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zeekayandGitHub
5b5cf9e9db
Transforms hanzoai/agents from a marketplace config repo into a full agent orchestration platform by merging the AgentField infrastructure: - Go control plane (K8s-like agent orchestration, service mesh, DAG workflows) - Python SDK (FastAPI-based agent framework, LiteLLM, memory, DID/VC) - TypeScript SDK (@hanzo/agents - Vercel AI SDK, MCP, workflows) - Go SDK (idiomatic agent builder + client) - React 19 embedded dashboard (XyFlow DAGs, Recharts, Radix UI) - Docker/K8s/Helm deployment configs - Examples: hello world, deep research, RAG, simulation, benchmarks - Functional test suite across Python/Go/TypeScript All references rebranded: AgentField → Hanzo Agents - Module: github.com/hanzoai/agents/control-plane - Python: hanzo_agents - TypeScript: @hanzo/agents - Go: github.com/hanzoai/agents/sdk/go - Env vars: HANZO_AGENTS_* - Config: hanzo-agents.yaml Previous marketplace configs moved to config/ directory.
79 lines
2.0 KiB
Python
79 lines
2.0 KiB
Python
"""
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Hello World Agent - Minimal Hanzo Agents Example
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Demonstrates:
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- One skill (deterministic function)
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- Two reasoners (AI-powered functions)
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- Call graph: say_hello → get_greeting (skill) + add_emoji (reasoner)
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"""
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from hanzo_agents import Agent
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from hanzo_agents import AIConfig
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from pydantic import BaseModel
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import os
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# Initialize agent
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app = Agent(
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node_id="hello-world",
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hanzo_agents_server=os.getenv("HANZO_AGENTS_URL", "http://localhost:8080"),
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ai_config=AIConfig(
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model=os.getenv("SMALL_MODEL", "openai/gpt-4o-mini"), temperature=0.7
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),
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)
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# ============= SKILL (DETERMINISTIC) =============
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@app.skill()
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def get_greeting(name: str) -> dict:
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"""Returns a greeting template (deterministic - no AI)"""
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return {"message": f"Hello, {name}! Welcome to Hanzo Agents."}
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# ============= REASONERS (AI-POWERED) =============
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class EmojiResult(BaseModel):
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"""Simple schema for emoji addition"""
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text: str
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emoji: str
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@app.reasoner()
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async def add_emoji(text: str) -> EmojiResult:
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"""Uses AI to add an appropriate emoji to text"""
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return await app.ai(
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user=f"Add one appropriate emoji to this greeting: {text}", schema=EmojiResult
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)
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@app.reasoner()
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async def say_hello(name: str) -> dict:
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"""
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Main entry point - orchestrates skill and reasoner.
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Call graph:
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say_hello (entry point)
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├─→ get_greeting (skill)
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└─→ add_emoji (reasoner)
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"""
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# Step 1: Get greeting from skill (deterministic)
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greeting = get_greeting(name)
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# Step 2: Add emoji using AI (reasoner)
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result = await add_emoji(greeting["message"])
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return {"greeting": result.text, "emoji": result.emoji, "name": name}
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# ============= START SERVER OR CLI =============
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if __name__ == "__main__":
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print("🚀 Hello World Agent")
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print("📍 Node: hello-world")
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print("🌐 Control Plane: http://localhost:8080")
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# Universal entry point - auto-detects CLI vs server mode
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app.run(auto_port=True)
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