Update app.py

app.py

@@ -17,14 +17,12 @@ def start_interview(interview_type, doc_file, name, num_questions):
             chatbot: gr.update(value=[[None, "Please select an interview type and upload a document to begin."]]),
             audio_in: gr.update(interactive=False)
         }
-
     doc_text = extract_text_from_document(doc_file.name)
     if "Error" in doc_text or "Unsupported" in doc_text:
         return {
             chatbot: gr.update(value=[[None, f"Error: {doc_text}"]]),
             audio_in: gr.update(interactive=False)
         }
-
     initial_state = {
         "interview_type": interview_type,
         "doc_text": doc_text,
@@ -34,15 +32,11 @@ def start_interview(interview_type, doc_file, name, num_questions):
         "interview_log": [],
         "start_time": time.time()
     }
-
     first_question = generate_question(interview_type, doc_text)
     initial_state["current_question_text"] = first_question
-    
     greeting = f"Hello {initial_state['name']}. We'll go through {int(num_questions)} questions today. Here is your first question:"
-    
     tts_prompt = f"{greeting} {first_question}"
     ai_voice_path = text_to_speech_file(tts_prompt)
-    
     return {
         state: initial_state,
         chatbot: gr.update(value=[[None, f"{greeting}\n\n{first_question}"]]),
@@ -62,14 +56,11 @@ def handle_interview_turn(user_audio, chatbot_history, current_state):
         "answer": user_answer_text,
         "evaluation": evaluation_text
     })
-
     if current_state["current_question_num"] >= current_state["question_count"]:
         end_message = "This concludes the interview. Generating your final report now."
         chatbot_history.append([None, end_message])
-        
         pdf_path = generate_pdf_file(current_state)
         ai_voice_path = text_to_speech_file(end_message)
-        
         yield {
             chatbot: chatbot_history,
             audio_out: gr.update(value=ai_voice_path, autoplay=True),
@@ -79,13 +70,10 @@ def handle_interview_turn(user_audio, chatbot_history, current_state):
         current_state["current_question_num"] += 1
         next_question = generate_question(current_state["interview_type"], current_state["doc_text"])
         current_state["current_question_text"] = next_question
-        
         q_num = current_state["current_question_num"]
         transition_message = f"Thank you. Here is question {q_num}:\n\n{next_question}"
         chatbot_history.append([None, transition_message])
-        
         ai_voice_path = text_to_speech_file(transition_message)
-
         yield {
             state: current_state,
             chatbot: chatbot_history,
@@ -94,7 +82,6 @@ def handle_interview_turn(user_audio, chatbot_history, current_state):
         }
 
 def generate_pdf_file(state):
-    # This function now correctly creates the dictionary for the report generator
     total_duration_minutes = (time.time() - state.get("start_time", time.time())) / 60
     final_data = { 
         "name": state.get("name", "N/A"), 
@@ -109,14 +96,20 @@ def generate_pdf_file(state):
 
 with gr.Blocks(theme=gr.themes.Default()) as app:
     state = gr.State({})
-    gr.Markdown("# AI Interview Coach for Super Kalam")
+    gr.Markdown("# 🤖 AI Interview Coach")
     with gr.Row():
         with gr.Column(scale=1):
             gr.Markdown("### Setup")
             user_name = gr.Textbox(label="Your Name")
             interview_type_dd = gr.Dropdown(config.INTERVIEW_TYPES, label="Interview Type")
             num_questions_slider = gr.Slider(minimum=2, maximum=10, value=5, step=1, label="Number of Questions")
-            doc_uploader = gr.File(label="Upload Resume/CV")
+            
+            # --- THIS IS THE UPDATED COMPONENT ---
+            doc_uploader = gr.File(
+                label="Upload Resume/CV (.pdf, .docx)",
+                file_types=['.pdf', '.docx']
+            )
+            
             start_btn = gr.Button("Start Interview", variant="primary")
         
         with gr.Column(scale=2):