Yes, absolutely! LangChain is specifically designed to connect different LLMs and leverage their outputs. You can: 👉 Chain LLMs sequentially: Feed the output of one LLM as input to another, creating a multi-step workflow. 👉 Use multiple LLMs in parallel: Pass different parts of the data to different LLMs for specialized tasks. 👉 Combine LLM outputs: Integrate results from various LLMs for more comprehensive answers. LangChain provides multiple built-in tools and supports various LLM providers for flexible use. Check out the documentation for specific examples and implementation details!
very helpful! thanks.
Very well explained 👏 Thanks for insightful content!
Glad it was helpful!
Why he did not use an API key for Vertex AI?
He mentioned previously that to use the Propertietory Foundation Model, we have to use an API key.
Can we connect langchain to different LLMs in same instance and use data from one LLM into another LLM ?
Yes, absolutely! LangChain is specifically designed to connect different LLMs and leverage their outputs. You can:
👉 Chain LLMs sequentially: Feed the output of one LLM as input to another, creating a multi-step workflow.
👉 Use multiple LLMs in parallel: Pass different parts of the data to different LLMs for specialized tasks.
👉 Combine LLM outputs: Integrate results from various LLMs for more comprehensive answers.
LangChain provides multiple built-in tools and supports various LLM providers for flexible use. Check out the documentation for specific examples and implementation details!
It will be helpful to get the notebook
Dear learner, we suggest you to implement the notebook as per the discussion in the video.
He missed the API part in Vertext AI.
So confusing...
Well Explained . ThankYou