Update agents/understanding.py

agents/understanding.py

@@ -22,7 +22,7 @@ def understanding_agent(anthropic_client, state: Dict[str, Any]) -> Dict[str, An
     # Get current messages
     messages = state.get("messages", [])
     
-    # Add agent-specific instructions
+    # Add agent-specific instructions as system parameter
     system_message = """
     You are an AI assistant specializing in understanding pharmaceutical data needs.
     Your job is to understand what data pipeline the user needs to create.
@@ -37,16 +37,21 @@ def understanding_agent(anthropic_client, state: Dict[str, Any]) -> Dict[str, An
     If you understand the request fully, summarize the user's intent and tag it as INTENT_COMPLETE.
     """
     
-    # Prepare prompt for Claude
-    prompt_messages = [
-        MessageParam(role="system", content=system_message),
-        *[MessageParam(role=m["role"], content=m["content"]) for m in messages]
-    ]
+    # Convert state messages to the format expected by Anthropic API
+    # Excluding any messages with role "system"
+    anthropic_messages = []
+    for msg in messages:
+        if msg["role"] != "system":  # Skip system messages
+            anthropic_messages.append(MessageParam(
+                role=msg["role"],
+                content=msg["content"]
+            ))
     
-    # Call Claude API
+    # Call Claude API with system message as separate parameter
     response = anthropic_client.messages.create(
         model="claude-3-7-sonnet-20250219",
-        messages=prompt_messages,
+        system=system_message,
+        messages=anthropic_messages,
         max_tokens=2000
     )
     
@@ -62,19 +67,4 @@ def understanding_agent(anthropic_client, state: Dict[str, Any]) -> Dict[str, An
         # Parse the structured intent from the response
         # This would be more sophisticated in production
         new_state["user_intent"] = {
-            "understood": True,
-            "description": agent_response.replace("INTENT_COMPLETE", "").strip(),
-            "time": time.time()
-        }
-        new_state["current_agent"] = "planning_agent"
-    else:
-        # Need more information, stay with understanding agent
-        new_state["current_agent"] = "understanding_agent"
-    
-    # Add agent's response to messages
-    new_messages = add_messages(state, [
-        {"role": "assistant", "content": agent_response.replace("INTENT_COMPLETE", "").strip()}
-    ])
-    new_state["messages"] = new_messages
-    
-    return new_state
+            "understood": T