gemini-rust

A comprehensive Rust client library for Google's Gemini API.

✨ Features

• 🚀 Complete Gemini API Implementation - Full support for all Gemini API endpoints
• 🛠️ Function Calling & Tools - Custom functions, Google Search, and Google Maps integration with OpenAPI schema support
• 🗺️ Google Maps Grounding - Location-aware responses with Google Maps data and widget support
• 📦 Batch Processing - Efficient batch content generation and embedding
• 💾 Content Caching - Cache system instructions and conversation history for cost optimization
• 🔄 Streaming Responses - Real-time streaming of generated content
• 🧠 Thinking Mode - Support for Gemini 2.5+ thinking capabilities
• 🚀 Gemini 3 Pro - Code execution, advanced thinking levels, and media resolution control
• 🔢 Token Count API - Pre-calculate token usage for cost optimization
• 🎯 Safety Settings - Customize content moderation and safety filters
• 📁 File Handles - Efficient file reference without re-encoding large files
• 🍌 Image Generation - Text-to-image generation and image editing capabilities
• 🎤 Speech Generation - Text-to-speech with single and multi-speaker support
• 🖼️ Multimodal Support - Images and binary data processing
• 📊 Text Embeddings - Advanced embedding generation with multiple task types
• ⚙️ Highly Configurable - Custom models, endpoints, and generation parameters with HTTP client builder
• 🔒 Type Safe - Comprehensive type definitions with full serde support
• ⚡ Async/Await - Built on tokio for high-performance async operations
• 🔍 Comprehensive Tracing - Built-in structured logging and telemetry with tracing for observability

📦 Installation

Add this to your Cargo.toml:

[dependencies]
gemini-rust = "1.6.1"

🚀 Quick Start

Basic Content Generation

Get started with simple text generation, system prompts, and conversations. See basic_generation.rs for complete examples including simple messages, system prompts, and multi-turn conversations.

Streaming Responses

Enable real-time content streaming for interactive applications. See basic_streaming.rs for examples of processing content as it's generated with immediate display.

Google Maps Grounding

Add location-aware capabilities to your applications with Google Maps integration. See simple_maps_example.rs for basic usage and google_maps_grounding.rs for comprehensive examples.

Token Count API

Calculate token usage before making generation requests for cost estimation and optimization. See count_tokens.rs.

Safety Settings

Customize content moderation with granular control over different harm categories and block thresholds. See safety_settings.rs.

Gemini 3 Pro

Access the latest model features including code execution and advanced thinking levels. See gemini_3_code_execution.rs for code execution and gemini_3_thinking_and_media.rs for thinking levels.

🛠️ Key Features

The library provides comprehensive access to all Gemini 2.5 capabilities through an intuitive Rust API:

🧠 Thinking Mode (Gemini 2.5)

Advanced reasoning capabilities with thought process visibility and custom thinking budgets. See thinking_basic.rs and thinking_advanced.rs.

🛠️ Function Calling & Tools

• Custom function declarations with OpenAPI schema support (using schemars)
• Google Search integration for real-time information
• Google Maps grounding for location-aware responses
• Type-safe function definitions with automatic schema generation
• See tools.rs, complex_function.rs, and google_maps_grounding.rs

🗺️ Google Maps Grounding

• Location-Aware Responses: Access Google Maps data for geographically specific queries
• Widget Support: Generate context tokens for interactive Google Maps widgets
• Grounding Sources: Access citation information for all Maps data used in responses
• Easy Integration: Simple API with location context configuration
• See simple_maps_example.rs and advanced_maps_configuration.rs

🎨 Multimodal Generation

• Image Generation: Nano Banana (Flash) and Pro (Gemini 3) Text-to-image with detailed thinking and follow up editing capabilities
• Speech Generation: Text-to-speech with single and multi-speaker support
• Image Processing: Analyze images, videos, and binary data
• See image_generation.rs and multi_speaker_tts.rs

📦 Batch Processing

Efficient processing of multiple requests with automatic file handling for large jobs. See batch_generate.rs.

💾 Content Caching

Cache system instructions and conversation history to reduce costs and improve performance. See cache_basic.rs.

📊 Text Embeddings

Advanced embedding generation with multiple task types for document retrieval and semantic search. See embedding.rs.

🔄 Streaming Responses

Real-time streaming of generated content for interactive applications. See streaming.rs.

