/WizSearch

Your intelligent ally for effortless information retrieval and seamless browsing across documents and the web.

Primary LanguagePythonMIT LicenseMIT

WizSearch 🌟

Your intelligent ally for effortless data retrieval across documents and seamless browsing the web.

wizsearch-demo.mp4

Ollama Quick Start Guides 🚀

Connects to large language models via the Ollama server.

Demos 🧩

Platform Demo Link Code Link
Replicate 🔄 🔗 Demo 💻 Code
OpenAI 🧠 🔗 Demo 💻 Code

How we built it 🛠️

We built Wiz Search using the following components:

  • LLM: Open source models like llama3, mistral, LLaVA, etc using Ollama for natural language understanding and generation.
  • Embeddings: BAAI/bge-small-en-v1.5 to enhance search relevance.
  • Intelligent Search: Tavily for advanced search capabilities.
  • Vector Databases: Qdrant for efficient data storage and retrieval.
  • Observability: Langfuse for monitoring and observability.
  • UI: Streamlit for creating an interactive and user-friendly interface.

Architecture

Run The Application ⚙️

  1. Clone the repo
git clone https://github.com/SSK-14/WizSearch.git
  1. Install required libraries
  • Create virtual environment
pip3 install virtualenv
python3 -m venv {your-venvname}
source {your-venvname}/bin/activate
  • Install required libraries
pip3 install -r requirements.txt
  • Activate your virtual environment
source {your-venvname}/bin/activate
  1. Set up your secrets.toml file
  • Copy example.secrets.toml into secrets.toml and replace the keys
  1. Running
streamlit run app.py

Contributing 🤝

Contributions to this project are welcome! If you find any issues or have suggestions for improvement, please open an issue or submit a pull request on the project's GitHub repository.

License 📝

This project is licensed under the MIT License. Feel free to use, modify, and distribute the code as per the terms of the license.