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updated ui
Browse files
app.py
CHANGED
@@ -8,7 +8,7 @@ from deep_translator import GoogleTranslator
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from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
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import torch
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# ===== TTS
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voice_characters = {
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"English - US": {
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@@ -17,7 +17,8 @@ voice_characters = {
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"Guy": "en-US-GuyNeural",
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},
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"Hindi": {
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"Swara": "hi-IN-SwaraNeural"
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}
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}
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@@ -33,37 +34,29 @@ def tts_wrapper(text, language, character, translation_direction):
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try:
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original_text = text.strip()
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if not original_text:
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return "
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if translation_direction == "English to Hindi":
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text = GoogleTranslator(source='en', target='hi').translate(original_text)
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elif translation_direction == "Hindi to English":
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text = GoogleTranslator(source='hi', target='en').translate(original_text)
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if language == "Hindi":
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voice = voice_characters["Hindi"]["Swara"]
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else:
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voice = voice_characters.get(language, {}).get(character)
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if not voice:
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return f"
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filename = asyncio.run(generate_tts(text, voice))
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return text, filename
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except Exception as e:
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return f"Error: {str(e)}", None
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def get_characters(language):
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chars = list(voice_characters.get(language, {}).keys())
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default_char = chars[0] if chars else None
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return gr.update(choices=chars, value=default_char, visible=True)
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# =====
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model_name = "facebook/blenderbot-400M-distill"
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tokenizer = BlenderbotTokenizer.from_pretrained(model_name)
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@@ -80,60 +73,69 @@ def chatbot_response(history, user_message):
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if history is None:
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history = []
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history.append(("
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conversation_text = " ".join([msg for _, msg in history]) + " " + user_message
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inputs = tokenizer([conversation_text], return_tensors="pt").to(device)
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reply_ids = model.generate(**inputs, max_length=200)
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response = tokenizer.decode(reply_ids[0], skip_special_tokens=True)
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chat_str = ""
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for speaker, msg in history:
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chat_str += f"{speaker}: {msg}\n"
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try:
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audio_path = asyncio.run(generate_bot_tts(response))
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except Exception as e:
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audio_path = None
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print(f"TTS
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return history, chat_str, audio_path
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# =====
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def create_app():
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with gr.Blocks() as app:
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gr.Markdown("
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language_dropdown.change(fn=get_characters, inputs=language_dropdown, outputs=character_dropdown)
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tts_button.click(fn=tts_wrapper,
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inputs=[text_input, language_dropdown, character_dropdown, translation_dropdown],
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outputs=[output_text, output_audio])
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with gr.Tab("Chatbot"):
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user_input.submit(fn=respond, inputs=[user_input, chat_history], outputs=[chat_history, chat_display, audio_output])
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return app
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from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
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import torch
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# ===== TTS Setup =====
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voice_characters = {
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"English - US": {
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"Guy": "en-US-GuyNeural",
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},
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"Hindi": {
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"Swara": "hi-IN-SwaraNeural",
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"Madhur": "hi-IN-MadhurNeural"
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}
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}
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try:
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original_text = text.strip()
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if not original_text:
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return "β οΈ Please enter some text.", None
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if translation_direction == "English to Hindi":
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text = GoogleTranslator(source='en', target='hi').translate(original_text)
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elif translation_direction == "Hindi to English":
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text = GoogleTranslator(source='hi', target='en').translate(original_text)
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voice = voice_characters.get(language, {}).get(character)
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if not voice:
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return f"β οΈ Voice '{character}' not available for '{language}'.", None
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filename = asyncio.run(generate_tts(text, voice))
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return text, filename
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except Exception as e:
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return f"β Error: {str(e)}", None
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def get_characters(language):
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chars = list(voice_characters.get(language, {}).keys())
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default_char = chars[0] if chars else None
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return gr.update(choices=chars, value=default_char)
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# ===== Chatbot Setup =====
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model_name = "facebook/blenderbot-400M-distill"
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tokenizer = BlenderbotTokenizer.from_pretrained(model_name)
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if history is None:
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history = []
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history.append(("π§", user_message))
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conversation_text = " ".join([msg for _, msg in history]) + " " + user_message
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inputs = tokenizer([conversation_text], return_tensors="pt").to(device)
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reply_ids = model.generate(**inputs, max_length=200)
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response = tokenizer.decode(reply_ids[0], skip_special_tokens=True)
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history.append(("π€", response))
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chat_str = "\n".join([f"{speaker}: {msg}" for speaker, msg in history])
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try:
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audio_path = asyncio.run(generate_bot_tts(response))
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except Exception as e:
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audio_path = None
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print(f"TTS failed: {e}")
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return history, chat_str, audio_path
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# ===== UI =====
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def create_app():
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with gr.Blocks(css="footer {text-align: center; padding: 10px;}") as app:
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gr.Markdown("""
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# π£οΈ SpeakEasy AI
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A simple and fun **Text-to-Speech + Translator + Chatbot** app!
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""")
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with gr.Tab("π§ Text to Speech + Translator"):
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with gr.Row():
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with gr.Column(scale=2):
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text_input = gr.Textbox(label="π¬ Your Text", placeholder="Enter text here...", lines=4)
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language_dropdown = gr.Dropdown(choices=list(voice_characters.keys()), value="English - US", label="π Language")
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character_dropdown = gr.Dropdown(choices=list(voice_characters["English - US"].keys()), value="Aria", label="π§βπ€ Voice Character")
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with gr.Accordion("π Translation Options", open=False):
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translation_dropdown = gr.Dropdown(choices=["None", "English to Hindi", "Hindi to English"],
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value="None", label="π Translate Text")
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tts_button = gr.Button("ποΈ Generate Voice")
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output_text = gr.Textbox(label="π Final Output / Translation")
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with gr.Column(scale=1):
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output_audio = gr.Audio(label="π Listen Here", autoplay=True)
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language_dropdown.change(fn=get_characters, inputs=language_dropdown, outputs=character_dropdown)
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tts_button.click(fn=tts_wrapper,
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inputs=[text_input, language_dropdown, character_dropdown, translation_dropdown],
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outputs=[output_text, output_audio])
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with gr.Tab("π€ Chatbot"):
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with gr.Row():
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with gr.Column(scale=2):
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user_input = gr.Textbox(label="π¬ Ask Anything", lines=2, placeholder="Try: What's your name?")
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chat_display = gr.Textbox(label="π Conversation", interactive=False, lines=15)
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send_button = gr.Button("π© Send")
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with gr.Column(scale=1):
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audio_output = gr.Audio(label="π Bot's Voice Reply", autoplay=True)
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chat_history = gr.State([])
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send_button.click(fn=chatbot_response, inputs=[chat_history, user_input],
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outputs=[chat_history, chat_display, audio_output])
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user_input.submit(fn=chatbot_response, inputs=[chat_history, user_input],
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outputs=[chat_history, chat_display, audio_output])
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gr.HTML("<footer>π§ Made by using Gradio, Edge TTS, and Hugging Face π€</footer>")
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return app
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