CentralMind/Gateway

--- title: 'Google Gemini' description: 'Integration with Gemini API for accessing Google language models' --- The Gemini provider enables direct integration with Google's language models through a compatible OpenAI-style API. This guide covers setup, configuration, authentication, and usage options for connecting to the Gemini API. ## Overview The Gemini provider allows access to Google's language models via an OpenAI-compatible interface. This provider offers streamlined integration with authentication through API keys, flexible configuration options, and support for advanced features. ## Authentication The provider uses API key authentication to access Gemini's services. You'll need to obtain a Gemini API key to use this provider: - **Environment Variable:** Set `GEMINI_API_KEY` to provide your credentials. - **Command Line:** Pass your API key using the appropriate flag. ### Getting an API Key Google offers a **free tier** for Gemini API access. You can obtain an API key by visiting Google AI Studio: - [Google AI Studio](https://aistudio.google.com/apikey) Once logged in, you can create an API key in the API section of AI Studio. The free tier includes a generous monthly token allocation, making it accessible for development and testing purposes. ## Example Usage ```bash export GEMINI_API_KEY='yourkey' ``` Below is a basic example of how to use the provider with a connection configuration file: ```bash ./gateway discover \ --ai-provider gemini \ ---connection-string "postgresql://my_user:my_pass@localhost:5432/mydb" ``` ## Model Selection By default, the Gemini provider uses `gemini-2.0-flash-thinking-exp`. You can specify a different model using one of the following methods: 1. **Command-line Flag:** Use the `--ai-model` flag. 2. **Environment Variable:** Set the `GEMINI_MODEL_ID`. Examples: ```bash # Specify model via command line ./gateway discover \ --ai-provider gemini \ --ai-model gemini-2.0-flash-thinking-exp \ --connection-string "postgresql://my_user:my_pass@localhost:5432/mydb" # Or via environment variable export GEMINI_MODEL_ID=gemini-2.0-flash-thinking-exp ./gateway discover \ --ai-provider gemini \ --connection-string "postgresql://my_user:my_pass@localhost:5432/mydb" ``` ## Advanced Configuration ### Response Length Control Control the maximum token count in responses: ```bash ./gateway discover \ --ai-provider gemini \ --ai-max-tokens 8192 \ --connection-string "postgresql://my_user:my_pass@localhost:5432/mydb" ``` If not specified, the default maximum token count is 100,000 tokens. ### Temperature Adjustment Adjust the randomness of responses with the temperature parameter: ```bash ./gateway discover \ --ai-provider gemini \ --ai-temperature 0.7 \ --connection-string "postgresql://my_user:my_pass@localhost:5432/mydb" ``` Lower values produce more deterministic outputs, while higher values increase creativity and randomness. ## Usage Costs Google offers a free tier for Gemini API usage with monthly token limits. For production workloads or higher usage requirements, please refer to Google's documentation for the current pricing for Gemini models. ## Recommended Best Practices - **API Key Security:** Use environment variables for sensitive settings like API keys. - **Manage Token Count:** Set a reasonable maximum token count to control costs. - **Select the Right Model:** Choose models based on your specific needs and budget constraints. - **Start with Free Tier:** Use the free tier to experiment and prototype before committing to paid usage. ## Additional Resources For more information about Google's language models and their capabilities, please refer to Google's official documentation and AI Studio resources.