add chat history

.env.example

@@ -1,12 +1,12 @@
 # make one like so https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key
 LANGFLOW_SECRET_KEY=
-# flow id from the the openrag flow json
+# flow id from the the openrag flow json (add the /flows/openrag_agent.json to your canva and get the flowid from the url)
 FLOW_ID=1098eea1-6649-4e1d-aed1-b77249fb8dd0
 # must match the hashed password in secureconfig, must change for secure deployment!!!
 OPENSEARCH_PASSWORD=OSisgendb1!
 # make here https://console.cloud.google.com/apis/credentials 
-GOOGLE_OAUTH_CLIENT_ID=
-GOOGLE_OAUTH_CLIENT_SECRET=
+GOOGLE_OAUTH_CLIENT_ID=287178119926-8t3co7hgnc5onv55k7hjv46qdcvbddfm.apps.googleusercontent.com
+GOOGLE_OAUTH_CLIENT_SECRET=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
 # Azure app registration credentials for SharePoint/OneDrive
 MICROSOFT_GRAPH_OAUTH_CLIENT_ID=
 MICROSOFT_GRAPH_OAUTH_CLIENT_SECRET=
@@ -20,3 +20,7 @@ AWS_SECRET_ACCESS_KEY=
 
 # OPTIONAL url for openrag link to langflow in the UI
 LANGFLOW_PUBLIC_URL=
+
+# Change the AUTO_LOGIN=False in .env
+LANGFLOW_SUPERUSER=langflow
+LANGFLOW_SUPERUSER_PASSWORD=langflow

frontend/components/navigation.tsx

@@ -85,6 +85,14 @@ export function Navigation() {
       if (!response.ok) {
         const errorText = await response.text()
         console.error("Upload failed:", errorText)
+        
+        // Trigger error event for chat page to handle
+        window.dispatchEvent(new CustomEvent('fileUploadError', { 
+          detail: { filename: file.name, error: 'Failed to process document' } 
+        }))
+        
+        // Trigger loading end event
+        window.dispatchEvent(new CustomEvent('fileUploadComplete'))
         return
       }
       
@@ -111,7 +119,7 @@ export function Navigation() {
       
       // Trigger error event for chat page to handle
       window.dispatchEvent(new CustomEvent('fileUploadError', { 
-        detail: { filename: file.name, error: error instanceof Error ? error.message : 'Unknown error' } 
+        detail: { filename: file.name, error: 'Failed to process document' } 
       }))
     }
   }

src/services/auth_service.py

@@ -14,6 +14,7 @@ from connectors.sharepoint.oauth import SharePointOAuth
 from connectors.google_drive import GoogleDriveConnector
 from connectors.onedrive import OneDriveConnector  
 from connectors.sharepoint import SharePointConnector
+from services.user_binding_service import user_binding_service
 
 class AuthService:
     def __init__(self, session_manager: SessionManager, connector_service=None):
@@ -208,7 +209,20 @@ class AuthService:
         if jwt_token:
             # Get the user info to create a persistent Google Drive connection
             user_info = await self.session_manager.get_user_info_from_token(token_data["access_token"])
-            user_id = user_info["id"] if user_info else None
+            google_user_id = user_info["id"] if user_info else None
+            
+            # Create or update user binding between Google ID and Langflow ID
+            if google_user_id and user_info:
+                try:
+                    print(f"[DEBUG] Creating/updating user binding for Google ID: {google_user_id}")
+                    binding_created = await user_binding_service.ensure_binding(google_user_id, user_info)
+                    if binding_created:
+                        print(f"[DEBUG] Successfully ensured user binding for Google ID: {google_user_id}")
+                    else:
+                        print(f"[DEBUG] Failed to create user binding for Google ID: {google_user_id}")
+                except Exception as e:
+                    print(f"[WARNING] Failed to create user binding for Google ID {google_user_id}: {e}")
+                    # Don't fail authentication if binding creation fails
             
             response_data = {
                 "status": "authenticated",
@@ -217,13 +231,13 @@ class AuthService:
                 "jwt_token": jwt_token  # Include JWT token in response
             }
             
