RepoPilot is a one-stop Python library that revolutionizes the way developers interact with and understand their codebases. Utilizing advanced Large Language Models (LLMs), RepoPilot acts as a multi-agent system, offering a next-generation coding assistant for comprehensive codebase exploration and impact analysis. Designed for developers who seek deeper insights into their projects, RepoPilot simplifies complex code analysis tasks, making it an indispensable tool for modern software development.
Key Features
- Whole Repository Understanding: Unlike other coding assistants, RepoPilot is engineered to grasp the full context of your entire codebase, enabling a more comprehensive analysis and more accurate recommendations.
- Natural Language Queries: Interact with your codebase using conversational queries. Ask RepoPilot about specific features, code impacts, and more, just like talking to an AI assistant.
- Codebase Exploration and Analysis: Delve into your codebase with ease. Understand how particular features are implemented and assess the impact of potential changes. Actionable Insights and Recommendations: Get practical suggestions and automated actions based on RepoPilot's deep understanding of your code.
- Seamless Integration: Integrate RepoPilot into your existing development workflow with its Python API, allowing for flexible and powerful code interactions.
RepoPilot is a multi-agent system that consists of three main components: the Planning Agent, the Navigation Agent, and the Analysis Agent.
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Planning Agent is responsible for understanding the user's query and determining a draft plan of action. The planning agent is based on GPT-4 prompted with a query and general information about the codebase.
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Navigation Agent is responsible for navigating the codebase, finding relevant code snippets and storing high value information related to the query into the working memory. The navigation agent is implemented with ReAct-like architecture with dynamic backtracking as well as multi-languages language server protocol (mLSP) support to efficiently navigate inside the codebase (go-to-definition, find references, code search, semantic code search, etc).
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Analysis Agent is responsible for finally giving the user the insights and recommendations based on the query and the information stored in the working memory. The analysis agent is based on GPT-4 prompted with the query and the information stored in the working memory.
Quick Demo:
demo.repopilot.-.official.mp4
RepoPilot uses Zoekt for code search. Please install Zoekt before installing RepoPilot. Zoekt requires latest Go installation, please follow the instructions here to install Go.
go get github.com/sourcegraph/zoekt/
# Install Zoekt Index
go install github.com/sourcegraph/zoekt/cmd/zoekt-index
# Install Zoekt Web Server
go install github.com/sourcegraph/zoekt/cmd/zoekt-webserverWe also need to install universal-ctags for semantic code search. Please follow the instructions here. Remember to set the environment variable of CTAGS CTAGS_COMMAND=universal-ctags. Finally, we can install RepoPilot.
pip3 install repopilot# Importing the RepoPilot library
import repopilot
# Initialize RepoPilot with the path to your code repository
repo_path = "/path/to/your/codebase"
rp = repopilot.RepoPilot(repo_path)
# Example 1: Natural Language Query about a Feature
# User asks about the login feature in a conversational manner
query = "Please explain how the login features work in this codebase."
login_feature_explanation = rp.query_codebase(query)
print("Login Feature Explanation:")
print(login_feature_explanation)
# Example 2: Impact of Changes in Natural Language
# User asks about the impact of a specific change
change_query = "What would be the impact if I refactor the authentication module?"
change_impact = rp.query_codebase(change_query)
print("Impact of Refactoring Authentication Module:")
print(change_impact)
# Example 3: Code Improvement Suggestions in Conversational Style
# User asks for general improvement suggestions
improvement_query = "How can I improve the code quality of the project?"
improvement_suggestions = rp.query_codebase(improvement_query)
print("Code Improvement Suggestions:")
print(improvement_suggestions)
# Example 4: Searching for Code Patterns using Natural Language
# User wants to find certain types of functions or methods
search_query = "Find all asynchronous functions in the codebase."
async_functions = rp.query_codebase(search_query)
print("Asynchronous Functions Found:")
print(async_functions)
# Example 5: Bug reproduction from Bug reports
# User wants to generate a fail-to-pass test case from a bug report
search_query = "Write a JUnit test case code in java that reproduce the failure behavior of the given bug report as following: {bug_report (in this case is Time 23 Defects4J)}."
bug_reproduction = rp.query_codebase(search_query)
print("Bug Reproduction:")usage: repopilot [--help] [command: setup, query]Usage: repopilot setup [OPTIONS] REPO_PATH [ARGS]...
╭─ Arguments ──────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ * repo_path TEXT The path to the repository to set up. [default: None] [required] │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ * --repository-name TEXT The name of the repository. [default: None] [required] │
│ * --language TEXT The programming language of the repository. [default: None] [required] │
│ --commit TEXT The commit to set up. │
│ --local-agent TEXT local agent path [default: model/mistral-7B] │
│ --devices TEXT devices to use for inference [default: 0] │
│ --clone-dir TEXT The directory to clone the repository to. [default: data/repos] │
│ --gh-token TEXT The GitHub token to use for cloning private repositories. [default: ""] │
│ --help Show this message and exit. │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Usage: repopilot query [OPTIONS] REPO_PATH [ARGS]...
╭─ Arguments ─────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ * repository_name TEXT The name of the repository to query. [default: None] [required] │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Options ───────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --planner-type TEXT The type of planner to use. [default: adaptive] │
│ --save-trajectories-path TEXT The path to save the trajectories to. [default: None] │
│ --help Show this message and exit. │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯We would like to thank the development of Multiplspy, Supporting Multiple languages chunking and codetext parser for the multi-language support of the navigation agent.