llama-index-vector-stores-pinecone
llama-index vector_stores pinecone integration
Decision gist · record as of 2026-08-14
Yes, if you are already using LlamaIndex and want to use Pinecone as your vector store. The package has low install friction, active maintenance, MIT licensing, and no known vulnerabilities. It is a straightforward integration layer with no hidden complexity—install it only if Pinecone is your chosen vector database.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires active Pinecone account and API credentials configured in environment or passed to the client.
- Low install friction with a pure Python wheel.
- Active maintenance as of release date.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions, typical for ecosystem integration packages.
last release 2026-08-14 (0 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 194,439 downloads/mo, #9,833 on PyPI
Alternatives
Verify before relying
pip install llama-index-vector-stores-pinecone
from llama_index.vector_stores.pinecone import PineconeVectorStore
vector_store = PineconeVectorStore(index_name="my-index")- Whether Pinecone API credentials or account setup is required before the package becomes functional
- Compatibility guarantees with specific versions of llama-index-core or pinecone beyond what requires_python declares
What it is and what it does
This package is a bridge between LlamaIndex and Pinecone, enabling you to use Pinecone as the vector storage backend for retrieval-augmented generation (RAG) and semantic search workflows. It abstracts Pinecone's API behind LlamaIndex's standard vector store interface, so you can swap vector databases without rewriting your application logic.
The package handles the low-level details of connecting to Pinecone, storing embeddings, and retrieving similar vectors based on semantic similarity. It's designed for developers building LLM applications who want to leverage Pinecone's managed vector database without writing custom integration code. Python 3.10 or later is required.
Use it for
- Build a RAG pipeline where documents are embedded and stored in Pinecone, then retrieved by semantic similarity to answer user queries.
- Implement semantic search over a large corpus by storing embeddings in Pinecone and querying through LlamaIndex.
- Swap Pinecone for another vector store in an existing LlamaIndex application by changing only the vector store initialization.
- Integrate Pinecone into a multi-step LLM workflow where context retrieval is one stage in a larger chain.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using LlamaIndex and want to use Pinecone as your vector store.
The package has low install friction, active maintenance, MIT licensing, and no known vulnerabilities. It is a straightforward integration layer with no hidden complexity—install it only if Pinecone is your chosen vector database.
Install
llama-index-vector-stores-pinecone on PyPI
Before you install
Low install friction with a pure Python wheel. Active maintenance as of release date. Depends on llama-index-core and pinecone, both established packages in the LLM ecosystem.
Requires active Pinecone account and API credentials configured in environment or passed to the client.
License in practice
MIT license permits commercial and private use with minimal restrictions, typical for ecosystem integration packages.
Quickstart
pip install llama-index-vector-stores-pinecone
from llama_index.vector_stores.pinecone import PineconeVectorStore
vector_store = PineconeVectorStore(index_name="my-index")Verify before relying
- Whether Pinecone API credentials or account setup is required before the package becomes functional
- Compatibility guarantees with specific versions of llama-index-core or pinecone beyond what requires_python declares
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesllama-index-corepinecone |
| Maintenance | Actively maintained 0 days since the last release |
| First released | |
| Downloads | 194,439 / month, #9,833 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: llama_index_vector_stores_pinecone-0.8.1-py3-none-any.whl
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See also langchain-pinecone · llama-index-vector-stores-chroma · llama-index-vector-stores-milvus · llama-index-vector-stores-qdrant · pinecone-plugin-inference · pinecone · llama-index-vector-stores-redis · pinecone-client · llama-index-vector-stores-faiss · llama-index-vector-stores-lancedb