Create gradio_app.py

gradio_app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Step 1: Load the pre-trained model
+# You can choose any suitable conversational model from the Hugging Face Model Hub
+chatbot = pipeline("conversational", model="microsoft/DialoGPT-small")
+
+# Step 2: Define the function that will process user input and return the model's response
+def respond(input_text):
+    conversation = chatbot([input_text])
+    return conversation[0]["generated_text"]
+
+# Step 3: Create a Gradio interface
+# This interface will take text input from the user and display the chatbot's response
+iface = gr.Interface(
+    fn=respond,  # The function to call when the user submits input
+    inputs="text",  # The type of input (text)
+    outputs="text",  # The type of output (text)
+    title="HugChat - Your AI Chatbot",  # The title of your chatbot
+    description="Chat with an AI-powered bot based on a pre-trained model."  # A short description
+)
+
+# Step 4: Launch the interface
+if __name__ == "__main__":
+    iface.launch()