Update app.py

app.py

@@ -9,24 +9,23 @@ subprocess.check_call(["pip", "install", "-q", "gradio", "transformers", "python
 #!pip install python-dotenv
 
 import gradio as gr
-from transformers import TFAutoModelForCausalLM, AutoTokenizer
-import openai
+from transformers import GPTNeoForCausalLM, AutoTokenizer
 
-from dotenv import load_dotenv
-import os
-load_dotenv() # load environment variables from .env file
-api_key = os.getenv("OPENAI_API_KEY") # access the value of the OPENAI_API_KEY environment variable
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
+model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-2.7B")
+
+def generate_text(prompt):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    output = model.generate(input_ids, max_length=1024, temperature=0.5, do_sample=True)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
 
-def openai_chat(prompt):
- completions = openai.Completion.create( engine="text-davinci-003",prompt=prompt,max_tokens=1024,n=1,temperature=0.5,)
- message = completions.choices[0].text
- return message.strip()
-    
 def chatbot(input, history=[]):
- output = openai_chat(input)
- history.append((input, output))
- return history, history
+    output = generate_text(input)
+    history.append((input, output))
+    return history, history
 
-gr.Interface(fn = chatbot,
-inputs = ["text",'state'],
-outputs = ["chatbot",'state']).launch(debug = True)
+gr.Interface(
+    fn=chatbot,
+    inputs=["text", "state"],
+    outputs=["chatbot", "state"]
+).launch(debug=True)