Create app.py

app.py

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+import gradio as gr
+import fitz
+import joblib
+import numpy as np
+import openai
+import pandas as pd
+from fpdf import FPDF
+import tempfile
+import os
+
+openai.api_key=os.getenv("OPENAI_API_KEY")
+
+linkedin_rag_df=pd.read_csv("final_linkedin_post_ideas.csv")
+
+
+# Load model + vectorizer
+model = joblib.load("xgb_resume_model.pkl")
+vectorizer = joblib.load("tfidf_vectorizer.pkl")
+
+# Thresholds from earlier training
+q_low = 0.5166355336146575
+q_high = 2.831921823997124
+
+
+# Weighted scoring dict (add yours here)
+weighted_keywords = {
+    # 🔹 Advanced AI / Technical
+    'llm': 3.5, 'langchain': 3.5, 'rag': 3.5, 'rag pipeline': 3.5,
+    'vector db': 3.5, 'weaviate': 3, 'chromadb': 3, 'pinecone': 3,
+    'agent': 3, 'langchain agents': 3.5, 'autonomous agent': 3,
+    'fine-tuning': 3, 'embedding': 3, 'semantic search': 3,
+    'transformers': 3, 'huggingface': 3, 'openai': 3,
+    'streamlit': 2.5, 'flask': 2.5, 'gradio': 2.5,
+    'pytorch': 2.5, 'tensorflow': 2.5,
+    'sql': 2, 'power bi': 2, 'pandas': 2, 'numpy': 2,
+    'data analysis': 2,
+
+    # 🔸 Business / Management
+    'project management': 3.5, 'agile': 3, 'stakeholder': 2.5,
+    'scrum': 3, 'planning': 2, 'budgeting': 2,
+    'strategic partnerships': 3, 'gtm': 2.5, 'account planning': 2.5,
+    'market share': 2.5, 'revenue growth': 3, 'client relationships': 2.5,
+
+    # 🟢 Sales / CRM
+    'crm': 3, 'channel sales': 3, 'business development': 3,
+    'partner engagement': 3, 'sales forecasting': 2.5,
+    'campaign': 2.5, 'salesforce': 2.5, 'leads': 2, 'market research': 2.5,
+    'negotiation': 2, 'presentation': 2,
+
+    # 🟠 Education / Teaching
+    'curriculum': 3, 'lesson planning': 2.5, 'teaching': 3,
+    'student engagement': 2.5, 'learning outcomes': 2.5, 'training': 2.5,
+    'academic institutions': 2.5, 'ministry of education': 3,
+    'educational partnerships': 2.5, 'demo': 2, 'workshop': 2,
+
+    # 🔵 HR / Support
+    'recruitment': 3, 'employee engagement': 2.5, 'onboarding': 2.5,
+    'conflict resolution': 2, 'policy': 2, 'human resources': 3,
+
+    # 🔴 Security / Law Enforcement
+    'security guard': 3, 'loss prevention': 3, 'cctv': 2.5, 'access control': 2.5,
+    'conflict de-escalation': 2, 'law enforcement': 2.5, 'threat assessment': 2,
+    'certified protection': 3, 'crisis intervention': 2, 'surveillance': 2
+}
+
+# Score function
+def weighted_score(text):
+    text = text.lower()
+    return sum(weight for kw, weight in weighted_keywords.items() if kw in text)
+
+# GPT key
+openai.api_key = userdata.get('openai')
+
+# GPT Job Role Prediction
+roles = ["AI Engineer", "Data Scientist", "Project Manager", "Sales Executive", "Teacher", "HR Specialist", "Security Officer"]
+
+def gpt_predict_role(resume_text):
+    prompt = f"""
+You are a job role classification expert. You will be given a resume summary and skills.
+
+From the list below, identify the **single most appropriate job role** this candidate fits into.
+Do not guess or create new titles. Choose **only from the list**.
+
+Roles:
+{', '.join(roles)}
+
+Resume:
+{resume_text}
+
+Answer only with one of the roles from the list.
+"""
+
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# GPT Resume Feedback
+def gpt_resume_feedback(resume_text):
+    prompt = f"""
+You are an expert resume reviewer.
+
+Analyze the resume text below and provide **structured, clear, and reader-friendly** markdown feedback under these sections:
+
+## 🔧 Resume Improvement Suggestions
+
+**Clarity & Formatting**
+- (Short bullet points)
+
+**Missing Sections**
+- (Mention if Skills, Certifications, Projects, etc. are missing)
+
+**Projects**
+- (How to describe them better or where to move them)
+
+---
+
+## 🧠 Missing Keywords
+List any specific tools, technologies, or keywords that are missing for the predicted role.
