Update app.py

app.py

@@ -1,9 +1,23 @@
-import streamlit as st
-from transformers import pipeline 
+import gradio as gr
+from transformers import pipeline
 
-pipe = pipeline('sentiment-analysis')
-text = st.text_area("Enter your text")
+# Initialize the text-generation pipeline with a pre-trained model (e.g., GPT-2)
+generator = pipeline("text-generation", model="gpt-2")
 
-if text:
-    out = pipe(text)
-    st.write(out)
+def generate_blogpost(topic):
+    prompt = f"Write a detailed blog post about {topic}."
+    result = generator(prompt, max_length=300, num_return_sequences=1)
+    return result[0]['generated_text']
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=generate_blogpost,
+    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter blog topic here..."),
+    outputs="text",
+    title="Blog Post Generator",
+    description="Generate a detailed blog post for a given topic using GPT-2."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    iface.launch()