Merge pull request #71 from langflow-ai/setting-updates

settings updates for true flow updates

.env.example

@@ -9,7 +9,7 @@ LANGFLOW_SECRET_KEY=
 LANGFLOW_CHAT_FLOW_ID=1098eea1-6649-4e1d-aed1-b77249fb8dd0
 LANGFLOW_INGEST_FLOW_ID=5488df7c-b93f-4f87-a446-b67028bc0813
 # Ingest flow using docling
-LANGFLOW_INGEST_FLOW_ID=1402618b-e6d1-4ff2-9a11-d6ce71186915
+# LANGFLOW_INGEST_FLOW_ID=1402618b-e6d1-4ff2-9a11-d6ce71186915
 NUDGES_FLOW_ID=ebc01d31-1976-46ce-a385-b0240327226c
 
 # Set a strong admin password for OpenSearch; a bcrypt hash is generated at

frontend/components/ui/select.tsx

@@ -2,7 +2,7 @@
 
 import * as React from "react"
 import * as SelectPrimitive from "@radix-ui/react-select"
-import { Check, ChevronDown, ChevronUp } from "lucide-react"
+import { Check, ChevronDown, ChevronUp, Lock } from "lucide-react"
 
 import { cn } from "@/lib/utils"
 
@@ -15,18 +15,24 @@ const SelectValue = SelectPrimitive.Value
 const SelectTrigger = React.forwardRef<
   React.ElementRef<typeof SelectPrimitive.Trigger>,
   React.ComponentPropsWithoutRef<typeof SelectPrimitive.Trigger>
->(({ className, children, ...props }, ref) => (
+>(({ className, children, disabled, ...props }, ref) => (
   <SelectPrimitive.Trigger
     ref={ref}
     className={cn(
       "flex h-10 w-full items-center justify-between rounded-md border border-input bg-background px-3 py-2 text-sm ring-offset-background placeholder:text-muted-foreground focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 [&>span]:line-clamp-1",
+      disabled && "bg-muted",
       className
     )}
+    disabled={disabled}
     {...props}
   >
     {children}
     <SelectPrimitive.Icon asChild>
-      <ChevronDown className="h-4 w-4 opacity-50" />
+      {disabled ? (
+        <Lock className="h-4 w-4 opacity-50" />
+      ) : (
+        <ChevronDown className="h-4 w-4 opacity-50" />
+      )}
     </SelectPrimitive.Icon>
   </SelectPrimitive.Trigger>
 ))

frontend/src/app/settings/page.tsx

@@ -764,8 +764,9 @@ function KnowledgeSourcesPage() {
                   "text-embedding-ada-002"
                 }
                 onValueChange={handleEmbeddingModelChange}
+                disabled={true}
               >
-                <SelectTrigger id="embedding-model-select">
+                <SelectTrigger id="embedding-model-select" disabled={true}>
                   <SelectValue placeholder="Select an embedding model" />
                 </SelectTrigger>
                 <SelectContent>

src/api/settings.py

@@ -182,6 +182,7 @@ async def update_settings(request, session_manager):
             "chunk_size",
             "chunk_overlap",
             "doclingPresets",
+            "embedding_model",
         }
 
         # Check for invalid fields
@@ -202,11 +203,53 @@ async def update_settings(request, session_manager):
             current_config.agent.llm_model = body["llm_model"]
             config_updated = True
 
+            # Also update the chat flow with the new model
+            try:
+                flows_service = _get_flows_service()
+                await flows_service.update_chat_flow_model(body["llm_model"])
+                logger.info(f"Successfully updated chat flow model to '{body['llm_model']}'")
+            except Exception as e:
+                logger.error(f"Failed to update chat flow model: {str(e)}")
+                # Don't fail the entire settings update if flow update fails
+                # The config will still be saved
+
         if "system_prompt" in body:
             current_config.agent.system_prompt = body["system_prompt"]
             config_updated = True
 
