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Chroma - Vector Database for LLM Applications | OpenAI integration
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☕️ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲:
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In this video, we'll take a look at the ChromaDB vector database, which can be used to store embedding data and retrieve embeddings that are most similar to an input query.
We'll take a look at loading and. embedding a real-life text dataset, and then querying for similar vectors. We'll also look at different client options for in-memory databases and persistent databases with Chroma, and how to integrate with OpenAI's embeddings API.
📌 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀:
00:00 Intro
00:56 ChromaDB introduction
02:18 Creating a ChromaDB client and collections
03:32 Adding documents to a collection
08:45 Passing filters to collection queries
10:24 Reading in real-life dataset with Polars
13:10 Creating Embeddings with OpenAI APIs
18:11 Adding OpenAI vectors to ChromaDB
28:27 Persisting the ChromaDB database
𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮:
📚 𝗙𝘂𝗿𝘁𝗵𝗲𝗿 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
#python #chromadb #datascience
To support the channel and encourage new videos, please consider buying me a coffee here:
In this video, we'll take a look at the ChromaDB vector database, which can be used to store embedding data and retrieve embeddings that are most similar to an input query.
We'll take a look at loading and. embedding a real-life text dataset, and then querying for similar vectors. We'll also look at different client options for in-memory databases and persistent databases with Chroma, and how to integrate with OpenAI's embeddings API.
📌 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀:
00:00 Intro
00:56 ChromaDB introduction
02:18 Creating a ChromaDB client and collections
03:32 Adding documents to a collection
08:45 Passing filters to collection queries
10:24 Reading in real-life dataset with Polars
13:10 Creating Embeddings with OpenAI APIs
18:11 Adding OpenAI vectors to ChromaDB
28:27 Persisting the ChromaDB database
𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮:
📚 𝗙𝘂𝗿𝘁𝗵𝗲𝗿 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
#python #chromadb #datascience
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