-            if user_id:
+            if google_user_id:
                 # Convert the temporary auth connection to a persistent Google Drive connection
                 await self.connector_service.connection_manager.update_connection(
                     connection_id=connection_id,
                     connector_type="google_drive",
                     name=f"Google Drive ({user_info.get('email', 'Unknown')})",
-                    user_id=user_id,
+                    user_id=google_user_id,
                     config={
                         **connection_config.config,
                         "purpose": "data_source",
@@ -256,7 +270,11 @@ class AuthService:
         user = getattr(request.state, 'user', None)
         
         if user:
-            return {
+            # Get user binding info if available
+            binding_info = user_binding_service.get_binding_info(user.user_id)
+            langflow_user_id = user_binding_service.get_langflow_user_id(user.user_id)
+            
+            user_data = {
                 "authenticated": True,
                 "user": {
                     "user_id": user.user_id,
@@ -267,6 +285,15 @@ class AuthService:
                     "last_login": user.last_login.isoformat() if user.last_login else None
                 }
             }
+            
+            # Add binding information if available
+            if langflow_user_id:
+                user_data["user"]["langflow_user_id"] = langflow_user_id
+            if binding_info:
+                user_data["user"]["binding_created_at"] = binding_info.get("created_at")
+                user_data["user"]["binding_last_updated"] = binding_info.get("last_updated")
+            
+            return user_data
         else:
             return {
                 "authenticated": False,

src/services/chat_service.py

@@ -172,52 +172,105 @@ class ChatService:
         }
 
     async def get_langflow_history(self, user_id: str):
-        """Get langflow conversation history for a user"""
+        """Get langflow conversation history for a user - now fetches from both OpenRAG memory and Langflow database"""
         from agent import get_user_conversations
+        from services.langflow_history_service import langflow_history_service
+        from services.user_binding_service import user_binding_service
         
         if not user_id:
             return {"error": "User ID is required", "conversations": []}
         
-        conversations_dict = get_user_conversations(user_id)
+        all_conversations = []
         
-        # Convert conversations dict to list format with metadata
-        conversations = []
-        for response_id, conversation_state in conversations_dict.items():
-            # Filter out system messages
-            messages = []
-            for msg in conversation_state.get("messages", []):
-                if msg.get("role") in ["user", "assistant"]:
-                    message_data = {
-                        "role": msg["role"],
-                        "content": msg["content"],
-                        "timestamp": msg.get("timestamp").isoformat() if msg.get("timestamp") else None
-                    }
-                    if msg.get("response_id"):
-                        message_data["response_id"] = msg["response_id"]
-                    messages.append(message_data)
+        try:
+            # 1. Get in-memory OpenRAG conversations (current session)
+            conversations_dict = get_user_conversations(user_id)
             
-            if messages:  # Only include conversations with actual messages
-                # Generate title from first user message
-                first_user_msg = next((msg for msg in messages if msg["role"] == "user"), None)
-                title = first_user_msg["content"][:50] + "..." if first_user_msg and len(first_user_msg["content"]) > 50 else first_user_msg["content"] if first_user_msg else "New chat"
+            for response_id, conversation_state in conversations_dict.items():
+                # Filter out system messages
+                messages = []
+                for msg in conversation_state.get("messages", []):
+                    if msg.get("role") in ["user", "assistant"]:
+                        message_data = {
+                            "role": msg["role"],
+                            "content": msg["content"],
+                            "timestamp": msg.get("timestamp").isoformat() if msg.get("timestamp") else None
+                        }
+                        if msg.get("response_id"):
+                            message_data["response_id"] = msg["response_id"]
+                        messages.append(message_data)
                 