⚙️ Highly Configurable

• Custom models and endpoints
• Detailed generation parameters (temperature, tokens, etc.)
• HTTP client customization with timeouts and proxies
• See generation_config.rs and custom_base_url.rs

🔍 Observability

Built-in structured logging and telemetry with tracing for comprehensive monitoring and debugging.

🔢 Token Count API

Pre-calculate token usage for cost estimation and optimization. Calculate tokens for your requests before executing them. See count_tokens.rs.

🎯 Safety Settings

Customize content moderation with granular control over different harm categories (Hate Speech, Dangerous Content, etc.) and block thresholds (Block None, Low, Medium, High). See safety_settings.rs.

🚀 Gemini 3 Pro

• Code Execution: Generate and execute Python code for mathematical calculations, data analysis, and computational tasks
• Thinking Levels: Choose Low for faster responses or High for deeper analysis
• Media Resolution: Fine-grained control over image and PDF processing quality
• See gemini_3_code_execution.rs and gemini_3_thinking_and_media.rs

📁 File Handles

Efficiently reference previously uploaded files without re-encoding. Upload files once and reference them multiple times, reducing data transfer. Supports PDFs, images, and other binary formats. See file_input.rs and files_usage.rs.

🔧 Configuration

Custom Models

Configure different Gemini models including Flash, Pro, Lite, and custom models. See custom_models.rs for examples of all model configuration options including convenience methods, enum variants, and custom model strings.

Custom Base URL

Use custom API endpoints and configurations. See custom_base_url.rs for examples of configuring custom endpoints with different models.

Configurable HTTP Client Builder

For advanced HTTP configuration (timeouts, proxies, custom headers), use the builder pattern. See http_client_builder.rs for a complete example with custom timeouts, user agents, connection pooling, and proxy configuration.

🔍 Tracing and Telemetry

The library is instrumented with the tracing crate to provide detailed telemetry data for monitoring and debugging. This allows you to gain deep insights into the library's performance and behavior.

Key tracing features include:

• HTTP Request Tracing: Captures detailed information about every API call, including HTTP method, URL, and response status, to help diagnose network-related issues
• Token Usage Monitoring: Records the number of prompt, candidate, and total tokens for each generation request, enabling cost analysis and optimization
• Structured Logging: Emits traces as structured events, compatible with modern log aggregation platforms like Elasticsearch, Datadog, and Honeycomb, allowing for powerful querying and visualization
• Performance Metrics: Provides timing information for each API request, allowing you to identify and address performance bottlenecks

To use these features, you will need to integrate a tracing subscriber into your application. See tracing_telemetry.rs for comprehensive examples including basic console logging, structured logging for production, and environment-based log level filtering.

📚 Examples

The repository includes 30+ comprehensive examples demonstrating all features. See examples/README.md for detailed information.

Quick Start Examples

• basic_generation.rs - Simple content generation for beginners
• basic_streaming.rs - Real-time streaming responses
• simple.rs - Comprehensive example with function calling
• thinking_basic.rs - Gemini 2.5 thinking mode
• count_tokens.rs - Pre-calculate token usage
• safety_settings.rs - Configure safety filters
• gemini_3_code_execution.rs - Code execution with Python
• file_input.rs - Upload and reference files
• batch_generate.rs - Batch content generation
• image_generation.rs - Text-to-image generation
• google_search.rs - Google Search integration
• url_context.rs - URL Context tool for web content analysis

Run any example:

GEMINI_API_KEY="your-api-key" cargo run --example basic_generation

🔑 API Key Setup

Get your API key from Google AI Studio and set it as an environment variable:

export GEMINI_API_KEY="your-api-key-here"

🚦 Supported Models

• Gemini 2.5 Flash - Fast, efficient model (default) - Model::Gemini25Flash
• Gemini 2.5 Flash Lite - Lightweight model - Model::Gemini25FlashLite
• Gemini 2.5 Pro - Advanced model with thinking capabilities - Model::Gemini25Pro
• Gemini 3 Pro - Latest model with code execution and advanced thinking - Model::Gemini3Pro (Preview)
• Text Embedding 004 - Latest embedding model - Model::TextEmbedding004
• Custom models - Use Model::Custom(String) or string literals for other models

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

For guidelines on developing agents and applications, see the Agent Development Guide.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Google for providing the Gemini API
• The Rust community for excellent async and HTTP libraries
• Special thanks to @npatsakula for major contributions that made this project more complete
• All contributors who have helped improve this library