Key Features
Vector Search
Perform fast, approximate nearest neighbor search across billions of embeddings.
Namespace & Metadata Filtering
Organize vectors and filter queries using metadata and namespaces.
Scalable Infrastructure
Handles billions of vectors with automatic sharding and replication.
RAG Optimization
Integrates with LLMs to retrieve relevant context for grounded generation.
Easy SDKs
Use Python, Node.js, or REST APIs to manage indexes and run queries.
How It Works
Create Index
Define your vector index with dimensions, metric type, and metadata schema.
Generate Embeddings
Use models like OpenAI, Cohere, or Hugging Face to convert data into vectors.
Upsert Vectors
Insert vectors into Pinecone with optional metadata and namespace tags.
Query with Similarity
Search for nearest neighbors using vector similarity and metadata filters.
Integrate with RAG
Use retrieved context to enhance LLM responses in chatbots and agents.
Code Example
import pinecone
import openai
pinecone.init(api_key="YOUR_API_KEY", environment="us-west1-gcp")
index = pinecone.Index("my-index")
query = "What is vector search?"
embedding = openai.Embedding.create(input=query, model="text-embedding-ada-002")["data"][0]["embedding"]
results = index.query(vector=embedding, top_k=5, include_metadata=True)
print(results)Use Cases
RAG Systems
Retrieve relevant context for LLMs to generate grounded responses.
Semantic Search
Search documents, FAQs, or transcripts using meaning-based similarity.
Recommendation Engines
Suggest products, content, or users based on vector proximity.
Personalization
Tailor experiences using user embeddings and behavioral vectors.
Fraud Detection
Identify anomalies by comparing transaction vectors to known patterns.
Integrations & Resources
Explore Pinecone’s ecosystem and find the tools, platforms, and docs to accelerate your workflow.
Popular Integrations
- OpenAI, Cohere, Hugging Face for embeddings
- LangChain and LlamaIndex for RAG
- FastAPI and Flask for deployment
- Streamlit and Gradio for demos
- Airbyte and Zapier for data pipelines
- AWS, GCP, Azure for cloud hosting
Helpful Resources
FAQ
Common questions about Pinecone’s capabilities, usage, and ecosystem.