-                conversations.append({
-                    "response_id": response_id,
-                    "title": title,
-                    "endpoint": "langflow",
-                    "messages": messages,
-                    "created_at": conversation_state.get("created_at").isoformat() if conversation_state.get("created_at") else None,
-                    "last_activity": conversation_state.get("last_activity").isoformat() if conversation_state.get("last_activity") else None,
-                    "previous_response_id": conversation_state.get("previous_response_id"),
-                    "total_messages": len(messages)
-                })
+                if messages:  # Only include conversations with actual messages
+                    first_user_msg = next((msg for msg in messages if msg["role"] == "user"), None)
+                    title = first_user_msg["content"][:50] + "..." if first_user_msg and len(first_user_msg["content"]) > 50 else first_user_msg["content"] if first_user_msg else "New chat"
+                    
+                    all_conversations.append({
+                        "response_id": response_id,
+                        "title": title,
+                        "endpoint": "langflow",
+                        "messages": messages,
+                        "created_at": conversation_state.get("created_at").isoformat() if conversation_state.get("created_at") else None,
+                        "last_activity": conversation_state.get("last_activity").isoformat() if conversation_state.get("last_activity") else None,
+                        "previous_response_id": conversation_state.get("previous_response_id"),
+                        "total_messages": len(messages),
+                        "source": "openrag_memory"
+                    })
+            
+            # 2. Get historical conversations from Langflow database 
+            # (works with both Google-bound users and direct Langflow users)
+            print(f"[DEBUG] Attempting to fetch Langflow history for user: {user_id}")
+            langflow_history = await langflow_history_service.get_user_conversation_history(user_id)
+            
+            if langflow_history.get("conversations"):
+                    for conversation in langflow_history["conversations"]:
+                        # Convert Langflow format to OpenRAG format
+                        messages = []
+                        for msg in conversation.get("messages", []):
+                            messages.append({
+                                "role": msg["role"],
+                                "content": msg["content"],
+                                "timestamp": msg.get("timestamp"),
+                                "langflow_message_id": msg.get("langflow_message_id"),
+                                "source": "langflow"
+                            })
+                        
+                        if messages:
+                            first_user_msg = next((msg for msg in messages if msg["role"] == "user"), None)
+                            title = first_user_msg["content"][:50] + "..." if first_user_msg and len(first_user_msg["content"]) > 50 else first_user_msg["content"] if first_user_msg else "Langflow chat"
+                            
+                            all_conversations.append({
+                                "response_id": conversation["session_id"],
+                                "title": title,
+                                "endpoint": "langflow",
+                                "messages": messages,
+                                "created_at": conversation.get("created_at"),
+                                "last_activity": conversation.get("last_activity"),
+                                "total_messages": len(messages),
+                                "source": "langflow_database",
+                                "langflow_session_id": conversation["session_id"],
+                                "langflow_flow_id": conversation.get("flow_id")
+                            })
+                    
+                    print(f"[DEBUG] Added {len(langflow_history['conversations'])} historical conversations from Langflow")
+            elif langflow_history.get("error"):
+                print(f"[DEBUG] Could not fetch Langflow history for user {user_id}: {langflow_history['error']}")
+            else:
+                print(f"[DEBUG] No Langflow conversations found for user {user_id}")
         
-        # Sort by last activity (most recent first)
-        conversations.sort(key=lambda c: c["last_activity"], reverse=True)
+        except Exception as e:
+            print(f"[ERROR] Failed to fetch Langflow history: {e}")
+            # Continue with just in-memory conversations
+        
+        # Sort all conversations by last activity (most recent first)
+        all_conversations.sort(key=lambda c: c.get("last_activity", ""), reverse=True)
         
         return {
             "user_id": user_id,
             "endpoint": "langflow",
-            "conversations": conversations,
-            "total_conversations": len(conversations)
+            "conversations": all_conversations,
+            "total_conversations": len(all_conversations),
+            "sources": {
+                "memory": len([c for c in all_conversations if c.get("source") == "openrag_memory"]),
+                "langflow_db": len([c for c in all_conversations if c.get("source") == "langflow_database"])
+            }
         }

