.

app.py

@@ -1,27 +1,27 @@
+import openai
 import gradio as gr
-import google.generativeai as genai
 import os
 
-# Set up Gemini API key
-api_key = os.getenv("GEMINI_API_KEY")
+def chat_with_openai(prompt, history=[]):
+    messages = [{"role": "system", "content": "You are a helpful assistant."}]
+    for user_msg, bot_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        messages.append({"role": "assistant", "content": bot_msg})
+    messages.append({"role": "user", "content": prompt})
+    
+    response = openai.ChatCompletion.create(
+        model="gpt-4",  # Change to "gpt-4" if needed
+        messages=messages
+    )
+    return response["choices"][0]["message"]["content"]
 
-def chat_with_ai(prompt):
-    """Simple chatbot using Google's Gemini AI."""
-    if not api_key:
-        return "Error: API key missing. Set GEMINI_API_KEY in Hugging Face secrets."
-    try:
-        genai.configure(api_key=api_key)
-        available_models = [m.name for m in genai.list_models()]
-        model_name = "gemini-pro" if "gemini-pro" in available_models else available_models[0]
-        model = genai.GenerativeModel(model_name)
-        response = model.generate_content(prompt)
-        return response.text
-    except Exception as e:
-        return f"Error: {str(e)}"
+def chatbot_interface(user_input, chat_history):
+    response = chat_with_openai(user_input, chat_history)
+    chat_history.append((user_input, response))
+    return response, chat_history
 
-# Create Gradio chatbot interface
-iface = gr.ChatInterface(fn=chat_with_ai)
+# Create a Gradio interface
+demo = gr.ChatInterface(fn=chatbot_interface)
 
-# Launch the app
 if __name__ == "__main__":
-    iface.launch()
+    demo.launch()

requirements.txt

@@ -1,3 +1,2 @@
-google-generativeai
-gradio
-python-dotenv
+openai
+gradio