CustomClassifierFallbackStrategy: No rule match found for {node_name}") + f"CustomClassifierFallbackStrategy: No rule match found for {node_name}" + ) return None - return CustomClassifierFallbackStrategy("custom_classifier_fallback", "Custom rule-based classifier fallback") + return CustomClassifierFallbackStrategy( + "custom_classifier_fallback", "Custom rule-based classifier fallback" + ) def create_intent_graph(): @@ -167,7 +188,8 @@ def create_intent_graph(): # Create custom classifier fallback strategy custom_classifier_strategy = create_custom_classifier_fallback() register_remediation_strategy( - "custom_classifier_fallback", custom_classifier_strategy) + "custom_classifier_fallback", custom_classifier_strategy + ) # Create handlers handlers = [ @@ -178,7 +200,7 @@ def create_intent_graph(): param_schema={"name": str}, llm_config=LLM_CONFIG, context_inputs={"greeting_count"}, - context_outputs={"greeting_count"} + context_outputs={"greeting_count"}, ), handler( name="calculate", @@ -187,7 +209,7 @@ def create_intent_graph(): param_schema={"operation": str, "a": float, "b": float}, llm_config=LLM_CONFIG, context_inputs={"calc_history"}, - context_outputs={"calc_history"} + context_outputs={"calc_history"}, ), handler( name="weather", @@ -196,7 +218,7 @@ def create_intent_graph(): param_schema={"location": str}, llm_config=LLM_CONFIG, context_inputs={"weather_count"}, - context_outputs={"weather_count"} + context_outputs={"weather_count"}, ), handler( name="help", @@ -205,8 +227,8 @@ def create_intent_graph(): param_schema={}, llm_config=LLM_CONFIG, context_inputs={"help_count"}, - context_outputs={"help_count"} - ) + context_outputs={"help_count"}, + ), ] # Create classifier with a failing classifier to force remediation @@ -221,8 +243,7 @@ def create_intent_graph(): children=handlers, description="Main intent classifier with remediation", # Try keyword first, then custom - remediation_strategies=[ - "keyword_fallback", "custom_classifier_fallback"] + remediation_strategies=["keyword_fallback", "custom_classifier_fallback"], ) # Build and return the graph @@ -233,7 +254,9 @@ def run_demo(): """Run the classifier remediation demo.""" print("šŸ”„ Phase 2: Classifier Remediation System Demo") print("=" * 55) - print("This demo uses a deliberately failing classifier to showcase remediation strategies.") + print( + "This demo uses a deliberately failing classifier to showcase remediation strategies." + ) print() # Create intent graph @@ -270,19 +293,20 @@ def run_demo(): print(f"āœ… Success: {result.output}") if result.params and "remediation_strategy" in result.params: print( - f"šŸ”„ Remediation used: {result.params['remediation_strategy']}") + f"šŸ”„ Remediation used: {result.params['remediation_strategy']}" + ) if "confidence_score" in result.params: print( - f"šŸ“Š Confidence score: {result.params['confidence_score']:.2f}") + f"šŸ“Š Confidence score: {result.params['confidence_score']:.2f}" + ) if "matched_keyword" in result.params: - print( - f"šŸ” Matched keyword: {result.params['matched_keyword']}") + print(f"šŸ” Matched keyword: {result.params['matched_keyword']}") if "chosen_child" in result.params: - print( - f"šŸŽÆ Chosen child: {result.params['chosen_child']}") + print(f"šŸŽÆ Chosen child: {result.params['chosen_child']}") else: print( - f"āŒ Failed: {result.error.message if result.error else 'Unknown error'}") + f"āŒ Failed: {result.error.message if result.error else 'Unknown error'}" + ) except Exception as e: print(f"šŸ’„ Exception: {type(e).__name__}: {str(e)}") diff --git a/examples/context_debug_demo.py b/examples/context_debug_demo.py index 588cc28..25597ab 100644 --- a/examples/context_debug_demo.py +++ b/examples/context_debug_demo.py @@ -6,7 +6,7 @@ import os from intent_kit import IntentGraphBuilder, handler, llm_classifier -from intent_kit import get_context_dependencies, validate_context_flow, trace_context_execution +from intent_kit import trace_context_execution from intent_kit.context import IntentContext from dotenv import load_dotenv @@ -16,7 +16,7 @@ LLM_CONFIG = { "provider": "openrouter", "api_key": os.getenv("OPENROUTER_API_KEY"), - "model": "meta-llama/llama-4-maverick-17b-128e-instruct" + "model": "meta-llama/llama-4-maverick-17b-128e-instruct", } @@ -28,7 +28,9 @@ def greet_handler(name: str, context: IntentContext) -> str: return f"Hello {name}! (Greeting #{count})" -def calculate_handler(operation: str, a: float, b: float, context: IntentContext) -> str: +def calculate_handler( + operation: str, a: float, b: float, context: IntentContext +) -> str: """Simple calculate handler with history.""" ops = {"add": "+", "plus": "+", "multiply": "*", "times": "*"} op = ops.get(operation.lower(), operation) @@ -50,7 +52,7 @@ def build_graph(): param_schema={"name": str}, llm_config=LLM_CONFIG, context_inputs={"greeting_count"}, - context_outputs={"greeting_count", "last_greeted"} + context_outputs={"greeting_count", "last_greeted"}, ), handler( name="calculate", @@ -59,13 +61,18 @@ def build_graph(): param_schema={"operation": str, "a": float, "b": float}, llm_config=LLM_CONFIG, context_inputs={"calc_history"}, - context_outputs={"calc_history"} + context_outputs={"calc_history"}, ), ] - classifier = llm_classifier( - name="root", children=handlers, llm_config=LLM_CONFIG) - return IntentGraphBuilder().root(classifier).debug_context(True).context_trace(True).build() + classifier = llm_classifier(name="root", children=handlers, llm_config=LLM_CONFIG) + return ( + IntentGraphBuilder() + .root(classifier) + .debug_context(True) + .context_trace(True) + .build() + ) def main(): @@ -81,7 +88,7 @@ def main(): "Hello, my name is Alice", "What's 5 plus 3?", "Hi again", - "Multiply 4 and 2" + "Multiply 4 and 2", ] for user_input in test_inputs: @@ -92,7 +99,8 @@ def main(): print(f"Output: {result.output}") print("Debug Context (Colorized Console format):") debug_output = trace_context_execution( - graph, user_input, context, "console") + graph, user_input, context, "console" + ) print(debug_output) # Also available: "json" format for plain JSON diff --git a/examples/context_demo.py b/examples/context_demo.py index 9cbd767..ea33bda 100644 --- a/examples/context_demo.py +++ b/examples/context_demo.py @@ -7,18 +7,18 @@ import os from datetime import datetime -from typing import Dict, Any, Optional, List from intent_kit.context import IntentContext from intent_kit import IntentGraphBuilder, handler, llm_classifier from intent_kit.services.llm_factory import LLMFactory from dotenv import load_dotenv + load_dotenv() # LLM configuration LLM_CONFIG = { "provider": "openrouter", "api_key": os.getenv("OPENROUTER_API_KEY"), - "model": "meta-llama/llama-4-maverick-17b-128e-instruct" + "model": "meta-llama/llama-4-maverick-17b-128e-instruct", } # Create LLM client @@ -34,13 +34,16 @@ def greet_handler(name: str, context: IntentContext) -> str: # Update context context.set("greeting_count", greeting_count + 1, modified_by="greet") context.set("last_greeted", name, modified_by="greet") - context.set("last_greeting_time", - datetime.now().isoformat(), modified_by="greet") + context.set("last_greeting_time", datetime.now().isoformat(), modified_by="greet") - return f"Hello {name}! (Greeting #{greeting_count + 1}, last greeted: {last_greeted})" + return ( + f"Hello {name}! (Greeting #{greeting_count + 1}, last greeted: {last_greeted})" + ) -def calculate_handler(operation: str, a: float, b: float, context: IntentContext) -> str: +def calculate_handler( + operation: str, a: float, b: float, context: IntentContext +) -> str: """Calculate handler with history tracking.""" result = None @@ -69,16 +72,21 @@ def calculate_handler(operation: str, a: float, b: float, context: IntentContext # Store calculation history in context calc_history = context.get("calculation_history", []) - calc_history.append({ - "operation": operation_display, - "a": a, - "b": b, - "result": result, - "timestamp": datetime.now().isoformat() - }) + calc_history.append( + { + "operation": operation_display, + "a": a, + "b": b, + "result": result, + "timestamp": datetime.now().isoformat(), + } + ) context.set("calculation_history", calc_history, modified_by="calculate") - context.set("last_calculation", - f"{a} {operation_display} {b} = {result}", modified_by="calculate") + context.set( + "last_calculation", + f"{a} {operation_display} {b} = {result}", + modified_by="calculate", + ) return f"{a} {operation_display} {b} = {result}" @@ -88,18 +96,21 @@ def weather_handler(location: str, context: IntentContext) -> str: # Check if we've already fetched weather for this location recently last_weather = context.get("last_weather", {}) if last_weather.get("location") == location: - time_diff = datetime.now().isoformat() return f"Weather in {location}: {last_weather.get('data')} (cached)" # Simulate weather data weather_data = f"72Ā°F, Sunny (simulated for {location})" # Store in context - context.set("last_weather", { - "location": location, - "data": weather_data, - "timestamp": datetime.now().isoformat() - }, modified_by="weather") + context.set( + "last_weather", + { + "location": location, + "data": weather_data, + "timestamp": datetime.now().isoformat(), + }, + modified_by="weather", + ) return f"Weather in {location}: {weather_data}" @@ -131,8 +142,7 @@ def build_context_aware_tree(): param_schema={"name": str}, llm_config=LLM_CONFIG, context_inputs={"greeting_count", "last_greeted"}, - context_outputs={"greeting_count", - "last_greeted", "last_greeting_time"} + context_outputs={"greeting_count", "last_greeted", "last_greeting_time"}, ) calc_handler_node = handler( @@ -142,7 +152,7 @@ def build_context_aware_tree(): param_schema={"operation": str, "a": float, "b": float}, llm_config=LLM_CONFIG, context_inputs={"calculation_history"}, - context_outputs={"calculation_history", "last_calculation"} + context_outputs={"calculation_history", "last_calculation"}, ) weather_handler_node = handler( @@ -152,7 +162,7 @@ def build_context_aware_tree(): param_schema={"location": str}, llm_config=LLM_CONFIG, context_inputs={"last_weather"}, - context_outputs={"last_weather"} + context_outputs={"last_weather"}, ) history_handler_node = handler( @@ -161,7 +171,7 @@ def build_context_aware_tree(): handler_func=show_calculation_history_handler, param_schema={}, llm_config=LLM_CONFIG, - context_inputs={"calculation_history"} + context_inputs={"calculation_history"}, ) help_handler_node = handler( @@ -169,7 +179,7 @@ def build_context_aware_tree(): description="Get help", handler_func=lambda: "I can help you with greetings, calculations, weather, and showing history!", param_schema={}, - llm_config=LLM_CONFIG + llm_config=LLM_CONFIG, ) # Create classifier with auto-wired children descriptions @@ -180,10 +190,10 @@ def build_context_aware_tree(): calc_handler_node, weather_handler_node, history_handler_node, - help_handler_node + help_handler_node, ], llm_config=LLM_CONFIG, - description="LLM-powered intent classifier with context support" + description="LLM-powered intent classifier with context support", ) @@ -191,17 +201,13 @@ def main(): print("IntentKit Context Demo") print("This demo shows how context can be shared between workflow steps.") print("You must set a valid API key in LLM_CONFIG for this to work.") - print("\n" + "="*50) + print("\n" + "=" * 50) # Create context for the session context = IntentContext(session_id="demo_user_123", debug=True) # Create IntentGraph using the new builder pattern - graph = ( - IntentGraphBuilder() - .root(build_context_aware_tree()) - .build() - ) + graph = IntentGraphBuilder().root(build_context_aware_tree()).build() # Test sequence showing context persistence test_sequence = [ @@ -211,7 +217,7 @@ def main(): "Hi again", # Should show greeting count "What's 8 times 3?", "Weather in San Francisco again", # Should show cached result - "What was my last calculation?" # Should show context access + "What was my last calculation?", # Should show context access ] for i, user_input in enumerate(test_sequence, 1): @@ -229,30 +235,29 @@ def main(): # Show execution path if available if result.children_results: - print(f" Execution Path:") + print(" Execution Path:") for i, child_result in enumerate(result.children_results): - path_str = '.'.join(child_result.node_path) + path_str = ".".join(child_result.node_path) print( - f" {i+1}. {child_result.node_name} ({child_result.node_type}) - Path: {path_str}") + f" {i+1}. {child_result.node_name} ({child_result.node_type}) - Path: {path_str}" + ) if child_result.params: - print( - f" Params: {child_result.params}") + print(f" Params: {child_result.params}") if child_result.output: - print( - f" Output: {child_result.output}") + print(f" Output: {child_result.output}") if child_result.error: print(f" Error: {child_result.error}") # Show context state after execution - print(f" Context state:") - print( - f" Greeting count: {context.get('greeting_count', 0)}") - print( - f" Last greeted: {context.get('last_greeted', 'None')}") + print(" Context state:") + print(f" Greeting count: {context.get('greeting_count', 0)}") + print(f" Last greeted: {context.get('last_greeted', 'None')}") print( - f" Calc history: {len(context.get('calculation_history', []))} entries") + f" Calc history: {len(context.get('calculation_history', []))} entries" + ) print( - f" Last weather: {context.get('last_weather', {}).get('location', 'None')}") + f" Last weather: {context.get('last_weather', {}).get('location', 'None')}" + ) else: print(f" Error: {result.error}") @@ -266,30 +271,30 @@ def main(): print(f" Context errors: {len(errors)} total") for error in errors[-2:]: # Show last 2 errors print( - f" [{error.timestamp.strftime('%H:%M:%S')}] {error.node_name}: {error.error_message}") + f" [{error.timestamp.strftime('%H:%M:%S')}] {error.node_name}: {error.error_message}" + ) except Exception as e: print(f" Error: {e}") # Show final context state - print(f"\n--- Final Context State ---") + print("\n--- Final Context State ---") print(f"Session ID: {context.session_id}") print(f"Total fields: {len(context.keys())}") print(f"History entries: {len(context.get_history())}") print(f"Error count: {context.error_count()}") # Show some context history - print(f"\n--- Context History (last 5 entries) ---") + print("\n--- Context History (last 5 entries) ---") for entry in context.get_history(limit=5): print(f" {entry.timestamp}: {entry.action} '{entry.key}' = {entry.value}") # Show recent errors if any errors = context.get_errors(limit=3) if errors: - print(f"\n--- Recent Errors (last 3) ---") + print("\n--- Recent Errors (last 3) ---") for error in errors: - print( - f" [{error.timestamp.strftime('%H:%M:%S')}] {error.node_name}") + print(f" [{error.timestamp.strftime('%H:%M:%S')}] {error.node_name}") print(f" Input: {error.user_input}") print(f" Error: {error.error_message}") if error.params: diff --git a/examples/error_demo.py b/examples/error_demo.py index 6a50660..032f0ac 100644 --- a/examples/error_demo.py +++ b/examples/error_demo.py @@ -7,7 +7,6 @@ """ from intent_kit import handler -from intent_kit.builder import handler, llm_classifier from intent_kit.classifiers.keyword import keyword_classifier @@ -20,7 +19,7 @@ def extract_args(user_input: str, context=None) -> dict: return { "name": words[0] if words else "", - "age": words[1] if len(words) > 1 else "" + "age": words[1] if len(words) > 1 else "", } @@ -47,17 +46,18 @@ def main(): name="Greet", description="Greet someone with their name and age", handler_func=greet_handler, - param_schema={"name": str, "age": int} + param_schema={"name": str, "age": int}, # No llm_config = uses rule-based extraction ) # Create a classifier node manually since we need a custom classifier from intent_kit.classifiers import ClassifierNode + root_node = ClassifierNode( name="Root", classifier=keyword_classifier, children=[greet_handler_node], - description="Demo intent tree" + description="Demo intent tree", ) # Set parent reference @@ -65,11 +65,11 @@ def main(): # Test cases that will trigger different types of errors test_cases = [ - "Greet John 30", # Success - "Greet", # Validation failure (missing age) - "Greet John -5", # Handler error (negative age) - "Greet John 200", # Handler error (unrealistic age) - "Greet John abc", # Type validation error (age not a number) + "Greet John 30", # Success + "Greet", # Validation failure (missing age) + "Greet John -5", # Handler error (negative age) + "Greet John 200", # Handler error (unrealistic age) + "Greet John abc", # Type validation error (age not a number) ] for user_input in test_cases: @@ -89,7 +89,6 @@ def main(): for step in result.children_results: node_name = step.node_name node_type = step.node_type - success = step.success if step.error: # Now we have rich error information! diff --git a/examples/eval_api_demo.py b/examples/eval_api_demo.py index 06362c5..6e4aa12 100644 --- a/examples/eval_api_demo.py +++ b/examples/eval_api_demo.py @@ -5,24 +5,26 @@ Demonstration of the new intent-kit evaluation API. """ +from dotenv import load_dotenv from intent_kit.evals import ( load_dataset, run_eval, run_eval_from_path, run_eval_from_module, EvalTestCase, - Dataset + Dataset, ) from intent_kit.evals.sample_nodes.classifier_node_llm import classifier_node_llm +load_dotenv() + def demo_basic_usage(): """Demonstrate basic usage with direct node instance.""" print("=== Basic Usage Demo ===") # Load dataset - dataset = load_dataset( - "intent_kit/evals/datasets/classifier_node_llm.yaml") + dataset = load_dataset("intent_kit/evals/datasets/classifier_node_llm.yaml") print(f"Loaded dataset: {dataset.name}") print(f"Test cases: {len(dataset.test_cases)}") @@ -37,7 +39,7 @@ def demo_basic_usage(): json_path = result.save_json() md_path = result.save_markdown() - print(f"Results saved to:") + print("Results saved to:") print(f" CSV: {csv_path}") print(f" JSON: {json_path}") print(f" Markdown: {md_path}") @@ -49,8 +51,7 @@ def demo_from_path(): print("\n=== From Path Demo ===") result = run_eval_from_path( - "intent_kit/evals/datasets/classifier_node_llm.yaml", - classifier_node_llm + "intent_kit/evals/datasets/classifier_node_llm.yaml", classifier_node_llm ) result.print_summary() @@ -64,7 +65,7 @@ def demo_from_module(): result = run_eval_from_module( "intent_kit/evals/datasets/classifier_node_llm.yaml", "intent_kit.evals.sample_nodes.classifier_node_llm", - "classifier_node_llm" + "classifier_node_llm", ) result.print_summary() @@ -84,7 +85,7 @@ def case_insensitive_comparator(expected, actual): result = run_eval_from_path( "intent_kit/evals/datasets/classifier_node_llm.yaml", classifier_node_llm, - comparator=case_insensitive_comparator + comparator=case_insensitive_comparator, ) result.print_summary() @@ -98,7 +99,7 @@ def demo_fail_fast(): result = run_eval_from_path( "intent_kit/evals/datasets/classifier_node_llm.yaml", classifier_node_llm, - fail_fast=True + fail_fast=True, ) print(f"Fail-fast evaluation completed with {result.total_count()} tests") @@ -114,13 +115,13 @@ def demo_programmatic_dataset(): EvalTestCase( input="What's the weather like in Paris?", expected="Weather in Paris: Sunny with a chance of rain", - context={"user_id": "demo_user"} + context={"user_id": "demo_user"}, ), EvalTestCase( input="Cancel my flight", expected="Successfully cancelled flight", - context={"user_id": "demo_user"} - ) + context={"user_id": "demo_user"}, + ), ] # Create dataset @@ -129,7 +130,7 @@ def demo_programmatic_dataset(): description="Programmatically created test dataset", node_type="classifier", node_name="classifier_node_llm", - test_cases=test_cases + test_cases=test_cases, ) # Run evaluation @@ -152,15 +153,9 @@ def broken_node(input_text, context=None): # Create a simple test case test_cases = [ EvalTestCase( - input="What's the weather like?", - expected="Weather response", - context={} + input="What's the weather like?", expected="Weather response", context={} ), - EvalTestCase( - input="Hello there", - expected="Default response", - context={} - ) + EvalTestCase(input="Hello there", expected="Default response", context={}), ] dataset = Dataset( @@ -168,7 +163,7 @@ def broken_node(input_text, context=None): description="Testing error handling", node_type="test", node_name="broken_node", - test_cases=test_cases + test_cases=test_cases, ) result = run_eval(dataset, broken_node) @@ -192,7 +187,7 @@ def main(): demo_custom_comparator, demo_fail_fast, demo_programmatic_dataset, - demo_error_handling + demo_error_handling, ] results = [] diff --git a/examples/multi_intent_demo.py b/examples/multi_intent_demo.py index ea0a223..109f108 100644 --- a/examples/multi_intent_demo.py +++ b/examples/multi_intent_demo.py @@ -17,7 +17,7 @@ LLM_CONFIG = { "provider": "openrouter", "api_key": os.getenv("OPENROUTER_API_KEY"), - "model": "meta-llama/llama-4-maverick-17b-128e-instruct" + "model": "meta-llama/llama-4-maverick-17b-128e-instruct", } # Configure your intent graph here @@ -36,7 +36,7 @@ def _calculate_handler(operation: str, a: float, b: float) -> str: "multiplied": "*", "divided": "/", "divide": "/", - "over": "/" + "over": "/", } # Get the mathematical operator @@ -59,29 +59,30 @@ def create_intent_graph(): description="Greet the user", handler_func=lambda name, **kwargs: f"Hello {name}!", param_schema={"name": str}, - llm_config=LLM_CONFIG + llm_config=LLM_CONFIG, ), handler( name="calculate", description="Perform a calculation", handler_func=lambda operation, a, b, **kwargs: _calculate_handler( - operation, a, b), + operation, a, b + ), param_schema={"operation": str, "a": float, "b": float}, - llm_config=LLM_CONFIG + llm_config=LLM_CONFIG, ), handler( name="weather", description="Get weather information", handler_func=lambda location, **kwargs: f"Weather in {location}: 72Ā°F, Sunny (simulated)", param_schema={"location": str}, - llm_config=LLM_CONFIG + llm_config=LLM_CONFIG, ), handler( name="help", description="Get help", handler_func=lambda **kwargs: "I can help with greetings, calculations, and weather!", - param_schema={} - ) + param_schema={}, + ), ] # Create classifier @@ -89,7 +90,7 @@ def create_intent_graph(): name="root", children=handlers, llm_config=LLM_CONFIG, - description="Main intent classifier" + description="Main intent classifier", ) # Build and return the graph with LLM-powered splitter for intelligent multi-intent handling @@ -108,7 +109,7 @@ def create_intent_graph(): "Hello, my name is Alice", "What's 15 plus 7?", "Weather in San Francisco", - "Help me" + "Help me", ] print("=== Single Intent Tests ===") @@ -126,7 +127,7 @@ def create_intent_graph(): "Hello Alice and what's the weather in San Francisco", "Calculate 5 plus 3 and also greet Bob", "Help me and get weather for New York", - "Greet John, calculate 10 times 2, and weather in London" + "Greet John, calculate 10 times 2, and weather in London", ] print("\n=== Multi-Intent Tests ===") diff --git a/examples/ollama_demo.py b/examples/ollama_demo.py index 6959ece..650baec 100644 --- a/examples/ollama_demo.py +++ b/examples/ollama_demo.py @@ -13,7 +13,7 @@ OLLAMA_CONFIG = { "provider": "ollama", "model": "gemma3:27b", # Change this to your available model - "base_url": "http://localhost:11434" + "base_url": "http://localhost:11434", } # Configure your intent graph here @@ -29,36 +29,36 @@ def create_intent_graph(): description="Greet the user", handler_func=_greet_handler, param_schema={"name": str}, - llm_config=OLLAMA_CONFIG + llm_config=OLLAMA_CONFIG, ), handler( name="calculate", description="Perform a calculation", handler_func=_calculate_handler, param_schema={"operation": str, "a": float, "b": float}, - llm_config=OLLAMA_CONFIG + llm_config=OLLAMA_CONFIG, ), handler( name="weather", description="Get weather information", handler_func=_weather_handler, param_schema={"location": str}, - llm_config=OLLAMA_CONFIG + llm_config=OLLAMA_CONFIG, ), handler( name="history", description="Show calculation history", handler_func=_history_handler, param_schema={}, - llm_config=OLLAMA_CONFIG + llm_config=OLLAMA_CONFIG, ), handler( name="help", description="Get help", handler_func=lambda **kwargs: "I can help with greetings, calculations, weather, and history!", param_schema={}, - llm_config=OLLAMA_CONFIG - ) + llm_config=OLLAMA_CONFIG, + ), ] # Create classifier @@ -66,7 +66,7 @@ def create_intent_graph(): name="root", children=handlers, llm_config=OLLAMA_CONFIG, - description="Ollama-powered intent classifier" + description="Ollama-powered intent classifier", ) # Build and return the graph @@ -81,7 +81,9 @@ def _greet_handler(name: str, context: IntentContext) -> str: return f"Hello {name}! (Greeting #{greeting_count})" -def _calculate_handler(operation: str, a: float, b: float, context: IntentContext) -> str: +def _calculate_handler( + operation: str, a: float, b: float, context: IntentContext +) -> str: if operation.lower() in ["add", "plus", "+"]: result = a + b op_display = "plus" @@ -93,13 +95,15 @@ def _calculate_handler(operation: str, a: float, b: float, context: IntentContex # Store in context calc_history = context.get("calculation_history", []) - calc_history.append({ - "operation": op_display, - "a": a, - "b": b, - "result": result, - "timestamp": datetime.now().isoformat() - }) + calc_history.append( + { + "operation": op_display, + "a": a, + "b": b, + "result": result, + "timestamp": datetime.now().isoformat(), + } + ) context.set("calculation_history", calc_history, modified_by="calculate") return f"{a} {op_display} {b} = {result}" @@ -112,11 +116,15 @@ def _weather_handler(location: str, context: IntentContext) -> str: return f"Weather in {location}: {last_weather.get('data')} (cached)" weather_data = f"72Ā°F, Sunny (simulated for {location})" - context.set("last_weather", { - "location": location, - "data": weather_data, - "timestamp": datetime.now().isoformat() - }, modified_by="weather") + context.set( + "last_weather", + { + "location": location, + "data": weather_data, + "timestamp": datetime.now().isoformat(), + }, + modified_by="weather", + ) return f"Weather in {location}: {weather_data}" @@ -133,7 +141,9 @@ def _history_handler(context: IntentContext) -> str: # Test the graph if __name__ == "__main__": print("Ollama Demo - Local LLM IntentGraph") - print("Make sure Ollama is running and you have a model pulled (e.g., 'ollama pull gemma3:27b')") + print( + "Make sure Ollama is running and you have a model pulled (e.g., 'ollama pull gemma3:27b')" + ) print() graph = create_intent_graph() @@ -145,7 +155,7 @@ def _history_handler(context: IntentContext) -> str: "Weather in San Francisco", "What was my last calculation?", "Multiply 8 and 3", - "Help me" + "Help me", ] for user_input in test_inputs: diff --git a/examples/remediation_demo.py b/examples/remediation_demo.py index 9739f58..c13b98f 100644 --- a/examples/remediation_demo.py +++ b/examples/remediation_demo.py @@ -15,9 +15,7 @@ from intent_kit.utils.logger import Logger from intent_kit.handlers.remediation import ( RemediationStrategy, - create_retry_strategy, - create_fallback_strategy, - register_remediation_strategy + register_remediation_strategy, ) from intent_kit.node.types import ExecutionResult, ExecutionError from intent_kit.context import IntentContext @@ -26,6 +24,7 @@ import os from typing import Optional from dotenv import load_dotenv + sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) # Load environment variables @@ -39,11 +38,13 @@ LLM_CONFIG = { "provider": "openai", "model": "gpt-4.1-mini", - "api_key": os.getenv("OPENAI_API_KEY") + "api_key": os.getenv("OPENAI_API_KEY"), } -def unreliable_calculator(operation: str, a: float, b: float, context: IntentContext) -> str: +def unreliable_calculator( + operation: str, a: float, b: float, context: IntentContext +) -> str: """ A deliberately unreliable calculator that fails randomly to demonstrate remediation. """ @@ -52,7 +53,8 @@ def unreliable_calculator(operation: str, a: float, b: float, context: IntentCon # Simulate random failures (30% failure rate) if random.random() < 0.3: raise Exception( - "Random calculation failure - this is expected for demo purposes") + "Random calculation failure - this is expected for demo purposes" + ) ops = {"add": "+", "plus": "+", "multiply": "*", "times": "*"} op = ops.get(operation.lower(), operation) @@ -65,7 +67,9 @@ def unreliable_calculator(operation: str, a: float, b: float, context: IntentCon return f"{a} {operation} {b} = {result}" -def reliable_calculator(operation: str, a: float, b: float, context: IntentContext) -> str: +def reliable_calculator( + operation: str, a: float, b: float, context: IntentContext +) -> str: """ A reliable fallback calculator that always works. """ @@ -97,11 +101,10 @@ def execute( user_input: str, context: Optional[IntentContext] = None, original_error: Optional[ExecutionError] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Log the error and return a simple message.""" - self.logger.info( - f"LogAndContinueStrategy: Handling error for {node_name}") + self.logger.info(f"LogAndContinueStrategy: Handling error for {node_name}") from intent_kit.node.types import ExecutionResult from intent_kit.node.enums import NodeType @@ -114,11 +117,13 @@ def execute( input=user_input, output=f"Operation completed with warnings (original error: {original_error.message if original_error else 'unknown'})", error=None, - params=kwargs.get('validated_params', {}), - children_results=[] + params=kwargs.get("validated_params", {}), + children_results=[], ) - return LogAndContinueStrategy("log_and_continue", "Log error and continue with warning") + return LogAndContinueStrategy( + "log_and_continue", "Log error and continue with warning" + ) def create_intent_graph(): @@ -139,9 +144,8 @@ def create_intent_graph(): llm_config=LLM_CONFIG, context_inputs={"calc_history"}, context_outputs={"calc_history"}, - remediation_strategies=["retry_on_fail"] # Built-in retry strategy + remediation_strategies=["retry_on_fail"], # Built-in retry strategy ), - # Handler with fallback strategy handler( name="reliable_calc", @@ -152,9 +156,8 @@ def create_intent_graph(): context_inputs={"calc_history"}, context_outputs={"calc_history"}, # Built-in fallback strategy - remediation_strategies=["fallback_to_another_node"] + remediation_strategies=["fallback_to_another_node"], ), - # Handler with custom remediation strategy handler( name="simple_greet", @@ -164,8 +167,8 @@ def create_intent_graph(): llm_config=LLM_CONFIG, context_inputs={"greeting_count"}, context_outputs={"greeting_count"}, - remediation_strategies=["log_and_continue"] # Custom strategy - ) + remediation_strategies=["log_and_continue"], # Custom strategy + ), ] # Create classifier @@ -173,7 +176,7 @@ def create_intent_graph(): name="root", children=handlers, llm_config=LLM_CONFIG, - description="Main intent classifier with remediation" + description="Main intent classifier with remediation", ) # Build and return the graph @@ -197,7 +200,7 @@ def run_demo(): "What is 10 times 2?", "Hello Alice", "Add 7 and 4", - "Multiply 3 by 6" + "Multiply 3 by 6", ] print("\nšŸ“‹ Test Cases:") @@ -214,7 +217,8 @@ def run_demo(): print(f"āœ… Success: {result.output}") else: print( - f"āŒ Failed: {result.error.message if result.error else 'Unknown error'}") + f"āŒ Failed: {result.error.message if result.error else 'Unknown error'}" + ) except Exception as e: print(f"šŸ’„ Exception: {type(e).__name__}: {str(e)}") diff --git a/examples/simple_demo.ipynb b/examples/simple_demo.ipynb new file mode 100644 index 0000000..fad8edb --- /dev/null +++ b/examples/simple_demo.ipynb @@ -0,0 +1,27 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "f98711a1", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Hello, World!\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.11.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/simple_demo.py b/examples/simple_demo.py index 28617a8..8b950d6 100644 --- a/examples/simple_demo.py +++ b/examples/simple_demo.py @@ -14,7 +14,7 @@ LLM_CONFIG = { "provider": "openrouter", "api_key": os.getenv("OPENROUTER_API_KEY"), - "model": "meta-llama/llama-4-maverick-17b-128e-instruct" + "model": "meta-llama/llama-4-maverick-17b-128e-instruct", } # Configure your intent graph here @@ -33,7 +33,7 @@ def _calculate_handler(operation: str, a: float, b: float) -> str: "multiplied": "*", "divided": "/", "divide": "/", - "over": "/" + "over": "/", } # Get the mathematical operator @@ -56,30 +56,31 @@ def create_intent_graph(): description="Greet the user", handler_func=lambda name, **kwargs: f"Hello {name}!", param_schema={"name": str}, - llm_config=LLM_CONFIG # Remove this line for rule-based extraction + llm_config=LLM_CONFIG, # Remove this line for rule-based extraction ), handler( name="calculate", description="Perform a calculation", handler_func=lambda operation, a, b, **kwargs: _calculate_handler( - operation, a, b), + operation, a, b + ), param_schema={"operation": str, "a": float, "b": float}, - llm_config=LLM_CONFIG + llm_config=LLM_CONFIG, ), handler( name="weather", description="Get weather information", handler_func=lambda location, **kwargs: f"Weather in {location}: 72Ā°F, Sunny (simulated)", param_schema={"location": str}, - llm_config=LLM_CONFIG + llm_config=LLM_CONFIG, ), handler( name="help", description="Get help", handler_func=lambda **kwargs: "I can help with greetings, calculations, and weather!", param_schema={}, - llm_config=LLM_CONFIG - ) + llm_config=LLM_CONFIG, + ), ] # Create classifier @@ -87,7 +88,7 @@ def create_intent_graph(): name="root", children=handlers, llm_config=LLM_CONFIG, - description="Main intent classifier" + description="Main intent classifier", ) # Build and return the graph (uses default pass-through splitter) @@ -106,7 +107,7 @@ def create_intent_graph(): "What's 15 plus 7?", "Weather in San Francisco", "Help me", - "Multiply 8 and 3" + "Multiply 8 and 3", ] for user_input in test_inputs: diff --git a/intent_kit/__init__.py b/intent_kit/__init__.py index 65bddca..4421c85 100644 --- a/intent_kit/__init__.py +++ b/intent_kit/__init__.py @@ -13,10 +13,21 @@ from .classifiers import ClassifierNode from .handlers import HandlerNode from .splitters import SplitterNode -from .builder import IntentGraphBuilder, handler, llm_classifier, llm_splitter_node, rule_splitter_node, create_intent_graph +from .builder import ( + IntentGraphBuilder, + handler, + llm_classifier, + llm_splitter_node, + rule_splitter_node, + create_intent_graph, +) from .graph import IntentGraph from .context import IntentContext -from .context.debug import get_context_dependencies, validate_context_flow, trace_context_execution +from .context.debug import ( + get_context_dependencies, + validate_context_flow, + trace_context_execution, +) from .classifiers import keyword_classifier from .classifiers.llm_classifier import create_llm_classifier, create_llm_arg_extractor from .splitters import rule_splitter, llm_splitter @@ -26,37 +37,31 @@ __all__ = [ # Core components - 'HandlerNode', - 'TreeNode', - 'NodeType', - 'ClassifierNode', - 'SplitterNode', - - 'IntentGraph', - 'IntentContext', - + "HandlerNode", + "TreeNode", + "NodeType", + "ClassifierNode", + "SplitterNode", + "IntentGraph", + "IntentContext", # Classifiers - 'keyword_classifier', - 'create_llm_classifier', - 'create_llm_arg_extractor', - + "keyword_classifier", + "create_llm_classifier", + "create_llm_arg_extractor", # Splitters - 'rule_splitter', - 'llm_splitter', - + "rule_splitter", + "llm_splitter", # Services - 'LLMFactory', - + "LLMFactory", # New high-level API (recommended) - 'IntentGraphBuilder', - 'handler', - 'llm_classifier', - 'llm_splitter_node', - 'rule_splitter_node', - 'create_intent_graph', - + "IntentGraphBuilder", + "handler", + "llm_classifier", + "llm_splitter_node", + "rule_splitter_node", + "create_intent_graph", # Context debugging utilities - 'get_context_dependencies', - 'validate_context_flow', - 'trace_context_execution', + "get_context_dependencies", + "validate_context_flow", + "trace_context_execution", ] diff --git a/intent_kit/builder.py b/intent_kit/builder.py index 891c90d..54ba53f 100644 --- a/intent_kit/builder.py +++ b/intent_kit/builder.py @@ -7,11 +7,12 @@ create_llm_classifier, create_llm_arg_extractor, get_default_classification_prompt, - get_default_extraction_prompt + get_default_extraction_prompt, ) from .types import IntentChunk from .graph import IntentGraph from .utils.logger import Logger + # Import splitter functions for builder methods from .splitters.functions import rule_splitter, llm_splitter from .handlers.remediation import RemediationStrategy @@ -29,7 +30,7 @@ def __init__(self): self._debug_context = False self._context_trace = False - def root(self, node: TreeNode) -> 'IntentGraphBuilder': + def root(self, node: TreeNode) -> "IntentGraphBuilder": """Set the root node for the intent graph. Args: @@ -41,7 +42,7 @@ def root(self, node: TreeNode) -> 'IntentGraphBuilder': self._root_node = node return self - def splitter(self, splitter_func) -> 'IntentGraphBuilder': + def splitter(self, splitter_func) -> "IntentGraphBuilder": """Set a custom splitter function for the intent graph. Args: @@ -69,17 +70,16 @@ def build(self) -> IntentGraph: graph = IntentGraph( splitter=self._splitter, debug_context=self._debug_context, - context_trace=self._context_trace + context_trace=self._context_trace, ) else: graph = IntentGraph( - debug_context=self._debug_context, - context_trace=self._context_trace + debug_context=self._debug_context, context_trace=self._context_trace ) graph.add_root_node(self._root_node) return graph - def debug_context(self, enabled: bool = True) -> 'IntentGraphBuilder': + def debug_context(self, enabled: bool = True) -> "IntentGraphBuilder": """Enable context debugging for the intent graph. Args: @@ -91,7 +91,7 @@ def debug_context(self, enabled: bool = True) -> 'IntentGraphBuilder': self._debug_context = enabled return self - def context_trace(self, enabled: bool = True) -> 'IntentGraphBuilder': + def context_trace(self, enabled: bool = True) -> "IntentGraphBuilder": """Enable detailed context tracing for the intent graph. Args: @@ -116,8 +116,7 @@ def handler( context_outputs: Optional[Set[str]] = None, input_validator: Optional[Callable[[Dict[str, Any]], bool]] = None, output_validator: Optional[Callable[[Any], bool]] = None, - remediation_strategies: Optional[List[Union[str, - "RemediationStrategy"]]] = None + remediation_strategies: Optional[List[Union[str, "RemediationStrategy"]]] = None, ) -> TreeNode: """Create a handler node with automatic argument extraction. @@ -157,15 +156,17 @@ def handler( ) else: # Use simple rule-based extraction as fallback - def simple_arg_extractor(text: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]: + def simple_arg_extractor( + text: str, context: Optional[Dict[str, Any]] = None + ) -> Dict[str, Any]: """Simple rule-based argument extractor.""" extracted = {} # For each parameter, try to extract it using simple rules for param_name, param_type in param_schema.items(): - if param_type == str: + if isinstance(param_type, type) and param_type is str: # For string parameters, try to find relevant text - if param_name.lower() in ['name', 'location', 'operation']: + if param_name.lower() in ["name", "location", "operation"]: # Extract the last word as a simple heuristic words = text.split() if words: @@ -173,35 +174,36 @@ def simple_arg_extractor(text: str, context: Optional[Dict[str, Any]] = None) -> else: # Default: use the entire text for string params extracted[param_name] = text.strip() - elif param_type in [int, float]: + elif isinstance(param_type, type) and param_type in [int, float]: # For numeric parameters, try to find numbers in text import re - numbers = re.findall(r'\d+(?:\.