308 lines
12 KiB
Python
308 lines
12 KiB
Python
import time
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import os
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import json
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import requests
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import re
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import threading
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from queue import Queue
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task_queue = Queue()
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llm_config = {
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"api_url": "",
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"api_key": "",
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"model": ""
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}
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def load_skills_md():
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try:
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with open('agent/skills.md', 'r', encoding='utf-8') as f:
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return f.read()
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except Exception as e:
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print(f"加载技能文档出错: {e}")
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return ""
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def llm_call(prompt):
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if not llm_config["api_url"] or not llm_config["api_key"] or not llm_config["model"]:
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return {"action": "stop", "args": {}}
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try:
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# 确保API URL以/chat/completions结尾（除了讯飞MaaS API）
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api_url = llm_config["api_url"].strip()
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# 对于非讯飞MaaS API，自动添加/chat/completions路径
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if "maas-api.cn" not in api_url and not api_url.endswith("/chat/completions"):
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if api_url.endswith("/"):
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api_url += "chat/completions"
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else:
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api_url += "/chat/completions"
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# 准备请求头
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headers = {
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"Content-Type": "application/json"
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}
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# 检查API Key格式，如果是client_id:client_secret格式，使用Basic认证
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api_key = llm_config["api_key"]
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if ":" in api_key:
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# 讯飞MaaS API格式：client_id:client_secret
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import base64
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auth_str = base64.b64encode(api_key.encode()).decode()
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headers["Authorization"] = f"Basic {auth_str}"
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else:
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# OpenAI API格式：Bearer token
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headers["Authorization"] = f"Bearer {api_key}"
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# 构建请求数据
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# 优先使用讯飞MaaS API格式
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if "maas-api.cn" in api_url:
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# 讯飞MaaS API格式
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data = {
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"model": llm_config["model"],
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"messages": [
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{"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。"},
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{"role": "user", "content": prompt}
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],
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"temperature": 0.7,
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"max_tokens": 500
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}
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else:
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# OpenAI API格式
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data = {
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"model": llm_config["model"],
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"messages": [
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{"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。"},
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{"role": "user", "content": prompt}
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]
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}
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print(f"调用LLM API: {api_url}")
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print(f"请求数据: {json.dumps(data, ensure_ascii=False)}")
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response = requests.post(api_url, headers=headers, json=data, timeout=15)
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print(f"API响应状态码: {response.status_code}")
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print(f"API响应内容: {response.text}")
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# 检查响应状态码
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if response.status_code != 200:
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print(f"API调用失败，状态码: {response.status_code}")
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return {"action": "stop", "args": {}}
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try:
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result = response.json()
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except json.JSONDecodeError as e:
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print(f"JSON解析错误: {e}")
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return {"action": "stop", "args": {}}
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# 处理不同API的响应格式
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if "maas-api.cn" in api_url:
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# 讯飞MaaS API响应格式
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if "choices" in result and len(result["choices"]) > 0:
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content = result["choices"][0]["message"]["content"]
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return safe_parse(content)
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else:
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return {"action": "stop", "args": {}}
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else:
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# OpenAI API响应格式
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if "choices" in result and len(result["choices"]) > 0:
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content = result["choices"][0]["message"]["content"]
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return safe_parse(content)
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else:
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return {"action": "stop", "args": {}}
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except Exception as e:
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print(f"LLM调用出错: {e}")
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return {"action": "stop", "args": {}}
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def safe_parse(result):
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try:
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if isinstance(result, dict):
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return result
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if isinstance(result, list):
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return result
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result = result.strip()
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if result.startswith("```"):
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lines = result.split("\n")
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for i, line in enumerate(lines):
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if not line.startswith("```") and line.strip():
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result = "\n".join(lines[i:])
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break
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if result.startswith("```"):
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return {"action": "stop", "args": {}}
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if result.endswith("```"):
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result = result[:-3].strip()
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# 尝试解析为JSON数组（多个动作）
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try:
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parsed = json.loads(result)
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if isinstance(parsed, list):
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return parsed
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except:
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pass
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# 尝试解析为JSON对象（单个动作）
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for line in result.split("\n"):
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line = line.strip()
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if line.startswith("{") and line.endswith("}"):
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return json.loads(line)
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match = re.search(r'\{[^}]+\}', result)
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if match:
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return json.loads(match.group())
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return {"action": "stop", "args": {}}
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except:
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return {"action": "stop", "args": {}}
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def execute_skill(action, args, motor_module):
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ALLOWED = [
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"move_forward", "move_backward", "turn_left", "turn_right",
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"stop", "play_path", "list_paths", "delete_path", "save_path"
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]