+            # Also update the chat flow with the new system prompt
+            try:
+                flows_service = _get_flows_service()
+                await flows_service.update_chat_flow_system_prompt(body["system_prompt"])
+                logger.info(f"Successfully updated chat flow system prompt")
+            except Exception as e:
+                logger.error(f"Failed to update chat flow system prompt: {str(e)}")
+                # Don't fail the entire settings update if flow update fails
+                # The config will still be saved
+
         # Update knowledge settings
+        if "embedding_model" in body:
+            if (
+                not isinstance(body["embedding_model"], str)
+                or not body["embedding_model"].strip()
+            ):
+                return JSONResponse(
+                    {"error": "embedding_model must be a non-empty string"},
+                    status_code=400,
+                )
+            current_config.knowledge.embedding_model = body["embedding_model"].strip()
+            config_updated = True
+
+            # Also update the ingest flow with the new embedding model
+            try:
+                flows_service = _get_flows_service()
+                await flows_service.update_ingest_flow_embedding_model(body["embedding_model"].strip())
+                logger.info(f"Successfully updated ingest flow embedding model to '{body['embedding_model'].strip()}'")
+            except Exception as e:
+                logger.error(f"Failed to update ingest flow embedding model: {str(e)}")
+                # Don't fail the entire settings update if flow update fails
+                # The config will still be saved
+
         if "doclingPresets" in body:
             preset_configs = get_docling_preset_configs()
             valid_presets = list(preset_configs.keys())
@@ -222,7 +265,8 @@ async def update_settings(request, session_manager):
 
             # Also update the flow with the new docling preset
             try:
-                await _update_flow_docling_preset(body["doclingPresets"], preset_configs[body["doclingPresets"]])
+                flows_service = _get_flows_service()
+                await flows_service.update_flow_docling_preset(body["doclingPresets"], preset_configs[body["doclingPresets"]])
                 logger.info(f"Successfully updated docling preset in flow to '{body['doclingPresets']}'")
             except Exception as e:
                 logger.error(f"Failed to update docling preset in flow: {str(e)}")
@@ -237,6 +281,16 @@ async def update_settings(request, session_manager):
             current_config.knowledge.chunk_size = body["chunk_size"]
             config_updated = True
 
+            # Also update the ingest flow with the new chunk size
+            try:
+                flows_service = _get_flows_service()
+                await flows_service.update_ingest_flow_chunk_size(body["chunk_size"])
+                logger.info(f"Successfully updated ingest flow chunk size to {body['chunk_size']}")
+            except Exception as e:
+                logger.error(f"Failed to update ingest flow chunk size: {str(e)}")
+                # Don't fail the entire settings update if flow update fails
+                # The config will still be saved
+
         if "chunk_overlap" in body:
             if not isinstance(body["chunk_overlap"], int) or body["chunk_overlap"] < 0:
                 return JSONResponse(
@@ -246,6 +300,16 @@ async def update_settings(request, session_manager):
             current_config.knowledge.chunk_overlap = body["chunk_overlap"]
             config_updated = True
 
+            # Also update the ingest flow with the new chunk overlap
+            try:
+                flows_service = _get_flows_service()
+                await flows_service.update_ingest_flow_chunk_overlap(body["chunk_overlap"])
+                logger.info(f"Successfully updated ingest flow chunk overlap to {body['chunk_overlap']}")
+            except Exception as e:
+                logger.error(f"Failed to update ingest flow chunk overlap: {str(e)}")
+                # Don't fail the entire settings update if flow update fails
+                # The config will still be saved
+
         if not config_updated:
             return JSONResponse(
                 {"error": "No valid fields provided for update"}, status_code=400
@@ -524,48 +588,12 @@ async def onboarding(request, flows_service):
         )
 
 
-async def _update_flow_docling_preset(preset: str, preset_config: dict):
-    """Helper function to update docling preset in the ingest flow"""
-    if not LANGFLOW_INGEST_FLOW_ID:
-        raise ValueError("LANGFLOW_INGEST_FLOW_ID is not configured")
 
-    # Get the current flow data from Langflow
-    response = await clients.langflow_request(
-        "GET", f"/api/v1/flows/{LANGFLOW_INGEST_FLOW_ID}"
-    )
 
