pinecone-assistant

To create a document QA assistant with Pinecone, you use provided scripts to provision a named assistant, upload files like PDF and Markdown, and query it to receive cited responses. This removes the need for manual embedding pipelines.

Yes, you can incrementally sync local folders to a Pinecone Assistant using mtime and size detection. The sync scripts identify changed files and optionally delete missing files from the assistant's knowledge base.

Pinecone Assistants support uploading Markdown, PDF, DOCX, JSON, and TXT files. These formats are parsed by the managed assistant service to enable cited question-and-answer retrieval.

You retrieve raw context snippets from Pinecone by using the context lookup script instead of the chat workflow. This returns unformatted text segments with metadata for debugging or integration into custom RAG pipelines.

Yes, a Pinecone API key is required to authenticate assistant creation, file uploads, and chat workflows. The scripts use the Pinecone Python SDK to handle these operations securely.

Yes, you can stream chat responses from a Pinecone Assistant. The chat script supports streaming to provide real-time generation of cited answers for support and research queries.