From the course: Complete Guide to Data Lakes and Lakehouses
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Installation and code walkthrough
From the course: Complete Guide to Data Lakes and Lakehouses
Installation and code walkthrough
- [Instructor] We just described the architecture of our project and the data flow. With the diagram we saw before in our mind, let's do a quick walk through the Python script. You can find it in the rag folder, and it's called manage_chroma_db.py. The code begins by importing several libraries and loading environment variables from line 1 to 17. Then from line 19, it defines some constants, like the path for the Chroma database and a template for prompts. Then in line 31st, logging is set up to show info level messages with timestamps, which helps in tracking the script execution. The main method at line 45 is the heart of the script. It parses common line arguments to determine whether to reset the database or run a query. Based on these arguments, it either clears the database, queries it, or populates it with new documents. The load_documents at line 65 fetches the documents from MinIO using the S3 directory loader. The split_documents method take the loaded documents and splits…
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Introduction to LLMs and vector embeddings: Llama3m 54s
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Introduction to RAG (retrieval-augmented generation)1m 29s
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Introduction to vector databases: Chroma2m 10s
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What is Langchain?1m 3s
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Generative AI project overview: Sales copilot3m 45s
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Installation and code walkthrough3m 30s
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Project execution: Using the copilot7m 35s
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