'commit'

AI/WxMini/Milvus/Utils/MilvusCollectionManager.py

@@ -71,7 +71,7 @@ class MilvusCollectionManager:
             # 使用 Milvus 的 query 方法查询指定 ID 的记录
             results = self.collection.query(
                 expr=f"id == {id}",  # 查询条件
-                output_fields=["id", "session_id", "user_input", "model_response", "timestamp"]  # 返回的字段
+                output_fields=["id", "person_id", "user_input", "model_response", "timestamp"]  # 返回的字段
             )
             if results:
                 return results[0]  # 返回第一条记录

AI/WxMini/Milvus/X1_create_collection.py

@@ -1,3 +1,5 @@
+import asyncio
+
 from pymilvus import FieldSchema, DataType, utility
 
 from WxMini.Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
@@ -23,13 +25,13 @@ if utility.has_collection(collection_name):
 # 5. 定义集合的字段和模式
 fields = [
     FieldSchema(name="id", dtype=DataType.INT64, is_primary=True, auto_id=True),  # 主键字段，自动生成 ID
-    FieldSchema(name="session_id", dtype=DataType.VARCHAR, max_length=64),  # 会话 ID
+    FieldSchema(name="person_id", dtype=DataType.VARCHAR, max_length=64),  # 会话 ID
     FieldSchema(name="user_input", dtype=DataType.VARCHAR, max_length=2048),  # 用户问题
     FieldSchema(name="model_response", dtype=DataType.VARCHAR, max_length=2048),  # 大模型反馈结果
     FieldSchema(name="timestamp", dtype=DataType.VARCHAR, max_length=32),  # 时间
     FieldSchema(name="embedding", dtype=DataType.FLOAT_VECTOR, dim=MS_DIMENSION)  # 向量字段，维度为 200
 ]
-schema_description = "Chat records collection with session ID, user input, model response, and timestamp"
+schema_description = "Chat records collection with person_id , user input, model response, and timestamp"
 
 # 6. 创建集合
 print(f"正在创建集合 '{collection_name}'...")

AI/WxMini/Milvus/X3_insert_data.py

@@ -66,14 +66,14 @@ print(f"大模型回复: {model_response}")
 
 # 7. 获取当前时间和会话 ID
 timestamp = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())  # 当前时间
-session_id = "F9D1C319-215D-3B4E-FAA0-0E024AC12D3C"  # 会话 ID（可以根据需要动态生成）
+person_id = "F9D1C319-215D-3B4E-FAA0-0E024AC12D3C"  # 会话 ID（可以根据需要动态生成）
 
 # 8. 将用户问题转换为嵌入向量
 user_embedding = text_to_embedding(user_input)
 
 # 9. 插入数据，确保字段顺序与集合定义一致
 entities = [
-    [session_id],  # session_id
+    [person_id],  # person_id
     [user_input],  # user_input
     [model_response],  # model_response
     [timestamp],  # timestamp

AI/WxMini/Milvus/X4_select_all_data.py

@@ -21,7 +21,7 @@ try:
     # 使用 Milvus 的 query 方法查询所有数据
     results = collection_manager.collection.query(
         expr="",  # 空表达式表示查询所有数据
-        output_fields=["id", "session_id", "user_input", "model_response", "timestamp", "embedding"],  # 指定返回的字段
+        output_fields=["id", "person_id", "user_input", "model_response", "timestamp", "embedding"],  # 指定返回的字段
         limit=1000  # 设置最大返回记录数
     )
     print("查询结果：")
@@ -29,14 +29,14 @@ try:
         for result in results:
             try:
                 # 获取字段值
-                session_id = result["session_id"]
+                person_id = result["person_id"]
                 user_input = result["user_input"]
                 model_response = result["model_response"]
                 timestamp = result["timestamp"]
                 embedding = result["embedding"]
                 # 打印结果
                 print(f"ID: {result['id']}")
-                print(f"会话 ID: {session_id}")
+                print(f"会话 ID: {person_id}")
                 print(f"用户问题: {user_input}")
                 print(f"大模型回复: {model_response}")
                 print(f"时间: {timestamp}")

