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app.py

@@ -2,96 +2,129 @@ import os
 import gradio as gr
 from openai import OpenAI
 
-# Initialize OpenAI client
+# Initialize OpenAI client (expects OPENAI_API_KEY in env)
 client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
-# Streaming response function
-def respond(
+def make_system_message(system_message, role, jobad, education, workexp, skills, ask_sugg):
+    msg = (
+        f"{system_message}\n\n"
+        f"Role, Industry and Type of Organization: {role}\n"
+        f"Job Ad Responsibilities and Key Requirements: {jobad}\n"
+        f"Education, Training and Certifications: {education}\n"
+        f"Work Experience: {workexp}\n"
+        f"Skills: {skills}\n"
+    )
+    if ask_sugg:
+        msg += " The user is also asking for suggestions of skills related to this role."
+    return msg
+
+def stream_chat(
     message,
-    history: list[tuple[str, str]],
+    history,                # list[list[str, str]] from gr.Chatbot
     system_message,
     role,
-    ad,
+    jobad,
     education,
-    experience,
+    workexp,
     skills,
-    ask_for_skills_suggestions,
+    ask_sugg,
     max_tokens,
-    temperature,
+    temp,
     top_p,
 ):
-    # Construct the system message
-    enhanced_system_message = (
-        f"{system_message}\n\n"
-        f"Role, Industry and Type of Organization: {role}\n"
-        f"Job Ad Responsibilities and Key Requirements: {ad}\n"
-        f"Education, Training and Certifications: {education}\n"
-        f"Work Experience: {experience}\n"
-        f"Skills: {skills}\n"
-    )
-
-    if ask_for_skills_suggestions:
-        enhanced_system_message += " The user is also asking for suggestions of skills related to this role."
+    """
+    Streaming generator that yields the progressively updated chat history.
+    """
+    # 1) Build system + conversation messages
+    sys_msg = make_system_message(system_message, role, jobad, education, workexp, skills, ask_sugg)
 
-    # Compose the conversation
-    messages = [{"role": "system", "content": enhanced_system_message}]
-    for user_msg, assistant_msg in history:
+    messages = [{"role": "system", "content": sys_msg}]
+    for user_msg, assistant_msg in (history or []):
         if user_msg:
             messages.append({"role": "user", "content": user_msg})
         if assistant_msg:
             messages.append({"role": "assistant", "content": assistant_msg})
     messages.append({"role": "user", "content": message})
 
