update app.py

app.py

@@ -1,25 +1,61 @@
-
+import openai
+import os
 import gradio as gr
+
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+
+class Conversation:
+    def __init__(self, prompt, num_of_round):
+        self.prompt = prompt
+        self.num_of_round = num_of_round
+        self.messages = []
+        self.messages.append({"role": "system", "content": self.prompt})
+
+    def ask(self, question):
+        try:
+            self.messages.append({"role": "user", "content": question})
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",
+                messages=self.messages,
+                temperature=0.5,
+                max_tokens=2048,
+                top_p=1,
+            )
+        except Exception as e:
+            print(e)
+            return e
+
+        message = response["choices"][0]["message"]["content"]
+        self.messages.append({"role": "assistant", "content": message})
+
+        if len(self.messages) > self.num_of_round * 2 + 1:
+            del self.messages[1:3]
+        return message
+
+
 prompt = """你是一个中国厨师，用中文回答做菜的问题。你的回答需要满足以下要求:
 1. 你的回答必须是中文
 2. 回答限制在100个字以内"""
 
-conv = Conversation(prompt, 10)
+conv = Conversation(prompt, 5)
 
-def answer(question, history=[]):
-    history.append(question)
-    response = conv.ask(question)
+
+def predict(input, history=[]):
+    history.append(input)
+    response = conv.ask(input)
     history.append(response)
-    responses = [(u,b) for u,b in zip(history[::2], history[1::2])]
+    responses = [(u, b) for u, b in zip(history[::2], history[1::2])]
     return responses, history
 
-with gr.Blocks(css="#chatbot{height:300px} .overflow-y-auto{height:500px}") as demo:
+
+with gr.Blocks(css="#chatbot{height:350px} .overflow-y-auto{height:500px}") as demo:
     chatbot = gr.Chatbot(elem_id="chatbot")
     state = gr.State([])
 
     with gr.Row():
         txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
 
-    txt.submit(answer, [txt, state], [chatbot, state])
+    txt.submit(predict, [txt, state], [chatbot, state])
 
-demo.launch()
+demo.launch()