AI/WxMini/Milvus/X5_search_near_data.py

@@ -62,7 +62,7 @@ if results:
                 # 查询非向量字段
                 record = collection_manager.query_by_id(hit.id)
                 print(f"ID: {hit.id}")
-                print(f"会话 ID: {record['session_id']}")
+                print(f"会话 ID: {record['person_id']}")
                 print(f"用户问题: {record['user_input']}")
                 print(f"大模型回复: {record['model_response']}")
                 print(f"时间: {record['timestamp']}")

AI/WxMini/Sql/t_chat_log.sql

@@ -23,7 +23,7 @@ SET FOREIGN_KEY_CHECKS = 0;
 DROP TABLE IF EXISTS `t_chat_log`;
 CREATE TABLE `t_chat_log`  (
   `id` int(11) NOT NULL AUTO_INCREMENT COMMENT '主键',
-  `session_id` char(36) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL COMMENT '用户人员编号',
+  `person_id` char(36) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL COMMENT '用户人员编号',
   `user_input` varchar(2000) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL COMMENT '用户提出的问题',
   `model_response` varchar(2000) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL COMMENT '大模型的反馈',
   `audio_url` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL COMMENT '生成的语音文件路径',

AI/WxMini/Start.py

@@ -13,7 +13,7 @@ from WxMini.Milvus.Utils.MilvusConnectionPool import *
 from WxMini.Utils.OssUtil import upload_mp3_to_oss_from_memory
 from WxMini.Utils.TtsUtil import TTS
 from WxMini.Utils.MySQLUtil import init_mysql_pool, save_chat_to_mysql, get_chat_log_by_session, update_risk, \
-    get_risk_chat_log_page, get_last_chat_log_id
+    get_risk_chat_log_page, get_last_chat_log_id, get_user_by_login_name
 from WxMini.Utils.EmbeddingUtil import text_to_embedding
 
 # 配置日志
@@ -46,9 +46,9 @@ async def lifespan(app: FastAPI):
 
 
 # 会话结束后，调用检查方法，判断是不是有需要介入的问题出现
-async def on_session_end(session_id):
+async def on_session_end(person_id):
     # 获取最后一条聊天记录
-    last_id = await get_last_chat_log_id(app.state.mysql_pool, session_id)
+    last_id = await get_last_chat_log_id(app.state.mysql_pool, person_id)
     if last_id:
         # 查询最后一条记录的详细信息
         async with app.state.mysql_pool.acquire() as conn:
@@ -90,10 +90,10 @@ async def on_session_end(session_id):
         analysis_result = response.choices[0].message.content.strip()
         if analysis_result.startswith("NO"):
             # 异步执行 update_risk
-            asyncio.create_task(update_risk(app.state.mysql_pool, session_id, analysis_result))
-            logger.info(f"已异步更新 session_id={session_id} 的风险状态。")
+            asyncio.create_task(update_risk(app.state.mysql_pool, person_id, analysis_result))
+            logger.info(f"已异步更新 person_id={person_id} 的风险状态。")
         else:
-            logger.info(f"AI大模型没有发现任何心理健康问题，用户会话 {session_id} 没有风险。")
+            logger.info(f"AI大模型没有发现任何心理健康问题，用户会话 {person_id} 没有风险。")
 
 
 # 初始化 FastAPI 应用
@@ -106,11 +106,12 @@ client = AsyncOpenAI(
 )
 
 
+
 @app.post("/aichat/reply")
-async def reply(session_id: str = Form(...), prompt: str = Form(...)):
+async def reply(person_id: str = Form(...), prompt: str = Form(...)):
     """
     接收用户输入的 prompt，调用大模型并返回结果
-    :param session_id: 用户会话 ID
+    :param person_id: 用户会话 ID
     :param prompt: 用户输入的 prompt
     :return: 大模型的回复
     """
@@ -132,7 +133,7 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
             collection_manager.search,
             data=current_embedding,  # 输入向量
             search_params=search_params,  # 搜索参数
-            expr=f"session_id == '{session_id}'",  # 按 session_id 过滤
+            expr=f"person_id == '{person_id}'",  # 按 person_id 过滤
             limit=5  # 返回 5 条结果
         )
         end_time = time.time()
@@ -182,7 +183,7 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
             # 记录用户输入和大模型反馈到向量数据库
             timestamp = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
             entities = [
-                [session_id],  # session_id
+                [person_id],  # person_id
                 [prompt[:500]],  # user_input，截断到 500 字符
                 [result[:500]],  # model_response，截断到 500 字符
                 [timestamp],  # timestamp
@@ -214,11 +215,11 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
             url = OSS_PREFIX + tts_file
 