src/services/langflow_history_service.py

@@ -0,0 +1,310 @@
+"""
+Langflow Message History Service
+Retrieves message history from Langflow's database using user bindings
+"""
+
+import asyncio
+import httpx
+from typing import List, Dict, Optional, Any
+from datetime import datetime
+
+from config.settings import LANGFLOW_URL, LANGFLOW_KEY, LANGFLOW_SUPERUSER, LANGFLOW_SUPERUSER_PASSWORD
+from services.user_binding_service import user_binding_service
+
+
+class LangflowHistoryService:
+    """Service to retrieve message history from Langflow using user bindings"""
+    
+    def __init__(self):
+        self.langflow_url = LANGFLOW_URL
+        self.auth_token = None
+        
+    def _resolve_langflow_user_id(self, user_id: str) -> Optional[str]:
+        """Resolve user_id to Langflow user ID
+        
+        Args:
+            user_id: Either Google user ID or direct Langflow user ID
+            
+        Returns:
+            Langflow user ID or None
+        """
+        # First, check if this is already a Langflow user ID by checking UUID format
+        if self._is_uuid_format(user_id):
+            print(f"User ID {user_id} appears to be a Langflow UUID, using directly")
+            return user_id
+            
+        # Otherwise, try to get Langflow user ID from Google binding
+        langflow_user_id = user_binding_service.get_langflow_user_id(user_id)
+        if langflow_user_id:
+            print(f"Found Langflow binding for Google user {user_id}: {langflow_user_id}")
+            return langflow_user_id
+            
+        print(f"No Langflow user ID found for {user_id}")
+        return None
+        
+    def _is_uuid_format(self, user_id: str) -> bool:
+        """Check if string looks like a UUID (Langflow user ID format)"""
+        import re
+        # Basic UUID pattern check (with or without dashes)
+        uuid_pattern = r'^[0-9a-f]{8}-?[0-9a-f]{4}-?[0-9a-f]{4}-?[0-9a-f]{4}-?[0-9a-f]{12}$'
+        return bool(re.match(uuid_pattern, user_id.lower().replace('-', '')))
+        
+    async def _authenticate(self) -> Optional[str]:
+        """Authenticate with Langflow and get access token"""
+        if self.auth_token:
+            return self.auth_token
+            
+        if not all([LANGFLOW_SUPERUSER, LANGFLOW_SUPERUSER_PASSWORD]):
+            print("Missing Langflow superuser credentials")
+            return None
+            
+        try:
+            login_data = {
+                "username": LANGFLOW_SUPERUSER,
+                "password": LANGFLOW_SUPERUSER_PASSWORD
+            }
+            
+            async with httpx.AsyncClient() as client:
+                response = await client.post(
+                    f"{self.langflow_url.rstrip('/')}/api/v1/login",
+                    data=login_data,
+                    headers={"Content-Type": "application/x-www-form-urlencoded"}
+                )
+                
+                if response.status_code == 200:
+                    result = response.json()
+                    self.auth_token = result.get('access_token')
+                    print(f"Successfully authenticated with Langflow for history retrieval")
+                    return self.auth_token
+                else:
+                    print(f"Langflow authentication failed: {response.status_code}")
+                    return None
+                    
+        except Exception as e:
+            print(f"Error authenticating with Langflow: {e}")
+            return None
+            
+    async def get_user_sessions(self, user_id: str, flow_id: Optional[str] = None) -> List[str]:
+        """Get all session IDs for a user's conversations
+        
+        Args:
+            user_id: Either Google user ID or direct Langflow user ID
+        """
+        # Determine the Langflow user ID
+        langflow_user_id = self._resolve_langflow_user_id(user_id)
+        if not langflow_user_id:
+            print(f"No Langflow user found for user: {user_id}")
+            return []
+            
+        token = await self._authenticate()
+        if not token:
+            return []
+            
+        try:
+            headers = {"Authorization": f"Bearer {token}"}
+            params = {}
+            
+            if flow_id:
+                params["flow_id"] = flow_id
+                
+            async with httpx.AsyncClient() as client:
+                response = await client.get(
+                    f"{self.langflow_url.rstrip('/')}/api/v1/monitor/messages/sessions",
