What to Ask Leina to Do with Pinecone
Copy a prompt, add your details, and send it to Leina in your connected team chat.
Describe an index and read its statistics using its host.
Describe Pinecone index [index name], then use its host to retrieve namespace statistics.
Search a namespace using an explicit vector and topK.
Query Pinecone host [index host], namespace [namespace], with vector [numeric vector] and topK [number]. Include metadata and summarize returned matches.
Get Started with Pinecone
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Connect Your Account
Connect using your Pinecone API Key.
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Try a Task
Tell Leina what you need in your team chat. Include the source, destination, and expected result.
Set Up Leina in Your Chat → -
Check the Result
Review the result and any changes in the connected app.
Supported Pinecone Capabilities
Pinecone operations let an AI assistant inspect indexes, store vectors, and query returned similarity matches in a namespace.
- Inspect an index
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Describe an index and read its statistics using its host.
- Describe Index
- Get Index Stats
- Query similar vectors
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Search a namespace using an explicit vector and topK.
- Query Vectors
View All 12 Actions
- List Indexes
- Describe Index
- Create Index
- Configure Index
- Delete Index
- Get Index Stats
- Upsert Vectors
- Query Vectors
- Fetch Vectors
- List Vector Ids
- Delete Vectors
- Update Vector
Frequently Asked Questions
Does query_vectors embed a text question?
This action searches using a vector or supported vector ID; text embedding must be produced separately.
Can I store sparse vectors?
upsert_vectors supports dense or sparse vectors in an index namespace.
Can delete_vectors clear a namespace?
It supports IDs, filter, or deleteAll. State the intended deletion scope explicitly.
Your AI employee for Pinecone
Tell Leina what you need in your team chat. Include the source, destination, and expected result.