Add Pinecone Online Store Integration

Add support for using Pinecone as an online store in Feast to enable low-latency feature serving backed by a vector database.

Motivation

Pinecone is widely used as a managed vector database for AI and retrieval-augmented generation (RAG) applications. As feature stores are increasingly used alongside vector search systems, a native Pinecone integration would enable users to:

- Store and retrieve embeddings as online features.
- Serve vector features directly from Pinecone.
- Reduce infrastructure complexity for AI workloads already using Pinecone.
- Support hybrid ML and GenAI use cases from a single feature management workflow.

Proposed Solution

Implement a Pinecone online store plugin that:

- Supports reading and writing feature values to Pinecone.
- Maps Feast entities to Pinecone namespaces or metadata.
- Supports configurable index names and namespaces.
- Provides batch materialization into Pinecone.
- Supports online feature retrieval with low latency.
- Includes configuration examples and documentation.

Example configuration:

online_store:
type: pinecone
api_key: ${PINECONE_API_KEY}
index_name: feast-online
namespace: default

Considerations

- Authentication using Pinecone API keys.
- Support for multiple namespaces.
- Metadata filtering where applicable.
- Error handling and retry logic.
- Compatibility with existing Feast OnlineStore abstractions.

Additional Context

This integration would benefit users building retrieval-augmented generation (RAG), semantic search, recommendation systems, and embedding-based ML pipelines that already rely on Pinecone for vector storage.

No files, tests, or entry points are named. Start by examining Feast's existing OnlineStore abstractions and integrations, then determine how Pinecone configuration, namespaces, materialization, retrieval, authentication, filtering, retries, and documentation fit those patterns; done means the proposed capabilities and examples are implemented and tested.

Written by the indexing model from the issue text.