Create app.py

app.py

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+import gradio as gr
+from langchain_huggingface.llms import HuggingFacePipeline
+from langchain_core.prompts import PromptTemplate
+
+# Load the HuggingFace model
+hf = HuggingFacePipeline.from_model_id(
+    model_id="gpt2",
+    task="text-generation",
+    pipeline_kwargs={"max_new_tokens": 10},
+)
+
+# Create a prompt template
+template = """Question: {question}
+
+Answer: Let's think step by step."""
+prompt = PromptTemplate.from_template(template)
+
+# Combine prompt with HuggingFace model
+chain = prompt | hf
+
+# Define a function for Gradio interface
+def respond(question):
+    return chain.invoke({"question": question})
+
+# Create Gradio ChatInterface
+chat_interface = gr.ChatInterface(fn=respond, title="Q&A Chatbot", description="Ask any question and get an answer!")
+
+# Launch the interface
+chat_interface.launch()