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Running RAG

  • install LlamaIndex

    • pip install llama-index-core llama-index-embeddings-huggingface llama-index-llms-huggingface llama-index-readers-file
  • install other necessary libraries if not already installed

    • pip install torch transformers
  • add documents that will be the context for RAG

    • these documents can be in one or in multiple directories
  • run setup_rag_index.py to create the index from your desired documents.

    • change the list of directories as needed
    • run python setup_rag_index.py
  • run python run_rag.py --problem_name PROBLEM_NAME --language LANG

    • For instance, for the problem problem_opt0 in default_prompts.py in Dafny, we can run python run_rag.py --problem_name problem_opt0 --language Dafny