ai-lib 🦀✨

A unified, reliable, high-performance multi-provider AI SDK for Rust

A production-grade, provider-agnostic SDK that provides a unified Rust API for 17+ AI platforms and growing (OpenAI, Groq, Anthropic, Gemini, Mistral, Cohere, Azure OpenAI, Ollama, DeepSeek, Qwen, Baidu ERNIE, Tencent Hunyuan, iFlytek Spark, Kimi, HuggingFace, TogetherAI, xAI Grok, and more).
Eliminates fragmented authentication flows, streaming formats, error semantics, model naming differences, and inconsistent function calling. Scale from one-liner scripts to production systems without rewriting integration code.

Official Website

🚀 Core Value

ai-lib unifies AI provider complexity into a single, ergonomic Rust interface:

• Universal API: Chat, multimodal, and function calling across all providers
• Unified Streaming: Consistent SSE/JSONL parsing with real-time deltas
• Reliability: Built-in retry, timeout, circuit breaker, and error classification
• Flexible Configuration: Environment variables, builder pattern, or explicit overrides
• Production Ready: Connection pooling, proxy support, observability hooks

Result: Focus on your product logic while ai-lib handles provider integration friction.

⚙️ Quick Start

Installation

[dependencies]
ai-lib = "0.3.3"
tokio = { version = "1", features = ["full"] }
futures = "0.3"

One-liner Chat

use ai_lib::Provider;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let reply = ai_lib::AiClient::quick_chat_text(Provider::Groq, "Hello!").await?;
    println!("Reply: {reply}");
    Ok(())
}

Standard Usage

use ai_lib::{AiClient, Provider, Message, Role, Content, ChatCompletionRequest};

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let client = AiClient::new(Provider::OpenAI)?;
    let req = ChatCompletionRequest::new(
        client.default_chat_model(),
        vec![Message {
            role: Role::User,
            content: Content::Text("Explain Rust ownership in one sentence.".to_string()),
            function_call: None,
        }]
    );
    let resp = client.chat_completion(req).await?;
    println!("Answer: {}", resp.choices[0].message.content.as_text());
    Ok(())
}

Streaming

use futures::StreamExt;
let mut stream = client.chat_completion_stream(req).await?;
while let Some(chunk) = stream.next().await {
    let c = chunk?;
    if let Some(delta) = c.choices[0].delta.content.clone() {
        print!("{delta}");
    }
}

🧠 Core Concepts

💡 Key Features

Core Capabilities

• Unified Provider Abstraction: Single API across all providers
• Universal Streaming: Consistent SSE/JSONL parsing with real-time deltas
• Multimodal Support: Text, image, and audio content handling
• Function Calling: Consistent tool patterns and OpenAI compatibility
• Batch Processing: Sequential and concurrent processing strategies

Reliability & Production

• Built-in Resilience: Retry with exponential backoff, circuit breakers
• Error Classification: Distinguish transient vs permanent failures
• Connection Management: Pooling, timeouts, proxy support
• Observability: Pluggable metrics and tracing integration
• Security: No sensitive content logging by default

🌍 Supported Providers

17+ providers and growing - We continuously add new AI platforms to support the evolving ecosystem.

See examples/ for provider-specific usage patterns.

🔑 Configuration

Environment Variables

# API Keys (convention-based)
export OPENAI_API_KEY=...
export GROQ_API_KEY=...
export GEMINI_API_KEY=...
export ANTHROPIC_API_KEY=...

# Optional: Custom endpoints
export GROQ_BASE_URL=https://custom.groq.com

# Optional: Proxy and timeouts
export AI_PROXY_URL=http://proxy.internal:8080
export AI_TIMEOUT_SECS=30

# Optional: Connection pooling (enabled by default)
export AI_HTTP_POOL_MAX_IDLE_PER_HOST=32
export AI_HTTP_POOL_IDLE_TIMEOUT_MS=90000

Programmatic Configuration

use ai_lib::{AiClient, Provider, ConnectionOptions};
use std::time::Duration;

let client = AiClient::with_options(
    Provider::Groq,
    ConnectionOptions {
        base_url: Some("https://custom.groq.com".into()),
        proxy: Some("http://proxy.internal:8080".into()),
        api_key: Some("override-key".into()),
        timeout: Some(Duration::from_secs(45)),
        disable_proxy: false,
    }
)?;

Concurrency Control

use ai_lib::{AiClientBuilder, Provider};

let client = AiClientBuilder::new(Provider::Groq)
    .with_max_concurrency(64)
    .for_production()
    .build()?;

🛡️ Reliability & Resilience

📊 Observability & Metrics

Custom Metrics Integration

struct CustomMetrics;
#[async_trait::async_trait]
impl ai_lib::metrics::Metrics for CustomMetrics {
    async fn incr_counter(&self, name: &str, value: u64) { /* ... */ }
    async fn start_timer(&self, name: &str) -> Option<Box<dyn ai_lib::metrics::Timer + Send>> { /* ... */ }
}
let client = AiClient::new_with_metrics(Provider::Groq, Arc::new(CustomMetrics))?;

Usage Tracking

match response.usage_status {
    UsageStatus::Finalized => println!("Accurate token counts: {:?}", response.usage),
    UsageStatus::Estimated => println!("Estimated tokens: {:?}", response.usage),
    UsageStatus::Pending => println!("Usage data not yet available"),
    UsageStatus::Unsupported => println!("Provider doesn't support usage tracking"),
}

Optional Features

• interceptors: Retry, timeout, circuit breaker pipeline
• unified_sse: Common SSE parser for all providers
• unified_transport: Shared HTTP client factory
• cost_metrics: Basic cost accounting via environment variables
• routing_mvp: Model selection and routing capabilities

🗂️ Examples

📄 License

Dual-licensed under MIT or Apache License 2.0 - choose what works best for your project.

🤝 Contributing

1. Fork & clone repository
2. Create feature branch: git checkout -b feature/your-feature
3. Run tests: cargo test
4. Add examples for new features
5. Follow adapter patterns (prefer config-driven over custom)
6. Open PR with rationale + benchmarks (if performance impact)

We value: clarity, test coverage, minimal surface area, incremental composability.

📚 Citation

@software{ai-lib,
    title = {ai-lib: A Unified AI SDK for Rust},
    author = {Luqiang Wang},
    url = {https://github.com/hiddenpath/ai-lib},
    year = {2025}
}