ADK-Rust

use adk_tool::{tool, AdkError};
use schemars::JsonSchema;
use serde::Deserialize;
use serde_json::{json, Value};

#[derive(Deserialize, JsonSchema)]
struct WeatherArgs {
    /// The city to look up
    city: String,
}

/// Get the current weather for a city.
#[tool]
async fn get_weather(args: WeatherArgs) -> std::result::Result<Value, AdkError> {
    Ok(json!({ "temp": 72, "city": args.city }))
}

// Use it: agent_builder.tool(Arc::new(GetWeather))

use adk_rust::run;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    dotenvy::dotenv().ok();
    // Set ANTHROPIC_API_KEY, OPENAI_API_KEY, or GOOGLE_API_KEY
    let response = run("You are a helpful assistant.", "What is 2 + 2?").await?;
    println!("{response}");
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    let api_key = std::env::var("GOOGLE_API_KEY")?;
    let model = GeminiModel::new(&api_key, "gemini-2.5-flash")?;

    let agent = LlmAgentBuilder::new("assistant")
        .description("Helpful AI assistant")
        .instruction("You are a helpful assistant. Be concise and accurate.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    let api_key = std::env::var("OPENAI_API_KEY")?;
    let model = OpenAIClient::new(OpenAIConfig::new(api_key, "gpt-5-mini"))?;

    let agent = LlmAgentBuilder::new("assistant")
        .instruction("You are a helpful assistant.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;
use adk_model::openai::{OpenAIResponsesClient, OpenAIResponsesConfig};

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    let api_key = std::env::var("OPENAI_API_KEY")?;
    let config = OpenAIResponsesConfig::new(api_key, "gpt-4.1-mini");
    let model = OpenAIResponsesClient::new(config)?;

    let agent = LlmAgentBuilder::new("assistant")
        .instruction("You are a helpful assistant.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    let api_key = std::env::var("ANTHROPIC_API_KEY")?;
    let model = AnthropicClient::new(AnthropicConfig::new(api_key, "claude-sonnet-4-6"))?;

    let agent = LlmAgentBuilder::new("assistant")
        .instruction("You are a helpful assistant.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    let api_key = std::env::var("DEEPSEEK_API_KEY")?;

    // Standard chat model
    let model = DeepSeekClient::chat(api_key)?;

    // Or use reasoner for chain-of-thought reasoning
    // let model = DeepSeekClient::reasoner(api_key)?;

    let agent = LlmAgentBuilder::new("assistant")
        .instruction("You are a helpful assistant.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    let api_key = std::env::var("GROQ_API_KEY")?;
    let model = GroqClient::new(GroqConfig::llama70b(api_key))?;

    let agent = LlmAgentBuilder::new("assistant")
        .instruction("You are a helpful assistant.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_rust::prelude::*;
use adk_rust::Launcher;

#[tokio::main]
async fn main() -> AnyhowResult<()> {
    dotenvy::dotenv().ok();
    // Requires: ollama serve && ollama pull llama3.2
    let model = OllamaModel::new(OllamaConfig::new("llama3.2"))?;

    let agent = LlmAgentBuilder::new("assistant")
        .instruction("You are a helpful assistant.")
        .model(Arc::new(model))
        .build()?;

    Launcher::new(Arc::new(agent)).run().await?;
    Ok(())
}

use adk_realtime::{RealtimeAgent, openai::OpenAIRealtimeModel, RealtimeModel};
use std::sync::Arc;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let model: Arc<dyn RealtimeModel> = Arc::new(
        OpenAIRealtimeModel::new(&api_key, "gpt-4o-realtime-preview-2024-12-17")
    );

    let agent = RealtimeAgent::builder("voice_assistant")
        .model(model)
        .instruction("You are a helpful voice assistant.")
        .voice("alloy")
        .server_vad()  // Enable voice activity detection
        .build()?;

    Ok(())
}

use adk_graph::{prelude::*, node::AgentNode};
use adk_agent::LlmAgentBuilder;
use adk_model::GeminiModel;

// Create LLM agents for different tasks
let translator = Arc::new(LlmAgentBuilder::new("translator")
    .model(Arc::new(GeminiModel::new(&api_key, "gemini-2.5-flash")?))
    .instruction("Translate the input text to French.")
    .build()?);

let summarizer = Arc::new(LlmAgentBuilder::new("summarizer")
    .model(model.clone())
    .instruction("Summarize the input text in one sentence.")
    .build()?);

