Repo Explainer Agent

Description

The Repo Explainer Agent is a tool designed to understand and explain code repositories. It analyzes the repository structure, code, and documentation to provide insights and answer user queries about the codebase.

How it Works: The Agent's Flow

The Repo Explainer Agent processes a code repository and user queries through a sequence of operations orchestrated by src/graph.py. The flow can be broadly divided into initial analysis and query-driven analysis:

Phase 1: Initial Repository Ingestion & Baseline Analysis

This phase occurs once when a new repository is introduced.

1. Repository Initialization (initialize_repository_node):

   • Clones the target Git repository (if a URL is provided) or prepares a local path.
   • Performs essential setup for the analysis.

2. Core Content Analysis:

   • Static Code Analysis (static_code_analyzer_node): Parses the source code to identify definitions (classes, functions, etc.), dependencies, and relationships between code components. This builds a structural map of the codebase.
   • Documentation Parsing (documentation_parser_node): Extracts information from documentation files (e.g., READMEs, Markdown files) and potentially inline comments to capture explicit developer knowledge.

3. Initial High-Level Summarization (initial_high_level_summarizer_node):

   • Based on the data gathered from static code analysis and documentation parsing, this node generates an initial, high-level overview of the repository's purpose, main components, and general architecture. This summary serves as a baseline understanding.

Phase 2: User Query Processing & Targeted Analysis

This phase is triggered when a user submits a query.

4. User Query Parsing (user_query_parser_node):

   • The agent processes the user's natural language question to determine its intent (e.g., "explain this file," "describe the architecture," "what is the purpose of this repo?").

5. Conditional Targeted Analysis:

   • Based on the parsed query intent, the graph routes the request to the appropriate specialized node(s):
     • File-Specific Explanation (file_explainer_node): If the query pertains to a specific file, this node is activated to generate a detailed explanation of that file's role, contents, and connections.
     • Architecture Analysis (architecture_analyzer_node): If the user asks about the repository's architecture, this node performs a more in-depth analysis of the codebase's structure, design patterns, and module interactions.
     • For general overview queries (e.g., "tell me about this repo"), the system may leverage the summary already generated by the initial_high_level_summarizer_node.

6. Response Generation (response_generator_node):

   • This final node synthesizes all relevant information—from the initial analysis, the parsed user query, and any targeted analysis performed (like file or architecture explanations)—to construct a coherent and informative answer for the user.

This structured flow, moving from broad initial analysis to specific query-driven deep dives, allows the Repo Explainer Agent to build a comprehensive understanding and provide relevant answers about the codebase.

Installation

1. Clone the repository:

   git clone https://github.com/your-username/repo_explainer_agent.git
   cd repo_explainer_agent

2. Build the Docker image:

   docker/build

   Alternatively, you can build it manually:

   docker build -t repo_explainer_agent .

Usage

To run the Repo Explainer Agent, use the provided docker/run script or execute the Docker container directly.

Example:

To ask a question about a specific repository, you can run:

docker/run https://github.com/andreimatveyeu/jackmesh.git "Where is the class Port defined?"

This command will:

1. Initialize the jackmesh repository.
2. Analyze its contents.
3. Attempt to answer the question "Where is the class Port defined?".

Project Structure

The project is organized into the following main directories:

• src/: Contains the core logic of the agent.
  • core/: Core components like data models, parsers, and state management.
  • nodes/: Different processing nodes responsible for specific tasks (e.g., static code analysis, documentation parsing).
  • utils/: Utility functions used across the project.
  • graph.py: Manages the graph representation of the repository and the flow of information between nodes.
• docker/: Contains Docker-related files for building and running the agent in a containerized environment.
  • Dockerfile: Defines the Docker image.
  • build: Script to build the Docker image.
  • run: Script to run the Docker container with specified arguments.

License

This project is licensed under the Apache License version 2.0 - see the LICENSE file for details.