Update app.py

app.py

@@ -1,26 +1,29 @@
 import gradio as gr
-import openai
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# Replace the placeholder text with your actual OpenAI API key
-openai.api_key = "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"
+# Load pre-trained GPT-2 model and tokenizer
+model_name = "google/gemma-7b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-def chat_with_gpt3(prompt):
-    response = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages=[
-            {"role": "system", "content": "You are a helpful assistant."},
-            {"role": "user", "content": prompt},
-        ],
-    )
-    return response.choices[0].message["content"]
+# Define function for generating response
+def generate_response(prompt):
+    # Tokenize input prompt
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
 
-interface = gr.Interface(
-    fn=chat_with_gpt3,
+    # Generate response from model
+    output = model.generate(input_ids, max_length=50, num_return_sequences=1, temperature=0.9)
+
+    # Decode response tokens
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+
+    return response
+
+gr.Interface(
+    fn=generate_response,
     inputs=gr.Textbox(lines=2, placeholder="Enter your message here..."),
     outputs="text",
-    title="Akhil's Basic Chatbot (powered by GPT-3.5 Turbo)",
-    description="This is a chatbot using OpenAI's GPT-3.5 Turbo. Ask it anything!",
-)
-
-if __name__ == "__main__":
-    interface.launch(share=True)
+    title="Akhil's Chatbot (powered by GPT2)",
+    description="This is a Basuc chatbot using OpenAI's GPT2. Ask it anything!",
+    theme="compact"
+).launch()