+                    headers=headers,
+                    params=params
+                )
+                
+                if response.status_code == 200:
+                    session_ids = response.json()
+                    
+                    # Filter sessions to only include those belonging to the user
+                    user_sessions = await self._filter_sessions_by_user(session_ids, langflow_user_id, token)
+                    print(f"Found {len(user_sessions)} sessions for user {user_id} (Langflow ID: {langflow_user_id})")
+                    return user_sessions
+                else:
+                    print(f"Failed to get sessions: {response.status_code} - {response.text}")
+                    return []
+                    
+        except Exception as e:
+            print(f"Error getting user sessions: {e}")
+            return []
+            
+    async def _filter_sessions_by_user(self, session_ids: List[str], langflow_user_id: str, token: str) -> List[str]:
+        """Filter session IDs to only include those belonging to the specified user"""
+        user_sessions = []
+        
+        try:
+            headers = {"Authorization": f"Bearer {token}"}
+            
+            async with httpx.AsyncClient() as client:
+                for session_id in session_ids:
+                    # Get a sample message from this session to check flow ownership
+                    response = await client.get(
+                        f"{self.langflow_url.rstrip('/')}/api/v1/monitor/messages",
+                        headers=headers,
+                        params={
+                            "session_id": session_id,
+                            "order_by": "timestamp"
+                        }
+                    )
+                    
+                    if response.status_code == 200:
+                        messages = response.json()
+                        if messages and len(messages) > 0:
+                            # Check if this session belongs to the user via flow ownership
+                            flow_id = messages[0].get('flow_id')
+                            if flow_id and await self._is_user_flow(flow_id, langflow_user_id, token):
+                                user_sessions.append(session_id)
+                                
+        except Exception as e:
+            print(f"Error filtering sessions by user: {e}")
+            
+        return user_sessions
+        
+    async def _is_user_flow(self, flow_id: str, langflow_user_id: str, token: str) -> bool:
+        """Check if a flow belongs to the specified user"""
+        try:
+            headers = {"Authorization": f"Bearer {token}"}
+            
+            async with httpx.AsyncClient() as client:
+                response = await client.get(
+                    f"{self.langflow_url.rstrip('/')}/api/v1/flows/{flow_id}",
+                    headers=headers
+                )
+                
+                if response.status_code == 200:
+                    flow_data = response.json()
+                    return flow_data.get('user_id') == langflow_user_id
+                    
+        except Exception as e:
+            print(f"Error checking flow ownership: {e}")
+            
+        return False
+        
+    async def get_session_messages(self, user_id: str, session_id: str) -> List[Dict[str, Any]]:
+        """Get all messages for a specific session"""
+        # Verify user has access to this session
+        langflow_user_id = self._resolve_langflow_user_id(user_id)
+        if not langflow_user_id:
+            return []
+            
+        token = await self._authenticate()
+        if not token:
+            return []
+            
+        try:
+            headers = {"Authorization": f"Bearer {token}"}
+            
+            async with httpx.AsyncClient() as client:
+                response = await client.get(
+                    f"{self.langflow_url.rstrip('/')}/api/v1/monitor/messages",
+                    headers=headers,
+                    params={
+                        "session_id": session_id,
+                        "order_by": "timestamp"
+                    }
+                )
+                
+                if response.status_code == 200:
+                    messages = response.json()
+                    
+                    # Verify user owns this session (security check)
+                    if messages and len(messages) > 0:
+                        flow_id = messages[0].get('flow_id')
