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Update app.py
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app.py
CHANGED
@@ -1,47 +1,67 @@
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import gradio as gr
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import speech_recognition as sr
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import torch
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from transformers import pipeline
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# Load ASR
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device = "cuda" if torch.cuda.is_available() else "cpu"
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speech_to_text = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=0 if device == "cuda" else -1)
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# Initialize Speech Recognition
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recognizer = sr.Recognizer()
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# Function to Capture Name
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def capture_name(audio):
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try:
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text = speech_to_text(audio)["text"]
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return f"Name Captured: {text}", "Please provide your email address."
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except Exception as e:
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return f"Error: {str(e)}", ""
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# Function to Capture Email
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def capture_email(audio):
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try:
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text = speech_to_text(audio)["text"]
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return f"Email Captured: {text}"
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except Exception as e:
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return f"Error: {str(e)}"
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# Gradio Interface
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def gradio_interface():
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with gr.Blocks() as demo:
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gr.Markdown("
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with gr.Column():
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gr.
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name_output = gr.Textbox(label="Your Name:")
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email_prompt_output = gr.Textbox(label="Next Step:", interactive=False)
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audio_input_name.change(capture_name, inputs=audio_input_name, outputs=[name_output, email_prompt_output])
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email_output = gr.Textbox(label="Your Email:")
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return demo
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import gradio as gr
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import speech_recognition as sr
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import torch
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import os
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from transformers import pipeline
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from gtts import gTTS
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import time
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# Load ASR Model (Whisper)
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device = "cuda" if torch.cuda.is_available() else "cpu"
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speech_to_text = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=0 if device == "cuda" else -1)
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# Initialize Speech Recognition
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recognizer = sr.Recognizer()
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# Function to Play Audio Prompt
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def play_audio(text):
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tts = gTTS(text=text, lang='en')
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filename = "prompt.mp3"
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tts.save(filename)
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os.system(f"mpg321 {filename}" if os.name != "nt" else f"start {filename}") # Works on Linux & Windows
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time.sleep(2) # Give some time for the speech to play
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# Function to Capture Name
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def capture_name(audio):
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play_audio("Tell me your name")
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try:
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text = speech_to_text(audio)["text"]
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return f"π€ Name Captured: {text}", "Please provide your email address."
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except Exception as e:
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return f"β Error: {str(e)}", ""
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# Function to Capture Email
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def capture_email(audio):
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play_audio("Please provide your email address")
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try:
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text = speech_to_text(audio)["text"]
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return f"π§ Email Captured: {text}"
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except Exception as e:
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return f"β Error: {str(e)}"
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# Gradio Interface
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def gradio_interface():
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with gr.Blocks() as demo:
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gr.Markdown("<h1 style='text-align: center;'>π½οΈ AI Dining Assistant</h1>")
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with gr.Column():
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gr.Image("/mnt/data/image.png", elem_id="header_image", show_label=False) # Upload the image you provided
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gr.Markdown("<p style='text-align: center;'>Press the mic button to start...</p>")
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gr.Markdown("#### π€ Step 1: Tell me your name")
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mic_button = gr.Button("ποΈ Tap to Speak Your Name")
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audio_input_name = gr.Audio(type="filepath", visible=False)
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name_output = gr.Textbox(label="Your Name:")
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email_prompt_output = gr.Textbox(label="Next Step:", interactive=False)
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mic_button.click(capture_name, inputs=audio_input_name, outputs=[name_output, email_prompt_output])
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gr.Markdown("#### π€ Step 2: Provide your email")
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mic_button_email = gr.Button("ποΈ Tap to Speak Your Email")
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audio_input_email = gr.Audio(type="filepath", visible=False)
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email_output = gr.Textbox(label="Your Email:")
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mic_button_email.click(capture_email, inputs=audio_input_email, outputs=email_output)
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return demo
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