How to Set Up a Local and Cloud LLM Aggregator Using Open WebUI

Why Aggregate Local and Cloud LLMs? Large Language Models (LLMs) like Llama 2, Mistral, and OpenAI’s GPT-4 offer unique strengths. By combining local and cloud-based models, you can:

• Maximize flexibility: Use local models for privacy-sensitive tasks and cloud APIs for state-of-the-art performance.
• Reduce costs: Offload lightweight tasks to local models and reserve cloud APIs for critical workloads.
• Future-proof your setup: Stay ready for new models, whether they’re local or cloud-based.

Prerequisites

• A machine with 16GB+ RAM (GPU recommended for speed).
• Basic terminal/Docker knowledge.
• Docker and Python installed.
• API keys for cloud services like OpenAI.

Step 1: Set Up Ollama (Local Model Manager)

Ollama simplifies running LLMs locally. Install via Docker:

docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama          

Download models like Llama 2 and Mistral:

docker exec -it ollama ollama pull llama2  
docker exec -it ollama ollama pull mistral          

Step 2: Deploy Open WebUI

Open WebUI is a user-friendly frontend for Ollama and cloud APIs. Deploy it with:

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui ghcr.io/open-webui/open-webui:main          

Access the UI at https://localhost:3000.

Step 3: Configure Local Models

1. Add Models: In Open WebUI, navigate to settings and link Ollama (default URL: https://host.docker.internal:11434).
2. Switch Models: Select any downloaded model from the dropdown during chats.
3. Customize Presets: Save prompts tailored to specific models (e.g., code generation with Mistral, creative writing with Llama 2).

Step 4: Integrate Cloud APIs (e.g., OpenAI)

1. Get Your API Key: Log in to your OpenAI account and generate an API key.
2. Add OpenAI to Open WebUI:
3. Switch Between Local and Cloud Models:

Advanced Tips

• Hybrid Workflows: Use local models for drafts and cloud APIs for final refinements.
• Cost Management: Set usage limits for cloud APIs to avoid unexpected bills.
• Security: Use HTTPS and auth tools like Caddy for secure remote access.

Conclusion

With Open WebUI, you’ve built a hybrid AI hub that combines the best of local and cloud-based models. Whether you prioritize privacy, cost, or performance, this setup adapts to your needs.

?? GitHub Repos: Ollama | Open WebUI

Ready to innovate? Dive deeper into the code, share your setups, and tag me in your experiments! ????