-    # Generate and stream response
-    response_text = ""
+    # 2) Start streaming back to the Chatbot
+    running_reply = ""
+    # Optimistically show the assistant "typing"
+    running_history = (history or []) + [[message, ""]]
+    yield running_history
+
     try:
         response = client.chat.completions.create(
-            model="gpt-4o-mini",  # use "gpt-4o-mini" when officially available
+            model="gpt-4o-mini",   # adjust if needed
             messages=messages,
-            max_tokens=max_tokens,
-            temperature=temperature,
-            top_p=top_p,
+            max_tokens=int(max_tokens),
+            temperature=float(temp),
+            top_p=float(top_p),
             stream=True,
         )
         for chunk in response:
-            if chunk.choices and chunk.choices[0].delta.content:
+            if chunk.choices and chunk.choices[0].delta and chunk.choices[0].delta.content:
                 token = chunk.choices[0].delta.content
-                response_text += token
-                yield response_text
+                running_reply += token
+                running_history[-1][1] = running_reply
+                # Yield the whole history each time so the UI updates
+                yield running_history
     except Exception as e:
-        yield f"❌ An error occurred: {str(e)}"
-
-# Gradio interface
-demo = gr.ChatInterface(
-    fn=respond,
-    additional_inputs=[
-        gr.Textbox(
-            value="You are a friendly Chatbot, a career coach and a talented copywriter. You are trying to help a user customize their resume according to a specific role, employer organization and job Ad - based on user input. Include tips if some items are missing.",
+        running_history[-1][1] = f"❌ An error occurred: {str(e)}"
+        yield running_history
+
+
+with gr.Blocks(title="Resumize – Customize your CV!") as demo:
+    gr.Markdown("""
+    # Resumize – Customize your CV!
+    This app customizes your resume to best suit a specific role, industry, employer and job ad.
+    Powered by OpenAI GPT-4o and domain expertise.
+    """)
+
+    chatbot = gr.Chatbot(height=400)
+
+    with gr.Column():
+        instructions = gr.Textbox(
+            value=(
+                "You are a friendly Chatbot, a career coach and a talented copywriter. "
+                "You are trying to help a user customize their resume according to a specific role, employer organization and job Ad "
+                "- based on user input. Include tips if some items are missing."
+            ),
             label="Instructions to Bot",
-        ),
-        gr.Textbox(label="Role, Industry and Employer", placeholder="Describe the role, industry and employer you are applying to."),
-        gr.Textbox(
-            label="Job Ad Responsibilities and Key Requirements",
-            placeholder="Describe the Responsibilities and Key Requirements advertised in the job ad",
-        ),
-        gr.Textbox(
-            label="Your Education, certifications, training, etc.",
-            placeholder="Describe your education, training, certifications and professional designations",
-        ),
-        gr.Textbox(
-            label="Your Work Experience",
-            placeholder="Describe your work experience, previous responsibilities and key career achievements",
-        ),
-        gr.Textbox(label="Skills", placeholder="List your key skills that match this job or ask for suggestions"),
-        gr.Checkbox(label="Ask for Skills Suggestions", value=False),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
-    ],
-    title="Resumize – Customize your CV!",
-    description="This app customizes your resume to best suit a specific role, industry, employer and job ad. Based on your input. Powered by OpenAI GPT-4o, design thinking, and domain expertise. Developed by wn. Disclaimer: AI can make mistakes. Use with caution and at your own risk!",
-    type="messages",  # Required for Gradio ChatInterface streaming
-)
+            lines=4,
+        )
+        role = gr.Textbox(label="Role, Industry and Employer", placeholder="Describe the role, industry and employer you are applying to.")
+        jobad = gr.Textbox(label="Job Ad Responsibilities and Key Requirements", placeholder="Paste/describe the job ad responsibilities and key requirements", lines=4)
+        education = gr.Textbox(label="Your Education, Certifications, Training, etc.", placeholder="Degrees, diplomas, certifications, courses", lines=3)
+        workexp = gr.Textbox(label="Your Work Experience", placeholder="Roles, responsibilities, achievements", lines=4)
+        skills = gr.Textbox(label="Skills", placeholder="List your key skills that match this job or ask for suggestions")
+        ask_sugg = gr.Checkbox(label="Ask for Skills Suggestions", value=False)
+
+        with gr.Row():
+            max_tokens = gr.Slider(minimum=1, maximum=4096, value=512, step=1, label="Max new tokens")
+            temp = gr.Slider(minimum=0.0, maximum=2.0, value=0.7, step=0.1, label="Temperature")
+            top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus)")
+
+    msg = gr.Textbox(label="Type your message here...", placeholder="e.g., Draft a tailored resume summary")
+    with gr.Row():
+        send = gr.Button("Send", variant="primary")
+        clear = gr.Button("Clear")
+
+    # Wire up sending (submit or button) → stream_chat → chatbot
+    inputs = [msg, chatbot, instructions, role, jobad, education, workexp, skills, ask_sugg, max_tokens, temp, top_p]
+    outputs = [chatbot]
+
+    msg.submit(stream_chat, inputs, outputs)
+    send.click(stream_chat, inputs, outputs)
+
+    # Clear everything
+    def do_clear():
+        return [], "", "", "", "", "", "", False, 512, 0.7, 0.95
+
+    clear.click(
+        do_clear,
+        inputs=[],
+        outputs=[chatbot, msg, instructions, role, jobad, education, workexp, skills, ask_sugg, max_tokens, temp, top_p],
+    )
 
 if __name__ == "__main__":
     demo.launch()