How To Use AutoGen With ANY Open-Source LLM FREE (Under 5 min!)
Getting Open-Source Models Working with Autogen
In this video, the speaker demonstrates how to use open-source models with Autogen. They introduce LM Studio as a tool for downloading and running open-source models on Windows or Mac. The process involves selecting a model, setting up a server, and connecting Autogen to the server.
LM Studio: Downloading Open-Source Models
- LM Studio is a powerful tool that allows users to download and run any open-source model on Windows or Mac.
- Visit LM studio.ai to download the required version for your operating system.
- Search for the desired model within LM Studio's interface.
- Choose the appropriate version of the model based on its compatibility and performance.
- The speaker recommends using Mistol 7B Instruct version 0.1 for Autogen.
- Download the selected model from LM Studio.
Setting Up a Local Server
- Install LM Studio and launch it.
- Click on the "Local Server" button in LM Studio's interface.
- Select the desired model from the dropdown menu.
- Start the server by clicking "Start server."
Connecting Autogen to the Local Server
- Import Autogen into your code environment.
- Modify the configuration settings in Autogen:
- Keep AI type as "open AI."
- Set API base to "localhost:1234/v1" (the local server address).
- Leave API key as null since no API key is needed for local servers.
Running Autogen with Open-Source Models
- Define an assistant agent and user proxy in your code, specifying their roles and settings.
- Execute your code, triggering interactions between the assistant agent and user proxy.
- Use prompts like "You are a coder specializing in Python" for assistant agent and tasks like "Write a Python method to output numbers 1 to 100" for user proxy.
- Monitor the inference happening in LM Studio's interface, observing the logs and outputs.
Challenges and Future Improvements
- The speaker acknowledges that there are still challenges in making Autogen work as well as GPT-4.
- Some issues may arise with prompt templates, causing incomplete or incorrect responses.
- Ongoing efforts are being made to improve Autogen's performance and address these challenges.
Conclusion
The speaker concludes by highlighting the ease of using open-source models with Autogen through LM Studio. They encourage viewers to explore this approach further and share their experiences.