Provides a single, ergonomic Rust API for native-protocol multi-AI provider access, including Anthropic, OpenAI, Gemini, xAI, Ollama, Groq, and more.

Currently natively supports over 25 providers: OpenAI, OpenAI Responses, Anthropic, Gemini, xAI, Ollama, Ollama Cloud, OpenCode Go, Groq, DeepSeek, Cohere, Together, Fireworks, Nebius, Mimo, Zai (Zhipu AI), BigModel, Aliyun, Baidu, Moonshot, Google Vertex, GitHub Copilot (GitHub Models API), AIHubMix, AWS Bedrock, OpenRouter.

Also supports a custom Endpoint and Auth with ServiceTargetResolver (see examples/c06-target-resolver.rs).

NOTE: Use genai = "0.6.0-beta.20" or later for improved robustness, even compared to 0.5.x, along with many more providers, fixes, performance improvements, and API enhancements. v0.6.0 is coming soon.

Docs for LLMs | CHANGELOG | BIG THANKS

By default, the library resolves the AdapterKind (AI Provider) based on the model name prefix:

• OpenAI: gpt-* (most), o1-*, o3-*, o4-*, chatgpt-*, codex-*
• OpenAI Responses: gpt-5-*, gpt-* (containing codex or pro)
• Anthropic: claude-*
• Gemini: gemini-*
• xAI: grok-*
• DeepSeek: deepseek-*
• Moonshot: moonshot-*
• Zai: glm-*
• Cohere: command-*, embed-*
• Mimo: mimo-*
• OpenCode Go: Namespace opencode_go:: only
• Fireworks: Models containing fireworks
• Ollama: Fallback for any other names, defaulting to local Ollama.

You can force a specific adapter by using the adapter_kind::model_name syntax. This is the recommended way for many providers and for disambiguating OpenAI-compatible services.

• groq::llama-3.1-8b-instant (Forces Groq adapter)
• together::meta-llama/Llama-3-8b-chat-hf (Forces Together adapter)
• ollama_cloud::gemma3:4b (Forces OllamaCloud adapter)
• github_copilot::openai/gpt-4.1-mini (Forces GithubCopilot adapter)
• nebius::Qwen/Qwen3-235B-A22B (Forces Nebius adapter)
• aliyun::qwen-plus (Forces Aliyun adapter)
• vertex::gemini-2.5-flash (Forces Google Vertex adapter)
• moonshot::moonshot-v1-8k (Forces Moonshot adapter)
• baidu::ernie-4.0 (Forces Baidu adapter)
• coding::glm-4.6 (Special namespace for Zai coding subscription)
• opencode_go::minimax-m2.5 (Forces OpenCodeGo adapter)
• bedrock_api::anthropic.claude-v2 (Forces AWS Bedrock adapter)
• open_router::google/gemini-2.0-flash-001 (Forces OpenRouter adapter)

For a complete list of AdapterKind, see the AdapterKind enum.

• What's new:
  • New Adapters: AWS Bedrock (API and SigV4), OpenRouter, Baidu, Moonshot, and many others.
  • Expanded Provider Support: Comprehensive coverage of major AI ecosystems.
  • Updated API: Refined ReasoningContent and StopReason handling (v0.6.0-beta.20).
  • Numerous fixes, optimizations, and API enhancements.

• What's new:
  • New Adapters: BigModel.cn and the MIMO model adapter (thanks to Akagi201).
  • zai: updated namespace strategy, using zai:: for default and zai-coding:: for subscriptions (same adapter).
  • Gemini Thinking & Thought: Full support for Gemini Thought signatures (thanks to Himmelschmidt) and thinking levels.
  • Reasoning Effort Control: Support for ReasoningEffort for Anthropic (Claude 3.7/4.5) and Gemini (Thinking levels), including ReasoningEffort::None.
  • Content & Binary Improvements: Enhanced binary/PDF API and size tracking.
  • Internal Stream Refactor: Switched to a unified EventSourceStream and WebStream for better reliability and performance across all providers.
  • Dependency Upgrade: Now using reqwest 0.13.
• Core Features:
  • Normalized and ergonomic Chat API across all major providers.
  • Native protocol support for Gemini and Anthropic protocols (Reasoning/Thinking controls).
  • PDF, image, and embedding support.
  • Custom authentication, endpoint, and header overrides.

See CHANGELOG

• Check out AIPACK, which wraps this genai library into an agentic runtime to run, build, and share AI Agent Packs. See pro@coder for a simple example of how I use AI PACK/genai for production coding.

Note: Feel free to send me a short description and a link to your application or library that uses genai.

