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import openai
import os
import gradio as gr
from openai import OpenAI
# Ensure the OPENAI_API_KEY environment variable is set
openai.api_key = os.getenv("OPENAI_API_KEY")
if openai.api_key is None:
raise ValueError("Die Umgebungsvariable OPENAI_API_KEY ist nicht gesetzt.")
client = OpenAI()
def chat_with_gpt(user_input, system_message, temperature, history):
if not history:
# If starting a new conversation, add the system message first
history = [{"role": "system", "content": system_message}]
# Append the latest user message
history.append({"role": "user", "content": user_input})
# Get response from GPT-3.5 Turbo
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=history,
temperature=temperature
)
# Append the assistant's response
assistant_message = response.choices[0].message['content']
history.append({"role": "assistant", "content": assistant_message})
return history, history # Return updated history for both display and state
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("### Chatte mit deinem Mini-Game")
with gr.Row():
system_message = gr.Textbox(value="Du bist ein dickköpfiger Bürokrat, der nicht hilfreich sein will.", label="Systemnachricht", placeholder="Gib hier die Systemnachricht ein...")
user_input = gr.Textbox(label="Deine Nachricht", placeholder="Gib hier deine Chatnachricht ein...")
temperature_slider = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.7, label="Temperatur")
submit_button = gr.Button("Senden")
chat_container = gr.Chatbot(label="Chatverlauf")
history_state = gr.State([]) # Using Gradio State to maintain conversation history
submit_button.click(fn=chat_with_gpt,
inputs=[user_input, system_message, temperature_slider, history_state],
outputs=[chat_container, history_state])
# Launch the Gradio app
demo.launch()
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