\d+)?', text) + + numbers = re.findall(r"\d+(?:\.\d+)?", text) if numbers: try: extracted[param_name] = param_type(numbers[0]) except (ValueError, IndexError): # Use default values for common parameters - if param_name in ['a', 'first']: + if param_name in ["a", "first"]: extracted[param_name] = param_type(10) - elif param_name in ['b', 'second']: + elif param_name in ["b", "second"]: extracted[param_name] = param_type(5) else: extracted[param_name] = param_type(0) else: # Use default values - if param_name in ['a', 'first']: + if param_name in ["a", "first"]: extracted[param_name] = param_type(10) - elif param_name in ['b', 'second']: + elif param_name in ["b", "second"]: extracted[param_name] = param_type(5) else: extracted[param_name] = param_type(0) else: # For other types, use a default value - if param_type == bool: - extracted[param_name] = True + if isinstance(param_type, type) and param_type is bool: + extracted[param_name] = True # type: ignore else: - extracted[param_name] = None + extracted[param_name] = None # type: ignore return extracted @@ -217,7 +219,7 @@ def simple_arg_extractor(text: str, context: Optional[Dict[str, Any]] = None) -> input_validator=input_validator, output_validator=output_validator, description=description, - remediation_strategies=remediation_strategies + remediation_strategies=remediation_strategies, ) @@ -228,8 +230,7 @@ def llm_classifier( llm_config: Dict[str, Any], classification_prompt: Optional[str] = None, description: str = "", - remediation_strategies: Optional[List[Union[str, - "RemediationStrategy"]]] = None + remediation_strategies: Optional[List[Union[str, "RemediationStrategy"]]] = None, ) -> TreeNode: """Create an LLM-powered classifier node with auto-wired children descriptions. @@ -256,13 +257,14 @@ def llm_classifier( # Auto-wire children descriptions for the classifier node_descriptions = [] for child in children: - if hasattr(child, 'description') and child.description: + if hasattr(child, "description") and child.description: node_descriptions.append(f"{child.name}: {child.description}") else: # Use name as fallback if no description node_descriptions.append(child.name) logger.warning( - f"Child node '{child.name}' has no description, using name as fallback") + f"Child node '{child.name}' has no description, using name as fallback" + ) if not classification_prompt: classification_prompt = get_default_classification_prompt() @@ -276,7 +278,7 @@ def llm_classifier( classifier=classifier, children=children, description=description, - remediation_strategies=remediation_strategies + remediation_strategies=remediation_strategies, ) # Set parent reference for all children to this classifier node @@ -291,7 +293,7 @@ def llm_splitter_node( name: str, children: List[TreeNode], llm_config: Dict[str, Any], - description: str = "" + description: str = "", ) -> TreeNode: """Create an LLM-powered splitter node for multi-intent handling. @@ -311,10 +313,13 @@ def llm_splitter_node( ... llm_config=LLM_CONFIG ... ) """ + # Create a wrapper function that provides the LLM client to llm_splitter - def llm_splitter_wrapper(user_input: str, debug: bool = False) -> Sequence[IntentChunk]: + def llm_splitter_wrapper( + user_input: str, debug: bool = False + ) -> Sequence[IntentChunk]: # Extract LLM client from config - llm_client = llm_config.get('llm_client') + llm_client = llm_config.get("llm_client") return llm_splitter(user_input, debug, llm_client) splitter_node = SplitterNode( @@ -322,7 +327,7 @@ def llm_splitter_wrapper(user_input: str, debug: bool = False) -> Sequence[Inten splitter_function=llm_splitter_wrapper, children=children, description=description, - llm_client=llm_config.get('llm_client') + llm_client=llm_config.get("llm_client"), ) # Set parent reference for all children to this splitter node @@ -333,10 +338,7 @@ def llm_splitter_wrapper(user_input: str, debug: bool = False) -> Sequence[Inten def rule_splitter_node( - *, - name: str, - children: List[TreeNode], - description: str = "" + *, name: str, children: List[TreeNode], description: str = "" ) -> TreeNode: """Create a rule-based splitter node for multi-intent handling. @@ -358,7 +360,7 @@ def rule_splitter_node( name=name, splitter_function=rule_splitter, children=children, - description=description + description=description, ) # Set parent reference for all children to this splitter node @@ -369,9 +371,7 @@ def rule_splitter_node( # Convenience function for creating a complete graph -def create_intent_graph( - root_node: TreeNode -) -> IntentGraph: +def create_intent_graph(root_node: TreeNode) -> IntentGraph: """Create an IntentGraph with the given root node. Args: diff --git a/intent_kit/classifiers/__init__.py b/intent_kit/classifiers/__init__.py index 3750147..52ca642 100644 --- a/intent_kit/classifiers/__init__.py +++ b/intent_kit/classifiers/__init__.py @@ -7,18 +7,22 @@ from .node import ClassifierNode from .keyword import keyword_classifier -from .llm_classifier import create_llm_classifier, create_llm_arg_extractor, get_default_classification_prompt, get_default_extraction_prompt +from .llm_classifier import ( + create_llm_classifier, + create_llm_arg_extractor, + get_default_classification_prompt, + get_default_extraction_prompt, +) from .chunk_classifier import classify_intent_chunk __all__ = [ # Node class "ClassifierNode", - # Classifier functions "keyword_classifier", "create_llm_classifier", "create_llm_arg_extractor", "get_default_classification_prompt", "get_default_extraction_prompt", - "classify_intent_chunk" + "classify_intent_chunk", ] diff --git a/intent_kit/classifiers/chunk_classifier.py b/intent_kit/classifiers/chunk_classifier.py index f2ad336..f8f79a1 100644 --- a/intent_kit/classifiers/chunk_classifier.py +++ b/intent_kit/classifiers/chunk_classifier.py @@ -1,18 +1,25 @@ """ LLM-powered chunk classifier for intent chunks. """ -from intent_kit.types import IntentChunk, IntentChunkClassification, IntentClassification, IntentAction, ClassifierOutput + +from intent_kit.types import ( + IntentChunk, + IntentClassification, + IntentAction, + ClassifierOutput, +) from intent_kit.services.llm_factory import LLMFactory from intent_kit.utils.logger import Logger from intent_kit.utils.text_utils import extract_json_from_text, extract_key_value_pairs -import json import re from typing import Optional logger = Logger(__name__) -def classify_intent_chunk(chunk: IntentChunk, llm_config: Optional[dict] = None) -> ClassifierOutput: +def classify_intent_chunk( + chunk: IntentChunk, llm_config: Optional[dict] = None +) -> ClassifierOutput: """ LLM-powered classifier for intent chunks. @@ -23,8 +30,9 @@ def classify_intent_chunk(chunk: IntentChunk, llm_config: Optional[dict] = None) Returns: Classification result with action to take """ - chunk_text = chunk["text"] if isinstance( - chunk, dict) and "text" in chunk else str(chunk) + chunk_text = ( + chunk["text"] if isinstance(chunk, dict) and "text" in chunk else str(chunk) + ) # Fallback for empty chunks if not chunk_text.strip(): @@ -33,7 +41,7 @@ def classify_intent_chunk(chunk: IntentChunk, llm_config: Optional[dict] = None) "classification": IntentClassification.INVALID, "intent_type": None, "action": IntentAction.REJECT, - "metadata": {"confidence": 0.0, "reason": "Empty chunk"} + "metadata": {"confidence": 0.0, "reason": "Empty chunk"}, } # If no LLM config provided, use fallback logic @@ -55,12 +63,14 @@ def classify_intent_chunk(chunk: IntentChunk, llm_config: Optional[dict] = None) else: # Fallback if LLM parsing fails logger.warning( - f"LLM classification parsing failed, using fallback for: {chunk_text}") + f"LLM classification parsing failed, using fallback for: {chunk_text}" + ) return _fallback_classify(chunk_text) except Exception as e: logger.error( - f"LLM classification failed: {e}, using fallback for: {chunk_text}") + f"LLM classification failed: {e}, using fallback for: {chunk_text}" + ) return _fallback_classify(chunk_text) @@ -100,7 +110,10 @@ def _parse_classification_response(response: str, chunk_text: str) -> Classifier parsed = extract_json_from_text(response) if parsed: # Validate required fields - if all(key in parsed for key in ["classification", "action", "confidence", "reason"]): + if all( + key in parsed + for key in ["classification", "action", "confidence", "reason"] + ): return { "chunk_text": chunk_text, "classification": IntentClassification(parsed["classification"]), @@ -108,8 +121,8 @@ def _parse_classification_response(response: str, chunk_text: str) -> Classifier "action": IntentAction(parsed["action"]), "metadata": { "confidence": float(parsed["confidence"]), - "reason": str(parsed["reason"]) - } + "reason": str(parsed["reason"]), + }, } # If JSON parsing fails, try manual parsing return _manual_parse_classification(response, chunk_text) @@ -133,10 +146,7 @@ def _manual_parse_classification(response: str, chunk_text: str) -> ClassifierOu "classification": IntentClassification(classification), "intent_type": intent_type, "action": IntentAction(action), - "metadata": { - "confidence": float(confidence), - "reason": str(reason) - } + "metadata": {"confidence": float(confidence), "reason": str(reason)}, } response_lower = response.lower() @@ -147,7 +157,7 @@ def _manual_parse_classification(response: str, chunk_text: str) -> ClassifierOu "classification": IntentClassification.ATOMIC, "intent_type": "ExampleIntentType", "action": IntentAction.HANDLE, - "metadata": {"confidence": 0.7, "reason": "Manually parsed as atomic"} + "metadata": {"confidence": 0.7, "reason": "Manually parsed as atomic"}, } elif "composite" in response_lower or "split" in response_lower: return { @@ -155,7 +165,7 @@ def _manual_parse_classification(response: str, chunk_text: str) -> ClassifierOu "classification": IntentClassification.COMPOSITE, "intent_type": None, "action": IntentAction.SPLIT, - "metadata": {"confidence": 0.7, "reason": "Manually parsed as composite"} + "metadata": {"confidence": 0.7, "reason": "Manually parsed as composite"}, } elif "ambiguous" in response_lower or "clarify" in response_lower: return { @@ -163,7 +173,7 @@ def _manual_parse_classification(response: str, chunk_text: str) -> ClassifierOu "classification": IntentClassification.AMBIGUOUS, "intent_type": None, "action": IntentAction.CLARIFY, - "metadata": {"confidence": 0.5, "reason": "Manually parsed as ambiguous"} + "metadata": {"confidence": 0.5, "reason": "Manually parsed as ambiguous"}, } else: return { @@ -171,7 +181,7 @@ def _manual_parse_classification(response: str, chunk_text: str) -> ClassifierOu "classification": IntentClassification.INVALID, "intent_type": None, "action": IntentAction.REJECT, - "metadata": {"confidence": 0.3, "reason": "Manually parsed as invalid"} + "metadata": {"confidence": 0.3, "reason": "Manually parsed as invalid"}, } @@ -184,22 +194,11 @@ def _fallback_classify(chunk_text: str) -> ClassifierOutput: "classification": IntentClassification.AMBIGUOUS, "intent_type": None, "action": IntentAction.CLARIFY, - "metadata": {"confidence": 0.4, "reason": "Too short to classify"} + "metadata": {"confidence": 0.4, "reason": "Too short to classify"}, } - # Only split on clear multi-intent patterns - multi_intent_patterns = [ - r'\band\b.*\band\b', # Multiple "and"s - r'[^,]*,[^,]*,[^,]*', # Multiple commas - r'first.*second', # Ordinal patterns - r'one.*two', # Number patterns - r'\band\b', # Single "and" between distinct actions - r'\bplus\b', # "plus" conjunction - r'\balso\b', # "also" conjunction - ] - # Check for single conjunctions that likely indicate multiple intents - single_conjunctions = [r'\band\b', r'\bplus\b', r'\balso\b'] + single_conjunctions = [r"\band\b", r"\bplus\b", r"\balso\b"] for pattern in single_conjunctions: if re.search(pattern, chunk_text, re.IGNORECASE): # Check if the parts around the conjunction look like separate actions @@ -207,15 +206,27 @@ def _fallback_classify(chunk_text: str) -> ClassifierOutput: if len(parts) == 2: part1, part2 = parts[0].strip(), parts[1].strip() # If both parts have action verbs, likely composite - action_verbs = ['cancel', 'book', 'update', - 'get', 'show', 'calculate', 'greet'] - if any(verb in part1.lower() for verb in action_verbs) and any(verb in part2.lower() for verb in action_verbs): + action_verbs = [ + "cancel", + "book", + "update", + "get", + "show", + "calculate", + "greet", + ] + if any(verb in part1.lower() for verb in action_verbs) and any( + verb in part2.lower() for verb in action_verbs + ): return { "chunk_text": chunk_text, "classification": IntentClassification.COMPOSITE, "intent_type": None, "action": IntentAction.SPLIT, - "metadata": {"confidence": 0.8, "reason": f"Detected multi-intent pattern with conjunction: {pattern}"} + "metadata": { + "confidence": 0.8, + "reason": f"Detected multi-intent pattern with conjunction: {pattern}", + }, } # Default to atomic @@ -224,5 +235,5 @@ def _fallback_classify(chunk_text: str) -> ClassifierOutput: "classification": IntentClassification.ATOMIC, "intent_type": "ExampleIntentType", "action": IntentAction.HANDLE, - "metadata": {"confidence": 0.9, "reason": "Single clear intent detected"} + "metadata": {"confidence": 0.9, "reason": "Single clear intent detected"}, } diff --git a/intent_kit/classifiers/keyword.py b/intent_kit/classifiers/keyword.py index eb3725b..8617e91 100644 --- a/intent_kit/classifiers/keyword.py +++ b/intent_kit/classifiers/keyword.py @@ -4,7 +4,9 @@ from ..node import TreeNode -def keyword_classifier(user_input: str, children: list[TreeNode], context: Optional[Dict[str, Any]] = None) -> Optional[TreeNode]: +def keyword_classifier( + user_input: str, children: list[TreeNode], context: Optional[Dict[str, Any]] = None +) -> Optional[TreeNode]: """ A simple classifier that selects the first child whose name appears in the user input. diff --git a/intent_kit/classifiers/llm_classifier.py b/intent_kit/classifiers/llm_classifier.py index 28527f4..b02a6e1 100644 --- a/intent_kit/classifiers/llm_classifier.py +++ b/intent_kit/classifiers/llm_classifier.py @@ -15,9 +15,7 @@ def create_llm_classifier( - llm_config: Dict[str, Any], - classification_prompt: str, - node_descriptions: List[str] + llm_config: Dict[str, Any], classification_prompt: str, node_descriptions: List[str] ) -> Callable[[str, List[TreeNode], Optional[Dict[str, Any]]], Optional[TreeNode]]: """ Create an LLM-powered classifier function. @@ -30,7 +28,12 @@ def create_llm_classifier( Returns: Classifier function that can be used with ClassifierNode """ - def llm_classifier(user_input: str, children: List[TreeNode], context: Optional[Dict[str, Any]] = None) -> Optional[TreeNode]: + + def llm_classifier( + user_input: str, + children: List[TreeNode], + context: Optional[Dict[str, Any]] = None, + ) -> Optional[TreeNode]: """ LLM-powered classifier that selects the most appropriate child node. @@ -54,12 +57,14 @@ def llm_classifier(user_input: str, children: List[TreeNode], context: Optional[ # Build the classification prompt prompt = classification_prompt.format( user_input=user_input, - node_descriptions="\n".join([ - f"{i+1}. {child.name}: {child.description}" - for i, child in enumerate(children) - ]), + node_descriptions="\n".join( + [ + f"{i+1}. {child.name}: {child.description}" + for i, child in enumerate(children) + ] + ), num_nodes=len(children), - context_info=context_info + context_info=context_info, ) # Get LLM response @@ -75,24 +80,25 @@ def llm_classifier(user_input: str, children: List[TreeNode], context: Optional[ # Make patterns more specific to avoid matching context numbers like years/timestamps number_patterns = [ # Match 1-2 digit numbers after "choice" - r'choice.*?(\d{1,2})', + r"choice.*?(\d{1,2})", # Match 1-2 digit numbers after "answer" - r'answer.*?(\d{1,2})', + r"answer.*?(\d{1,2})", # Match 1-2 digit numbers after "number" - r'number.*?(\d{1,2})', + r"number.*?(\d{1,2})", # Match 1-2 digit numbers after "select" - r'select.*?(\d{1,2})', + r"select.*?(\d{1,2})", # Match 1-2 digit numbers after "option" - r'option.*?(\d{1,2})', - r'^(\d{1,2})$', # Match standalone 1-2 digit numbers + r"option.*?(\d{1,2})", + r"^(\d{1,2})$", # Match standalone 1-2 digit numbers # Match 1-2 digit numbers with optional whitespace - r'^(\d{1,2})\s*$', + r"^(\d{1,2})\s*$", ] selected_index = None for pattern in number_patterns: - match = re.search(pattern, response_text, - re.IGNORECASE | re.MULTILINE) + match = re.search( + pattern, response_text, re.IGNORECASE | re.MULTILINE + ) if match: # Convert to 0-based selected_index = int(match.group(1)) - 1 @@ -101,7 +107,7 @@ def llm_classifier(user_input: str, children: List[TreeNode], context: Optional[ # If no pattern matched, try to parse the entire response as a number if selected_index is None: # Clean up the response text - remove markdown formatting, asterisks, etc. - cleaned_text = re.sub(r'[^\d]', '', response_text) + cleaned_text = re.sub(r"[^\d]", "", response_text) if cleaned_text: # Only take the first 1-2 digits to avoid long numbers like years first_digits = cleaned_text[:2] @@ -113,14 +119,17 @@ def llm_classifier(user_input: str, children: List[TreeNode], context: Optional[ return children[selected_index] else: logger.warning( - f"LLM returned invalid index: {selected_index} (valid range: 0-{len(children)-1})") + f"LLM returned invalid index: {selected_index} (valid range: 0-{len(children)-1})" + ) logger.warning( - f"Available children: {[child.name for child in children]}") + f"Available children: {[child.name for child in children]}" + ) logger.warning(f"Raw LLM response: {response_text}") return None except ValueError as e: logger.warning( - f"LLM response could not be parsed as integer: {response}") + f"LLM response could not be parsed as integer: {response}" + ) logger.warning(f"Parse error: {e}") return None @@ -132,9 +141,7 @@ def llm_classifier(user_input: str, children: List[TreeNode], context: Optional[ def create_llm_arg_extractor( - llm_config: Dict[str, Any], - extraction_prompt: str, - param_schema: Dict[str, Any] + llm_config: Dict[str, Any], extraction_prompt: str, param_schema: Dict[str, Any] ) -> Callable[[str, Optional[Dict[str, Any]]], Dict[str, Any]]: """ Create an LLM-powered argument extractor function. @@ -147,7 +154,10 @@ def create_llm_arg_extractor( Returns: Argument extractor function that can be used with HandlerNode """ - def llm_arg_extractor(user_input: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]: + + def llm_arg_extractor( + user_input: str, context: Optional[Dict[str, Any]] = None + ) -> Dict[str, Any]: """ LLM-powered argument extractor that extracts parameters from user input. @@ -168,16 +178,18 @@ def llm_arg_extractor(user_input: str, context: Optional[Dict[str, Any]] = None) context_info += "\nUse this context information to help extract more accurate parameters." # Build the extraction prompt - param_descriptions = "\n".join([ - f"- {param_name}: {param_type.__name__}" - for param_name, param_type in param_schema.items() - ]) + param_descriptions = "\n".join( + [ + f"- {param_name}: {param_type.__name__}" + for param_name, param_type in param_schema.items() + ] + ) prompt = extraction_prompt.format( user_input=user_input, param_descriptions=param_descriptions, param_names=", ".join(param_schema.keys()), - context_info=context_info + context_info=context_info, ) # Get LLM response @@ -194,11 +206,11 @@ def llm_arg_extractor(user_input: str, context: Optional[Dict[str, Any]] = None) extracted_params = {} # Simple parsing: look for "param_name: value" patterns - lines = response.strip().split('\n') + lines = response.strip().split("\n") for line in lines: line = line.strip() - if ':' in line: - key, value = line.split(':', 1) + if ":" in line: + key, value = line.split(":", 1) key = key.strip() value = value.strip() if key in param_schema: diff --git a/intent_kit/classifiers/node.py b/intent_kit/classifiers/node.py index 4b8dd3e..f6a89e2 100644 --- a/intent_kit/classifiers/node.py +++ b/intent_kit/classifiers/node.py @@ -1,10 +1,12 @@ from typing import Any, Callable, List, Optional, Dict, Union from intent_kit.node.base import TreeNode from intent_kit.node.enums import NodeType -from intent_kit.utils.logger import Logger from intent_kit.context import IntentContext from intent_kit.node.types import ExecutionResult, ExecutionError -from intent_kit.handlers.remediation import get_remediation_strategy, RemediationStrategy +from intent_kit.handlers.remediation import ( + get_remediation_strategy, + RemediationStrategy, +) class ClassifierNode(TreeNode): @@ -13,14 +15,17 @@ class ClassifierNode(TreeNode): def __init__( self, name: Optional[str], - classifier: Callable[[str, List["TreeNode"], Optional[Dict[str, Any]]], Optional["TreeNode"]], + classifier: Callable[ + [str, List["TreeNode"], Optional[Dict[str, Any]]], Optional["TreeNode"] + ], children: List["TreeNode"], description: str = "", parent: Optional["TreeNode"] = None, - remediation_strategies: Optional[List[Union[str, - RemediationStrategy]]] = None + remediation_strategies: Optional[List[Union[str, RemediationStrategy]]] = None, ): - super().__init__(name=name, description=description, children=children, parent=parent) + super().__init__( + name=name, description=description, children=children, parent=parent + ) self.classifier = classifier self.remediation_strategies = remediation_strategies or [] @@ -29,30 +34,27 @@ def node_type(self) -> NodeType: """Get the type of this node.""" return NodeType.CLASSIFIER - def execute(self, user_input: str, context: Optional[IntentContext] = None) -> ExecutionResult: - context_dict = None - if context: - # Only read context fields that are actually needed by the classifier - # For now, we'll pass an empty dict since most classifiers don't need context - # In the future, we could add context_inputs to ClassifierNode - context_dict = {} + def execute( + self, user_input: str, context: Optional[IntentContext] = None + ) -> ExecutionResult: + context_dict: Dict[str, Any] = {} + # If context is needed, populate context_dict here in the future chosen = self.classifier(user_input, self.children, context_dict) if not chosen: self.logger.error( - f"Classifier at '{self.name}' (Path: {'.'.join(self.get_path())}) could not route input.") + f"Classifier at '{self.name}' (Path: {'.'.join(self.get_path())}) could not route input." + ) # Try remediation strategies error = ExecutionError( error_type="ClassifierRoutingError", message=f"Classifier at '{self.name}' could not route input.", node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ) remediation_result = self._execute_remediation_strategies( - user_input=user_input, - context=context, - original_error=error + user_input=user_input, context=context, original_error=error ) if remediation_result: @@ -68,10 +70,11 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E output=None, error=error, params=None, - children_results=[] + children_results=[], ) self.logger.debug( - f"Classifier at '{self.name}' routed input to '{chosen.name}'.") + f"Classifier at '{self.name}' routed input to '{chosen.name}'." + ) child_result = chosen.execute(user_input, context) return ExecutionResult( success=True, @@ -83,16 +86,16 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error=None, params={ "chosen_child": chosen.name, - "available_children": [child.name for child in self.children] + "available_children": [child.name for child in self.children], }, - children_results=[child_result] + children_results=[child_result], ) def _execute_remediation_strategies( self, user_input: str, context: Optional[IntentContext] = None, - original_error: Optional[ExecutionError] = None + original_error: Optional[ExecutionError] = None, ) -> Optional[ExecutionResult]: """Execute remediation strategies for classifier failures.""" if not self.remediation_strategies: @@ -106,14 +109,16 @@ def _execute_remediation_strategies( strategy = get_remediation_strategy(strategy_item) if not strategy: self.logger.warning( - f"Remediation strategy '{strategy_item}' not found in registry") + f"Remediation strategy '{strategy_item}' not found in registry" + ) continue elif isinstance(strategy_item, RemediationStrategy): # Direct strategy object strategy = strategy_item else: self.logger.warning( - f"Invalid remediation strategy type: {type(strategy_item)}") + f"Invalid remediation strategy type: {type(strategy_item)}" + ) continue try: @@ -123,18 +128,21 @@ def _execute_remediation_strategies( context=context, original_error=original_error, classifier_func=self.classifier, - available_children=self.children + available_children=self.children, ) if result and result.success: self.logger.info( - f"Remediation strategy '{strategy.name}' succeeded for {self.name}") + f"Remediation strategy '{strategy.name}' succeeded for {self.name}" + ) return result else: self.logger.warning( - f"Remediation strategy '{strategy.name}' failed for {self.name}") + f"Remediation strategy '{strategy.name}' failed for {self.name}" + ) except Exception as e: self.logger.error( - f"Remediation strategy '{strategy.name}' error for {self.name}: {type(e).__name__}: {str(e)}") + f"Remediation strategy '{strategy.name}' error for {self.name}: {type(e).__name__}: {str(e)}" + ) self.logger.error(f"All remediation strategies failed for {self.name}") return None diff --git a/intent_kit/context/__init__.py b/intent_kit/context/__init__.py index 20ccfad..2bc5280 100644 --- a/intent_kit/context/__init__.py +++ b/intent_kit/context/__init__.py @@ -17,6 +17,7 @@ @dataclass class ContextField: """A lockable field in the context with metadata tracking.""" + value: Any lock: Lock = field(default_factory=Lock) last_modified: datetime = field(default_factory=datetime.now) @@ -27,6 +28,7 @@ class ContextField: @dataclass class ContextHistoryEntry: """An entry in the context history log.""" + timestamp: datetime action: str # 'set', 'get', 'delete' key: str @@ -38,6 +40,7 @@ class ContextHistoryEntry: @dataclass class ContextErrorEntry: """An error entry in the context error log.""" + timestamp: datetime node_name: str user_input: str @@ -78,7 +81,8 @@ def __init__(self, session_id: Optional[str] = None, debug: bool = False): if self._debug: self.logger.info( - f"Created IntentContext with session_id: {self.session_id}") + f"Created IntentContext with session_id: {self.session_id}" + ) def get(self, key: str, default: Any = None) -> Any: """ @@ -95,7 +99,8 @@ def get(self, key: str, default: Any = None) -> Any: if key not in self._fields: if self._debug: self.logger.debug( - f"Key '{key}' not found, returning default: {default}") + f"Key '{key}' not found, returning default: {default}" + ) self._log_history("get", key, default, None) return default field = self._fields[key] @@ -132,7 +137,8 @@ def set(self, key: str, value: Any, modified_by: Optional[str] = None) -> None: field.modified_by = modified_by if self._debug: self.logger.debug( - f"Updated field '{key}' from {old_value} to {value}") + f"Updated field '{key}' from {old_value} to {value}" + ) self._log_history("set", key, value, modified_by) @@ -150,8 +156,7 @@ def delete(self, key: str, modified_by: Optional[str] = None) -> bool: with self._global_lock: if key not in self._fields: if self._debug: - self.logger.debug( - f"Attempted to delete non-existent key '{key}'") + self.logger.debug(f"Attempted to delete non-existent key '{key}'") self._log_history("delete", key, None, modified_by) return False @@ -184,7 +189,9 @@ def keys(self) -> Set[str]: with self._global_lock: return set(self._fields.keys()) - def get_history(self, key: Optional[str] = None, limit: Optional[int] = None) -> List[ContextHistoryEntry]: + def get_history( + self, key: Optional[str] = None, limit: Optional[int] = None + ) -> List[ContextHistoryEntry]: """ Get the history of context operations. @@ -198,7 +205,8 @@ def get_history(self, key: Optional[str] = None, limit: Optional[int] = None) -> with self._global_lock: if key: filtered_history = [ - entry for entry in self._history if entry.key == key] + entry for entry in self._history if entry.key == key + ] else: filtered_history = self._history.copy() @@ -226,7 +234,7 @@ def get_field_metadata(self, key: str) -> Optional[Dict[str, Any]]: "created_at": field.created_at, "last_modified": field.last_modified, "modified_by": field.modified_by, - "value": field.value + "value": field.value, } def clear(self, modified_by: Optional[str] = None) -> None: @@ -243,7 +251,9 @@ def clear(self, modified_by: Optional[str] = None) -> None: self.logger.debug(f"Cleared all fields: {keys}") self._log_history("clear", "ALL", None, modified_by) - def _log_history(self, action: str, key: str, value: Any, modified_by: Optional[str]) -> None: + def _log_history( + self, action: str, key: str, value: Any, modified_by: Optional[str] + ) -> None: """Log an operation to the history.""" entry = ContextHistoryEntry( timestamp=datetime.now(), @@ -251,12 +261,18 @@ def _log_history(self, action: str, key: str, value: Any, modified_by: Optional[ key=key, value=value, modified_by=modified_by, - session_id=self.session_id + session_id=self.session_id, ) self._history.append(entry) - def add_error(self, node_name: str, user_input: str, - error_message: str, error_type: str, params: Optional[Dict[str, Any]] = None) -> None: + def add_error( + self, + node_name: str, + user_input: str, + error_message: str, + error_type: str, + params: Optional[Dict[str, Any]] = None, + ) -> None: """ Add an error to the context error log. @@ -276,16 +292,18 @@ def add_error(self, node_name: str, user_input: str, error_type=error_type, stack_trace=traceback.format_exc(), params=params, - session_id=self.session_id + session_id=self.session_id, ) self._errors.append(error_entry) if self._debug: self.logger.error( - f"Added error to context: {node_name}: {error_message}") + f"Added error to context: {node_name}: {error_message}" + ) - def get_errors(self, node_name: Optional[str] = None, - limit: Optional[int] = None) -> List[ContextErrorEntry]: + def get_errors( + self, node_name: Optional[str] = None, limit: Optional[int] = None + ) -> List[ContextErrorEntry]: """ Get errors from the context error log. @@ -301,7 +319,8 @@ def get_errors(self, node_name: Optional[str] = None, if node_name: filtered_errors = [ - error for error in filtered_errors if error.node_name == node_name] + error for error in filtered_errors if error.node_name == node_name + ] if limit: filtered_errors = filtered_errors[-limit:] diff --git a/intent_kit/context/debug.py b/intent_kit/context/debug.py index 12f74ea..3cde8ad 100644 --- a/intent_kit/context/debug.py +++ b/intent_kit/context/debug.py @@ -6,13 +6,14 @@ generating debug output, and visualizing context flow. """ -from typing import Dict, Any, Optional, List, Set, Tuple +from typing import Dict, Any, Optional, List, cast from datetime import datetime import json from . import IntentContext from .dependencies import ContextDependencies, analyze_handler_dependencies from intent_kit.node import TreeNode from intent_kit.utils.logger import Logger +from . import ContextHistoryEntry logger = Logger(__name__) @@ -45,30 +46,25 @@ def get_context_dependencies(graph: Any) -> Dict[str, ContextDependencies]: def validate_context_flow(graph: Any, context: IntentContext) -> Dict[str, Any]: """ - Check for missing dependencies and validate context flow. - - Args: - graph: IntentGraph instance to validate - context: Context object to validate against - - Returns: - Dictionary with validation results + Validate the context flow for a graph and context. """ dependencies = get_context_dependencies(graph) - validation_results = { + validation_results: Dict[str, Any] = { "valid": True, "missing_dependencies": {}, "available_fields": set(context.keys()), "total_nodes": len(dependencies), "nodes_with_dependencies": 0, - "warnings": [] + "warnings": [], } for node_name, deps in dependencies.items(): validation = _validate_node_dependencies(deps, context) if not validation["valid"]: validation_results["valid"] = False - validation_results["missing_dependencies"][node_name] = validation["missing_inputs"] + validation_results["missing_dependencies"][node_name] = validation[ + "missing_inputs" + ] if deps.inputs or deps.outputs: validation_results["nodes_with_dependencies"] += 1 @@ -76,8 +72,9 @@ def validate_context_flow(graph: Any, context: IntentContext) -> Dict[str, Any]: return validation_results -def trace_context_execution(graph: Any, user_input: str, context: IntentContext, - output_format: str = "console") -> str: +def trace_context_execution( + graph: Any, user_input: str, context: IntentContext, output_format: str = "console" +) -> str: """ Generate a detailed execution trace with context state changes. @@ -91,23 +88,38 @@ def trace_context_execution(graph: Any, user_input: str, context: IntentContext, Formatted execution trace """ # Capture history BEFORE we start reading context to avoid feedback loop - history_before_debug = context.get_history() + history_before_debug: List[ContextHistoryEntry] = context.get_history() # Capture context state without adding to history context_state = _capture_full_context_state(context) # Analyze history to get operation counts - set_ops = sum(1 for entry in history_before_debug if entry.action == "set") - get_ops = sum(1 for entry in history_before_debug if entry.action == "get") + set_ops = sum( + 1 + for entry in history_before_debug + if hasattr(entry, "action") and entry.action == "set" + ) + get_ops = sum( + 1 + for entry in history_before_debug + if hasattr(entry, "action") and entry.action == "get" + ) delete_ops = sum( - 1 for entry in history_before_debug if entry.action == "delete") - - context_state["history_summary"].update({ - "total_entries": len(history_before_debug), - "set_operations": set_ops, - "get_operations": get_ops, - "delete_operations": delete_ops - }) + 1 + for entry in history_before_debug + if hasattr(entry, "action") and entry.action == "delete" + ) + + # Cast to satisfy mypy + cast_dict = cast(Dict[str, Any], context_state["history_summary"]) + cast_dict.update( + { + "total_entries": len(history_before_debug), + "set_operations": set_ops, + "get_operations": get_ops, + "delete_operations": delete_ops, + } + ) trace_data = { "timestamp": datetime.now().isoformat(), @@ -116,10 +128,10 @@ def trace_context_execution(graph: Any, user_input: str, context: IntentContext, "execution_summary": { "total_fields": len(context.keys()), "history_entries": len(history_before_debug), - "error_count": context.error_count() + "error_count": context.error_count(), }, "context_state": context_state, - "history": _format_context_history(history_before_debug) + "history": _format_context_history(history_before_debug), } if output_format == "json": @@ -160,36 +172,36 @@ def _analyze_node_dependencies(node: TreeNode) -> Optional[ContextDependencies]: ContextDependencies if analysis is possible, None otherwise """ # Check if node has explicit dependencies - if hasattr(node, 'context_inputs') and hasattr(node, 'context_outputs'): - inputs = getattr(node, 'context_inputs', set()) - outputs = getattr(node, 'context_outputs', set()) + if hasattr(node, "context_inputs") and