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from openai import OpenAI
import gradio as gr
def predict(message, history, api_key):
client = OpenAI(api_key=api_key)
history_openai_format = []
for human, assistant in history:
history_openai_format.append({"role": "user", "content": human})
history_openai_format.append({"role": "assistant", "content": assistant})
history_openai_format.append({"role": "user", "content": message})
response = client.chat.completions.create(
model='gpt-3.5-turbo',
messages=history_openai_format,
temperature=1.0,
stream=True
)
partial_message = ""
for chunk in response:
if chunk.choices[0].delta.content is not None:
partial_message += chunk.choices[0].delta.content
yield partial_message
def chat_with_api_key(api_key, message, history):
return predict(message, history, api_key)
with gr.Blocks() as demo:
api_key = gr.Textbox(label="API Key", placeholder="Enter your API key", type="password")
message = gr.Textbox(label="Message")
state = gr.State([])
output = gr.Textbox(label="Output")
def update_output(api_key, message, state):
response = chat_with_api_key(api_key, message, state)
state.append((message, response))
return response, state
btn = gr.Button("Submit")
btn.click(update_output, inputs=[api_key, message, state], outputs=[output, state])
demo.launch()
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