Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Initialize the text-generation pipeline
+pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-beta", torch_dtype="auto", device_map="auto")
+
+# Define agent roles
+agents = {
+    "Pirate": "You are a friendly chatbot who always responds in the style of a pirate.",
+    "Professor": "You are a knowledgeable professor who explains concepts in detail.",
+    "Comedian": "You are a witty comedian who answers with humor and jokes.",
+    "Motivator": "You are a motivational speaker who provides inspiring and uplifting responses.",
+}
+
+def multi_agent_system(agent, user_input):
+    # Set the role of the selected agent
+    messages = [
+        {"role": "system", "content": agents[agent]},
+        {"role": "user", "content": user_input},
+    ]
+    # Format the chat template
+    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    # Generate the response
+    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+    return outputs[0]["generated_text"]
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# Multi-Agent Chat System")
+    
+    with gr.Row():
+        agent_dropdown = gr.Dropdown(
+            choices=list(agents.keys()), label="Select an Agent", value="Pirate"
+        )
+        user_input = gr.Textbox(label="Enter your message:", placeholder="Type your query here...")
+    
+    submit_button = gr.Button("Submit")
+    chat_output = gr.Textbox(label="Agent's Response:", interactive=False)
+    
+    submit_button.click(
+        fn=multi_agent_system, 
+        inputs=[agent_dropdown, user_input], 
+        outputs=chat_output
+    )
+
+# Launch the app
+demo.launch()