| import gradio as gr |
| from transformers import pipeline |
|
|
| sentiment_model = pipeline("sentiment-analysis") |
| chatbot_model = pipeline("text-generation", model="microsoft/DialoGPT-medium") |
| summarization_model = pipeline("summarization") |
| text_to_speech_model = pipeline("text-to-speech") |
|
|
| def get_sentiment(input_text): |
| analysis = sentiment_model(input_text) |
| sent = analysis[0]['label'] |
| score = analysis[0]['score'] |
| return sent, score |
|
|
| def chatbot_response(input_text): |
| response = chatbot_model(input_text, max_length=100, do_sample=True)[0]['generated_text'] |
| return response |
|
|
| def summarize_text(input_text): |
| summary = summarization_model(input_text, max_length=100, min_length=30, do_sample=False) |
| return summary[0]['summary_text'] |
|
|
| def text_to_speech(input_text): |
| audio = text_to_speech_model(input_text) |
| return audio |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("## Multi-Function AI Language Application") |
| |
| with gr.Tab("Sentiment Analysis"): |
| text_input = gr.Textbox(label="Enter text for sentiment analysis:") |
| sentiment_output = gr.Textbox(label="Sentiment") |
| score_output = gr.Number(label="Confidence Score") |
| sentiment_button = gr.Button("Analyze") |
| sentiment_button.click(get_sentiment, inputs=text_input, outputs=[sentiment_output, score_output]) |
| |
| with gr.Tab("Chatbot"): |
| chat_input = gr.Textbox(label="Enter your message:") |
| chat_output = gr.Textbox(label="Chatbot Response") |
| chat_button = gr.Button("Send") |
| chat_button.click(chatbot_response, inputs=chat_input, outputs=chat_output) |
| |
| with gr.Tab("Summarization"): |
| summary_input = gr.Textbox(label="Enter text to summarize:", lines=5) |
| summary_output = gr.Textbox(label="Summary") |
| summary_button = gr.Button("Summarize") |
| summary_button.click(summarize_text, inputs=summary_input, outputs=summary_output) |
| |
| with gr.Tab("Text-to-Speech"): |
| tts_input = gr.Textbox(label="Enter text to convert to speech:") |
| tts_output = gr.Audio(label="Generated Speech") |
| tts_button = gr.Button("Convert") |
| tts_button.click(text_to_speech, inputs=tts_input, outputs=tts_output) |
|
|
| |
| demo.launch() |