• Multi-AI Provider/Model access optimized per provider: native protocols when available, OpenAI-compatible APIs when appropriate or required, and one common Rust API for OpenAI, OpenAI Responses, Anthropic, Gemini, Ollama, Ollama Cloud, OpenCode Go, Groq, xAI, DeepSeek, Cohere, Together, Fireworks, Nebius, Mimo, Zai, BigModel, Aliyun, Google Vertex, and GitHub Copilot (direct chat and streaming) (see examples/c00-readme.rs)
• DeepSeekR1 support, with reasoning_content (and stream support), plus DeepSeek Groq and Ollama support (and reasoning_content normalization)
• Image Analysis (for OpenAI, Gemini flash-2, Anthropic) (see examples/c07-image.rs)
• Custom Auth/API Key (see examples/c02-auth.rs)
• Model aliases (see examples/c05-model-names.rs)
• Custom endpoint, auth, and model identifier (see examples/c06-target-resolver.rs)

Examples | Thanks | Library Focus | Changelog | Provider Mapping: ChatOptions | Usage

examples/c00-readme.rs

//! Base examples demonstrating the core capabilities of genai

use genai::chat::printer::{print_chat_stream, PrintChatStreamOptions};
use genai::chat::{ChatMessage, ChatRequest};
use genai::Client;

const MODEL_OPENAI: &str = "gpt-4o-mini"; // o1-mini, gpt-4o-mini
const MODEL_ANTHROPIC: &str = "claude-3-haiku-20240307";
// or namespaced with simple name "fireworks::qwen3-30b-a3b", or "fireworks::accounts/fireworks/models/qwen3-30b-a3b"
const MODEL_FIREWORKS: &str = "accounts/fireworks/models/qwen3-30b-a3b";
const MODEL_TOGETHER: &str = "together::openai/gpt-oss-20b";
const MODEL_GEMINI: &str = "gemini-2.0-flash";
const MODEL_GROQ: &str = "groq::llama-3.1-8b-instant";
const MODEL_OLLAMA: &str = "gemma:2b"; // sh: `ollama pull gemma:2b`
const MODEL_OLLAMA_CLOUD: &str = "ollama_cloud::gemma3:4b";
const MODEL_XAI: &str = "grok-3-mini";
const MODEL_DEEPSEEK: &str = "deepseek-chat";
const MODEL_ZAI: &str = "glm-4-plus";
const MODEL_COHERE: &str = "command-r7b-12-2024";
const MODEL_MOONSHOT: &str = "moonshot::moonshot-v1-8k";
const MODEL_BAIDU: &str = "baidu::ernie-4.0";
const MODEL_BIGMODEL: &str = "bigmodel::glm-4-plus";
const MODEL_ALIYUN: &str = "aliyun::qwen-plus";
// or any publisher: "github_copilot::anthropic/claude-sonnet-4-6", "github_copilot::google/gemini-2.5-pro", "github_copilot::xai/grok-3-mini"
const MODEL_GITHUB_COPILOT: &str = "github_copilot::openai/gpt-4.1-mini";
const MODEL_OPEN_ROUTER: &str = "open_router::google/gemini-2.0-flash-001";

// NOTE: These are the default environment keys for each AI Adapter Type.
//       They can be customized; see `examples/c02-auth.rs`.
const MODEL_AND_KEY_ENV_NAME_LIST: &[(&str, &str)] = &[
	// -- De/activate models/providers
	(MODEL_OPENAI, "OPENAI_API_KEY"),
	(MODEL_ANTHROPIC, "ANTHROPIC_API_KEY"),
	(MODEL_GEMINI, "GEMINI_API_KEY"),
	(MODEL_FIREWORKS, "FIREWORKS_API_KEY"),
	(MODEL_TOGETHER, "TOGETHER_API_KEY"),
	(MODEL_GROQ, "GROQ_API_KEY"),
	(MODEL_XAI, "XAI_API_KEY"),
	(MODEL_DEEPSEEK, "DEEPSEEK_API_KEY"),
	(MODEL_OLLAMA, ""),
	(MODEL_OLLAMA_CLOUD, "OLLAMA_API_KEY"),
	(MODEL_ZAI, "ZAI_API_KEY"),
	(MODEL_COHERE, "COHERE_API_KEY"),
	(MODEL_MOONSHOT, "MOONSHOT_API_KEY"),
	(MODEL_BAIDU, "BAIDU_API_KEY"),
	(MODEL_BIGMODEL, "BIGMODEL_API_KEY"),
	(MODEL_ALIYUN, "ALIYUN_API_KEY"),
	(MODEL_GITHUB_COPILOT, "GITHUB_TOKEN"),
	(MODEL_OPEN_ROUTER, "OPEN_ROUTER_API_KEY"),
];

// NOTE: Model to AdapterKind (AI Provider) type mapping rule
//  - starts_with "gpt"      -> OpenAI (or OpenAI Responses for gpt-5/codex/pro)
//  - starts_with "claude"   -> Anthropic
//  - starts_with "command"  -> Cohere
//  - starts_with "gemini"   -> Gemini
//  - model in Groq models   -> Groq
//  - starts_with "glm"      -> ZAI
//  - starts_with "ollama_cloud::" -> OllamaCloud
//  - For anything else      -> Ollama
//
// This can be customized; see `examples/c03-mapper.rs`

