Update app.py

complete rework

app.py

@@ -1,32 +1,47 @@
-# Define the conversation history variable
-conversation_history = ""
+import openai
+import gradio as gr
 
-# Define the OpenAI chat function
-def chat(text):
-    # Access the global conversation history variable
-    global conversation_history
-    
-    # Update the conversation history with the latest input
-    conversation_history += f"User: {text}\nAI: "
-    
-    # Set up the OpenAI prompt with the full conversation history
-    prompt = conversation_history
-    
-    # Call the OpenAI API to generate a response
+# Set up OpenAI API credentials
+openai.api_key = OPENAPI_KEY
+
+# Set up the GPT-3 model
+model_engine = "gpt-3.5-turbo-0301"
+prompt = (
+    "I want you to act as a math teacher. I will provide some mathematical equations or concepts, "
+    "and it will be your job to explain them in easy-to-understand terms. This could include providing "
+    "step-by-step instructions for solving a problem, demonstrating various techniques with visuals or "
+    "suggesting online resources for further study. My first request is \"I need help understanding how "
+    "probability works.\""
+)
+temperature = 0.7
+max_tokens = 1000
+context_length = 2
+
+# Define the function that generates the response
+def generate_response(prompt):
     response = openai.Completion.create(
-        engine="gpt-3.5-turbo-0301",
+        engine=model_engine,
         prompt=prompt,
-        max_tokens=1024,
-        n=1,
-        stop=["\n", ".", "?", "!"],
-        temperature=0.7,
+        temperature=temperature,
+        max_tokens=max_tokens,
+        n = 1,
+        stop=None,
+        frequency_penalty=0,
+        presence_penalty=0,
+        context=context_length * [prompt],
     )
-    
-    # Extract the response text from the OpenAI API result
-    message = response.choices[0].text.strip()
-    
-    # Update the conversation history with the latest response
-    conversation_history += f"{message}\n"
-    
-    # Return the response to the user
-    return message
+
+    return response.choices[0].text.strip()
+
+# Set up the Gradio interface
+io = gr.Interface(
+    generate_response,
+    "textbox",
+    "textbox",
+    title="Chat with a Math Teacher",
+    description="Type a math question or concept that you need help understanding, and the math teacher will explain it to you in easy-to-understand terms!",
+    article="This app uses the GPT-3 language model to generate responses. The math teacher is programmed to provide step-by-step instructions for solving a problem, demonstrate various techniques with visuals, or suggest online resources for further study. Please keep in mind that this is an AI language model and may not always provide accurate or complete information.",
+)
+
+# Launch the interface
+io.launch()