Fine-Tune a Smaller Open Source LLM with Devcontainer Repositories

[nkkko]

Is your feature request related to a problem? Please describe. Current large language models (LLMs) can be resource-intensive and lack the specificity to generate high-quality devcontainer.json files for diverse repositories. Fine-tuning a smaller, open-source LLM with specific data can enhance its accuracy and efficiency.

Describe the solution you'd like

• Fetch repositories that already have devcontainer.json files or use our db if adequate.
• Extract relevant contexts from these repositories as described in the script.
• Fine-tune a smaller, open-source LLM (e.g., llama, etc.) using these context-devcontainer.json pairs to improve its ability to generate high-quality devcontainer configurations.

Describe alternatives you've considered

• Continuing to rely on larger, more generic models, but this approach may not be as effective or efficient.
• Using pre-trained models without fine-tuning, which might not capture the specifics of devcontainer.json generation.

Additional context

1. Data Collection:

   • Script to fetch repositories with existing devcontainer.json files.
   • Extract and format relevant context from these repositories.

2. Model Fine-Tuning:

   • Use the collected data to fine-tune a smaller, open-source LLM.
   • Ensure the model is trained to understand context and generate appropriate devcontainer.json configurations.

3. Implementation:

   • Integrate the fine-tuned model into the existing workflow for generating devcontainer.json files.
   • Test the model to ensure it produces accurate and useful configurations.

This approach will enhance the efficiency and accuracy of generating devcontainer files, leveraging a smaller, optimized model tailored to the specific use case.