Fix: chat_history addition

agents/agent_helpers.py

@@ -7,7 +7,7 @@ def format_history_for_prompt(chat_history: list = None) -> str:
     
     history_for_prompt = ""
     for turn in chat_history:
-        # Ensure 'parts' is a list and not empty before accessing
+        #  Ensure 'parts' is a list and not empty before accessing
         if turn.get('parts') and isinstance(turn.get('parts'), list):
             role = "User" if turn['role'] == 'user' else "AI"
             history_for_prompt += f"{role}: {turn['parts'][0]}\n"

agents/router_agent.py

@@ -294,46 +294,72 @@ class RouterAgent:
         self.quiz_agent = QuizAgent(gemini_model)
         self.viva_agent = VivaAgent(gemini_model)
         self.default_agent = self.academic_agent
-
+    
     def route_query(self, query: str, file_context: str = "", viva_state: dict = None, chat_history: list = None):
+            """
+        Determines the user's intent and routes the query with all necessary
+        context to the correct specialist agent.
         """
-        Determines the user's intent and routes the query to the correct agent.
+            query_lower = query.lower()
+
+            # --- Intent Detection Logic ---
+            if viva_state and viva_state.get('active'):
+                return self.viva_agent.process_query(query, file_context, viva_state)
+            if any(cmd in query_lower for cmd in ["viva", "interview", "start viva"]):
+                return self.viva_agent.process_query(query, file_context, viva_state)
+
+            if any(cmd in query_lower for cmd in ["mnemonic", "memory aid", "remember"]):
+                return self.mnemonic_agent.process_query(query, file_context, chat_history)
+
+            if any(cmd in query_lower for cmd in ["quiz", "test me", "flashcard"]):
+                return self.quiz_agent.process_query(query, file_context, chat_history)
+
+            if any(cmd in query_lower for cmd in ["drug", "medicine", "medication", "side effect", "dosage"]):
+                return self.drug_info_agent.process_query(query, file_context, chat_history)
+
+            # Default to Academic Agent for general queries, passing all context
+            return self.academic_agent.process_query(query, file_context, chat_history)
+
+
+    # def route_query(self, query: str, file_context: str = "", viva_state: dict = None, chat_history: list = None):
+    #     """
+    #     Determines the user's intent and routes the query to the correct agent.
         
-        Args:
-            query (str): The user's input query.
-            file_context (str): Text content from any uploaded files.
-            viva_state (dict): The current state of the viva session.
+    #     Args:
+    #         query (str): The user's input query.
+    #         file_context (str): Text content from any uploaded files.
+    #         viva_state (dict): The current state of the viva session.
 
-        Returns:
-            dict: The response dictionary from the selected agent.
-        """
-        query_lower = query.lower()
+    #     Returns:
+    #         dict: The response dictionary from the selected agent.
+    #     """
+    #     query_lower = query.lower()
 
-        # --- Intent Detection Logic ---
+    #     # --- Intent Detection Logic ---
 
-        # 1. Viva Agent: High priority to catch session-based commands
-        # If a viva session is active, or user wants to start/end one.
-        if viva_state and viva_state.get('active'):
-            # The VivaAgent itself handles all logic when a session is active
-            return self.viva_agent.process_query(query, file_context, viva_state)
-        if any(cmd in query_lower for cmd in ["viva", "interview"]):
-            return self.viva_agent.process_query(query, file_context, viva_state)
+    #     # 1. Viva Agent: High priority to catch session-based commands
+    #     # If a viva session is active, or user wants to start/end one.
+    #     if viva_state and viva_state.get('active'):
+    #         # The VivaAgent itself handles all logic when a session is active
+    #         return self.viva_agent.process_query(query, file_context, viva_state)
+    #     if any(cmd in query_lower for cmd in ["viva", "interview"]):
+    #         return self.viva_agent.process_query(query, file_context, viva_state)
 
-        # 2. Mnemonic Agent
-        if any(cmd in query_lower for cmd in ["mnemonic", "memory aid", "remember"]):
-            return self.mnemonic_agent.process_query(query, file_context,chat_history)
+    #     # 2. Mnemonic Agent
+    #     if any(cmd in query_lower for cmd in ["mnemonic", "memory aid", "remember"]):
+    #         return self.mnemonic_agent.process_query(query, file_context,chat_history)
 
