Create app.py

app.py

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+import streamlit as st
+import os
+from langchain_community.llms import HuggingFaceHub
+from PyPDF2 import PdfReader
+import docx2txt
+
+# Set Hugging Face token (Get yours from https://huggingface.co/settings/tokens)
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets["HUGGINGFACEHUB_API_TOKEN"]
+
+# Initialize Mistral 7B model
+repo_id = "mistralai/Mistral-7B-v0.1"
+llm = HuggingFaceHub(
+    repo_id=repo_id,
+    model_kwargs={"temperature": 0.5, "max_length": 4096}
+)
+
+def extract_text(uploaded_file):
+    """Extract text from PDF or DOCX files"""
+    if uploaded_file.type == "application/pdf":
+        pdf_reader = PdfReader(uploaded_file)
+        return "\n".join([page.extract_text() for page in pdf_reader.pages])
+    elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
+        return docx2txt.process(uploaded_file)
+    return ""
+
+def analyze_resume(resume_text, job_desc):
+    """Analyze resume using Mistral 7B"""
+    prompt = f"""
+    Analyze this resume against the job description below. Provide:
+    1. Top 5 missing keywords from job description
+    2. Three suggested improvements
+    3. ATS compatibility score (0-100)
+    
+    Resume:
+    {resume_text[:3000]}
+    
+    Job Description:
+    {job_desc[:2000]}
+    
+    Format output using markdown with clear sections.
+    """
+    return llm.invoke(prompt)
+
+def check_ats_compliance(text):
+    """Basic ATS formatting checks"""
+    forbidden_elements = ["table", "image", "column", "graphic"]
+    return all(element not in text.lower() for element in forbidden_elements)
+
+def generate_ats_version(text):
+    """Convert text to ATS-friendly format"""
+    return text.replace("\n", " ").strip()
+
+# Streamlit UI
+st.set_page_config(page_title="ATS Resume Optimizer", layout="wide")
+
+st.title("📄 Free ATS Resume Optimizer")
+st.markdown("Upload your resume and job description to get AI-powered optimization tips!")
+
+col1, col2 = st.columns(2)
+
+with col1:
+    uploaded_file = st.file_uploader("Upload Resume (PDF/DOCX)", type=["pdf", "docx"])
+    job_description = st.text_area("Paste Job Description", height=200)
+
+with col2:
+    if uploaded_file and job_description:
+        if st.button("Analyze and Optimize"):
+            with st.spinner("Processing with Mistral 7B..."):
+                resume_text = extract_text(uploaded_file)
+                
+                # Perform analysis
+                analysis = analyze_resume(resume_text, job_description)
+                ats_compliant = check_ats_compliance(resume_text)
+                optimized_text = generate_ats_version(resume_text)
+                
+                # Display results
+                st.subheader("Analysis Results")
+                st.markdown(analysis)
+                
+                st.subheader("ATS Compliance Check")
+                st.metric("Format Status", "Pass ✅" if ats_compliant else "Fail ❌")
+                
+                # Download optimized version
+                st.download_button(
+                    label="Download ATS-Optimized Resume",
+                    data=optimized_text,
+                    file_name="optimized_resume.txt",
+                    mime="text/plain"
+                )
+    else:
+        st.info("👈 Upload your resume and paste a job description to get started")
+
+st.markdown("---")
+st.caption("Note: This tool uses Mistral 7B AI model for analysis. Always review suggestions before submitting applications.")