Update agent.py

agent.py

@@ -12,13 +12,15 @@ from openai import OpenAI
 from models import AgentState, Message, ExtractedIntelligence
 
 # --- Configuration ---
-CALLBACK_URL = "https://hackathon.guvi.in/api/updateHoneyPotFinalResult" 
+CALLBACK_URL = "https://hackathon.guvi.in/api/updateHoneyPotFinalResult"
 HONEYPOT_API_KEY = os.environ.get("HONEYPOT_API_KEY", "sk_test_123456789")
 
-# OpenRouter configuration
+# Choose a specific, supported model instead of the router to avoid empty messages
+# Models like anthropic/claude-3-haiku or meta-llama/llama-3.1-8b-instruct are robust for classification
+OPENROUTER_MODEL = os.environ.get("OPENROUTER_MODEL", "anthropic/claude-3-haiku")
+
+# API key for OpenRouter
 OPENROUTER_API_KEY = os.environ.get("OPENROUTER_API_KEY")
-# Using a highly capable model for complex reasoning
-OPENROUTER_MODEL = os.environ.get("OPENROUTER_MODEL", "openrouter/free")
 
 client = OpenAI(
     base_url="https://openrouter.ai/api/v1",
@@ -26,21 +28,29 @@ client = OpenAI(
 )
 
 def call_openrouter(messages: List[Dict[str, str]], max_tokens: int = 512) -> str:
-    """Call the OpenRouter API to generate a text response."""
+    """
+    Call the OpenRouter API to generate a text response.
+    This version avoids reasoning tokens (which can leave message.content empty)
+    and checks for empty content, raising an error to trigger fallback logic.
+    """
     if not OPENROUTER_API_KEY:
         raise ValueError("OPENROUTER_API_KEY is not set.")
-    
-    try:
-        response = client.chat.completions.create(
-            model=OPENROUTER_MODEL,
-            messages=messages,
-            max_tokens=max_tokens,
-            extra_body={"reasoning": {"enabled": True}}
-        )
-        return response.choices[0].message.content
-    except Exception as e:
-        print(f"OpenRouter API error: {e}")
-        raise
+
+    response = client.chat.completions.create(
+        model=OPENROUTER_MODEL,
+        messages=messages,
+        max_tokens=max_tokens
+        # No extra_body to avoid reasoning tokens; reasoning can cause empty content:contentReference[oaicite:2]{index=2}
+    )
+
+    # Guard against empty responses: if no content, raise to trigger fallback
+    message_obj = response.choices[0].message
+    content = getattr(message_obj, "content", "")
+    if not content or not content.strip():
+        # Optionally, you could parse reasoning_details here, but that complicates your flow
+        raise ValueError("Empty model response from OpenRouter; check model or parameters.")
+
+    return content
 
 # --- LangGraph Nodes (Functions) ---
 
@@ -50,7 +60,7 @@ def detect_scam(state: AgentState) -> AgentState:
     text = latest_message.text
     is_scam = False
     reason = "No scam indicators found"
-    
+
     # Detailed prompt focusing on specific Indian scam vectors and subtle indicators
     prompt = (
         "You are a Senior Fraud Analyst specializing in Indian Cybercrime patterns. "
@@ -68,12 +78,13 @@ def detect_scam(state: AgentState) -> AgentState:
         "Respond ONLY in the format 'true|<reason>' if it is a scam or 'false|<reason>' if not. "
         f"Message: {text}"
     )
-    
+
     try:
         response = call_openrouter([{"role": "user", "content": prompt}], max_tokens=150)
         resp = (response or "").strip()
         if not resp:
             raise ValueError("OpenRouter returned empty response")
+
         first_line = resp.splitlines()[0].strip()
 
