Currently supports natively: Ollama, OpenAI, Gemini, Anthropic, Cohere (more to come)
# cargo.toml
genai = "=0.1.0" # Version lock for `0.1.x`
The goal of this library is to provide a common and ergonomic single API to many generative AI Providers, such as OpenAI, Anthropic, Cohere, Ollama.
-
IMPORTANT 1
0.1.x
will still have some breaking changes in patches, so make sure to lock your version, e.g.,genai = "=0.1.0"
. In short,0.1.x
can be considered "beta releases." -
IMPORTANT 2 This is NOT intended to be a replacement for async-openai and ollama-rs, but rather to tackle the simpler lowest common denominator of chat generation use cases, where API depth is less aa priority than API commonality.
-
Focuses on standardizing chat completion APIs across major AI Services.
-
Native implementation, meaning no per-service SDKs.
- Reason: While there are some variations between all of the various APIs, they all follow the same pattern and high-level flow and constructs. Managing the differences at a lower layer is actually simpler and more cumulative accross services than doing sdks gymnastic.
-
Prioritizes ergonomics and commonality, with depth being secondary. (If you require complete client API, consider using async-openai and ollama-rs; they are both excellent and easy to use.)
-
Initially, this library will mostly focus on text chat API (images, or even function calling in the first stage).
-
The
0.1.x
version will work, but the APIs will change in the patch version, not following semver strictly. -
Version
0.2.x
will follow semver more strictly.
use genai::chat::{ChatMessage, ChatRequest};
use genai::client::Client;
use genai::utils::{print_chat_stream, PrintChatStreamOptions};
const MODEL_OPENAI: &str = "gpt-3.5-turbo";
const MODEL_ANTHROPIC: &str = "claude-3-haiku-20240307";
const MODEL_COHERE: &str = "command-light";
const MODEL_GEMINI: &str = "gemini-1.5-flash-latest";
const MODEL_OLLAMA: &str = "mixtral";
// NOTE: Those are the default env keys for each AI Provider type.
const MODEL_AND_KEY_ENV_NAME_LIST: &[(&str, &str)] = &[
// -- de/activate models/providers
(MODEL_OPENAI, "OPENAI_API_KEY"),
(MODEL_ANTHROPIC, "ANTHROPIC_API_KEY"),
(MODEL_COHERE, "COHERE_API_KEY"),
(MODEL_GEMINI, "GEMINI_API_KEY"),
(MODEL_OLLAMA, ""),
];
// NOTE: Model to AdapterKind (AI Provider) type mapping rule
// - starts_with "gpt" -> OpenAI
// - starts_with "claude" -> Anthropic
// - starts_with "command" -> Cohere
// - starts_with "gemini" -> Gemini
// - For anything else -> Ollama
//
// Refined mapping rules will be added later and extended as provider support grows.
#[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_stream_events(true);
for (model, env_name) in MODEL_AND_KEY_ENV_NAME_LIST {
// Skip if does not have the environment name set
if !env_name.is_empty() && std::env::var(env_name).is_err() {
continue;
}
println!("\n===== MODEL: {model} =====");
println!("\n--- Question:\n{question}");
println!("\n--- Answer: (oneshot response)");
let chat_res = client.exec_chat(model, chat_req.clone(), None).await?;
println!("{}", chat_res.content.as_deref().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:
- 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-kind.rs - Demonstrates how to provide a custom
AdapterKindResolver
to customize the "model name" to "adapter kind" mapping.
- Will add more data on ChatResponse and ChatStream, especially metadata about usage.
- Add vision/image support to chat messages and responses.
- Add function calling support to chat messages and responses.
- Add
embbed
andembbed_batch
- Add the AWS Bedrock variants (e.g., Mistral, and Anthropic). Most of the work will be on "interesting" token signature scheme (without having to drag big SDKs, might be below feature).
- Add the Google VertexAI variants.
- (might) add the Azure OpenAI variant (not sure yet).
- crates.io: crates.io/crates/genai
- GitHub: github.com/jeremychone/rust-genai
- Sponsored by BriteSnow (Jeremy Chones's consulting company)