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- Add docker-publish.yml workflow for ghcr.io - Add production-ready Dockerfile (if missing) - Enable automated builds on push to main - Support for semantic versioning tags
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
"""Agent tools for Hanzo AI.
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This module provides tools that allow Claude to delegate tasks to sub-agents,
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enabling concurrent execution of multiple operations and specialized processing.
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"""
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from mcp.server import FastMCP
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from hanzo_mcp.tools.agent.agent_tool import AgentTool
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from hanzo_mcp.tools.common.base import BaseTool, ToolRegistry
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from hanzo_mcp.tools.common.permissions import PermissionManager
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def register_agent_tools(
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mcp_server: FastMCP,
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permission_manager: PermissionManager,
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agent_model: str | None = None,
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agent_max_tokens: int | None = None,
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agent_api_key: str | None = None,
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agent_base_url: str | None = None,
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agent_max_iterations: int = 10,
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agent_max_tool_uses: int = 30,
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) -> list[BaseTool]:
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"""Register agent tools with the MCP server.
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Args:
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mcp_server: The FastMCP server instance
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permission_manager: Permission manager for access control
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agent_model: Optional model name for agent tool in LiteLLM format
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agent_max_tokens: Optional maximum tokens for agent responses
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agent_api_key: Optional API key for the LLM provider
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agent_base_url: Optional base URL for the LLM provider API endpoint
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agent_max_iterations: Maximum number of iterations for agent (default: 10)
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agent_max_tool_uses: Maximum number of total tool uses for agent (default: 30)
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Returns:
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List of registered tools
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"""
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# Create agent tool
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agent_tool = AgentTool(
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permission_manager=permission_manager,
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model=agent_model,
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api_key=agent_api_key,
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base_url=agent_base_url,
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max_tokens=agent_max_tokens,
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max_iterations=agent_max_iterations,
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max_tool_uses=agent_max_tool_uses,
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)
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# Register agent tool
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ToolRegistry.register_tool(mcp_server, agent_tool)
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# Return list of registered tools
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return [agent_tool]
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