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LangChain and LangGraph unit in the agents course
This is a discussion to talk about the LangChain and LangGraph unit(s) in the course.
🧑🎓 If you're a student, let us know what you want to learn.
👩🏫 If you're a pro, let us know what you want to contribute and your relationship to the framework.
🙂
I would be interested in how to start creating a workflow with no/low-code, and then customize it with code.
Also, how to create persistent agents (with memory of previous conversations).
I would like to learn how to create an agent that understands documents and correlated time series data which is mentioned in the documents
I want to learn to create an Agentic RAG system using LangChain and LangGraph to improvise normal RAG applications.
Smaller models usually struggle with large inputs and usually with RAG you need to pass context that can be relatively large. That said, I'd love to learn agentic RAG patterns so you can create effective RAG pipelines with smol models.