> ## Documentation Index > Fetch the complete documentation index at: https://docs.pipeshub.com/llms.txt > Use this file to discover all available pages before exploring further. # OpenAI > Configure PipesHub to use OpenAI embedding models # OpenAI Embeddings Configuration OpenAI Embeddings Configuration Interface *The OpenAI embeddings configuration screen in PipesHub where you'll enter your API Key and Model Name* PipesHub allows you to integrate with OpenAI's embedding models to enable vector search, semantic similarity, and document retrieval in your workspace. ## Required Fields ### API Key \* The 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](https://platform.openai.com/account/api-keys) 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. ### Model Name \* The Model Name 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 a model:** * For most applications and cost efficiency, select `text-embedding-3-small` * For specialised applications requiring maximum performance, select `text-embedding-3-large` * Check OpenAI's [embedding documentation](https://platform.openai.com/docs/guides/embeddings) for the most up-to-date options ## Optional Fields ### Output Dimensions Override the size of the embedding vectors produced by the model. Supported by the `text-embedding-3-*` model series. **When to set this:** * To reduce storage costs by producing smaller vectors * When your vector database requires a specific dimension size **Note:** Leave blank to use the model's default dimensions. Setting this on models that do not support a `dimensions` parameter will cause an error. ## Configuration Steps As shown in the image above: 1. Click **Configure** on the OpenAI provider card 2. Enter your OpenAI API Key in the designated field (marked with \*) 3. Specify your desired Model Name (marked with \*) 4. (Optional) Set Output Dimensions if you need a non-default vector size 5. Click **Add Model** to save and validate your credentials > Both the API Key and Model Name are required fields to successfully configure OpenAI embedding integration. ## 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 * Consider storage requirements based on the embedding dimensions you select ## 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 model name is spelled correctly * Only set Output Dimensions for models that support the `dimensions` parameter (`text-embedding-3-small` and `text-embedding-3-large`) For additional support, refer to the [OpenAI Embeddings documentation](https://platform.openai.com/docs/guides/embeddings) or contact PipesHub support.