+                        if not await self._is_user_flow(flow_id, langflow_user_id, token):
+                            print(f"User {user_id} does not own session {session_id}")
+                            return []
+                    
+                    # Convert to OpenRAG format
+                    return self._convert_langflow_messages(messages)
+                else:
+                    print(f"Failed to get messages for session {session_id}: {response.status_code}")
+                    return []
+                    
+        except Exception as e:
+            print(f"Error getting session messages: {e}")
+            return []
+            
+    def _convert_langflow_messages(self, langflow_messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """Convert Langflow messages to OpenRAG format"""
+        converted_messages = []
+        
+        for msg in langflow_messages:
+            try:
+                # Map Langflow message format to OpenRAG format
+                converted_msg = {
+                    "role": "user" if msg.get("sender") == "User" else "assistant",
+                    "content": msg.get("text", ""),
+                    "timestamp": msg.get("timestamp"),
+                    "langflow_message_id": msg.get("id"),
+                    "langflow_session_id": msg.get("session_id"),
+                    "langflow_flow_id": msg.get("flow_id"),
+                    "sender": msg.get("sender"),
+                    "sender_name": msg.get("sender_name"),
+                    "files": msg.get("files", []),
+                    "properties": msg.get("properties", {}),
+                    "error": msg.get("error", False),
+                    "edit": msg.get("edit", False)
+                }
+                converted_messages.append(converted_msg)
+                
+            except Exception as e:
+                print(f"Error converting message: {e}")
+                continue
+                
+        return converted_messages
+        
+    async def get_user_conversation_history(self, user_id: str, flow_id: Optional[str] = None) -> Dict[str, Any]:
+        """Get all conversation history for a user, organized by session"""
+        langflow_user_id = self._resolve_langflow_user_id(user_id)
+        if not langflow_user_id:
+            return {
+                "error": f"No Langflow user found for {user_id}",
+                "conversations": []
+            }
+            
+        try:
+            # Get all user sessions
+            session_ids = await self.get_user_sessions(user_id, flow_id)
+            
+            conversations = []
+            for session_id in session_ids:
+                messages = await self.get_session_messages(user_id, session_id)
+                if messages:
+                    # Create conversation metadata
+                    first_message = messages[0] if messages else None
+                    last_message = messages[-1] if messages else None
+                    
+                    conversation = {
+                        "session_id": session_id,
+                        "langflow_session_id": session_id,  # For compatibility
+                        "response_id": session_id,  # Map session_id to response_id for frontend compatibility
+                        "messages": messages,
+                        "message_count": len(messages),
+                        "created_at": first_message.get("timestamp") if first_message else None,
+                        "last_activity": last_message.get("timestamp") if last_message else None,
+                        "flow_id": first_message.get("langflow_flow_id") if first_message else None,
+                        "source": "langflow"
+                    }
+                    conversations.append(conversation)
+            
+            # Sort by last activity (most recent first)
+            conversations.sort(key=lambda c: c.get("last_activity", ""), reverse=True)
+            
+            return {
+                "conversations": conversations,
+                "total_conversations": len(conversations),
+                "langflow_user_id": langflow_user_id,
+                "user_id": user_id
+            }
+            
+        except Exception as e:
+            print(f"Error getting user conversation history: {e}")
+            return {
+                "error": str(e),
+                "conversations": []
+            }
+
+
+# Global instance
+langflow_history_service = LangflowHistoryService()

