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Ratatoskr

A Comprehensive Information Retrieval and Knowledge Management Platform

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Overview

Ratatoskr is a tool designed to streamline information retrieval and knowledge management.

Key Features

  • Interactive Querying: Ratatoskr enables users to interact with a language model (Ollama) through a user-friendly interface to ask questions and get answers. It supports both direct querying and retrieval-augmented generation (RAG) for more contextually relevant responses.
  • Metadata Summary Generation: The system can summarize metadata information from various sources.
  • Document Processing: Ratatoskr can process both uploaded files (with type validation) and URLs (with RAG support) to extract information and store it for future retrieval.
  • Elasticsearch Integration: It seamlessly integrates with Elasticsearch to store and retrieve documents and vectors, enabling powerful search capabilities and similarity-based retrieval.

Technologies Used

  • Flask: A lightweight web framework for building the API and user interface.
  • Ollama: A local LLM model used for interactive querying and response generation.
  • Elasticsearch: A distributed search and analytics engine for document and vector storage.
  • LangChain: A framework for developing applications powered by language models.
  • Hugging Face Embeddings: Embeddings models used for semantic search and similarity calculations.

Installation

  1. Clone the Repository:

    git clone [https://github.com/](https://github.com/)<your-username>/ratatoskr.git
cd ratatoskr

  2. Install Dependencies:

    python3 -m venv .venv 
source .venv/bin/activate
pip install -r requirements.txt

  3. (Optional) Docker Setup: If you prefer using Docker:

    docker build -t ratatoskr .
docker run -it \
   --name ratatoskr \
   -p 6666:6666 \
   -v $(pwd)/config.yaml:/app/config.yaml \
   ratatoskr

  4. Configuration:

    • Rename config_sample.yaml to config.yaml.
    • Update config.yaml with your specific settings.

  5. Start Ratatoskr:

    • From Source: 
      python src/main.py
    • Using Docker: 
      docker start ratatoskr

Now you can access Ratatoskr at http://localhost:6666.

Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.