Create app.py

app.py

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+
+import streamlit as st
+from transformers import pipeline
+
+# Page configuration
+st.set_page_config(
+    page_title="AI Text Generator",
+    page_icon="🤖",
+    layout="centered"
+)
+
+# Mandatory title: Name and Student ID
+st.title("Dawar Shariq | Student ID: B04-0923-000022")
+
+st.header("AI Text Generator")
+st.write(
+    "Enter a prompt and let the AI generate a continuation "
+    "using a pretrained Hugging Face model."
+)
+
+# Load and cache the model so it is not reloaded on every interaction
+MODEL_NAME = "distilgpt2"
+
+@st.cache_resource
+def load_model():
+    return pipeline(
+        "text-generation",
+        model=MODEL_NAME
+    )
+
+# Load the model
+with st.spinner("Loading AI model..."):
+    generator = load_model()
+
+st.success(f"Model loaded: {MODEL_NAME}")
+
+# Input widget
+prompt = st.text_area(
+    "Enter your starting text:",
+    placeholder="Artificial intelligence can help people...",
+    height=120
+)
+
+# Required feature: control maximum generated tokens
+max_new_tokens = st.slider(
+    "Maximum new tokens",
+    min_value=10,
+    max_value=200,
+    value=50,
+    step=10
+)
+
+# Button and model call
+if st.button("Generate Text", type="primary"):
+    if prompt.strip():
+        with st.spinner("Generating text..."):
+            result = generator(
+                prompt,
+                max_new_tokens=max_new_tokens,
+                num_return_sequences=1,
+                do_sample=True,
+                temperature=0.8,
+                pad_token_id=generator.tokenizer.eos_token_id
+            )
+
+        # Display only the generated continuation
+        full_text = result[0]["generated_text"]
+        continuation = full_text[len(prompt):]
+
+        st.subheader("Generated Continuation")
+        if continuation.strip():
+            st.write(continuation)
+        else:
+            st.write(full_text)
+
+    else:
+        st.warning("Please enter a prompt before generating text.")
+
+# Model information
+with st.expander("About this application"):
+    st.write("Model: distilgpt2")
+    st.write("Pipeline task: text-generation")
+    st.write("Framework: Hugging Face Transformers")
+    st.write("Interface: Streamlit")