-    if response.status_code != 200:
+def _get_flows_service():
-        raise Exception(f"Failed to get ingest flow: HTTP {response.status_code} - {response.text}")
+    """Helper function to get flows service instance"""
-
+    from services.flows_service import FlowsService
-    flow_data = response.json()
+    return FlowsService()
-
-    # Find the target node in the flow using environment variable
-    nodes = flow_data.get("data", {}).get("nodes", [])
-    target_node = None
-    target_node_index = None
-
-    for i, node in enumerate(nodes):
-        if node.get("id") == DOCLING_COMPONENT_ID:
-            target_node = node
-            target_node_index = i
-            break
-
-    if target_node is None:
-        raise Exception(f"Docling component '{DOCLING_COMPONENT_ID}' not found in ingest flow")
-
-    # Update the docling_serve_opts value directly in the existing node
-    if (target_node.get("data", {}).get("node", {}).get("template", {}).get("docling_serve_opts")):
-        flow_data["data"]["nodes"][target_node_index]["data"]["node"]["template"]["docling_serve_opts"]["value"] = preset_config
-    else:
-        raise Exception(f"docling_serve_opts field not found in node '{DOCLING_COMPONENT_ID}'")
-
-    # Update the flow via PATCH request
-    patch_response = await clients.langflow_request(
-        "PATCH", f"/api/v1/flows/{LANGFLOW_INGEST_FLOW_ID}", json=flow_data
-    )
-
-    if patch_response.status_code != 200:
-        raise Exception(f"Failed to update ingest flow: HTTP {patch_response.status_code} - {patch_response.text}")
 
 
 async def update_docling_preset(request, session_manager):
@@ -595,7 +623,8 @@ async def update_docling_preset(request, session_manager):
         preset_config = preset_configs[preset]
 
         # Use the helper function to update the flow
-        await _update_flow_docling_preset(preset, preset_config)
+        flows_service = _get_flows_service()
+        await flows_service.update_flow_docling_preset(preset, preset_config)
 
         logger.info(f"Successfully updated docling preset to '{preset}' in ingest flow")
 

src/services/flows_service.py

@@ -400,6 +400,128 @@ class FlowsService:
                 return node
         return None
 
