> ## 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. # Gemini > Configure PipesHub to use Google Gemini embedding models # Gemini Embeddings Configuration Gemini Embeddings Configuration Interface *The Gemini embeddings configuration screen in PipesHub where you'll enter your API Key and Model Name* PipesHub allows you to integrate with Google's Gemini 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 Google's Gemini AI services. **How to obtain an API Key:** 1. Log in to [Google AI Studio](https://aistudio.google.com/) 2. Click on your profile icon in the top right corner 3. Select "Get API key" 4. Create a new API key or use an existing one 5. Copy the generated API key **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 Google Gemini. ### Model Name \* The Model Name field defines which Gemini embedding model you want to use with PipesHub. **Available Gemini embedding models:** * `gemini-embedding-001` - Google's latest embedding model with strong semantic understanding **How to choose a model:** * For most use cases, select `gemini-embedding-001` * Check Google's [embedding documentation](https://ai.google.dev/docs) for the most up-to-date options ## Configuration Steps As shown in the image above: 1. Click **Configure** on the Gemini provider card 2. Enter your Google AI API Key in the designated field (marked with \*) 3. Specify your desired Model Name (marked with \*) 4. Click **Add Model** to save and validate your credentials > Both the API Key and Model Name are required fields to successfully configure Gemini embedding integration. ## Usage Considerations * API usage will count against your Google AI API quota and billing * Different models have different pricing — check Google AI's pricing page for details * Gemini embedding models support a wide range of languages ## Troubleshooting * If you encounter authentication errors, verify your API key is correct and has not expired * Ensure your Google account has billing set up if you are using paid service tiers * Check that the model name is spelled correctly and is available in your region * Verify that your API key has access to the Gemini embedding API For additional support, refer to the [Google Gemini documentation](https://ai.google.dev/docs) or contact PipesHub support.