conversadocs / conversadocs/code-scan-docs

[Feature]: core functionality

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#3 0 comments 0 reactions 1 assignee Claimed by @stoopidJSON View on GitHub
enhancement
Dominant language
Rust
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1
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No merged PRs in 30d

Description

### Description

Implement the core functionality of code-scan-docs, laying the foundation for the tool's primary capabilities. This includes developing the Rust-based core that handles file system operations, matrix management, LLM orchestration, plugin system integration, and the command-line interface (CLI).

### Feature Functions

- **File System Operations**
- Recursive directory traversal and file discovery
- File type detection and filtering
- Parallel file reading and caching
- Watch mode for incremental analysis
- Git integration (ignore files, diff analysis)

- **Matrix Management**
- Develop the core relationship data structure (likely a graph)
- Matrix serialization/deserialization (JSON/MessagePack)
- Dependency resolution and cycle detection
- Cross-file relationship mapping
- Implement caching and persistence layer

- **LLM Orchestration**
- Implement HTTP client for LLM APIs (OpenAI, Ollama, Anthropic)
- Async request management and rate limiting
- Token counting and context window management
- Develop prompt template engine
- Response parsing and validation
- Error handling and retries

- **Plugin System Integration**
- Python subprocess management
- Plugin discovery and registration
- Inter-process communication (JSON over stdin/stdout)
- Plugin lifecycle management
- Error isolation to ensure plugin crashes don't affect the core

- **CLI Interface**
- Argument parsing and configuration management
- Progress reporting and logging
- Output formatting and report generation
- CI/CD integration utilities

### Notes

- This feature is high-level and encompasses the core components necessary for the initial release.
- Each functionality area can be broken down into sub-tasks for detailed implementation.
- Focus on establishing a solid architecture that allows for future expansion and scalability.
- Ensure that the integration with LLMs is abstracted to support multiple providers via RESTful APIs.
- Prioritize error handling and robust logging to aid in debugging and future development.

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