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Description
Is your feature request related to a problem?
- Yes, it is related to a problem
Describe the feature you'd like
🌟 Feature Description
This feature introduces a new, advanced tool for the DevRel Agent: a General-Purpose GitHub Query Tool. Instead of using pre-defined functions, this tool understands a user's natural language question, generates the Python code needed to query the GitHub API, executes it, and returns the answer.
This allows it to handle a wide variety of questions like:
- "What repositories does sm0kxy contribute to?"
- "How many open issues are in the Devr.AI repository?"
🔍 Problem Statement
Creating a separate, hard-coded tool for every possible GitHub query is not scalable. A more flexible, intelligent solution is needed to handle a wide range of user questions without bloating the agent's toolkit.
🎯 Expected Outcome
The result is a single, versatile tool that acts as a natural language interface to the GitHub API. It will:
- Increase the agent's versatility to answer ad-hoc questions.
- Reduce the need to develop numerous, narrowly-focused tools.
- Empower users by letting them query GitHub using plain English.
📷 Screenshots and Design Ideas
The tool functions by translating a user's question into executable Python code.
- Trigger: The agent receives a query like, "How many repos does 'AOSSIE-Org' have?"
- Code Generation: The tool uses an LLM to translate the query into a Python script that calls the GitHub API.
- Secure Execution: The generated script is run in a secure, isolated sandbox environment to prevent any risk to the host system.
- Return Result: The output from the script's execution is captured.
- Final Answer: The agent takes the result and formats it into a human-readable response.
📋 Additional Context
- Security: The use of a sandboxed environment is a critical, built-in part of the tool to ensure all code execution is safe.
- Scope: Initially, the tool should be limited to read-only (
GET) operations for maximum safety.
Record
- I agree to follow this project's Code of Conduct
- I want to work on implementing this feature