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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10000个字以内"""
conv = Conversation(prompt, 5)
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])]
return responses, history
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(predict, [txt, state], [chatbot, state])
demo.launch() |