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import streamlit as st |
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import pdfplumber |
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import spacy |
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import openai |
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import os |
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from dotenv import load_dotenv |
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import subprocess |
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load_dotenv() |
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openai.api_key = os.getenv("OPENAI_API_KEY") |
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try: |
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nlp = spacy.load("en_core_web_sm") |
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except OSError: |
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st.warning("Downloading 'en_core_web_sm' model. Please wait...") |
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subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"]) |
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nlp = spacy.load("en_core_web_sm") |
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def extract_text_from_pdf(pdf_file): |
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"""Extracts text from an uploaded PDF resume.""" |
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text = "" |
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try: |
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with pdfplumber.open(pdf_file) as pdf: |
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for page in pdf.pages: |
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text += page.extract_text() + "\n" |
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except Exception as e: |
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st.error(f"Error extracting text from PDF: {e}") |
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return text.strip() |
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def extract_keywords(text): |
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"""Extracts important keywords from resume text using spaCy.""" |
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doc = nlp(text) |
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keywords = set() |
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for token in doc: |
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if token.pos_ in ["NOUN", "PROPN"]: |
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keywords.add(token.text.lower()) |
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return list(keywords) |
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def analyze_resume(text): |
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"""Uses OpenAI GPT to analyze resume and suggest improvements.""" |
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prompt = f""" |
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You are a professional resume analyzer. Given the following resume text, |
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provide a rating (out of 10), identify missing keywords based on general job trends, |
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and suggest improvements. |
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Resume Text: |
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{text} |
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Your response should be in this structured format: |
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- Resume Rating: (score out of 10) |
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- Missing Keywords: (comma-separated list) |
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- Suggestions for Improvement: (bullet points) |
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""" |
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response = openai.ChatCompletion.create( |
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model="gpt-4", |
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messages=[{"role": "user", "content": prompt}] |
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) |
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return response["choices"][0]["message"]["content"] |
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st.title("📝 AI-Powered Resume Analyzer") |
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st.write("Upload your resume, and AI will provide feedback to improve it!") |
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uploaded_file = st.file_uploader("Upload your Resume (PDF format)", type=["pdf"]) |
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if uploaded_file is not None: |
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with st.spinner("Processing your resume..."): |
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resume_text = extract_text_from_pdf(uploaded_file) |
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if resume_text: |
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keywords = extract_keywords(resume_text) |
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analysis_result = analyze_resume(resume_text) |
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st.subheader("🔍 Resume Analysis Report") |
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st.write(analysis_result) |
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st.subheader("📌 Extracted Keywords") |
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st.write(", ".join(keywords)) |
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st.success("✅ Resume analyzed successfully!") |
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else: |
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st.error("Could not extract text from the PDF. Please try another file.") |
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