from llm.bedrock import BedrockClient from jarvis_mcp.client import MCPClient from config import MCP_URL from util.logger import get_logger import asyncio from pathlib import Path # Import des neuen Web-Search Tools und der IR Sender Api from tools.web_search import web_search_tool, web_search from tools.script_api_tool import script_api_tool class Agent: def __init__(self): self.logger = get_logger("NORA") self.llm = BedrockClient() self.mcp = MCPClient(MCP_URL) self.tools = [] # Personality / System-Prompt (als User-Message für Nova 2 Lite) self.system_prompt = self._load_system_prompt() self.messages = [ { "role": "user", "content": [{"text": self.system_prompt}] } ] def _load_system_prompt(self) -> str: """Lädt Personality aus externer Datei""" try: prompt_path = Path("prompts/nora_system.txt") if prompt_path.exists(): return prompt_path.read_text(encoding="utf-8").strip() else: self.logger.warning("System-Prompt-Datei nicht gefunden. Verwende Standard.") return ( "Du bist N.O.R.A (Neural Operations for Residential Automation), " "ein freundlicher, kompetenter und leicht ironischer Smart-Home Assistent. " "Du antwortest natürlich und auf Deutsch. Nutze Tools wenn sinnvoll." ) except Exception: return "Du bist N.O.R.A, ein hilfreicher Smart-Home Assistent." # ------------------------- # TOOL LOADING # ------------------------- async def load_tools(self): try: # 1. OpenHAB Tools vom MCP Server laden res = await self.mcp.list_tools() self.tools = [] for t in res.tools: schema = t.inputSchema # Bedrock-kompatibles Format if isinstance(schema, dict) and "json" not in schema: bedrock_schema = {"json": schema} else: bedrock_schema = schema self.tools.append(script_api_tool) self.tools.append({ "toolSpec": { "name": t.name, "description": t.description, "inputSchema": bedrock_schema } }) self.logger.info(f"{len(self.tools)} OpenHAB-Tools erfolgreich geladen") # 2. Web-Search Tool manuell hinzufügen if not any(t.get("toolSpec", {}).get("name") == "web_search" for t in self.tools): self.tools.append(web_search_tool) self.logger.info("Web-Search Tool hinzugefügt (DuckDuckGo)") self.logger.info(f"Gesamt: {len(self.tools)} Tools geladen") except Exception as e: self.logger.error(f"Tool Load Error: {e}") self.tools = [] # ------------------------- # TOOL EXECUTION # ------------------------- async def _run_tool(self, tool): try: tool_use = tool.get("toolUse", tool) name = tool_use.get("name") args = tool_use.get("input", {}) or {} self.logger.info(f"Tool Call → {name} | args={args}") # Web-Search Tool if name == "web_search": return await web_search(**args) if tool_name == "run_script": result = await run_script( arguments["command"], arguments.get("args") ) # Normale MCP Tools (OpenHAB) result = await self.mcp.call_tool(name, args) if hasattr(result, "content"): return result.content return result except Exception as e: self.logger.error(f"Tool Error ({name}): {e}") return f"ERROR: {e}" # ------------------------- # MAIN LOOP # ------------------------- async def run(self, user_input: str): self.messages.append({ "role": "user", "content": [{"text": user_input}] }) for iteration in range(12): try: response = await self.llm.chat( messages=self.messages, tools=self.tools if self.tools else None ) except Exception as e: self.logger.error(f"LLM Error: {e}") return f"LLM Fehler: {e}" output = response.get("output", {}) message = output.get("message", {}) content = message.get("content", []) tool_uses = [] final_text = [] for c in content: if "toolUse" in c: tool_uses.append(c) elif "text" in c: final_text.append(c["text"]) if tool_uses: self.logger.info(f"{len(tool_uses)} Tool(s) detected") self.messages.append({ "role": "assistant", "content": content }) tool_results = [] for tool in tool_uses: result = await self._run_tool(tool) tool_results.append({ "toolResult": { "toolUseId": tool.get("toolUse", tool).get("toolUseId"), "content": [{"text": str(result)}] } }) self.messages.append({ "role": "user", "content": tool_results }) continue # Finale Antwort if final_text: text = "\n".join(final_text) self.messages.append({ "role": "assistant", "content": [{"text": text}] }) return text return "Tool Loop Limit erreicht. Bitte versuche es erneut."