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import openai | |
from keys import mykey | |
import gradio as gr | |
# Set your OpenAI API key | |
openai.api_key = mykey["mediQ"] | |
# Chat function | |
def gpt_response(message, history=[]): | |
# Reformat history into proper OpenAI chat message format | |
messages = [ | |
{"role": "system", "content": "You are a careful and experienced clinical reasoning expert."} | |
] | |
for user_msg, bot_msg in history: | |
messages.append({"role": "user", "content": user_msg}) | |
messages.append({"role": "assistant", "content": bot_msg}) | |
messages.append({"role": "user", "content": message}) | |
# Call OpenAI GPT-4 | |
response = openai.ChatCompletion.create( | |
model="gpt-3.5-turbo", | |
messages=messages, | |
temperature=0.3, | |
max_tokens=300 | |
) | |
reply = response["choices"][0]["message"]["content"] | |
return reply | |
# Gradio chat interface | |
gr.ChatInterface( | |
fn=gpt_response, | |
title="🧠 MediQ GPT-4 Clinical Reasoning", | |
description="Ask a clinical question. GPT-4 will simulate adaptive expert reasoning.", | |
).launch() | |