Integrations
Pinecone
Connect your Pinecone vector database for semantic search and RAG applications
Overview
The Pinecone integration enables your agents to perform semantic search on vector embeddings stored in your Pinecone database. This allows agents to find relevant documents, build RAG (Retrieval-Augmented Generation) applications, and perform similarity searches based on meaning rather than keywords.
Features
- Semantic Search: Find documents based on meaning and context
- Vector Similarity: High-performance similarity matching using embeddings
- Namespace Support: Search within specific data collections
- Configurable Results: Control the number of results returned
- Metadata Access: Retrieve document metadata along with similarity scores
- RAG Applications: Perfect for building retrieval-augmented generation systems
Prerequisites
- Active Pinecone account with a configured index
- Pinecone API key with read permissions
- Pinecone host URL for your index
- Vector embeddings already stored in your index
- Understanding of your namespace structure
Setup Guide
1
Enable Pinecone Integration
Navigate to Control Hub > Integrations and locate the Pinecone card. Click “Connect” to begin setup.
2
Configure Connection
Provide your Pinecone connection details:
- API Key: Your Pinecone API key from the console
- Host: Your Pinecone index host URL (e.g., your-index-abc123.svc.us-east1-gcp.pinecone.io)
3
Test Connection
Click “Test Connection” to verify your configuration. The system will attempt to connect and validate your index access.
Finding Your Pinecone Details
API Key
- Log into your Pinecone console
- Navigate to “API Keys” in the sidebar
- Copy your API key value
Host URL
- Go to your Pinecone console
- Select your index
- Copy the host URL from the index details (without https://)
Security Considerations
- Store API keys securely and rotate them regularly
- Use read-only API keys when possible
- Implement proper access controls for sensitive data
- Monitor query usage and costs
- Consider using namespaces to isolate different data types
- Regularly audit which agents have access to which namespaces
Troubleshooting
Related Tools
- Query Pinecone - Search your vector database for similar documents