Update app.py

app.py

@@ -1,31 +1,30 @@
-import streamlit as st
+import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
-# Load model and tokenizer
-model_name = "gpt2"  # You can change this to your fine-tuned model
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+# Load a proper text-generation model
+model_name = "gpt2"  # Replace with your own trained model if available
 model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-# Create text-generation pipeline
-text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+# Create a text-generation pipeline
+nlp_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
-# Streamlit UI
-st.set_page_config(page_title="AI Text Generator", layout="centered")
-st.title("🧠 AI Text Generator")
-st.write("Enter a prompt and get AI-generated text!")
+# Function to generate response
+def generate_response(text):
+    try:
+        result = nlp_pipeline(text, max_length=50, do_sample=True)
+        return result[0]['generated_text']
+    except Exception as e:
+        return f"Error: {str(e)}"
 
-# Input box
-user_input = st.text_area("Enter your text prompt here:", height=150)
+# Gradio UI
+iface = gr.Interface(
+    fn=generate_response,
+    inputs="text",
+    outputs="text",
+    title="AI Text Generator",
+    description="Enter text and get AI-generated responses!"
+)
 
-# Generate button
-if st.button("Generate"):
-    if user_input.strip() != "":
-        with st.spinner("Generating..."):
-            try:
-                output = text_generator(user_input, max_length=100, do_sample=True)
-                st.success("Generated Text:")
-                st.write(output[0]["generated_text"])
-            except Exception as e:
-                st.error(f"Error: {str(e)}")
-    else:
-        st.warning("Please enter some text.")
+# Launch Gradio (Fix: Remove share=True, add enable_queue=True)
+iface.launch(server_name="0.0.0.0", server_port=7860)