From the course: Level up LLM applications development with LangChain and OpenAI
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Conclusion
From the course: Level up LLM applications development with LangChain and OpenAI
Conclusion
- I really hope that you enjoyed the course and that you learned a lot from it. LangChain is the perfect choice to leverage the language models and to build context-aware and multitask applications. So, what to learn next. So, LangChain is backed up by a large community of experts to keep things updated and to guarantee continuous improvements, so stay tuned for the next updates and be ready to take your AI skills to the next level. So, keep up the good work and keep on learning.
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Contents
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RAG: Overview and architecture2m 12s
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Breaking down the RAG pipeline2m 50s
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Project setup3m 33s
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Load and split documents into chunks5m 6s
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Initialize a vector store (Chroma) and ingest documents5m 6s
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Create the chain: Prompt + model + parser5m 39s
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Create the chain: Add context with a retriever4m 48s
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Pass data with RunnablePassthrough and query data3m 27s
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Challenge: Create a custom agent with history3m 12s
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Solution: Add a chain with chat history5m 19s
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Solution: Context- and history-aware chatbot5m 49s
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Retrieval with query analysis1m 16s
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Connect to a data source and create an index4m 23s
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Set up query analysis to handle multiple data sources5m 55s
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Retrieval with query analysis5m 7s
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Challenge: Retrieval with multiple data sources3m 11s
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Solution: Q&A with multiple data sources7m 13s
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Getting started with MongoDB: Create an account1m 35s
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Build and deploy a free cluster1m 41s
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Set up the MongoDB environment and connect to the cluster6m 23s
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Create a secured database access (user)3m 27s
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Load sample data and create the vector store4m 18s
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Create the Atlas Vector Search index4m 4s
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Run vector search queries5m 33s
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Using agents to perform actions in chains1m 36s
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Define tools5m 37s
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Select the perfect prompt1m 12s
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Bind tools and create agent2m 19s
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Create and run the agent executor4m 41s
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Challenge: Create a multitask agent5m 31s
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Solution: Define tools and functions6m 9s
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Introducing LangServe: Installation and setup3m 35s
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Create a server49s
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Create the routes and the endpoints5m 56s
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Create a runnable to combine a prompt, a model, and output3m 35s
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Challenge: Deploy a RESTful API1m 39s
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Solution: Deploy a RESTful API2m 51s
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