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Agent Operating System — Production-ready multi-model agent framework with Tool-Using Agent, LLM Provider abstraction (OpenAI/DeepSeek/Anthropic), Function Calling, streaming, retry, checkpoint/resume, A2A protocol, swarm coordination, and comprehensive observability.

Project description


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AgentOS v1.0

Production-ready multi-model agent framework.

Quick Start

pip install agentos

With an API key:

export OPENAI_API_KEY=sk-...
agentos "What's the weather in Beijing?"

Without an API key (mock demo mode):

agentos demo

Features

  • LLM Provider: OpenAI / DeepSeek / Anthropic, unified interface
  • Tool-Using Agent: Autonomous multi-step reasoning with Function Calling
  • Streaming: run_stream() for real-time step yielding
  • Retry & Checkpoint: Configurable retry + JSON checkpoint/resume
  • Mock Mode: Test without API keys
  • A2A Protocol: Agent-to-agent communication
  • Swarm Coordination: Multi-agent topologies

CLI

agentos <task>         Run a task
agentos demo           Weather agent demo
agentos serve          Start API server
agentos version        Show version

Provider Auto-Detection

Env Var Provider Default Model
OPENAI_API_KEY OpenAI gpt-4o-mini
DEEPSEEK_API_KEY DeepSeek deepseek-chat
ANTHROPIC_API_KEY Anthropic claude-sonnet-4

Python API

from agentos.llm import create_provider
from agentos.llm.base import Tool, ToolParameter
from agentos.agent import ToolAgent, ToolExecutor, AgentConfig

provider = create_provider("openai")
executor = ToolExecutor()
executor.register(
    Tool.from_function("get_weather", "Get weather", {
        "city": ToolParameter(type="string", description="City name"),
    }),
    lambda city: f"{city}: 22°C sunny",
)

agent = ToolAgent(provider, executor, config=AgentConfig())
result = agent.run("What's the weather in Tokyo?")
print(result.final_answer)

(内容由AI生成,仅供参考)

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