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Query local data using an Embedding model to convert your data into vectors and an LLM to respond to queries.

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LLM Search

Query for information in documents using natural language and the power of LLMs and semantic search through local vector indexes.

Installation

  1. Install poetry with pip install poetry
  2. Install the project and required dependencies with poetry install
  3. Set your OpenAI secret key with export OPENAI_API_KEY=<YOUR KEY>
  4. Add text files to the "data" folder as context.
  5. Run the chat interface with poetry run python llm_search/main.py

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Query local data using an Embedding model to convert your data into vectors and an LLM to respond to queries.

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