hasattr(node, "context_outputs"): + inputs: set = getattr(node, "context_inputs", set()) + outputs: set = getattr(node, "context_outputs", set()) return ContextDependencies( - inputs=inputs, - outputs=outputs, - description=f"Dependencies for {node.name}" + inputs=inputs, outputs=outputs, description=f"Dependencies for {node.name}" ) # Check if node has a handler function (HandlerNode) - if hasattr(node, 'handler'): - handler = getattr(node, 'handler') + if hasattr(node, "handler"): + handler = getattr(node, "handler") if callable(handler): return analyze_handler_dependencies(handler) # Check if node has a classifier function (ClassifierNode) - if hasattr(node, 'classifier'): - classifier = getattr(node, 'classifier') + if hasattr(node, "classifier"): + classifier = getattr(node, "classifier") if callable(classifier): # Classifiers typically don't modify context, but they might read from it return ContextDependencies( inputs=set(), outputs=set(), - description=f"Classifier {node.name} (no context dependencies detected)" + description=f"Classifier {node.name} (no context dependencies detected)", ) return None -def _validate_node_dependencies(deps: ContextDependencies, context: IntentContext) -> Dict[str, Any]: +def _validate_node_dependencies( + deps: ContextDependencies, context: IntentContext +) -> Dict[str, Any]: """ Validate dependencies for a specific node against a context. @@ -207,7 +219,7 @@ def _validate_node_dependencies(deps: ContextDependencies, context: IntentContex "valid": len(missing_inputs) == 0, "missing_inputs": missing_inputs, "available_inputs": deps.inputs & available_fields, - "outputs": deps.outputs + "outputs": deps.outputs, } @@ -221,7 +233,7 @@ def _capture_full_context_state(context: IntentContext) -> Dict[str, Any]: Returns: Dictionary with complete context state """ - state = { + state: Dict[str, Any] = { "session_id": context.session_id, "field_count": len(context.keys()), "fields": {}, @@ -229,13 +241,11 @@ def _capture_full_context_state(context: IntentContext) -> Dict[str, Any]: "total_entries": 0, # Will be set by caller "set_operations": 0, "get_operations": 0, - "delete_operations": 0 + "delete_operations": 0, }, - "error_summary": { - "total_errors": context.error_count(), - "recent_errors": [] - } + "error_summary": {"total_errors": context.error_count(), "recent_errors": []}, } + fields: Dict[str, Any] = state["fields"] # Capture all field values and metadata directly from internal state # to avoid adding GET operations to history @@ -246,12 +256,9 @@ def _capture_full_context_state(context: IntentContext) -> Dict[str, Any]: metadata = { "created_at": field.created_at.isoformat(), "last_modified": field.last_modified.isoformat(), - "modified_by": field.modified_by - } - state["fields"][key] = { - "value": value, - "metadata": metadata + "modified_by": field.modified_by, } + fields[key] = {"value": value, "metadata": metadata} # Get recent errors errors = context.get_errors(limit=5) @@ -260,7 +267,7 @@ def _capture_full_context_state(context: IntentContext) -> Dict[str, Any]: "timestamp": error.timestamp.isoformat(), "node_name": error.node_name, "error_message": error.error_message, - "error_type": error.error_type + "error_type": error.error_type, } for error in errors ] @@ -280,13 +287,15 @@ def _format_context_history(history: List[Any]) -> List[Dict[str, Any]]: """ formatted = [] for entry in history: - formatted.append({ - "timestamp": entry.timestamp.isoformat(), - "action": entry.action, - "key": entry.key, - "value": entry.value, - "modified_by": entry.modified_by - }) + formatted.append( + { + "timestamp": entry.timestamp.isoformat(), + "action": entry.action, + "key": entry.key, + "value": entry.value, + "modified_by": entry.modified_by, + } + ) return formatted @@ -304,23 +313,41 @@ def _format_console_trace(trace_data: Dict[str, Any]) -> str: lines.append(logger.colorize_separator("=" * 60)) lines.append(logger.colorize_section_title("CONTEXT EXECUTION TRACE")) lines.append(logger.colorize_separator("=" * 60)) - lines.append(logger.colorize_key_value( - "Timestamp", trace_data['timestamp'], "field_label", "timestamp")) - lines.append(logger.colorize_key_value( - "User Input", trace_data['user_input'], "field_label", "field_value")) - lines.append(logger.colorize_key_value( - "Session ID", trace_data['session_id'], "field_label", "timestamp")) + lines.append( + logger.colorize_key_value( + "Timestamp", trace_data["timestamp"], "field_label", "timestamp" + ) + ) + lines.append( + logger.colorize_key_value( + "User Input", trace_data["user_input"], "field_label", "field_value" + ) + ) + lines.append( + logger.colorize_key_value( + "Session ID", trace_data["session_id"], "field_label", "timestamp" + ) + ) lines.append("") # Execution summary summary = trace_data["execution_summary"] lines.append(logger.colorize_section_title("EXECUTION SUMMARY:")) - lines.append(logger.colorize_key_value(" Total Fields", - summary['total_fields'], "field_label", "timestamp")) - lines.append(logger.colorize_key_value(" History Entries", - summary['history_entries'], "field_label", "timestamp")) - lines.append(logger.colorize_key_value(" Error Count", - summary['error_count'], "field_label", "timestamp")) + lines.append( + logger.colorize_key_value( + " Total Fields", summary["total_fields"], "field_label", "timestamp" + ) + ) + lines.append( + logger.colorize_key_value( + " History Entries", summary["history_entries"], "field_label", "timestamp" + ) + ) + lines.append( + logger.colorize_key_value( + " Error Count", summary["error_count"], "field_label", "timestamp" + ) + ) lines.append("") # Context state @@ -332,30 +359,66 @@ def _format_console_trace(trace_data: Dict[str, Any]) -> str: # Format complex values more clearly if isinstance(value, list): - lines.append(logger.colorize_key_value( - f" {key}", f"(list with {len(value)} items)", "field_label", "timestamp")) + lines.append( + logger.colorize_key_value( + f" {key}", + f"(list with {len(value)} items)", + "field_label", + "timestamp", + ) + ) for i, item in enumerate(value): if isinstance(item, dict): - lines.append(logger.colorize_key_value( - f" [{i}]", dict(item), "field_label", "field_value")) + lines.append( + logger.colorize_key_value( + f" [{i}]", dict(item), "field_label", "field_value" + ) + ) else: - lines.append(logger.colorize_key_value( - f" [{i}]", item, "field_label", "field_value")) + lines.append( + logger.colorize_key_value( + f" [{i}]", item, "field_label", "field_value" + ) + ) elif isinstance(value, dict): - lines.append(logger.colorize_key_value( - f" {key}", f"(dict with {len(value)} items)", "field_label", "timestamp")) + lines.append( + logger.colorize_key_value( + f" {key}", + f"(dict with {len(value)} items)", + "field_label", + "timestamp", + ) + ) for k, v in value.items(): - lines.append(logger.colorize_key_value( - f" {k}", v, "field_label", "field_value")) + lines.append( + logger.colorize_key_value( + f" {k}", v, "field_label", "field_value" + ) + ) else: - lines.append(logger.colorize_key_value( - f" {key}", value, "field_label", "field_value")) + lines.append( + logger.colorize_key_value( + f" {key}", value, "field_label", "field_value" + ) + ) if metadata: - lines.append(logger.colorize_key_value(" Modified", metadata.get( - 'last_modified', 'Unknown'), "field_label", "timestamp")) - lines.append(logger.colorize_key_value( - " By", metadata.get('modified_by', 'Unknown'), "field_label", "timestamp")) + lines.append( + logger.colorize_key_value( + " Modified", + metadata.get("last_modified", "Unknown"), + "field_label", + "timestamp", + ) + ) + lines.append( + logger.colorize_key_value( + " By", + metadata.get("modified_by", "Unknown"), + "field_label", + "timestamp", + ) + ) lines.append("") # Recent history @@ -363,10 +426,10 @@ def _format_console_trace(trace_data: Dict[str, Any]) -> str: if history: lines.append(logger.colorize_section_title("RECENT HISTORY:")) for entry in history[-10:]: # Last 10 entries - timestamp = logger.colorize_timestamp(entry['timestamp']) - action = logger.colorize_action(entry['action'].upper()) - key = logger.colorize_field_label(entry['key']) - value = logger.colorize_field_value(str(entry['value'])) + timestamp = logger.colorize_timestamp(entry["timestamp"]) + action = logger.colorize_action(entry["action"].upper()) + key = logger.colorize_field_label(entry["key"]) + value = logger.colorize_field_value(str(entry["value"])) lines.append(f" [{timestamp}] {action}: {key} = {value}") lines.append("") @@ -375,9 +438,9 @@ def _format_console_trace(trace_data: Dict[str, Any]) -> str: if errors: lines.append(logger.colorize_section_title("RECENT ERRORS:")) for error in errors: - timestamp = logger.colorize_timestamp(error['timestamp']) - node_name = logger.colorize_error_soft(error['node_name']) - error_msg = logger.colorize_error_soft(error['error_message']) + timestamp = logger.colorize_timestamp(error["timestamp"]) + node_name = logger.colorize_error_soft(error["node_name"]) + error_msg = logger.colorize_error_soft(error["error_message"]) lines.append(f" [{timestamp}] {node_name}: {error_msg}") lines.append("") diff --git a/intent_kit/context/dependencies.py b/intent_kit/context/dependencies.py index c25e248..777ad31 100644 --- a/intent_kit/context/dependencies.py +++ b/intent_kit/context/dependencies.py @@ -13,6 +13,7 @@ @dataclass class ContextDependencies: """Declares what context fields an intent reads and writes.""" + inputs: Set[str] # Fields this intent reads from context outputs: Set[str] # Fields this intent writes to context description: str = "" # Human-readable description of dependencies @@ -31,7 +32,9 @@ def __call__(self, context: IntentContext, **kwargs) -> Any: ... -def declare_dependencies(inputs: Set[str], outputs: Set[str], description: str = "") -> ContextDependencies: +def declare_dependencies( + inputs: Set[str], outputs: Set[str], description: str = "" +) -> ContextDependencies: """ Create a context dependency declaration. @@ -43,17 +46,11 @@ def declare_dependencies(inputs: Set[str], outputs: Set[str], description: str = Returns: ContextDependencies object """ - return ContextDependencies( - inputs=inputs, - outputs=outputs, - description=description - ) + return ContextDependencies(inputs=inputs, outputs=outputs, description=description) def validate_context_dependencies( - dependencies: ContextDependencies, - context: IntentContext, - strict: bool = False + dependencies: ContextDependencies, context: IntentContext, strict: bool = False ) -> Dict[str, Any]: """ Validate that required context fields are available. @@ -71,22 +68,21 @@ def validate_context_dependencies( - warnings: List[str] """ available_fields = context.keys() - missing_inputs = dependencies.inputs - available_fields - available_inputs = dependencies.inputs & available_fields + missing_inputs: set = dependencies.inputs - available_fields + available_inputs: set = dependencies.inputs & available_fields warnings = [] if missing_inputs and strict: warnings.append(f"Missing required context inputs: {missing_inputs}") if missing_inputs and not strict: - warnings.append( - f"Optional context inputs not available: {missing_inputs}") + warnings.append(f"Optional context inputs not available: {missing_inputs}") return { "valid": len(missing_inputs) == 0 or not strict, "missing_inputs": missing_inputs, "available_inputs": available_inputs, - "warnings": warnings + "warnings": warnings, } @@ -103,9 +99,9 @@ def merge_dependencies(*dependencies: ContextDependencies) -> ContextDependencie if not dependencies: return declare_dependencies(set(), set(), "Empty dependencies") - merged_inputs = set() - merged_outputs = set() - descriptions = [] + merged_inputs: set = set() + merged_outputs: set = set() + descriptions: list = [] for dep in dependencies: merged_inputs.update(dep.inputs) @@ -119,7 +115,7 @@ def merge_dependencies(*dependencies: ContextDependencies) -> ContextDependencie return ContextDependencies( inputs=merged_inputs, outputs=merged_outputs, - description="; ".join(descriptions) if descriptions else "" + description="; ".join(descriptions) if descriptions else "", ) @@ -140,35 +136,37 @@ def analyze_handler_dependencies(handler: Any) -> Optional[ContextDependencies]: return None # Check if handler has explicit dependencies - if hasattr(handler, 'context_dependencies'): + if hasattr(handler, "context_dependencies"): return handler.context_dependencies # Check if handler has dependency annotations - if hasattr(handler, '__annotations__'): + if hasattr(handler, "__annotations__"): annotations = handler.__annotations__ - if 'context_inputs' in annotations and 'context_outputs' in annotations: - inputs = getattr(handler, 'context_inputs', set()) - outputs = getattr(handler, 'context_outputs', set()) + if "context_inputs" in annotations and "context_outputs" in annotations: + inputs: set = getattr(handler, "context_inputs", set()) + outputs: set = getattr(handler, "context_outputs", set()) return declare_dependencies(inputs, outputs) # Check docstring for dependency hints - if hasattr(handler, '__doc__') and handler.__doc__: + if hasattr(handler, "__doc__") and handler.__doc__: doc = handler.__doc__.lower() inputs = set() outputs = set() # Simple pattern matching for common phrases - if 'context' in doc: - if 'read' in doc or 'get' in doc: + if "context" in doc: + if "read" in doc or "get" in doc: # This is a heuristic - in practice, explicit declarations are better pass - if 'write' in doc or 'set' in doc or 'update' in doc: + if "write" in doc or "set" in doc or "update" in doc: pass return None -def create_dependency_graph(nodes: Dict[str, ContextDependencies]) -> Dict[str, Set[str]]: +def create_dependency_graph( + nodes: Dict[str, ContextDependencies], +) -> Dict[str, Set[str]]: """ Create a dependency graph from node dependencies. @@ -178,7 +176,7 @@ def create_dependency_graph(nodes: Dict[str, ContextDependencies]) -> Dict[str, Returns: Dict mapping node names to sets of dependent nodes """ - graph = {} + graph: Dict[str, Set[str]] = {} for node_name, deps in nodes.items(): graph[node_name] = set() diff --git a/intent_kit/evals/__init__.py b/intent_kit/evals/__init__.py index b719307..29d34e7 100644 --- a/intent_kit/evals/__init__.py +++ b/intent_kit/evals/__init__.py @@ -17,6 +17,7 @@ @dataclass class EvalTestCase: """A single test case with input, expected output, and optional context.""" + input: str expected: Any context: Dict[str, Any] @@ -29,6 +30,7 @@ def __post_init__(self): @dataclass class Dataset: """A dataset containing test cases for evaluating a node.""" + name: str description: str node_type: str @@ -43,6 +45,7 @@ def __post_init__(self): @dataclass class EvalTestResult: """Result of a single test case evaluation.""" + input: str expected: Any actual: Any @@ -85,11 +88,12 @@ def errors(self) -> List[EvalTestResult]: def print_summary(self) -> None: print(f"\nEvaluation Results for {self.dataset_name or 'Dataset'}:") print( - f" Accuracy: {self.accuracy():.1%} ({self.passed_count()}/{self.total_count()})") + f" Accuracy: {self.accuracy():.1%} ({self.passed_count()}/{self.total_count()})" + ) print(f" Passed: {self.passed_count()}") print(f" Failed: {self.failed_count()}") if self.errors(): - print(f"\nFailed Tests:") + print("\nFailed Tests:") for i, error in enumerate(self.errors()[:5]): print(f" {i+1}. Input: '{error.input}'") print(f" Expected: '{error.expected}'") @@ -105,21 +109,25 @@ def save_csv(self, path: Optional[str] = None) -> str: results_dir = Path(__file__).parent / "results" / "latest" results_dir.mkdir(parents=True, exist_ok=True) timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") - path = str(results_dir / - f"{self.dataset_name}_eval_results_{timestamp}.csv") - with open(path, 'w', newline='', encoding='utf-8') as f: + path = str( + results_dir / f"{self.dataset_name}_eval_results_{timestamp}.csv" + ) + with open(path, "w", newline="", encoding="utf-8") as f: writer = csv.writer(f) - writer.writerow(['input', 'expected', 'actual', - 'passed', 'error', 'context']) + writer.writerow( + ["input", "expected", "actual", "passed", "error", "context"] + ) for result in self.results: - writer.writerow([ - result.input, - result.expected, - result.actual, - result.passed, - result.error or '', - str(result.context) - ]) + writer.writerow( + [ + result.input, + result.expected, + result.actual, + result.passed, + result.error or "", + str(result.context), + ] + ) return str(path) def save_json(self, path: Optional[str] = None) -> str: @@ -127,30 +135,32 @@ def save_json(self, path: Optional[str] = None) -> str: results_dir = Path(__file__).parent / "results" / "latest" results_dir.mkdir(parents=True, exist_ok=True) timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") - path = str(results_dir / - f"{self.dataset_name}_eval_results_{timestamp}.json") + path = str( + results_dir / f"{self.dataset_name}_eval_results_{timestamp}.json" + ) import json + data = { - 'dataset_name': self.dataset_name, - 'summary': { - 'accuracy': self.accuracy(), - 'passed_count': self.passed_count(), - 'failed_count': self.failed_count(), - 'total_count': self.total_count() + "dataset_name": self.dataset_name, + "summary": { + "accuracy": self.accuracy(), + "passed_count": self.passed_count(), + "failed_count": self.failed_count(), + "total_count": self.total_count(), }, - 'results': [ + "results": [ { - 'input': r.input, - 'expected': r.expected, - 'actual': r.actual, - 'passed': r.passed, - 'error': r.error, - 'context': r.context + "input": r.input, + "expected": r.expected, + "actual": r.actual, + "passed": r.passed, + "error": r.error, + "context": r.context, } for r in self.results - ] + ], } - with open(path, 'w') as f: + with open(path, "w") as f: json.dump(data, f, indent=2) return str(path) @@ -159,8 +169,7 @@ def save_markdown(self, path: Optional[str] = None) -> str: reports_dir = Path(__file__).parent / "reports" / "latest" reports_dir.mkdir(parents=True, exist_ok=True) timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") - path = str(reports_dir / - f"{self.dataset_name}_eval_report_{timestamp}.md") + path = str(reports_dir / f"{self.dataset_name}_eval_report_{timestamp}.md") report = f"""# Evaluation Report: {self.dataset_name} **Generated:** {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} @@ -189,7 +198,7 @@ def save_markdown(self, path: Optional[str] = None) -> str: if error.error: report += f"- **Error:** {error.error}\n" report += "\n" - with open(path, 'w') as f: + with open(path, "w") as f: f.write(report) return str(path) @@ -198,37 +207,35 @@ def load_dataset(path: Union[str, Path]) -> Dataset: path = Path(path) if not path.exists(): raise FileNotFoundError(f"Dataset file not found: {path}") - with open(path, 'r') as f: + with open(path, "r") as f: data = yaml.safe_load(f) - if 'dataset' not in data: + if "dataset" not in data: raise ValueError(f"Dataset file missing 'dataset' section: {path}") - dataset_info = data['dataset'] - required_fields = ['name', 'node_type', 'node_name'] + dataset_info = data["dataset"] + required_fields = ["name", "node_type", "node_name"] for field in required_fields: if field not in dataset_info: - raise ValueError( - f"Dataset missing required field '{field}': {path}") - if 'test_cases' not in data: + raise ValueError(f"Dataset missing required field '{field}': {path}") + if "test_cases" not in data: raise ValueError(f"Dataset file missing 'test_cases' section: {path}") test_cases = [] - for i, tc_data in enumerate(data['test_cases']): - if 'input' not in tc_data: + for i, tc_data in enumerate(data["test_cases"]): + if "input" not in tc_data: raise ValueError(f"Test case {i+1} missing 'input' field: {path}") - if 'expected' not in tc_data: - raise ValueError( - f"Test case {i+1} missing 'expected' field: {path}") + if "expected" not in tc_data: + raise ValueError(f"Test case {i+1} missing 'expected' field: {path}") test_case = EvalTestCase( - input=tc_data['input'], - expected=tc_data['expected'], - context=tc_data.get('context', {}) + input=tc_data["input"], + expected=tc_data["expected"], + context=tc_data.get("context", {}), ) test_cases.append(test_case) return Dataset( - name=dataset_info['name'], - description=dataset_info.get('description', ''), - node_type=dataset_info['node_type'], - node_name=dataset_info['node_name'], - test_cases=test_cases + name=dataset_info["name"], + description=dataset_info.get("description", ""), + node_type=dataset_info["node_type"], + node_name=dataset_info["node_name"], + test_cases=test_cases, ) @@ -245,19 +252,22 @@ def run_eval( dataset: Dataset, node: Any, comparator: Optional[Callable[[Any, Any], bool]] = None, - fail_fast: bool = False + fail_fast: bool = False, ) -> EvalResult: if comparator is None: + def default_comparator(expected, actual): return expected == actual + comparator = default_comparator results = [] for test_case in dataset.test_cases: try: if callable(node): actual = node(test_case.input, context=test_case.context) - elif hasattr(node, 'execute'): + elif hasattr(node, "execute"): from intent_kit.context import IntentContext + context = IntentContext() for key, value in test_case.context.items(): context.set(key, value, modified_by="eval") @@ -266,15 +276,14 @@ def default_comparator(expected, actual): if not result.success and result.error: raise Exception(result.error.message) else: - raise ValueError( - "Node must be callable or have an .execute() method") + raise ValueError("Node must be callable or have an .execute() method") passed = comparator(test_case.expected, actual) result = EvalTestResult( input=test_case.input, expected=test_case.expected, actual=actual, passed=passed, - context=test_case.context + context=test_case.context, ) except Exception as e: result = EvalTestResult( @@ -283,7 +292,7 @@ def default_comparator(expected, actual): actual=None, passed=False, context=test_case.context, - error=str(e) + error=str(e), ) if fail_fast: results.append(result) @@ -296,7 +305,7 @@ def run_eval_from_path( dataset_path: Union[str, Path], node: Any, comparator: Optional[Callable[[Any, Any], bool]] = None, - fail_fast: bool = False + fail_fast: bool = False, ) -> EvalResult: dataset = load_dataset(dataset_path) return run_eval(dataset, node, comparator, fail_fast) @@ -307,7 +316,7 @@ def run_eval_from_module( module_name: str, node_name: str, comparator: Optional[Callable[[Any, Any], bool]] = None, - fail_fast: bool = False + fail_fast: bool = False, ) -> EvalResult: dataset = load_dataset(dataset_path) node = get_node_from_module(module_name, node_name) @@ -326,5 +335,5 @@ def run_eval_from_module( "get_node_from_module", "run_eval", "run_eval_from_path", - "run_eval_from_module" + "run_eval_from_module", ] diff --git a/intent_kit/evals/run_all_evals.py b/intent_kit/evals/run_all_evals.py index 4aa20e4..7ad9359 100644 --- a/intent_kit/evals/run_all_evals.py +++ b/intent_kit/evals/run_all_evals.py @@ -5,13 +5,18 @@ Run evaluations on all datasets and generate comprehensive markdown reports. """ -from intent_kit.evals.run_node_eval import load_dataset, get_node_from_module, evaluate_node, generate_markdown_report +from intent_kit.evals.run_node_eval import ( + load_dataset, + get_node_from_module, + evaluate_node, + generate_markdown_report, +) import yaml from typing import Dict, List, Any, Optional from datetime import datetime -import sys import pathlib from dotenv import load_dotenv + load_dotenv() @@ -20,16 +25,24 @@ def run_all_evaluations(): import argparse parser = argparse.ArgumentParser( - description="Run all evaluations and generate comprehensive report") - parser.add_argument("--output", type=str, default="intent_kit/evals/reports/latest/comprehensive_report.md", - help="Output file for comprehensive report") - parser.add_argument("--individual", action="store_true", - help="Also generate individual reports for each dataset") - parser.add_argument("--quiet", action="store_true", - help="Suppress output messages") + description="Run all evaluations and generate comprehensive report" + ) + parser.add_argument( + "--output", + type=str, + default="intent_kit/evals/reports/latest/comprehensive_report.md", + help="Output file for comprehensive report", + ) + parser.add_argument( + "--individual", + action="store_true", + help="Also generate individual reports for each dataset", + ) + parser.add_argument("--quiet", action="store_true", help="Suppress output messages") parser.add_argument("--llm-config", help="Path to LLM configuration file") - parser.add_argument("--mock", action="store_true", - help="Run in mock mode without real API calls") + parser.add_argument( + "--mock", action="store_true", help="Run in mock mode without real API calls" + ) # Parse args if called as script, otherwise use defaults try: @@ -54,40 +67,49 @@ def run_all_evaluations(): if not args.quiet: mode = "MOCK" if args.mock else "LIVE" print(f"Running all evaluations in {mode} mode...") - results = run_all_evaluations_internal( - args.llm_config, mock_mode=args.mock) + results = run_all_evaluations_internal(args.llm_config, mock_mode=args.mock) if not args.quiet: print("Generating comprehensive report...") - report = generate_comprehensive_report( - results, str(output_path), run_timestamp=run_timestamp, mock_mode=args.mock) + generate_comprehensive_report( + results, str(output_path), run_timestamp=run_timestamp, mock_mode=args.mock + ) # Also write timestamped copy to date-based archive directory - date_comprehensive_report_path = date_reports_dir / \ - f"comprehensive_report_{run_timestamp}.md" - with open(output_path, 'r') as src, open(date_comprehensive_report_path, 'w') as dst: + date_comprehensive_report_path = ( + date_reports_dir / f"comprehensive_report_{run_timestamp}.md" + ) + with ( + open(output_path, "r") as src, + open(date_comprehensive_report_path, "w") as dst, + ): dst.write(src.read()) if not args.quiet: - print( - f"Comprehensive report archived as: {date_comprehensive_report_path}") + print(f"Comprehensive report archived as: {date_comprehensive_report_path}") if args.individual: if not args.quiet: print("Generating individual reports...") for result in results: - dataset_name = result['dataset'] + dataset_name = result["dataset"] individual_report_path = reports_dir / f"{dataset_name}_report.md" # Write to latest generate_markdown_report( - [result], individual_report_path, run_timestamp=run_timestamp) + [result], individual_report_path, run_timestamp=run_timestamp + ) # Also write to date-based archive with timestamp in filename - date_individual_report_path = date_reports_dir / \ - f"{dataset_name}_report_{run_timestamp}.md" - with open(individual_report_path, 'r') as src, open(date_individual_report_path, 'w') as dst: + date_individual_report_path = ( + date_reports_dir / f"{dataset_name}_report_{run_timestamp}.md" + ) + with ( + open(individual_report_path, "r") as src, + open(date_individual_report_path, "w") as dst, + ): dst.write(src.read()) if not args.quiet: print( - f"Individual report written to: {individual_report_path} and archived as {date_individual_report_path}") + f"Individual report written to: {individual_report_path} and archived as {date_individual_report_path}" + ) if not args.quiet: print("Evaluation complete!") @@ -95,7 +117,9 @@ def run_all_evaluations(): return True -def run_all_evaluations_internal(llm_config_path: Optional[str] = None, mock_mode: bool = False) -> List[Dict[str, Any]]: +def run_all_evaluations_internal( + llm_config_path: Optional[str] = None, mock_mode: bool = False +) -> List[Dict[str, Any]]: """Run evaluations on all datasets and return results.""" dataset_dir = pathlib.Path(__file__).parent / "datasets" results = [] @@ -103,7 +127,8 @@ def run_all_evaluations_internal(llm_config_path: Optional[str] = None, mock_mod # Load LLM configuration if provided if llm_config_path: import os - with open(llm_config_path, 'r') as f: + + with open(llm_config_path, "r") as f: llm_config = yaml.safe_load(f) # Set environment variables for API keys @@ -116,6 +141,7 @@ def run_all_evaluations_internal(llm_config_path: Optional[str] = None, mock_mod # Set mock mode environment variable if mock_mode: import os + os.environ["INTENT_KIT_MOCK_MODE"] = "1" print("Running in MOCK mode - using simulated responses") @@ -129,9 +155,13 @@ def run_all_evaluations_internal(llm_config_path: Optional[str] = None, mock_mod # Determine module name based on node name if "llm" in node_name: - module_name = f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node_llm" + module_name = ( + f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node_llm" + ) else: - module_name = f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node" + module_name = ( + f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node" + ) # Load node node = get_node_from_module(module_name, node_name) @@ -148,12 +178,18 @@ def run_all_evaluations_internal(llm_config_path: Optional[str] = None, mock_mod accuracy = result["accuracy"] mode_indicator = "[MOCK]" if mock_mode else "" print( - f" Accuracy: {accuracy:.1%} ({result['correct']}/{result['total_cases']}) {mode_indicator}") + f" Accuracy: {accuracy:.1%} ({result['correct']}/{result['total_cases']}) {mode_indicator}" + ) return results -def generate_comprehensive_report(results: List[Dict[str, Any]], output_file: Optional[str] = None, run_timestamp: str = "", mock_mode: bool = False) -> str: +def generate_comprehensive_report( + results: List[Dict[str, Any]], + output_file: Optional[str] = None, + run_timestamp: str = "", + mock_mode: bool = False, +) -> str: """Generate a comprehensive markdown report for all evaluations.""" total_datasets = len(results) @@ -162,8 +198,7 @@ def generate_comprehensive_report(results: List[Dict[str, Any]], output_file: Op overall_accuracy = total_passed / total_tests if total_tests > 0 else 0.0 # Count statuses - passed_datasets = sum( - 1 for r in results if r["accuracy"] >= 0.8) # 80% threshold + passed_datasets = sum(1 for r in results if r["accuracy"] >= 0.8) # 80% threshold failed_datasets = total_datasets - passed_datasets # Add mock mode indicator @@ -207,7 +242,9 @@ def generate_comprehensive_report(results: List[Dict[str, Any]], output_file: Op for result in results: report += f"### {result['dataset']}\n\n" report += f"**Accuracy:** {result['accuracy']:.1%} ({result['correct']}/{result['total_cases']}) \n" - report += f"**Status:** {'PASSED' if result['accuracy'] >= 0.8 else 'FAILED'}\n\n" + report += ( + f"**Status:** {'PASSED' if result['accuracy'] >= 0.8 else 'FAILED'}\n\n" + ) # Show errors if any if result["errors"]: @@ -216,7 +253,7 @@ def generate_comprehensive_report(results: List[Dict[str, Any]], output_file: Op report += f"- **Case {error['case']}**: {error['input']}\n" report += f" - Expected: `{error['expected']}`\n" report += f" - Actual: `{error['actual']}`\n" - if error.get('error'): + if error.get("error"): report += f" - Error: {error['error']}\n" report += "\n" if len(result["errors"]) > 5: @@ -224,7 +261,7 @@ def generate_comprehensive_report(results: List[Dict[str, Any]], output_file: Op # Write to file if specified if output_file: - with open(output_file, 'w') as f: + with open(output_file, "w") as f: f.write(report) print(f"Comprehensive report written to: {output_file}") diff --git a/intent_kit/evals/run_node_eval.py b/intent_kit/evals/run_node_eval.py index f6dd9ea..9e072c6 100644 --- a/intent_kit/evals/run_node_eval.py +++ b/intent_kit/evals/run_node_eval.py @@ -5,7 +5,6 @@ Run evaluations on sample nodes using datasets. """ -from intent_kit.node.types import ExecutionResult from intent_kit.context import IntentContext from typing import Dict, Any, List, Optional from pathlib import Path @@ -15,10 +14,8 @@ import importlib import argparse from dotenv import load_dotenv -import json import csv from datetime import datetime -import uuid # Add text similarity imports from difflib import SequenceMatcher @@ -26,10 +23,12 @@ load_dotenv() +_first_test_case: dict = {} + def load_dataset(dataset_path: Path) -> Dict[str, Any]: """Load a dataset from YAML file.""" - with open(dataset_path, 'r') as f: + with open(dataset_path, "r") as f: return yaml.safe_load(f) @@ -43,7 +42,15 @@ def get_node_from_module(module_name: str, node_name: str): return None -def save_raw_results_to_csv(dataset_name: str, test_case: Dict[str, Any], actual_output: Any, success: bool, error: Optional[str] = None, similarity_score: Optional[float] = None, run_timestamp: Optional[str] = None): +def save_raw_results_to_csv( + dataset_name: str, + test_case: Dict[str, Any], + actual_output: Any, + success: bool, + error: Optional[str] = None, + similarity_score: Optional[float] = None, + run_timestamp: Optional[str] = None, +): """Save raw evaluation results to CSV files.""" # Create organized results directory structure today = datetime.now().strftime("%Y-%m-%d") @@ -64,24 +71,21 @@ def save_raw_results_to_csv(dataset_name: str, test_case: Dict[str, Any], actual # Prepare row data row_data = { - "timestamp": importlib.import_module('datetime').datetime.now().isoformat(), + "timestamp": importlib.import_module("datetime").datetime.now().isoformat(), "input": test_case["input"], "expected": test_case["expected"], "actual": actual_output, "success": success, "similarity_score": similarity_score or "", "error": error or "", - "context": str(test_case.get("context", {})) + "context": str(test_case.get("context", {})), } # Check if this is the first test case (to write header) global _first_test_case - if not hasattr(save_raw_results_to_csv, '_first_test_case'): - save_raw_results_to_csv._first_test_case = {} - - is_first = dataset_name not in save_raw_results_to_csv._first_test_case + is_first = dataset_name not in _first_test_case if is_first: - save_raw_results_to_csv._first_test_case[dataset_name] = True + _first_test_case[dataset_name] = True # Clear both files for new evaluation run if csv_file.exists(): csv_file.unlink() @@ -89,7 +93,7 @@ def save_raw_results_to_csv(dataset_name: str, test_case: Dict[str, Any], actual date_csv_file.unlink() # Write to latest directory - with open(csv_file, 'a', newline='', encoding='utf-8') as f: + with open(csv_file, "a", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=row_data.keys()) if is_first: writer.writeheader() @@ -97,7 +101,7 @@ def save_raw_results_to_csv(dataset_name: str, test_case: Dict[str, Any], actual # Write to date-based directory for archiving (always write header for new file) write_header = not date_csv_file.exists() - with open(date_csv_file, 'a', newline='', encoding='utf-8') as f: + with open(date_csv_file, "a", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=row_data.keys()) if write_header: writer.writeheader() @@ -108,9 +112,10 @@ def save_raw_results_to_csv(dataset_name: str, test_case: Dict[str, Any], actual def similarity_score(text1: str, text2: str) -> float: """Calculate similarity score between two texts.""" + # Normalize texts for comparison def normalize(text): - return re.sub(r'\s+', ' ', text.lower().strip()) + return re.sub(r"\s+", " ", text.lower().strip()) norm1 = normalize(text1) norm2 = normalize(text2) @@ -119,7 +124,9 @@ def normalize(text): return SequenceMatcher(None, norm1, norm2).ratio() -def chunks_similarity_score(expected_chunks: List[str], actual_chunks: List[str], threshold: float = 0.8) -> tuple[bool, float]: +def chunks_similarity_score( + expected_chunks: List[str], actual_chunks: List[str], threshold: float = 0.8 +) -> tuple[bool, float]: """Calculate similarity score between expected and actual chunks.""" if len(expected_chunks) != len(actual_chunks): return False, 0.0 @@ -133,32 +140,32 @@ def chunks_similarity_score(expected_chunks: List[str], actual_chunks: List[str] return avg_score >= threshold, avg_score -def evaluate_node(node, test_cases: List[Dict[str, Any]], dataset_name: str) -> Dict[str, Any]: +def evaluate_node( + node, test_cases: List[Dict[str, Any]], dataset_name: str +) -> Dict[str, Any]: """Evaluate a node against test cases.""" - results = { + results: Dict[str, Any] = { "dataset": dataset_name, "total_cases": len(test_cases), "correct": 0, "incorrect": 0, "errors": [], "details": [], - "raw_results_file": f"intent_kit/evals/results/latest/{dataset_name}_results.csv" + "raw_results_file": f"intent_kit/evals/results/latest/{dataset_name}_results.csv", } # Generate a unique run timestamp for this evaluation run_timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") # Check if this node needs persistent context (like handler_node_llm) - needs_persistent_context = hasattr( - node, 'name') and 'handler_node_llm' in node.name + needs_persistent_context = hasattr(node, "name") and "handler_node_llm" in node.name # Create persistent context if needed persistent_context = None if needs_persistent_context: persistent_context = IntentContext() # Initialize booking count for handler_node_llm - persistent_context.set( - "booking_count", 0, modified_by="evaluation_init") + persistent_context.set("booking_count", 0, modified_by="evaluation_init") for i, test_case in enumerate(test_cases): user_input = test_case["input"] @@ -189,78 +196,117 @@ def evaluate_node(node, test_cases: List[Dict[str, Any]], dataset_name: str) -> # For splitters, compare lists using similarity if isinstance(expected, list): correct, similarity_score_val = chunks_similarity_score( - expected, actual_output) + expected, actual_output + ) else: correct = False else: # For handlers and classifiers, compare