Update app.py

app.py

@@ -1,65 +1,77 @@
-import os
 import gradio as gr
-import requests
+import google.generativeai as genai
+import os
 from dotenv import load_dotenv
 
+# Load environment variable
 load_dotenv()
+API_KEY = os.getenv("GEMINI_API_KEY")
 
-BACKEND_URL = "http://127.0.0.1:5000/api"  # Adjust if hosted elsewhere
+genai.configure(api_key=API_KEY)
+model = genai.GenerativeModel("gemini-pro")
 
+# --- AI Functions ---
 def generate_resume(name, email, phone, summary, experience, education, skills):
-    payload = {
-        "name": name,
-        "email": email,
-        "phone": phone,
-        "summary": summary,
-        "experience": experience,
-        "education": education,
-        "skills": skills
-    }
-    response = requests.post(f"{BACKEND_URL}/generate", json=payload)
-    if response.status_code == 200:
-        return response.json().get("resume", "")
-    return f"Error: {response.text}"
-
-def score_resume(resume_text, job_description):
-    payload = {
-        "resume": resume_text,
-        "job_description": job_description
-    }
-    response = requests.post(f"{BACKEND_URL}/score", json=payload)
-    if response.status_code == 200:
-        data = response.json()
-        return f"Score: {data['score']}/100\nSuggestions:\n" + "\n".join(data['suggestions'])
-    return f"Error: {response.text}"
+    prompt = f"""
+    Create a professional resume using the following details:
+
+    Name: {name}
+    Email: {email}
+    Phone: {phone}
+
+    Summary:
+    {summary}
+
+    Experience:
+    {experience}
+
+    Education:
+    {education}
+
+    Skills:
+    {skills}
+
+    Format it clearly and professionally.
+    """
+    response = model.generate_content(prompt)
+    return response.text
+
+def score_resume(resume, job_desc):
+    prompt = f"""
+    Evaluate how well the following resume matches the job description below. 
+    Return a match score out of 100 and specific, actionable suggestions to improve the resume.
+
+    Resume:
+    {resume}
+
+    Job Description:
+    {job_desc}
+    """
+    response = model.generate_content(prompt)
+    return response.text
 
 def refine_section(section_text, instruction):
-    payload = {
-        "text": section_text,
-        "instruction": instruction
-    }
-    response = requests.post(f"{BACKEND_URL}/refine_section", json=payload)
-    if response.status_code == 200:
-        return response.json().get("refined_text", "")
-    return f"Error: {response.text}"
+    prompt = f"Refine this section according to the instruction.\nInstruction: {instruction}\nText: {section_text}"
+    response = model.generate_content(prompt)
+    return response.text
 
+# --- Gradio UI ---
 with gr.Blocks() as demo:
-    gr.Markdown("## 🤖 AI Resume Builder")
+    gr.Markdown("## 🤖 AI Resume Builder using Gemini")
 
     with gr.Tab("1️⃣ Generate Resume"):
-        with gr.Row():
-            name = gr.Textbox(label="Name")
-            email = gr.Textbox(label="Email")
-            phone = gr.Textbox(label="Phone")
+        name = gr.Textbox(label="Name")
+        email = gr.Textbox(label="Email")
+        phone = gr.Textbox(label="Phone")
         summary = gr.Textbox(label="Professional Summary")
         experience = gr.Textbox(label="Experience")
         education = gr.Textbox(label="Education")
         skills = gr.Textbox(label="Skills")
         resume_output = gr.Textbox(label="Generated Resume", lines=15)
-        generate_btn = gr.Button("Generate Full Resume")
+        generate_btn = gr.Button("Generate Resume")
 
         generate_btn.click(
-            generate_resume,
+            fn=generate_resume,
             inputs=[name, email, phone, summary, experience, education, skills],
             outputs=resume_output
         )
@@ -67,26 +79,25 @@ with gr.Blocks() as demo:
     with gr.Tab("2️⃣ Score Resume Against Job"):
         resume_input = gr.Textbox(label="Your Resume", lines=10)
         job_desc = gr.Textbox(label="Job Description", lines=5)
-        score_output = gr.Textbox(label="Job Match Score + Suggestions", lines=10)
+        score_output = gr.Textbox(label="Match Score & Suggestions", lines=10)
         score_btn = gr.Button("Evaluate")
 
         score_btn.click(
-            score_resume,
+            fn=score_resume,
             inputs=[resume_input, job_desc],
             outputs=score_output
         )
 
     with gr.Tab("3️⃣ Refine Resume Section"):
         section_input = gr.Textbox(label="Resume Section", lines=5)
-        instruction_input = gr.Textbox(label="Refinement Instruction (e.g., make it more concise)")
+        instruction_input = gr.Textbox(label="Refinement Instruction")
         refined_output = gr.Textbox(label="Refined Text", lines=5)
         refine_btn = gr.Button("Refine")
 
         refine_btn.click(
-            refine_section,
+            fn=refine_section,
             inputs=[section_input, instruction_input],
             outputs=refined_output
         )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()