dekun
e329d3398a
Add FastAPI/React app with Docker deployment, Ubuntu one-click install, and docs for junior/senior high score tracking and mistake bank. Co-authored-by: Cursor <cursoragent@cursor.com>
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
import httpx
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from app.core.config import settings
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from app.services.school_level import school_level_label
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QUESTION_PROMPT = """你是一位{stage}老师。以下是从试卷 OCR 识别出的文字，可能含有噪声。
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科目：{subject}
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请整理出清晰的题目内容（保留题号、选项、公式），只输出题目正文，不要解释。
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OCR 原文：
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{ocr_text}
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"""
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SOLUTION_PROMPT = """你是一位耐心的{stage}{subject}老师。请为以下题目给出详细解法。
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要求：步骤清晰，语言适合{stage}学生理解，指出考点和易错点。
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题目：
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{question_text}
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"""
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async def ollama_generate(prompt: str) -> str:
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url = f"{settings.OLLAMA_BASE_URL.rstrip('/')}/api/generate"
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payload = {
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"model": settings.OLLAMA_MODEL,
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"prompt": prompt,
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"stream": False,
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}
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async with httpx.AsyncClient(timeout=120.0) as client:
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response = await client.post(url, json=payload)
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response.raise_for_status()
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data = response.json()
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return (data.get("response") or "").strip()
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async def format_question(subject: str, ocr_text: str, school_level=None) -> str:
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stage = school_level_label(school_level)
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prompt = QUESTION_PROMPT.format(stage=stage, subject=subject, ocr_text=ocr_text)
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return await ollama_generate(prompt)
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async def generate_solution(subject: str, question_text: str, school_level=None) -> str:
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stage = school_level_label(school_level)
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prompt = SOLUTION_PROMPT.format(
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stage=stage, subject=subject, question_text=question_text
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)
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return await ollama_generate(prompt)
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