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
	let question = "Why is the sky red?";

	let chat_req = ChatRequest::new(vec![
		// -- Messages (de/activate to see the differences)
		ChatMessage::system("Answer in one sentence"),
		ChatMessage::user(question),
	]);

	let client = Client::default();

	let print_options = PrintChatStreamOptions::from_print_events(false);

	for (model, env_name) in MODEL_AND_KEY_ENV_NAME_LIST {
		// Skip if the environment name is not set
		if !env_name.is_empty() && std::env::var(env_name).is_err() {
			println!("===== Skipping model: {model} (env var not set: {env_name})");
			continue;
		}

		let adapter_kind = client.resolve_service_target(model).await?.model.adapter_kind;

		println!("\n===== MODEL: {model} ({adapter_kind}) =====");

		println!("\n--- Question:\n{question}");

		println!("\n--- Answer:");
		let chat_res = client.exec_chat(model, chat_req.clone(), None).await?;
		println!("{}", chat_res.first_text().unwrap_or("NO ANSWER"));

		println!("\n--- Answer: (streaming)");
		let chat_res = client.exec_chat_stream(model, chat_req.clone(), None).await?;
		print_chat_stream(chat_res, Some(&print_options)).await?;

		println!();
	}

	Ok(())
}

• examples/c00-readme.rs - Quick overview code with multiple providers and streaming.
• examples/c01-conv.rs - Shows how to build a conversation flow.
• examples/c02-auth.rs - Demonstrates how to provide a custom AuthResolver to provide auth data (i.e., for api_key) per adapter kind.
• examples/c03-mapper.rs - Demonstrates how to provide a custom AdapterKindResolver to customize the "model name" to "adapter kind" mapping.
• examples/c04-chat-options.rs - Demonstrates how to set chat generation options such as temperature and max_tokens at the client level (for all requests) and at the per-request level.
• examples/c05-model-names.rs - Shows how to get model names per AdapterKind.
• examples/c06-target-resolver.rs - For custom auth, endpoint, and model.
• examples/c07-image.rs - Image analysis support

• genai ModelMapper code demo (v0.1.7)

• genai introduction (v0.1.0)

• genai live coding, code design, & best practices

  • Adding Gemini Structured Output (vid-0060)
  • Adding OpenAI Structured Output (vid-0059)
  • Splitting the json value extension trait to its own public crate value-ext value-ext
  • (part 1/3) Module, Error, constructors/builders
  • (part 2/3) Extension Traits, Project Files, Versioning
  • (part 3/3) When to Async? Project Files, Versioning strategy

• Focuses on standardizing chat completion APIs across major AI providers while preserving provider-specific strengths.

• Native implementation without per-service SDK dependencies.

  • Reason: genai uses each provider's native protocol when available, so features such as reasoning controls, thinking budgets, streaming metadata, and multimodal inputs can be represented more completely. When a provider primarily exposes an OpenAI-compatible API, genai uses that compatibility layer instead. Managing these protocol differences at the adapter layer is simpler and more cumulative than dealing with multiple SDKs.

• Prioritizes ergonomics and commonality, while depth is secondary. (If you require a complete client API, consider using async-openai and ollama-rs; both are excellent and easy to use.)

• This library focuses on text chat APIs, with vision and function calling support being expanded.

• (1) - OpenAI-compatible notes
  • Models: OpenAI, DeepSeek, Groq, Ollama, xAI, Mimo, Together, Fireworks, Nebius, Zai, AIHubMix

• (1) - OpenAI-compatible notes

  • Models: OpenAI, DeepSeek, Groq, Ollama, xAI, Mimo, AIHubMix
  • For Groq, the property x_groq.usage.
  • At this point, Ollama does not emit input/output tokens when streaming due to a limitation in the Ollama OpenAI compatibility layer. (see ollama #4448 - Streaming Chat Completion via OpenAI API should support stream option to include Usage)
  • prompt_tokens_details and completion_tokens_details will have the value sent by the compatible provider (or None)

• (2): Gemini tokens

  • Right now, with the Gemini Stream API, it's not clear whether usage for each event is cumulative or must be summed. It appears to be cumulative, meaning the last message shows the total number of input, output, and total tokens, so that is the current assumption. See possible tweet answer for more info.

• Will add more data to ChatResponse and ChatStream, especially usage metadata.
• Add vision/image support to chat messages and responses.
• Add function calling support to chat messages and responses.
• Add embed and embed_batch.
• Add the AWS Bedrock variants (e.g., Mistral and Anthropic). Most of the work will be on the "interesting" token signature scheme. To avoid bringing in large SDKs, this might be a lower-priority feature.
• Add the Google Vertex AI variants.
• May add the Azure OpenAI variant (not sure yet).

• crates.io: crates.io/crates/genai
• GitHub: github.com/jeremychone/rust-genai
• Sponsored by BriteSnow (Jeremy Chone's consulting company)