Update app.py

app.py

@@ -1,61 +1,56 @@
-# from transformers import AutoModelForCausalLM, AutoTokenizer
-# import gradio as gradio
-# import torch
-# title = "🤖AI ChatBot"
-# description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
-# examples = [["How are you?"]]
-# tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
-# model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
-# def predict(input, history=[]):    
-#     # tokenize the new input sentence    
-#     new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors="pt"    )    
-#     # append the new user input tokens to the chat history    
-#     bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)    
-#     # generate a response    
-#     history = model.generate(bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id).tolist()    
-#     # convert the tokens to text, and then split the responses into lines    
-#     response = tokenizer.decode(history[0]).split("<|endoftext|>")    
-#     # print('decoded_response-->>'+str(response))    
-#     response = [(response[i], response[i + 1]) for i in range(0,len(response) - 1, 2)]  
-#     # convert to tuples of list    
-#     # print('response-->>'+str(response))    
-#     return response, history
-# gradio.Interface(fn=predict,title=title,description=description,examples=examples,inputs=["text", "state"],outputs=["chatbot", "state"],theme="finlaymacklon/boxy_violet",).launch(share=True)
-
-
-
-import gradio  as gr
-def add_text(history, text):
-    global messages  #message[list] is defined globally
-    history = history + [(text,'')]
-    messages = messages + [{"role":'user', 'content': text}]
-    return history, ""
-def generate_response(history, model):
-        global messages
-
-        response = openai.ChatCompletion.create(
-            model = model,
-            messages=messages,
-            temperature=0.2,
-        )
-
-        response_msg = response.choices[0].message.content
-        messages = messages + [{"role":'assistant', 'content': response_msg}]
+import openai
+import os
+import gradio as gr
+
+# 设置 OpenAI API 密钥
+openai.api_key = "sk-NYsoG3VBKDiTuvdtC969F95aFc4f45379aD3854a93602327"
+
+class Conversation:
+    def __init__(self, prompt, num_of_round):
+        self.prompt = prompt
+        self.num_of_round = num_of_round
+        self.messages = [{"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 str(e)
         
-        for char in response_msg:
-            history[-1][1] += char
-            #time.sleep(0.05)
-            yield history
-
-
-with gr.Blocks() as demo:
-    radio = gr.Radio(value='gpt-3.5-turbo', choices=['gpt-3.5-turbo','gpt-4'], label='models')
-    chatbot = gr.Chatbot(value=[],elem_id="chatbot")
+        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]  # 移除第一轮对话
+        return message
+
+
+prompt = """你是一个大数据和AI领域的专家，用中文回答大数据和AI的相关问题。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, 6)
+def answer(question, history=[]):
+    history.append(question)
+    message = conv.ask(question)
+    history.append(message)
+    responses = [(u,b) for u,b in zip(history[::2], history[1::2])]
+    print(responses)
+    return responses, history
+with gr.Blocks(css="#chatbot{height:300px} .overflow-y-auto{height:500px}") as rxbot:
+    chatbot = gr.Chatbot(elem_id="chatbot")
+    state = gr.State([])
     with gr.Row():
-        with gr.Column(scale=1):
-            txt = gr.Textbox(show_label=False,placeholder="Enter text and press enter",) 
+        txt = gr.Textbox(show_label=False, placeholder="请输入你的问题").style(container=False)
+    txt.submit(answer, [txt, state], [chatbot, state])
+    
+rxbot.launch()
+
 
-    txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-            generate_response, inputs =[chatbot,radio],outputs = chatbot,)
-            
-demo.queue()