feat；代码整理提交

.env

@@ -0,0 +1,2 @@
+API_KEY=sk-WK7dkfpYfaXYtOQGMOfax5DmQF5itLZ2WXvi8ReVpQfGmbCN
+MODEL_BASE_URL=https://www.chataiapi.com

yj_room_agent/LLM/ai_service.py

@@ -0,0 +1,128 @@
+from threading import Lock
+from datetime import datetime
+import requests, json
+from openai_client import call_openai_api
+
+MODEL_NAME = ''
+BASE_URL = ''
+
+
+def is_json(myjson):
+    try:
+        json_object = json.loads(myjson)
+        return True
+    except ValueError:
+        return False
+
+
+def build_prompt():
+    """构建增强提示词"""
+    # 获取可用会议室信息
+    room_info = {}
+    for_mart_str = '''
+     {
+            "room_id":"11", //会议室ID
+            "capacity":20,
+            "start_time":"2025-06-04 09:30:10",
+            "end_time":"2025-06-04 12:30:10",
+            "user_confirm":1 //用户是否确认
+        }
+    '''
+
+    time_now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    # 增强提示词模板
+    template = f"""你是一个专业的OA会议预订助手，请根据以下信息提供服务：
+    现在时间是 :{time_now}
+    可用会议室信息：
+    {room_info}
+    请按以下步骤处理：
+    1. 解析用户需求（时间、人数、设备要求等）
+    2. 根据可用会议室列表推荐合适选项,推荐选项请不要返回json格式数据
+    3. 如果用户确定要预订某间会议室，请帮我提取用户预订信息并返回，结果请以json结果返回且不需要包含多余的描述内容,输出结果示例如下:
+     {for_mart_str}
+    4. 用户其他需求，请按照自然语言对话返回
+
+    """
+    return template
+
+
+class DialogManager:
+    def __init__(self):
+        self.dialogs = {}
+        self.lock = Lock()
+
+    def get_history(self, session_id: str) -> list:
+        return self.dialogs.get(session_id, [])
+
+    def add_message(self, session_id, role, content):
+        with self.lock:
+            if session_id not in self.dialogs:
+                self.dialogs[session_id] = []
+            # 自动维护对话历史
+            self.dialogs[session_id].append({
+                "role": role,
+                "timestamp": datetime.now().isoformat(),
+                "content": content
+            })
+            # 上下文压缩（超长对话处理）
+            if len(self.dialogs[session_id]) > 10:
+                self.compress_context(session_id)
+
+    def compress_context(self, session_id):
+        """对话历史压缩算法"""
+        history = self.dialogs[session_id]
+        # 保留最近3条完整记录
+        recent = history[-3:]
+        # 摘要生成中间对话内容
+        summary = self.generate_summary(history[3:-3])
+        # 重组会话历史
+        self.dialogs[session_id] = [
+            {"role": "system", "content": f"对话摘要：{summary}"},
+            *recent
+        ]
+
+    def generate_summary(self, messages):
+        """生成对话摘要（调用本地模型）"""
+        text = "\n".join([f"{m['role']}: {m['content']}" for m in messages])
+        payload = {
+            "model": MODEL_NAME,
+            "prompt": f"请生成以下对话的简明摘要（保留关键信息）：\n\n{text}"
+        }
+        response = requests.post(f"{BASE_URL}", json=payload, timeout=10)
+        return response.json().get("response", "摘要生成失败")
+
+
+dialog_manager = DialogManager()
+
+
+def process_chat(user_id: str, user_input: str):
+    history = dialog_manager.get_history(user_id)
+    prompt = ''
+    if history is None or len(history) == 0:
+        prompt = build_prompt()
+    resp = call_openai_api(model=MODEL_NAME, system_prompt=prompt, user_query=user_input,
+                           api_key='sk-KnfrPFFnNDOCFkPkWsvRE7uJGNR0QMDCZ1Ie83ARhtOKMMWa',
+                           history=history)
+    content = resp["choices"][0]["message"]["content"]
+    reasoning_content = resp["choices"][0]["message"]["reasoning_content"]
+    print(content)
+    if 'json' in content or is_json(content):
+        new_content = content.replace("json", '')
+        new_content = new_content.replace("`", '')
+        print(type(new_content))
+        print(new_content)
+        data = json.loads(new_content)
+        # 触发预订函数------
+        result = {}
+        book_promot = f'''
+               用户预订会议室的结果如下:
+              {result}
+              请解析预订会议室的结果，并根据结果给予用户相应反馈
+             '''
+        resp = call_openai_api(model=MODEL_NAME, system_prompt=book_promot, user_query=None,
+                               api_key='sk-KnfrPFFnNDOCFkPkWsvRE7uJGNR0QMDCZ1Ie83ARhtOKMMWa',
+                               history=history)
+        return {'response': resp}
+    else:
+        dialog_manager.add_message(dialog_manager, 'assistant', reasoning_content)
+        return {'response': resp}

yj_room_agent/settings.py

@@ -12,12 +12,16 @@ https://docs.djangoproject.com/en/5.2/ref/settings/
 
 from pathlib import Path
 
+from dotenv import load_dotenv
+
+
+
 # Build paths inside the project like this: BASE_DIR / 'subdir'.
 BASE_DIR = Path(__file__).resolve().parent.parent
 
 # Quick-start development settings - unsuitable for production
 # See https://docs.djangoproject.com/en/5.2/howto/deployment/checklist/
-
+load_dotenv()
 # SECURITY WARNING: keep the secret key used in production secret!
 SECRET_KEY = 'django-insecure-i(fm5c2v*=vgfwmgdl^qi7iezv(xfwovbqu=+^=vm72e$gnx&l'