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import streamlit as st
from groq import Client
# API Key Configuration (Use environment variables in production)
GROQ_API_KEY = "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"
def main():
st.set_page_config(page_title="🧠 AI ассистент врача-невролога", layout="wide")
st.title("🧠 AI ассистент врача-невролога")
# Load chatbot model
@st.cache_resource
def load_model():
return Client(api_key=GROQ_API_KEY)
chatbot = load_model()
# Strict system prompt with appointment booking feature
system_prompt = {
"role": "system",
"content": ("You are a professional neurology assistant. Your role is to provide accurate and up-to-date medical insights related to neurological disorders, brain health, symptoms, treatments, and neuroscience research."
" Always ensure that responses are factual, empathetic, and professional. If a query is **unrelated to neurology** or medical concerns, politely redirect the user by saying: 'I specialize in neurology-related assistance. Let me know how I can help with your neurological health concerns.'"
" If a user wants to book an appointment with a neurologist, ask for their preferred date, time, and location. Provide a confirmation message once details are received. Ответы прошу давать на русском языке")
}
# Initialize chat history
if "messages" not in st.session_state:
st.session_state["messages"] = [system_prompt]
# Display chat history (excluding system message)
for message in st.session_state["messages"]:
if message["role"] != "system":
with st.chat_message(message["role"]):
st.markdown(message["content"])
# User input
user_input = st.chat_input("Прошу здесь задавать вопросы по неврологии..")
if user_input:
# Add user message to session state
st.session_state["messages"].append({"role": "user", "content": user_input})
with st.chat_message("user"):
st.markdown(user_input)
# Generate response with strict system prompt
response = chatbot.chat.completions.create(
model="llama-3.3-70b-versatile",
messages=[system_prompt] + st.session_state["messages"] # Always include system prompt
)
bot_response = response.choices[0].message.content
# Add assistant's response to session state
st.session_state["messages"].append({"role": "assistant", "content": bot_response})
with st.chat_message("assistant"):
st.markdown(bot_response)
if __name__ == "__main__":
main()
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