133 lines
5.8 KiB
Python
133 lines
5.8 KiB
Python
from fastapi import APIRouter, Request, HTTPException
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import json
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import logging
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from Util import OcrUtil, LlmUtil
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from sse_starlette.sse import EventSourceResponse
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# 创建路由路由器
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router = APIRouter(prefix="/api", tags=["作文批阅"])
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# 配置日志
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logger = logging.getLogger(__name__)
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@router.post("/zuowen_chinese")
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async def zuowen_chinese(request: Request):
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"""
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批阅中文作文接口
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参数:
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grade_name: 年级名称 (如: 三年级, 四年级)
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image_url: 已上传的作文图片URL
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返回:
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SSE流式响应，包含作文识别和批阅结果
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"""
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try:
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# 获取请求参数
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try:
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data = await request.json()
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grade_name = data.get("grade_name")
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image_url = data.get("image_url")
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except Exception:
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# 如果JSON解析失败，尝试从表单数据中获取
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form = await request.form()
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grade_name = form.get("grade_name")
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image_url = form.get("image_url")
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# 验证参数
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if not grade_name or not image_url:
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raise HTTPException(status_code=400, detail="缺少必要参数: grade_name 或 image_url")
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async def generate_zuowen_response():
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try:
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# 步骤1: OCR识别作文内容
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yield f"{json.dumps({'step': 'ocr', 'content': '开始识别作文内容...'}, ensure_ascii=False)}"
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content = OcrUtil.recognize_handwriting(image_url)
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yield f"{json.dumps({'step': 'ocr', 'content': content}, ensure_ascii=False)}"
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# 步骤2: 生成点评提示词
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query_text = f'我将提供一篇{grade_name}学生作文，请点评学生作文，并打分，满分30分。下面是作文内容：{content}'
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yield f"{json.dumps({'step': 'review', 'content': '开始生成作文点评...'}, ensure_ascii=False)}"
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# 步骤3: 异步调用LLM进行点评
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full_response = []
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async for chunk in LlmUtil.get_llm_response_async(query_text):
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if chunk:
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full_response.append(chunk)
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yield f"{json.dumps({'step': 'review', 'content': chunk}, ensure_ascii=False)}"
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# 发送完成信号
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yield f"{json.dumps({'step': 'review', 'content': '作文点评完成', 'done': True}, ensure_ascii=False)}"
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yield f"DONE"
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except Exception as e:
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logger.error(f"作文批阅异常: {str(e)}")
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yield f"{json.dumps({'error': f'处理异常: {str(e)}'}, ensure_ascii=False)}"
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yield f"DONE"
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# 返回SSE响应
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return EventSourceResponse(generate_zuowen_response())
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except HTTPException as e:
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raise e
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except Exception as e:
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logger.error(f"接口异常: {str(e)}")
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raise HTTPException(status_code=500, detail=f"服务器内部错误: {str(e)}")
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@router.post("/zuowen_english")
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async def zuowen_english(request: Request):
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"""
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批阅英文作文接口
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参数:
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grade_name: 年级名称 (如: Grade 3, Grade 4)
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image_url: 已上传的作文图片URL
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返回:
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SSE流式响应，包含作文识别和批阅结果
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"""
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try:
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# 获取请求参数
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try:
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data = await request.json()
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grade_name = data.get("grade_name")
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image_url = data.get("image_url")
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except Exception:
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# 如果JSON解析失败，尝试从表单数据中获取
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form = await request.form()
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grade_name = form.get("grade_name")
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image_url = form.get("image_url")
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# 验证参数
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if not grade_name or not image_url:
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raise HTTPException(status_code=400, detail="缺少必要参数: grade_name 或 image_url")
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async def generate_zuowen_response():
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try:
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# 步骤1: OCR识别作文内容
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yield f"{json.dumps({'step': 'ocr', 'content': '开始识别英文作文内容...'}, ensure_ascii=False)}"
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content = OcrUtil.recognize_handwriting(image_url)
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yield f"{json.dumps({'step': 'ocr', 'content': content}, ensure_ascii=False)}"
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# 步骤2: 生成点评提示词
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query_text = f"I will provide an English composition from a {grade_name} student. Please evaluate the composition and give a score out of 30 points. Here is the composition content: {content}"
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yield f"{json.dumps({'step': 'review', 'content': '开始生成作文点评...'}, ensure_ascii=False)}"
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# 步骤3: 异步调用LLM进行点评
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full_response = []
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async for chunk in LlmUtil.get_llm_response_async(query_text):
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if chunk:
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full_response.append(chunk)
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yield f"{json.dumps({'step': 'review', 'content': chunk}, ensure_ascii=False)}"
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# 发送完成信号
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yield f"{json.dumps({'step': 'review', 'content': '作文点评完成', 'done': True}, ensure_ascii=False)}"
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yield f"DONE"
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except Exception as e:
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logger.error(f"英文作文批阅异常: {str(e)}")
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yield f"{json.dumps({'error': f'处理异常: {str(e)}'}, ensure_ascii=False)}"
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yield f"DONE"
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# 返回SSE响应
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return EventSourceResponse(generate_zuowen_response())
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except HTTPException as e:
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raise e
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except Exception as e:
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logger.error(f"英文作文批阅接口异常: {str(e)}")
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raise HTTPException(status_code=500, detail=f"服务器内部错误: {str(e)}") |