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Overview

The vector database for machine learning applications. Through Langdock’s integration, you can access and manage Pinecone directly from your conversations.
Authentication: API Key
Category: AI & Search
Availability: All workspace plans

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Available Actions

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Search Namespace

pinecone.searchNamespace
Searches the database for the most relevant information based on the query provided Requires Confirmation: No Parameters:
  • query (VECTOR, Required): Vector query for similarity search
Output: Returns search results with matching vectors, metadata, and similarity scores

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Common Use Cases

Data Management

Manage and organize your Pinecone data

Automation

Automate workflows with Pinecone

Reporting

Generate insights and reports

Integration

Connect Pinecone with other tools

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Best Practices

Getting Started:
  1. Enable the Pinecone integration in your workspace settings
  2. Authenticate using API Key
  3. Test the connection with a simple read operation
  4. Explore available actions for your use case
Important Considerations:
  • Ensure proper authentication credentials
  • Respect rate limits and API quotas
  • Review data privacy settings
  • Test operations in a safe environment first

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Troubleshooting

IssueSolution
Authentication failedVerify your API Key credentials
Rate limit exceededReduce request frequency
Data not foundCheck permissions and data availability
Connection timeoutVerify network connectivity

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Support

For additional help with the Pinecone integration, contact support@langdock.com