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Ollama Setup with WizSearch 🦙✨

⏳ Download Ollama

Start by downloading the Ollama application from the official website: Ollama Download. Once installed, Ollama will be running at: http://localhost:11434

📦 Pull a Model

Explore the various models available in the Ollama library: Ollama Library.

To run a model, use the following command:

ollama pull llama3.1

Recommended Models:

  • Llama3.1
  • Llava (Vision model)

🌐 Tavily

Get your tavily api key by signing up at https://app.tavily.com/home

📚 Qdrant Database (Optional)

  • Use qdrant cloud:
  1. Sign up at https://cloud.qdrant.io/
  2. Create your cluster
  3. Get url database URL and API key
  • Run qdrant in local using docker:
docker run -p 6333:6333 -p 6334:6334 qdrant/qdrant

🚀 Serve with Wiz

  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 Create a secrets.toml file in .streamlit folder Refer. Add the following values:
MODEL_BASE_URL = "http://localhost:11434/v1"
MODEL_NAMES = ["llama3.1", "llava"] 
VISION_MODELS = ["llava"]
TAVILY_API_KEY = "Your Tavily API Key"
QDRANT_URL = "Your Qdrant URL" Eg: "http://localhost:6333"
QDRANT_API_KEY = "Your Qdrant API Key" (optional for cloud deployments)
  1. Running
streamlit run app.py