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Updated 2 months ago

Looking for an example with Chroma for

Looking for an example with Chroma for managing documents. Retrieving Document 1 and Generating Embedding: The text of Document 1 is retrieved from ChromaDB and an embedding is generated using LlamaIndex.

ChatGPT Interaction : An request is sent to the ChatGPT API to obtain a summary of Document 1.

Adding Document 2: The text and embedding of Document 2 are added to ChromaDB.

ChatGPT Interaction: An optional request is sent to the ChatGPT API to generate a comparison between Document 1 and Document 2.

Updating Document 1: The text of Document 1 is updated, a new embedding is generated, and it is stored in ChromaDB.

ChatGPT Interaction: An optional request is sent to the ChatGPT API to summarize the changes made to Document 1.

Deleting Document 2: Document 2 is deleted from ChromaDB.
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use an ingestion pipeline with a docstore and vector store attached

Plain Text
pipeline = IngestionPipeline(transformations=[], docstore=docstore, vector_store=vector_store)


Ignore the cache in this example, its not really needed, and swap in redis vector store for chroma
https://docs.llamaindex.ai/en/stable/examples/ingestion/redis_ingestion_pipeline/
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