ln0422
96997daed0
- FastAPI backend with SQLAlchemy ORM and SQLite - AI chatbot with OpenAI-compatible LLM integration (SSE streaming) - Admin panel for content management, LLM config, token management - Anonymous access with 3-question limit, token-based access control - Recruiter intent detection with admin notification - Resume generator (JD-based, Markdown to Word export) - Chinese localized public interface Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import base64
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import io
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from fastapi import UploadFile
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async def parse_file(file: UploadFile) -> dict:
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"""Parse uploaded file and extract text content or base64 image data."""
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content = await file.read()
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filename = file.filename or ""
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ext = filename.rsplit(".", 1)[-1].lower() if "." in filename else ""
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if len(content) > 10 * 1024 * 1024:
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return {"text": "", "error": "文件大小超过10MB限制"}
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try:
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if ext == "txt":
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return {"text": _decode_text(content)}
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elif ext == "docx":
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return {"text": _parse_docx(content)}
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elif ext == "pdf":
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return {"text": _parse_pdf(content)}
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elif ext in ("png", "jpg", "jpeg", "gif", "bmp", "webp"):
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b64 = base64.b64encode(content).decode("utf-8")
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mime = f"image/{ext}" if ext != "jpg" else "image/jpeg"
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return {"text": "", "base64_image": b64, "mime_type": mime}
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else:
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return {"text": "", "error": f"不支持的文件格式: .{ext}"}
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except Exception as e:
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return {"text": "", "error": f"文件解析失败: {str(e)}"}
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def _decode_text(content: bytes) -> str:
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for encoding in ("utf-8", "gbk", "gb2312", "utf-16"):
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try:
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return content.decode(encoding)
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except (UnicodeDecodeError, LookupError):
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continue
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return content.decode("utf-8", errors="replace")
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def _parse_docx(content: bytes) -> str:
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from docx import Document
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doc = Document(io.BytesIO(content))
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paragraphs = [p.text for p in doc.paragraphs if p.text.strip()]
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return "\n".join(paragraphs)
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def _parse_pdf(content: bytes) -> str:
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from PyPDF2 import PdfReader
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reader = PdfReader(io.BytesIO(content))
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texts = []
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for page in reader.pages:
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text = page.extract_text()
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if text:
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texts.append(text)
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return "\n".join(texts)
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