// Create AgentNodes with custom input/output mappers
let translator_node = AgentNode::new(translator)
    .with_input_mapper(|state| {
        let text = state.get("input").and_then(|v| v.as_str()).unwrap_or("");
        adk_core::Content::new("user").with_text(text)
    })
    .with_output_mapper(|events| {
        let mut updates = HashMap::new();
        for event in events {
            if let Some(content) = event.content() {
                let text: String = content.parts.iter()
                    .filter_map(|p| p.text())
                    .collect::<Vec<_>>()
                    .join("");
                updates.insert("translation".to_string(), json!(text));
            }
        }
        updates
    });

// Build graph with parallel execution
let agent = GraphAgent::builder("text_processor")
    .description("Translates and summarizes text in parallel")
    .channels(&["input", "translation"Release History
Version
Changes
Urgency
Date
v2.2.0
API-compatible minor release. All 43 crates are on [crates.io](https://crates.io/crates/adk-rust/2.2.0).  ```toml adk-rust = "2.2.0" ```  ## Added  **Wave 4 platform services** complete the Gemini Enterprise Agent Platform consumption path. Every one is opt-in, composable with any preset, and appended to `gemini-agent-platform`.  | Feature | Crate | What it gives you | |---------|-------|-------------------| | `vertex-eval` | adk-eval | Gen AI Evaluation Service bridge — `evaluateInstances` and 
Medium
9/1/2026
v2.1.0
ADK-Rust 2.1.0 is an API-compatible minor release adding portable team orchestration, the owned runtime UI, Gemini Enterprise Agent Platform integrations, hardened ambient scheduling and tool guardrails, expanded Anthropic capabilities, refreshed provider model catalogs, and security dependency updates.  All 43 workspace crates are published on crates.io. See the [2.1.0 changelog](https://github.com/zavora-ai/adk-rust/blob/v2.1.0/CHANGELOG.md#210---2026-08-25) for the detailed compatibility and 
High
8/25/2026
v2.0.0
# ADK-Rust v2.0.0 — Agents That Act  A major release for agents that run on their own and finish what they start. **42 crates. 4,300+ tests. 104 runnable examples. 568 μs agent-loop overhead.**  <a href="https://www.youtube.com/watch?v=RIh-M0W1CiQ"><img src="https://raw.githubusercontent.com/zavora-ai/adk-rust/main/docs/podcast/episode-3-thumbnail.png" alt="Watch Episode 3: Agents That Act" width="100%"></a>  **🎬 [Rust & Beyond, Episode 3 — Agents That Act](https://www.youtube.com/watch?v=RIh-M
High
8/17/2026
v1.0.0
# ADK-Rust v1.0.0 — The Stable Foundation  The first stable release of the Rust Agent Development Kit. **39 crates. 130K+ downloads in 6 months. Semver stability guarantee.**  <a href="https://www.youtube.com/watch?v=tlqaE8qeHac"><img src="https://raw.githubusercontent.com/zavora-ai/adk-rust/main/docs/podcast/episode-2-thumbnail.jpg" alt="▶ Watch the launch video" width="560"></a>  ## Highlights  - **Semver stable** — pin to `1.x` and your build won't break - **All former Beta crates promoted to
High
6/7/2026
v0.9.0
## ADK-Rust v0.9.0  ### Added  - **Composable Template System** — 8 base templates, 9 addons, 5 enterprise patterns via `cargo adk new --addon` - **Cargo Adk Build** — Compile-without-deploy subcommand for pre-deployment verification - **A2A Simple Scaffolding** — `A2aServer::quick_start`, `A2aServer::builder`, `cargo adk new --template a2a`  ### Changed  - Version bump from 0.8.5 to 0.9.0  ### Security  - hickory-proto 0.26.1 (moderate — DNS cache poisoning) - openssl 0.10.80 (moderate — certif
High
5/24/2026
v0.8.4
## Fixed  - **Gemini schema: array types require `items`**: v0.8.3 stripped tuple-style `items` entirely, causing Gemini to reject arrays with "missing field" errors. Now tuple `items` (`[{type:number},{type:number}]`) are converted to a single schema using the first element (`{type:number}`). Arrays without any `items` field also get a default `{type:string}` added.  ## Upgrade  ```toml adk-gemini = "0.8.4" ```  **Full Changelog**: https://github.com/zavora-ai/adk-rust/compare/v0.8.3...v0.8.4
High
5/18/2026
v0.8.1
