save_load_learned

This commit is contained in:
CakeCN
2025-11-17 23:14:55 +08:00
parent 553a7724b3
commit 0fd548edcd
5 changed files with 194 additions and 151 deletions

View File

@@ -1,6 +1,8 @@
# myapp/services/course_service.py
import re
from typing import Dict, List
import requests
import json
from typing import Dict, List, Optional
from flask import current_app
from urllib.parse import urlparse
from datetime import datetime
@@ -450,10 +452,10 @@ def _default_markdowns(lesson_name: str):
## 阶段一:示例阶段
### 步骤A
请基于“步骤A”的教学目标与材料,生成指导性提示词(尽量结构化,给出评估标准和示例)。
请基于"步骤A"的教学目标与材料,生成指导性提示词(尽量结构化,给出评估标准和示例)。
### 步骤B
请基于“步骤B”的教学目标与材料,生成指导性提示词。
请基于"步骤B"的教学目标与材料,生成指导性提示词。
"""
score_prompt_md = f"""# {lesson_name}
@@ -463,8 +465,134 @@ def _default_markdowns(lesson_name: str):
## 阶段一:示例阶段
### 步骤A
对学员在“步骤A”的输出进行评分与文字反馈,分数区间 0-100并输出 JSON```{{"score": <int>, "reasons": "<string>", "advices": "<string>"}}```
对学员在"步骤A"的输出进行评分与文字反馈,分数区间 0-100并输出 JSON```{{"score": <int>, "reasons": "<string>", "advices": "<string>"}}```
### 步骤B
同上,对“步骤B”输出进行评分与反馈。
同上,对"步骤B"输出进行评分与反馈。
"""
return lesson_md, prompt_md, score_prompt_md
def save_learning_progress(user_uuid: str, chatmanager, user_id: str) -> bool:
"""
保存用户学习进度到MongoDB
参数:
- user_uuid: 用户UUID
- chatmanager: ChatManager实例包含学习进度数据
- user_id: 用户ID
返回:
- bool: 保存是否成功
"""
try:
# 获取MongoDB连接
mongo = current_app.extensions["mongo"]
# 获取MultiAgents框架中的对话列表
dialog_list = get_multiagents_dialog_list(user_id)
# 构建学习进度数据
progress_data = {
"user_uuid": user_uuid,
"user_id": user_id,
"material_id": chatmanager.material_id,
"chapter_name": chatmanager.chapter_name,
"lesson_name": chatmanager.lesson_name,
"chapter_chain_now": chatmanager.chapter_chain_now,
"chat_historys": chatmanager.chat_historys,
"scores": chatmanager.scores,
"multiagents_dialogs": dialog_list,
"updated_at": datetime.now()
}
# 保存到MongoDB使用upsert操作如果存在则更新不存在则插入
mongo.db.learning_progress.update_one(
{
"user_uuid": user_uuid,
"material_id": chatmanager.material_id,
"chapter_name": chatmanager.chapter_name,
"lesson_name": chatmanager.lesson_name
},
{"$set": progress_data},
upsert=True
)
current_app.logger.info(f"学习进度保存成功: user_uuid={user_uuid}, lesson={chatmanager.lesson_name}")
return True
except Exception as e:
current_app.logger.error(f"保存学习进度失败: {str(e)}")
return False
def get_multiagents_dialog_list(user_id: str) -> List[Dict]:
"""
从MultiAgents框架获取用户对话列表
参数:
- user_id: 用户ID
返回:
- List[Dict]: 对话列表
"""
try:
# 从配置中获取ASE引擎URL和token
config = current_app.config
url_token = config.get("ASE_ENGINE_URL_TOKEN", "")
# 构建请求URL
base_url = config.get("ASE_ENGINE_URL", "")
api_url = f"{base_url}/api/sync/download"
# 构建请求参数
payload = {
"namespace_url": url_token, # 使用配置中的token作为namespace_url
"user_id": user_id
}
# 发送POST请求
response = requests.post(
api_url,
json=payload,
headers={"Content-Type": "application/json"},
timeout=10
)
# 检查响应
if response.status_code == 200:
return response.json()
else:
current_app.logger.error(f"获取MultiAgents对话列表失败: HTTP {response.status_code}")
return []
except Exception as e:
current_app.logger.error(f"获取MultiAgents对话列表异常: {str(e)}")
return []
def load_learning_progress(user_uuid: str, material_id: str, chapter_name: str, lesson_name: str) -> Optional[Dict]:
"""
加载用户学习进度
参数:
- user_uuid: 用户UUID
- material_id: 课程ID
- chapter_name: 章节名
- lesson_name: 课时名
返回:
- Optional[Dict]: 学习进度数据如果不存在则返回None
"""
try:
mongo = current_app.extensions["mongo"]
progress = mongo.db.learning_progress.find_one({
"user_uuid": user_uuid,
"material_id": material_id,
"chapter_name": chapter_name,
"lesson_name": lesson_name
})
if progress:
# 转换ObjectId为字符串
if "_id" in progress:
progress["_id"] = str(progress["_id"])
return progress
return None
except Exception as e:
current_app.logger.error(f"加载学习进度失败: {str(e)}")
return None