Update app.py

app.py

@@ -1,9 +1,13 @@
-import gradio as gr
-from fpdf import FPDF
+from fastapi import FastAPI
+from fastapi.responses import FileResponse
 from transformers import pipeline
+from fpdf import FPDF
 import os
+import uvicorn
+
+app = FastAPI()
 
-# Load Hugging Face token (set in HF Space Settings → Variables and secrets → HF_TOKEN)
+# Hugging Face token (set this in your Space settings → Variables and secrets)
 HF_TOKEN = os.getenv("HF_TOKEN")
 
 # Load Gemma model
@@ -14,94 +18,56 @@ pipe = pipeline(
     max_new_tokens=400
 )
 
-def generate_resume_with_gemma(pipe, data):
+def generate_resume_with_gemma(data):
     prompt = f"""
     Create a professional resume based on the following details.
-    Write in clear sections with strong action verbs and professional wording.
+    Write in clear sections (Education, Internships, Projects, Skills, Extra Curricular).
 
     Personal Information:
-    - Name: {data['name']}
-    - Email: {data['email']}
-    - Phone: {data['phone']}
-    - LinkedIn: {data['linkedin']}
+    - Name: {data.get('name')}
+    - Email: {data.get('email')}
+    - Phone: {data.get('phone')}
+    - LinkedIn: {data.get('linkedin')}
 
     Education:
-    {data['education']}
+    {data.get('education')}
 
     Internships:
-    {data['internships']}
+    {data.get('internships')}
 
     Projects:
-    {data['projects']}
+    {data.get('projects')}
 
     Skills:
-    {data['skills']}
+    {data.get('skills')}
 
     Extra Curricular:
-    {data['extra']}
+    {data.get('extra')}
 
     Resume:
     """
-
     result = pipe(prompt, max_new_tokens=400, do_sample=False)
     return result[0]['generated_text']
 
-
-def generate_resume_pdf(text, template="modern"):
+def generate_resume_pdf(text):
     pdf = FPDF()
     pdf.add_page()
-
-    if template == "modern":
-        pdf.set_font("Arial", size=12)
-        for line in text.split("\n"):
-            pdf.multi_cell(0, 8, line)
-    else:  # minimal template
-        pdf.set_font("Times", size=12)
-        for line in text.split("\n"):
-            pdf.multi_cell(0, 8, line)
-
+    pdf.set_font("Arial", size=12)
+    for line in text.split("\n"):
+        pdf.multi_cell(0, 8, line)
     filename = "resume.pdf"
     pdf.output(filename)
     return filename
 
+@app.post("/generate_resume")
+async def generate_resume(data: dict):
+    # Step 1: Ask Gemma to polish resume text
+    text = generate_resume_with_gemma(data)
+    # Step 2: Generate PDF
+    pdf_file = generate_resume_pdf(text)
+    # Step 3: Return PDF file
+    return FileResponse(pdf_file, media_type="application/pdf", filename="resume.pdf")
 
-def build_resume(name, email, phone, linkedin, education, internships, projects, skills, extra, template):
-    data = {
-        "name": name,
-        "email": email,
-        "phone": phone,
-        "linkedin": linkedin,
-        "education": education,
-        "internships": internships,
-        "projects": projects,
-        "skills": skills,
-        "extra": extra
-    }
-    # Step 1: Generate polished text with Gemma
-    polished_resume = generate_resume_with_gemma(pipe, data)
-    # Step 2: Convert to PDF
-    pdf_file = generate_resume_pdf(polished_resume, template)
-    return pdf_file
-
-
-demo = gr.Interface(
-    fn=build_resume,
-    inputs=[
-        gr.Textbox(label="Full Name"),
-        gr.Textbox(label="Email"),
-        gr.Textbox(label="Phone"),
-        gr.Textbox(label="LinkedIn"),
-        gr.Textbox(label="Education (Degrees, Years, Scores)", lines=4),
-        gr.Textbox(label="Internships", lines=4),
-        gr.Textbox(label="Projects", lines=4),
-        gr.Textbox(label="Skills (comma separated)"),
-        gr.Textbox(label="Extra Curricular Activities", lines=3),
-        gr.Dropdown(choices=["modern", "minimal"], value="modern", label="Choose Resume Template")
-    ],
-    outputs=gr.File(label="Download Resume PDF"),
-    title="AI Resume Builder (Gemma + Templates)",
-    description="Fill your details → AI generates a polished resume → Download as PDF."
-)
-
+# For local debugging (not needed in HF Spaces)
 if __name__ == "__main__":
-    demo.launch()
+    uvicorn.run(app, host="0.0.0.0", port=7860)