Agent SDK

A Rust SDK for building AI agents powered by large language models (LLMs). Create agents that can reason, use tools, and take actions through a streaming, event-driven architecture.

⚠️ Early Development: This library is in active development (v0.1.x). APIs may change between versions and there may be bugs. Use in production at your own risk. Feedback and contributions are welcome!

What is an Agent?

An agent is an LLM that can do more than just chat—it can use tools to interact with the world. This SDK provides the infrastructure to:

• Send messages to an LLM and receive streaming responses
• Define tools the LLM can call (APIs, file operations, databases, etc.)
• Execute tool calls and feed results back to the LLM
• Control the agent loop with hooks for logging, security, and approval workflows

Features

• Agent Loop - Core orchestration that handles the LLM conversation and tool execution cycle
• Provider Agnostic - Built-in support for Anthropic (Claude), OpenAI, and Google Gemini, plus a trait for custom providers
• Tool System - Define tools with JSON schema validation; the LLM decides when to use them
• Lifecycle Hooks - Intercept tool calls for logging, user confirmation, rate limiting, or security checks
• Streaming Events - Real-time event stream for building responsive UIs
• Primitive Tools - Ready-to-use tools for file operations (Read, Write, Edit, Glob, Grep, Bash)
• Security Model - Capability-based permissions and tool tiers (Observe, Confirm, RequiresPin)
• Persistence - Trait-based storage for conversation history and agent state

Requirements

• Rust 1.85+ (2024 edition)
• An API key for your chosen LLM provider

Installation

Add to your Cargo.toml:

[dependencies]
agent-sdk = "0.1"
tokio = { version = "1", features = ["rt-multi-thread", "macros"] }
anyhow = "1"

Or to install the latest development version from git:

[dependencies]
agent-sdk = { git = "https://github.com/bipa-app/agent-sdk", branch = "main" }

Quick Start

use agent_sdk::{builder, ThreadId, ToolContext, AgentEvent, providers::AnthropicProvider};

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Get your API key from the environment
    let api_key = std::env::var("ANTHROPIC_API_KEY")?;

    // Build an agent with the Anthropic provider
    // The ::<()> specifies no custom context type (see "Custom Context" below)
    let agent = builder::<()>()
        .provider(AnthropicProvider::sonnet(api_key))
        .build();

    // Each conversation gets a unique thread ID
    let thread_id = ThreadId::new();

    // ToolContext can carry custom data to your tools (empty here)
    let tool_ctx = ToolContext::new(());

    // Run the agent and get a stream of events
    let mut events = agent.run(
        thread_id,
        "What is the capital of France?".to_string(),
        tool_ctx,
    );

    // Process events as they arrive
    while let Some(event) = events.recv().await {
        match event {
            AgentEvent::Text { text } => print!("{text}"),
            AgentEvent::Done { .. } => break,
            AgentEvent::Error { message, .. } => eprintln!("Error: {message}"),
            _ => {} // Other events: ToolCallStart, ToolCallEnd, etc.
        }
    }

    Ok(())
}

Examples

Clone the repo and run the examples:

git clone https://github.com/bipa-app/agent-sdk
cd agent-sdk

# Basic conversation (no tools)
ANTHROPIC_API_KEY=your_key cargo run --example basic_agent

# Agent with custom tools
ANTHROPIC_API_KEY=your_key cargo run --example custom_tool

# Using lifecycle hooks for logging and rate limiting
ANTHROPIC_API_KEY=your_key cargo run --example custom_hooks

# Agent with file operation tools
ANTHROPIC_API_KEY=your_key cargo run --example with_primitive_tools

Creating Custom Tools

Tools let your agent interact with external systems. Implement the Tool trait:

use agent_sdk::{Tool, ToolContext, ToolResult, ToolTier, ToolRegistry};
use async_trait::async_trait;
use serde_json::{Value, json};

/// A tool that fetches the current weather for a city
struct WeatherTool;

#[async_trait]
impl Tool<()> for WeatherTool {
    fn name(&self) -> &'static str {
        "get_weather"
    }

    fn description(&self) -> &'static str {
        "Get the current weather for a city. Returns temperature and conditions."
    }

    fn input_schema(&self) -> Value {
        json!({
            "type": "object",
            "properties": {
                "city": {
                    "type": "string",
                    "description": "The city name, e.g. 'San Francisco'"
                }
            },
            "required": ["city"]
        })
    }

    fn tier(&self) -> ToolTier {
        // Observe = no confirmation needed
        // Confirm = requires user approval
        // RequiresPin = requires PIN verification
        ToolTier::Observe
    }

    async fn execute(&self, _ctx: &ToolContext<()>, input: Value) -> anyhow::Result<ToolResult> {
        let city = input["city"].as_str().unwrap_or("Unknown");