+    def _find_node_in_flow(self, flow_data, node_id=None, display_name=None):
+        """
+        Helper function to find a node in flow data by ID or display name.
+        Returns tuple of (node, node_index) or (None, None) if not found.
+        """
+        nodes = flow_data.get("data", {}).get("nodes", [])
+
+        for i, node in enumerate(nodes):
+            node_data = node.get("data", {})
+            node_template = node_data.get("node", {})
+
+            # Check by ID if provided
+            if node_id and node_data.get("id") == node_id:
+                return node, i
+
+            # Check by display_name if provided
+            if display_name and node_template.get("display_name") == display_name:
+                return node, i
+
+        return None, None
+
+    async def _update_flow_field(self, flow_id: str, field_name: str, field_value: str, node_display_name: str = None, node_id: str = None):
+        """
+        Generic helper function to update any field in any Langflow component.
+
+        Args:
+            flow_id: The ID of the flow to update
+            field_name: The name of the field to update (e.g., 'model_name', 'system_message', 'docling_serve_opts')
+            field_value: The new value to set
+            node_display_name: The display name to search for (optional)
+            node_id: The node ID to search for (optional, used as fallback or primary)
+        """
+        if not flow_id:
+            raise ValueError("flow_id is required")
+
+        # Get the current flow data from Langflow
+        response = await clients.langflow_request(
+            "GET", f"/api/v1/flows/{flow_id}"
+        )
+
+        if response.status_code != 200:
+            raise Exception(f"Failed to get flow: HTTP {response.status_code} - {response.text}")
+
+        flow_data = response.json()
+
+        # Find the target component by display name first, then by ID as fallback
+        target_node, target_node_index = None, None
+        if node_display_name:
+            target_node, target_node_index = self._find_node_in_flow(flow_data, display_name=node_display_name)
+
+        if target_node is None and node_id:
+            target_node, target_node_index = self._find_node_in_flow(flow_data, node_id=node_id)
+
+        if target_node is None:
+            identifier = node_display_name or node_id
+            raise Exception(f"Component '{identifier}' not found in flow {flow_id}")
+
+        # Update the field value directly in the existing node
+        template = target_node.get("data", {}).get("node", {}).get("template", {})
+        if template.get(field_name):
+            flow_data["data"]["nodes"][target_node_index]["data"]["node"]["template"][field_name]["value"] = field_value
+        else:
+            identifier = node_display_name or node_id
+            raise Exception(f"{field_name} field not found in {identifier} component")
+
+        # Update the flow via PATCH request
+        patch_response = await clients.langflow_request(
+            "PATCH", f"/api/v1/flows/{flow_id}", json=flow_data
+        )
+
+        if patch_response.status_code != 200:
+            raise Exception(f"Failed to update flow: HTTP {patch_response.status_code} - {patch_response.text}")
+
+    async def update_chat_flow_model(self, model_name: str):
+        """Helper function to update the model in the chat flow"""
+        if not LANGFLOW_CHAT_FLOW_ID:
+            raise ValueError("LANGFLOW_CHAT_FLOW_ID is not configured")
+        await self._update_flow_field(LANGFLOW_CHAT_FLOW_ID, "model_name", model_name,
+                                node_display_name="Language Model",
+                                node_id="LanguageModelComponent-0YME7")
+
+    async def update_chat_flow_system_prompt(self, system_prompt: str):
+        """Helper function to update the system prompt in the chat flow"""
+        if not LANGFLOW_CHAT_FLOW_ID:
+            raise ValueError("LANGFLOW_CHAT_FLOW_ID is not configured")
+        await self._update_flow_field(LANGFLOW_CHAT_FLOW_ID, "system_message", system_prompt,
+                                node_display_name="Language Model",
+                                node_id="LanguageModelComponent-0YME7")
+
+    async def update_flow_docling_preset(self, preset: str, preset_config: dict):
+        """Helper function to update docling preset in the ingest flow"""
+        if not LANGFLOW_INGEST_FLOW_ID:
+            raise ValueError("LANGFLOW_INGEST_FLOW_ID is not configured")
+
+        from config.settings import DOCLING_COMPONENT_ID
+        await self._update_flow_field(LANGFLOW_INGEST_FLOW_ID, "docling_serve_opts", preset_config,
+                                node_id=DOCLING_COMPONENT_ID)
+
+    async def update_ingest_flow_chunk_size(self, chunk_size: int):
+        """Helper function to update chunk size in the ingest flow"""
+        if not LANGFLOW_INGEST_FLOW_ID:
+            raise ValueError("LANGFLOW_INGEST_FLOW_ID is not configured")
+        await self._update_flow_field(LANGFLOW_INGEST_FLOW_ID, "chunk_size", chunk_size,
+                                node_display_name="Split Text",
+                                node_id="SplitText-3ZI5B")
+
+    async def update_ingest_flow_chunk_overlap(self, chunk_overlap: int):
+        """Helper function to update chunk overlap in the ingest flow"""
+        if not LANGFLOW_INGEST_FLOW_ID:
+            raise ValueError("LANGFLOW_INGEST_FLOW_ID is not configured")
+        await self._update_flow_field(LANGFLOW_INGEST_FLOW_ID, "chunk_overlap", chunk_overlap,
+                                node_display_name="Split Text",
+                                node_id="SplitText-3ZI5B")
+
+    async def update_ingest_flow_embedding_model(self, embedding_model: str):
+        """Helper function to update embedding model in the ingest flow"""
+        if not LANGFLOW_INGEST_FLOW_ID:
+            raise ValueError("LANGFLOW_INGEST_FLOW_ID is not configured")
+        await self._update_flow_field(LANGFLOW_INGEST_FLOW_ID, "model", embedding_model,
+                                node_display_name="Embedding Model",
+                                node_id="EmbeddingModel-eZ6bT")
+
     def _replace_node_in_flow(self, flow_data, old_id, new_node):
         """Replace a node in the flow data"""
         nodes = flow_data.get("data", {}).get("nodes", [])