How to deploy Ollama
Installation:
- Download Ollama: Get the Ollama package from the GitHub repository.
- Install Dependencies: Ensure you have any required dependencies, including libraries for your specific model.
- Verify Installation: Use
ollama --version
to confirm Ollama is installed correctly.
2. Model Deployment and Usage:
- Pull the Model: Use the
ollama pull <model_name>
command to download the desired model. - Run the Model: Use
ollama run <model_name>
to initiate the model's execution. - Interacting with the Model: Ollama provides an API at
http://localhost:11434/api/generate
for interacting with the model. - Optional: Web UI: Explore Open WebUI for a user-friendly interface to manage and interact with models.
- Optional: Custom Applications: Build custom applications using libraries like FastAPI and Gradio to integrate Ollama models into your workflows.
How to deploy open-webui
Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with built-in inference engine for RAG, making it a powerful AI deployment solution.
Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using Python 3.11 to avoid compatibility issues.
Install Open WebUI: Open your terminal and run the following command to install Open WebUI:
pip install open-webui
Running Open WebUI: After installation, you can start Open WebUI by executing:
open-webui serve
This will start the Open WebUI server, which you can access at http://localhost:8080
To upgrade the Open-webui components
pip install open-webui --upgrade
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