app.py

app.py

@@ -1,31 +1,22 @@
 
 
-import gradio 
-import graphics as gr
-
-# Create a text input
-text_input = gr.inputs.Textbox(lines=2, label="Enter your text:")
-
-# Create a text output
-text_output = gr.outputs.Textbox(label="ChatGPT Output:")
-
-# Create a button
-button = gradio.inputs.Button(label="Submit")
-
-# Create a form
-form = gr.Interface(
-    text_input,
-    button,
-    text_output,
-    title="ChatGPT",
-    description="Chat with a GPT-3 model"
-)
-
-# Define the function that will be called when the button is clicked
-def process_input(values):
-    text = values["text_input"]
-    response = chatgpt.chat(text)
-    return {"text_output": response}
-
-# Launch the form
-form.launch(process_input)
+import gradio as gr
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+# Initialize tokenizer and model
+tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
+model = GPT2LMHeadModel.from_pretrained('gpt2')
+
+# Create a function to generate text
+def generate_text(input_text):
+    # Encode the input text
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
+    # Generate the output text
+    output_ids = model.generate(input_ids, max_length=50, do_sample=True, top_k=50, top_p=0.95, num_return_sequences=1)
+    # Decode the output text
+    output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    return output_text
+
+# Create the interface
+gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Chat GPT").launch()