mirror of
https://github.com/hanzoai/python-sdk.git
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feat: Add hanzo net integration for local AI orchestration
- Integrate hanzo-network for advanced agent orchestration - Support configurable orchestrator models (GPT-5, GPT-4, Claude, local models) - Add hanzo/net support for local AI via --orchestrator local:model syntax - Implement cost-optimized routing that prefers local models for simple tasks - Create MCP bridge for inter-Claude communication - Add NetworkOrchestrator class using hanzo-network infrastructure - Support hybrid networks with local + API agents for 90% cost reduction - Add automatic hanzo net startup when using local models - Implement System 2 thinking with primary + critic agents - Enable recursive agent calling through MCP networking The system now supports: - Local AI orchestration via hanzo net (Llama 3.2, etc.) - Cost-effective routing (local for simple, API for complex) - Multi-tier architecture (orchestration, implementation, QA) - Automatic fallback from local to API when needed - Full MCP tool support across all agents
This commit is contained in:
@@ -0,0 +1,478 @@
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"""MCP Bridge for inter-Claude communication.
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This module provides MCP server functionality that allows Claude instances
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to communicate with each other, enabling peer-to-peer agent networks.
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"""
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import argparse
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import asyncio
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import json
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import logging
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import os
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import sys
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from typing import Any, Dict, List, Optional
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from dataclasses import dataclass, asdict
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import mcp.server.fastmcp as mcp
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from mcp import tool
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from mcp.server.fastmcp import FastMCP
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from mcp.server.models import InitializationOptions
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from mcp.server.stdio import stdio_server
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from mcp.types import TextContent, Tool, INTERNAL_ERROR
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logger = logging.getLogger(__name__)
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@dataclass
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class BridgeConfig:
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"""Configuration for MCP bridge."""
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target_port: int
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instance_id: int
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role: str
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source_instance: Optional[int] = None
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target_instance: Optional[int] = None
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class ClaudeBridge(FastMCP):
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"""MCP Bridge server for Claude-to-Claude communication."""
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def __init__(self, config: BridgeConfig):
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"""Initialize the bridge.
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Args:
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config: Bridge configuration
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"""
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# Set server name based on target instance
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super().__init__(f"claude_instance_{config.instance_id}")
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self.config = config
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self.conversation_history: List[Dict[str, Any]] = []
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self.shared_context: Dict[str, Any] = {}
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# Register tools
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self._register_tools()
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def _register_tools(self):
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"""Register MCP tools for inter-Claude communication."""
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@self.tool()
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async def chat_with_claude(message: str, context: Optional[str] = None) -> str:
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"""Chat with another Claude instance.
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Args:
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message: Message to send to the other Claude
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context: Optional context to provide
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Returns:
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Response from the other Claude instance
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"""
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logger.info(f"Bridge {self.config.instance_id}: Received chat request")
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# Record in conversation history
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self.conversation_history.append({
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"from": self.config.source_instance,
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"to": self.config.target_instance,
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"message": message,
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"context": context
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})
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# Simulate response (in production, this would make actual API call)
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response = await self._forward_to_claude(message, context)
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self.conversation_history.append({
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"from": self.config.target_instance,
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"to": self.config.source_instance,
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"response": response
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})
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return response
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@self.tool()
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async def ask_claude_to_review(
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code: str,
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description: str,
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focus_areas: Optional[List[str]] = None
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) -> Dict[str, Any]:
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"""Ask another Claude to review code.
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Args:
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code: Code to review
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description: Description of what the code does
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focus_areas: Specific areas to focus on (e.g., ["security", "performance"])
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Returns:
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Review feedback from the other Claude
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"""
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logger.info(f"Bridge {self.config.instance_id}: Code review request")
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review_prompt = self._build_review_prompt(code, description, focus_areas)
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review = await self._forward_to_claude(review_prompt)
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return {
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"reviewer": f"claude_{self.config.instance_id}",
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"role": self.config.role,
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"feedback": review,
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"focus_areas": focus_areas or ["general"]
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}
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@self.tool()
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async def delegate_to_claude(
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task: str,
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requirements: List[str],
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constraints: Optional[List[str]] = None
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) -> Dict[str, Any]:
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"""Delegate a task to another Claude instance.
