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| # Documentation | |
| ## File Structure: | |
| - `docs/` - Documentation files | |
| - `code/` - Code files | |
| - `storage/` - Storage files | |
| - `vectorstores/` - Vector Databases | |
| - `.env` - Environment Variables | |
| - `Dockerfile` - Dockerfile for Hugging Face | |
| - `.chainlit` - Chainlit Configuration | |
| - `chainlit.md` - Chainlit README | |
| - `README.md` - Repository README | |
| - `.gitignore` - Gitignore file | |
| - `requirements.txt` - Python Requirements | |
| - `.gitattributes` - Gitattributes file | |
| ## Code Structure | |
| - `code/main.py` - Main Chainlit App | |
| - `code/config.yaml` - Configuration File to set Embedding related, Vector Database related, and Chat Model related parameters. | |
| - `code/modules/vector_db.py` - Vector Database Creation | |
| - `code/modules/chat_model_loader.py` - Chat Model Loader (Creates the Chat Model) | |
| - `code/modules/constants.py` - Constants (Loads the Environment Variables, Prompts, Model Paths, etc.) | |
| - `code/modules/data_loader.py` - Loads and Chunks the Data | |
| - `code/modules/embedding_model.py` - Creates the Embedding Model to Embed the Data | |
| - `code/modules/llm_tutor.py` - Creates the RAG LLM Tutor | |
| - The Function `qa_bot()` loads the vector database and the chat model, and sets the prompt to pass to the chat model. | |
| - `code/modules/helpers.py` - Helper Functions | |
| ## Storage and Vectorstores | |
| - `storage/data/` - Data Storage (Put your pdf files under this directory, and urls in the urls.txt file) | |
| - `storage/models/` - Model Storage (Put your local LLMs under this directory) | |
| - `vectorstores/` - Vector Databases (Stores the Vector Databases generated from `code/modules/vector_db.py`) | |
| ## Useful Configurations | |
| set these in `code/config.yaml`: | |
| * ``["embedding_options"]["embedd_files"]`` - If set to True, embeds the files from the storage directory everytime you run the chainlit command. If set to False, uses the stored vector database. | |
| * ``["embedding_options"]["expand_urls"]`` - If set to True, gets and reads the data from all the links under the url provided. If set to False, only reads the data in the url provided. | |
| * ``["embedding_options"]["search_top_k"]`` - Number of sources that the retriever returns | |
| * ``["llm_params]["use_history"]`` - Whether to use history in the prompt or not | |
| * ``["llm_params]["memory_window"]`` - Number of interactions to keep a track of in the history | |
| ## LlamaCpp | |
| * https://python.langchain.com/docs/integrations/llms/llamacpp | |
| ## Hugging Face Models | |
| * Download the ``.gguf`` files for your Local LLM from Hugging Face (Example: https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF) |