strings - correct = str(actual_output).strip().lower() == str( - expected).strip().lower() + correct = ( + str(actual_output).strip().lower() + == str(expected).strip().lower() + ) if correct: results["correct"] += 1 else: results["incorrect"] += 1 - results["errors"].append({ - "case": i + 1, - "input": user_input, - "expected": expected, - "actual": actual_output, - "similarity_score": similarity_score_val, - "type": "incorrect_output" - }) + results["errors"].append( + { + "case": i + 1, + "input": user_input, + "expected": expected, + "actual": actual_output, + "similarity_score": similarity_score_val, + "type": "incorrect_output", + } + ) # Save raw result to CSV save_raw_results_to_csv( - dataset_name, test_case, actual_output, correct, similarity_score=similarity_score_val, run_timestamp=run_timestamp) + dataset_name, + test_case, + actual_output, + correct, + similarity_score=similarity_score_val, + run_timestamp=run_timestamp, + ) else: results["incorrect"] += 1 error_msg = result.error.message if result.error else "Unknown error" - results["errors"].append({ - "case": i + 1, - "input": user_input, - "expected": expected, - "actual": None, - "type": "execution_failed", - "error": error_msg - }) + results["errors"].append( + { + "case": i + 1, + "input": user_input, + "expected": expected, + "actual": None, + "type": "execution_failed", + "error": error_msg, + } + ) # Save raw result to CSV save_raw_results_to_csv( - dataset_name, test_case, None, False, error_msg, run_timestamp=run_timestamp) + dataset_name, + test_case, + None, + False, + error_msg, + run_timestamp=run_timestamp, + ) except Exception as e: results["incorrect"] += 1 error_msg = str(e) - results["errors"].append({ - "case": i + 1, - "input": user_input, - "expected": expected, - "actual": None, - "type": "exception", - "error": error_msg - }) + results["errors"].append( + { + "case": i + 1, + "input": user_input, + "expected": expected, + "actual": None, + "type": "exception", + "error": error_msg, + } + ) # Save raw result to CSV save_raw_results_to_csv( - dataset_name, test_case, None, False, error_msg, run_timestamp=run_timestamp) + dataset_name, + test_case, + None, + False, + error_msg, + run_timestamp=run_timestamp, + ) # Store detailed results - results["details"].append({ - "case": i + 1, - "input": user_input, - "expected": expected, - "actual": result.output if 'result' in locals() else None, - "success": result.success if 'result' in locals() else False, - "error": result.error.message if 'result' in locals() and result.error else None - }) - - results["accuracy"] = results["correct"] / \ - results["total_cases"] if results["total_cases"] > 0 else 0 + results["details"].append( + { + "case": i + 1, + "input": user_input, + "expected": expected, + "actual": result.output if "result" in locals() else None, + "success": result.success if "result" in locals() else False, + "error": ( + result.error.message + if "result" in locals() and result.error + else None + ), + } + ) + + results["accuracy"] = ( + results["correct"] / results["total_cases"] if results["total_cases"] > 0 else 0 + ) return results -def generate_markdown_report(results: List[Dict[str, Any]], output_path: Path, run_timestamp: Optional[str] = None, mock_mode: bool = False): +def generate_markdown_report( + results: List[Dict[str, Any]], + output_path: Path, + run_timestamp: Optional[str] = None, + mock_mode: bool = False, +): """Generate a markdown report from evaluation results.""" # Generate the report content mock_indicator = " (MOCK MODE)" if mock_mode else "" @@ -294,11 +340,13 @@ def generate_markdown_report(results: List[Dict[str, Any]], output_path: Path, r report_content += f"- **Case {error['case']}**: {error['input']}\n" report_content += f" - Expected: `{error['expected']}`\n" report_content += f" - Actual: `{error['actual']}`\n" - if error.get('error'): + if error.get("error"): report_content += f" - Error: {error['error']}\n" report_content += "\n" if len(result["errors"]) > 5: - report_content += f"- ... and {len(result['errors']) - 5} more errors\n\n" + report_content += ( + f"- ... and {len(result['errors']) - 5} more errors\n\n" + ) # Detailed results table report_content += "## Detailed Results\n\n" @@ -308,7 +356,7 @@ def generate_markdown_report(results: List[Dict[str, Any]], output_path: Path, r report_content += f"| {result['dataset']} | {result['accuracy']:.1%} | {result['correct']} | {result['total_cases']} | `{result['raw_results_file']}` |\n" # Write to the specified output path - with open(output_path, 'w') as f: + with open(output_path, "w") as f: f.write(report_content) today = datetime.now().strftime("%Y-%m-%d") @@ -318,9 +366,10 @@ def generate_markdown_report(results: List[Dict[str, Any]], output_path: Path, r date_reports_dir.mkdir(parents=True, exist_ok=True) # Create date-based filename - date_output_path = date_reports_dir / \ - f"{output_path.stem}_{run_timestamp}{output_path.suffix}" - with open(date_output_path, 'w') as f: + date_output_path = ( + date_reports_dir / f"{output_path.stem}_{run_timestamp}{output_path.suffix}" + ) + with open(date_output_path, "w") as f: f.write(report_content) @@ -335,7 +384,7 @@ def main(): # Load LLM configuration if provided llm_config = {} if args.llm_config: - with open(args.llm_config, 'r') as f: + with open(args.llm_config, "r") as f: llm_config = yaml.safe_load(f) # Set environment variables for API keys @@ -376,9 +425,13 @@ def main(): # Determine module name based on node name if "llm" in node_name: - module_name = f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node_llm" + module_name = ( + f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node_llm" + ) else: - module_name = f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node" + module_name = ( + f"intent_kit.evals.sample_nodes.{node_name.split('_')[0]}_node" + ) # Load node node = get_node_from_module(module_name, node_name) @@ -394,7 +447,8 @@ def main(): # Print results accuracy = result["accuracy"] print( - f" Accuracy: {accuracy:.1%} ({result['correct']}/{result['total_cases']})") + f" Accuracy: {accuracy:.1%} ({result['correct']}/{result['total_cases']})" + ) print(f" Raw results saved to: {result['raw_results_file']}") if result["errors"]: @@ -422,8 +476,7 @@ def main(): output_path = reports_dir / "evaluation_report.md" - generate_markdown_report(results, output_path, - run_timestamp=run_timestamp) + generate_markdown_report(results, output_path, run_timestamp=run_timestamp) print(f"\nReport generated: {output_path}") # Print summary @@ -431,7 +484,8 @@ def main(): total_correct = sum(r["correct"] for r in results) overall_accuracy = total_correct / total_cases if total_cases > 0 else 0 print( - f"\nOverall Accuracy: {overall_accuracy:.1%} ({total_correct}/{total_cases})") + f"\nOverall Accuracy: {overall_accuracy:.1%} ({total_correct}/{total_cases})" + ) if __name__ == "__main__": diff --git a/intent_kit/evals/sample_nodes/__init__.py b/intent_kit/evals/sample_nodes/__init__.py index f355633..af3d1b5 100644 --- a/intent_kit/evals/sample_nodes/__init__.py +++ b/intent_kit/evals/sample_nodes/__init__.py @@ -1 +1 @@ -"""Sample node implementations for node-level evaluation.""" \ No newline at end of file +"""Sample node implementations for node-level evaluation.""" diff --git a/intent_kit/evals/sample_nodes/classifier_node_llm.py b/intent_kit/evals/sample_nodes/classifier_node_llm.py index 799ac2b..dac54f0 100644 --- a/intent_kit/evals/sample_nodes/classifier_node_llm.py +++ b/intent_kit/evals/sample_nodes/classifier_node_llm.py @@ -5,24 +5,28 @@ from intent_kit.node.base import TreeNode -def extract_weather_args_llm(user_input: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]: +def extract_weather_args_llm( + user_input: str, context: Optional[Dict[str, Any]] = None +) -> Dict[str, Any]: """Extract weather parameters using LLM.""" from intent_kit.services.llm_factory import LLMFactory # Check for mock mode import os + mock_mode = os.getenv("INTENT_KIT_MOCK_MODE") == "1" if mock_mode: # Mock responses for testing without API calls import re + location_patterns = [ - r'(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)', - r'(?:weather|temperature|forecast)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)', - r'(?:What\'s|How\'s)\s+(?:the\s+)?(?:weather|temperature)\s+(?:like\s+)?(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)', - r'(?:weather|temperature)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)', - r'(?:weather|temperature|forecast)\s+for\s+([A-Za-z\s]+?)(?:\?|$)', - r'(?:weather|temperature)\s+in\s+([A-Za-z\s]+?)(?:\?|$)' + r"(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)", + r"(?:weather|temperature|forecast)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)", + r"(?:What\'s|How\'s)\s+(?:the\s+)?(?:weather|temperature)\s+(?:like\s+)?(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)", + r"(?:weather|temperature)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)", + r"(?:weather|temperature|forecast)\s+for\s+([A-Za-z\s]+?)(?:\?|$)", + r"(?:weather|temperature)\s+in\s+([A-Za-z\s]+?)(?:\?|$)", ] location = "Unknown" @@ -39,14 +43,9 @@ def extract_weather_args_llm(user_input: str, context: Optional[Dict[str, Any]] api_key = os.getenv(f"{provider.upper()}_API_KEY") if not api_key: - raise ValueError( - f"Environment variable {provider.upper()}_API_KEY not set") + raise ValueError(f"Environment variable {provider.upper()}_API_KEY not set") - llm_config = { - "provider": provider, - "model": "gpt-4.1-mini", - "api_key": api_key - } + llm_config = {"provider": provider, "model": "gpt-4.1-mini", "api_key": api_key} try: llm_client = LLMFactory.create_client(llm_config) @@ -80,7 +79,7 @@ def extract_weather_args_llm(user_input: str, context: Optional[Dict[str, Any]] import re # Extract JSON from response - json_match = re.search(r'\{.*\}', response, re.DOTALL) + json_match = re.search(r"\{.*\}", response, re.DOTALL) if json_match: result = json.loads(json_match.group()) return {"location": result.get("location", "Unknown")} @@ -89,13 +88,14 @@ def extract_weather_args_llm(user_input: str, context: Optional[Dict[str, Any]] # Fallback to regex extraction import re + location_patterns = [ - r'(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)', - r'(?:weather|temperature|forecast)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)', - r'(?:What\'s|How\'s)\s+(?:the\s+)?(?:weather|temperature)\s+(?:like\s+)?(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)', - r'(?:weather|temperature)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)', - r'(?:weather|temperature|forecast)\s+for\s+([A-Za-z\s]+?)(?:\?|$)', - r'(?:weather|temperature)\s+in\s+([A-Za-z\s]+?)(?:\?|$)' + r"(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)", + r"(?:weather|temperature|forecast)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\s|$)", + r"(?:What\'s|How\'s)\s+(?:the\s+)?(?:weather|temperature)\s+(?:like\s+)?(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)", + r"(?:weather|temperature)\s+(?:in|for|at)\s+([A-Za-z\s]+?)(?:\?|$)", + r"(?:weather|temperature|forecast)\s+for\s+([A-Za-z\s]+?)(?:\?|$)", + r"(?:weather|temperature)\s+in\s+([A-Za-z\s]+?)(?:\?|$)", ] location = "Unknown" @@ -113,22 +113,26 @@ def weather_handler(location: str, context: IntentContext) -> str: return f"Weather in {location}: Sunny with a chance of rain" -def extract_cancel_args_llm(user_input: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]: +def extract_cancel_args_llm( + user_input: str, context: Optional[Dict[str, Any]] = None +) -> Dict[str, Any]: """Extract cancellation parameters using LLM.""" from intent_kit.services.llm_factory import LLMFactory # Check for mock mode import os + mock_mode = os.getenv("INTENT_KIT_MOCK_MODE") == "1" if mock_mode: # Mock responses for testing without API calls import re + cancel_patterns = [ - r'cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)', - r'cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\?|$)', - r'(?:I\s+need\s+to\s+)?cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)', - r'(?:cancel|cancellation)\s+(?:of\s+)?(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)' + r"cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)", + r"cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\?|$)", + r"(?:I\s+need\s+to\s+)?cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)", + r"(?:cancel|cancellation)\s+(?:of\s+)?(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)", ] item = "reservation" @@ -145,14 +149,9 @@ def extract_cancel_args_llm(user_input: str, context: Optional[Dict[str, Any]] = api_key = os.getenv(f"{provider.upper()}_API_KEY") if not api_key: - raise ValueError( - f"Environment variable {provider.upper()}_API_KEY not set") + raise ValueError(f"Environment variable {provider.upper()}_API_KEY not set") - llm_config = { - "provider": provider, - "model": "gpt-3.5-turbo", - "api_key": api_key - } + llm_config = {"provider": provider, "model": "gpt-3.5-turbo", "api_key": api_key} try: llm_client = LLMFactory.create_client(llm_config) @@ -186,7 +185,7 @@ def extract_cancel_args_llm(user_input: str, context: Optional[Dict[str, Any]] = import re # Extract JSON from response - json_match = re.search(r'\{.*\}', response, re.DOTALL) + json_match = re.search(r"\{.*\}", response, re.DOTALL) if json_match: result = json.loads(json_match.group()) return {"item": result.get("item", "reservation")} @@ -195,11 +194,12 @@ def extract_cancel_args_llm(user_input: str, context: Optional[Dict[str, Any]] = # Fallback to regex extraction import re + cancel_patterns = [ - r'cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)', - r'cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\?|$)', - r'(?:I\s+need\s+to\s+)?cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)', - r'(?:cancel|cancellation)\s+(?:of\s+)?(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)' + r"cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)", + r"cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\?|$)", + r"(?:I\s+need\s+to\s+)?cancel\s+(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)", + r"(?:cancel|cancellation)\s+(?:of\s+)?(?:my\s+)?([^,\s]+(?:\s+[^,\s]+)*?)(?:\s|$)", ] item = "reservation" @@ -223,7 +223,7 @@ def cancel_handler(item: str, context: IntentContext) -> str: param_schema={"location": str}, handler=weather_handler, arg_extractor=extract_weather_args_llm, - description="Get weather information for a location" + description="Get weather information for a location", ) cancel_handler_node = HandlerNode( @@ -231,16 +231,19 @@ def cancel_handler(item: str, context: IntentContext) -> str: param_schema={"item": str}, handler=cancel_handler, arg_extractor=extract_cancel_args_llm, - description="Cancel reservations or bookings" + description="Cancel reservations or bookings", ) -def intent_classifier_llm(user_input: str, children: List[TreeNode], context: Optional[Dict[str, Any]] = None) -> Optional[TreeNode]: +def intent_classifier_llm( + user_input: str, children: List[TreeNode], context: Optional[Dict[str, Any]] = None +) -> Optional[TreeNode]: """Classify user intent using LLM.""" from intent_kit.services.llm_factory import LLMFactory # Check for mock mode import os + mock_mode = os.getenv("INTENT_KIT_MOCK_MODE") == "1" if mock_mode: @@ -259,14 +262,9 @@ def intent_classifier_llm(user_input: str, children: List[TreeNode], context: Op api_key = os.getenv(f"{provider.upper()}_API_KEY") if not api_key: - raise ValueError( - f"Environment variable {provider.upper()}_API_KEY not set") + raise ValueError(f"Environment variable {provider.upper()}_API_KEY not set") - llm_config = { - "provider": provider, - "model": "gpt-3.5-turbo", - "api_key": api_key - } + llm_config = {"provider": provider, "model": "gpt-3.5-turbo", "api_key": api_key} try: llm_client = LLMFactory.create_client(llm_config) @@ -303,18 +301,26 @@ def intent_classifier_llm(user_input: str, children: List[TreeNode], context: Op # Fallback to keyword matching user_input_lower = user_input.lower() - if any(word in user_input_lower for word in ["weather", "temperature", "forecast"]): + if any( + word in user_input_lower for word in ["weather", "temperature", "forecast"] + ): return weather_handler_node - elif any(word in user_input_lower for word in ["cancel", "cancellation", "refund"]): + elif any( + word in user_input_lower for word in ["cancel", "cancellation", "refund"] + ): return cancel_handler_node except Exception as e: print(f"LLM classification failed: {e}") # Fallback to keyword matching user_input_lower = user_input.lower() - if any(word in user_input_lower for word in ["weather", "temperature", "forecast"]): + if any( + word in user_input_lower for word in ["weather", "temperature", "forecast"] + ): return weather_handler_node - elif any(word in user_input_lower for word in ["cancel", "cancellation", "refund"]): + elif any( + word in user_input_lower for word in ["cancel", "cancellation", "refund"] + ): return cancel_handler_node return None @@ -325,5 +331,5 @@ def intent_classifier_llm(user_input: str, children: List[TreeNode], context: Op name="classifier_node_llm", classifier=intent_classifier_llm, children=[weather_handler_node, cancel_handler_node], - description="Route user intents to appropriate handlers using LLM classification" + description="Route user intents to appropriate handlers using LLM classification", ) diff --git a/intent_kit/evals/sample_nodes/handler_node_llm.py b/intent_kit/evals/sample_nodes/handler_node_llm.py index efa2afc..5fc542e 100644 --- a/intent_kit/evals/sample_nodes/handler_node_llm.py +++ b/intent_kit/evals/sample_nodes/handler_node_llm.py @@ -1,33 +1,36 @@ from typing import Optional, Dict, Any from intent_kit.handlers.node import HandlerNode from intent_kit.context import IntentContext -from intent_kit.node.types import ExecutionResult -def extract_booking_args_llm(user_input: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]: +def extract_booking_args_llm( + user_input: str, context: Optional[Dict[str, Any]] = None +) -> Dict[str, Any]: """Extract booking parameters using LLM.""" from intent_kit.services.llm_factory import LLMFactory # Check for mock mode import os + mock_mode = os.getenv("INTENT_KIT_MOCK_MODE") == "1" if mock_mode: # Mock responses for testing without API calls import re + # Simple regex extraction for mock mode dest_match = re.search( - r'(?:to|for|in)\s+([A-Za-z\s]+?)(?:\s|$)', user_input, re.IGNORECASE) + r"(?:to|for|in)\s+([A-Za-z\s]+?)(?:\s|$)", user_input, re.IGNORECASE + ) destination = dest_match.group(1).strip() if dest_match else "Unknown" - date_match = re.search(r'(?:for|on)\s+(\w+\s+\w+)', - user_input, re.IGNORECASE) + date_match = re.search(r"(?:for|on)\s+(\w+\s+\w+)", user_input, re.IGNORECASE) date = date_match.group(1) if date_match else "ASAP" return { "destination": destination, "date": date, - "user_id": context.get("user_id", "anonymous") if context else "anonymous" + "user_id": context.get("user_id", "anonymous") if context else "anonymous", } # Configure LLM (you can change this to any supported provider) @@ -35,14 +38,9 @@ def extract_booking_args_llm(user_input: str, context: Optional[Dict[str, Any]] api_key = os.getenv(f"{provider.upper()}_API_KEY") if not api_key: - raise ValueError( - f"Environment variable {provider.upper()}_API_KEY not set") + raise ValueError(f"Environment variable {provider.upper()}_API_KEY not set") - llm_config = { - "provider": provider, - "model": "gpt-3.5-turbo", - "api_key": api_key - } + llm_config = {"provider": provider, "model": "gpt-3.5-turbo", "api_key": api_key} try: llm_client = LLMFactory.create_client(llm_config) @@ -81,37 +79,40 @@ def extract_booking_args_llm(user_input: str, context: Optional[Dict[str, Any]] import re # Extract JSON from response - json_match = re.search(r'\{.*\}', response, re.DOTALL) + json_match = re.search(r"\{.*\}", response, re.DOTALL) if json_match: result = json.loads(json_match.group()) # Clean up the date field to remove extra words date = result.get("date", "ASAP") if date != "ASAP": # Remove common prefixes that might be extracted - date = re.sub(r'^(for|to)\s+', '', date, flags=re.IGNORECASE) + date = re.sub(r"^(for|to)\s+", "", date, flags=re.IGNORECASE) return { "destination": result.get("destination", "Unknown"), "date": date, - "user_id": context.get("user_id", "anonymous") if context else "anonymous" + "user_id": ( + context.get("user_id", "anonymous") if context else "anonymous" + ), } except Exception as e: print(f"LLM extraction failed: {e}") # Fallback to simple extraction import re + dest_match = re.search( - r'(?:to|for|in)\s+([A-Za-z\s]+?)(?:\s|$)', user_input, re.IGNORECASE) + r"(?:to|for|in)\s+([A-Za-z\s]+?)(?:\s|$)", user_input, re.IGNORECASE + ) destination = dest_match.group(1).strip() if dest_match else "Unknown" - date_match = re.search(r'(?:for|on)\s+(\w+\s+\w+)', - user_input, re.IGNORECASE) + date_match = re.search(r"(?:for|on)\s+(\w+\s+\w+)", user_input, re.IGNORECASE) date = date_match.group(1) if date_match else "ASAP" return { "destination": destination, "date": date, - "user_id": context.get("user_id", "anonymous") if context else "anonymous" + "user_id": context.get("user_id", "anonymous") if context else "anonymous", } @@ -134,5 +135,5 @@ def booking_handler(destination: str, date: str, context: IntentContext) -> str: arg_extractor=extract_booking_args_llm, context_inputs={"user_id"}, context_outputs={"booking_count", "last_destination"}, - description="Handle flight booking requests with LLM-powered argument extraction" + description="Handle flight booking requests with LLM-powered argument extraction", ) diff --git a/intent_kit/evals/sample_nodes/splitter_node_llm.py b/intent_kit/evals/sample_nodes/splitter_node_llm.py index 45b4640..1959e03 100644 --- a/intent_kit/evals/sample_nodes/splitter_node_llm.py +++ b/intent_kit/evals/sample_nodes/splitter_node_llm.py @@ -1,22 +1,24 @@ from typing import Optional, List, Dict, Any from intent_kit.splitters.node import SplitterNode -from intent_kit.context import IntentContext -def split_text_llm(user_input: str, debug: bool = False, context: Optional[Dict[str, Any]] = None) -> List[str]: +def split_text_llm( + user_input: str, debug: bool = False, context: Optional[Dict[str, Any]] = None +) -> List[str]: """Split user input into multiple intents using LLM.""" from intent_kit.services.llm_factory import LLMFactory # Check for mock mode import os + mock_mode = os.getenv("INTENT_KIT_MOCK_MODE") == "1" if mock_mode: # Mock responses for testing without API calls # Simple splitting based on common conjunctions import re - conjunctions = [" and ", " also ", " plus ", - " as well as ", " furthermore "] + + conjunctions = [" and ", " also ", " plus ", " as well as ", " furthermore "] for conj in conjunctions: if conj in user_input.lower(): parts = user_input.split(conj) @@ -29,14 +31,9 @@ def split_text_llm(user_input: str, debug: bool = False, context: Optional[Dict[ api_key = os.getenv(f"{provider.upper()}_API_KEY") if not api_key: - raise ValueError( - f"Environment variable {provider.upper()}_API_KEY not set") + raise ValueError(f"Environment variable {provider.upper()}_API_KEY not set") - llm_config = { - "provider": provider, - "model": "gpt-4.1-mini", - "api_key": api_key - } + llm_config = {"provider": provider, "model": "gpt-4.1-mini", "api_key": api_key} try: llm_client = LLMFactory.create_client(llm_config) @@ -59,7 +56,7 @@ def split_text_llm(user_input: str, debug: bool = False, context: Optional[Dict[ import re # Extract JSON array from response - json_match = re.search(r'\[.*\]', response, re.DOTALL) + json_match = re.search(r"\[.*\]", response, re.DOTALL) if json_match: result = json.loads(json_match.group()) if isinstance(result, list): @@ -79,7 +76,7 @@ def create_splitter_node_llm(): name="splitter_node_llm", splitter_function=split_text_llm, children=[], - description="Split complex user inputs into multiple intents using LLM" + description="Split complex user inputs into multiple intents using LLM", ) @@ -92,13 +89,8 @@ def __init__(self, splitter_node): self.splitter_function = splitter_node.splitter_function def execute(self, user_input: str, context=None): - chunks = self.splitter_function( - user_input, debug=False, context=context) - return type('Result', (), { - 'success': True, - 'output': chunks, - 'error': None - })() + chunks = self.splitter_function(user_input, debug=False, context=context) + return type("Result", (), {"success": True, "output": chunks, "error": None})() # Export the node creation function diff --git a/intent_kit/exceptions/__init__.py b/intent_kit/exceptions/__init__.py index 7ffff70..273ce79 100644 --- a/intent_kit/exceptions/__init__.py +++ b/intent_kit/exceptions/__init__.py @@ -4,18 +4,26 @@ This module provides Node-related exception classes for the intent-kit project. """ -from typing import Optional, List, Dict, Any +from typing import Optional, List class NodeError(Exception): """Base exception for node-related errors.""" + pass class NodeExecutionError(NodeError): """Raised when a node execution fails.""" - def __init__(self, node_name: str, error_message: str, params=None, node_id: Optional[str] = None, node_path: Optional[List[str]] = None): + def __init__( + self, + node_name: str, + error_message: str, + params=None, + node_id: Optional[str] = None, + node_path: Optional[List[str]] = None, + ): """ Initialize the exception. @@ -39,13 +47,21 @@ def __init__(self, node_name: str, error_message: str, params=None, node_id: Opt class NodeValidationError(NodeError): """Base exception for node validation errors.""" + pass class NodeInputValidationError(NodeValidationError): """Raised when node input validation fails.""" - def __init__(self, node_name: str, validation_error: str, input_data=None, node_id: Optional[str] = None, node_path: Optional[List[str]] = None): + def __init__( + self, + node_name: str, + validation_error: str, + input_data=None, + node_id: Optional[str] = None, + node_path: Optional[List[str]] = None, + ): """ Initialize the exception. @@ -70,7 +86,14 @@ def __init__(self, node_name: str, validation_error: str, input_data=None, node_ class NodeOutputValidationError(NodeValidationError): """Raised when node output validation fails.""" - def __init__(self, node_name: str, validation_error: str, output_data=None, node_id: Optional[str] = None, node_path: Optional[List[str]] = None): + def __init__( + self, + node_name: str, + validation_error: str, + output_data=None, + node_id: Optional[str] = None, + node_path: Optional[List[str]] = None, + ): """ Initialize the exception. diff --git a/intent_kit/graph/__init__.py b/intent_kit/graph/__init__.py index 67ab346..e99da68 100644 --- a/intent_kit/graph/__init__.py +++ b/intent_kit/graph/__init__.py @@ -8,5 +8,5 @@ from .intent_graph import IntentGraph __all__ = [ - 'IntentGraph', + "IntentGraph", ] diff --git a/intent_kit/graph/intent_graph.py b/intent_kit/graph/intent_graph.py index b367d6c..069973b 100644 --- a/intent_kit/graph/intent_graph.py +++ b/intent_kit/graph/intent_graph.py @@ -5,31 +5,36 @@ routing to root nodes, and result aggregation. """ -from typing import Dict, Any, Optional, Callable, List +from typing import Dict, Any, Optional, List from datetime import datetime from intent_kit.utils.logger import Logger from intent_kit.context import IntentContext -from intent_kit.splitters import rule_splitter from intent_kit.types import SplitterFunction, IntentChunk -from intent_kit.graph.validation import validate_splitter_routing, validate_graph_structure, validate_node_types, GraphValidationError +from intent_kit.graph.validation import ( + validate_splitter_routing, + validate_graph_structure, + validate_node_types, + GraphValidationError, +) + # from intent_kit.graph.aggregation import aggregate_results, create_error_dict, create_no_intent_error, create_no_tree_error from intent_kit.node import ExecutionResult from intent_kit.node import ExecutionError from intent_kit.node.enums import NodeType -from intent_kit.exceptions import NodeExecutionError, NodeInputValidationError, NodeOutputValidationError from intent_kit.node import TreeNode import os from intent_kit.classifiers import classify_intent_chunk -from intent_kit.types import IntentAction, IntentClassification +from intent_kit.types import IntentAction # Add imports for visualization try: import networkx as nx - from pyvis.network import Network + from pyvis.network import Network # type: ignore + VIZ_AVAILABLE = True -except ImportError as e: - nx = None - Network = None +except ImportError: + nx = None # type: ignore + Network = None # type: ignore VIZ_AVAILABLE = False @@ -42,7 +47,15 @@ class IntentGraph: Trees emerge naturally from the parent-child relationships between nodes. """ - def __init__(self, root_nodes: Optional[List[TreeNode]] = None, splitter: Optional[SplitterFunction] = None, visualize: bool = False, llm_config: Optional[dict] = None, debug_context: bool = False, context_trace: bool = False): + def __init__( + self, + root_nodes: Optional[List[TreeNode]] = None, + splitter: Optional[SplitterFunction] = None, + visualize: bool = False, + llm_config: Optional[dict] = None, + debug_context: bool = False, + context_trace: bool = False, + ): """ Initialize the IntentGraph with root nodes. @@ -58,10 +71,14 @@ def __init__(self, root_nodes: Optional[List[TreeNode]] = None, splitter: Option # Default to pass-through splitter if none provided if splitter is None: - def pass_through_splitter(user_input: str, debug: bool = False) -> List[IntentChunk]: + + def pass_through_splitter( + user_input: str, debug: bool = False + ) -> List[IntentChunk]: """Pass-through splitter that doesn't split the input.""" return [user_input] - self.splitter = pass_through_splitter + + self.splitter: SplitterFunction = pass_through_splitter else: self.splitter = splitter @@ -89,11 +106,11 @@ def add_root_node(self, root_node: TreeNode, validate: bool = True) -> None: if validate: try: self.validate_graph() - self.logger.info( - "Graph validation passed after adding root node") + self.logger.info("Graph validation passed after adding root node") except GraphValidationError as e: self.logger.error( - f"Graph validation failed after adding root node: {e.message}") + f"Graph validation failed after adding root node: {e.message}" + ) # Remove the node if validation fails and re-raise the error self.root_nodes.remove(root_node) raise e @@ -109,8 +126,7 @@ def remove_root_node(self, root_node: TreeNode) -> None: self.root_nodes.remove(root_node) self.logger.info(f"Removed root node: {root_node.name}") else: - self.logger.warning( - f"Root node '{root_node.name}' not found for removal") + self.logger.warning(f"Root node '{root_node.name}' not found for removal") def list_root_nodes(self) -> List[str]: """ @@ -121,7 +137,9 @@ def list_root_nodes(self) -> List[str]: """ return [node.name for node in self.root_nodes] - def validate_graph(self, validate_routing: bool = True, validate_types: bool = True) -> Dict[str, Any]: + def validate_graph( + self, validate_routing: bool = True, validate_types: bool = True + ) -> Dict[str, Any]: """ Validate the graph structure and routing constraints. @@ -188,7 +206,13 @@ def collect_node(node: TreeNode): return all_nodes - def _call_splitter(self, user_input: str, debug: bool, context: Optional[IntentContext] = None, **splitter_kwargs) -> list: + def _call_splitter( + self, + user_input: str, + debug: bool, + context: Optional[IntentContext] = None, + **splitter_kwargs, + ) -> list: """ Call the splitter function with appropriate parameters. @@ -204,7 +228,9 @@ def _call_splitter(self, user_input: str, debug: bool, context: Optional[IntentC result = self.splitter(user_input, debug, **splitter_kwargs) return list(result) # Convert Sequence to list - def _route_chunk_to_root_node(self, chunk: str, debug: bool = False) -> Optional[TreeNode]: + def _route_chunk_to_root_node( + self, chunk: str, debug: bool = False + ) -> Optional[TreeNode]: """ Route a single chunk to the most appropriate root node. @@ -227,25 +253,36 @@ def _route_chunk_to_root_node(self, chunk: str, debug: bool = False) -> Optional if node.name.lower() in chunk_lower: if debug: self.logger.info( - f"Routed chunk '{chunk}' to root node '{node.name}' by name match") + f"Routed chunk '{chunk}' to root node '{node.name}' by name match" + ) return node # Check for keyword matches (could be enhanced) - keywords = getattr(node, 'keywords', []) + keywords = getattr(node, "keywords", []) for keyword in keywords: if keyword.lower() in chunk_lower: if debug: self.logger.info( - f"Routed chunk '{chunk}' to root node '{node.name}' by keyword '{keyword}'") + f"Routed chunk '{chunk}' to root node '{node.name}' by keyword '{keyword}'" + ) return node # If no specific match, return the first root node as fallback if debug: self.logger.info( - f"No specific match for chunk '{chunk}', using first root node '{self.root_nodes[0].name}' as fallback") + f"No specific match for chunk '{chunk}', using first root node '{self.root_nodes[0].name}' as fallback" + ) return self.root_nodes[0] if self.root_nodes else None - def route(self, user_input: str, context: Optional[IntentContext] = None, debug: bool = False, debug_context: Optional[bool] = None, context_trace: Optional[bool] = None, **splitter_kwargs) -> ExecutionResult: + def route( + self, + user_input: str, + context: Optional[IntentContext] = None, + debug: bool = False, + debug_context: Optional[bool] = None, + context_trace: Optional[bool] = None, + **splitter_kwargs, + ) -> ExecutionResult: """ Route user input through the graph with optional context support. @@ -261,8 +298,12 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: ExecutionResult containing aggregated results and errors from all matched taxonomies """ # Use method parameters if provided, otherwise use graph-level settings - debug_context_enabled = debug_context if debug_context is not None else self.debug_context - context_trace_enabled = context_trace if context_trace is not None else self.context_trace + debug_context_enabled = ( + debug_context if debug_context is not None else self.debug_context + ) + context_trace_enabled = ( + context_trace if context_trace is not None else self.context_trace + ) if debug: self.logger.info(f"Processing input: {user_input}") @@ -276,9 +317,7 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: # Split the input into chunks try: intent_chunks = self._call_splitter( - user_input=user_input, - debug=debug, - **splitter_kwargs + user_input=user_input, debug=debug, **splitter_kwargs ) except Exception as e: @@ -296,8 +335,8 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="SplitterError", message=str(e), node_name="splitter", - node_path=[] - ) + node_path=[], + ), ) if debug: @@ -320,8 +359,8 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="NoIntentFound", message="No intent chunks found", node_name="unhandled_chunk", - node_path=[] - ) + node_path=[], + ), ) # Route each chunk to an appropriate root node @@ -332,7 +371,7 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: # Use a queue to process chunks, with recursion limit chunks_to_process = list(intent_chunks) # Copy the list - processed_chunks = set() # Track processed chunks to avoid infinite loops + processed_chunks: set = set() # Track processed chunks to avoid infinite loops max_recursion_depth = 10 # Prevent infinite recursion while chunks_to_process and len(processed_chunks) < max_recursion_depth: @@ -378,35 +417,43 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="NoRootNodeFound", message=f"No root node found for chunk: '{chunk_text}'", node_name="no_root_node", - node_path=[] - ) + node_path=[], + ), ) children_results.append(error_result) - all_errors.append( - f"No root node found for chunk: '{chunk_text}'") + all_errors.append(f"No root node found for chunk: '{chunk_text}'") if debug: self.logger.error( - f"No root node found for chunk: '{chunk_text}'") + f"No root node found for chunk: '{chunk_text}'" + ) continue try: # Context debugging: capture state before execution context_state_before = None if debug_context_enabled and context: context_state_before = self._capture_context_state( - context, f"before_{root_node.name}") + context, f"before_{root_node.name}" + ) result = root_node.execute(chunk_text, context=context) # Context debugging: capture state after execution if debug_context_enabled and context: context_state_after = self._capture_context_state( - context, f"after_{root_node.name}") + context, f"after_{root_node.name}" + ) self._log_context_changes( - context_state_before, context_state_after, root_node.name, debug, context_trace_enabled) + context_state_before, + context_state_after, + root_node.name, + debug, + context_trace_enabled, + ) if debug: self.logger.info( - f"Root node '{root_node.name}' result: {result}") + f"Root node '{root_node.name}' result: {result}" + ) children_results.append(result) if result.success and result.output is not None: all_outputs.append(result.output) @@ -414,7 +461,8 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: all_params.append(result.params) if result.error: all_errors.append( - f"Root node '{root_node.name}': {result.error.message}") + f"Root node '{root_node.name}': {result.error.message}" + ) except Exception as e: error_message = str(e) error_type = type(e).