+
+---
+
+## 🚀 Quick Wins
+
+**Certifications**
+- Recommend top 2 certifications to improve resume strength
+
+**Free Courses**
+- Suggest 1-2 free courses from platforms like Coursera, edX, or YouTube
+
+**Small Edits**
+- Easy improvements: better formatting, quantifiable achievements, etc.
+
+Be professional, clean, encouraging and use proper markdown formatting:
+- Use **bold** for subheadings
+- Use `-` for bullet points
+- If suggesting any certifications or courses, format them as **clickable links** using markdown like:
+  `[Course Title](https://example.com)`
+
+
+Resume:
+{resume_text}
+"""
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.3
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# Main app logic
+def process_resume(file):
+    doc = fitz.open(file.name)
+    resume_text = " ".join([page.get_text() for page in doc]).strip()
+
+    # ML prediction
+    X_input = vectorizer.transform([resume_text])
+    predicted_strength = model.predict(X_input)[0]
+
+    # Hybrid logic
+    resume_score = weighted_score(resume_text)
+    normalized_score = resume_score / np.log(len(resume_text.split()) + 1)
+
+    if predicted_strength == 'Average' and normalized_score >= q_high:
+        predicted_strength = 'Strong'
+    elif predicted_strength == 'Average' and normalized_score < q_low:
+        predicted_strength = 'Weak'
+
+    # GPT feedback + role
+    role = gpt_predict_role(resume_text)
+    tips = gpt_resume_feedback(resume_text)
+
+    return predicted_strength, role, tips
+
+#Linkedin Enhancement
+def generate_linkedin_feedback(about_text, file, role):
+    try:
+        doc = fitz.open(file.name)
+        resume_text = " ".join([page.get_text() for page in doc]).strip()
+    except:
+        resume_text = ""
+
+    # Get RAG tips
+    # Check if the role exists in the dataframe before accessing .values
+    if role in linkedin_rag_df['role'].values:
+        rag_tip = linkedin_rag_df[linkedin_rag_df['role'] == role]['tips'].values
+        rag_tip_text = rag_tip[0] if len(rag_tip) > 0 else ""
+    else:
+        rag_tip_text = "" # Provide a default or empty tip if role not found
+
+
+    prompt = f"""
+You are a career branding expert helping people improve their LinkedIn.
+
+Based on the resume and predicted role, generate structured LinkedIn content guidance.
+
+1. 🔧 **Improve "About Me"**
+
+If About Me is provided: suggest improvements.
+If no About Me is given, generate a new one in a confident, first-person tone — as if the user is speaking directly to their network without mentioning that nothing was provided. Avoid formal third-person voice. Use warm, natural language suitable for LinkedIn.
+
+
+2. ✍ **Suggest 3 LinkedIn post ideas**
+Inspire posts relevant to their role. Include tips from this RAG input:\n{rag_tip_text}
+
+3. 🔖 **Offer engagement tips**
+How to grow visibility (e.g., comment, hashtag use, follow-up posts)
+
+Format your reply with markdown bullets and emojis. Be concise and encouraging.
+
+Resume: {resume_text}
+About Section: {about_text}
+"""
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.5
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+#Job Match
+def match_resume_with_jd(resume_file, jd_text):
+    try:
+        doc = fitz.open(resume_file.name)
+        resume_text = " ".join([page.get_text() for page in doc]).strip()
+    except:
+        return "❌ Unable to read resume."
+
+    prompt = f"""
+You are a helpful and ethical career assistant.
+
+Compare the candidate's resume and the job description below. Do these 3 things:
+
+1. **Match Score**: Estimate how well the resume matches the JD (0–100%) with clear reasoning.
+
+2. **Missing Keywords**: Identify only the important keywords or skills that are *actually not found* in the resume.
+
+3. **Suggestions to Improve**: Based ONLY on the content present in the resume, suggest realistic ways the candidate can:
+- Rephrase existing experience to better match the job
+- Emphasize transferrable skills (like mentoring, public speaking, teamwork)
+- Avoid fabricating roles or experiences not present
+
+Never invent teaching experience, tools, or certifications that are not mentioned.
+
+Resume:
+{resume_text}
+Job Description:
+{jd_text}
+
+Respond in markdown format with bold section headings.