src/services/user_binding_service.py

@@ -0,0 +1,256 @@
+"""
+User Binding Service
+Manages mappings between Google OAuth user IDs and Langflow user IDs
+Uses verified Langflow API endpoints: /api/v1/login and /api/v1/users/whoami
+"""
+
+import json
+import os
+from typing import Dict, Optional, Any
+import httpx
+from config.settings import LANGFLOW_URL, LANGFLOW_KEY
+
+USER_BINDINGS_FILE = "user_bindings.json"
+
+class UserBindingService:
+    def __init__(self):
+        self.bindings_file = USER_BINDINGS_FILE
+        self.bindings = self._load_bindings()
+
+    def _load_bindings(self) -> Dict[str, Any]:
+        """Load user bindings from JSON file"""
+        try:
+            if os.path.exists(self.bindings_file):
+                with open(self.bindings_file, 'r') as f:
+                    return json.load(f)
+            else:
+                return {}
+        except Exception as e:
+            print(f"Error loading user bindings: {e}")
+            return {}
+
+    def _save_bindings(self):
+        """Save user bindings to JSON file"""
+        try:
+            with open(self.bindings_file, 'w') as f:
+                json.dump(self.bindings, f, indent=2)
+            print(f"Saved user bindings to {self.bindings_file}")
+        except Exception as e:
+            print(f"Error saving user bindings: {e}")
+
+    def get_langflow_user_id(self, google_user_id: str) -> Optional[str]:
+        """Get Langflow user ID from Google user ID"""
+        return self.bindings.get(google_user_id, {}).get('langflow_user_id')
+
+    def get_google_user_id(self, langflow_user_id: str) -> Optional[str]:
+        """Get Google user ID from Langflow user ID (reverse lookup)"""
+        for google_id, binding in self.bindings.items():
+            if binding.get('langflow_user_id') == langflow_user_id:
+                return google_id
+        return None
+
+    def create_binding(self, google_user_id: str, langflow_user_id: str, google_user_info: Dict[str, Any]):
+        """Create a new binding between Google and Langflow user IDs"""
+        self.bindings[google_user_id] = {
+            'langflow_user_id': langflow_user_id,
+            'google_user_info': {
+                'email': google_user_info.get('email'),
+                'name': google_user_info.get('name'),
+                'picture': google_user_info.get('picture'),
+                'verified_email': google_user_info.get('verified_email')
+            },
+            'created_at': __import__('datetime').datetime.now().isoformat(),
+            'last_updated': __import__('datetime').datetime.now().isoformat()
+        }
+        self._save_bindings()
+        print(f"Created binding: Google ID {google_user_id} -> Langflow ID {langflow_user_id}")
+
+    def update_binding(self, google_user_id: str, google_user_info: Dict[str, Any]):
+        """Update existing binding with fresh Google user info"""
+        if google_user_id in self.bindings:
+            self.bindings[google_user_id]['google_user_info'] = {
+                'email': google_user_info.get('email'),
+                'name': google_user_info.get('name'),
+                'picture': google_user_info.get('picture'),
+                'verified_email': google_user_info.get('verified_email')
+            }
+            self.bindings[google_user_id]['last_updated'] = __import__('datetime').datetime.now().isoformat()
+            self._save_bindings()
+            print(f"Updated binding for Google ID {google_user_id}")
+
+    def has_binding(self, google_user_id: str) -> bool:
+        """Check if a binding exists for the Google user ID"""
+        return google_user_id in self.bindings
+
+    async def get_langflow_user_info(self, langflow_access_token: str) -> Optional[Dict[str, Any]]:
+        """Get current user info from Langflow /me endpoint"""
+        if not LANGFLOW_URL:
+            print("LANGFLOW_URL not configured")
+            return None
+
+        try:
+            # Use the correct Langflow endpoint based on source code analysis
+            endpoint = "/api/v1/users/whoami"
+            
+            headers = {}
+            if langflow_access_token:
+                headers["Authorization"] = f"Bearer {langflow_access_token}"
+            elif LANGFLOW_KEY:
+                # Try with global Langflow API key if available
+                headers["Authorization"] = f"Bearer {LANGFLOW_KEY}"
+                headers["x-api-key"] = LANGFLOW_KEY
+
+            async with httpx.AsyncClient() as client:
+                url = f"{LANGFLOW_URL.rstrip('/')}{endpoint}"
+                print(f"Getting Langflow user info from: {url}")
+                
+                response = await client.get(url, headers=headers)
+                
+                if response.status_code == 200:
+                    user_data = response.json()
+                    print(f"Successfully got Langflow user data")
+                    return user_data
+                else:
+                    print(f"Langflow /whoami endpoint returned: {response.status_code} - {response.text}")
+                    return None
+            
+        except Exception as e:
+            print(f"Error getting Langflow user info: {e}")
+            return None
+
+    async def authenticate_with_langflow(self) -> Optional[str]:
+        """Authenticate with Langflow using superuser credentials to get access token"""
+        if not LANGFLOW_URL:
+            return None
+
+        try:
+            from config.settings import LANGFLOW_SUPERUSER, LANGFLOW_SUPERUSER_PASSWORD
+            