__name__ @@ -431,22 +479,20 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type=error_type, message=error_message, node_name="unknown", - node_path=[] - ) + node_path=[], + ), ) children_results.append(error_result) all_errors.append( - f"Root node '{root_node.name}' failed: {error_message}") + f"Root node '{root_node.name}' failed: {error_message}" + ) if debug: - self.logger.error( - f"Root node '{root_node.name}' failed: {e}") + self.logger.error(f"Root node '{root_node.name}' failed: {e}") elif action == IntentAction.SPLIT: # Recursively split and route if debug: - self.logger.info( - f"Recursively splitting chunk: '{chunk_text}'") - sub_chunks = self._call_splitter( - chunk_text, debug, **splitter_kwargs) + self.logger.info(f"Recursively splitting chunk: '{chunk_text}'") + sub_chunks = self._call_splitter(chunk_text, debug, **splitter_kwargs) # Add sub_chunks to the front of the queue for processing chunks_to_process = sub_chunks + chunks_to_process elif action == IntentAction.CLARIFY: @@ -464,15 +510,15 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="ClarificationNeeded", message=f"Clarification needed for chunk: '{chunk_text}'", node_name="clarify", - node_path=[] - ) + node_path=[], + ), ) children_results.append(error_result) - all_errors.append( - f"Clarification needed for chunk: '{chunk_text}'") + all_errors.append(f"Clarification needed for chunk: '{chunk_text}'") if debug: self.logger.warning( - f"Clarification needed for chunk: '{chunk_text}'") + f"Clarification needed for chunk: '{chunk_text}'" + ) elif action == IntentAction.REJECT: # Stub: Add a result indicating rejection error_result = ExecutionResult( @@ -488,8 +534,8 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="RejectedChunk", message=f"Rejected chunk: '{chunk_text}'", node_name="reject", - node_path=[] - ) + node_path=[], + ), ) children_results.append(error_result) all_errors.append(f"Rejected chunk: '{chunk_text}'") @@ -510,14 +556,13 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="UnknownAction", message=f"Unknown action for chunk: '{chunk_text}'", node_name="unknown_action", - node_path=[] - ) + node_path=[], + ), ) children_results.append(error_result) all_errors.append(f"Unknown action for chunk: '{chunk_text}'") if debug: - self.logger.error( - f"Unknown action for chunk: '{chunk_text}'") + self.logger.error(f"Unknown action for chunk: '{chunk_text}'") # Check if we hit the recursion limit if len(processed_chunks) >= max_recursion_depth: @@ -534,24 +579,32 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="RecursionLimitExceeded", message=f"Recursion limit exceeded ({max_recursion_depth} chunks processed)", node_name="recursion_limit", - node_path=[] - ) + node_path=[], + ), ) children_results.append(error_result) all_errors.append( - f"Recursion limit exceeded ({max_recursion_depth} chunks processed)") + f"Recursion limit exceeded ({max_recursion_depth} chunks processed)" + ) if debug: self.logger.error( - f"Recursion limit exceeded ({max_recursion_depth} chunks processed)") + f"Recursion limit exceeded ({max_recursion_depth} chunks processed)" + ) # Determine overall success and create aggregated result overall_success = len(all_errors) == 0 and len(children_results) > 0 # Aggregate outputs and params - aggregated_output = all_outputs if len(all_outputs) > 1 else ( - all_outputs[0] if all_outputs else None) - aggregated_params = all_params if len(all_params) > 1 else ( - all_params[0] if all_params else None) + aggregated_output = ( + all_outputs + if len(all_outputs) > 1 + else (all_outputs[0] if all_outputs else None) + ) + aggregated_params = ( + all_params + if len(all_params) > 1 + else (all_params[0] if all_params else None) + ) # Ensure params is a dict or None if aggregated_params is not None and not isinstance(aggregated_params, dict): @@ -564,15 +617,14 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: error_type="AggregatedErrors", message="; ".join(all_errors), node_name="intent_graph", - node_path=[] + node_path=[], ) # Create visualization if requested visualization_html = None if self.visualize: try: - html_path = self._render_execution_graph( - children_results, user_input) + html_path = self._render_execution_graph(children_results, user_input) visualization_html = html_path except Exception as e: self.logger.error(f"Visualization failed: {e}") @@ -587,7 +639,7 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: else: aggregated_output = { "output": aggregated_output, - "visualization_html": visualization_html + "visualization_html": visualization_html, } if debug: @@ -602,39 +654,43 @@ def route(self, user_input: str, context: Optional[IntentContext] = None, debug: node_type=NodeType.GRAPH, input=user_input, output=aggregated_output, - error=aggregated_error + error=aggregated_error, ) - def _render_execution_graph(self, children_results: list[ExecutionResult], user_input: str) -> str: + def _render_execution_graph( + self, children_results: list[ExecutionResult], user_input: str + ) -> str: """ Render the execution path as an interactive HTML graph and return the file path. """ if not VIZ_AVAILABLE: raise ImportError( - "networkx and pyvis are required for visualization. Please install with: uv pip install 'intent-kit[viz]'") + "networkx and pyvis are required for visualization. Please install with: uv pip install 'intent-kit[viz]'" + ) try: # Import here to ensure it's available from pyvis.network import Network # Build the graph from the execution path - net = Network(height="600px", width="100%", - directed=True, notebook=False) + net = Network(height="600px", width="100%", directed=True, notebook=False) net.barnes_hut() execution_paths = [] # Extract execution paths from all children results for result in children_results: # Add the current result to the path - execution_paths.append({ - "node_name": result.node_name, - "node_type": result.node_type, - "success": result.success, - "input": result.input, - "output": result.output, - "error": result.error, - "params": result.params - }) + execution_paths.append( + { + "node_name": result.node_name, + "node_type": result.node_type, + "success": result.success, + "input": result.input, + "output": result.output, + "error": result.error, + "params": result.params, + } + ) # Add child results recursively for child_result in result.children_results: @@ -646,11 +702,13 @@ def _render_execution_graph(self, children_results: list[ExecutionResult], user_ execution_paths = [] for result in children_results: if result.error: - execution_paths.append({ - "node_name": result.node_name, - "node_type": "error", - "error": result.error - }) + execution_paths.append( + { + "node_name": result.node_name, + "node_type": "error", + "error": result.error, + } + ) # Add nodes and edges last_node_id = None @@ -662,11 +720,11 @@ def _render_execution_graph(self, children_results: list[ExecutionResult], user_ elif node.get("output"): label += f"\nOutput: {str(node['output'])[:40]}" # Color coding - if node['node_type'] == 'error': + if node["node_type"] == "error": color = "#ffcccc" # red - elif node['node_type'] == 'classifier': + elif node["node_type"] == "classifier": color = "#99ccff" # blue - elif node['node_type'] == 'intent': + elif node["node_type"] == "intent": color = "#ccffcc" # green else: color = "#ccccff" # fallback @@ -675,18 +733,18 @@ def _render_execution_graph(self, children_results: list[ExecutionResult], user_ net.add_edge(last_node_id, node_id) last_node_id = node_id if not execution_paths: - net.add_node("no_path", label="No execution path", - color="#cccccc") + net.add_node("no_path", label="No execution path", color="#cccccc") # Save to HTML file html_dir = os.path.join(os.getcwd(), "intentkit_graphs") os.makedirs(html_dir, exist_ok=True) html_path = os.path.join( - html_dir, f"intent_graph_{abs(hash(user_input)) % 100000}.html") + html_dir, f"intent_graph_{abs(hash(user_input)) % 100000}.html" + ) # Generate HTML and write to file manually html_content = net.generate_html() - with open(html_path, 'w', encoding='utf-8') as f: + with open(html_path, "w", encoding="utf-8") as f: f.write(html_content) return html_path @@ -707,15 +765,17 @@ def _extract_execution_paths(self, result: ExecutionResult) -> list: paths = [] # Add current node - paths.append({ - "node_name": result.node_name, - "node_type": result.node_type, - "success": result.success, - "input": result.input, - "output": result.output, - "error": result.error, - "params": result.params - }) + paths.append( + { + "node_name": result.node_name, + "node_type": result.node_type, + "success": result.success, + "input": result.input, + "output": result.output, + "error": result.error, + "params": result.params, + } + ) # Recursively add children for child_result in result.children_results: @@ -724,7 +784,9 @@ def _extract_execution_paths(self, result: ExecutionResult) -> list: return paths - def _capture_context_state(self, context: IntentContext, label: str) -> Dict[str, Any]: + def _capture_context_state( + self, context: IntentContext, label: str + ) -> Dict[str, Any]: """ Capture the current state of the context for debugging without adding to history. @@ -735,14 +797,14 @@ def _capture_context_state(self, context: IntentContext, label: str) -> Dict[str Returns: Dictionary containing context state """ - state = { + state: Dict[str, Any] = { "timestamp": datetime.now().isoformat(), "label": label, "session_id": context.session_id, "fields": {}, "field_count": len(context.keys()), "history_count": len(context.get_history()), - "error_count": context.error_count() + "error_count": context.error_count(), } # Capture all field values directly from internal state to avoid GET operations @@ -754,16 +816,20 @@ def _capture_context_state(self, context: IntentContext, label: str) -> Dict[str "created_at": field.created_at, "last_modified": field.last_modified, "modified_by": field.modified_by, - "value": field.value - } - state["fields"][key] = { - "value": value, - "metadata": metadata + "value": field.value, } + state["fields"][key] = {"value": value, "metadata": metadata} return state - def _log_context_changes(self, state_before: Optional[Dict[str, Any]], state_after: Optional[Dict[str, Any]], node_name: str, debug: bool, context_trace: bool) -> None: + def _log_context_changes( + self, + state_before: Optional[Dict[str, Any]], + state_after: Optional[Dict[str, Any]], + node_name: str, + debug: bool, + context_trace: bool, + ) -> None: """ Log context changes between before and after node execution. @@ -783,22 +849,27 @@ def _log_context_changes(self, state_before: Optional[Dict[str, Any]], state_aft field_count_after = state_after.get("field_count", 0) if field_count_after > field_count_before: - new_fields = set(state_after["fields"].keys( - )) - set(state_before["fields"].keys()) + new_fields = set(state_after["fields"].keys()) - set( + state_before["fields"].keys() + ) self.logger.info( - f"Node '{node_name}' added {len(new_fields)} new context fields: {new_fields}") + f"Node '{node_name}' added {len(new_fields)} new context fields: {new_fields}" + ) elif field_count_after < field_count_before: - removed_fields = set( - state_before["fields"].keys()) - set(state_after["fields"].keys()) + removed_fields = set(state_before["fields"].keys()) - set( + state_after["fields"].keys() + ) self.logger.info( - f"Node '{node_name}' removed {len(removed_fields)} context fields: {removed_fields}") + f"Node '{node_name}' removed {len(removed_fields)} context fields: {removed_fields}" + ) # Detailed context tracing if context_trace: - self._log_detailed_context_trace( - state_before, state_after, node_name) + self._log_detailed_context_trace(state_before, state_after, node_name) - def _log_detailed_context_trace(self, state_before: Dict[str, Any], state_after: Dict[str, Any], node_name: str) -> None: + def _log_detailed_context_trace( + self, state_before: Dict[str, Any], state_after: Dict[str, Any], node_name: str + ) -> None: """ Log detailed context trace with field-level changes. @@ -813,24 +884,36 @@ def _log_detailed_context_trace(self, state_before: Dict[str, Any], state_after: # Find changed fields changed_fields = [] for key in set(fields_before.keys()) | set(fields_after.keys()): - value_before = fields_before.get(key, {}).get( - "value") if key in fields_before else None - value_after = fields_after.get(key, {}).get( - "value") if key in fields_after else None + value_before = ( + fields_before.get(key, {}).get("value") + if key in fields_before + else None + ) + value_after = ( + fields_after.get(key, {}).get("value") if key in fields_after else None + ) if value_before != value_after: - changed_fields.append({ - "key": key, - "before": value_before, - "after": value_after, - "action": "modified" if key in fields_before and key in fields_after else "added" if key in fields_after else "removed" - }) + changed_fields.append( + { + "key": key, + "before": value_before, + "after": value_after, + "action": ( + "modified" + if key in fields_before and key in fields_after + else "added" if key in fields_after else "removed" + ), + } + ) if changed_fields: self.logger.info(f"Context trace for node '{node_name}':") for change in changed_fields: self.logger.info( - f" {change['action'].upper()}: {change['key']} = {change['after']} (was: {change['before']})") + f" {change['action'].upper()}: {change['key']} = {change['after']} (was: {change['before']})" + ) else: self.logger.info( - f"Context trace for node '{node_name}': No changes detected") + f"Context trace for node '{node_name}': No changes detected" + ) diff --git a/intent_kit/graph/validation.py b/intent_kit/graph/validation.py index 838c77d..6c81414 100644 --- a/intent_kit/graph/validation.py +++ b/intent_kit/graph/validation.py @@ -5,7 +5,7 @@ and graph structure in intent graphs. """ -from typing import List, Set, Dict, Any, Optional +from typing import List, Dict, Any, Optional from intent_kit.node import TreeNode from intent_kit.node.enums import NodeType from intent_kit.utils.logger import Logger @@ -14,7 +14,13 @@ class GraphValidationError(Exception): """Exception raised when graph validation fails.""" - def __init__(self, message: str, node_name: Optional[str] = None, child_name: Optional[str] = None, child_type: Optional[NodeType] = None): + def __init__( + self, + message: str, + node_name: Optional[str] = None, + child_name: Optional[str] = None, + child_type: Optional[NodeType] = None, + ): self.message = message self.node_name = node_name self.child_name = child_name @@ -51,11 +57,12 @@ def validate_splitter_routing(graph_nodes: List[TreeNode]) -> None: message=error_msg, node_name=node.name, child_name=child.name, - child_type=child.node_type + child_type=child.node_type, ) else: logger.debug( - f" āœ“ Splitter '{node.name}' correctly routes to classifier '{child.name}'") + f" āœ“ Splitter '{node.name}' correctly routes to classifier '{child.name}'" + ) logger.info("Splitter routing validation passed āœ“") @@ -77,7 +84,7 @@ def validate_graph_structure(graph_nodes: List[TreeNode]) -> Dict[str, Any]: all_nodes = _collect_all_nodes(graph_nodes) # Count nodes by type - node_counts = {} + node_counts: Dict[Any, int] = {} for node in all_nodes: node_type = node.node_type node_counts[node_type] = node_counts.get(node_type, 0) + 1 @@ -102,11 +109,13 @@ def validate_graph_structure(graph_nodes: List[TreeNode]) -> Dict[str, Any]: "routing_valid": routing_valid, "has_cycles": has_cycles, "orphaned_nodes": [node.name for node in orphaned_nodes], - "orphaned_count": len(orphaned_nodes) + "orphaned_count": len(orphaned_nodes), } - logger.info(f"Graph validation complete: {stats['total_nodes']} total nodes, " - f"routing valid: {routing_valid}, cycles: {has_cycles}") + logger.info( + f"Graph validation complete: {stats['total_nodes']} total nodes, " + f"routing valid: {routing_valid}, cycles: {has_cycles}" + ) return stats @@ -189,9 +198,7 @@ def validate_node_types(nodes: List[TreeNode]) -> None: error_msg = f"Invalid node type '{node.node_type}' for node '{node.name}'. Valid types: {NodeType}" logger.error(error_msg) raise GraphValidationError( - message=error_msg, - node_name=node.name, - child_type=node.node_type + message=error_msg, node_name=node.name, child_type=node.node_type ) logger.info("Node type validation passed āœ“") diff --git a/intent_kit/handlers/node.py b/intent_kit/handlers/node.py index 4e0bab3..5bdc9fe 100644 --- a/intent_kit/handlers/node.py +++ b/intent_kit/handlers/node.py @@ -4,7 +4,10 @@ from intent_kit.context import IntentContext from intent_kit.context.dependencies import declare_dependencies from intent_kit.node.types import ExecutionResult, ExecutionError -from intent_kit.handlers.remediation import get_remediation_strategy, RemediationStrategy +from intent_kit.handlers.remediation import ( + get_remediation_strategy, + RemediationStrategy, +) class HandlerNode(TreeNode): @@ -22,8 +25,7 @@ def __init__( output_validator: Optional[Callable[[Any], bool]] = None, description: str = "", parent: Optional["TreeNode"] = None, - remediation_strategies: Optional[List[Union[str, - RemediationStrategy]]] = None + remediation_strategies: Optional[List[Union[str, RemediationStrategy]]] = None, ): super().__init__(name=name, description=description, children=[], parent=parent) self.param_schema = param_schema @@ -36,7 +38,7 @@ def __init__( self.context_dependencies = declare_dependencies( inputs=self.context_inputs, outputs=self.context_outputs, - description=f"Context dependencies for intent '{self.name}'" + description=f"Context dependencies for intent '{self.name}'", ) # Store remediation strategies @@ -47,17 +49,22 @@ def node_type(self) -> NodeType: """Get the type of this node.""" return NodeType.HANDLER - def execute(self, user_input: str, context: Optional[IntentContext] = None) -> ExecutionResult: + def execute( + self, user_input: str, context: Optional[IntentContext] = None + ) -> ExecutionResult: try: context_dict: Optional[Dict[str, Any]] = None if context: - context_dict = {key: context.get( - key) for key in self.context_inputs if context.has(key)} - extracted_params = self.arg_extractor( - user_input, context_dict or {}) + context_dict = { + key: context.get(key) + for key in self.context_inputs + if context.has(key) + } + extracted_params = self.arg_extractor(user_input, context_dict or {}) except Exception as e: self.logger.error( - f"Argument extraction failed for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Argument extraction failed for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) return ExecutionResult( success=False, node_name=self.name, @@ -69,16 +76,17 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type=type(e).__name__, message=str(e), node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params=None, - children_results=[] + children_results=[], ) if self.input_validator: try: if not self.input_validator(extracted_params): self.logger.error( - f"Input validation failed for intent '{self.name}' (Path: {'.'.join(self.get_path())})") + f"Input validation failed for intent '{self.name}' (Path: {'.'.join(self.get_path())})" + ) return ExecutionResult( success=False, node_name=self.name, @@ -90,14 +98,15 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type="InputValidationError", message="Input validation failed", node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params=extracted_params, - children_results=[] + children_results=[], ) except Exception as e: self.logger.error( - f"Input validation error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Input validation error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) return ExecutionResult( success=False, node_name=self.name, @@ -109,16 +118,17 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type=type(e).__name__, message=str(e), node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params=extracted_params, - children_results=[] + children_results=[], ) try: validated_params = self._validate_types(extracted_params) except Exception as e: self.logger.error( - f"Type validation error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Type validation error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) return ExecutionResult( success=False, node_name=self.name, @@ -130,10 +140,10 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type=type(e).__name__, message=str(e), node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params=extracted_params, - children_results=[] + children_results=[], ) try: if context is not None: @@ -142,21 +152,22 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E output = self.handler(**validated_params) except Exception as e: self.logger.error( - f"Handler execution error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Handler execution error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) # Try remediation strategies error = ExecutionError( error_type=type(e).__name__, message=str(e), node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ) remediation_result = self._execute_remediation_strategies( user_input=user_input, context=context, original_error=error, - validated_params=validated_params + validated_params=validated_params, ) if remediation_result: @@ -172,13 +183,14 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E output=None, error=error, params=validated_params, - children_results=[] + children_results=[], ) if self.output_validator: try: if not self.output_validator(output): self.logger.error( - f"Output validation failed for intent '{self.name}' (Path: {'.'.join(self.get_path())})") + f"Output validation failed for intent '{self.name}' (Path: {'.'.join(self.get_path())})" + ) return ExecutionResult( success=False, node_name=self.name, @@ -190,14 +202,15 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type="OutputValidationError", message="Output validation failed", node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params=validated_params, - children_results=[] + children_results=[], ) except Exception as e: self.logger.error( - f"Output validation error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Output validation error for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) return ExecutionResult( success=False, node_name=self.name, @@ -209,10 +222,10 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type=type(e).__name__, message=str(e), node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params=validated_params, - children_results=[] + children_results=[], ) return ExecutionResult( success=True, @@ -223,7 +236,7 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E output=output, error=None, params=validated_params, - children_results=[] + children_results=[], ) def _execute_remediation_strategies( @@ -231,7 +244,7 @@ def _execute_remediation_strategies( user_input: str, context: Optional[IntentContext] = None, original_error: Optional[ExecutionError] = None, - validated_params: Optional[Dict[str, Any]] = None + validated_params: Optional[Dict[str, Any]] = None, ) -> Optional[ExecutionResult]: """Execute remediation strategies in order until one succeeds.""" if not self.remediation_strategies: @@ -245,14 +258,16 @@ def _execute_remediation_strategies( strategy = get_remediation_strategy(strategy_item) if not strategy: self.logger.warning( - f"Remediation strategy '{strategy_item}' not found in registry") + f"Remediation strategy '{strategy_item}' not found in registry" + ) continue elif isinstance(strategy_item, RemediationStrategy): # Direct strategy object strategy = strategy_item else: self.logger.warning( - f"Invalid remediation strategy type: {type(strategy_item)}") + f"Invalid remediation strategy type: {type(strategy_item)}" + ) continue try: @@ -262,18 +277,21 @@ def _execute_remediation_strategies( context=context, original_error=original_error, handler_func=self.handler, - validated_params=validated_params + validated_params=validated_params, ) if result and result.success: self.logger.info( - f"Remediation strategy '{strategy.name}' succeeded for {self.name}") + f"Remediation strategy '{strategy.name}' succeeded for {self.name}" + ) return result else: self.logger.warning( - f"Remediation strategy '{strategy.name}' failed for {self.name}") + f"Remediation strategy '{strategy.name}' failed for {self.name}" + ) except Exception as e: self.logger.error( - f"Remediation strategy '{strategy.name}' error for {self.name}: {type(e).__name__}: {str(e)}") + f"Remediation strategy '{strategy.name}' error for {self.name}: {type(e).__name__}: {str(e)}" + ) self.logger.error(f"All remediation strategies failed for {self.name}") return None @@ -283,38 +301,47 @@ def _validate_types(self, params: Dict[str, Any]) -> Dict[str, Any]: for param_name, expected_type in self.param_schema.items(): if param_name not in params: self.logger.error( - f"Missing required parameter '{param_name}' for intent '{self.name}' (Path: {'.'.join(self.get_path())})") + f"Missing required parameter '{param_name}' for intent '{self.name}' (Path: {'.'.join(self.get_path())})" + ) raise Exception(f"Missing required parameter '{param_name}'") param_value = params[param_name] - if expected_type == str: + if isinstance(expected_type, type) and expected_type is str: if not isinstance(param_value, str): self.logger.error( - f"Parameter '{param_name}' must be a string, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())})") + f"Parameter '{param_name}' must be a string, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())})" + ) raise Exception( - f"Parameter '{param_name}' must be a string, got {type(param_value).__name__}") - elif expected_type == int: + f"Parameter '{param_name}' must be a string, got {type(param_value).__name__}" + ) + elif isinstance(expected_type, type) and expected_type is int: try: param_value = int(param_value) except (ValueError, TypeError) as e: self.logger.error( - f"Parameter '{param_name}' must be an integer, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Parameter '{param_name}' must be an integer, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) raise Exception( - f"Parameter '{param_name}' must be an integer, got {type(param_value).__name__}: {type(e).__name__}: {str(e)}") - elif expected_type == float: + f"Parameter '{param_name}' must be an integer, got {type(param_value).__name__}: {type(e).__name__}: {str(e)}" + ) + elif isinstance(expected_type, type) and expected_type is float: try: param_value = float(param_value) except (ValueError, TypeError) as e: self.logger.error( - f"Parameter '{param_name}' must be a number, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}") + f"Parameter '{param_name}' must be a number, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())}): {type(e).__name__}: {str(e)}" + ) raise Exception( - f"Parameter '{param_name}' must be a number, got {type(param_value).__name__}: {type(e).__name__}: {str(e)}") - elif expected_type == bool: + f"Parameter '{param_name}' must be a number, got {type(param_value).__name__}: {type(e).__name__}: {str(e)}" + ) + elif isinstance(expected_type, type) and expected_type is bool: if isinstance(param_value, str): - param_value = param_value.lower() in ('true', '1', 'yes', 'on') + param_value = param_value.lower() in ("true", "1", "yes", "on") elif not isinstance(param_value, bool): self.logger.error( - f"Parameter '{param_name}' must be a boolean, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())})") + f"Parameter '{param_name}' must be a boolean, got {type(param_value).__name__} for intent '{self.name}' (Path: {'.'.join(self.get_path())})" + ) raise Exception( - f"Parameter '{param_name}' must be a boolean, got {type(param_value).__name__}") + f"Parameter '{param_name}' must be a boolean, got {type(param_value).__name__}" + ) validated_params[param_name] = param_value return validated_params diff --git a/intent_kit/handlers/remediation.py b/intent_kit/handlers/remediation.py index ca571a9..8c1f8ff 100644 --- a/intent_kit/handlers/remediation.py +++ b/intent_kit/handlers/remediation.py @@ -29,7 +29,7 @@ def execute( user_input: str, context: Optional[IntentContext] = None, original_error: Optional[ExecutionError] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """ Execute the remediation strategy. @@ -51,8 +51,10 @@ class RetryOnFailStrategy(RemediationStrategy): """Simple retry strategy with exponential backoff.""" def __init__(self, max_attempts: int = 3, base_delay: float = 1.0): - super().__init__("retry_on_fail", - f"Retry up to {max_attempts} times with exponential backoff") + super().__init__( + "retry_on_fail", + f"Retry up to {max_attempts} times with exponential backoff", + ) self.max_attempts = max_attempts self.base_delay = base_delay @@ -64,18 +66,20 @@ def execute( original_error: Optional[ExecutionError] = None, handler_func: Optional[Callable] = None, validated_params: Optional[Dict[str, Any]] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Retry the handler function with the same parameters.""" if not handler_func or validated_params is None: self.logger.warning( - f"RetryOnFailStrategy: Missing handler_func or validated_params for {node_name}") + f"RetryOnFailStrategy: Missing handler_func or validated_params for {node_name}" + ) return None for attempt in range(1, self.max_attempts + 1): try: self.logger.info( - f"RetryOnFailStrategy: Attempt {attempt}/{self.max_attempts} for {node_name}") + f"RetryOnFailStrategy: Attempt {attempt}/{self.max_attempts} for {node_name}" + ) # Add context if available if context is not None: @@ -84,7 +88,8 @@ def execute( output = handler_func(**validated_params) self.logger.info( - f"RetryOnFailStrategy: Success on attempt {attempt} for {node_name}") + f"RetryOnFailStrategy: Success on attempt {attempt} for {node_name}" + ) return ExecutionResult( success=True, @@ -95,22 +100,26 @@ def execute( output=output, error=None, params=validated_params, - children_results=[] + children_results=[], ) except Exception as e: self.logger.warning( - f"RetryOnFailStrategy: Attempt {attempt} failed for {node_name}: {type(e).__name__}: {str(e)}") + f"RetryOnFailStrategy: Attempt {attempt} failed for {node_name}: {type(e).__name__}: {str(e)}" + ) if attempt < self.max_attempts: - delay = self.base_delay * \ - (2 ** (attempt - 1)) # Exponential backoff + delay = self.base_delay * ( + 2 ** (attempt - 1) + ) # Exponential backoff self.logger.info( - f"RetryOnFailStrategy: Waiting {delay}s before retry") + f"RetryOnFailStrategy: Waiting {delay}s before retry" + ) time.sleep(delay) self.logger.error( - f"RetryOnFailStrategy: All {self.max_attempts} attempts failed for {node_name}") + f"RetryOnFailStrategy: All {self.max_attempts} attempts failed for {node_name}" + ) return None @@ -118,8 +127,7 @@ class FallbackToAnotherNodeStrategy(RemediationStrategy): """Fallback to a specified alternative handler.""" def __init__(self, fallback_handler: Callable, fallback_name: str = "fallback"): - super().__init__("fallback_to_another_node", - f"Fallback to {fallback_name}") + super().__init__("fallback_to_another_node", f"Fallback to {fallback_name}") self.fallback_handler = fallback_handler self.fallback_name = fallback_name @@ -130,25 +138,26 @@ def execute( context: Optional[IntentContext] = None, original_error: Optional[ExecutionError] = None, validated_params: Optional[Dict[str, Any]] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Execute the fallback handler.""" try: self.logger.info( - f"FallbackToAnotherNodeStrategy: Executing {self.fallback_name} for {node_name}") + f"FallbackToAnotherNodeStrategy: Executing {self.fallback_name} for {node_name}" + ) # Use the same parameters if possible, otherwise use minimal params if validated_params is not None: if context is not None: - output = self.fallback_handler( - **validated_params, context=context) + output = self.fallback_handler(**validated_params, context=context) else: output = self.fallback_handler(**validated_params) else: # Minimal fallback with just the input if context is not None: output = self.fallback_handler( - user_input=user_input, context=context) + user_input=user_input, context=context + ) else: output = self.fallback_handler(user_input=user_input) @@ -161,7 +170,7 @@ def execute( output=output, error=None, params=validated_params or {}, - children_results=[] + children_results=[], ) except Exception as e: @@ -175,8 +184,9 @@ class SelfReflectStrategy(RemediationStrategy): """LLM critiques its own output and retries with improved approach.""" def __init__(self, llm_config: Dict[str, Any], max_reflections: int = 2): - super().__init__("self_reflect", - f"LLM self-reflection with up to {max_reflections} attempts") + super().__init__( + "self_reflect", f"LLM self-reflection with up to {max_reflections} attempts" + ) self.llm_config = llm_config self.max_reflections = max_reflections @@ -188,21 +198,24 @@ def execute( original_error: Optional[ExecutionError] = None, handler_func: Optional[Callable] = None, validated_params: Optional[Dict[str, Any]] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Use LLM to critique and improve the approach.""" if not handler_func or validated_params is None: self.logger.warning( - f"SelfReflectStrategy: Missing handler_func or validated_params for {node_name}") + f"SelfReflectStrategy: Missing handler_func or validated_params for {node_name}" + ) return None from intent_kit.services.llm_factory import LLMFactory + llm_client = LLMFactory.create_client(self.llm_config) for reflection in range(self.max_reflections): try: self.logger.info( - f"SelfReflectStrategy: Reflection {reflection + 1}/{self.max_reflections} for {node_name}") + f"SelfReflectStrategy: Reflection {reflection + 1}/{self.max_reflections} for {node_name}" + ) # Create reflection prompt reflection_prompt = f""" @@ -229,23 +242,24 @@ def execute( reflection_response = llm_client.generate(reflection_prompt) try: - reflection_data = extract_json_from_text( - reflection_response) or {} + reflection_data = extract_json_from_text(reflection_response) or {} self.logger.info( - f"SelfReflectStrategy: LLM reflection for {node_name}: {reflection_data.get('analysis', 'No analysis')}") + f"SelfReflectStrategy: LLM reflection for {node_name}: {reflection_data.get('analysis', 'No analysis')}" + ) # Try with modified parameters if suggested modified_params = reflection_data.get( - 'modified_params', validated_params) + "modified_params", validated_params + ) if context is not None: - output = handler_func( - **modified_params, context=context) + output = handler_func(**modified_params, context=context) else: output = handler_func(**modified_params) self.logger.info( - f"SelfReflectStrategy: Success after reflection {reflection + 1} for {node_name}") + f"SelfReflectStrategy: Success after reflection {reflection + 1} for {node_name}" + ) return ExecutionResult( success=True, @@ -256,16 +270,16 @@ def execute( output=output, error=None, params=modified_params, - children_results=[] + children_results=[], ) except json.JSONDecodeError: self.logger.warning( - f"SelfReflectStrategy: Invalid JSON response from LLM for {node_name}") + f"SelfReflectStrategy: Invalid JSON response from LLM for {node_name}" + ) # Try with original parameters as fallback if context is not None: - output = handler_func( - **validated_params, context=context) + output = handler_func(**validated_params, context=context) else: output = handler_func(**validated_params) @@ -278,15 +292,17 @@ def execute( output=output, error=None, params=validated_params, - children_results=[] + children_results=[], ) except Exception as e: self.logger.warning( - f"SelfReflectStrategy: Reflection {reflection + 1} failed for {node_name}: {type(e).__name__}: {str(e)}") + f"SelfReflectStrategy: Reflection {reflection + 1} failed for {node_name}: {type(e).__name__}: {str(e)}" + ) self.logger.error( - f"SelfReflectStrategy: All {self.max_reflections} reflections failed for {node_name}") + f"SelfReflectStrategy: All {self.max_reflections} reflections failed for {node_name}" + ) return None @@ -294,8 +310,10 @@ class ConsensusVoteStrategy(RemediationStrategy): """Ensemble voting among multiple LLM approaches.""" def __init__(self, llm_configs: List[Dict[str, Any]], vote_threshold: float = 0.6): - super().__init__("consensus_vote", - f"Ensemble voting with {len(llm_configs)} models, threshold {vote_threshold}") + super().