Merge pull request #328 from RajalakshmiMadhavan/resume_job_match

Added new demo: Resume & Job matcher

advanced_llm_apps/resume_job_matcher/README.md

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+# 📄 Resume & Job Matcher
+
+## 🚀 Overview
+This app allows you to upload a **Resume** and a **Job Description**, then uses an LLM to:
+- ✅ Provide a **Fit Score** (0–100%)
+- 💪 Highlight strengths in the resume
+- 📝 Suggest improvements tailored to the job
+
+A great tool for job seekers to optimize resumes for each application.
+
+---
+
+## 🛠️ Tech Stack
+- **Python**
+- **Streamlit** – for UI
+- **Ollama + LLM** (e.g., `llama3`) – for analysis
+- **PyMuPDF** – for PDF parsing
+
+---
+
+## ⚡ Setup Instructions 
+1. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+2. Install Ollama and run a model (e.g. llama3): `ollama run llama3`
+3. Start the app: `streamlit run app.py`

advanced_llm_apps/resume_job_matcher/app.py

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+import streamlit as st
+import requests
+import fitz  # PyMuPDF for PDF parsing
+
+st.set_page_config(page_title="📄 Resume & Job Matcher", layout="centered")
+
+st.title("📄 Resume & Job Matcher")
+
+st.sidebar.info("""
+This app uses a local LLM via **Ollama**.
+1. Install Ollama: https://ollama.ai
+2. Run a model (e.g., `ollama run llama3`).
+3. Upload a Resume + Job Description to get a fit score and suggestions.
+""")
+
+# Helper: Extract text from PDF
+def extract_pdf_text(file):
+    text = ""
+    with fitz.open(stream=file.read(), filetype="pdf") as doc:
+        for page in doc:
+            text += page.get_text()
+    return text
+
+# File uploaders
+resume_file = st.file_uploader("Upload Resume (PDF/TXT)", type=["pdf", "txt"])
+job_file = st.file_uploader("Upload Job Description (PDF/TXT)", type=["pdf", "txt"])
+
+if st.button("🔍 Match Resume with Job Description"):
+    if resume_file and job_file:
+        # Extract Resume text
+        if resume_file.type == "application/pdf":
+            resume_text = extract_pdf_text(resume_file)
+        else:
+            resume_text = resume_file.read().decode("utf-8")
+
+        # Extract Job text
+        if job_file.type == "application/pdf":
+            job_text = extract_pdf_text(job_file)
+        else:
+            job_text = job_file.read().decode("utf-8")
+
+        # Prompt
+        prompt = f"""
+        You are an AI career assistant.
+        
+        Resume:
+        {resume_text}
+
+        Job Description:
+        {job_text}
+
+        Please analyze and return:
+        1. A **Fit Score** (0-100%) of how well this resume matches the job.
+        2. Key strengths (resume areas that align well).
+        3. Specific recommendations to improve the resume to better fit the job.
+        Format neatly in Markdown.
+        """
+
+        try:
+            with st.spinner("⏳ Analyzing Resume vs Job Description..."):
+                response = requests.post(
+                    "http://localhost:11434/api/generate",
+                    json={"model": "llama3", "prompt": prompt, "stream": False},
+                )
+                data = response.json()
+                output = data.get("response", "⚠️ No response from model.")
+
+            # Show Results
+            st.subheader("📌 Match Analysis")
+            st.markdown(output)
+
+            # Save in session for download
+            st.session_state["resume_match"] = output
+
+        except Exception as e:
+            st.error(f"An error occurred: {str(e)}")
+
+    else:
+        st.warning("⚠️ Please upload both Resume and Job Description.")
+
+# Download button
+if "resume_match" in st.session_state:
+    st.download_button(
+        "💾 Download Match Report",
+        st.session_state["resume_match"],
+        file_name="resume_match_report.md",
+        mime="text/markdown"
+    )

advanced_llm_apps/resume_job_matcher/requirements.txt

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+streamlit
+requests
+pymupdf