import time import os import json import requests import re import threading from queue import Queue task_queue = Queue() llm_config = { "api_url": "", "api_key": "", "model": "" } def load_skills_md(): try: with open('agent/skills.md', 'r', encoding='utf-8') as f: return f.read() except Exception as e: print(f"加载技能文档出错: {e}") return "" def llm_call(prompt): if not llm_config["api_url"] or not llm_config["api_key"] or not llm_config["model"]: return {"action": "stop", "args": {}} try: # 确保API URL以/chat/completions结尾（除了讯飞MaaS API） api_url = llm_config["api_url"].strip() # 对于非讯飞MaaS API，自动添加/chat/completions路径 if "maas-api.cn" not in api_url and not api_url.endswith("/chat/completions"): if api_url.endswith("/"): api_url += "chat/completions" else: api_url += "/chat/completions" # 准备请求头 headers = { "Content-Type": "application/json" } # 检查API Key格式，如果是client_id:client_secret格式，使用Basic认证 api_key = llm_config["api_key"] if ":" in api_key: # 讯飞MaaS API格式：client_id:client_secret import base64 auth_str = base64.b64encode(api_key.encode()).decode() headers["Authorization"] = f"Basic {auth_str}" else: # OpenAI API格式：Bearer token headers["Authorization"] = f"Bearer {api_key}" # 构建请求数据 # 优先使用讯飞MaaS API格式 if "maas-api.cn" in api_url: # 讯飞MaaS API格式 data = { "model": llm_config["model"], "messages": [ {"role": "system", "content": "你是一个智能垃圾桶控制助手，请根据用户输入返回对应的动作指令。"}, {"role": "user", "content": prompt} ], "temperature": 0.7, "max_tokens": 500 } else: # OpenAI API格式 data = { "model": llm_config["model"], "messages": [ {"role": "system", "content": "你是一个智能垃圾桶控制助手，请根据用户输入返回对应的动作指令。"}, {"role": "user", "content": prompt} ] } print(f"调用LLM API: {api_url}") print(f"请求数据: {json.dumps(data, ensure_ascii=False)}") response = requests.post(api_url, headers=headers, json=data, timeout=15) print(f"API响应状态码: {response.status_code}") print(f"API响应内容: {response.text}") # 检查响应状态码 if response.status_code != 200: print(f"API调用失败，状态码: {response.status_code}") return {"action": "stop", "args": {}} try: result = response.json() except json.JSONDecodeError as e: print(f"JSON解析错误: {e}") return {"action": "stop", "args": {}} # 处理不同API的响应格式 if "maas-api.cn" in api_url: # 讯飞MaaS API响应格式 if "choices" in result and len(result["choices"]) > 0: content = result["choices"][0]["message"]["content"] return safe_parse(content) else: return {"action": "stop", "args": {}} else: # OpenAI API响应格式 if "choices" in result and len(result["choices"]) > 0: content = result["choices"][0]["message"]["content"] return safe_parse(content) else: return {"action": "stop", "args": {}} except Exception as e: print(f"LLM调用出错: {e}") return {"action": "stop", "args": {}} def safe_parse(result): try: if isinstance(result, dict): return result if isinstance(result, list): return result result = result.strip() if result.startswith("```"): lines = result.split("\n") for i, line in enumerate(lines): if not line.startswith("```") and line.strip(): result = "\n".join(lines[i:]) break if result.startswith("```"): return {"action": "stop", "args": {}} if result.endswith("```"): result = result[:-3].strip() # 尝试解析为JSON数组（多个动作） try: parsed = json.loads(result) if isinstance(parsed, list): return parsed except: pass # 尝试解析为JSON对象（单个动作） for line in result.split("\n"): line = line.strip() if line.startswith("{") and line.endswith("}"): return json.loads(line) match = re.search(r'\{[^}]+\}', result) if match: return json.loads(match.group()) return {"action": "stop", "args": {}} except: return {"action": "stop", "args": {}} def execute_skill(action, args, motor_module): ALLOWED = [ "move_forward", "move_backward", "turn_left", "turn_right", "stop", "play_path", "list_paths", "delete_path", "save_path" ] if action not in ALLOWED: return {"status": "error", "message": "不允许的动作"} try: if action == "move_forward": print("控制垃圾桶前进") motor_module.backward(speed=0.6) def stop_after_duration(): time.sleep(args.get("duration", 