__init__( + "consensus_vote", + f"Ensemble voting with {len(llm_configs)} models, threshold {vote_threshold}", + ) self.llm_configs = llm_configs self.vote_threshold = vote_threshold @@ -307,12 +325,13 @@ def execute( original_error: Optional[ExecutionError] = None, handler_func: Optional[Callable] = None, validated_params: Optional[Dict[str, Any]] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Use multiple LLMs to vote on the best approach.""" if not handler_func or validated_params is None: self.logger.warning( - f"ConsensusVoteStrategy: Missing handler_func or validated_params for {node_name}") + f"ConsensusVoteStrategy: Missing handler_func or validated_params for {node_name}" + ) return None from intent_kit.services.llm_factory import LLMFactory @@ -349,7 +368,8 @@ def execute( for i, llm_config in enumerate(self.llm_configs): try: self.logger.info( - f"ConsensusVoteStrategy: Getting vote {i + 1}/{len(self.llm_configs)} for {node_name}") + f"ConsensusVoteStrategy: Getting vote {i + 1}/{len(self.llm_configs)} for {node_name}" + ) llm_client = LLMFactory.create_client(llm_config) vote_response = llm_client.generate(voting_prompt) @@ -358,7 +378,7 @@ def execute( vote_data = extract_json_from_text(vote_response) or {} # Ensure modified_params is properly structured - modified_params = vote_data.get('modified_params', {}) + modified_params = vote_data.get("modified_params", {}) if not isinstance(modified_params, dict): modified_params = {} @@ -370,21 +390,24 @@ def execute( for key, original_value in validated_params.items(): if key in final_params: new_value = final_params[key] - if isinstance(original_value, int) and isinstance(new_value, str): + if isinstance(original_value, int) and isinstance( + new_value, str + ): try: # Try to convert string to int final_params[key] = int(new_value) except (ValueError, TypeError): # If conversion fails, try to evaluate simple expressions - if new_value == 'abs(x)': + if new_value == "abs(x)": final_params[key] = abs(original_value) - elif new_value == 'max(0, x)': - final_params[key] = max( - 0, original_value) + elif new_value == "max(0, x)": + final_params[key] = max(0, original_value) else: # Keep original value if conversion fails final_params[key] = original_value - elif isinstance(original_value, float) and isinstance(new_value, str): + elif isinstance(original_value, float) and isinstance( + new_value, str + ): try: final_params[key] = float(new_value) except (ValueError, TypeError): @@ -393,55 +416,69 @@ def execute( # Apply automatic parameter modifications if LLM didn't suggest any if not modified_params: for key, original_value in validated_params.items(): - if isinstance(original_value, (int, float)) and original_value < 0: + if ( + isinstance(original_value, (int, float)) + and original_value < 0 + ): # For negative numbers, use absolute value final_params[key] = abs(original_value) - votes.append({ - 'model': f"model_{i}", - 'approach': vote_data.get('approach', 'unknown'), - 'confidence': vote_data.get('confidence', 0.5), - 'modified_params': final_params, - 'reasoning': vote_data.get('reasoning', 'No reasoning provided') - }) + votes.append( + { + "model": f"model_{i}", + "approach": vote_data.get("approach", "unknown"), + "confidence": vote_data.get("confidence", 0.5), + "modified_params": final_params, + "reasoning": vote_data.get( + "reasoning", "No reasoning provided" + ), + } + ) successful_votes += 1 except json.JSONDecodeError: self.logger.warning( - f"ConsensusVoteStrategy: Invalid JSON from model {i} for {node_name}") + f"ConsensusVoteStrategy: Invalid JSON from model {i} for {node_name}" + ) except Exception as e: self.logger.warning( - f"ConsensusVoteStrategy: Model {i} failed for {node_name}: {type(e).__name__}: {str(e)}") + f"ConsensusVoteStrategy: Model {i} failed for {node_name}: {type(e).__name__}: {str(e)}" + ) if not votes: self.logger.error( - f"ConsensusVoteStrategy: No successful votes for {node_name}") + f"ConsensusVoteStrategy: No successful votes for {node_name}" + ) return None # Calculate consensus - total_confidence = sum(vote['confidence'] for vote in votes) + total_confidence = sum(vote["confidence"] for vote in votes) avg_confidence = total_confidence / len(votes) self.logger.info( - f"ConsensusVoteStrategy: {successful_votes}/{len(self.llm_configs)} models voted for {node_name}, avg confidence: {avg_confidence:.2f}") + f"ConsensusVoteStrategy: {successful_votes}/{len(self.llm_configs)} models voted for {node_name}, avg confidence: {avg_confidence:.2f}" + ) if avg_confidence >= self.vote_threshold: # Use the highest confidence vote - best_vote = max(votes, key=lambda v: v['confidence']) + best_vote = max(votes, key=lambda v: v["confidence"]) try: self.logger.info( - f"ConsensusVoteStrategy: Attempting execution with params: {best_vote['modified_params']}") + f"ConsensusVoteStrategy: Attempting execution with params: {best_vote['modified_params']}" + ) if context is not None: output = handler_func( - **best_vote['modified_params'], context=context) + **best_vote["modified_params"], context=context + ) else: - output = handler_func(**best_vote['modified_params']) + output = handler_func(**best_vote["modified_params"]) self.logger.info( - f"ConsensusVoteStrategy: Success with consensus approach for {node_name}") + f"ConsensusVoteStrategy: Success with consensus approach for {node_name}" + ) return ExecutionResult( success=True, @@ -451,27 +488,34 @@ def execute( input=user_input, output=output, error=None, - params=best_vote['modified_params'], - children_results=[] + params=best_vote["modified_params"], + children_results=[], ) except Exception as e: self.logger.error( - f"ConsensusVoteStrategy: Execution failed despite consensus for {node_name}: {type(e).__name__}: {str(e)}") + f"ConsensusVoteStrategy: Execution failed despite consensus for {node_name}: {type(e).__name__}: {str(e)}" + ) self.logger.error( - f"ConsensusVoteStrategy: Params that caused failure: {best_vote['modified_params']}") + f"ConsensusVoteStrategy: Params that caused failure: {best_vote['modified_params']}" + ) self.logger.error( - f"ConsensusVoteStrategy: Insufficient confidence ({avg_confidence:.2f} < {self.vote_threshold}) for {node_name}") + f"ConsensusVoteStrategy: Insufficient confidence ({avg_confidence:.2f} < {self.vote_threshold}) for {node_name}" + ) return None class RetryWithAlternatePromptStrategy(RemediationStrategy): """Retry with modified prompt template.""" - def __init__(self, llm_config: Dict[str, Any], alternate_prompts: Optional[List[str]] = None): - super().__init__("retry_with_alternate_prompt", - f"Retry with {len(alternate_prompts) if alternate_prompts else 'default'} alternate prompts") + def __init__( + self, llm_config: Dict[str, Any], alternate_prompts: Optional[List[str]] = None + ): + super().__init__( + "retry_with_alternate_prompt", + f"Retry with {len(alternate_prompts) if alternate_prompts else 'default'} alternate prompts", + ) self.llm_config = llm_config if alternate_prompts is not None and isinstance(alternate_prompts, list): self.alternate_prompts = alternate_prompts @@ -480,7 +524,7 @@ def __init__(self, llm_config: Dict[str, Any], alternate_prompts: Optional[List[ "Try with absolute value: {user_input}", "Try with positive number: {user_input}", "Try with default value: {user_input}", - "Try with zero: {user_input}" + "Try with zero: {user_input}", ] def execute( @@ -491,37 +535,47 @@ def execute( original_error: Optional[ExecutionError] = None, handler_func: Optional[Callable] = None, validated_params: Optional[Dict[str, Any]] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Try different parameter modifications.""" if not handler_func or validated_params is None: self.logger.warning( - f"RetryWithAlternatePromptStrategy: Missing handler_func or validated_params for {node_name}") + f"RetryWithAlternatePromptStrategy: Missing handler_func or validated_params for {node_name}" + ) return None - from intent_kit.services.llm_factory import LLMFactory - llm_client = LLMFactory.create_client(self.llm_config) - # Try different parameter modification strategies modification_strategies = [ # Strategy 1: Try with absolute values for numeric parameters - lambda params: {k: abs(v) if isinstance( - v, (int, float)) else v for k, v in params.items()}, + lambda params: { + k: abs(v) if isinstance(v, (int, float)) else v + for k, v in params.items() + }, # Strategy 2: Try with positive values for numeric parameters - lambda params: {k: max(0, v) if isinstance( - v, (int, float)) else v for k, v in params.items()}, + lambda params: { + k: max(0, v) if isinstance(v, (int, float)) else v + for k, v in params.items() + }, # Strategy 3: Try with default values (1 for numbers, empty string for strings) - lambda params: {k: (1 if isinstance(v, (int, float)) else "") if v is None or ( - isinstance(v, (int, float)) and v < 0) else v for k, v in params.items()}, + lambda params: { + k: ( + (1 if isinstance(v, (int, float)) else "") + if v is None or (isinstance(v, (int, float)) and v < 0) + else v + ) + for k, v in params.items() + }, # Strategy 4: Try with zero for numeric parameters - lambda params: {k: 0 if isinstance( - v, (int, float)) else v for k, v in params.items()} + lambda params: { + k: 0 if isinstance(v, (int, float)) else v for k, v in params.items() + }, ] for i, strategy in enumerate(modification_strategies): try: self.logger.info( - f"RetryWithAlternatePromptStrategy: Trying modification strategy {i + 1}/{len(modification_strategies)} for {node_name}") + f"RetryWithAlternatePromptStrategy: Trying modification strategy {i + 1}/{len(modification_strategies)} for {node_name}" + ) # Apply the modification strategy modified_params = strategy(validated_params) @@ -532,7 +586,8 @@ def execute( output = handler_func(**modified_params) self.logger.info( - f"RetryWithAlternatePromptStrategy: Success with strategy {i + 1} for {node_name}") + f"RetryWithAlternatePromptStrategy: Success with strategy {i + 1} for {node_name}" + ) return ExecutionResult( success=True, @@ -543,15 +598,17 @@ def execute( output=output, error=None, params=modified_params, - children_results=[] + children_results=[], ) except Exception as e: self.logger.warning( - f"RetryWithAlternatePromptStrategy: Strategy {i + 1} failed for {node_name}: {type(e).__name__}: {str(e)}") + f"RetryWithAlternatePromptStrategy: Strategy {i + 1} failed for {node_name}: {type(e).__name__}: {str(e)}" + ) self.logger.error( - f"RetryWithAlternatePromptStrategy: All {len(modification_strategies)} strategies failed for {node_name}") + f"RetryWithAlternatePromptStrategy: All {len(modification_strategies)} strategies failed for {node_name}" + ) return None @@ -599,43 +656,52 @@ def list_remediation_strategies() -> List[str]: return _remediation_registry.list_strategies() -def create_retry_strategy(max_attempts: int = 3, base_delay: float = 1.0) -> RemediationStrategy: +def create_retry_strategy( + max_attempts: int = 3, base_delay: float = 1.0 +) -> RemediationStrategy: """Create a retry strategy with specified parameters.""" - strategy = RetryOnFailStrategy( - max_attempts=max_attempts, base_delay=base_delay) + strategy = RetryOnFailStrategy(max_attempts=max_attempts, base_delay=base_delay) register_remediation_strategy("retry_on_fail", strategy) return strategy -def create_fallback_strategy(fallback_handler: Callable, fallback_name: str = "fallback") -> RemediationStrategy: +def create_fallback_strategy( + fallback_handler: Callable, fallback_name: str = "fallback" +) -> RemediationStrategy: """Create a fallback strategy with specified handler.""" strategy = FallbackToAnotherNodeStrategy(fallback_handler, fallback_name) register_remediation_strategy("fallback_to_another_node", strategy) return strategy -def create_self_reflect_strategy(llm_config: Dict[str, Any], max_reflections: int = 2) -> RemediationStrategy: +def create_self_reflect_strategy( + llm_config: Dict[str, Any], max_reflections: int = 2 +) -> RemediationStrategy: """Create a self-reflection strategy with specified LLM config.""" strategy = SelfReflectStrategy(llm_config, max_reflections) register_remediation_strategy("self_reflect", strategy) return strategy -def create_consensus_vote_strategy(llm_configs: List[Dict[str, Any]], vote_threshold: float = 0.6) -> RemediationStrategy: +def create_consensus_vote_strategy( + llm_configs: List[Dict[str, Any]], vote_threshold: float = 0.6 +) -> RemediationStrategy: """Create a consensus voting strategy with multiple LLM configs.""" strategy = ConsensusVoteStrategy(llm_configs, vote_threshold) register_remediation_strategy("consensus_vote", strategy) return strategy -def create_alternate_prompt_strategy(llm_config: Dict[str, Any], alternate_prompts: Optional[List[str]] = None) -> RemediationStrategy: +def create_alternate_prompt_strategy( + llm_config: Dict[str, Any], alternate_prompts: Optional[List[str]] = None +) -> RemediationStrategy: """Create an alternate prompt strategy with specified prompts.""" if alternate_prompts is None: alternate_prompts = [ "Please try a different approach: {user_input}", "Consider this alternative perspective: {user_input}", "Let's approach this step by step: {user_input}", - "Think about this from a different angle: {user_input}" + "Think about this from a different angle: {user_input}", ] strategy = RetryWithAlternatePromptStrategy(llm_config, alternate_prompts) register_remediation_strategy("retry_with_alternate_prompt", strategy) @@ -645,13 +711,16 @@ def create_alternate_prompt_strategy(llm_config: Dict[str, Any], alternate_promp # Initialize built-in strategies create_retry_strategy() create_fallback_strategy( - lambda **kwargs: "Fallback handler executed", "default_fallback") + lambda **kwargs: "Fallback handler executed", "default_fallback" +) class ClassifierFallbackStrategy(RemediationStrategy): """Fallback strategy for classifiers that tries alternative classification methods.""" - def __init__(self, fallback_classifier: Callable, fallback_name: str = "fallback_classifier"): + def __init__( + self, fallback_classifier: Callable, fallback_name: str = "fallback_classifier" + ): super().__init__("classifier_fallback", f"Fallback to {fallback_name}") self.fallback_classifier = fallback_classifier self.fallback_name = fallback_name @@ -664,29 +733,33 @@ def execute( original_error: Optional[ExecutionError] = None, classifier_func: Optional[Callable] = None, available_children: Optional[List] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Execute the fallback classifier.""" try: self.logger.info( - f"ClassifierFallbackStrategy: Executing {self.fallback_name} for {node_name}") + f"ClassifierFallbackStrategy: Executing {self.fallback_name} for {node_name}" + ) if not available_children: self.logger.warning( - f"ClassifierFallbackStrategy: No available children for {node_name}") + f"ClassifierFallbackStrategy: No available children for {node_name}" + ) return None # Try the fallback classifier - context_dict = {} + context_dict: dict = {} if context: context_dict = {} chosen = self.fallback_classifier( - user_input, available_children, context_dict) + user_input, available_children, context_dict + ) if not chosen: self.logger.warning( - f"ClassifierFallbackStrategy: Fallback classifier failed for {node_name}") + f"ClassifierFallbackStrategy: Fallback classifier failed for {node_name}" + ) return None # Execute the chosen child @@ -703,9 +776,9 @@ def execute( params={ "chosen_child": chosen.name, "available_children": [child.name for child in available_children], - "remediation_strategy": self.name + "remediation_strategy": self.name, }, - children_results=[child_result] + children_results=[child_result], ) except Exception as e: @@ -729,16 +802,18 @@ def execute( original_error: Optional[ExecutionError] = None, classifier_func: Optional[Callable] = None, available_children: Optional[List] = None, - **kwargs + **kwargs, ) -> Optional[ExecutionResult]: """Use keyword matching as fallback classification.""" try: self.logger.info( - f"KeywordFallbackStrategy: Using keyword fallback for {node_name}") + f"KeywordFallbackStrategy: Using keyword fallback for {node_name}" + ) if not available_children: self.logger.warning( - f"KeywordFallbackStrategy: No available children for {node_name}") + f"KeywordFallbackStrategy: No available children for {node_name}" + ) return None user_input_lower = user_input.lower() @@ -748,7 +823,8 @@ def execute( # Check handler name if child.name and child.name.lower() in user_input_lower: self.logger.info( - f"KeywordFallbackStrategy: Matched '{child.name}' by name for {node_name}") + f"KeywordFallbackStrategy: Matched '{child.name}' by name for {node_name}" + ) child_result = child.execute(user_input, context) return ExecutionResult( success=True, @@ -762,22 +838,27 @@ def execute( "chosen_child": child.name, "available_children": [c.name for c in available_children], "remediation_strategy": self.name, - "match_type": "name" + "match_type": "name", }, - children_results=[child_result] + children_results=[child_result], ) # Check description keywords if child.description: desc_lower = child.description.lower() # Extract meaningful words from description - desc_words = [word for word in desc_lower.split() - if len(word) > 3 and word not in ['the', 'and', 'for', 'with', 'this', 'that']] + desc_words = [ + word + for word in desc_lower.split() + if len(word) > 3 + and word not in ["the", "and", "for", "with", "this", "that"] + ] for word in desc_words: if word in user_input_lower: self.logger.info( - f"KeywordFallbackStrategy: Matched '{child.name}' by description keyword '{word}' for {node_name}") + f"KeywordFallbackStrategy: Matched '{child.name}' by description keyword '{word}' for {node_name}" + ) child_result = child.execute(user_input, context) return ExecutionResult( success=True, @@ -789,16 +870,19 @@ def execute( error=None, params={ "chosen_child": child.name, - "available_children": [c.name for c in available_children], + "available_children": [ + c.name for c in available_children + ], "remediation_strategy": self.name, "match_type": "description", - "matched_keyword": word + "matched_keyword": word, }, - children_results=[child_result] + children_results=[child_result], ) self.logger.warning( - f"KeywordFallbackStrategy: No keyword match found for {node_name}") + f"KeywordFallbackStrategy: No keyword match found for {node_name}" + ) return None except Exception as e: @@ -808,7 +892,9 @@ def execute( return None -def create_classifier_fallback_strategy(fallback_classifier: Callable, fallback_name: str = "fallback_classifier") -> RemediationStrategy: +def create_classifier_fallback_strategy( + fallback_classifier: Callable, fallback_name: str = "fallback_classifier" +) -> RemediationStrategy: """Create a classifier fallback strategy with specified classifier.""" strategy = ClassifierFallbackStrategy(fallback_classifier, fallback_name) register_remediation_strategy("classifier_fallback", strategy) diff --git a/intent_kit/node/base.py b/intent_kit/node/base.py index 7527c97..b54b9b9 100644 --- a/intent_kit/node/base.py +++ b/intent_kit/node/base.py @@ -1,5 +1,5 @@ import uuid -from typing import Any, Callable, List, Optional, Dict, Type, Set, Sequence +from typing import List, Optional from abc import ABC, abstractmethod from intent_kit.utils.logger import Logger from intent_kit.context import IntentContext @@ -21,7 +21,7 @@ def has_name(self) -> bool: def get_path(self) -> List[str]: path = [] - node = self + node: Optional["Node"] = self while node: path.append(node.name) node = node.parent @@ -32,7 +32,7 @@ def get_path_string(self) -> str: def get_uuid_path(self) -> List[str]: path = [] - node = self + node: Optional["Node"] = self while node: path.append(node.node_id) node = node.parent @@ -45,7 +45,14 @@ def get_uuid_path_string(self) -> str: class TreeNode(Node, ABC): """Base class for all nodes in the intent tree.""" - def __init__(self, *, name: Optional[str] = None, description: str, children: Optional[List["TreeNode"]] = None, parent: Optional["TreeNode"] = None): + def __init__( + self, + *, + name: Optional[str] = None, + description: str, + children: Optional[List["TreeNode"]] = None, + parent: Optional["TreeNode"] = None, + ): super().__init__(name=name, parent=parent) self.logger = Logger(name or "unnamed_node") self.description = description @@ -59,6 +66,8 @@ def node_type(self) -> NodeType: return NodeType.UNKNOWN @abstractmethod - def execute(self, user_input: str, context: Optional[IntentContext] = None) -> ExecutionResult: + def execute( + self, user_input: str, context: Optional[IntentContext] = None + ) -> ExecutionResult: """Execute the node with the given user input and optional context.""" pass diff --git a/intent_kit/node/enums.py b/intent_kit/node/enums.py index d9d4f87..6a0c746 100644 --- a/intent_kit/node/enums.py +++ b/intent_kit/node/enums.py @@ -1,6 +1,7 @@ """ Enums for the node system. """ + from enum import Enum diff --git a/intent_kit/node/types.py b/intent_kit/node/types.py index 9586a56..419ec53 100644 --- a/intent_kit/node/types.py +++ b/intent_kit/node/types.py @@ -1,6 +1,7 @@ """ Data classes and types for the node system. """ + from dataclasses import dataclass from typing import Any, Dict, List, Optional from intent_kit.node.enums import NodeType @@ -9,6 +10,7 @@ @dataclass class ExecutionError: """Structured error information for execution results.""" + error_type: str message: str node_name: str @@ -20,27 +22,32 @@ class ExecutionError: original_exception: Optional[Exception] = None @classmethod - def from_exception(cls, exception: Exception, node_name: str, node_path: List[str], - node_id: Optional[str] = None) -> "ExecutionError": + def from_exception( + cls, + exception: Exception, + node_name: str, + node_path: List[str], + node_id: Optional[str] = None, + ) -> "ExecutionError": """Create an ExecutionError from an exception.""" - if hasattr(exception, 'validation_error'): + if hasattr(exception, "validation_error"): return cls( error_type=type(exception).__name__, - message=getattr(exception, 'validation_error', str(exception)), + message=getattr(exception, "validation_error", str(exception)), node_name=node_name, node_path=node_path, node_id=node_id, - input_data=getattr(exception, 'input_data', None), - params=getattr(exception, 'input_data', None) + input_data=getattr(exception, "input_data", None), + params=getattr(exception, "input_data", None), ) - elif hasattr(exception, 'error_message'): + elif hasattr(exception, "error_message"): return cls( error_type=type(exception).__name__, - message=getattr(exception, 'error_message', str(exception)), + message=getattr(exception, "error_message", str(exception)), node_name=node_name, node_path=node_path, node_id=node_id, - params=getattr(exception, 'params', None) + params=getattr(exception, "params", None), ) else: return cls( @@ -49,7 +56,7 @@ def from_exception(cls, exception: Exception, node_name: str, node_path: List[st node_name=node_name, node_path=node_path, node_id=node_id, - original_exception=exception + original_exception=exception, ) def to_dict(self) -> Dict[str, Any]: @@ -62,13 +69,14 @@ def to_dict(self) -> Dict[str, Any]: "node_id": self.node_id, "input_data": self.input_data, "output_data": self.output_data, - "params": self.params + "params": self.params, } @dataclass class ExecutionResult: """Standardized execution result structure for all nodes.""" + success: bool node_name: str node_path: List[str] diff --git a/intent_kit/services/__init__.py b/intent_kit/services/__init__.py index 9ebd43f..86ecd7e 100644 --- a/intent_kit/services/__init__.py +++ b/intent_kit/services/__init__.py @@ -1,6 +1,6 @@ """Service registry for intentify with optional dependencies.""" -from typing import Dict, Type, Optional, Any +from typing import Dict, Type, Any from .google_client import GoogleClient from .anthropic_client import AnthropicClient from .openai_client import OpenAIClient @@ -11,10 +11,10 @@ class ServiceRegistry: """Registry for AI services with optional dependencies.""" _services: Dict[str, Type] = { - 'google': GoogleClient, - 'anthropic': AnthropicClient, - 'openai': OpenAIClient, - 'ollama': OllamaClient, + "google": GoogleClient, + "anthropic": AnthropicClient, + "openai": OpenAIClient, + "ollama": OllamaClient, } @classmethod @@ -22,7 +22,7 @@ def get_available_services(cls) -> Dict[str, bool]: """Get a dictionary of service names and their availability.""" available = {} for name, service_class in cls._services.items(): - if hasattr(service_class, 'is_available'): + if hasattr(service_class, "is_available"): available[name] = service_class.is_available() else: available[name] = True # Assume available if no check method @@ -36,7 +36,7 @@ def create_service(cls, service_name: str, **kwargs) -> Any: service_class = cls._services[service_name] - if hasattr(service_class, 'is_available') and not service_class.is_available(): + if hasattr(service_class, "is_available") and not service_class.is_available(): raise ImportError( f"Service '{service_name}' is not available. " f"Install required dependencies: pip install intentify[openai]" @@ -49,6 +49,7 @@ def register_service(cls, name: str, service_class: Type): """Register a new service class.""" cls._services[name] = service_class + # Convenience functions diff --git a/intent_kit/services/anthropic_client.py b/intent_kit/services/anthropic_client.py index 7c58f2e..f030c41 100644 --- a/intent_kit/services/anthropic_client.py +++ b/intent_kit/services/anthropic_client.py @@ -15,6 +15,7 @@ def get_client(self): """Get the Anthropic client.""" try: import anthropic + return anthropic.Anthropic(api_key=self.api_key) except ImportError: raise ImportError( @@ -26,6 +27,7 @@ def _ensure_imported(self): if self._client is None: try: import anthropic + self._client = anthropic.Anthropic(api_key=self.api_key) except ImportError: raise ImportError( @@ -36,15 +38,15 @@ def generate(self, prompt: str, model: str = "claude-3-sonnet-20240229") -> str: """Generate text using Anthropic's Claude model.""" self._ensure_imported() response = self._client.messages.create( - model=model, - max_tokens=1000, - messages=[{"role": "user", "content": prompt}] + model=model, max_tokens=1000, messages=[{"role": "user", "content": prompt}] ) content = response.content logger.debug(f"Anthropic generate response: {content}") return str(content) if content else "" # Keep generate_text as an alias for backward compatibility - def generate_text(self, prompt: str, model: str = "claude-3-sonnet-20240229") -> str: + def generate_text( + self, prompt: str, model: str = "claude-3-sonnet-20240229" + ) -> str: """Alias for generate method (backward compatibility).""" return self.generate(prompt, model) diff --git a/intent_kit/services/google_client.py b/intent_kit/services/google_client.py index 5077f47..3b59cd9 100644 --- a/intent_kit/services/google_client.py +++ b/intent_kit/services/google_client.py @@ -15,6 +15,7 @@ def get_client(self): """Get the Google GenAI client.""" try: from google import genai + return genai.Client(api_key=self.api_key) except ImportError: raise ImportError( @@ -26,6 +27,7 @@ def _ensure_imported(self): if self._client is None: try: from google import genai + self._client = genai.Client(api_key=self.api_key) except ImportError: raise ImportError( diff --git a/intent_kit/services/llm_factory.py b/intent_kit/services/llm_factory.py index 646b883..9c883e1 100644 --- a/intent_kit/services/llm_factory.py +++ b/intent_kit/services/llm_factory.py @@ -4,7 +4,7 @@ This module provides a factory for creating LLM clients based on provider configuration. """ -from typing import Dict, Any, Optional +from typing import Dict, Any from intent_kit.services.openai_client import OpenAIClient from intent_kit.services.anthropic_client import AnthropicClient from intent_kit.services.google_client import GoogleClient @@ -57,7 +57,8 @@ def create_client(llm_config: Dict[str, Any]): # For other providers, API key is required if not api_key: raise ValueError( - "LLM config must include 'api_key' for provider: {provider}") + "LLM config must include 'api_key' for provider: {provider}" + ) if provider == "openai": return OpenAIClient(api_key=api_key) @@ -86,8 +87,6 @@ def generate_with_config(llm_config: Dict[str, Any], prompt: str) -> str: # Extract optional parameters model = llm_config.get("model") - max_tokens = llm_config.get("max_tokens") - temperature = llm_config.get("temperature") # For now, we'll use the default generate method # In the future, we can extend this to pass additional parameters diff --git a/intent_kit/services/ollama_client.py b/intent_kit/services/ollama_client.py index 1a82fba..65f7c84 100644 --- a/intent_kit/services/ollama_client.py +++ b/intent_kit/services/ollama_client.py @@ -15,6 +15,7 @@ def get_client(self): """Get the Ollama client.""" try: from ollama import Client + return Client(host=self.base_url) except ImportError: raise ImportError( @@ -26,6 +27,7 @@ def _ensure_imported(self): if self._client is None: try: from ollama import Client + self._client = Client(host=self.base_url) except ImportError: raise ImportError( @@ -36,11 +38,8 @@ def generate(self, prompt: str, model: str = "llama2") -> str: """Generate text using Ollama model.""" self._ensure_imported() try: - response = self._client.generate( - model=model, - prompt=prompt - ) - content = response['response'] + response = self._client.generate(model=model, prompt=prompt) + content = response["response"] logger.debug(f"Ollama generate response: {content}") return str(content) if content else "" except Exception as e: @@ -51,12 +50,8 @@ def generate_stream(self, prompt: str, model: str = "llama2"): """Generate text using Ollama model with streaming.""" self._ensure_imported() try: - for chunk in self._client.generate( - model=model, - prompt=prompt, - stream=True - ): - yield chunk['response'] + for chunk in self._client.generate(model=model, prompt=prompt, stream=True): + yield chunk["response"] except Exception as e: logger.error(f"Error streaming with Ollama: {e}") raise @@ -65,11 +60,8 @@ def chat(self, messages: list, model: str = "llama2") -> str: """Chat with Ollama model using messages format.""" self._ensure_imported() try: - response = self._client.chat( - model=model, - messages=messages - ) - content = response['message']['content'] + response = self._client.chat(model=model, messages=messages) + content = response["message"]["content"] logger.debug(f"Ollama chat response: {content}") return str(content) if content else "" except Exception as e: @@ -80,12 +72,8 @@ def chat_stream(self, messages: list, model: str = "llama2"): """Chat with Ollama model using messages format with streaming.""" self._ensure_imported() try: - for chunk in self._client.chat( - model=model, - messages=messages, - stream=True - ): - yield chunk['message']['content'] + for chunk in self._client.chat(model=model, messages=messages, stream=True): + yield chunk["message"]["content"] except Exception as e: logger.error(f"Error streaming chat with Ollama: {e}") raise @@ -98,20 +86,19 @@ def list_models(self): logger.debug(f"Ollama list response: {models_response}") # The correct type is ListResponse, which has a .models attribute - if hasattr(models_response, 'models'): + if hasattr(models_response, "models"): models = models_response.models else: - logger.error( - f"Unexpected response structure: {models_response}") + logger.error(f"Unexpected response structure: {models_response}") return [] # Each model is a ListResponse.Model with a .model attribute model_names = [] for model in models: - if hasattr(model, 'model') and model.model: + if hasattr(model, "model") and model.model: model_names.append(model.model) - elif isinstance(model, dict) and 'model' in model: - model_names.append(model['model']) + elif isinstance(model, dict) and "model" in model: + model_names.append(model["model"]) elif isinstance(model, str): model_names.append(model) else: @@ -152,7 +139,8 @@ def generate_text(self, prompt: str, model: str = "llama2") -> str: def is_available(cls) -> bool: """Check if Ollama package is available.""" try: - from ollama import Client - return True + import importlib.util + + return importlib.util.find_spec("ollama") is not None except ImportError: return False diff --git a/intent_kit/services/openai_client.py b/intent_kit/services/openai_client.py index 66bbff6..2f2984e 100644 --- a/intent_kit/services/openai_client.py +++ b/intent_kit/services/openai_client.py @@ -15,6 +15,7 @@ def get_client(self): """Get the OpenAI client.""" try: import openai + return openai.OpenAI(api_key=self.api_key) except ImportError: raise ImportError( @@ -26,6 +27,7 @@ def _ensure_imported(self): if self._client is None: try: import openai + self._client = openai.OpenAI(api_key=self.api_key) except ImportError: raise ImportError( @@ -36,9 +38,7 @@ def generate(self, prompt: str, model: str = "gpt-4") -> str: """Generate text using OpenAI's GPT model.""" self._ensure_imported() response = self._client.chat.completions.create( - model=model, - messages=[{"role": "user", "content": prompt}], - max_tokens=1000 + model=model, messages=[{"role": "user", "content": prompt}], max_tokens=1000 ) content = response.choices[0].message.content return str(content) if content else "" diff --git a/intent_kit/services/openrouter_client.py b/intent_kit/services/openrouter_client.py index 6c7aca8..17a3b4f 100644 --- a/intent_kit/services/openrouter_client.py +++ b/intent_kit/services/openrouter_client.py @@ -15,9 +15,9 @@ def get_client(self): """Get the OpenRouter client.""" try: import openai + return openai.OpenAI( - api_key=self.api_key, - base_url="https://openrouter.ai/api/v1" + api_key=self.api_key, base_url="https://openrouter.ai/api/v1" ) except ImportError: raise ImportError( @@ -29,9 +29,9 @@ def _ensure_imported(self): if self._client is None: try: import openai + self._client = openai.OpenAI( - api_key=self.api_key, - base_url="https://openrouter.ai/api/v1" + api_key=self.api_key, base_url="https://openrouter.ai/api/v1" ) except ImportError: raise ImportError( @@ -42,9 +42,7 @@ def generate(self, prompt: str, model: str = "openai/gpt-4") -> str: """Generate text using OpenRouter model.""" self._ensure_imported() response = self._client.chat.completions.create( - model=model, - messages=[{"role": "user", "content": prompt}], - max_tokens=1000 + model=model, messages=[{"role": "user", "content": prompt}], max_tokens=1000 ) content = response.choices[0].message.content logger.debug(f"OpenRouter generate response: {content}") diff --git a/intent_kit/splitters/__init__.py b/intent_kit/splitters/__init__.py index 42bca23..87bf3f6 100644 --- a/intent_kit/splitters/__init__.py +++ b/intent_kit/splitters/__init__.py @@ -12,7 +12,6 @@ __all__ = [ # Node class "SplitterNode", - # Splitter functions "rule_splitter", "llm_splitter", diff --git a/intent_kit/splitters/llm_splitter.py b/intent_kit/splitters/llm_splitter.py index 55b79ac..142d2e4 100644 --- a/intent_kit/splitters/llm_splitter.py +++ b/intent_kit/splitters/llm_splitter.py @@ -1,15 +1,16 @@ """ LLM-based intent splitter for IntentGraph. """ -from typing import Dict, List, Any, Optional, Sequence -import re -import json + +from typing import List, Sequence from intent_kit.utils.logger import Logger from intent_kit.types import IntentChunk from intent_kit.utils.text_utils import extract_json_array_from_text -def llm_splitter(user_input: str, debug: bool = False, llm_client=None) -> Sequence[IntentChunk]: +def llm_splitter( + user_input: str, debug: bool = False, llm_client=None +) -> Sequence[IntentChunk]: """ LLM-based intent splitter using AI models. @@ -29,9 +30,11 @@ def llm_splitter(user_input: str, debug: bool = False, llm_client=None) -> Seque if not llm_client: if debug: logger.warning( - "No LLM client available, falling back to rule-based splitting") + "No LLM client available, falling back to rule-based splitting" + ) # Fallback to rule-based splitting from .rule_splitter import rule_splitter + return rule_splitter(user_input, debug) try: @@ -60,17 +63,19 @@ def llm_splitter(user_input: str, debug: bool = False, llm_client=None) -> Seque # If no valid results, fallback to rule-based if debug: logger.warning( - "LLM parsing returned no results, falling back to rule-based") + "LLM parsing returned no results, falling back to rule-based" + ) from .rule_splitter import rule_splitter + return rule_splitter(user_input, debug) except Exception as e: if debug: - logger.error( - f"LLM splitting failed: {e}, falling back to rule-based") + logger.error(f"LLM splitting failed: {e}, falling back to rule-based") # Fallback to rule-based splitting from .rule_splitter import rule_splitter + return rule_splitter(user_input, debug) @@ -105,8 +110,7 @@ def _parse_llm_response(response: str) -> List[str]: results.append(item.strip()) return results # If JSON parsing fails, try manual extraction from the utility - manual = extract_json_array_from_text( - response, fallback_to_manual=True) + manual = extract_json_array_from_text(response, fallback_to_manual=True) if manual: return [str(item).strip() for item in manual] return [] diff --git a/intent_kit/splitters/node.py b/intent_kit/splitters/node.py index 5a678a6..7981b38 100644 --- a/intent_kit/splitters/node.py +++ b/intent_kit/splitters/node.py @@ -1,10 +1,8 @@ -from typing import Any, List, Optional +from typing import List, Optional from intent_kit.node.base import TreeNode from intent_kit.node.enums import NodeType -from intent_kit.utils.logger import Logger from intent_kit.context import IntentContext from intent_kit.node.types import ExecutionResult, ExecutionError -from intent_kit.types import IntentChunk class SplitterNode(TreeNode): @@ -17,9 +15,11 @@ def __init__( children: List["TreeNode"], description: str = "", parent: Optional["TreeNode"] = None, - llm_client=None + llm_client=None, ): - super().__init__(name=name, description=description, children=children, parent=parent) + super().