## Highlights  **Agent Client Protocol (ACP) support** — connect ADK agents to Claude Code, Codex, Kiro CLI, and any ACP-compatible agent as tools.  ### New Crate: `adk-acp`  ```rust use adk_acp::AcpAgentTool;  let kiro = AcpAgentTool::new("kiro-cli acp --trust-all-tools")     .description("Delegate coding tasks to Kiro CLI");  let agent = LlmAgentBuilder::new("orchestrator")     .tool(Arc::new(kiro))     .build()?; ```  - `AcpAgentTool` — wraps any ACP agent as an ADK Tool - `AcpToolset` — mult
High
5/13/2026
v0.8.0
## Highlights  **Performance release** — default builds are 32% lighter with new feature tiers.  ### Breaking Changes  - **Default feature changed from `standard` to `minimal`**: `adk-rust = "0.8.0"` now activates only `agents`, `models`, `gemini`, `runner`, and `sessions`. Add `features = ["standard"]` for the full production preset.  ### New Feature Tiers  | Tier | Includes | Use case | |------|----------|----------| | `minimal` (default) | Gemini, agents, runner, sessions | Fast starter agent
High
5/7/2026
v0.7.0
## ADK-Rust v0.7.0  ### Highlights  - **Agentic Web Protocol (AWP)** — Two new crates (`awp-types`, `adk-awp`) implementing the full AWP protocol: discovery, capability manifests, trust levels, rate limiting, consent, events, health monitoring, and version negotiation. [AWP Docs](https://github.com/zavora-ai/adk-rust/blob/main/docs/official_docs/deployment/awp.md) - **DeepSeek V4 Provider** — `ThinkingMode`, `ReasoningEffort`, strict tool mode, beta URL support, `v4_pro`/`v4_flash` constructors 
High
4/26/2026
v0.6.0
## 🚀 ADK-Rust v0.6.0  **31 crates published to crates.io** · [Listen to the podcast →](https://github.com/zavora-ai/adk-rust#-rust--beyond-podcast--episode-1-what-is-adk-rust)  ### 🎧 Rust & Beyond Podcast  Episode 1 is live on the README — a 2:21 podcast about ADK-Rust generated entirely by the framework using Gemini 3.1 Flash TTS. Two AI hosts, natural voices, zero manual editing.  ### ✨ Highlights  #### Multimodal Function Responses (`adk-core`, `adk-gemini`, `adk-model`, `adk-agent`)  Tools
High
4/16/2026
v0.5.0
# ADK-Rust v0.5.0  **31 crates published to crates.io** — the largest ADK-Rust release to date.  ## Highlights  ### Zero-Config Ergonomics - **`provider_from_env()`** — auto-detect LLM provider from environment variables (Anthropic → OpenAI → Gemini precedence) - **`adk::run(instructions, input)`** — single-function agent invocation with auto provider detection, session creation, and execution  ### Prompt Caching Enabled by Default - **Anthropic**: `prompt_caching` now defaults to `true` (cache_
Medium
3/29/2026
v0.4.0
## Highlights  **ADK-Rust is now a focused, lean Rust framework.** UI, Studio, and 120+ examples extracted to standalone repos. Default builds dropped from ~2min to ~50s. New `cargo-adk` scaffolding CLI and `#[tool]` proc macro for zero-boilerplate DX.  ### Get Started  ```bash cargo install cargo-adk cargo adk new my-agent cd my-agent && cargo run ```  Templates: `--template tools` | `rag` | `api` | `openai`  ---  ## Breaking Changes  - **Default preset:** `full` → `standard`. Server/CLI includ
Low
3/16/2026
v0.3.1
## ADK-Rust v0.3.1  ### ⭐ Highlights  - **Vertex AI Streaming**: `adk-gemini` refactored with `GeminiBackend` trait — pluggable `StudioBackend` (REST) and `VertexBackend` (REST SSE streaming + gRPC fallback) - **Realtime Audio Transport**: Three new transports for `adk-realtime` — Vertex AI Live (OAuth2/ADC), LiveKit WebRTC bridge, OpenAI WebRTC (str0m + Opus) - **Vertex AI Live Tool Calling**: New `vertex_live_tools` example demonstrating real-time voice agents with function calling via Vertex 
Low
2/15/2026
v0.3.0
## ⭐ Highlights - **Context Compaction**: Sliding-window summarization of older events to reduce LLM context size (ADK Python parity) - **Workflow Agent Hardening**: ConditionalAgent, LlmConditionalAgent, and ParallelAgent production fixes - **adk-core Production Hardening**: Security limits, validation, provider-agnostic Event, hand-written template parser - **Action Node Code Generation**: Full Rust codegen for HTTP, Database, Email, and Code action nodes - **Workflow Triggers**: Complete trig
Low
2/10/2026
v0.2.1
## ⭐ Highlights - **OpenAI Structured Output**: `output_schema` now works with OpenAI/Azure via `response_format` API - **Ralph Autonomous Agent**: New example showcasing spec-driven development with loop agents - **Local Model Support**: New examples for Ollama and OpenAI-compatible local APIs - **Improved Error Handling**: Replaced `unwrap()` calls with proper error handling across crates  ## Added - **adk-model**: OpenAI/Azure clients now wire `output_schema` to `response_format` with `json_s
Low
