Spaces:
Sleeping
Sleeping
Create resume_parser.py
Browse files
backend/agents/resume_parser.py
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import PyPDF2
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import docx
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import io
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def parse_pdf(file_stream):
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"""
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Extracts text from a PDF file stream.
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Args:
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file_stream: A file-like object (e.g., from st.file_uploader).
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Returns:
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str: The extracted text from the PDF.
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"""
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text = ""
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try:
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reader = PyPDF2.PdfReader(file_stream)
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for page in reader.pages:
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text += page.extract_text() or ""
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except Exception as e:
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print(f"Error reading PDF: {e}")
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raise ValueError("Could not parse the PDF file. It might be corrupted or image-based.")
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return text
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def parse_docx(file_stream):
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"""
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Extracts text from a DOCX file stream.
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Args:
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file_stream: A file-like object.
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Returns:
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str: The extracted text from the DOCX file.
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"""
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text = ""
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try:
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doc = docx.Document(file_stream)
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for para in doc.paragraphs:
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text += para.text + "\n"
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except Exception as e:
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print(f"Error reading DOCX: {e}")
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raise ValueError("Could not parse the DOCX file.")
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return text
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def parse_resume(uploaded_file):
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"""
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Parses an uploaded resume file (PDF or DOCX) and returns its text content.
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Args:
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uploaded_file: The file object from Streamlit's file_uploader.
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Returns:
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str: The text content of the resume.
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Raises:
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ValueError: If the file type is not supported or parsing fails.
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"""
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if uploaded_file is None:
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raise ValueError("No file uploaded.")
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file_extension = uploaded_file.name.split('.')[-1].lower()
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# We use BytesIO to handle the file in memory
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file_stream = io.BytesIO(uploaded_file.getvalue())
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if file_extension == 'pdf':
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return parse_pdf(file_stream)
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elif file_extension == 'docx':
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return parse_docx(file_stream)
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else:
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raise ValueError(f"Unsupported file type: '{file_extension}'. Please upload a PDF or DOCX file.")
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