Update src/services/ai_modal_engine.py

src/services/ai_modal_engine.py

@@ -1,49 +1,23 @@
 import google.generativeai as genai
-import csv
-import io
 import traceback
 from ..config import db, get_user_keys
 
 class AiModalEngine:
-    @staticmethod
-    def context_to_csv(trades):
-        """Serializes trade list to token-efficient CSV format."""
-        if not trades or not isinstance(trades, list):
-            return str(trades)
-            
-        output = io.StringIO()
-        if len(trades) > 0:
-            # Extract headers from first record
-            keys = trades[0].keys()
-            writer = csv.DictWriter(output, fieldnames=keys)
-            writer.writeheader()
-            writer.writerows(trades)
-        
-        return output.getvalue()
-
     @staticmethod
     def initialize_firebase_session(uid, context):
-        """Bootstraps Auditor session and persists initial state to Firestore."""
+        """
+        Bootstraps Auditor session.
+        Args:
+            uid: User ID.
+            context: Raw CSV string provided by frontend.
+        """
         try:
             keys = get_user_keys(uid)
             api_key = keys.get('gemini_key')
             if not api_key: 
                 return "Error: No API Key found in Settings."
 
-            genai.configure(api_key=api_key)
-            
-            # Compression threshold: 20k characters
-            threshold = 20000
-            is_large_data = len(str(context)) > threshold
-            
-            # Toggle data format based on payload size
-            if is_large_data and isinstance(context, list):
-                clean_context = AiModalEngine.context_to_csv(context)
-                data_label = "STRUCTURED CSV DATA"
-            else:
-                clean_context = str(context)
-                data_label = "FILTERED TRADE LOGS"
-
+            genai.configure(api_key=api_key) 
             instruction = f"""
             PARSONA:
             You are the QuantVAT AI Trading Journal Auditor, a senior Risk Manager and Trading Psychologist with 50 years trading experience like a Market Wizard. 
@@ -59,21 +33,21 @@ class AiModalEngine:
             4. NO TABLES: Use bullet points only.
             5. INTERACTION: End with a provocative question about a specific trade.
 
-            {data_label}:
-            {clean_context}
+            TRADING LEDGER (CSV FORMAT):
+            {context}
             """
 
-            # Initialize model with embedded system instructions
             model = genai.GenerativeModel(
-                model_name='gemini-flash-latest',
+                model_name='gemini-3-flash-preview',
                 system_instruction=instruction
             )
             
             chat = model.start_chat(history=[])
-            prompt = "Analyze my execution performance. End with: 'I have analyzed your data. Ready for audit.'"
+            # Priming prompt to force immediate analysis
+            prompt = "Analyze my execution performance based on the CSV data above. End with: 'I have analyzed your data. Ready for audit.'"
             response = chat.send_message(prompt)
             
-            # Persist turn history to database
+            #  Persist initial state to Firestore for session continuity
             history = [
                 {"role": "user", "parts": [prompt]}, 
                 {"role": "model", "parts": [response.text]}
@@ -87,7 +61,9 @@ class AiModalEngine:
 
     @staticmethod
     def continue_firebase_chat(uid, prompt):
-        """Resumes active session using state retrieved from Firestore."""
+        """
+        Resumes active session using state retrieved from Firestore.
+        """
         try:
             user_doc = db.collection('users').document(uid).get()
             data = user_doc.to_dict() if user_doc.exists else {}
@@ -99,16 +75,16 @@ class AiModalEngine:
 
             genai.configure(api_key=api_key)
             
-            # Re-apply persona constraints for session continuity
+            #  Re-assert persona for stateless continuity
             model = genai.GenerativeModel(
-                model_name='gemini-flash-latest',
-                system_instruction="PARSONA: QuantVAT AI Trading Journal Auditor. Senior Risk Manager and Trading Psychologist with 50 years trading experience like a Market Wizard."
+                model_name='gemini-3-flash-preview',
+                system_instruction="PARSONA: QuantVAT AI Trading Journal Auditor. Senior Risk Manager."
             )
             
             chat = model.start_chat(history=history)
             response = chat.send_message(prompt)
             
-            # Sync new turn to database
+            # Append new turn and sync to DB
             history.append({"role": "user", "parts": [prompt]})
             history.append({"role": "model", "parts": [response.text]})
             db.collection('users').document(uid).set({"ai_history": history}, merge=True)