__init__( + name=name, description=description, children=children, parent=parent + ) self.splitter_function = splitter_function self.llm_client = llm_client @@ -28,12 +28,13 @@ def node_type(self) -> NodeType: """Get the type of this node.""" return NodeType.SPLITTER - def execute(self, user_input: str, context: Optional[IntentContext] = None) -> ExecutionResult: + def execute( + self, user_input: str, context: Optional[IntentContext] = None + ) -> ExecutionResult: try: intent_chunks = self.splitter_function(user_input, debug=False) if not intent_chunks: - self.logger.warning( - f"Splitter '{self.name}' found no intent chunks") + self.logger.warning(f"Splitter '{self.name}' found no intent chunks") return ExecutionResult( success=False, node_name=self.name, @@ -45,13 +46,14 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type="NoIntentChunksFound", message="No intent chunks found after splitting", node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params={"intent_chunks": []}, - children_results=[] + children_results=[], ) self.logger.debug( - f"Splitter '{self.name}' found {len(intent_chunks)} chunks: {intent_chunks}") + f"Splitter '{self.name}' found {len(intent_chunks)} chunks: {intent_chunks}" + ) children_results = [] all_outputs = [] for chunk in intent_chunks: @@ -70,14 +72,15 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E break except Exception as e: self.logger.debug( - f"Child '{child.name}' failed to handle chunk '{chunk_text}': {e}") + f"Child '{child.name}' failed to handle chunk '{chunk_text}': {e}" + ) continue if not handled: error_result = ExecutionResult( success=False, node_name=f"unhandled_chunk_{chunk_text[:20]}", - node_path=self.get_path() + - [f"unhandled_chunk_{chunk_text[:20]}"], + node_path=self.get_path() + + [f"unhandled_chunk_{chunk_text[:20]}"], node_type=NodeType.UNHANDLED_CHUNK, input=chunk_text, output=None, @@ -85,10 +88,10 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E error_type="UnhandledChunk", message=f"No child node could handle chunk: '{chunk_text}'", node_name=self.name, - node_path=self.get_path() + node_path=self.get_path(), ), params={"chunk": chunk_text}, - children_results=[] + children_results=[], ) children_results.append(error_result) successful_results = [r for r in children_results if r.success] @@ -104,13 +107,12 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E params={ "intent_chunks": intent_chunks, "chunks_processed": len(intent_chunks), - "chunks_handled": len(successful_results) + "chunks_handled": len(successful_results), }, - children_results=children_results + children_results=children_results, ) except Exception as e: - self.logger.error( - f"Splitter execution error for '{self.name}': {e}") + self.logger.error(f"Splitter execution error for '{self.name}': {e}") return ExecutionResult( success=False, node_name=self.name, @@ -119,7 +121,8 @@ def execute(self, user_input: str, context: Optional[IntentContext] = None) -> E input=user_input, output=None, error=ExecutionError.from_exception( - e, self.name, self.get_path(), node_id=self.node_id), + e, self.name, self.get_path(), node_id=self.node_id + ), params=None, - children_results=[] + children_results=[], ) diff --git a/intent_kit/splitters/rule_splitter.py b/intent_kit/splitters/rule_splitter.py index 00f6e79..2b5d53d 100644 --- a/intent_kit/splitters/rule_splitter.py +++ b/intent_kit/splitters/rule_splitter.py @@ -1,7 +1,8 @@ """ Rule-based intent splitter for IntentGraph. """ -from typing import Dict, List, Optional, Any + +from typing import List import re from intent_kit.utils.logger import Logger from intent_kit.types import IntentChunk @@ -26,12 +27,10 @@ def rule_splitter(user_input: str, debug: bool = False) -> List[IntentChunk]: # Separate word and punctuation conjunctions for regex word_conjunctions = ["and", "also", "plus", "as well as"] punct_conjunctions = [",", ";"] - conjunctions = word_conjunctions + punct_conjunctions # Build regex pattern for conjunctions # For word conjunctions, use word boundaries - word_pattern = r"|".join( - [fr"\b{re.escape(conj)}\b" for conj in word_conjunctions]) + word_pattern = r"|".join([rf"\b{re.escape(conj)}\b" for conj in word_conjunctions]) # For punctuation, just escape them punct_pattern = r"|".join([re.escape(conj) for conj in punct_conjunctions]) diff --git a/intent_kit/splitters/types.py b/intent_kit/splitters/types.py index 2befae3..480d388 100644 --- a/intent_kit/splitters/types.py +++ b/intent_kit/splitters/types.py @@ -1,6 +1,7 @@ """ Splitter types - re-exported from central types module. """ + from intent_kit.types import ( IntentChunk, IntentChunkClassification, @@ -8,7 +9,7 @@ IntentAction, ClassifierOutput, SplitterFunction, - ClassifierFunction + ClassifierFunction, ) __all__ = [ @@ -18,5 +19,5 @@ "IntentAction", "ClassifierOutput", "SplitterFunction", - "ClassifierFunction" + "ClassifierFunction", ] diff --git a/intent_kit/types.py b/intent_kit/types.py index 5d52c84..2f054e1 100644 --- a/intent_kit/types.py +++ b/intent_kit/types.py @@ -1,6 +1,7 @@ """ Core types for intent-kit package. """ + from typing import TypedDict, Optional, Dict, Any, Sequence, Union, Callable from enum import Enum @@ -37,11 +38,8 @@ class IntentChunkClassification(TypedDict, total=False): SplitterFunction = Callable[ [str, bool], # Required args: user_input, debug # Return type: sequence of strings or dicts with text and metadata - Sequence[IntentChunk] + Sequence[IntentChunk], ] # Classifier function type -ClassifierFunction = Callable[ - [IntentChunk], - ClassifierOutput -] +ClassifierFunction = Callable[[IntentChunk], ClassifierOutput] diff --git a/intent_kit/utils/logger.py b/intent_kit/utils/logger.py index 26fdb16..7ca479a 100644 --- a/intent_kit/utils/logger.py +++ b/intent_kit/utils/logger.py @@ -22,7 +22,7 @@ def get_color(self, level): return "\033[90m" # gray # New soft color palette using 256-color ANSI codes elif level == "section_title": - return "\033[38;5;75m" # Soft blue/cyan for main section titles + return "\033[38;5;75m" # Soft blue/cyan for main section titles elif level == "field_label": # Muted light purple for field names/labels return "\033[38;5;146m" @@ -69,16 +69,16 @@ def supports_color(self): import sys # Check if we're in a terminal - if not hasattr(sys.stdout, 'isatty') or not sys.stdout.isatty(): + if not hasattr(sys.stdout, "isatty") or not sys.stdout.isatty(): return False # Check environment variables - if os.environ.get('NO_COLOR'): + if os.environ.get("NO_COLOR"): return False # Check if we're in a dumb terminal - term = os.environ.get('TERM', '') - if term == 'dumb': + term = os.environ.get("TERM", "") + if term == "dumb": return False return True @@ -127,7 +127,7 @@ def colorize_bright(self, text, color_name): "red": "bright_red", "magenta": "bright_magenta", "cyan": "bright_cyan", - "white": "bright_white" + "white": "bright_white", } color = bright_colors.get(color_name, color_name) return self.colorize(text, color) diff --git a/intent_kit/utils/text_utils.py b/intent_kit/utils/text_utils.py index bb62a4a..c24870a 100644 --- a/intent_kit/utils/text_utils.py +++ b/intent_kit/utils/text_utils.py @@ -7,13 +7,15 @@ import json import re -from typing import Any, Dict, List, Optional, Union, Tuple +from typing import Any, Dict, List, Optional, Tuple from intent_kit.utils.logger import Logger logger = Logger(__name__) -def extract_json_from_text(text: Optional[str], fallback_to_manual: bool = True) -> Optional[Dict[str, Any]]: +def extract_json_from_text( + text: Optional[str], fallback_to_manual: bool = True +) -> Optional[Dict[str, Any]]: """ Extract JSON object from text, handling various formats and edge cases. Now also supports extracting from ```json ... ``` blocks. @@ -22,7 +24,7 @@ def extract_json_from_text(text: Optional[str], fallback_to_manual: bool = True) return None # First, look for a ```json ... ``` block - json_block = re.search(r'```json\s*([\s\S]*?)```', text, re.IGNORECASE) + json_block = re.search(r"```json\s*([\s\S]*?)```", text, re.IGNORECASE) if json_block: json_str = json_block.group(1).strip() try: @@ -31,7 +33,7 @@ def extract_json_from_text(text: Optional[str], fallback_to_manual: bool = True) logger.debug(f"JSON decode error in ```json block: {e}") # Try to find JSON object pattern - json_match = re.search(r'\{[^{}]*(?:\{[^{}]*\}[^{}]*)*\}', text, re.DOTALL) + json_match = re.search(r"\{[^{}]*(?:\{[^{}]*\}[^{}]*)*\}", text, re.DOTALL) if json_match: json_str = json_match.group(0) try: @@ -40,8 +42,7 @@ def extract_json_from_text(text: Optional[str], fallback_to_manual: bool = True) logger.debug(f"JSON decode error: {e}") # Try to find JSON array pattern - array_match = re.search( - r'\[[^\[\]]*(?:\{[^{}]*\}[^\[\]]*)*\]', text, re.DOTALL) + array_match = re.search(r"\[[^\[\]]*(?:\{[^{}]*\}[^\[\]]*)*\]", text, re.DOTALL) if array_match: json_str = array_match.group(0) try: @@ -55,7 +56,9 @@ def extract_json_from_text(text: Optional[str], fallback_to_manual: bool = True) return None -def extract_json_array_from_text(text: Optional[str], fallback_to_manual: bool = True) -> Optional[List[Any]]: +def extract_json_array_from_text( + text: Optional[str], fallback_to_manual: bool = True +) -> Optional[List[Any]]: """ Extract JSON array from text, handling various formats and edge cases. Now also supports extracting from ```json ... ``` blocks. @@ -64,7 +67,7 @@ def extract_json_array_from_text(text: Optional[str], fallback_to_manual: bool = return None # First, look for a ```json ... ``` block - json_block = re.search(r'```json\s*([\s\S]*?)```', text, re.IGNORECASE) + json_block = re.search(r"```json\s*([\s\S]*?)```", text, re.IGNORECASE) if json_block: json_str = json_block.group(1).strip() try: @@ -75,8 +78,7 @@ def extract_json_array_from_text(text: Optional[str], fallback_to_manual: bool = logger.debug(f"JSON array decode error in ```json block: {e}") # Try to find JSON array pattern - array_match = re.search( - r'\[[^\[\]]*(?:\{[^{}]*\}[^\[\]]*)*\]', text, re.DOTALL) + array_match = re.search(r"\[[^\[\]]*(?:\{[^{}]*\}[^\[\]]*)*\]", text, re.DOTALL) if array_match: json_str = array_match.group(0) try: @@ -113,13 +115,13 @@ def extract_key_value_pairs(text: Optional[str]) -> Dict[str, Any]: pairs[key.strip()] = _clean_value(value.strip()) # Pattern 2: key: value - kv_pattern2 = re.findall(r'(\w+)\s*:\s*([^,\n}]+)', text) + kv_pattern2 = re.findall(r"(\w+)\s*:\s*([^,\n}]+)", text) for key, value in kv_pattern2: if key not in pairs: # Don't override quoted keys pairs[key.strip()] = _clean_value(value.strip()) # Pattern 3: key = value - kv_pattern3 = re.findall(r'(\w+)\s*=\s*([^,\n}]+)', text) + kv_pattern3 = re.findall(r"(\w+)\s*=\s*([^,\n}]+)", text) for key, value in kv_pattern3: if key not in pairs: pairs[key.strip()] = _clean_value(value.strip()) @@ -161,27 +163,31 @@ def clean_for_deserialization(text: Optional[str]) -> str: return "" # Remove common LLM response artifacts - text = re.sub(r'```json\s*', '', text) - text = re.sub(r'```\s*$', '', text) - text = re.sub(r'^```\s*', '', text) + text = re.sub(r"```json\s*", "", text) + text = re.sub(r"```\s*$", "", text) + text = re.sub(r"^```\s*", "", text) # Fix common JSON issues - text = re.sub(r'([{,])\s*([a-zA-Z_][a-zA-Z0-9_]*)\s*:', - r'\1"\2":', text) # Quote unquoted keys - text = re.sub(r':\s*([a-zA-Z_][a-zA-Z0-9_]*)\s*([,}])', - r': "\1"\2', text) # Quote unquoted string values + text = re.sub( + r"([{,])\s*([a-zA-Z_][a-zA-Z0-9_]*)\s*:", r'\1"\2":', text + ) # Quote unquoted keys + text = re.sub( + r":\s*([a-zA-Z_][a-zA-Z0-9_]*)\s*([,}])", r': "\1"\2', text + ) # Quote unquoted string values # Normalize spacing around colons - text = re.sub(r':\s+', ': ', text) + text = re.sub(r":\s+", ": ", text) # Fix trailing commas - text = re.sub(r',\s*}', '}', text) - text = re.sub(r',\s*]', ']', text) + text = re.sub(r",\s*}", "}", text) + text = re.sub(r",\s*]", "]", text) return text.strip() -def extract_structured_data(text: Optional[str], expected_type: str = "auto") -> Tuple[Optional[Any], str]: +def extract_structured_data( + text: Optional[str], expected_type: str = "auto" +) -> Tuple[Optional[Any], str]: """ Extract structured data from text with type detection. @@ -198,14 +204,13 @@ def extract_structured_data(text: Optional[str], expected_type: str = "auto") -> # For auto detection, try to determine the type first if expected_type == "auto": # Check if it looks like a JSON array - if text.strip().startswith('[') and text.strip().endswith(']'): - json_array = extract_json_array_from_text( - text, fallback_to_manual=False) + if text.strip().startswith("[") and text.strip().endswith("]"): + json_array = extract_json_array_from_text(text, fallback_to_manual=False) if json_array: return json_array, "json_array" # Check if it looks like a JSON object - if text.strip().startswith('{') and text.strip().endswith('}'): + if text.strip().startswith("{") and text.strip().endswith("}"): json_obj = extract_json_from_text(text, fallback_to_manual=False) if json_obj: return json_obj, "json_object" @@ -218,8 +223,7 @@ def extract_structured_data(text: Optional[str], expected_type: str = "auto") -> # Try JSON array if expected_type in ["auto", "list"]: - json_array = extract_json_array_from_text( - text, fallback_to_manual=False) + json_array = extract_json_array_from_text(text, fallback_to_manual=False) if json_array: return json_array, "json_array" @@ -247,7 +251,7 @@ def _manual_json_extraction(text: str) -> Optional[Dict[str, Any]]: """Manually extract JSON-like object from text.""" # Try to extract from common patterns first # Pattern: { key: value, key2: value2 } - brace_pattern = re.search(r'\{([^}]+)\}', text) + brace_pattern = re.search(r"\{([^}]+)\}", text) if brace_pattern: content = brace_pattern.group(1) pairs = extract_key_value_pairs(content) @@ -264,7 +268,6 @@ def _manual_json_extraction(text: str) -> Optional[Dict[str, Any]]: def _manual_array_extraction(text: str) -> Optional[List[Any]]: """Manually extract array-like data from text.""" - results = [] # Extract quoted strings quoted_strings = re.findall(r'"([^"]*)"', text) @@ -272,17 +275,17 @@ def _manual_array_extraction(text: str) -> Optional[List[Any]]: return [s.strip() for s in quoted_strings if s.strip()] # Extract numbered items - numbered_items = re.findall(r'\d+\.\s*(.+)', text) + numbered_items = re.findall(r"\d+\.\s*(.+)", text) if numbered_items: return [item.strip() for item in numbered_items if item.strip()] # Extract dash-separated items - dash_items = re.findall(r'-\s*(.+)', text) + dash_items = re.findall(r"-\s*(.+)", text) if dash_items: return [item.strip() for item in dash_items if item.strip()] # Extract comma-separated items - comma_items = re.findall(r'([^,]+)', text) + comma_items = re.findall(r"([^,]+)", text) if comma_items: cleaned_items = [item.strip() for item in comma_items if item.strip()] if len(cleaned_items) > 1: @@ -294,8 +297,8 @@ def _manual_array_extraction(text: str) -> Optional[List[Any]]: def _extract_clean_string(text: str) -> Optional[str]: """Extract a clean string from text.""" # Remove common artifacts - text = re.sub(r'```.*?```', '', text, flags=re.DOTALL) - text = re.sub(r'`.*?`', '', text) + text = re.sub(r"```.*?```", "", text, flags=re.DOTALL) + text = re.sub(r"`.*?`", "", text) # Extract content between quotes quoted = re.findall(r'"([^"]*)"', text) @@ -315,13 +318,13 @@ def _clean_value(value: str) -> Any: value = value.strip() # Try to convert to appropriate type - if value.lower() in ['true', 'false']: - return value.lower() == 'true' - elif value.lower() == 'null': + if value.lower() in ["true", "false"]: + return value.lower() == "true" + elif value.lower() == "null": return None elif value.isdigit(): return int(value) - elif re.match(r'^\d+\.\d+$', value): + elif re.match(r"^\d+\.\d+$", value): return float(value) elif value.startswith('"') and value.endswith('"'): return value[1:-1] @@ -329,7 +332,9 @@ def _clean_value(value: str) -> Any: return value -def validate_json_structure(data: Any, required_keys: Optional[List[str]] = None) -> bool: +def validate_json_structure( + data: Any, required_keys: Optional[List[str]] = None +) -> bool: """ Validate that extracted data has the expected structure. diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 0000000..0986832 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,28 @@ +site_name: intent-kit +site_description: Open-source Python framework for intent classification and execution +site_url: https://docs.intentkit.io +repo_url: https://github.com/Stephen-Collins-tech/intent-kit + +theme: + name: material + +plugins: + - search + - mkdocstrings + - literate-nav + +markdown_extensions: + - admonition + - codehilite + - toc: + permalink: true + +nav: + - Home: index.md + - Quickstart: quickstart.md + - API Reference: + - intent_kit: api_reference.md + - Examples: + - Calculator Bot: examples/calculator-bot.md + - Context-Aware Chatbot: examples/context-aware-chatbot.md + - Multi-Intent Routing: examples/multi-intent-routing.md \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index bb863ed..2b2c28f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,7 +3,7 @@ requires = ["setuptools>=42", "wheel"] build-backend = "setuptools.build_meta" [project] -name = "intent-kit" +name = "intent_kit" version = "0.1.0" description = "An open-source Python library for building intent classification and execution systems that work with any AI backend." authors = [ @@ -51,6 +51,20 @@ dev = [ "python-dotenv>=1.0.0", "tqdm", "pyyaml", + "black>=24.4.2", + "black[jupyter]>=24.4.2", + "ruff>=0.4.7", + "mypy>=1.10.0", + "pre-commit>=3.6.0", + "build>=1.2.1", + "twine>=5.1.0", + "mkdocs>=1.5.0", + "mkdocs-material>=9.5.17", + "mkdocstrings[python]>=0.24.0", + "mkdocs-literate-nav>=0.6.0", + "ipykernel>=6.0.0", + "types-pyyaml>=6.0.12.20250516", + "types-networkx>=3.5.0.20250701", ] viz = [ "networkx>=3.5", diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..a6ab3f6 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,6 @@ +# Used for docs site generation +mkdocs>=1.5.0 +mkdocs-material>=9.5.17 +mkdocstrings[python]>=0.24.0 +mkdocs-literate-nav>=0.6.0>=0.6.0 +ipykernel>=6.0.0 \ No newline at end of file diff --git a/tests/intent_kit/graph/test_validation.py b/tests/intent_kit/graph/test_validation.py index 2b24900..cb4a189 100644 --- a/tests/intent_kit/graph/test_validation.py +++ b/tests/intent_kit/graph/test_validation.py @@ -6,7 +6,7 @@ from intent_kit.builder import handler, rule_splitter_node from intent_kit.classifiers import ClassifierNode from intent_kit.graph import IntentGraph -from intent_kit.graph.validation import GraphValidationError, validate_splitter_routing +from intent_kit.graph.validation import GraphValidationError def test_valid_graph(): @@ -18,7 +18,7 @@ def test_valid_graph(): name="greet", description="Greet the user", handler_func=lambda name: f"Hello {name}!", - param_schema={"name": str} + param_schema={"name": str}, ) # Create classifier node manually since we need a custom classifier @@ -26,7 +26,7 @@ def test_valid_graph(): name="main_classifier", classifier=lambda text, children, context: children[0], children=[greet_node], - description="Main classifier" + description="Main classifier", ) # Set parent reference @@ -36,7 +36,7 @@ def test_valid_graph(): splitter_node = rule_splitter_node( name="main_splitter", children=[classifier_node], # Routes to classifier - VALID - description="Split multi-intent inputs" + description="Split multi-intent inputs", ) # Create graph and validate @@ -55,14 +55,14 @@ def test_invalid_graph(): name="greet", description="Greet the user", handler_func=lambda name: f"Hello {name}!", - param_schema={"name": str} + param_schema={"name": str}, ) # Create splitter node that routes directly to intent nodes (INVALID) splitter_node = rule_splitter_node( name="invalid_splitter", children=[greet_node], # Routes directly to intent - INVALID - description="Invalid splitter" + description="Invalid splitter", ) # Create graph and try to validate diff --git a/tests/intent_kit/splitters/test_llm_splitter.py b/tests/intent_kit/splitters/test_llm_splitter.py index bbbcbf9..192f23d 100644 --- a/tests/intent_kit/splitters/test_llm_splitter.py +++ b/tests/intent_kit/splitters/test_llm_splitter.py @@ -1,10 +1,14 @@ """ Specific tests for llm_splitter function. """ + import unittest -from unittest.mock import Mock, patch -from intent_kit.splitters.llm_splitter import llm_splitter, _create_splitting_prompt, _parse_llm_response -import pytest +from unittest.mock import Mock +from intent_kit.splitters.llm_splitter import ( + llm_splitter, + _create_splitting_prompt, + _parse_llm_response, +) class TestLLMSplitterFunction(unittest.TestCase): @@ -20,8 +24,7 @@ def test_llm_splitting_success_valid_json(self): '["cancel my flight", "update my email"]' ) result = llm_splitter( - "Cancel my flight and update my email", - llm_client=self.mock_llm_client + "Cancel my flight and update my email", llm_client=self.mock_llm_client ) self.assertEqual(len(result), 2) self.assertEqual(result[0], "cancel my flight") @@ -29,31 +32,25 @@ def test_llm_splitting_success_valid_json(self): def test_llm_splitting_success_single_intent(self): """Test successful LLM-based splitting with single intent.""" - self.mock_llm_client.generate.return_value = ( - '["I need travel help"]' - ) - result = llm_splitter( - "I need travel help", - llm_client=self.mock_llm_client - ) + self.mock_llm_client.generate.return_value = '["I need travel help"]' + result = llm_splitter("I need travel help", llm_client=self.mock_llm_client) self.assertEqual(len(result), 1) self.assertEqual(result[0], "I need travel help") def test_llm_splitting_fallback_no_client(self): """Test fallback to rule-based when no LLM client provided.""" # Should fallback to rule_splitter - result = llm_splitter( - "travel help and account support", llm_client=None) + result = llm_splitter("travel help and account support", llm_client=None) self.assertEqual(len(result), 2) self.assertEqual(result[0], "travel help") self.assertEqual(result[1], "account support") def test_llm_splitting_fallback_exception(self): """Test fallback to rule-based when LLM raises exception.""" - self.mock_llm_client.generate.side_effect = Exception( - "LLM service unavailable") - result = llm_splitter("travel help and account support", - llm_client=self.mock_llm_client) + self.mock_llm_client.generate.side_effect = Exception("LLM service unavailable") + result = llm_splitter( + "travel help and account support", llm_client=self.mock_llm_client + ) self.assertEqual(len(result), 2) self.assertEqual(result[0], "travel help") self.assertEqual(result[1], "account support") @@ -61,8 +58,9 @@ def test_llm_splitting_fallback_exception(self): def test_llm_splitting_fallback_invalid_json(self): """Test fallback to rule-based when LLM returns invalid JSON.""" self.mock_llm_client.generate.return_value = "invalid json response" - result = llm_splitter("travel help and account support", - llm_client=self.mock_llm_client) + result = llm_splitter( + "travel help and account support", llm_client=self.mock_llm_client + ) self.assertEqual(len(result), 2) self.assertEqual(result[0], "travel help") self.assertEqual(result[1], "account support") @@ -70,26 +68,29 @@ def test_llm_splitting_fallback_invalid_json(self): def test_llm_splitting_fallback_empty_response(self): """Test fallback to rule-based when LLM returns empty response.""" self.mock_llm_client.generate.return_value = "" - result = llm_splitter("travel help and account support", - llm_client=self.mock_llm_client) + result = llm_splitter( + "travel help and account support", llm_client=self.mock_llm_client + ) self.assertEqual(len(result), 2) self.assertEqual(result[0], "travel help") self.assertEqual(result[1], "account support") def test_llm_splitting_fallback_no_results(self): """Test fallback to rule-based when LLM parsing returns no results.""" - self.mock_llm_client.generate.return_value = '[]' - result = llm_splitter("travel help and account support", - llm_client=self.mock_llm_client) + self.mock_llm_client.generate.return_value = "[]" + result = llm_splitter( + "travel help and account support", llm_client=self.mock_llm_client + ) self.assertEqual(len(result), 2) self.assertEqual(result[0], "travel help") self.assertEqual(result[1], "account support") def test_llm_splitting_manual_parsing_fallback(self): """Test manual parsing fallback when JSON parsing fails.""" - self.mock_llm_client.generate.return_value = 'chunk1, chunk2' - result = llm_splitter("travel help and account support", - llm_client=self.mock_llm_client) + self.mock_llm_client.generate.return_value = "chunk1, chunk2" + result = llm_splitter( + "travel help and account support", llm_client=self.mock_llm_client + ) # Should now extract quoted/comma-separated items self.assertEqual(result, ["chunk1", "chunk2"]) @@ -102,9 +103,7 @@ def test_prompt_creation(self): def test_debug_logging(self): """Test debug logging functionality.""" - self.mock_llm_client.generate.return_value = ( - '["travel help"]' - ) + self.mock_llm_client.generate.return_value = '["travel help"]' # Should not raise, just exercise debug path result = llm_splitter( "travel help", debug=True, llm_client=self.mock_llm_client @@ -114,9 +113,7 @@ def test_debug_logging(self): def test_llm_client_called_with_prompt(self): """Test that LLM client is called with the generated prompt.""" - self.mock_llm_client.generate.return_value = ( - '["travel help"]' - ) + self.mock_llm_client.generate.return_value = '["travel help"]' llm_splitter("travel help", llm_client=self.mock_llm_client) self.mock_llm_client.generate.assert_called_once() call_args = self.mock_llm_client.generate.call_args[0][0] @@ -138,7 +135,7 @@ def test_parse_llm_response_invalid_json(self): def test_parse_llm_response_malformed_json(self): """Test parsing of malformed JSON response.""" - response = '[123]' # Not strings + response = "[123]" # Not strings result = _parse_llm_response(response) self.assertEqual(len(result), 0) @@ -159,7 +156,7 @@ def test_parse_llm_response_quoted_strings(self): def test_parse_llm_response_numbered_items(self): """Test manual parsing with numbered items.""" - response = '1. cancel flight\n2. update email' + response = "1. cancel flight\n2. update email" result = _parse_llm_response(response) self.assertEqual(len(result), 2) self.assertEqual(result[0], "cancel flight") @@ -167,7 +164,7 @@ def test_parse_llm_response_numbered_items(self): def test_parse_llm_response_dash_items(self): """Test manual parsing with dash-separated items.""" - response = '- cancel flight\n- update email' + response = "- cancel flight\n- update email" result = _parse_llm_response(response) self.assertEqual(len(result), 2) self.assertEqual(result[0], "cancel flight") @@ -181,7 +178,7 @@ def test_parse_llm_response_valid_json(): def test_parse_llm_response_malformed_json(): - response = '[123]' + response = "[123]" result = _parse_llm_response(response) assert result == [] @@ -193,28 +190,28 @@ def test_parse_llm_response_quoted_strings(): def test_parse_llm_response_numbered_items(): - response = '1. cancel flight\n2. update email' + response = "1. cancel flight\n2. update email" result = _parse_llm_response(response) assert result == ["cancel flight", "update email"] def test_parse_llm_response_dash_items(): - response = '- cancel flight\n- update email' + response = "- cancel flight\n- update email" result = _parse_llm_response(response) assert result == ["cancel flight", "update email"] def test_parse_llm_response_empty(): - response = '' + response = "" result = _parse_llm_response(response) assert result == [] def test_parse_llm_response_garbage(): - response = 'nonsense text with no structure' + response = "nonsense text with no structure" result = _parse_llm_response(response) assert result == [] -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/tests/intent_kit/splitters/test_rule_splitter.py b/tests/intent_kit/splitters/test_rule_splitter.py index e5f0895..e0ce233 100644 --- a/tests/intent_kit/splitters/test_rule_splitter.py +++ b/tests/intent_kit/splitters/test_rule_splitter.py @@ -1,8 +1,8 @@ """ Specific tests for rule_splitter function. """ + import unittest -from unittest.mock import Mock from intent_kit.splitters.rule_splitter import rule_splitter @@ -67,8 +67,7 @@ def test_case_insensitive_splitting(self): def test_multiple_conjunctions(self): """Test input with multiple conjunctions.""" - result = rule_splitter( - "travel help, account support and booking flights") + result = rule_splitter("travel help, account support and booking flights") self.assertEqual(len(result), 3) self.assertEqual(result[0], "travel help") self.assertEqual(result[1], "account support") @@ -76,11 +75,9 @@ def test_multiple_conjunctions(self): def test_no_match_found(self): """Test when no conjunctions are found.""" - result = rule_splitter( - "I need help with something completely unrelated") + result = rule_splitter("I need help with something completely unrelated") self.assertEqual(len(result), 1) - self.assertEqual( - result[0], "I need help with something completely unrelated") + self.assertEqual(result[0], "I need help with something completely unrelated") def test_empty_input(self): """Test handling of empty input.""" @@ -100,5 +97,5 @@ def test_debug_logging(self): self.assertEqual(result[1], "account support") -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/tests/test_context.py b/tests/test_context.py index 505a272..9c09c8b 100644 --- a/tests/test_context.py +++ b/tests/test_context.py @@ -3,9 +3,12 @@ """ import pytest -from datetime import datetime -from intent_kit.context import IntentContext, ContextField, ContextHistoryEntry -from intent_kit.context.dependencies import ContextDependencies, declare_dependencies, validate_context_dependencies, merge_dependencies +from intent_kit.context import IntentContext +from intent_kit.context.dependencies import ( + declare_dependencies, + validate_context_dependencies, + merge_dependencies, +) class TestIntentContext: @@ -140,8 +143,11 @@ def test_context_thread_safety(self): def worker(thread_id): for i in range(10): - context.set(f"thread_{thread_id}_key_{i}", - f"value_{i}", modified_by=f"thread_{thread_id}") + context.set( + f"thread_{thread_id}_key_{i}", + f"value_{i}", + modified_by=f"thread_{thread_id}", + ) # Small delay to increase chance of race conditions time.sleep(0.001) value = context.get(f"thread_{thread_id}_key_{i}") @@ -174,7 +180,7 @@ def test_declare_dependencies(self): deps = declare_dependencies( inputs={"input1", "input2"}, outputs={"output1"}, - description="Test dependencies" + description="Test dependencies", ) assert deps.inputs == {"input1", "input2"} @@ -188,8 +194,7 @@ def test_validate_context_dependencies(self): context.set("input2", "value2") deps = declare_dependencies( - inputs={"input1", "input2", "missing_input"}, - outputs={"output1"} + inputs={"input1", "input2", "missing_input"}, outputs={"output1"} ) result = validate_context_dependencies(deps, context, strict=False) @@ -204,8 +209,7 @@ def test_validate_context_dependencies_strict(self): context.set("input1", "value1") deps = declare_dependencies( - inputs={"input1", "missing_input"}, - outputs={"output1"} + inputs={"input1", "missing_input"}, outputs={"output1"} ) result = validate_context_dependencies(deps, context, strict=True) diff --git a/tests/test_eval_api.py b/tests/test_eval_api.py index 0aad71c..3f34877 100644 --- a/tests/test_eval_api.py +++ b/tests/test_eval_api.py @@ -11,18 +11,16 @@ load_dataset, run_eval, run_eval_from_path, - run_eval_from_module, EvalTestCase, Dataset, EvalTestResult, - EvalResult + EvalResult, ) def test_load_dataset(): """Test loading a dataset from YAML.""" - dataset = load_dataset( - "intent_kit/evals/datasets/classifier_node_llm.yaml") + dataset = load_dataset("intent_kit/evals/datasets/classifier_node_llm.yaml") assert dataset.name == "classifier_node_llm" assert dataset.node_type == "classifier" @@ -48,7 +46,7 @@ def test_load_dataset_malformed(): import tempfile import yaml - with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f: + with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: yaml.dump({"invalid": "data"}, f) temp_path = f.name @@ -61,11 +59,7 @@ def test_load_dataset_malformed(): def test_test_case_defaults(): """Test EvalTestCase with default context.""" - test_case = EvalTestCase( - input="test input", - expected="test expected", - context={} - ) + test_case = EvalTestCase(input="test input", expected="test expected", context={}) assert test_case.input == "test input" assert test_case.expected == "test expected" @@ -80,7 +74,7 @@ def test_dataset_defaults(): description="", node_type="test", node_name="test_node", - test_cases=test_cases + test_cases=test_cases, ) assert dataset.description == "" @@ -91,12 +85,12 @@ def test_eval_result_methods(): results = [ EvalTestResult("input1", "expected1", "actual1", True, {}), EvalTestResult("input2", "expected2", "actual2", False, {}), - EvalTestResult("input3", "expected3", "actual3", True, {}) + EvalTestResult("input3", "expected3", "actual3", True, {}), ] eval_result = EvalResult(results, "test_dataset") - assert eval_result.accuracy() == 2/3 + assert eval_result.accuracy() == 2 / 3 assert eval_result.passed_count() == 2 assert eval_result.failed_count() == 1 assert eval_result.total_count() == 3 @@ -118,12 +112,13 @@ def test_eval_result_empty(): def test_run_eval_with_callable(): """Test run_eval with a callable node.""" + def simple_node(input_text, context=None): return f"Processed: {input_text}" test_cases = [ EvalTestCase("hello", "Processed: hello", {}), - EvalTestCase("world", "Processed: world", {}) + EvalTestCase("world", "Processed: world", {}), ] dataset = Dataset( @@ -131,7 +126,7 @@ def simple_node(input_text, context=None): description="Test dataset", node_type="test", node_name="simple_node", - test_cases=test_cases + test_cases=test_cases, ) result = run_eval(dataset, simple_node) @@ -143,6 +138,7 @@ def simple_node(input_text, context=None): def test_run_eval_with_error(): """Test run_eval with a node that raises exceptions.""" + def error_node(input_text, context=None): if "error" in input_text.lower(): raise ValueError("Intentional error") @@ -152,7 +148,7 @@ def error_node(input_text, context=None): EvalTestCase("hello", "success", {}), # This will fail due to exception EvalTestCase("error", "success", {}), - EvalTestCase("world", "success", {}) + EvalTestCase("world", "success", {}), ] dataset = Dataset( @@ -160,12 +156,12 @@ def error_node(input_text, context=None): description="Test dataset", node_type="test", node_name="error_node", - test_cases=test_cases + test_cases=test_cases, ) result = run_eval(dataset, error_node) - assert result.accuracy() == 2/3 + assert result.accuracy() == 2 / 3 assert not result.all_passed() assert result.failed_count() == 1 assert result.errors()[0].error == "Intentional error" @@ -173,6 +169,7 @@ def error_node(input_text, context=None): def test_run_eval_fail_fast(): """Test run_eval with fail_fast=True.""" + def error_node(input_text, context=None): if "error" in input_text.lower(): raise ValueError("Intentional error") @@ -183,7 +180,7 @@ def error_node(input_text, context=None): # This will fail and stop execution EvalTestCase("error", "success", {}), # This won't run due to fail_fast - EvalTestCase("world", "success", {}) + EvalTestCase("world", "success", {}), ] dataset = Dataset( @@ -191,7 +188,7 @@ def error_node(input_text, context=None): description="Test dataset", node_type="test", node_name="error_node", - test_cases=test_cases + test_cases=test_cases, ) result = run_eval(dataset, error_node, fail_fast=True) @@ -203,6 +200,7 @@ def error_node(input_text, context=None): def test_run_eval_custom_comparator(): """Test run_eval with custom comparator.""" + def simple_node(input_text, context=None): return input_text.upper() @@ -211,7 +209,7 @@ def case_insensitive_comparator(expected, actual): test_cases = [ EvalTestCase("hello", "HELLO", {}), - EvalTestCase("world", "WORLD", {}) + EvalTestCase("world", "WORLD", {}), ] dataset = Dataset( @@ -219,11 +217,10 @@ def case_insensitive_comparator(expected, actual): description="Test dataset", node_type="test", node_name="simple_node", - test_cases=test_cases + test_cases=test_cases, ) - result = run_eval(dataset, simple_node, - comparator=case_insensitive_comparator) + result = run_eval(dataset, simple_node, comparator=case_insensitive_comparator) assert result.accuracy() == 1.0 assert result.all_passed() @@ -231,6 +228,7 @@ def case_insensitive_comparator(expected, actual): def test_run_eval_from_path(): """Test run_eval_from_path convenience function.""" + def simple_node(input_text, context=None): return f"Processed: {input_text}" @@ -243,18 +241,18 @@ def simple_node(input_text, context=None): "name": "test_dataset", "description": "Test dataset", "node_type": "test", - "node_name": "simple_node" + "node_name": "simple_node", }, "test_cases": [ { "input": "hello", "expected": "Processed: hello", - "context": {"user_id": "test"} + "context": {"user_id": "test"}, } - ] + ], } - with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f: + with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: yaml.dump(test_data, f) temp_path = f.name @@ -270,15 +268,15 @@ def test_save_results(): """Test saving results to different formats.""" results = [ EvalTestResult("input1", "expected1", "actual1", True, {}), - EvalTestResult("input2", "expected2", "actual2", - False, {}, "test error") + EvalTestResult("input2", "expected2", "actual2", False, {}, "test error"), ] eval_result = EvalResult(results, "test_dataset") # Test CSV save import tempfile - with tempfile.NamedTemporaryFile(mode='w', suffix='.csv', delete=False) as f: + + with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f: csv_path = f.name try: @@ -288,7 +286,7 @@ def test_save_results(): Path(csv_path).unlink() # Test JSON save - with tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as f: + with tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False) as f: json_path = f.name try: @@ -298,7 +296,7 @@ def test_save_results(): Path(json_path).unlink() # Test Markdown save - with tempfile.NamedTemporaryFile(mode='w', suffix='.md', delete=False) as f: + with tempfile.NamedTemporaryFile(mode="w", suffix=".md", delete=False) as f: md_path = f.name try: diff --git a/tests/test_ollama_client.py b/tests/test_ollama_client.py index bcf3b8b..e73a4dc 100644 --- a/tests/test_ollama_client.py +++ b/tests/test_ollama_client.py @@ -20,7 +20,7 @@ def test_init_custom_base_url(self): client = OllamaClient(base_url="http://custom:11434") assert client.base_url == "http://custom:11434" - @patch('ollama.Client') + @patch("ollama.Client") def test_get_client_success(self, mock_client_class): """Test successful client creation.""" mock_client = Mock() @@ -28,10 +28,9 @@ def test_get_client_success(self, mock_client_class): client = OllamaClient() assert client._client == mock_client - mock_client_class.assert_called_once_with( - host="http://localhost:11434") + mock_client_class.assert_called_once_with(host="http://localhost:11434") - @patch('ollama.Client') + @patch("ollama.Client") def test_get_client_import_error(self, mock_client_class): """Test client creation with import error.""" mock_client_class.side_effect = ImportError("No module named 'ollama'") @@ -39,12 +38,12 @@ def test_get_client_import_error(self, mock_client_class): with pytest.raises(ImportError, match="Ollama package not installed"): OllamaClient() - @patch('ollama.Client') + @patch("ollama.Client") def test_generate_success(self, mock_client_class): """Test successful text generation.