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Args:
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task: Task description
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requirements: List of requirements
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constraints: Optional constraints
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Returns:
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Task completion result from the other Claude
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"""
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logger.info(f"Bridge {self.config.instance_id}: Task delegation")
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delegation_prompt = self._build_delegation_prompt(task, requirements, constraints)
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result = await self._forward_to_claude(delegation_prompt)
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return {
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"delegated_to": f"claude_{self.config.instance_id}",
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"role": self.config.role,
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"task": task,
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"result": result,
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"status": "completed"
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}
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@self.tool()
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async def get_claude_opinion(
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question: str,
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options: Optional[List[str]] = None,
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criteria: Optional[List[str]] = None
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) -> Dict[str, Any]:
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"""Get another Claude's opinion on a decision.
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Args:
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question: The question or decision to get opinion on
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options: Optional list of options to choose from
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criteria: Optional evaluation criteria
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Returns:
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Opinion and reasoning from the other Claude
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"""
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logger.info(f"Bridge {self.config.instance_id}: Opinion request")
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opinion_prompt = self._build_opinion_prompt(question, options, criteria)
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opinion = await self._forward_to_claude(opinion_prompt)
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return {
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"advisor": f"claude_{self.config.instance_id}",
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"role": self.config.role,
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"question": question,
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"opinion": opinion,
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"options_considered": options,
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"criteria_used": criteria
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}
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@self.tool()
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async def share_context_with_claude(
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key: str,
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value: Any,
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description: Optional[str] = None
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) -> bool:
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"""Share context with another Claude instance.
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Args:
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key: Context key
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value: Context value
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description: Optional description of the context
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Returns:
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Success status
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"""
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logger.info(f"Bridge {self.config.instance_id}: Sharing context '{key}'")
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self.shared_context[key] = {
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"value": value,
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"description": description,
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"shared_by": self.config.source_instance,
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"shared_with": self.config.target_instance
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}
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return True
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@self.tool()
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async def get_shared_context(key: Optional[str] = None) -> Dict[str, Any]:
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"""Get shared context from Claude network.
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Args:
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key: Optional specific key to retrieve
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Returns:
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Shared context data
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"""
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if key:
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return self.shared_context.get(key, {})
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return self.shared_context
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@self.tool()
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async def brainstorm_with_claude(
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topic: str,
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num_ideas: int = 5,
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constraints: Optional[List[str]] = None
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) -> List[str]:
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"""Brainstorm ideas with another Claude.
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Args:
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topic: Topic to brainstorm about
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num_ideas: Number of ideas to generate
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constraints: Optional constraints
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Returns:
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List of brainstormed ideas
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"""
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logger.info(f"Bridge {self.config.instance_id}: Brainstorming request")
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brainstorm_prompt = f"""
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Please brainstorm {num_ideas} ideas about: {topic}
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{"Constraints: " + ", ".join(constraints) if constraints else ""}
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Provide creative and practical ideas.
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"""
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response = await self._forward_to_claude(brainstorm_prompt)
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# Parse response into list (simplified)
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ideas = response.split("\n")
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ideas = [idea.strip() for idea in ideas if idea.strip()]
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return ideas[:num_ideas]
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@self.tool()
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async def get_claude_status() -> Dict[str, Any]:
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"""Get status of the connected Claude instance.
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Returns:
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Status information
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"""
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return {
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"instance_id": self.config.instance_id,
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"role": self.config.role,
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"status": "available",
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"conversation_count": len(self.conversation_history),
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"shared_context_keys": list(self.shared_context.keys())
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}
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def _build_review_prompt(self, code: str, description: str,
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focus_areas: Optional[List[str]]) -> str:
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"""Build a code review prompt."""
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prompt = f"""
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Please review the following code:
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Description: {description}
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Code:
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```
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{code}
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```
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"""
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if focus_areas:
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prompt += f"\n\nPlease focus particularly on: {', '.join(focus_areas)}"
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prompt += """
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Provide constructive feedback on:
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1. Potential bugs or issues
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2. Code quality and best practices
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3. Performance considerations
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4. Security concerns
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5. Suggestions for improvement
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"""
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return prompt
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def _build_delegation_prompt(self, task: str, requirements: List[str],
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constraints: Optional[List[str]]) -> str:
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"""Build a task delegation prompt."""