        // In a real implementation, call a weather API here
        let weather = format!("Weather in {city}: 72°F, Sunny");

        Ok(ToolResult::success(weather))
    }
}

// Register tools with the agent
let mut tools = ToolRegistry::new();
tools.register(WeatherTool);

let agent = builder::<()>()
    .provider(provider)
    .tools(tools)
    .build();

Lifecycle Hooks

Hooks let you intercept and control agent behavior:

use agent_sdk::{AgentHooks, AgentEvent, ToolDecision, ToolResult, ToolTier};
use async_trait::async_trait;
use serde_json::Value;

struct MyHooks;

#[async_trait]
impl AgentHooks for MyHooks {
    /// Called before each tool execution
    async fn pre_tool_use(&self, tool_name: &str, input: &Value, tier: ToolTier) -> ToolDecision {
        println!("[LOG] Tool call: {tool_name}");

        // You could implement:
        // - User confirmation dialogs
        // - Rate limiting
        // - Input validation
        // - Audit logging

        match tier {
            ToolTier::Observe => ToolDecision::Allow,
            ToolTier::Confirm => {
                // In a real app, prompt the user here
                ToolDecision::Allow
            }
            ToolTier::RequiresPin => {
                ToolDecision::Block("PIN verification not implemented".to_string())
            }
        }
    }

    /// Called after each tool execution
    async fn post_tool_use(&self, tool_name: &str, result: &ToolResult) {
        println!("[LOG] {tool_name} completed: success={}", result.success);
    }

    /// Called for every agent event (optional)
    async fn on_event(&self, event: &AgentEvent) {
        // Track events, update UI, etc.
    }
}

let agent = builder::<()>()
    .provider(provider)
    .hooks(MyHooks)
    .build();

Custom Context

The generic parameter T in Tool<T> and builder::<T>() lets you pass custom data to your tools:

// Define your context type
struct MyContext {
    user_id: String,
    database: Database,
}

// Implement tools with access to context
#[async_trait]
impl Tool<MyContext> for MyTool {
    async fn execute(&self, ctx: &ToolContext<MyContext>, input: Value) -> anyhow::Result<ToolResult> {
        // Access your context
        let user = &ctx.data.user_id;
        let db = &ctx.data.database;
        // ...
    }
}

// Build agent with your context type
let agent = builder::<MyContext>()
    .provider(provider)
    .tools(tools)
    .build();

// Pass context when running
let tool_ctx = ToolContext::new(MyContext {
    user_id: "user_123".to_string(),
    database: db,
});
agent.run(thread_id, prompt, tool_ctx);

Architecture

┌─────────────────────────────────────────────────────────────┐
│                        Agent Loop                           │
│  Orchestrates: prompt → LLM → tool calls → results → LLM   │
├─────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────┐ │
│  │ LlmProvider │  │    Tools    │  │       Hooks         │ │
│  │  (trait)    │  │  Registry   │  │  (pre/post tool)    │ │
│  └─────────────┘  └─────────────┘  └─────────────────────┘ │
├─────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────┐ │
│  │MessageStore │  │ StateStore  │  │    Environment      │ │
│  │  (trait)    │  │  (trait)    │  │  (file/exec ops)    │ │
│  └─────────────┘  └─────────────┘  └─────────────────────┘ │
└─────────────────────────────────────────────────────────────┘

Built-in Providers

Provider	Models	Usage
Anthropic	Claude Sonnet, Opus, Haiku	AnthropicProvider::sonnet(api_key)
OpenAI	GPT-4, GPT-3.5, etc.	OpenAiProvider::new(api_key, model)
Google	Gemini Pro, etc.	GeminiProvider::new(api_key, model)

Implement LlmProvider trait to add your own.

Built-in Primitive Tools

For agents that need file system access:

Tool	Description
ReadTool	Read file contents
WriteTool	Create or overwrite files
EditTool	Make targeted edits to files
GlobTool	Find files matching patterns
GrepTool	Search file contents with regex
BashTool	Execute shell commands

These require an Environment (use InMemoryFileSystem for sandboxed testing or LocalFileSystem for real file access).

Security Considerations

• #[forbid(unsafe_code)] - No unsafe Rust anywhere in the codebase
• Capability-based permissions - Control read/write/exec access via AgentCapabilities
• Tool tiers - Classify tools by risk level; use hooks to require confirmation
• Sandboxing - Use InMemoryFileSystem for testing without real file access

See SECURITY.md for the full security policy.

Contributing

Contributions are welcome! Please read CONTRIBUTING.md for:

• Development setup
• Code quality requirements
• Pull request process

License

Licensed under the Apache License, Version 2.0. See LICENSE for details.