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OpenAI Embeddings Configuration

The OpenAI embeddings configuration screen in PipesHub where you’ll enter your API Key and Embedding Model PipesHub allows you to integrate with OpenAI’s powerful embedding models to enable vector search, semantic similarity, and other AI features in your workspace.

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Required Fields

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API Key

The OpenAI API Key is required to authenticate your requests to OpenAI’s embedding services. How to obtain an API Key:

1. Log in to your OpenAI account
2. Navigate to the API section
3. Create a new secret key
4. Copy the key immediately (it will only be shown once)

Security Note: Your API key should be kept secure and never shared publicly. PipesHub securely stores your API key and uses it only for authenticating requests to OpenAI.

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Embedding Model

The Embedding Model field defines which OpenAI embedding model you want to use with PipesHub. Available OpenAI embedding models:

• text-embedding-3-small - Cost-effective model with excellent performance for most use cases
• text-embedding-3-large - Higher dimensional embeddings for tasks requiring maximum accuracy

How to choose an embedding model:

• For most applications and cost efficiency, select text-embedding-3-small
• For specialized applications requiring maximum performance, select text-embedding-3-large
• Check OpenAI’s embedding documentation for the most up-to-date options

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Configuration Steps

As shown in the image above:

1. Select “OpenAI” as your Embedding Provider from the dropdown
2. Enter your OpenAI API Key in the designated field (marked with *)
3. Specify your desired Embedding Model (marked with *)
4. Click “Continue” to proceed with setup

The system configuration interface clearly indicates which fields are required with an asterisk (*). Both the API Key and Embedding Model are required fields to successfully configure OpenAI embedding integration.

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Model Specifications

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Advanced Parameters

OpenAI’s embedding models support parameters to control the output:

• Dimensions - Control the size of embedding vectors (smaller dimensions = smaller storage requirements)
• Encoding Format - Choose between “float” and “base64” for different precision and size tradeoffs

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Usage Considerations

• API usage will count against your OpenAI account’s quota and billing
• Different models have different pricing - check OpenAI’s pricing page for details
• Embedding models are optimized for different languages and use cases
• Consider storage requirements based on the embedding dimensions you select

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Troubleshooting

• If you encounter authentication errors, verify your API key is correct and has not expired
• Ensure your OpenAI account has billing set up
• Check that the embedding model name is spelled correctly
• For large document collections, consider batching embedding requests

For additional support, refer to the OpenAI Embeddings documentation or contact PipesHub support.