+"""
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.3
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"❌ GPT Error: {str(e)}"
+
+# Job Explorer
+def generate_job_explorer_output(resume_file):
+    import fitz
+    from urllib.parse import quote
+
+    # Step 1: Extract text from PDF
+    try:
+        doc = fitz.open(resume_file.name)
+        resume_text = " ".join([page.get_text() for page in doc]).strip()
+    except:
+        return "❌ Unable to read resume. Please upload a valid PDF."
+
+    # Step 2: Use GPT to detect experience level + suggest roles
+    prompt = f"""
+You are an AI career coach.
+
+Read the resume below and do the following:
+1. Predict the user's experience level: Entry / Mid / Senior
+   - Consider total years of work **and** how recent their last full-time job was.
+   - If they had a long break or are doing a training/residency now, treat them as Entry-Level.
+2. Suggest 3–4 job roles the candidate is likely to be a good fit for (avoid duplicates)
+
+Respond in this markdown format:
+**Experience Level**: Entry
+
+**Suggested Roles**:
+- Data Analyst
+- Junior BI Developer
+- Reporting Analyst
+
+Resume:
+{resume_text}
+"""
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.5
+        )
+        result = response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"❌ Error from GPT: {str(e)}"
+
+    # Step 3: Generate Indeed links based on experience level
+    final_output = result + "\n\n**🔗 Explore Jobs on Indeed UAE:**\n"
+
+    # Extract experience level
+    experience_level = "entry"
+    for line in result.splitlines():
+        if "Experience Level" in line:
+            experience_level = line.split(":")[-1].strip().lower()
+
+    # Experience level filters for Indeed
+    experience_filters = {
+        "entry": "&explvl=entry_level",
+        "mid": "&explvl=mid_level",
+        "senior": "&explvl=senior_level"
+    }
+    exp_filter = experience_filters.get(experience_level, "")
+
+    # Create links for each suggested role
+    for line in result.splitlines():
+        if "- " in line and "Suggested Roles" not in line:
+            role = line.strip("- ").strip()
+            query = quote(role)
+            indeed_url = f"https://ae.indeed.com/jobs?q={query}&l=United+Arab+Emirates{exp_filter}"
+            final_output += f"- [{role} Jobs in UAE]({indeed_url})\n"
+
+    # Final tip
+    final_output += "\n💡 _Tip: You can also search the same job titles on LinkedIn or Bayt for more options._"
+
+    return final_output
+
+# 🧠 Conversational career agent
+def chat_with_career_agent(history, user_message, resume_file):
+    try:
+        doc = fitz.open(resume_file.name)
+        resume_text = " ".join([page.get_text() for page in doc]).strip()
+    except:
+        return history + [{"role": "user", "content": user_message},
+                          {"role": "assistant", "content": "❌ Unable to read resume."}]
+
+    prompt = f"""
+You are a warm and friendly AI career coach.
+
+ONLY answer questions related to:
+- Resume review, improvement
+- LinkedIn profile enhancement
+- Role suitability or job matching
+- Career growth plans (e.g., certifications, skill roadmaps)
+- Interview tips, career clarity
+
+Ignore personal, unrelated questions (like recipes, coding help, travel).
+
+Resume:
+{resume_text}
+
+User asked:
+{user_message}
+
+If the query is valid (even if slightly unclear), ask a clarifying question and help warmly.
+If it's off-topic (not career/job related), reply:
+"I'm here to support your career and resume journey only 😊"
+"""
+
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[
+                {"role": "system", "content": "You are a career guidance assistant."},
+                {"role": "user", "content": prompt}
+            ],
+            temperature=0.5
+        )
+        reply = response.choices[0].message.content.strip()
+    except Exception as e:
+        reply = f"❌ Error: {str(e)}"
+
+    return history + [[user_message, reply]]
+
+#Download PDF
+#for main tab
+def rewrite_resume_main(resume_file, strength, role, tips):
+    resume_text = extract_resume_text(resume_file)
+
+    prompt = f"""
+You are a professional resume rewriter. Rewrite the following resume to improve its strength, based on:
+
+- Strength: {strength}
+- Predicted Role: {role}
+- AI Feedback: {tips}
+
+Generate a clean, ATS-friendly version with proper formatting in sections like:
+
+1. **Summary**
+2. **Skills**
+3. **Experience**
+4. **Projects**
+5. **Certifications**
+
+Keep the language warm, confident, and professional. Do NOT mention the words 'suggestion' or 'AI'.
