Feat: Integrate Pinecone for Embedding and Storage

[anishvkalbhor]

Set up the vector database pipeline using Pinecone. This involves creating a service that can:

• Take extracted text from a document.
• Split the text into smaller, meaningful chunks.
• Generate vector embeddings for each chunk using an LLM.
• Store these vectors in a Pinecone index for later retrieval.

Acceptance Criteria:

• The application successfully connects to the Pinecone service.
• A function can take a large block of text and store it as chunked vectors in Pinecone.

[riyaindap7]

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