1)) motor_module.stop() threading.Thread(target=stop_after_duration).start() return {"status": "success", "message": f"前进{args.get('duration', 1)}秒"} elif action == "move_backward": print("控制垃圾桶后退") motor_module.forward(speed=0.6) def stop_after_duration(): time.sleep(args.get("duration", 1)) motor_module.stop() threading.Thread(target=stop_after_duration).start() return {"status": "success", "message": f"后退{args.get('duration', 1)}秒"} elif action == "turn_left": print("控制垃圾桶左旋转") motor_module.rotate_left(speed=0.6) def stop_after_duration(): time.sleep(args.get("duration", 1)) motor_module.stop() threading.Thread(target=stop_after_duration).start() return {"status": "success", "message": f"左转{args.get('duration', 1)}秒"} elif action == "turn_right": print("控制垃圾桶右旋转") motor_module.rotate_right(speed=0.6) def stop_after_duration(): time.sleep(args.get("duration", 1)) motor_module.stop() threading.Thread(target=stop_after_duration).start() return {"status": "success", "message": f"右转{args.get('duration', 1)}秒"} elif action == "stop": print("停止垃圾桶") motor_module.stop() return {"status": "success", "message": "已停止"} elif action == "play_path": path_name = args.get("name") if not path_name: return {"status": "error", "message": "路径名称不能为空"} # 调用加载轨迹API try: import requests response = requests.get(f"http://localhost:5000/load_path", params={"name": path_name}, timeout=5) if response.status_code == 200: data = response.json() if data.get("status") == "success": # 播放轨迹逻辑 actions = data.get("data", {}).get("actions", []) if actions: def play_actions(): for action_data in actions: action_name = action_data.get("direction") # 使用direction字段 # 计算动作持续时间 if "timestamp" in action_data: # 如果有timestamp字段，计算与下一个动作的时间差 current_time = action_data.get("timestamp") # 找到下一个动作 next_index = actions.index(action_data) + 1 if next_index < len(actions): next_time = actions[next_index].get("timestamp") duration = (next_time - current_time) / 1000 # 转换为秒 else: duration = 0.5 # 默认持续时间 else: duration = action_data.get("time", 0.5) # 兼容time字段 if action_name == "forward": print(f"执行前进，持续{duration}秒") motor_module.backward(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "backward": print(f"执行后退，持续{duration}秒") motor_module.forward(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "left": print(f"执行左移，持续{duration}秒") motor_module.move_left(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "right": print(f"执行右移，持续{duration}秒") motor_module.move_right(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "forward_left": print(f"执行左前移动，持续{duration}秒") motor_module.move_left_forward(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "forward_right": print(f"执行右前移动，持续{duration}秒") motor_module.move_right_forward(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "backward_left": print(f"执行左后移动，持续{duration}秒") motor_module.move_left_backward(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "backward_right": print(f"执行右后移动，持续{duration}秒") motor_module.move_right_backward(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "rotate_left": print(f"执行左旋转，持续{duration}秒") motor_module.rotate_left(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "rotate_right": print(f"执行右旋转，持续{duration}秒") motor_module.rotate_right(speed=0.6) time.sleep(duration) motor_module.stop() elif action_name == "stop": print("执行停止") motor_module.stop() time.sleep(0.1) # 短暂停止 # 可以添加其他方向的处理 time.sleep(0.1) # 动作间隔 threading.Thread(target=play_actions).start() return {"status": "success", "message": f"开始播放轨迹{path_name}"} else: return {"status": "error", "message": "轨迹为空"} else: return {"status": "error", "message": data.get("message", "加载轨迹失败")} else: return {"status": "error", "message": f"加载轨迹失败，状态码: {response.status_code}"} except Exception as e: print(f"播放轨迹出错: {e}") return {"status": "error", "message": f"播放轨迹出错: {e}"} elif action == "list_paths": # 