+
+Resume to rewrite:
+{resume_text}
+"""
+
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.4
+        )
+        rewritten = response.choices[0].message.content.strip()
+    except Exception as e:
+        return None, f"❌ GPT Error: {str(e)}"
+
+    pdf_path = generate_pdf(rewritten)
+    print("✅ PDF saved at:", pdf_path)
+    return pdf_path, "✅ Resume rewritten successfully!"
+
+#for jdmatch tab
+def rewrite_resume_for_jd(resume_file, jd_text):
+    resume_text = extract_resume_text(resume_file)
+
+    prompt = f"""
+You are an AI resume enhancer.
+
+Rewrite this resume to best match the following job description (JD) while being honest and using only real information found in the resume.
+
+Resume:
+{resume_text}
+
+JD:
+{jd_text}
+
+Structure it with proper headings: Summary, Skills, Experience, Projects, and Certifications.
+
+Do not add false experiences. Use persuasive language to reframe existing experience in a way that aligns with the JD.
+"""
+
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.4
+        )
+        rewritten = response.choices[0].message.content.strip()
+    except Exception as e:
+        return None, f"❌ GPT Error: {str(e)}"
+
+    pdf_path = generate_pdf(rewritten)
+    return pdf_path, "✅ Resume rewritten for JD match!"
+
+def generate_pdf(resume_text):
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.set_font("Arial", size=12)
+
+    for line in resume_text.split("\n"):
+        if line.strip() == "":
+            pdf.ln()
+        else:
+           pdf.multi_cell(0, 10, line.encode("latin-1", "replace").decode("latin-1"))
+
+    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
+    pdf.output(temp_file.name)
+    return temp_file.name
+
+
+def clear_fields():
+    return None, "", "","","","",None,"",""
+
+def show_loading_linkedin():
+    return "⏳ Generating your LinkedIn suggestions... Please wait."
+
+def hide_loading_linkedin():
+    return ""
+
+def show_main_loading():
+    return "⏳ Preparing your resume... Please wait."
+
+def show_main_file(file_path):
+    return gr.update(value=file_path, visible=True)
+
+def hide_main_loading():
+    return ""  # Clears the status message
+
+def show_loading_jd():
+    return "⏳ Matching in progress..."
+
+def hide_loading_jd():
+    return ""
+
+def show_loading():
+    return "⏳ Looking for jobs based on your resume…"
+
+def hide_loading():
+    return " "  # Clears the status message
+
+
+def clear_jd_fields():
+    # Clears the JD Tab fields
+    return None, "", ""," ",None  # Corresponds to shared_resume_file, jd_text_input, jd_output
+
+def clear_explore_fields():
+    # Clears the Job Explorer Tab fields
+     return None, "" , " "# Corresponds to shared_resume_file, explore_output
+
+def extract_resume_text(resume_file):
+    try:
+        doc = fitz.open(resume_file.name)
+        return " ".join([page.get_text() for page in doc]).strip()
+    except:
+        return ""
+def show_chat_ui():
+    return gr.update(visible=True)
+
+
+with gr.Blocks(css="""
+/* ✨ Updated Clean UI */
+body {
+    background-color: #f0f4f8 !important;
+}
+
+.gradio-container {
+    font-family: 'Segoe UI', sans-serif;
+    max-width: 960px;
+    margin: auto;
+    padding: 30px;
+    background-color: #ffffff;
+    border-radius: 16px;
+    box-shadow: 0 6px 18px rgba(0,0,0,0.08);
+}
+
+h1, h2, h3 {
+    color: #2a4365;
+}
+
+.card {
+    background-color: #ffffff;
+    border: 1px solid #e2e8f0;
+    padding: 20px;
+    border-radius: 10px;
+    margin-bottom: 20px;
+    box-shadow: 0 2px 6px rgba(0,0,0,0.05);
+}
+
+/* Upload Box Styling */
+.gr-file-upload, .gr-file, div[data-testid="file"] {
+    background-color: #f7fafc !important;
+    border: 2px dashed #90cdf4 !important;
+    color: #2d3748 !important;
+    font-size: 14px !important;
+    border-radius: 10px !important;
+    min-height: 30px !important;
+}
+.gr-file .file-preview {
+    max-height: 18px !important;
+    font-size: 12px !important;
+    padding: 2px !important;
+}
+
+button {
+    background-color: #3182ce !important;
+    color: white !important;
+    font-weight: bold;
+    border-radius: 8px !important;
+    padding: 10px 16px !important;
+}
+button.secondary {
+    background-color: #e2e8f0 !important;
+    color: #2d3748 !important;
+}
+.gr-button {
+    width: 100% !important;
+    margin-top: 8px;
+}
+
+/* ✅ Compact Upload Size */
+.compact-upload {
+    min-height: 80px !important;
+    height: 80px !important;
+    padding: 8px !important;
+}
+
+/* ✅ Markdown Enhancements */
+.gr-markdown {
+    font-size: 16px;
+    color: #1a202c;
+}
+
+/* ✅ Labels */
+label {
+    font-weight: 500;
+    color: #374151;
+}
+
+/* ✅ Resume Output Boxes */
+textarea[aria-label*="Resume Strength"], textarea[aria-label*="Predicted Job Role"] {
+    background-color: #fff !important;
+    border: 1px solid #ddd !important;
+    color: #111;
+}
+""") as demo:
+
+    gr.Markdown("## 🚀 <b>PATHFORGE AI</b>")
+    gr.Markdown("Empower your job search with AI resume analysis, job fit, and LinkedIn guidance.")