1/22/2026
v0.2.0
## Release v0.2.0 - Major Documentation & Feature Update  ### 🚀 New Features  **Streaming Mode Control** - Implement `StreamingMode.None` and SSE per ADK spec - Add streaming mode control to Launcher API - Use stable event IDs for all streaming chunks  **Tracing & Observability** - Add `call_llm` span in llm_agent.rs for all model types - Fix async tool execution tracing to match adk-go pattern - Group spans by invocation_id in trace UI - Add get_event endpoint for trace-event linking  **Agents
Low
1/7/2026
v0.1.8
## ⭐ Highlights - **ADK Studio**: Complete visual agent builder with drag-and-drop workflow design - **Real-Time Streaming**: Live SSE streaming with agent animations and trace events - **Code Generation**: Compile visual workflows to production Rust code - **Rust 2024 Edition**: Migrated to Rust 2024 edition for latest language features  ## Added - **ADK Studio** (`adk-studio`): Visual agent development environment   - Drag-and-drop agent creation with ReactFlow-based canvas   - Full agent pale
Low
12/28/2025
v0.1.7
## 🛡️ Guardrails Framework  This release introduces **adk-guardrail**, a new crate for agent safety and validation.  ### New Crate: adk-guardrail  - **`Guardrail` trait** - Async validation returning `Pass`, `Fail`, or `Transform` - **`GuardrailSet`** - Collection with parallel execution and early exit on `Critical` severity - **`Severity` levels** - `Low`, `Medium`, `High`, `Critical`  ### Built-in Guardrails  | Guardrail | Description | |-----------|-------------| | `PiiRedactor` | Detects an
Low
12/14/2025
v0.1.6
# Release v0.1.6 🦀  ## 🎨 Introducing adk-ui: Dynamic UI Generation for AI Agents  This release introduces **adk-ui**, a complete framework for AI agents to generate rich, interactive user interfaces through tool calls. Give your agents the power to render forms, tables, charts, dashboards, and more!  ### Why adk-ui?  Traditional AI chatbots are limited to text responses. With adk-ui, your agents can: - **Collect structured data** via forms (registration, settings, surveys) - **Display data** w
Low
12/12/2025
v0.1.5
## Added - **DeepSeek provider support**: Native integration with DeepSeek's LLM models   - `DeepSeekClient` and `DeepSeekConfig` for easy configuration   - Support for `deepseek-chat` (standard) and `deepseek-reasoner` (thinking mode)   - Thinking mode with chain-of-thought reasoning   - Context caching for 10x cost reduction on repeated prefixes   - Full function calling/tool support   - Feature flag: `adk-model = { features = ["deepseek"] }` - 8 new DeepSeek examples:   - `deepseek_basic` - B
Low
12/10/2025
v0.1.4
Release v0.1.4 - Graph Workflows, Browser Automation, Evaluation    This release adds three major new crates: adk-graph for LangGraph-style workflows, adk-browser for browser automation, and adk-eval for agent evaluation.    ✨ New Features    adk-graph Crate    - StateGraph for building complex agent workflows with state channels   - AgentNode for wrapping LLM agents as graph nodes with input/output mappers   - Conditional routing with Router::by_field and custom predicates   - Human-
Low
12/9/2025
v0.1.3
## Release v0.1.3 - Real-time Voice-Enabled AI Agents    This release introduces the `adk-realtime` crate for building voice-enabled AI agents with real-time audio streaming.    ### ✨ New Features    #### adk-realtime Crate   - **RealtimeAgent** implementing `adk_core::Agent` trait with full callback/tool/instruction support   - **OpenAI Realtime API** support (`gpt-4o-realtime-preview-2024-12-17`, `gpt-realtime`)   - **Gemini Live API** support (`gemini-2.0-flash-live-preview-04-09`) 
Low
12/9/2025
v0.1.2
## Release v0.1.2 - Multi-Provider LLM Support  This release adds support for OpenAI and Anthropic providers, making ADK-Rust a truly multi-provider LLM framework supporting Gemini, OpenAI, and Claude.  ### ✨ New Features  #### OpenAI Provider Support - Full integration with OpenAI GPT models (GPT-4o, GPT-4o-mini, GPT-4-turbo, GPT-3.5-turbo) - `OpenAIClient` and `OpenAIConfig` for easy configuration - Streaming support with proper tool call accumulation - Feature flag: `adk-model = { features = 
Low
12/7/2025