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if action not in ALLOWED:
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return {"status": "error", "message": "不允许的动作"}
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try:
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if action == "move_forward":
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print("控制垃圾桶前进")
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motor_module.backward(speed=0.6)
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def stop_after_duration():
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time.sleep(args.get("duration", 1))
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motor_module.stop()
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threading.Thread(target=stop_after_duration).start()
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return {"status": "success", "message": f"前进{args.get('duration', 1)}秒"}
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elif action == "move_backward":
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print("控制垃圾桶后退")
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motor_module.forward(speed=0.6)
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def stop_after_duration():
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time.sleep(args.get("duration", 1))
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motor_module.stop()
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threading.Thread(target=stop_after_duration).start()
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return {"status": "success", "message": f"后退{args.get('duration', 1)}秒"}
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elif action == "turn_left":
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print("控制垃圾桶左旋转")
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motor_module.rotate_left(speed=0.6)
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def stop_after_duration():
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time.sleep(args.get("duration", 1))
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motor_module.stop()
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threading.Thread(target=stop_after_duration).start()
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return {"status": "success", "message": f"左转{args.get('duration', 1)}秒"}
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elif action == "turn_right":
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print("控制垃圾桶右旋转")
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motor_module.rotate_right(speed=0.6)
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def stop_after_duration():
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time.sleep(args.get("duration", 1))
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motor_module.stop()
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threading.Thread(target=stop_after_duration).start()
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return {"status": "success", "message": f"右转{args.get('duration', 1)}秒"}
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elif action == "stop":
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print("停止垃圾桶")
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motor_module.stop()
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return {"status": "success", "message": "已停止"}
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elif action == "play_path":
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path_name = args.get("name")
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if not path_name:
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return {"status": "error", "message": "路径名称不能为空"}
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return {"status": "success", "message": f"播放轨迹{path_name}"}
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elif action == "list_paths":
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return {"status": "success", "message": "获取轨迹列表"}
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elif action == "delete_path":
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path_name = args.get("name")
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if not path_name:
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return {"status": "error", "message": "路径名称不能为空"}
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return {"status": "success", "message": f"删除轨迹{path_name}"}
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elif action == "save_path":
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path_name = args.get("name")
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if not path_name:
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return {"status": "error", "message": "路径名称不能为空"}
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return {"status": "success", "message": f"保存轨迹{path_name}"}
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else:
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return {"status": "error", "message": "无效的动作"}
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except Exception as e:
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print(f"执行技能出错: {e}")
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return {"status": "error", "message": f"执行技能出错: {e}"}
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def create_agent_routes(app, motor_module):
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@app.route('/agent_config', methods=['POST'])
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def agent_config():
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from flask import request, jsonify
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data = request.get_json()
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api_url = data.get('api_url', '')
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api_key = data.get('api_key', '')
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model = data.get('model', '')
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llm_config['api_url'] = api_url
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llm_config['api_key'] = api_key
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llm_config['model'] = model
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print(f"LLM配置已更新: API={api_url}, Model={model}")
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return jsonify({'status': 'success', 'message': '配置已保存'})
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@app.route('/agent_config', methods=['GET'])
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def get_agent_config():
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from flask import jsonify
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return jsonify({
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'status': 'success',
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'api_url': llm_config['api_url'],
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'api_key': llm_config['api_key'],
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'model': llm_config['model']
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})
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@app.route('/agent_chat', methods=['POST'])
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def agent_chat():
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from flask import request, jsonify
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data = request.get_json()
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text = data.get('text')
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if not text:
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return jsonify({'status': 'error', 'message': '输入文本不能为空'})
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try:
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skills_prompt = load_skills_md()
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prompt = skills_prompt + "\n用户输入：" + text
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result = llm_call(prompt)
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parsed_result = safe_parse(result)
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# 检查是否是多个动作（列表）
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if isinstance(parsed_result, list) and len(parsed_result) > 0:
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# 执行第一个动作
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first_action = parsed_result[0]
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action = first_action.get("action", "stop")
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args = first_action.get("args", {})
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task_queue.put((action, args))
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response = execute_skill(action, args, motor_module)
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# 如果有后续动作，在第一个动作完成后执行
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if len(parsed_result) > 1:
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def execute_next_actions():
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for i, next_action_data in enumerate(parsed_result[1:]):
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# 等待前一个动作完成
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time.sleep(next_action_data.get("args", {}).get("duration", 1))
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# 添加0.5秒缓冲时间
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time.sleep(0.5)
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next_action = next_action_data.get("action", "stop")
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next_args = next_action_data.get("args", {})
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task_queue.put((next_action, next_args))
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execute_skill(next_action, next_args, motor_module)
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threading.Thread(target=execute_next_actions).start()
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return jsonify({"status": "success", "message": f"开始执行复合指令，共{len(parsed_result)}个动作"})
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else:
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# 单个动作的处理
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action = parsed_result.get("action", "stop")
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args = parsed_result.get("args", {})
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task_queue.put((action, args))
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response = execute_skill(action, args, motor_module)
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return jsonify(response)
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except Exception as e:
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print(f"Agent聊天出错: {e}")
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return jsonify({'status': 'error', 'message': f'Agent聊天出错: {e}'}) |