+
+    with gr.Tabs():
+        with gr.Tab("🏠 Main Resume Coach"):
+            with gr.Column(elem_classes="card"):
+                resume_file = gr.File(label="📄 Upload Resume", file_types=[".pdf"])
+                with gr.Row():
+                    submit_btn = gr.Button("🔍 Analyze Resume", interactive=False)
+                    clear_btn = gr.Button("🗑️ Clear", variant="secondary")
+                    download_main_btn = gr.Button("📥 Download AI Resume")
+                status_text_main = gr.Markdown(" ")
+
+            # ✅ Define missing output file
+            main_pdf_file = gr.File(visible=False, elem_classes="compact-upload")
+
+            with gr.Accordion("💪 Resume Insights", open=True):
+                with gr.Row():
+                    with gr.Column(): # Added Column
+                        strength_output = gr.Textbox(label="Resume Strength", interactive=False)
+                    with gr.Column(): # Added Column
+                        role_output = gr.Textbox(label="Predicted Role", interactive=False)
+
+
+            with gr.Accordion("🛠️ AI Feedback", open=False):
+                tips_output = gr.Markdown("")
+
+            with gr.Column(elem_classes="card"):
+                about_input = gr.Textbox(label="LinkedIn About (Optional)", lines=3)
+                linkedin_btn = gr.Button("✨ Enhance LinkedIn")
+                linkedin_output = gr.Markdown("")
+                status_text = gr.Markdown(" ")
+
+        with gr.Tab("🎯 JD Match + Explorer"):
+            with gr.Column(elem_classes="card"):
+                shared_resume_file = gr.File(label="📄 Upload Resume Again", file_types=[".pdf"])
+
+            with gr.Column(elem_classes="card"):
+                jd_text_input = gr.Textbox(label="📋 Paste JD")
+                with gr.Row():
+                    jd_match_btn = gr.Button("🔍 Match with JD")
+                    jd_clear_btn = gr.Button("🧹 Clear", variant="secondary")
+                    download_jd_btn = gr.Button("📥 JD Resume")
+                jd_status = gr.Markdown(" ")
+                jd_output = gr.Markdown("")
+
+            # ✅ Define missing output file
+            jd_pdf_file = gr.File(visible=True, elem_classes="compact-upload")
+
+            with gr.Column(elem_classes="card"):
+                explore_btn = gr.Button("🌍 Suggest Jobs")
+                explore_status = gr.Markdown(" ")
+                explore_output = gr.Markdown("")
+
+            with gr.Column(elem_classes="card"):
+                career_chat_btn = gr.Button("💬 Talk to Career Coach")
+                chat_section = gr.Column(visible=False)
+                with chat_section:
+                    career_chatbot = gr.Chatbot()
+                    text_input = gr.Textbox(label="💬 Ask your question")
+                    send_btn = gr.Button("🧠 Send")
+
+
+    # Define button clicks *inside* the gr.Blocks context
+    submit_btn.click(
+        fn=process_resume,
+        inputs=resume_file,
+        outputs=[strength_output, role_output, tips_output]
+    )
+    # Dynamically enable button + add green border on upload
+    resume_file.change(
+        lambda file: (
+          gr.update(interactive=True), # submit_btn
+          gr.update(interactive=True), # download_main_btn
+          gr.update(visible=True if file else False), # main_pdf_file
+          gr.update(elem_classes="compact-upload uploaded") if file else gr.update(elem_classes="compact-upload") # resume_file css
+       ),
+       inputs=[resume_file],
+       outputs=[submit_btn, download_main_btn, main_pdf_file, resume_file]
+  )
+
+
+    clear_btn.click(
+        fn=clear_fields,
