Use the OpenAI API to call Mistral, Llama, and other LLMs (works with local AND serverless models)

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AI Summary

Video Summary: Swapping Serverless Models for OpenAI Requests

• Introduction
  • The video discusses how to swap in a serverless model for OpenAI requests.
  • Encountered some issues but recent changes have simplified the process.
  • The same OpenAI API can be used for local or serverless models with a few overrides.
• Serverless Model Integration
  • Serverless options like Together have OpenAI API compatibility.
  • Python and Node SDKs can be used to make requests with the same structure as the OpenAI API.
  • AMA (local models) recently introduced OpenAI compatibility but lacks function calling support.
• Configuration and Overrides
  • Requires specifying API key, organization, and base URL in the environment file.
  • For local models, direct requests to Local Host with the API key.
  • For serverless models like Together, set the base URL and API key.
  • Overrides allow toggling between models by changing the base URL, API key, and model.
• Demonstration
  • Showed how to set up and use serverless options for chat completions requests.
  • Discussed streaming responses and parallel function calling.
  • Noted that only certain models support tool calling out of the box.
  • AMA does not yet support function calling, but it may soon.
• Lang Chain Compatibility
  • Lang Chain works similarly to OpenAI API with a few overrides.
  • Demonstrated how to use different models with Lang Chain.
• Agent Setup
  • Discussed setting up an agent with different LLMs as the “brain.”
  • Showed how to swap between different models within the agent setup.
  • Noted that local models may be slower but offer privacy benefits.
  • Serverless options are faster and cheaper but may have limitations.
• Model Performance
  • Some models drift or do not perform as expected, especially with tool calling.
  • OpenAI remains the gold standard with good support.
• Conclusion
  • The ability to interchange models easily is beneficial and cost-effective.
  • The presenter prefers serverless for generating text and GPT versions for tool outputs.
  • AMA’s support for OpenAI is a positive development.
  • The future looks promising for easily swapping models.
  • GitHub code is available for experimentation.
• Resources
  • GitHub code for the project is provided in the video description.