flow to support passing filters

docker-compose.yml

@@ -94,5 +94,6 @@ services:
       - LANGFLOW_LOAD_FLOWS_PATH=/app/flows
       - LANGFLOW_SECRET_KEY=${LANGFLOW_SECRET_KEY}
       - JWT="dummy"
+      - GENDB-QUERY-FILTER="{}"
       - LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT=JWT
       - LANGFLOW_LOG_LEVEL=DEBUG

frontend/src/app/page.tsx

@@ -10,6 +10,7 @@ import { Checkbox } from "@/components/ui/checkbox"
 import { Collapsible, CollapsibleContent, CollapsibleTrigger } from "@/components/ui/collapsible"
 import { Search, Loader2, FileText, Zap, ChevronDown, ChevronUp, Filter, X, Settings, Save } from "lucide-react"
 import { ProtectedRoute } from "@/components/protected-route"
+import { toast } from 'sonner'
 
 interface SearchResult {
   filename: string
@@ -329,12 +330,12 @@ function SearchPage() {
           setContextTitle("")
           setContextDescription("")
         }
-        console.log(contextId ? "Context updated successfully:" : "Context saved successfully:", result)
+        toast.success(contextId ? "Context updated successfully" : "Context saved successfully")
       } else {
-        console.error(contextId ? "Failed to update context:" : "Failed to save context:", result.error)
+        toast.error(contextId ? "Failed to update context" : "Failed to save context")
       }
     } catch (error) {
-      console.error(contextId ? "Error updating context:" : "Error saving context:", error)
+      toast.error(contextId ? "Error updating context" : "Error saving context")
     } finally {
       setSavingContext(false)
     }

src/services/chat_service.py

@@ -1,6 +1,7 @@
 from config.settings import clients, LANGFLOW_URL, FLOW_ID, LANGFLOW_KEY
 from agent import async_chat, async_langflow, async_chat_stream, async_langflow_stream
 from auth_context import set_auth_context
+import json
 
 class ChatService:
     
@@ -35,6 +36,50 @@ class ChatService:
         if jwt_token:
             extra_headers['X-LANGFLOW-GLOBAL-VAR-JWT'] = jwt_token
 
+        # Get context variables for filters, limit, and threshold
+        from auth_context import get_search_filters, get_search_limit, get_score_threshold
+        filters = get_search_filters()
+        limit = get_search_limit()
+        score_threshold = get_score_threshold()
+
+        # Build the complete filter expression like the search service does
+        filter_expression = {}
+        if filters:
+            filter_clauses = []
+            # Map frontend filter names to backend field names
+            field_mapping = {
+                "data_sources": "filename",
+                "document_types": "mimetype", 
+                "owners": "owner"
+            }
+            
+            for filter_key, values in filters.items():
+                if values is not None and isinstance(values, list) and len(values) > 0:
+                    # Map frontend key to backend field name
+                    field_name = field_mapping.get(filter_key, filter_key)
+                    
+                    if len(values) == 1:
+                        # Single value filter
+                        filter_clauses.append({"term": {field_name: values[0]}})
+                    else:
+                        # Multiple values filter
+                        filter_clauses.append({"terms": {field_name: values}})
+            
+            if filter_clauses:
+                filter_expression["filter"] = filter_clauses
+        
+        # Add limit and score threshold to the filter expression (only if different from defaults)
+        if limit and limit != 10:  # 10 is the default limit
+            filter_expression["limit"] = limit
+            
+        if score_threshold and score_threshold != 0:  # 0 is the default threshold
+            filter_expression["score_threshold"] = score_threshold
+
+        # Pass the complete filter expression as a single header to Langflow (only if we have something to send)
+        if filter_expression:
+            print(f"Sending GenDB query filter to Langflow: {json.dumps(filter_expression, indent=2)}")
+            extra_headers['X-LANGFLOW-GLOBAL-VAR-GENDB-QUERY-FILTER'] = json.dumps(filter_expression)
+
         if stream:
             return async_langflow_stream(clients.langflow_client, FLOW_ID, prompt, extra_headers=extra_headers, previous_response_id=previous_response_id)
         else: