Chat with your data using LangChain, Pinecone, and Airbyte

Dagster and Airbyte can be used together to extract unstructured data from various sources and load it into a vector database for analysis. The tutorial provides a real-world use case of using vector databases and LLMs to make sense of unstructured data. The process involves fetching Github issues, loading them into a vector database, creating a connection between the source and destination, and setting up a chat interface using an LLM to answer questions based on the data. The tutorial also covers integrating the chat interface with Slack and scraping a documentation website to provide additional information to the chatbot.

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