Ratatoskr

A Comprehensive Information Retrieval and Knowledge Management Platform

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.