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Update app.py
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app.py
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@@ -13,15 +13,21 @@ from database_functions import add_user_privacy, add_submission
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from tab_teachers_dashboard import create_teachers_dashboard_tab
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from config import CLASS_OPTIONS
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import spaces
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from streaming_stt_nemo import Model
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import edge_tts
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import tempfile
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# Load environment variables
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load_dotenv()
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# For maintaining user session (to keep track of userID)
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user_state = gr.State(value="")
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@@ -33,11 +39,12 @@ image_path = "picturePerformance.jpg"
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img_html = get_image_html(image_path)
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@spaces.GPU(duration=120)
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def transcribe(
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@spaces.GPU(duration=120)
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def generate_feedback(user_id, question_choice, strategy_choice, message, feedback_level):
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from tab_teachers_dashboard import create_teachers_dashboard_tab
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from config import CLASS_OPTIONS
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import spaces
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import edge_tts
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import tempfile
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# Load environment variables
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load_dotenv()
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# Whisper API settings
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API_URL = "https://api-inference.huggingface.co/models/whisper-large"
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headers = {"Authorization": f"Bearer {os.getenv('HF_AUTH_TOKEN')}"}
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def whisper_query(filename):
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with open(filename, "rb") as f:
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data = f.read()
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response = requests.post(API_URL, headers=headers, data=data)
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return response.json()
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# For maintaining user session (to keep track of userID)
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user_state = gr.State(value="")
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img_html = get_image_html(image_path)
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@spaces.GPU(duration=120)
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def transcribe(audio_path):
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response = whisper_query(audio_path)
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if "text" in response:
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return response["text"]
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else:
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raise ValueError("Transcription failed.")
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@spaces.GPU(duration=120)
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def generate_feedback(user_id, question_choice, strategy_choice, message, feedback_level):
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