Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+# Load pretrained GPT-2 model and tokenizer
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
+
+# Function to generate script
+def generate_script(title):
+    # Add a context prompt to the title
+    prompt = "Title: " + title + "\n\nScript:"
+
+    # Tokenize the prompt
+    input_ids = tokenizer.encode(prompt, return_tensors="pt", max_length=1024, truncation=True)
+
+    # Generate text based on the prompt
+    output = model.generate(input_ids, max_length=200, num_return_sequences=1, temperature=0.7)
+
+    # Decode generated text and return
+    script = tokenizer.decode(output[0], skip_special_tokens=True)
+    return script
+
+# Create Gradio interface
+title_input = gr.inputs.Textbox(lines=2, label="Enter Title")
+script_output = gr.outputs.Textbox(label="Generated Script")
+
+gr.Interface(generate_script, title_input, script_output, title="Script Generator", description="Generate a script based on the provided title.").launch()