Update app.py

app.py

@@ -3,7 +3,7 @@ from langchain_groq import ChatGroq
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_core.tools import tool
-from typing import TypedDict, Annotated, List, Optional
+from typing import Optional
 import json
 
 # Configuration
@@ -24,32 +24,15 @@ class MedicalConfig:
 # Define tools with proper schemas
 @tool
 def order_lab_test(test_name: str, reason: str) -> str:
-    """Orders a lab test with specified parameters.
-    
-    Args:
-        test_name: Name of the lab test to order
-        reason: Clinical justification for the test
-        
-    Returns:
-        Confirmation message with test details
-    """
-    return f"Lab ordered: {test_name} ({reason})"
+    """Orders a lab test with specified parameters."""
+    return f"✅ Lab ordered: {test_name} ({reason})"
 
 @tool
 def prescribe_medication(name: str, dosage: str, frequency: str) -> str:
-    """Prescribes medication with specific dosage instructions.
-    
-    Args:
-        name: Name of the medication
-        dosage: Dosage amount (e.g., '500mg')
-        frequency: Administration frequency (e.g., 'every 6 hours')
-        
-    Returns:
-        Confirmation message with prescription details
-    """
-    return f"Prescribed: {name} {dosage} {frequency}"
+    """Prescribes medication with specific dosage instructions."""
+    return f"✅ Prescribed: {name} {dosage} {frequency}"
 
-# Initialize tools
+# Initialize tools and model
 tools = [order_lab_test, prescribe_medication, TavilySearchResults(max_results=3)]
 
 class MedicalAgent:
@@ -82,4 +65,57 @@ class MedicalAgent:
         except Exception as e:
             return f"Error processing action: {str(e)}"
 
-# Rest of the Streamlit UI code remains the same...
+# 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 form
+    with st.sidebar:
+        st.header("Patient Intake")
+        symptoms = st.multiselect("Symptoms", ["Fever", "Cough", "Chest Pain", "Shortness of Breath"])
+        medical_history = st.text_input("Medical History")
+        current_meds = st.text_input("Current Medications")
+        temp = st.number_input("Temperature (°C)", 35.0, 42.0, 37.0)
+        bp = st.text_input("Blood Pressure (mmHg)", "120/80")
+        
+        patient_data = {
+            "symptoms": symptoms,
+            "history": {
+                "conditions": medical_history,
+                "medications": current_meds
+            },
+            "vitals": {
+                "temp": temp,
+                "bp": bp
+            }
+        }
+    
+    # Main interface
+    st.title("AI-Powered Clinical Support System")
+    
+    # Analysis button
+    if st.button("Start Analysis", type="primary"):
+        with st.spinner("Analyzing patient data..."):
+            response = st.session_state.agent.analyze_patient(patient_data)
+            
+            if response:
+                st.subheader("Clinical Recommendations")
+                
+                # Check for tool calls
+                if hasattr(response, 'tool_calls') and response.tool_calls:
+                    for action in response.tool_calls:
+                        result = st.session_state.agent.process_action({
+                            "name": action['name'],
+                            "args": action['args']
+                        })
+                        st.success(result)
+                else:
+                    st.info("No specific actions recommended. Clinical Summary:")
+                    st.write(response.content)
+
+if __name__ == "__main__":
+    main()