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Add ElevenLabs TTS for VIVA questions
Browse files
app.py
CHANGED
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@@ -13,11 +13,57 @@ load_dotenv()
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SERPAPI_KEY = os.getenv("SERPAPI_KEY")
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HYPERBOLIC_API_KEY = os.getenv("HYPERBOLIC_API_KEY")
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# Hyperbolic API configuration
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HYPERBOLIC_API_URL = "https://api.hyperbolic.xyz/v1/chat/completions"
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HYPERBOLIC_MODEL = "meta-llama/Llama-3.3-70B-Instruct"
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def is_anatomy_related(query: str) -> tuple[bool, str]:
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"""
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Validate if the query is anatomy-related using the LLM.
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@@ -516,6 +562,10 @@ def start_viva_mode(topic, image):
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# Start with question 1
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q1 = questions[0]
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return (
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gr.update(visible=True), # Show VIVA container
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f"**VIVA MODE ACTIVE** 📝\nTopic: {topic}", # viva_status
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@@ -525,7 +575,8 @@ def start_viva_mode(topic, image):
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"", # Clear answer input
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"", # Clear feedback
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gr.update(interactive=True, value="Submit Answer"), # Enable submit button
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questions # Store questions in state
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)
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@@ -544,13 +595,18 @@ def submit_viva_answer(answer, questions, current_q_idx):
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next_q = questions[next_idx]
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next_question = f"### Question {next_idx + 1} of 5\n\n**{next_q['question']}**"
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next_hint = f"💡 **Hint:** {next_q.get('hint', 'Think carefully about the anatomical relationships.')}"
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return (
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next_question, # Show next question
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next_hint, # Show next hint
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"", # Clear answer box
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feedback_text, # Show feedback for current answer
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gr.update(interactive=True, value="Submit Answer"), # Keep button enabled
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next_idx # Update question index
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)
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else:
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# VIVA complete
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@@ -561,7 +617,8 @@ def submit_viva_answer(answer, questions, current_q_idx):
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"", # Clear answer
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feedback_text, # Final feedback
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gr.update(interactive=False, value="VIVA Complete"),
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next_idx
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)
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@@ -701,6 +758,9 @@ with gr.Blocks(title="AnatomyBot - MBBS Anatomy Tutor") as demo:
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current_question_display = gr.Markdown("### Question will appear here")
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hint_display = gr.Markdown("💡 Hint will appear here")
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student_answer = gr.Textbox(
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label="Your Answer",
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placeholder="Type your answer here...",
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@@ -739,7 +799,8 @@ with gr.Blocks(title="AnatomyBot - MBBS Anatomy Tutor") as demo:
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viva_container, viva_status, viva_image,
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current_question_display, hint_display,
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student_answer, feedback_display, submit_answer_btn,
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viva_questions_state
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]
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).then(
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fn=lambda: gr.update(selected=1), # Switch to VIVA tab
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@@ -755,7 +816,8 @@ with gr.Blocks(title="AnatomyBot - MBBS Anatomy Tutor") as demo:
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inputs=[student_answer, viva_questions_state, current_question_idx],
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outputs=[
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current_question_display, hint_display, student_answer,
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feedback_display, submit_answer_btn, current_question_idx
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]
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)
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SERPAPI_KEY = os.getenv("SERPAPI_KEY")
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HYPERBOLIC_API_KEY = os.getenv("HYPERBOLIC_API_KEY")
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ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")
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# Hyperbolic API configuration
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HYPERBOLIC_API_URL = "https://api.hyperbolic.xyz/v1/chat/completions"
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HYPERBOLIC_MODEL = "meta-llama/Llama-3.3-70B-Instruct"
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# ElevenLabs API configuration
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ELEVENLABS_API_URL = "https://api.elevenlabs.io/v1/text-to-speech"
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# Using a standard "Professor" like voice (e.g., "Brian" - a deep, authoritative British voice, or similar)
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# Voice ID for "Brian": nPczCjzI2devNBz1zQrb
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ELEVENLABS_VOICE_ID = "nPczCjzI2devNBz1zQrb"
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def generate_audio(text: str) -> str:
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"""
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Generate audio from text using ElevenLabs API.
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Returns path to temporary audio file or None if failed.
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"""
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if not ELEVENLABS_API_KEY or not text:
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return None
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try:
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url = f"{ELEVENLABS_API_URL}/{ELEVENLABS_VOICE_ID}"
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headers = {
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"Accept": "audio/mpeg",
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"Content-Type": "application/json",
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"xi-api-key": ELEVENLABS_API_KEY
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}
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data = {
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"text": text,
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"model_id": "eleven_monolingual_v1",
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"voice_settings": {
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"stability": 0.5,
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"similarity_boost": 0.5
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}
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}
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response = requests.post(url, json=data, headers=headers)
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if response.status_code == 200:
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# Save to temp file
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as f:
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f.write(response.content)
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return f.name
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else:
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print(f"ElevenLabs API Error: {response.text}")
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return None
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except Exception as e:
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print(f"Error generating audio: {str(e)}")
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return None
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def is_anatomy_related(query: str) -> tuple[bool, str]:
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"""
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Validate if the query is anatomy-related using the LLM.
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# Start with question 1
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q1 = questions[0]
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# Generate audio for first question
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audio_path = generate_audio(q1['question'])
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return (
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gr.update(visible=True), # Show VIVA container
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f"**VIVA MODE ACTIVE** 📝\nTopic: {topic}", # viva_status
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"", # Clear answer input
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"", # Clear feedback
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gr.update(interactive=True, value="Submit Answer"), # Enable submit button
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questions, # Store questions in state
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audio_path # Return audio path
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)
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next_q = questions[next_idx]
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next_question = f"### Question {next_idx + 1} of 5\n\n**{next_q['question']}**"
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next_hint = f"💡 **Hint:** {next_q.get('hint', 'Think carefully about the anatomical relationships.')}"
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# Generate audio for next question
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audio_path = generate_audio(next_q['question'])
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return (
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next_question, # Show next question
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next_hint, # Show next hint
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"", # Clear answer box
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feedback_text, # Show feedback for current answer
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gr.update(interactive=True, value="Submit Answer"), # Keep button enabled
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next_idx, # Update question index
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audio_path # Play next question audio
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)
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else:
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# VIVA complete
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"", # Clear answer
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feedback_text, # Final feedback
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gr.update(interactive=False, value="VIVA Complete"),
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next_idx,
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None # No audio
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)
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current_question_display = gr.Markdown("### Question will appear here")
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hint_display = gr.Markdown("💡 Hint will appear here")
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# Audio player for question
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question_audio = gr.Audio(label="🔊 Listen to Question", autoplay=True, interactive=False)
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student_answer = gr.Textbox(
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label="Your Answer",
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placeholder="Type your answer here...",
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viva_container, viva_status, viva_image,
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current_question_display, hint_display,
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student_answer, feedback_display, submit_answer_btn,
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viva_questions_state,
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question_audio # Output audio
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]
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).then(
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fn=lambda: gr.update(selected=1), # Switch to VIVA tab
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inputs=[student_answer, viva_questions_state, current_question_idx],
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outputs=[
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current_question_display, hint_display, student_answer,
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feedback_display, submit_answer_btn, current_question_idx,
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question_audio # Output audio for next question
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]
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)
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