             # 记录聊天数据到 MySQL
-            await save_chat_to_mysql(app.state.mysql_pool, session_id, prompt, result, url, duration)
+            await save_chat_to_mysql(app.state.mysql_pool, person_id, prompt, result, url, duration)
             logger.info("用户输入和大模型反馈已记录到 MySQL 数据库。")
 
             # 调用会话检查机制
-            await on_session_end(session_id)
+            await on_session_end(person_id)
 
             # 返回数据
             return {
@@ -241,22 +242,62 @@ async def reply(session_id: str = Form(...), prompt: str = Form(...)):
 # 获取聊天记录
 from fastapi import Query
 
+# 登录接口
+@app.post("/aichat/login")
+async def login(
+    login_name: str = Form(..., description="用户名"),
+    password: str = Form(..., description="密码")
+):
+    """
+    用户登录接口
+    :param login_name: 用户名
+    :param password: 密码
+    :return: 登录结果
+    """
+    if not login_name or not password:
+        raise HTTPException(status_code=400, detail="用户名和密码不能为空")
+
+    # 调用 get_user_by_login_name 方法
+    user = await get_user_by_login_name(app.state.mysql_pool, login_name)
+    if not user:
+        raise HTTPException(status_code=404, detail="用户不存在")
+    if user['password'] != password:
+        raise HTTPException(status_code=401, detail="密码错误")
+
+    # 返回带字段名称的数据
+    return {
+        "code": 200,
+        "message": "登录成功",
+        "data": {
+            "person_id": user["person_id"],
+            "login_name": user["login_name"],
+            "identity_id": user["identity_id"],
+            "person_name": user["person_name"],
+            "xb_name": user["xb_name"],
+            "city_name": user["city_name"],
+            "area_name": user["area_name"],
+            "school_name": user["school_name"],
+            "grade_name": user["grade_name"],
+            "class_name": user["class_name"]
+        }
+    }
+
 # 获取聊天记录
 @app.get("/aichat/get_chat_log")
 async def get_chat_log(
-        session_id: str,
+        person_id: str,
         page: int = Query(default=1, ge=1, description="当前页码（默认值为 1，但会动态计算为最后一页）"),
         page_size: int = Query(default=10, ge=1, le=100, description="每页记录数")
 ):
     """
     获取指定会话的聊天记录，默认返回最新的记录（最后一页）
-    :param session_id: 用户会话 ID
+    :param person_id: 用户会话 ID
     :param page: 当前页码（默认值为 1，但会动态计算为最后一页）
     :param page_size: 每页记录数
     :return: 分页数据
     """
     # 调用 get_chat_log_by_session 方法
-    result = await get_chat_log_by_session(app.state.mysql_pool, session_id, page, page_size)
+    result = await get_chat_log_by_session(app.state.mysql_pool, person_id, page, page_size)
     return result
 
 @app.get("/aichat/get_risk_page")

AI/WxMini/Test/Math1.py

@@ -14,10 +14,10 @@ prompt = "You are a helpful and harmless assistant. You are Qwen developed by Al
 #img_url = 'https://qianwen-res.oss-cn-beijing.aliyuncs.com/QVQ/demo.png'
 # 答案=46
 
-img_url='https://hzkc.oss-cn-beijing.aliyuncs.com/Temp/simple_math.jpeg'
+#img_url='https://hzkc.oss-cn-beijing.aliyuncs.com/Temp/simple_math.jpeg'
 # 答案应该是80度
 
-# img_url='https://hzkc.oss-cn-beijing.aliyuncs.com/Temp/hard_math.jpeg'
+img_url='https://hzkc.oss-cn-beijing.aliyuncs.com/Temp/hard_math.jpeg'
 
 response = client.chat.completions.create(
     #model="Qwen/QVQ-72B-Preview",

AI/WxMini/Utils/MySQLUtil.py

@@ -1,4 +1,6 @@
 import logging
+from typing import Optional, Dict
+
 from aiomysql import create_pool
 from WxMini.Milvus.Config.MulvusConfig import *
 
