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
Connection Failed
Connection Failed
- Verify your API key is correct and active
- Check that the host URL is properly formatted
- Ensure your Pinecone index is running
- Confirm network connectivity to Pinecone
Authentication Error
Authentication Error
- Verify your API key hasn’t expired
- Check that the API key has proper permissions
- Ensure you’re using the correct Pinecone project
- Confirm the index exists in your account
Query Execution Error
Query Execution Error
- Verify the namespace exists and contains data
- Check that your index has vector embeddings
- Ensure the query format is correct
- Confirm the index dimensions match your embeddings
Related Tools
- Query Pinecone - Search your vector database for similar documents