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import gradio as gr
from transformers import pipeline
# Load Hugging Face pipelines
ner_pipeline = pipeline("ner", model="dslim/bert-base-NER")
sentiment_pipeline = pipeline("sentiment-analysis")
summarization_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")
conversation_pipeline = pipeline("text-generation", model="microsoft/DialoGPT-medium")
# Function to process user input
def ai_doctor_interaction(user_input, chat_history=[]):
# Perform NER
ner_results = ner_pipeline(user_input)
entities = [f"{entity['entity_group']}: {entity['word']}" for entity in ner_results]
# Perform Sentiment Analysis
sentiment_results = sentiment_pipeline(user_input)
sentiment = f"{sentiment_results[0]['label']} (Confidence: {sentiment_results[0]['score']:.2f})"
# Perform Summarization
summary = summarization_pipeline(user_input, max_length=50, min_length=10, do_sample=False)[0]['summary_text']
# Generate AI Doctor response
ai_response = conversation_pipeline(user_input, max_length=100, num_return_sequences=1)[0]["generated_text"]
# Combine results
response = f"""
**Entities Identified**: {', '.join(entities)}
**Sentiment**: {sentiment}
**Summary**: {summary}
**AI Doctor Response**: {ai_response}
"""
chat_history.append(("You", user_input))
chat_history.append(("AI Doctor", response))
return chat_history, chat_history
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("<h1 style='text-align: center;'>AI Doctor Avatar</h1>")
gr.Markdown("<p style='text-align: center;'>Interact with the AI Doctor to resolve your health-related queries.</p>")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("<h3 style='text-align: center;'>AI Doctor Avatar</h3>")
gr.HTML("""
<div style="position: relative; overflow: hidden; aspect-ratio: 1920/1080">
<iframe src="https://ff-resource.aistudios.com/2025-05-01/6813589d929f360ef7c28ecd.completed.mp4"
loading="lazy" title="AI Doctor Avatar" allow="encrypted-media; fullscreen;"
style="position: absolute; width: 100%; height: 100%; top: 0; left: 0; border: none; padding: 0; margin: 0; overflow:hidden;">
</iframe>
</div>
""")
with gr.Column(scale=2):
chatbot = gr.Chatbot(label="AI Doctor Chat Interface", height=400)
user_input = gr.Textbox(label="Your Message", placeholder="Type your question here...", lines=2)
with gr.Row():
submit_button = gr.Button("Send", variant="primary")
clear_button = gr.Button("Clear Chat", variant="secondary")
# Define interactions
submit_button.click(ai_doctor_interaction, inputs=[user_input, chatbot], outputs=[chatbot, chatbot])
clear_button.click(lambda: [], inputs=[], outputs=[chatbot])
# Launch the Gradio app
demo.launch() |