Feature/analyzer rules

[denis-mutuma]

This pull request primarily adds comprehensive documentation and configuration files to support development, integration, and usage of the PatchPro agent. The changes provide clear guidance for developers, detail the results of a major integration, and document the implementation of the Agent Core module. Additionally, environment and static analysis tool configuration files are included to streamline setup and code quality enforcement.

Documentation Additions and Updates:

• Added DEVELOPMENT.md with step-by-step instructions for setting up, running, and troubleshooting PatchPro locally, including artifact generation, environment variables, and performance notes.
• Added README_INTEGRATION.md summarizing the successful integration of the agent-dev branch, outlining the new modular architecture, updated dependencies, verification checklist, and next steps for CI/DevEx integration.
• Added docs/AGENT_IMPLEMENTATION.md providing a detailed summary of the Agent Core implementation, including architecture diagrams, feature lists, configuration options, usage examples, and future improvements.

Configuration and Tooling:

• Added .env.example as a template for environment variables, including OpenAI API key and optional model/agent settings.
• Added .ruff.toml to configure the Ruff static analysis tool, specifying rules, exclusions, formatting, and per-file ignores for consistent code quality enforcement.

[Copilot]

Pull Request Overview

This PR adds comprehensive documentation and configuration files to support development, integration, and usage of the PatchPro agent. The changes provide complete test infrastructure, configuration templates, and detailed implementation documentation for a CI code-repair assistant that uses static analysis and LLM integration.

• Extensive test coverage with 5 new test files covering models, LLM integration, diff generation, and analysis components
• Complete modular codebase implementing analysis reading, LLM integration, and diff generation with Pydantic models
• Environment configuration templates and static analysis rule configuration for development setup

Reviewed Changes

Copilot reviewed 63 out of 64 changed files in this pull request and generated 3 comments.

Show a summary per file

File	Description
tests/test_models.py	Comprehensive unit tests for Pydantic data models and analysis finding structures
tests/test_llm.py	Tests for LLM integration including prompt building and response parsing
tests/test_diff.py	Tests for unified diff generation and patch writing functionality
tests/test_analysis.py	Tests for analysis file reading and finding aggregation
tests/test_agent.py	Integration tests for the main agent module
tests/sample_data/	Sample JSON data files and example Python code for testing
tests/conftest.py	Test fixtures and configuration for pytest
src/patchpro_bot/	Complete modular implementation with analysis, LLM, diff, and models packages
pyproject.toml	Updated dependencies and project configuration with development tools
examples/	Sample code and configuration files demonstrating usage

Comments suppressed due to low confidence (1)

src/patchpro_bot/llm/response_parser.py:1

• Token estimation logic is inconsistent - comment says '1 token ≈ 4 chars' but implementation uses '// 3'. The comment and implementation should match, or use a more accurate tokenization method.

"""Parser for LLM responses."""

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[Copilot]

[nitpick] Using lowercase tuple instead of Tuple from typing. For Python 3.9+ this is fine, but for better compatibility with older Python versions and consistency, consider using from typing import Tuple and Tuple[List[str], int].

[Copilot]

The test assertions check for diff format components but don't verify the diff is actually valid or applicable. Consider using a proper diff parsing library to validate the complete diff structure.

[Copilot]

Same token estimation inconsistency as in response_parser.py. This duplicated logic should be extracted to a common utility function to maintain consistency.