@@ -24,12 +26,12 @@ async def init_mysql_pool():
 
 
 # 保存聊天记录到 MySQL
-async def save_chat_to_mysql(mysql_pool, session_id, prompt, result, audio_url, duration):
+async def save_chat_to_mysql(mysql_pool, person_id, prompt, result, audio_url, duration):
     async with mysql_pool.acquire() as conn:
         async with conn.cursor() as cur:
             await cur.execute(
-                "INSERT INTO t_chat_log (session_id, user_input, model_response,audio_url,duration,create_time) VALUES (%s, %s, %s, %s, %s,NOW())",
-                (session_id, prompt, result, audio_url, duration)
+                "INSERT INTO t_chat_log (person_id, user_input, model_response,audio_url,duration,create_time) VALUES (%s, %s, %s, %s, %s,NOW())",
+                (person_id, prompt, result, audio_url, duration)
             )
             await conn.commit()
 
@@ -46,11 +48,11 @@ async def truncate_chat_log(mysql_pool):
 from aiomysql import DictCursor
 
 # 分页查询聊天记录
-async def get_chat_log_by_session(mysql_pool, session_id, page=1, page_size=10):
+async def get_chat_log_by_session(mysql_pool, person_id, page=1, page_size=10):
     """
-    根据 session_id 查询聊天记录，并按 id 降序分页
+    根据 person_id 查询聊天记录，并按 id 降序分页
     :param mysql_pool: MySQL 连接池
-    :param session_id: 用户会话 ID
+    :param person_id: 用户会话 ID
     :param page: 当前页码（默认值为 1，但会动态计算为最后一页）
     :param page_size: 每页记录数
     :return: 分页数据
@@ -62,8 +64,8 @@ async def get_chat_log_by_session(mysql_pool, session_id, page=1, page_size=10):
         async with conn.cursor(DictCursor) as cur:  # 使用 DictCursor
             # 查询总记录数
             await cur.execute(
-                "SELECT COUNT(*) FROM t_chat_log WHERE session_id = %s",
-                (session_id,)
+                "SELECT COUNT(*) FROM t_chat_log WHERE person_id = %s",
+                (person_id,)
             )
             total = (await cur.fetchone())['COUNT(*)']
 
@@ -75,9 +77,9 @@ async def get_chat_log_by_session(mysql_pool, session_id, page=1, page_size=10):
 
             # 查询分页数据，按 id 降序排列
             await cur.execute(
-                "SELECT id, session_id, user_input, model_response, audio_url, duration, create_time "
-                "FROM t_chat_log WHERE session_id = %s ORDER BY id DESC LIMIT %s OFFSET %s",
-                (session_id, page_size, offset)
+                "SELECT id, person_id, user_input, model_response, audio_url, duration, create_time "
+                "FROM t_chat_log WHERE person_id = %s ORDER BY id DESC LIMIT %s OFFSET %s",
+                (person_id, page_size, offset)
             )
             records = await cur.fetchall()
 
@@ -88,7 +90,7 @@ async def get_chat_log_by_session(mysql_pool, session_id, page=1, page_size=10):
             result = [
                 {
                     "id": record['id'],
-                    "session_id": record['session_id'],
+                    "person_id": record['person_id'],
                     "user_input": record['user_input'],
                     "model_response": record['model_response'],
                     "audio_url": record['audio_url'],
@@ -108,7 +110,7 @@ async def get_chat_log_by_session(mysql_pool, session_id, page=1, page_size=10):
 
 
 # 获取指定会话的最后一条记录的 id
-async def get_last_chat_log_id(mysql_pool, session_id):
+async def get_last_chat_log_id(mysql_pool, person_id):
     """
     获取指定会话的最后一条记录的 id
     :param mysql_pool: MySQL 连接池
@@ -118,19 +120,19 @@ async def get_last_chat_log_id(mysql_pool, session_id):
     async with mysql_pool.acquire() as conn:
         async with conn.cursor() as cur:
             await cur.execute(
-                "SELECT id FROM t_chat_log WHERE session_id = %s ORDER BY id DESC LIMIT 1",
-                (session_id,)
+                "SELECT id FROM t_chat_log WHERE person_id = %s ORDER BY id DESC LIMIT 1",
+                (person_id,)
             )
             result = await cur.fetchone()
             return result[0] if result else None
 
