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Update app.py
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app.py
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import openai
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import gradio as gr
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import
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from functools import reduce
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# Remove the oldest user and assistant messages
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messages.pop(1)
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messages.pop(1)
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total_tokens = sum([len(msg["content"]) for msg in messages])
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return messages
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def CustomChatGPT(user_input):
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messages.append({"role": "user", "content": user_input})
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managed_messages = manage_conversation_history(messages)
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=managed_messages
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)
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ChatGPT_reply = response["choices"][0]["message"]["content"]
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messages.append({"role": "assistant", "content": ChatGPT_reply})
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return ChatGPT_reply
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description = "Check for ChatGPT outages <a href=https://status.openai.com/>here.</a>"
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demo = gr.Interface(
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fn=CustomChatGPT,
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inputs=gr.Textbox(label="Ask a question:", placeholder="E.g. What are gas fees? ...can you simplify that with an analogy?"),
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outputs=gr.Textbox(label="Answer:"),
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title=""
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)
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demo.launch(inline=True)
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import gradio as gr
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from transformers import pipeline
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def chat_with_gpt(input_text):
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model_name = "gpt-3.5-turbo" # Replace this with the appropriate GPT model you want to use.
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chat_gpt = pipeline("text-generation", model=model_name, device=0)
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generated_text = chat_gpt(input_text, max_length=150, do_sample=True, top_k=50, top_p=0.95)
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return generated_text[0]["generated_text"]
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# Gradio user interface
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input_text = gr.inputs.Textbox(lines=5, label="Your question about AI:")
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output_text = gr.outputs.Textbox(label="ChatGPT Response:")
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iface = gr.Interface(fn=chat_with_gpt, inputs=input_text, outputs=output_text, title="Chat with ChatGPT", description="Ask ChatGPT questions about AI.")
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iface.launch()
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