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import streamlit as st
from langchain_groq import ChatGroq
from langchain_community.tools.tavily_search import TavilySearchResults
from langchain_core.messages import HumanMessage, SystemMessage
from typing import TypedDict, Annotated, List
# Configuration
class MedicalConfig:
SYSTEM_PROMPT = """You are an AI clinical assistant. Follow these rules:
1. Analyze patient data using latest medical guidelines
2. Always check for drug interactions
3. Suggest tests only when necessary
4. Use structured actions:
- order_lab_test: {test_name, reason}
- prescribe_medication: {name, dosage, frequency}"""
# State Management
class AgentState(TypedDict):
messages: Annotated[List[dict], lambda l, r: l + r]
patient_data: dict
class MedicalAgent:
def __init__(self):
self.model = ChatGroq(temperature=0.1, model="Llama-3.3-70b-Specdec")
self.tools = {
"medical_actions": {
"order_lab_test": self.order_lab_test,
"prescribe_medication": self.prescribe_medication
},
"research": TavilySearchResults(max_results=3)
}
def analyze_patient(self, patient_data):
response = self.model.invoke([
SystemMessage(content=MedicalConfig.SYSTEM_PROMPT),
HumanMessage(content=f"Patient Data: {patient_data}")
])
return response
def process_action(self, action):
if action['name'] in self.tools['medical_actions']:
return self.tools['medical_actions'][action['name']](action['args'])
return "Unknown action"
def order_lab_test(self, params):
return f"Lab ordered: {params['test_name']} ({params['reason']})"
def prescribe_medication(self, params):
return f"Prescribed: {params['name']} {params['dosage']} {params['frequency']}"
# Streamlit UI
def main():
st.set_page_config(page_title="AI Clinic", layout="wide")
# Initialize agent
if 'agent' not in st.session_state:
st.session_state.agent = MedicalAgent()
# Patient intake
with st.sidebar:
st.header("Patient Intake")
patient_data = {
"symptoms": st.multiselect("Symptoms", ["Fever", "Cough", "Chest Pain"]),
"history": {
"conditions": st.text_input("Medical History"),
"medications": st.text_input("Current Medications")
},
"vitals": {
"temp": st.number_input("Temp (°C)", 35.0, 42.0, 37.0),
"bp": st.text_input("BP (mmHg)", "120/80")
}
}
# Main interface
st.title("AI-Powered Clinical Support System")
if st.button("Start Analysis"):
with st.spinner("Analyzing patient data..."):
response = st.session_state.agent.analyze_patient(patient_data)
if hasattr(response, 'tool_calls'):
for action in response.tool_calls:
result = st.session_state.agent.process_action(action)
st.success(result)
else:
st.info(response.content)
if __name__ == "__main__":
main() |