Update app.py

app.py

@@ -3,18 +3,17 @@ import gradio as gr
 from llama_index.readers.file import PDFReader
 from llama_index.core import VectorStoreIndex
 from llama_index.llms.openai import OpenAI as LlamaOpenAI
-from openai import OpenAI  
-import openai
+from openai import OpenAI  # New SDK
 from gtts import gTTS
 import random
 import tempfile
 import speech_recognition as sr
 
-# Set API key (use HF secret if available)
-openai.api_key = os.environ.get('HF_OPENAI_API_KEY', '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')
-client = OpenAI()  # OpenAI SDK
+# 🔐 Set API key directly (use HF secret or hardcode for testing)
+OPENAI_API_KEY = os.environ.get('HF_OPENAI_API_KEY', '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')  # Replace or use HF secret
+client = OpenAI(api_key=OPENAI_API_KEY)
 
-# Globals
+# Global state
 query_engine = None
 resume_summary = ""
 questions = []
@@ -100,22 +99,22 @@ Only return: Score: <number>
     except Exception as e:
         return "❌ Evaluation failed", str(e)
 
-# Gradio UI
+# Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# 🎤 Voice-Based Resume Interview Bot\nUpload your resume, get voice questions, answer by mic, and receive feedback.")
+    gr.Markdown("# 🎤 Voice Resume Interview Bot\nUpload your resume → get questions in voice → answer via mic → get score.")
 
     with gr.Row():
         resume_file = gr.File(label="📄 Upload Resume", file_types=[".pdf"])
         resume_summary_box = gr.Textbox(label="Resume Summary", lines=6)
     gr.Button("Analyze Resume").click(fn=load_resume, inputs=resume_file, outputs=resume_summary_box)
 
-    gr.Markdown("## 🔊 Ask Next Resume-Based Question")
+    gr.Markdown("## 🔊 Ask a Resume-Based Question")
     question_text = gr.Textbox(label="Question", lines=2)
-    question_audio = gr.Audio(label="Listen", type="filepath", autoplay=True)
+    question_audio = gr.Audio(label="Voice", type="filepath", autoplay=True)
     gr.Button("Ask Question").click(fn=ask_next_question, outputs=[question_text, question_audio])
 
-    gr.Markdown("## 🎙️ Answer the Question with Your Voice")
-    user_audio = gr.Audio(label="🎤 Record Answer", type="filepath")
+    gr.Markdown("## 🎙️ Speak Your Answer")
+    user_audio = gr.Audio(label="Record Your Answer", type="filepath")
     transcript_output = gr.Textbox(label="Transcript")
     score_output = gr.Textbox(label="LLM Score")
     gr.Button("Submit Answer").click(fn=evaluate_answer, inputs=user_audio, outputs=[transcript_output, score_output])