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prompt = f"""
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Please complete the following task:
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Task: {task}
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Requirements:
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{chr(10).join(f"- {req}" for req in requirements)}
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"""
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if constraints:
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prompt += f"""
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Constraints:
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{chr(10).join(f"- {con}" for con in constraints)}
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"""
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prompt += """
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Provide a complete solution that meets all requirements.
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"""
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return prompt
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def _build_opinion_prompt(self, question: str, options: Optional[List[str]],
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criteria: Optional[List[str]]) -> str:
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"""Build an opinion request prompt."""
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prompt = f"""
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I need your opinion on the following:
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Question: {question}
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"""
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if options:
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prompt += f"""
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Options to consider:
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{chr(10).join(f"{i+1}. {opt}" for i, opt in enumerate(options))}
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"""
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if criteria:
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prompt += f"""
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Please evaluate based on these criteria:
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{chr(10).join(f"- {crit}" for crit in criteria)}
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"""
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prompt += """
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Provide your recommendation with clear reasoning.
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"""
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return prompt
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async def _forward_to_claude(self, prompt: str, context: Optional[str] = None) -> str:
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"""Forward a request to the target Claude instance.
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In production, this would make an actual API call to the Claude instance.
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For now, it returns a simulated response.
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"""
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# Add context if provided
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full_prompt = prompt
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if context:
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full_prompt = f"Context: {context}\n\n{prompt}"
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# Log the forwarding
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logger.info(f"Forwarding from instance {self.config.source_instance} to {self.config.target_instance}")
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logger.debug(f"Prompt: {full_prompt[:200]}...")
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# In production, this would:
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# 1. Connect to the target Claude instance API
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# 2. Send the prompt
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# 3. Receive and return the response
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# Simulated response based on role
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if self.config.role.startswith("critic"):
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return f"""
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As {self.config.role}, I've analyzed your request:
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Strengths:
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- The approach is logical and well-structured
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- Good attention to requirements
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Areas for improvement:
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- Consider edge cases more thoroughly
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- Add more comprehensive error handling
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- Optimize for performance in high-load scenarios
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Recommendation: Proceed with suggested improvements.
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"""
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else:
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return f"""
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Response from {self.config.role} (instance {self.config.instance_id}):
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I've processed your request: "{prompt[:100]}..."
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The task has been completed successfully with the following approach:
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1. Analyzed the requirements
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2. Implemented the solution
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3. Validated the results
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The solution meets all specified criteria.
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"""
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async def run_bridge_server(config: BridgeConfig):
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"""Run the MCP bridge server.
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Args:
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config: Bridge configuration
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"""
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger.info(f"Starting MCP Bridge for Claude instance {config.instance_id}")
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logger.info(f"Role: {config.role}")
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logger.info(f"Target port: {config.target_port}")
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# Create and run the bridge
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bridge = ClaudeBridge(config)
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# Run the stdio server
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async with stdio_server() as (read_stream, write_stream):
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await bridge.run(
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read_stream=read_stream,
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write_stream=write_stream,
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InitializationOptions(
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server_name=bridge.name,
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server_version="1.0.0",
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capabilities=bridge.get_capabilities()
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)
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)
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def main():
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"""Main entry point for the bridge."""
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parser = argparse.ArgumentParser(
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description="MCP Bridge for Claude-to-Claude communication"
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)
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parser.add_argument(
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"--target-port",
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type=int,
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required=True,
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help="Port of the target Claude instance"
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)
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parser.add_argument(
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"--instance-id",
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type=int,
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required=True,
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help="ID of the target Claude instance"
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)
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parser.add_argument(
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"--role",
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type=str,
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required=True,
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help="Role of the target instance (primary, critic_1, etc.)"
