Update app.py

app.py

@@ -1,29 +1,25 @@
 import subprocess
-subprocess.check_call(["pip", "install", "-q", "gradio", "transformers", "python-dotenv", "torch"])
-#!pip install -q gradio
-#!pip install gradio
-#!pip install --quiet gradio
-#!pip install transformers
-#!pip install python-dotenv
-
 import gradio as gr
-from transformers import GPTNeoForCausalLM, AutoTokenizer
+from transformers import TFAutoModelForCausalLM, AutoTokenizer
+import openai
+from dotenv import load_dotenv
+import os
 
-tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
-model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-2.7B")
+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
 
-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 = generate_text(input)
+    output = openai_chat(input)
     history.append((input, output))
     return history, history
 
-gr.Interface(
-    fn=chatbot,
-    inputs=["text", "state"],
-    outputs=["chatbot", "state"]
-).launch(debug=True)
+title = "My Chatbot Title"
+inputs = ["text", "state"]
+outputs = ["chatbot", "state"]
+interface = gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title=title)
+interface.launch(debug=True)