+        inputs=[],
+        outputs=[resume_file, strength_output, role_output, tips_output, about_input, linkedin_output,main_pdf_file, status_text_main, status_text]
+    )
+
+    linkedin_btn.click(
+        fn=show_loading_linkedin,
+        inputs=[],
+        outputs=[status_text]
+    ).then(
+        fn=generate_linkedin_feedback,
+        inputs=[about_input, resume_file, role_output], # Use resume_file from Tab 1
+        outputs=[linkedin_output]
+    ).then(
+        fn=hide_loading_linkedin,
+        inputs=[],
+        outputs=[status_text]
+    )
+
+    def rewrite_main_flow(resume_file, strength, role, tips):
+         path, msg = rewrite_resume_main(resume_file, strength, role, tips)
+         print("✅ PDF Path:", path)
+         if path:
+          return gr.update(value=path, visible=True, interactive=True), msg
+         else:
+          return gr.update(visible=False), msg  # Handle error case
+
+    download_main_btn.click(
+        fn=show_main_loading,
+        inputs=[],
+        outputs=[status_text_main]
+    ).then(
+       fn=rewrite_main_flow,
+       inputs=[resume_file, strength_output, role_output, tips_output],
+       outputs=[main_pdf_file, status_text_main]
+    ).then(
+       fn=hide_main_loading,
+       inputs=[],
+       outputs=[status_text_main]
+    )
+
+
+
+    # JD Match Clicks
+    jd_match_btn.click(
+        fn=show_loading_jd,
+        inputs=[],
+        outputs=[jd_status] # Update JD status
+    ).then(
+        fn=match_resume_with_jd,
+        inputs=[shared_resume_file, jd_text_input], # Use shared_resume_file from Tab 2
+        outputs=[jd_output]
+    ).then(
+        fn=hide_loading_jd,  # hide status
+        inputs=[],
+        outputs=[jd_status] # Update JD status
+    )
+    jd_clear_btn.click(
+       fn=clear_jd_fields,
+       inputs=[],
+       outputs=[shared_resume_file, jd_text_input, jd_output, jd_status, jd_pdf_file]
+   )
+
+
+
+    # Processing flow
+    explore_btn.click(
+     fn=show_loading,
+     inputs=[],
+     outputs=[explore_status]
+   ).then(
+      fn=generate_job_explorer_output,
+      inputs=[shared_resume_file],
+      outputs=[explore_output]
+   ).then(
+      fn=hide_loading,
+      inputs=[],
+      outputs=[explore_status]
+   )
+    # Added clear_explore_btn click event
+    clear_explore_btn.click(
+      fn=clear_explore_fields,
+      inputs=[],
+      outputs=[shared_resume_file, explore_output, explore_status]
+   )
+    def rewrite_jd_flow(resume_file, jd_text_input):
+       path, msg = rewrite_resume_for_jd(resume_file, jd_text_input)
+       print("✅ JD PDF Path:", path)
+       return gr.update(value=path, visible=True, interactive=True), msg
+
+    download_jd_btn.click(
+      fn=lambda: "⏳ Preparing tailored resume for JD... please wait.",
+      inputs=[],
+      outputs=[jd_status]
+   ).then(
+      fn=rewrite_jd_flow,
+      inputs=[shared_resume_file, jd_text_input],
+      outputs=[jd_pdf_file, jd_status]
+   ).then(
+      fn=lambda: "",  # hide status
+      inputs=[],
+      outputs=[jd_status]
+   )
+
+    career_chat_btn.click(
+     fn=show_chat_ui,
+     inputs=[],
+     outputs=[chat_section]
+   )
+    send_btn.click(
+      fn=chat_with_career_agent,
+      inputs=[career_chatbot, text_input, shared_resume_file],  # shared_resume_file from JD tab
+      outputs=career_chatbot
+   ).then(
+      fn=lambda: "",  # clear the text input
+      inputs=[],
+      outputs=[text_input]
+   )
+
+
+
+
+    gr.Markdown(
+        "<p style='text-align:center; font-size: 14px;'>✨ Built with 💻 ML + GPT | Made for the AI Challenge By Kiruthika Ramalingam</p>")
+
+demo.launch()