-        # 3. Quiz Agent
-        if any(cmd in query_lower for cmd in ["quiz", "test me", "flashcard"]):
-            return self.quiz_agent.process_query(query, file_context,chat_history)
+    #     # 3. Quiz Agent
+    #     if any(cmd in query_lower for cmd in ["quiz", "test me", "flashcard"]):
+    #         return self.quiz_agent.process_query(query, file_context,chat_history)
 
-        # 4. Drug Info Agent
-        # Uses keywords and also checks for common drug endings like 'ol', 'in', 'am'
-        if any(cmd in query_lower for cmd in ["drug", "medicine", "medication", "side effect", "dosage", "interaction"]):
-            return self.drug_info_agent.process_query(query, file_context,chat_history)
-        if re.search(r'\b(paracetamol|ibuprofen|metformin|aspirin|amoxicillin)\b', query_lower):
-            return self.drug_info_agent.process_query(query, file_context)
+    #     # 4. Drug Info Agent
+    #     # Uses keywords and also checks for common drug endings like 'ol', 'in', 'am'
+    #     if any(cmd in query_lower for cmd in ["drug", "medicine", "medication", "side effect", "dosage", "interaction"]):
+    #         return self.drug_info_agent.process_query(query, file_context,chat_history)
+    #     if re.search(r'\b(paracetamol|ibuprofen|metformin|aspirin|amoxicillin)\b', query_lower):
+    #         return self.drug_info_agent.process_query(query, file_context)
 
-        # 5. Default to Academic Agent
-        # If no other intent is detected, it's likely a general academic question.
-        return self.academic_agent.process_query(query, file_context,chat_history)
+    #     # 5. Default to Academic Agent
+    #     # If no other intent is detected, it's likely a general academic question.
+    #     return self.academic_agent.process_query(query, file_context,chat_history)

app.py

@@ -443,36 +443,34 @@ class MyPharmaAI:
         self.quotes = load_quotes()
         self.file_processor = FileProcessor()
 
-    def process_query(self, query, user_name="Student", viva_state=None, uploaded_files=None,chat_history=None):
-        """Routes a user's query to the appropriate agent, handling context."""
-        try:
-            file_context = ""
-            if uploaded_files:
-                file_context = self.get_file_context(uploaded_files)
-            
-            # --- ADD THIS LINE FOR DEBUGGING ---
-            print(f"--- DEBUG: Here is the text extracted from the file ---\n{file_context[:1000]}\n--- END DEBUG ---")
-            
-            # Pass all context to the router
-            response_data = self.router.route_query(query, file_context, viva_state, chat_history)
-            
-            return {
-                'success': True,
-                **response_data # Unpack the dictionary from the agent
-            }
-        except Exception as e:
-            print(f"Error in MyPharmaAI.process_query: {e}")
-            return {
-                'success': False,
-                'message': f"माफ करें (Sorry), a critical error occurred: {str(e)}",
-                'agent_used': 'error'
-            }
+    def process_query(self, query, user_name="Student", viva_state=None, uploaded_files=None, chat_history=None):
+            """Routes a user's query to the appropriate agent, handling context."""
+            try:
+                # This block correctly gets the file content from the session data
+                file_context = ""
+                if uploaded_files:
+                    file_context = self.get_file_context(uploaded_files)
+                
+                # This passes the file content and chat history to the router
+                response_data = self.router.route_query(query, file_context, viva_state, chat_history)
+                
+                return {
+                    'success': True,
+                    **response_data
+                }
+            except Exception as e:
+                print(f"Error in MyPharmaAI.process_query: {e}")
+                return {
+                    'success': False,
+                    'message': f"Sorry, a critical error occurred: {str(e)}",
+                    'agent_used': 'error'
+                }
+
 
     def get_file_context(self, uploaded_files_session):
         """Extracts text from the most recent files to use as context."""
         context = ""
-        # Limit context to the last 3 uploaded files to manage token size
-        for file_info in uploaded_files_session[-3:]:
+        for file_info in uploaded_files_session[-3:]: # Limit to last 3 files
             file_path = file_info.get('path')
             if file_path and os.path.exists(file_path):
                 try:
@@ -523,7 +521,7 @@ def chat():
         uploaded_files = session.get('uploaded_files', None)
 
         # Process the query through the main orchestrator
-        result = pharma_ai.process_query(query, viva_state=viva_state, uploaded_files=uploaded_files,chat_history=chat_history)
+        result = pharma_ai.process_query(query, viva_state=viva_state, uploaded_files=uploaded_files,chathistory=chat_history)
         # If the query was successful, update the history
         if result.get('success'):
             # Add the user's query and the AI's message to the history