Update app.py

app.py

@@ -1,28 +1,33 @@
 import gradio as gr
-from transformers import pipeline
+import openai
 
-# Load the gpt2 like FLAN-T5 Large model
-generator = pipeline("text2text-generation", model="google/flan-t5-xxl")
+# Initialize the OpenAI API with your API key
+openai.api_key = "openai-api-key"
 
 def generate_text(prompt, max_length=100, temperature=1.0):
-    # Generate text using gpt2 like FLAN-T5 Large
-    result = generator(prompt, max_length=max_length, temperature=temperature, num_return_sequences=1)
-    return result[0]["generated_text"]
+    # Generate text using GPT-3
+    response = openai.Completion.create(
+        engine="text-davinci-003",  # You can also use other engines like "gpt-3.5-turbo"
+        prompt=prompt,
+        max_tokens=max_length,
+        temperature=temperature,
+        n=1,
+        stop=None
+    )
+    return response.choices[0].text.strip()
 
 # Create a Gradio interface
 iface = gr.Interface(
     fn=generate_text,
     inputs=[
         gr.Textbox(lines=3, placeholder="Enter your prompt here...", label="Prompt"),
-        gr.Slider(minimum=50, maximum=500, value=100, label="Max Length"),  # Use 'value' instead of 'default'
-        gr.Slider(minimum=0.1, maximum=1.5, value=1.0, label="Temperature"),  # Use 'value' instead of 'default'
+        gr.Slider(minimum=50, maximum=500, value=100, label="Max Length"),
+        gr.Slider(minimum=0.1, maximum=1.5, value=1.0, label="Temperature"),
     ],
     outputs=gr.Textbox(label="Generated Text"),
-    title="GPT2-Like FLAN-T5 Large Text Generator",
-    description="Enter a prompt and generate text using the GTP2-Like FLAN-T5 (LLM) Large Language Model."
+    title="GPT Text Generator",
+    description="Enter a prompt and generate text using the GPT model."
 )
 
 # Launch the interface
-iface.launch(share=True)
-
-
+iface.launch(share=True)