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'response': 'Test response'} + mock_response = {"response": "Test response"} mock_client.generate.return_value = mock_response client = OllamaClient() @@ -52,38 +51,31 @@ def test_generate_success(self, mock_client_class): assert result == "Test response" mock_client.generate.assert_called_once_with( - model="llama2", - prompt="Test prompt" + model="llama2", prompt="Test prompt" ) - @patch('ollama.Client') + @patch("ollama.Client") def test_generate_stream_success(self, mock_client_class): """Test successful streaming generation.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_chunks = [ - {'response': 'Hello'}, - {'response': ' '}, - {'response': 'World'} - ] + mock_chunks = [{"response": "Hello"}, {"response": " "}, {"response": "World"}] mock_client.generate.return_value = mock_chunks client = OllamaClient() result = list(client.generate_stream("Test prompt", model="llama2")) - assert result == ['Hello', ' ', 'World'] + assert result == ["Hello", " ", "World"] mock_client.generate.assert_called_once_with( - model="llama2", - prompt="Test prompt", - stream=True + model="llama2", prompt="Test prompt", stream=True ) - @patch('ollama.Client') + @patch("ollama.Client") def test_chat_success(self, mock_client_class): """Test successful chat functionality.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'message': {'content': 'Hello there!'}} + mock_response = {"message": {"content": "Hello there!"}} mock_client.chat.return_value = mock_response client = OllamaClient() @@ -91,20 +83,17 @@ def test_chat_success(self, mock_client_class): result = client.chat(messages, model="llama2") assert result == "Hello there!" - mock_client.chat.assert_called_once_with( - model="llama2", - messages=messages - ) + mock_client.chat.assert_called_once_with(model="llama2", messages=messages) - @patch('ollama.Client') + @patch("ollama.Client") def test_chat_stream_success(self, mock_client_class): """Test successful streaming chat functionality.""" mock_client = Mock() mock_client_class.return_value = mock_client mock_chunks = [ - {'message': {'content': 'Hello'}}, - {'message': {'content': ' '}}, - {'message': {'content': 'World'}} + {"message": {"content": "Hello"}}, + {"message": {"content": " "}}, + {"message": {"content": "World"}}, ] mock_client.chat.return_value = mock_chunks @@ -112,14 +101,12 @@ def test_chat_stream_success(self, mock_client_class): messages = [{"role": "user", "content": "Hello"}] result = list(client.chat_stream(messages, model="llama2")) - assert result == ['Hello', ' ', 'World'] + assert result == ["Hello", " ", "World"] mock_client.chat.assert_called_once_with( - model="llama2", - messages=messages, - stream=True + model="llama2", messages=messages, stream=True ) - @patch('ollama.Client') + @patch("ollama.Client") def test_list_models_success(self, mock_client_class): """Test successful model listing with new response structure.""" mock_client = Mock() @@ -127,11 +114,11 @@ def test_list_models_success(self, mock_client_class): # Create mock models with .model attribute mock_model1 = Mock() - mock_model1.model = 'llama2' + mock_model1.model = "llama2" mock_model2 = Mock() - mock_model2.model = 'mistral' + mock_model2.model = "mistral" mock_model3 = Mock() - mock_model3.model = 'codellama' + mock_model3.model = "codellama" # Create mock response with .models attribute mock_response = Mock() @@ -141,18 +128,18 @@ def test_list_models_success(self, mock_client_class): client = OllamaClient() result = client.list_models() - assert result == ['llama2', 'mistral', 'codellama'] + assert result == ["llama2", "mistral", "codellama"] mock_client.list.assert_called_once() - @patch('ollama.Client') + @patch("ollama.Client") def test_list_models_dict_fallback(self, mock_client_class): """Test model listing with dictionary fallback.""" mock_client = Mock() mock_client_class.return_value = mock_client # Use a mock object with .models attribute containing dicts - mock_model1 = {'model': 'llama2'} - mock_model2 = {'model': 'mistral'} - mock_model3 = {'model': 'codellama'} + mock_model1 = {"model": "llama2"} + mock_model2 = {"model": "mistral"} + mock_model3 = {"model": "codellama"} mock_response = Mock() mock_response.models = [mock_model1, mock_model2, mock_model3] mock_client.list.return_value = mock_response @@ -160,26 +147,26 @@ def test_list_models_dict_fallback(self, mock_client_class): client = OllamaClient() result = client.list_models() - assert result == ['llama2', 'mistral', 'codellama'] + assert result == ["llama2", "mistral", "codellama"] mock_client.list.assert_called_once() - @patch('ollama.Client') + @patch("ollama.Client") def test_list_models_string_fallback(self, mock_client_class): """Test model listing with string fallback.""" mock_client = Mock() mock_client_class.return_value = mock_client # Use a mock object with .models attribute containing strings mock_response = Mock() - mock_response.models = ['llama2', 'mistral', 'codellama'] + mock_response.models = ["llama2", "mistral", "codellama"] mock_client.list.return_value = mock_response client = OllamaClient() result = client.list_models() - assert result == ['llama2', 'mistral', 'codellama'] + assert result == ["llama2", "mistral", "codellama"] mock_client.list.assert_called_once() - @patch('ollama.Client') + @patch("ollama.Client") def test_list_models_empty_response(self, mock_client_class): """Test model listing with empty response.""" mock_client = Mock() @@ -196,14 +183,14 @@ def test_list_models_empty_response(self, mock_client_class): assert result == [] mock_client.list.assert_called_once() - @patch('ollama.Client') + @patch("ollama.Client") def test_list_models_unexpected_structure(self, mock_client_class): """Test model listing with unexpected response structure.""" mock_client = Mock() mock_client_class.return_value = mock_client # Test with unexpected structure - mock_response = {'unexpected': 'structure'} + mock_response = {"unexpected": "structure"} mock_client.list.return_value = mock_response client = OllamaClient() @@ -212,12 +199,12 @@ def test_list_models_unexpected_structure(self, mock_client_class): assert result == [] mock_client.list.assert_called_once() - @patch('ollama.Client') + @patch("ollama.Client") def test_show_model_success(self, mock_client_class): """Test successful model info retrieval.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'name': 'llama2', 'size': '3.8GB'} + mock_response = {"name": "llama2", "size": "3.8GB"} mock_client.show.return_value = mock_response client = OllamaClient() @@ -226,12 +213,12 @@ def test_show_model_success(self, mock_client_class): assert result == mock_response mock_client.show.assert_called_once_with("llama2") - @patch('ollama.Client') + @patch("ollama.Client") def test_pull_model_success(self, mock_client_class): """Test successful model pulling.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'status': 'success'} + mock_response = {"status": "success"} mock_client.pull.return_value = mock_response client = OllamaClient() @@ -240,12 +227,12 @@ def test_pull_model_success(self, mock_client_class): assert result == mock_response mock_client.pull.assert_called_once_with("llama2") - @patch('ollama.Client') + @patch("ollama.Client") def test_generate_text_alias(self, mock_client_class): """Test generate_text alias method.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'response': 'Test response'} + mock_response = {"response": "Test response"} mock_client.generate.return_value = mock_response client = OllamaClient() @@ -253,13 +240,12 @@ def test_generate_text_alias(self, mock_client_class): assert result == "Test response" mock_client.generate.assert_called_once_with( - model="llama2", - prompt="Test prompt" + model="llama2", prompt="Test prompt" ) def test_is_available_with_ollama(self): """Test is_available when ollama is installed.""" - with patch('ollama.Client'): + with patch("ollama.Client"): assert OllamaClient.is_available() is True def test_is_available_without_ollama(self): @@ -268,12 +254,12 @@ def test_is_available_without_ollama(self): # So we skip it or just assert True for now. assert True - @patch('ollama.Client') + @patch("ollama.Client") def test_generate_empty_response(self, mock_client_class): """Test handling of empty response.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'response': ''} + mock_response = {"response": ""} mock_client.generate.return_value = mock_response client = OllamaClient() @@ -281,12 +267,12 @@ def test_generate_empty_response(self, mock_client_class): assert result == "" - @patch('ollama.Client') + @patch("ollama.Client") def test_generate_none_response(self, mock_client_class): """Test handling of None response.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'response': None} + mock_response = {"response": None} mock_client.generate.return_value = mock_response client = OllamaClient() @@ -294,12 +280,12 @@ def test_generate_none_response(self, mock_client_class): assert result == "" - @patch('ollama.Client') + @patch("ollama.Client") def test_chat_empty_response(self, mock_client_class): """Test handling of empty chat response.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'message': {'content': ''}} + mock_response = {"message": {"content": ""}} mock_client.chat.return_value = mock_response client = OllamaClient() @@ -308,12 +294,12 @@ def test_chat_empty_response(self, mock_client_class): assert result == "" - @patch('ollama.Client') + @patch("ollama.Client") def test_chat_none_response(self, mock_client_class): """Test handling of None chat response.""" mock_client = Mock() mock_client_class.return_value = mock_client - mock_response = {'message': {'content': None}} + mock_response = {"message": {"content": None}} mock_client.chat.return_value = mock_response client = OllamaClient() @@ -322,7 +308,7 @@ def test_chat_none_response(self, mock_client_class): assert result == "" - @patch('ollama.Client') + @patch("ollama.Client") def test_list_models_exception_handling(self, mock_client_class): """Test exception handling in list_models.""" mock_client = Mock() @@ -335,7 +321,7 @@ def test_list_models_exception_handling(self, mock_client_class): assert result == [] mock_client.list.assert_called_once() - @patch('ollama.Client') + @patch("ollama.Client") def test_show_model_exception_handling(self, mock_client_class): """Test exception handling in show_model.""" mock_client = Mock() @@ -346,7 +332,7 @@ def test_show_model_exception_handling(self, mock_client_class): with pytest.raises(Exception, match="Model not found"): client.show_model("nonexistent") - @patch('ollama.Client') + @patch("ollama.Client") def test_pull_model_exception_handling(self, mock_client_class): """Test exception handling in pull_model.""" mock_client = Mock() diff --git a/tests/test_remediation.py b/tests/test_remediation.py index edf3ad1..bf4256c 100644 --- a/tests/test_remediation.py +++ b/tests/test_remediation.py @@ -2,7 +2,6 @@ Tests for the remediation strategies. """ -import pytest import json from unittest.mock import Mock, patch, MagicMock from intent_kit.handlers.remediation import ( @@ -20,10 +19,9 @@ create_fallback_strategy, create_self_reflect_strategy, create_consensus_vote_strategy, - create_alternate_prompt_strategy + create_alternate_prompt_strategy, ) -from intent_kit.node.types import ExecutionResult, ExecutionError -from intent_kit.node.enums import NodeType +from intent_kit.node.types import ExecutionError from intent_kit.context import IntentContext from intent_kit.utils.text_utils import extract_json_from_text @@ -48,7 +46,7 @@ def test_retry_strategy_success_on_first_attempt(self): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -67,7 +65,7 @@ def test_retry_strategy_success_on_retry(self): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -85,7 +83,7 @@ def test_retry_strategy_all_attempts_fail(self): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is None @@ -103,13 +101,12 @@ def test_retry_strategy_with_context(self): user_input="test input", context=context, handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None assert result.success is True - handler_func.assert_called_once_with( - **validated_params, context=context) + handler_func.assert_called_once_with(**validated_params, context=context) def test_retry_strategy_missing_parameters(self): """Test retry strategy with missing handler_func or validated_params.""" @@ -117,18 +114,14 @@ def test_retry_strategy_missing_parameters(self): # Missing handler_func result = strategy.execute( - node_name="test_node", - user_input="test input", - validated_params={"x": 5} + node_name="test_node", user_input="test input", validated_params={"x": 5} ) assert result is None # Missing validated_params handler_func = Mock() result = strategy.execute( - node_name="test_node", - user_input="test input", - handler_func=handler_func + node_name="test_node", user_input="test input", handler_func=handler_func ) assert result is None @@ -139,8 +132,7 @@ class TestFallbackToAnotherNodeStrategy: def test_fallback_strategy_creation(self): """Test creating a fallback strategy.""" fallback_handler = Mock() - strategy = FallbackToAnotherNodeStrategy( - fallback_handler, "fallback_name") + strategy = FallbackToAnotherNodeStrategy(fallback_handler, "fallback_name") assert strategy.name == "fallback_to_another_node" assert strategy.fallback_handler == fallback_handler assert strategy.fallback_name == "fallback_name" @@ -155,7 +147,7 @@ def test_fallback_strategy_success(self): node_name="test_node", user_input="test input", handler_func=Mock(), - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -176,13 +168,12 @@ def test_fallback_strategy_with_context(self): user_input="test input", context=context, handler_func=Mock(), - validated_params=validated_params + validated_params=validated_params, ) assert result is not None assert result.success is True - fallback_handler.assert_called_once_with( - **validated_params, context=context) + fallback_handler.assert_called_once_with(**validated_params, context=context) def test_fallback_strategy_no_validated_params(self): """Test fallback strategy when no validated_params provided.""" @@ -190,9 +181,7 @@ def test_fallback_strategy_no_validated_params(self): strategy = FallbackToAnotherNodeStrategy(fallback_handler, "fallback") result = strategy.execute( - node_name="test_node", - user_input="test input", - handler_func=Mock() + node_name="test_node", user_input="test input", handler_func=Mock() ) assert result is not None @@ -208,7 +197,7 @@ def test_fallback_strategy_failure(self): node_name="test_node", user_input="test input", handler_func=Mock(), - validated_params={"x": 5} + validated_params={"x": 5}, ) assert result is None @@ -217,31 +206,31 @@ def test_fallback_strategy_failure(self): class TestSelfReflectStrategy: """Test the SelfReflectStrategy.""" - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_self_reflect_strategy_creation(self, mock_llm_factory): """Test creating a self-reflect strategy.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = SelfReflectStrategy(llm_config, max_reflections=2) assert strategy.name == "self_reflect" assert strategy.llm_config == llm_config assert strategy.max_reflections == 2 - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_self_reflect_strategy_success(self, mock_llm_factory): """Test self-reflect strategy when LLM provides good analysis.""" # Mock LLM client mock_client = Mock() - mock_client.generate.return_value = json.dumps({ - "analysis": "The handler failed because of negative input", - "suggestions": ["Use absolute value", "Use positive numbers"], - "modified_params": {"x": 5}, - "confidence": 0.8 - }) + mock_client.generate.return_value = json.dumps( + { + "analysis": "The handler failed because of negative input", + "suggestions": ["Use absolute value", "Use positive numbers"], + "modified_params": {"x": 5}, + "confidence": 0.8, + } + ) mock_llm_factory.create_client.return_value = mock_client - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = SelfReflectStrategy(llm_config, max_reflections=1) handler_func = Mock(return_value="success") validated_params = {"x": -3} @@ -255,8 +244,8 @@ def test_self_reflect_strategy_success(self, mock_llm_factory): error_type="ValueError", message="Cannot handle negative numbers", node_name="test_node", - node_path=["test_node"] - ) + node_path=["test_node"], + ), ) assert result is not None @@ -265,7 +254,7 @@ def test_self_reflect_strategy_success(self, mock_llm_factory): assert result.params == {"x": 5} # Modified params handler_func.assert_called_once_with(x=5) - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_self_reflect_strategy_invalid_json(self, mock_llm_factory): """Test self-reflect strategy when LLM returns invalid JSON.""" # Mock LLM client @@ -273,8 +262,7 @@ def test_self_reflect_strategy_invalid_json(self, mock_llm_factory): mock_client.generate.return_value = "invalid json" mock_llm_factory.create_client.return_value = mock_client - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = SelfReflectStrategy(llm_config, max_reflections=1) handler_func = Mock(return_value="success") validated_params = {"x": 3} @@ -283,7 +271,7 @@ def test_self_reflect_strategy_invalid_json(self, mock_llm_factory): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -292,7 +280,7 @@ def test_self_reflect_strategy_invalid_json(self, mock_llm_factory): # Should use original params when JSON is invalid assert result.params == validated_params - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_self_reflect_strategy_llm_failure(self, mock_llm_factory): """Test self-reflect strategy when LLM fails.""" # Mock LLM client that raises exception @@ -300,8 +288,7 @@ def test_self_reflect_strategy_llm_failure(self, mock_llm_factory): mock_client.generate.side_effect = Exception("LLM error") mock_llm_factory.create_client.return_value = mock_client - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = SelfReflectStrategy(llm_config, max_reflections=1) handler_func = Mock() validated_params = {"x": 3} @@ -310,7 +297,7 @@ def test_self_reflect_strategy_llm_failure(self, mock_llm_factory): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is None @@ -319,44 +306,47 @@ def test_self_reflect_strategy_llm_failure(self, mock_llm_factory): class TestConsensusVoteStrategy: """Test the ConsensusVoteStrategy.""" - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_consensus_vote_strategy_creation(self, mock_llm_factory): """Test creating a consensus vote strategy.""" llm_configs = [ {"provider": "openai", "model": "gpt-4", "api_key": "test-key"}, - {"provider": "google", "model": "gemini", "api_key": "test-key"} + {"provider": "google", "model": "gemini", "api_key": "test-key"}, ] strategy = ConsensusVoteStrategy(llm_configs, vote_threshold=0.6) assert strategy.name == "consensus_vote" assert strategy.llm_configs == llm_configs assert strategy.vote_threshold == 0.6 - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_consensus_vote_strategy_success(self, mock_llm_factory): """Test consensus vote strategy when models agree.""" # Mock LLM clients mock_client1 = Mock() - mock_client1.generate.return_value = json.dumps({ - "approach": "Use positive numbers", - "confidence": 0.8, - "modified_params": {"x": 5}, - "reasoning": "Negative numbers cause errors" - }) + mock_client1.generate.return_value = json.dumps( + { + "approach": "Use positive numbers", + "confidence": 0.8, + "modified_params": {"x": 5}, + "reasoning": "Negative numbers cause errors", + } + ) mock_client2 = Mock() - mock_client2.generate.return_value = json.dumps({ - "approach": "Use absolute value", - "confidence": 0.9, - "modified_params": {"x": 3}, - "reasoning": "Convert negative to positive" - }) + mock_client2.generate.return_value = json.dumps( + { + "approach": "Use absolute value", + "confidence": 0.9, + "modified_params": {"x": 3}, + "reasoning": "Convert negative to positive", + } + ) - mock_llm_factory.create_client.side_effect = [ - mock_client1, mock_client2] + mock_llm_factory.create_client.side_effect = [mock_client1, mock_client2] llm_configs = [ {"provider": "openai", "model": "gpt-4", "api_key": "test-key"}, - {"provider": "google", "model": "gemini", "api_key": "test-key"} + {"provider": "google", "model": "gemini", "api_key": "test-key"}, ] strategy = ConsensusVoteStrategy(llm_configs, vote_threshold=0.5) handler_func = Mock(return_value="success") @@ -371,8 +361,8 @@ def test_consensus_vote_strategy_success(self, mock_llm_factory): error_type="ValueError", message="Cannot handle negative numbers", node_name="test_node", - node_path=["test_node"] - ) + node_path=["test_node"], + ), ) assert result is not None @@ -381,35 +371,39 @@ def test_consensus_vote_strategy_success(self, mock_llm_factory): # Should use the highest confidence vote (model 2 with x=3) assert result.params == {"x": 3} - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_consensus_vote_strategy_low_confidence(self, mock_llm_factory): """Test consensus vote strategy when confidence is too low.""" # Mock LLM clients with low confidence mock_client1 = Mock() - mock_client1.generate.return_value = json.dumps({ - "approach": "Try something", - "confidence": 0.3, - "modified_params": {"x": 5}, - "reasoning": "Low confidence approach" - }) + mock_client1.generate.return_value = json.dumps( + { + "approach": "Try something", + "confidence": 0.3, + "modified_params": {"x": 5}, + "reasoning": "Low confidence approach", + } + ) mock_client2 = Mock() - mock_client2.generate.return_value = json.dumps({ - "approach": "Try another thing", - "confidence": 0.4, - "modified_params": {"x": 3}, - "reasoning": "Another low confidence approach" - }) + mock_client2.generate.return_value = json.dumps( + { + "approach": "Try another thing", + "confidence": 0.4, + "modified_params": {"x": 3}, + "reasoning": "Another low confidence approach", + } + ) - mock_llm_factory.create_client.side_effect = [ - mock_client1, mock_client2] + mock_llm_factory.create_client.side_effect = [mock_client1, mock_client2] llm_configs = [ {"provider": "openai", "model": "gpt-4", "api_key": "test-key"}, - {"provider": "google", "model": "gemini", "api_key": "test-key"} + {"provider": "google", "model": "gemini", "api_key": "test-key"}, ] strategy = ConsensusVoteStrategy( - llm_configs, vote_threshold=0.6) # Higher threshold + llm_configs, vote_threshold=0.6 + ) # Higher threshold handler_func = Mock() validated_params = {"x": -3} @@ -417,12 +411,12 @@ def test_consensus_vote_strategy_low_confidence(self, mock_llm_factory): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is None # Should fail due to low confidence - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_consensus_vote_strategy_no_votes(self, mock_llm_factory): """Test consensus vote strategy when no models provide valid votes.""" # Mock LLM client that fails @@ -430,8 +424,7 @@ def test_consensus_vote_strategy_no_votes(self, mock_llm_factory): mock_client.generate.side_effect = Exception("LLM error") mock_llm_factory.create_client.return_value = mock_client - llm_configs = [{"provider": "openai", - "model": "gpt-4", "api_key": "test-key"}] + llm_configs = [{"provider": "openai", "model": "gpt-4", "api_key": "test-key"}] strategy = ConsensusVoteStrategy(llm_configs, vote_threshold=0.6) handler_func = Mock() validated_params = {"x": -3} @@ -440,7 +433,7 @@ def test_consensus_vote_strategy_no_votes(self, mock_llm_factory): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is None @@ -451,8 +444,7 @@ class TestRetryWithAlternatePromptStrategy: def test_alternate_prompt_strategy_creation(self): """Test creating an alternate prompt strategy.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = RetryWithAlternatePromptStrategy(llm_config) assert strategy.name == "retry_with_alternate_prompt" assert strategy.llm_config == llm_config @@ -460,17 +452,17 @@ def test_alternate_prompt_strategy_creation(self): def test_alternate_prompt_strategy_custom_prompts(self): """Test alternate prompt strategy with custom prompts.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} custom_prompts = ["Try {user_input}", "Test {user_input}"] strategy = RetryWithAlternatePromptStrategy(llm_config, custom_prompts) assert strategy.alternate_prompts == custom_prompts - @patch('intent_kit.services.llm_factory.LLMFactory') - def test_alternate_prompt_strategy_success_with_absolute_values(self, mock_llm_factory): + @patch("intent_kit.services.llm_factory.LLMFactory") + def test_alternate_prompt_strategy_success_with_absolute_values( + self, mock_llm_factory + ): """Test alternate prompt strategy with absolute value modification.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = RetryWithAlternatePromptStrategy(llm_config) handler_func = Mock(return_value="success") validated_params = {"x": -3} @@ -479,7 +471,7 @@ def test_alternate_prompt_strategy_success_with_absolute_values(self, mock_llm_f node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -488,11 +480,12 @@ def test_alternate_prompt_strategy_success_with_absolute_values(self, mock_llm_f # Should use absolute value of -3, which is 3 assert result.params == {"x": 3} - @patch('intent_kit.services.llm_factory.LLMFactory') - def test_alternate_prompt_strategy_success_with_positive_values(self, mock_llm_factory): + @patch("intent_kit.services.llm_factory.LLMFactory") + def test_alternate_prompt_strategy_success_with_positive_values( + self, mock_llm_factory + ): """Test alternate prompt strategy with positive value modification.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = RetryWithAlternatePromptStrategy(llm_config) handler_func = Mock(side_effect=[Exception("fail"), "success"]) validated_params = {"x": -3} @@ -501,7 +494,7 @@ def test_alternate_prompt_strategy_success_with_positive_values(self, mock_llm_f node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -510,11 +503,10 @@ def test_alternate_prompt_strategy_success_with_positive_values(self, mock_llm_f # Should use max(0, -3) = 0 assert result.params == {"x": 0} - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_alternate_prompt_strategy_all_strategies_fail(self, mock_llm_factory): """Test alternate prompt strategy when all strategies fail.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = RetryWithAlternatePromptStrategy(llm_config) handler_func = Mock(side_effect=Exception("always fail")) validated_params = {"x": -3} @@ -523,16 +515,15 @@ def test_alternate_prompt_strategy_all_strategies_fail(self, mock_llm_factory): node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is None - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_alternate_prompt_strategy_mixed_parameter_types(self, mock_llm_factory): """Test alternate prompt strategy with mixed parameter types.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = RetryWithAlternatePromptStrategy(llm_config) handler_func = Mock(return_value="success") validated_params = {"x": -3, "y": "test", "z": 0.5} @@ -541,7 +532,7 @@ def test_alternate_prompt_strategy_mixed_parameter_types(self, mock_llm_factory) node_name="test_node", user_input="test input", handler_func=handler_func, - validated_params=validated_params + validated_params=validated_params, ) assert result is not None @@ -606,39 +597,35 @@ def test_create_retry_strategy(self): def test_create_fallback_strategy(self): """Test creating a fallback strategy via factory function.""" fallback_handler = Mock() - strategy = create_fallback_strategy( - fallback_handler, "custom_fallback") + strategy = create_fallback_strategy(fallback_handler, "custom_fallback") assert isinstance(strategy, FallbackToAnotherNodeStrategy) assert strategy.fallback_handler == fallback_handler assert strategy.fallback_name == "custom_fallback" - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_create_self_reflect_strategy(self, mock_llm_factory): """Test creating a self-reflect strategy via factory function.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} strategy = create_self_reflect_strategy(llm_config, max_reflections=3) assert isinstance(strategy, SelfReflectStrategy) assert strategy.llm_config == llm_config assert strategy.max_reflections == 3 - @patch('intent_kit.services.llm_factory.LLMFactory') + @patch("intent_kit.services.llm_factory.LLMFactory") def test_create_consensus_vote_strategy(self, mock_llm_factory): """Test creating a consensus vote strategy via factory function.""" llm_configs = [ {"provider": "openai", "model": "gpt-4", "api_key": "test-key"}, - {"provider": "google", "model": "gemini", "api_key": "test-key"} + {"provider": "google", "model": "gemini", "api_key": "test-key"}, ] - strategy = create_consensus_vote_strategy( - llm_configs, vote_threshold=0.7) + strategy = create_consensus_vote_strategy(llm_configs, vote_threshold=0.7) assert isinstance(strategy, ConsensusVoteStrategy) assert strategy.llm_configs == llm_configs assert strategy.vote_threshold == 0.7 def test_create_alternate_prompt_strategy(self): """Test creating an alternate prompt strategy via factory function.""" - llm_config = {"provider": "openai", - "model": "gpt-4", "api_key": "test-key"} + llm_config = {"provider": "openai", "model": "gpt-4", "api_key": "test-key"} custom_prompts = ["Custom prompt 1", "Custom prompt 2"] strategy = create_alternate_prompt_strategy(llm_config, custom_prompts) assert isinstance(strategy, RetryWithAlternatePromptStrategy) @@ -675,9 +662,13 @@ def test_list_remediation_strategies(self): def test_reflection_response_valid_json(): - with patch('intent_kit.services.llm_factory.LLMFactory.create_client') as mock_create_client: + with patch( + "intent_kit.services.llm_factory.LLMFactory.create_client" + ) as mock_create_client: mock_client = MagicMock() - mock_client.generate.return_value = '{"analysis": "Looks good", "confidence": 0.9}' + mock_client.generate.return_value = ( + '{"analysis": "Looks good", "confidence": 0.9}' + ) mock_create_client.return_value = mock_client reflection_response = '{"analysis": "Looks good", "confidence": 0.9}' data = extract_json_from_text(reflection_response) @@ -685,20 +676,24 @@ def test_reflection_response_valid_json(): def test_reflection_response_malformed(): - with patch('intent_kit.services.llm_factory.LLMFactory.create_client') as mock_create_client: + with patch( + "intent_kit.services.llm_factory.LLMFactory.create_client" + ) as mock_create_client: mock_client = MagicMock() - mock_client.generate.return_value = 'analysis: Looks good, confidence: 0.9' + mock_client.generate.return_value = "analysis: Looks good, confidence: 0.9" mock_create_client.return_value = mock_client - reflection_response = 'analysis: Looks good, confidence: 0.9' + reflection_response = "analysis: Looks good, confidence: 0.9" data = extract_json_from_text(reflection_response) assert data == {"analysis": "Looks good", "confidence": 0.9} def test_vote_response_empty(): - with patch('intent_kit.services.llm_factory.LLMFactory.create_client') as mock_create_client: + with patch( + "intent_kit.services.llm_factory.LLMFactory.create_client" + ) as mock_create_client: mock_client = MagicMock() - mock_client.generate.return_value = '' + mock_client.generate.return_value = "" mock_create_client.return_value = mock_client - vote_response = '' + vote_response = "" data = extract_json_from_text(vote_response) assert data is None or data == {} diff --git a/tests/test_text_utils.py b/tests/test_text_utils.py index 8c191ef..cf41f0c 100644 --- a/tests/test_text_utils.py +++ b/tests/test_text_utils.py @@ -10,7 +10,7 @@ is_deserializable_json, clean_for_deserialization, extract_structured_data, - validate_json_structure + validate_json_structure, ) import json @@ -26,7 +26,7 @@ def test_extract_json_from_text_valid_json(self): def test_extract_json_from_text_invalid_json(self): """Test extracting invalid JSON from text.""" - text = 'Here is the response: {key: value, number: 42}' + text = "Here is the response: {key: value, number: 42}" result = extract_json_from_text(text) self.assertEqual(result, {"key": "value", "number": 42}) @@ -38,7 +38,7 @@ def test_extract_json_from_text_with_code_blocks(self): def test_extract_json_from_text_no_json(self): """Test extracting JSON when none exists.""" - text = 'This is just plain text' + text = "This is just plain text" result = extract_json_from_text(text) self.assertIsNone(result) @@ -50,13 +50,13 @@ def test_extract_json_array_from_text_valid_array(self): def test_extract_json_array_from_text_manual_extraction(self): """Test manual extraction of array-like data.""" - text = '1. First item\n2. Second item\n3. Third item' + text = "1. First item\n2. Second item\n3. Third item" result = extract_json_array_from_text(text) self.assertEqual(result, ["First item", "Second item", "Third item"]) def test_extract_json_array_from_text_dash_items(self): """Test extracting dash-separated items.""" - text = '- Item one\n- Item two\n- Item three' + text = "- Item one\n- Item two\n- Item three" result = extract_json_array_from_text(text) self.assertEqual(result, ["Item one", "Item two", "Item three"]) @@ -68,13 +68,13 @@ def test_extract_key_value_pairs_quoted_keys(self): def test_extract_key_value_pairs_unquoted_keys(self): """Test extracting key-value pairs with unquoted keys.""" - text = 'name: John, age: 30, active: true' + text = "name: John, age: 30, active: true" result = extract_key_value_pairs(text) self.assertEqual(result, {"name": "John", "age": 30, "active": True}) def test_extract_key_value_pairs_equals_sign(self): """Test extracting key-value pairs with equals sign.""" - text = 'name = John, age = 30, active = true' + text = "name = John, age = 30, active = true" result = extract_key_value_pairs(text) self.assertEqual(result, {"name": "John", "age": 30, "active": True}) @@ -86,7 +86,7 @@ def test_is_deserializable_json_valid(self): def test_is_deserializable_json_invalid(self): """Test checking invalid JSON.""" - text = '{key: value}' + text = "{key: value}" result = is_deserializable_json(text) self.assertFalse(result) @@ -130,21 +130,21 @@ def test_extract_structured_data_json_array(self): def test_extract_structured_data_manual_object(self): """Test extracting structured data with manual object extraction.""" - text = 'key: value, number: 42' + text = "key: value, number: 42" data, method = extract_structured_data(text, "dict") self.assertEqual(data, {"key": "value", "number": 42}) self.assertEqual(method, "manual_object") def test_extract_structured_data_manual_array(self): """Test extracting structured data with manual array extraction.""" - text = '1. Item one\n2. Item two' + text = "1. Item one\n2. Item two" data, method = extract_structured_data(text, "list") self.assertEqual(data, ["Item one", "Item two"]) self.assertEqual(method, "manual_array") def test_extract_structured_data_string(self): """Test extracting structured data as string.""" - text = 'This is a simple string' + text = "This is a simple string" data, method = extract_structured_data(text, "string") self.assertEqual(data, "This is a simple string") self.assertEqual(method, "string") @@ -220,28 +220,28 @@ def test_edge_cases_non_string_input(self): self.assertEqual(result, {}) def test_extract_json_from_text_json_block(self): - text = '''Here is a block: + text = """Here is a block: ```json {"foo": "bar", "num": 123} ``` - ''' + """ result = extract_json_from_text(text) self.assertEqual(result, {"foo": "bar", "num": 123}) def test_extract_json_array_from_text_json_block(self): - text = '''Some output: + text = """Some output: ```json ["a", "b", "c"] ``` - ''' + """ result = extract_json_array_from_text(text) 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