 
 # 更新为危险的记录
-async def update_risk(mysql_pool, session_id, risk_memo):
+async def update_risk(mysql_pool, person_id, risk_memo):
     async with mysql_pool.acquire() as conn:
         async with conn.cursor() as cur:
             # 1. 获取此人员的最后一条记录 id
-            last_id = await get_last_chat_log_id(mysql_pool, session_id)
+            last_id = await get_last_chat_log_id(mysql_pool, person_id)
 
             if last_id:
                 # 2. 更新 risk_flag 和 risk_memo
@@ -139,9 +141,9 @@ async def update_risk(mysql_pool, session_id, risk_memo):
                     (risk_memo.replace('\n', '').replace("NO", ""), last_id)
                 )
                 await conn.commit()
-                logger.info(f"已更新 session_id={session_id} 的最后一条记录 (id={last_id}) 的 risk_flag 和 risk_memo。")
+                logger.info(f"已更新 person_id={person_id} 的最后一条记录 (id={last_id}) 的 risk_flag 和 risk_memo。")
             else:
-                logger.warning(f"未找到 session_id={session_id} 的记录。")
+                logger.warning(f"未找到 person_id={person_id} 的记录。")
 
 
 # 查询有风险的聊天记录
@@ -166,7 +168,7 @@ async def get_risk_chat_log_page(mysql_pool, risk_flag, page=1, page_size=10):
 
             # 查询分页数据
             query = (
-                "SELECT id, session_id, user_input, model_response, audio_url, duration, create_time, risk_memo "
+                "SELECT id, person_id, user_input, model_response, audio_url, duration, create_time, risk_memo "
                 "FROM t_chat_log WHERE risk_flag = %s ORDER BY id DESC LIMIT %s OFFSET %s"
             )
             params = (risk_flag, page_size, offset)
@@ -180,7 +182,7 @@ async def get_risk_chat_log_page(mysql_pool, risk_flag, page=1, page_size=10):
             result = [
                 {
                     "id": record[0],
-                    "session_id": record[1],
+                    "person_id": record[1],
                     "user_input": record[2],
                     "model_response": record[3],
                     "audio_url": record[4],
@@ -196,4 +198,23 @@ async def get_risk_chat_log_page(mysql_pool, risk_flag, page=1, page_size=10):
                 "total": total,
                 "page": page,
                 "page_size": page_size
-            }
+            }
+# 查询用户信息
+async def get_user_by_login_name(mysql_pool, login_name: str) -> Optional[Dict]:
+    """
+    根据用户名查询用户信息
+    :param pool: MySQL 连接池
+    :param login_name: 用户名
+    :return: 用户信息（字典形式）
+    """
+    async with mysql_pool.acquire() as conn:
+        async with conn.cursor() as cursor:
+            sql = "SELECT * FROM t_base_person WHERE login_name = %s"
+            await cursor.execute(sql, (login_name,))
+            row = await cursor.fetchone()
+            if not row:
+                return None
+
+            # 将元组转换为字典
+            columns = [column[0] for column in cursor.description]
+            return dict(zip(columns, row))

AI/WxMini/alibabacloud-nls-python-sdk-dev/build/lib/nls/stream_input_tts.py

@@ -32,10 +32,10 @@ __all__ = ["NlsStreamInputTtsSynthesizer"]
 
 
 class NlsStreamInputTtsRequest:
-    def __init__(self, task_id, session_id, appkey):
+    def __init__(self, task_id, person_id, appkey):
         self.task_id = task_id
         self.appkey = appkey
-        self.session_id = session_id
+        self.person_id = person_id
 
     def getStartCMD(self, voice, format, sample_rate, volumn, speech_rate, pitch_rate, ex):
         self.voice = voice
@@ -53,7 +53,7 @@ class NlsStreamInputTtsRequest:
                 "appkey": self.appkey,
             },
             "payload": {
-                "session_id": self.session_id,
+                "session_id": self.person_id,
                 "voice": self.voice,
                 "format": self.format,
                 "sample_rate": self.sample_rate,