import os import requests from langchain_mcp_adapters.tool import MCPTool gaia_system_prompt = """ You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string. """ class BasicAgent: def __init__(self, model_name="deepseek-ai/deepseek-v3.1"): print("BasicAgent initialized.") # MCP tool configuration self.mcp_tool = MCPTool( tool_name="generic_tool", # replace with actual tool name exposed by MCP server_url="http://localhost:8080", ) # NVIDIA NIM API configuration self.model_name = model_name self.api_key = os.getenv("NVIDIA_API_KEY") self.api_base = "https://integrate.api.nvidia.com/v1" def call_nim_api(self, user_input: str) -> str: headers = { "Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json" } payload = { "model": self.model_name, "messages": [ {"role": "system", "content": gaia_system_prompt}, {"role": "user", "content": user_input} ], "temperature": 0.7 } response = requests.post( f"{self.api_base}/chat/completions", headers=headers, json=payload ) try: return response.json()["choices"][0]["message"]["content"] except Exception as e: print("Error calling NIM API:", e) return "NIM API call failed." def __call__(self, question: str) -> str: print(f"Agent received input (first 50 chars): {question[:50]}...") # Call NVIDIA NIM API nim_output = self.call_nim_api(question) print(f"NIM response: {nim_output[:100]}...") # Optionally use MCP tool based on input if "scrape" in question.lower(): mcp_result = self.mcp_tool.run({ "url": "https://example.com", "selectors": { "title": ".title", "price": ".price" } }) print("MCP result:", mcp_result) return f"NIM: {nim_output}\n\nMCP: {mcp_result}" return nim_output