         # Expected format: true|<reason> or false|<reason>
@@ -99,8 +110,9 @@ def detect_scam(state: AgentState) -> AgentState:
 
         if not reason:
             reason = "OpenRouter classification did not provide a reason"
+
     except Exception as e:
-        print(f"OpenRouter classification error: {e}. Falling back to heuristic.")
+        # Fallback heuristic if the model fails or returns empty content
         lower_text = text.lower()
         scam_keywords = [
             "bank", "account", "blocked", "verify", "otp", "password", "upi", "urgent", "link", "update",
@@ -112,7 +124,7 @@ def detect_scam(state: AgentState) -> AgentState:
                 is_scam = True
                 reason = f"Keyword '{kw}' found in message (fallback)"
                 break
-                
+
     state["scamDetected"] = is_scam
     if "agentNotes" not in state:
         state["agentNotes"] = ""
@@ -127,7 +139,7 @@ def agent_persona_response(state: AgentState) -> AgentState:
         return state
 
     latest_text = state["conversationHistory"][-1].text
-    
+
     # Detailed prompt for persona engagement
     prompt = (
         "You are an AI Honeypot Agent. Your goal is to keep a scammer engaged to extract intelligence (UPI IDs, Bank Accounts, Links, Phone Numbers). "
@@ -140,13 +152,16 @@ def agent_persona_response(state: AgentState) -> AgentState:
         f"Scammer's latest message: {latest_text}\n\n"
         "Respond in under 40 words. Be polite and encouraging."
     )
-    
+
     try:
         response_text = call_openrouter([{"role": "user", "content": prompt}], max_tokens=150)
         response_text = response_text.strip().split('\n')[0]
-    except Exception as e:
-        print(f"OpenRouter persona generation error: {e}. Falling back to heuristic.")
-        response_text = "Sir, I am trying to do as you said but it is not working. Can you please guide me again? I don't want my account to be blocked."
+    except Exception:
+        # Fallback phrase if the model fails or returns empty content
+        response_text = (
+            "Sir, I am trying to do as you said but it is not working. "
+            "Can you please guide me again? I don't want my account to be blocked."
+        )
 
     agent_message = Message(
         sender="user",
@@ -349,8 +364,8 @@ def decide_engagement_end(state: AgentState) -> AgentState:
     continue_engagement = True
 
     # End if we have gathered significant actionable intelligence
-    if (len(intelligence.bankAccounts) > 0 or 
-        len(intelligence.upiIds) > 0 or 
+    if (len(intelligence.bankAccounts) > 0 or
+        len(intelligence.upiIds) > 0 or
         len(intelligence.phishingLinks) > 0):
         continue_engagement = False
 
@@ -368,13 +383,12 @@ def decide_engagement_end(state: AgentState) -> AgentState:
     state["should_continue_engagement"] = continue_engagement
     return state
 
-
 def final_callback(state: AgentState) -> AgentState:
     """Node 5: Sends the mandatory final result callback."""
     # If it's a scam and we haven't sent the callback yet, send it
     if not state["scamDetected"] or state.get("callbackSent", False):
         return state
-        
+
     intelligence = state.get("extractedIntelligence", ExtractedIntelligence())
     payload = {
         "sessionId": state.get("sessionId"),
@@ -383,12 +397,12 @@ def final_callback(state: AgentState) -> AgentState:
         "extractedIntelligence": intelligence.model_dump(),
         "agentNotes": state.get("agentNotes", "")
     }
-    
+
     headers = {
         "Content-Type": "application/json",
         "x-api-key": HONEYPOT_API_KEY
     }
-    
+
     try:
         response = requests.post(CALLBACK_URL, json=payload, headers=headers, timeout=10)
         response.raise_for_status()
@@ -397,11 +411,10 @@ def final_callback(state: AgentState) -> AgentState:
             state["agentNotes"] = ""
         state["agentNotes"] += "Final callback sent successfully. "
     except Exception as e:
-        print(f"Final callback failed: {e}")
         if "agentNotes" not in state:
             state["agentNotes"] = ""
         state["agentNotes"] += f"Final callback failed: {e}. "
-        
+
     return state
 
 def create_honeypot_graph(checkpoint_saver: BaseCheckpointSaver):