implemeted an Model , login free✅✅`

app.py

@@ -1,10 +1,11 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load Hugging Face pipelines directly (no local storage required)
-ner_pipeline = pipeline("ner", model="blackshadow1/biobert-ner-model")
-sentiment_pipeline = pipeline("sentiment-analysis", model="blackshadow1/sentiment-model")
-summarization_pipeline = pipeline("summarization", model="blackshadow1/t5-summarization-model")
+# Load Hugging Face pipelines directly
+ner_pipeline = pipeline("ner", model="dslim/bert-base-NER")  # Named Entity Recognition
+sentiment_pipeline = pipeline("sentiment-analysis")  # Sentiment Analysis
+summarization_pipeline = pipeline("summarization", model="facebook/bart-large-cnn")  # Summarization
+conversation_pipeline = pipeline("conversational", model="microsoft/DialoGPT-medium")  # Conversational AI
 
 # Function to process user input
 def ai_doctor_interaction(user_input, chat_history=[]):
@@ -20,10 +21,15 @@ def ai_doctor_interaction(user_input, chat_history=[]):
     summary = summarization_pipeline(user_input, max_length=50, min_length=10, do_sample=False)[0]['summary_text']
 
     # Generate AI Doctor response
+    conversation = conversation_pipeline(user_input)
+    ai_response = conversation.generated_responses[-1]
+
+    # Combine results into a response
     response = f"""
-    **Entities Identified**: {', '.join(entities)}
-    **Sentiment**: {sentiment}
-    **Summary**: {summary}
+    **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))
@@ -31,17 +37,26 @@ def ai_doctor_interaction(user_input, 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>")
+    gr.Markdown("<h1 style='text-align: center; color: #4CAF50;'>AI Doctor Avatar</h1>")
+    gr.Markdown("<p style='text-align: center; font-size: 1.2em;'>Interact with the AI Doctor to resolve your health-related queries.</p>")
     
     with gr.Row():
         with gr.Column(scale=1):
-            gr.Video(value="https://app.aistudios.com/share/681356f694258c96c250d3d0", autoplay=True, loop=True, show_controls=False)
+            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")
-            user_input = gr.Textbox(label="Your Message", placeholder="Type your question here...")
-            submit_button = gr.Button("Send")
-            clear_button = gr.Button("Clear Chat")
+            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])