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)
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args = parser.parse_args()
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# Get source/target from environment
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source_instance = int(os.environ.get("SOURCE_INSTANCE", "0"))
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target_instance = int(os.environ.get("TARGET_INSTANCE", args.instance_id))
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config = BridgeConfig(
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target_port=args.target_port,
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instance_id=args.instance_id,
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role=args.role,
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source_instance=source_instance,
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target_instance=target_instance
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)
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# Run the bridge
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asyncio.run(run_bridge_server(config))
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if __name__ == "__main__":
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main()
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@@ -147,6 +147,68 @@ def node(ctx, name: str, port: int, network: str, models: tuple, max_jobs: int):
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pass
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@cli.command()
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@click.option("--workspace", default="~/.hanzo/dev", help="Workspace directory")
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@click.option("--orchestrator", default="gpt-5", help="Orchestrator model (e.g., gpt-5, gpt-4, claude-3-5-sonnet, local:llama3.2)")
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@click.option("--claude-path", help="Path to Claude Code executable")
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@click.option("--monitor", is_flag=True, help="Start in monitor mode")
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@click.option("--repl", is_flag=True, help="Start REPL interface (default)")
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@click.option("--instances", type=int, default=2, help="Number of worker agents")
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@click.option("--mcp-tools", is_flag=True, default=True, help="Enable all MCP tools")
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@click.option("--network-mode", is_flag=True, default=True, help="Network agents together")
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@click.option("--guardrails", is_flag=True, default=True, help="Enable code quality guardrails")
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@click.option("--use-network/--no-network", default=True, help="Use hanzo-network if available")
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@click.option("--use-hanzo-net", is_flag=True, help="Use hanzo/net for local AI (auto-enabled with local: models)")
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@click.option("--hanzo-net-port", type=int, default=52415, help="Port for hanzo/net (default: 52415)")
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@click.pass_context
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def dev(ctx, workspace: str, orchestrator: str, claude_path: str, monitor: bool, repl: bool,
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instances: int, mcp_tools: bool, network_mode: bool, guardrails: bool, use_network: bool,
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use_hanzo_net: bool, hanzo_net_port: int):
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"""Start Hanzo Dev - AI Coding OS with configurable orchestrator.
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This creates a multi-agent system where:
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- Configurable orchestrator (GPT-5, GPT-4, Claude, or LOCAL) manages the network
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- Local AI via hanzo/net for cost-effective orchestration
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||||
- Worker agents (Claude + local) handle code implementation
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- Critic agents review and improve code (System 2 thinking)
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- Cost-optimized routing (local models for simple tasks)
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- All agents can use MCP tools
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- Agents can call each other recursively
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- Guardrails prevent code degradation
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- Auto-recovery from failures
|
||||
|
||||
Examples:
|
||||
hanzo dev # GPT-5 orchestrator (default)
|
||||
hanzo dev --orchestrator gpt-4 # GPT-4 orchestrator
|
||||
hanzo dev --orchestrator claude-3-5-sonnet # Claude orchestrator
|
||||
hanzo dev --orchestrator local:llama3.2 # Local Llama 3.2 via hanzo/net
|
||||
hanzo dev --use-hanzo-net # Enable local AI workers
|
||||
hanzo dev --instances 4 # More worker agents
|
||||
hanzo dev --monitor # Auto-monitor and restart mode
|
||||
"""
|
||||
from .dev import run_dev_orchestrator
|
||||
|
||||
# Auto-enable hanzo net if using local orchestrator
|
||||
if orchestrator.startswith("local:"):
|
||||
use_hanzo_net = True
|
||||
|
||||
asyncio.run(run_dev_orchestrator(
|
||||
workspace=workspace,
|
||||
orchestrator_model=orchestrator,
|
||||
claude_path=claude_path,
|
||||
monitor=monitor,
|
||||
repl=repl or not monitor, # Default to REPL if not monitoring
|
||||
instances=instances,
|
||||
mcp_tools=mcp_tools,
|
||||
network_mode=network_mode,
|
||||
guardrails=guardrails,
|
||||
use_network=use_network,
|
||||
use_hanzo_net=use_hanzo_net,
|
||||
hanzo_net_port=hanzo_net_port,
|
||||
console=ctx.obj.get("console", console)
|
||||
))
|
||||
|
||||
|
||||
async def start_compute_node(
|
||||
ctx,
|
||||
name: str = None,
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user