Update app.py

app.py

@@ -1,31 +1,31 @@
-import gradio as gr
+import streamlit as st
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
-# Load a proper text-generation model
-model_name = "gpt2"  # Replace with your own trained model if available
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Load model and tokenizer
+model_name = "gpt2"  # You can change this to your fine-tuned model
 tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-# Create a text-generation pipeline
-nlp_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-# 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)}"
+# Create text-generation pipeline
+text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
-# Gradio UI
-iface = gr.Interface(
-    fn=generate_response,
-    inputs="text",
-    outputs="text",
-    title="AI Text Generator",
-    description="Enter text and get AI-generated responses!"
-)
+# 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!")
 
-# Launch Gradio (Fix: Remove `share=True`, add `enable_queue=True`)
-iface.launch(server_name="0.0.0.0", server_port=7860)
+# Input box
+user_input = st.text_area("Enter your text prompt here:", height=150)
 
+# 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.")