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62 lines
2.2 KiB
Python
62 lines
2.2 KiB
Python
import os
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from openai import OpenAI
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import gradio as gr
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import logging as log
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from dotenv import load_dotenv
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load_dotenv()
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OPEN_API_KEY=os.getenv("OPENAI_API_KEY")
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CHAT_COMPLETION_ENDPOINT = os.getenv("CHAT_COMPLETION_ENDPOINT")
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MODEL_NAME = os.getenv("MODEL_NAME", "gpt-3.5-turbo")
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log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
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client = OpenAI(api_key=OPEN_API_KEY, base_url=CHAT_COMPLETION_ENDPOINT)
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def predict(message, history):
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# history_openai_format = []
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# for human, assistant in history:
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# history_openai_format.append({"role": "user", "content": human })
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# history_openai_format.append({"role": "assistant", "content":assistant})
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history.append({"role": "user", "content": message})
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log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
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log.info("history: ", history)
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try:
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response = client.chat.completions.create(model=MODEL_NAME,
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messages= history,
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temperature=1.0
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)
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except Exception as e:
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log.info(e)
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# remove last user message in case of exception
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history.pop()
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log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
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log.info("Error with OpenAI API: {}".format(e.message))
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raise gr.Error("Error with OpenAI API: {}".format(e.message))
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# for chunk in response:
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# if chunk.choices[0].delta.content is not None:
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# partial_message = partial_message + chunk.choices[0].delta.content
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# yield partial_message
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choices = response.choices
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message = choices[0].message
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content = message.content
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history.append({"role": "assistant", "content": content})
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history[-1]["model"] = response.model
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messages = [(history[i]["content"], history[i+1]["content"]) for i in range(0, len(history)-1, 2)]
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return messages, history
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with gr.Blocks(fill_height=True, css="footer {visibility: hidden}") as demo:
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print("Starting Demo...")
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chatbot = gr.Chatbot(label="Bolt Chatbot", scale=1)
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state = gr.State([])
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with gr.Row():
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txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter", scale=1, autofocus=True)
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txt.submit(predict, [txt, state], [chatbot, state])
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demo.launch(server_name="0.0.0.0", server_port=8080, show_error=True, debug=True)
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