Fusion 360 MCP

""" Google Gemini API Client Supports Gemini 1.5 Pro and Flash models """ import time import json from typing import Dict, Optional import google.generativeai as genai from loguru import logger class GeminiClient: """Client for Google Gemini API""" def __init__(self, api_key: str, timeout: int = 30): """ Initialize Gemini client Args: api_key: Google API key timeout: Request timeout in seconds """ genai.configure(api_key=api_key) self.timeout = timeout async def generate( self, model: str, prompt: str, system_prompt: Optional[str] = None, temperature: float = 0.7, max_tokens: int = 2000 ) -> Dict: """ Generate response using Gemini Args: model: Model name (gemini-1.5-pro-latest, gemini-1.5-flash-latest) prompt: User prompt system_prompt: System prompt temperature: Temperature for generation max_tokens: Maximum tokens to generate Returns: Dict with provider, model, output, and json fields """ start_time = time.time() # Build full prompt full_prompt = prompt if system_prompt: full_prompt = f"{system_prompt}\n\nUser: {prompt}\n\nAssistant:" # Configure generation generation_config = { "temperature": temperature, "max_output_tokens": max_tokens, } try: # Create model gemini_model = genai.GenerativeModel( model_name=model, generation_config=generation_config ) # Generate response response = gemini_model.generate_content(full_prompt) output = response.text # Try to get token count tokens_used = None if hasattr(response, 'usage_metadata'): tokens_used = response.usage_metadata.total_token_count latency = (time.time() - start_time) * 1000 logger.info(f"Gemini generation completed in {latency:.0f}ms") return { "provider": "gemini", "model": model, "output": output, "json": self._parse_json(output), "tokens_used": tokens_used, "latency_ms": latency } except Exception as e: logger.error(f"Gemini API error: {e}") raise def _parse_json(self, text: str) -> Optional[Dict]: """ Try to extract JSON from response Args: text: Response text Returns: Parsed JSON dict or None """ # Try direct parse try: return json.loads(text) except json.JSONDecodeError: pass # Try to find JSON object try: start = text.find('{') end = text.rfind('}') if start != -1 and end != -1: json_str = text[start:end+1] return json.loads(json_str) except json.JSONDecodeError: pass return None async def list_models(self) -> list: """List available Gemini models""" try: models = genai.list_models() return [ model.name.split('/')[-1] for model in models if 'gemini' in model.name.lower() ] except Exception as e: logger.error(f"Failed to list Gemini models: {e}") return []