Update

.env

@@ -0,0 +1 @@
+OPENAI_API_KEY = org-TgJiwZlNrnXba0FGCx33ZaAs

app.py

@@ -1,20 +1,23 @@
 import gradio as gr
-from transformers import GPT2LMHeadModel, GPT2Tokenizer
+import openai
+import os
 
-# Load the pre-trained GPT-2 model and tokenizer
-model_name = "gpt2"  # You can change this to any other model like "gpt2-medium", "gpt2-large", etc.
-model = GPT2LMHeadModel.from_pretrained(model_name)
-tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+# Set your OpenAI API key
+openai.api_key = os.getenv("OPENAI_API_KEY")  # Make sure to set this environment variable in Hugging Face Spaces
 
-# Function to generate text
-def generate_text(input_text):
-    input_ids = tokenizer.encode(input_text, return_tensors="pt")
-    output = model.generate(input_ids, max_length=150, num_return_sequences=1, no_repeat_ngram_size=2, early_stopping=True)
-    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
-    return generated_text
+def generate_text(prompt):
+    response = openai.Completion.create(
+        engine="text-davinci-003",  # You can use other engines like "text-curie-001" or "text-babbage-001"
+        prompt=prompt,
+        max_tokens=150,
+        n=1,
+        stop=None,
+        temperature=0.7,
+    )
+    return response.choices[0].text.strip()
 
 # Create a Gradio interface
-iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="GPT-2 Text Generator", description="Enter a prompt to generate text using GPT-2.")
+iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="GPT-3 Text Generator", description="Enter a prompt to generate text using GPT-3.")
 
 # Launch the interface
-iface.launch(share=True)
+iface.launch(public=True)