Hello everyone! I decided that I would like to do a project using LangGraph. For those who are unfamiliar with LangGraph: LangGraph is a library that builds on top of LangChain to simplify and automate the process of creating advanced language model-based workflows, particularly for Retrieval-Augmented Generation (RAG) tasks. It is good at managing complex workflows by leveraging graph-based structures for modular, reusable components. (https://langchain-ai.github.io/langgraph/tutorials/introduction/) Some examples of worflows are shown in the images below. Basically we can have a list of tools, agents that would do different things... Do you have any ideas of applications that I can create other than the basic/generic ones as the "costumer support" ones or maybe having the worflows shown below to come up with other ideas. I really don't know what approach I can take and if some of you have any ideas from where I can start it would be awesome. Thank you!😄

Can someone tell me what's wrong with the code below?

I strongly recommend the courses from DeepLearning.AI, I find them very useful and easy to follow 😄https://www.deeplearning.ai/courses/

Hear from practitioners on a wide range of topics on LLMs, including RAG, evaluation, applications, fine-tuning and prompt engineering. https://parlance-labs.com/education/

I have found this medium series that I found really interesting to understand what is a RAG and how you can implement one and all the technical consideration https://medium.com/@vipra_singh/building-llm-applications-introduction-part-1-1c90294b155b