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Feature Request: Integrate llama-github for Enhanced GitHub Retrieval in Simple Mode #59

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JetXu-LLM opened this issue Jun 5, 2024 · 0 comments

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@JetXu-LLM
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Hello,

I hope this message finds you well. I am the maintainer of llama-github, an open-source Python library designed to empower LLM Chatbots, AI Agents, and Auto-dev Solutions by providing intelligent retrieval of code snippets, issues, and repository information from GitHub.

Proposal:
I believe that integrating llama-github into llama-coder could significantly enhance its functionality by enabling efficient retrieval of relevant GitHub content. This would align with llama-coder's philosophy of using local models, as llama-github can operate in a "simple mode" that does not require GPT-4, thus maintaining the spirit of local processing.

Benefits:

  • Efficient Retrieval: llama-github's advanced retrieval techniques can quickly provide relevant code snippets and repository information, enhancing the coding assistance provided by llama-coder.
  • Local Processing: By using the simple mode of llama-github, you can avoid external OpenAI calls, ensuring that all LLM processing remains local, which is in line with the design principles of llama-coder.
  • Repository Pool: llama-github features a repository pool mechanism that helps conserve users' GitHub API quota by efficiently managing and reusing repository data. This can be particularly beneficial for llama-coder users who may have limited API quota.
  • Enhanced Context: Integrating llama-github can provide richer context and more comprehensive answers to coding queries, improving the overall user experience.

Example Usage:
Here is a simple mode example of how llama-github can be integrated into llama-coder:

pip install llama-github
from llama_github import GithubRAG

# Initialize GithubRAG with your credentials
github_rag = GithubRAG(
    github_access_token="your_github_access_token"
)

# Retrieve context for a coding question
query = "How to create a NumPy array in Python?"
context = github_rag.retrieve_context(query, simple_mode = True)
print(context)

Additional Information:
You can find more details and documentation about llama-github here. I would be more than happy to assist with the integration process if you find this proposal valuable.

Thank you for considering this request!

Best regards,
Jet Xu

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