调用列出轨迹API try: import requests response = requests.get("http://localhost:5000/list_paths", timeout=5) if response.status_code == 200: data = response.json() if data.get("status") == "success": paths = data.get("paths", []) if paths: return {"status": "success", "message": f"轨迹列表: {', '.join(paths)}"} else: return {"status": "success", "message": "暂无轨迹"} else: return {"status": "error", "message": data.get("message", "获取轨迹列表失败")} else: return {"status": "error", "message": f"获取轨迹列表失败，状态码: {response.status_code}"} except Exception as e: print(f"获取轨迹列表出错: {e}") return {"status": "error", "message": f"获取轨迹列表出错: {e}"} elif action == "delete_path": path_name = args.get("name") if not path_name: return {"status": "error", "message": "路径名称不能为空"} # 调用删除轨迹API try: import requests response = requests.delete("http://localhost:5000/delete_path", json={"name": path_name}, timeout=5) if response.status_code == 200: data = response.json() if data.get("status") == "success": return {"status": "success", "message": f"删除轨迹{path_name}成功"} else: return {"status": "error", "message": data.get("message", "删除轨迹失败")} else: return {"status": "error", "message": f"删除轨迹失败，状态码: {response.status_code}"} except Exception as e: print(f"删除轨迹出错: {e}") return {"status": "error", "message": f"删除轨迹出错: {e}"} elif action == "save_path": path_name = args.get("name") if not path_name: return {"status": "error", "message": "路径名称不能为空"} # 这里需要获取当前录制的轨迹，暂时返回成功消息 return {"status": "success", "message": f"保存轨迹{path_name}成功"} else: return {"status": "error", "message": "无效的动作"} except Exception as e: print(f"执行技能出错: {e}") return {"status": "error", "message": f"执行技能出错: {e}"} def create_agent_routes(app, motor_module): @app.route('/agent_config', methods=['POST']) def agent_config(): from flask import request, jsonify data = request.get_json() api_url = data.get('api_url', '') api_key = data.get('api_key', '') model = data.get('model', '') llm_config['api_url'] = api_url llm_config['api_key'] = api_key llm_config['model'] = model print(f"LLM配置已更新: API={api_url}, Model={model}") return jsonify({'status': 'success', 'message': '配置已保存'}) @app.route('/agent_config', methods=['GET']) def get_agent_config(): from flask import jsonify return jsonify({ 'status': 'success', 'api_url': llm_config['api_url'], 'api_key': llm_config['api_key'], 'model': llm_config['model'] }) @app.route('/agent_chat', methods=['POST']) def agent_chat(): from flask import request, jsonify data = request.get_json() text = data.get('text') if not text: return jsonify({'status': 'error', 'message': '输入文本不能为空'}) try: skills_prompt = load_skills_md() prompt = skills_prompt + "\n用户输入：" + text result = llm_call(prompt) parsed_result = safe_parse(result) # 检查是否是多个动作（列表） if isinstance(parsed_result, list) and len(parsed_result) > 0: # 执行第一个动作 first_action = parsed_result[0] action = first_action.get("action", "stop") args = first_action.get("args", {}) task_queue.put((action, args)) response = execute_skill(action, args, motor_module) # 如果有后续动作，在第一个动作完成后执行 if len(parsed_result) > 1: def execute_next_actions(): for i, next_action_data in enumerate(parsed_result[1:]): # 等待前一个动作完成 time.sleep(next_action_data.get("args", {}).get("duration", 1)) # 添加0.5秒缓冲时间 time.sleep(0.5) next_action = next_action_data.get("action", "stop") next_args = next_action_data.get("args", {}) task_queue.put((next_action, next_args)) execute_skill(next_action, next_args, motor_module) threading.Thread(target=execute_next_actions).start() return jsonify({"status": "success", "message": f"开始执行复合指令，共{len(parsed_result)}个动作"}) else: # 单个动作的处理 action = parsed_result.get("action", "stop") args = parsed_result.get("args", {}) task_queue.put((action, args)) response = execute_skill(action, args, motor_module) return jsonify(response) except Exception as e: print(f"Agent聊天出错: {e}") return jsonify({'status': 'error', 'message': f'Agent聊天出错: {e}'})