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mmccanse
commited on
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87a8f85
1
Parent(s):
91fc0ef
update code to reconfigure formatting and layout.
Browse files- __pycache__/functions_mm.cpython-311.pyc +0 -0
- app.py +49 -37
__pycache__/functions_mm.cpython-311.pyc
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Binary file (10.7 kB). View file
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app.py
CHANGED
@@ -41,57 +41,69 @@ from functions_mm import handle_query, transcribe_audio_original, submit_questio
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# Load environment variables.
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load_dotenv()
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# Set the model name for our LLMs.
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OPENAI_MODEL = "gpt-3.5-turbo"
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# Store the API key in a variable.
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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# In[5]:
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instructions = """
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# Diabetes Chatbot
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#### Step 1: Record your audio OR input text (NOT both!) -- Step 2: Would you like response in new language? Choose your language
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#### Step 3: Submit question -- Step 4: Translate response -- Step 5: Clear inputs and start fresh
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"""
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with gr.Blocks() as app2:
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with gr.Row():
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gr.Markdown(instructions)
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with gr.Row():
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#Divide the screen horizontally into 2 columns
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with gr.Row():
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query_text = gr.Textbox(label="Type your question here. If there is audio recorded AND question text, app will submit question text. Click transcribe button to populate with audio text")
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# output_original_speech = gr.Audio(label="Text to speech here")
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with gr.Column():
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response_text = gr.Textbox(label="Chatbot response")
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response_speech = gr.Audio(label="Chatbot response speech")
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#This column will be on the right side of screen
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with gr.Column():
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output_translated = gr.Textbox(label="Translated text")
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output_translated_speech = gr.Audio(label="Translated speech")
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# Audio transcription
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transcribe_button.click(
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# Load environment variables.
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# load_dotenv()
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# # Set the model name for our LLMs.
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# OPENAI_MODEL = "gpt-3.5-turbo"
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# # Store the API key in a variable.
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# OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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# In[5]:
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instructions="""
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# Diabetes Chatbot!
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## Ask a question through audio recording/text. Receive a response. Translate to selected language."""
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with gr.Blocks(theme=theme) as app2:
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with gr.Row():
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gr.Markdown(instructions)
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with gr.Row():
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with gr.Column(variant="panel", scale=1):
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# gr.Markdown("## Step 1: Enter question by recording audio")
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input_audio = gr.Audio(
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label="Click the microphone to record audio",
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type="filepath",
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waveform_options=gr.WaveformOptions(
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waveform_color="#01C6FF",
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waveform_progress_color="#0066B4",
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skip_length=2,
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show_controls=False,)
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)
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# gr.Markdown("## Step 2: Transcribe audio into text")
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transcribe_button = gr.Button("Transcribe audio", variant="primary")
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# gr.Markdown("## Step 3: Transcribed audio appears here. Or, type your question here.")
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query_text = gr.Textbox(placeholder="transcribed audio appears here. Or, type a question here.")
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# gr.Markdown("## Submit your question")
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submit_button = gr.Button("Submit your question", variant="primary")
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with gr.Column(variant="panel", scale=2):
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response_text = gr.Textbox(label="Chatbot response")
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response_speech = gr.Audio(label="Chatbot response speech",
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waveform_options=gr.WaveformOptions(
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waveform_color="#01C6FF",
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waveform_progress_color="#0066B4",
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skip_length=2,
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show_controls=False,))
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with gr.Column(variant="panel", scale=2):
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language_dropdown = gr.Dropdown(label="Click the middle of the dropdown bar to select translation language",
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choices=list(language_map.keys()), value=default_language, type='value')
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translate_button = gr.Button("Translate the response", variant="primary")
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output_translated = gr.Textbox(label="Translated text")
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output_translated_speech = gr.Audio(label="Translated speech",
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waveform_options=gr.WaveformOptions(
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waveform_color="#01C6FF",
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waveform_progress_color="#0066B4",
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skip_length=2,
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show_controls=False,))
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with gr.Row():
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clear_button = gr.Button("Clear All", variant="primary")
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# Audio transcription
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transcribe_button.click(
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