feat: Create LocalRAG project with local models#83
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This commit introduces a new project, LocalRAG, which implements a Retrieval Augmented Generation pipeline using entirely local models for embeddings and language generation. Key features: - Project structure based on common Python application layouts. - Local sentence transformer embeddings (e.g., all-MiniLM-L6-v2) via `sentence-transformers`. - Local Large Language Model (e.g., distilgpt2) via Hugging Face `transformers`. - Configurable model choices through `src/config.py`. - Basic RAG pipeline in `src/core.py` and `src/main.py`. - Data loading and processing for text files. - Placeholder for vector database functionality. - Comprehensive test suite (`tests/`) for all components. - Detailed README.md with setup and usage instructions. Note: Due to environmental constraints (insufficient disk space for PyTorch installation), I could not successfully run the automated tests during development. The code and test suite are otherwise complete.
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This commit introduces a new project, LocalRAG, which implements a Retrieval Augmented Generation pipeline using entirely local models for embeddings and language generation.
Key features:
sentence-transformers.transformers.src/config.py.src/core.pyandsrc/main.py.tests/) for all components.Note: Due to environmental constraints (insufficient disk space for PyTorch installation), I could not successfully run the automated tests during development. The code and test suite are otherwise complete.