Update app.py

app.py

@@ -1,25 +1,33 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import openai
 
-# Replace these with your desired model and tokenizer names
-model_name = "t5-small"
-tokenizer_name = "t5-small"
-
-tokenizer = AutoTokenizer.from_pretrained(tokenizer_name)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+# Set your OpenAI API key here
+openai.api_key = "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"  # Replace with your actual API key
 
 def generate_response(message):
-    input_ids = tokenizer(message, return_tensors="pt").input_ids
-    outputs = model.generate(input_ids)
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    try:
+        response = openai.Completion.create(
+            engine="text-davinci-003",  # Adjust model as needed
+            prompt=f"Question: {message}",
+            max_tokens=150,
+            n=1,
+            stop=None,  # No explicit stop sequences for chat-like interactions
+            temperature=0.7,
+        )
+        # Return the content of the response
+        return response.choices[0].text.strip()
+    except Exception as e:
+        return f"Error: {str(e)}"
 
+# Create the Gradio interface
 iface = gr.Interface(
     fn=generate_response,
     inputs=gr.Textbox(placeholder="Type your message here...", label="Message"),
     outputs="text",
-    title="Real-Time Chatbot with Hugging Face Transformers",
-    description="Ask any question or start a conversation.",
-    theme="dark",  # Optional: Use a dark theme
+    title="Real-Time Chatbot with GPT-3.5",
+    description="Ask any question or start a conversation. Powered by OpenAI GPT-3.5-turbo.",
+    theme="dark",  # Optional: Use a dark theme for a more modern look
 )
 
-iface.launch(debug=True)  # Set debug=True for detailed logging during development
+# Launch the interface
+iface.launch()