+            if not LANGFLOW_SUPERUSER or not LANGFLOW_SUPERUSER_PASSWORD:
+                print("Langflow superuser credentials not configured")
+                return None
+
+            # Try to login to Langflow
+            login_data = {
+                "username": LANGFLOW_SUPERUSER,
+                "password": LANGFLOW_SUPERUSER_PASSWORD
+            }
+
+            async with httpx.AsyncClient() as client:
+                # Use the correct Langflow login endpoint based on source code analysis
+                endpoint = "/api/v1/login"
+                url = f"{LANGFLOW_URL.rstrip('/')}{endpoint}"
+                
+                # Try form-encoded data first (standard OAuth2 flow)
+                try:
+                    response = await client.post(
+                        url,
+                        data=login_data,
+                        headers={"Content-Type": "application/x-www-form-urlencoded"}
+                    )
+                    
+                    if response.status_code == 200:
+                        result = response.json()
+                        access_token = result.get('access_token')
+                        if access_token:
+                            print(f"Successfully authenticated with Langflow via {endpoint}")
+                            return access_token
+                    else:
+                        print(f"Langflow login returned: {response.status_code} - {response.text}")
+                        
+                except Exception as e:
+                    print(f"Error with form login: {e}")
+
+                # If form login didn't work, try JSON (fallback)
+                try:
+                    response = await client.post(
+                        url,
+                        json=login_data,
+                        headers={"Content-Type": "application/json"}
+                    )
+                    
+                    if response.status_code == 200:
+                        result = response.json()
+                        access_token = result.get('access_token')
+                        if access_token:
+                            print(f"Successfully authenticated with Langflow via {endpoint} (JSON)")
+                            return access_token
+                    else:
+                        print(f"Langflow login (JSON) returned: {response.status_code} - {response.text}")
+                        
+                except Exception as e:
+                    print(f"Error with JSON login: {e}")
+
+            print("Failed to authenticate with Langflow")
+            return None
+            
+        except Exception as e:
+            print(f"Error authenticating with Langflow: {e}")
+            return None
+
+    async def ensure_binding(self, google_user_id: str, google_user_info: Dict[str, Any]) -> bool:
+        """Ensure a binding exists for the Google user, create if needed"""
+        if self.has_binding(google_user_id):
+            # Update existing binding with fresh Google info
+            self.update_binding(google_user_id, google_user_info)
+            return True
+
+        # No binding exists, try to create one
+        try:
+            # First authenticate with Langflow
+            langflow_token = await self.authenticate_with_langflow()
+            if not langflow_token:
+                print("Could not authenticate with Langflow to create binding")
+                return False
+
+            # Get Langflow user info
+            langflow_user_info = await self.get_langflow_user_info(langflow_token)
+            if not langflow_user_info:
+                print("Could not get Langflow user info")
+                return False
+
+            # Extract Langflow user ID (try different possible fields)
+            langflow_user_id = None
+            for id_field in ['id', 'user_id', 'sub', 'username']:
+                if id_field in langflow_user_info:
+                    langflow_user_id = str(langflow_user_info[id_field])
+                    break
+
+            if not langflow_user_id:
+                print(f"Could not extract Langflow user ID from: {langflow_user_info}")
+                return False
+
+            # Create the binding
+            self.create_binding(google_user_id, langflow_user_id, google_user_info)
+            return True
+
+        except Exception as e:
+            print(f"Error creating binding for Google user {google_user_id}: {e}")
+            return False
+
+    def get_binding_info(self, google_user_id: str) -> Optional[Dict[str, Any]]:
+        """Get complete binding information for a Google user ID"""
+        return self.bindings.get(google_user_id)
+
+    def list_all_bindings(self) -> Dict[str, Any]:
+        """Get all user bindings (for admin purposes)"""
+        return self.bindings.copy()
+        
+    def is_langflow_user_id(self, user_id: str) -> bool:
+        """Check if user_id appears to be a Langflow UUID"""
+        import re
+        # Basic UUID pattern check (with or without dashes)
+        uuid_pattern = r'^[0-9a-f]{8}-?[0-9a-f]{4}-?[0-9a-f]{4}-?[0-9a-f]{4}-?[0-9a-f]{12}$'
+        return bool(re.match(uuid_pattern, user_id.lower().replace('-', '')))
+        
+    def get_user_type(self, user_id: str) -> str:
+        """Determine user type: 'google_oauth', 'langflow_direct', or 'unknown'"""
+        if self.has_binding(user_id):
+            return "google_oauth"
+        elif self.is_langflow_user_id(user_id):
+            return "langflow_direct"
+        else:
+            return "unknown"
+
+# Global instance
+user_binding_service = UserBindingService()