fix: disable upload message when ingesting on onboarding, wait for file to be ingested, added knowledge filters on nudges (#345)

* Removed upload start message

* Made onboarding upload refetch nudges and only finish when document is ingested

* Implemented query filters on nudges

* changed get to post

* Implemented filtering for documents that are not sample data on nudges

---------

Co-authored-by: Sebastián Estévez <estevezsebastian@gmail.com>

flows/openrag_nudges.json

@@ -7,7 +7,7 @@
         "data": {
           "sourceHandle": {
             "dataType": "EmbeddingModel",
-            "id": "EmbeddingModel-eZ6bT",
+            "id": "EmbeddingModel-rofSg",
             "name": "embeddings",
             "output_types": [
               "Embeddings"
@@ -15,19 +15,19 @@
           },
           "targetHandle": {
             "fieldName": "embedding",
-            "id": "OpenSearch-iYfjf",
+            "id": "OpenSearchVectorStoreComponent-JA880",
             "inputTypes": [
               "Embeddings"
             ],
             "type": "other"
           }
         },
-        "id": "xy-edge__EmbeddingModel-eZ6bT{œdataTypeœ:œEmbeddingModelœ,œidœ:œEmbeddingModel-eZ6bTœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-OpenSearch-iYfjf{œfieldNameœ:œembeddingœ,œidœ:œOpenSearch-iYfjfœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}",
+        "id": "reactflow__edge-EmbeddingModel-rofSg{œdataTypeœ:œEmbeddingModelœ,œidœ:œEmbeddingModel-rofSgœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-OpenSearchVectorStoreComponent-JA880{œfieldNameœ:œembeddingœ,œidœ:œOpenSearchVectorStoreComponent-JA880œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}",
         "selected": false,
-        "source": "EmbeddingModel-eZ6bT",
+        "source": "EmbeddingModel-rofSg",
-        "sourceHandle": "{œdataTypeœ:œEmbeddingModelœ,œidœ:œEmbeddingModel-eZ6bTœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}",
+        "sourceHandle": "{œdataTypeœ:œEmbeddingModelœ,œidœ:œEmbeddingModel-rofSgœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}",
-        "target": "OpenSearch-iYfjf",
+        "target": "OpenSearchVectorStoreComponent-JA880",
-        "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œOpenSearch-iYfjfœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}"
+        "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œOpenSearchVectorStoreComponent-JA880œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}"
       },
       {
         "animated": false,
@@ -35,7 +35,7 @@
         "data": {
           "sourceHandle": {
             "dataType": "ParserComponent",
-            "id": "ParserComponent-tZs7s",
+            "id": "ParserComponent-uMBcK",
             "name": "parsed_text",
             "output_types": [
               "Message"
@@ -43,19 +43,19 @@
           },
           "targetHandle": {
             "fieldName": "docs",
-            "id": "Prompt Template-Wo6kR",
+            "id": "Prompt Template-OoRfU",
             "inputTypes": [
               "Message"
             ],
             "type": "str"
           }
         },
-        "id": "xy-edge__ParserComponent-tZs7s{œdataTypeœ:œParserComponentœ,œidœ:œParserComponent-tZs7sœ,œnameœ:œparsed_textœ,œoutput_typesœ:[œMessageœ]}-Prompt Template-Wo6kR{œfieldNameœ:œdocsœ,œidœ:œPrompt Template-Wo6kRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
+        "id": "reactflow__edge-ParserComponent-uMBcK{œdataTypeœ:œParserComponentœ,œidœ:œParserComponent-uMBcKœ,œnameœ:œparsed_textœ,œoutput_typesœ:[œMessageœ]}-Prompt Template-OoRfU{œfieldNameœ:œdocsœ,œidœ:œPrompt Template-OoRfUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
         "selected": false,
-        "source": "ParserComponent-tZs7s",
+        "source": "ParserComponent-uMBcK",
-        "sourceHandle": "{œdataTypeœ:œParserComponentœ,œidœ:œParserComponent-tZs7sœ,œnameœ:œparsed_textœ,œoutput_typesœ:[œMessageœ]}",
+        "sourceHandle": "{œdataTypeœ:œParserComponentœ,œidœ:œParserComponent-uMBcKœ,œnameœ:œparsed_textœ,œoutput_typesœ:[œMessageœ]}",
-        "target": "Prompt Template-Wo6kR",
+        "target": "Prompt Template-OoRfU",
-        "targetHandle": "{œfieldNameœ:œdocsœ,œidœ:œPrompt Template-Wo6kRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
+        "targetHandle": "{œfieldNameœ:œdocsœ,œidœ:œPrompt Template-OoRfUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
       },
       {
         "animated": false,
@@ -63,7 +63,7 @@
         "data": {
           "sourceHandle": {
             "dataType": "ChatInput",
-            "id": "ChatInput-bqH7H",
+            "id": "ChatInput-kYraY",
             "name": "message",
             "output_types": [
               "Message"
@@ -71,19 +71,19 @@
           },
           "targetHandle": {
             "fieldName": "prompt",
-            "id": "Prompt Template-Wo6kR",
+            "id": "Prompt Template-OoRfU",
             "inputTypes": [
               "Message"
             ],
             "type": "str"
           }
         },
-        "id": "xy-edge__ChatInput-bqH7H{œdataTypeœ:œChatInputœ,œidœ:œChatInput-bqH7Hœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt Template-Wo6kR{œfieldNameœ:œpromptœ,œidœ:œPrompt Template-Wo6kRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
+        "id": "reactflow__edge-ChatInput-kYraY{œdataTypeœ:œChatInputœ,œidœ:œChatInput-kYraYœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt Template-OoRfU{œfieldNameœ:œpromptœ,œidœ:œPrompt Template-OoRfUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
         "selected": false,
-        "source": "ChatInput-bqH7H",
+        "source": "ChatInput-kYraY",
-        "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-bqH7Hœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}",
+        "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-kYraYœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}",
-        "target": "Prompt Template-Wo6kR",
+        "target": "Prompt Template-OoRfU",
-        "targetHandle": "{œfieldNameœ:œpromptœ,œidœ:œPrompt Template-Wo6kRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
+        "targetHandle": "{œfieldNameœ:œpromptœ,œidœ:œPrompt Template-OoRfUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
       },
       {
         "animated": false,
@@ -91,7 +91,7 @@
         "data": {
           "sourceHandle": {
             "dataType": "LanguageModelComponent",
-            "id": "LanguageModelComponent-NSTA6",
+            "id": "LanguageModelComponent-dxtYP",
             "name": "text_output",
             "output_types": [
               "Message"
@@ -99,7 +99,7 @@
           },
           "targetHandle": {
             "fieldName": "input_value",
-            "id": "ChatOutput-BMVN5",
+            "id": "ChatOutput-S4nKr",
             "inputTypes": [
               "Data",
               "DataFrame",
@@ -108,12 +108,12 @@
             "type": "other"
           }
         },
-        "id": "xy-edge__LanguageModelComponent-NSTA6{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-NSTA6œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-BMVN5{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-BMVN5œ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}",
+        "id": "reactflow__edge-LanguageModelComponent-dxtYP{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-dxtYPœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-S4nKr{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-S4nKrœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}",
         "selected": false,
-        "source": "LanguageModelComponent-NSTA6",
+        "source": "LanguageModelComponent-dxtYP",
-        "sourceHandle": "{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-NSTA6œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}",
+        "sourceHandle": "{œdataTypeœ:œLanguageModelComponentœ,œidœ:œLanguageModelComponent-dxtYPœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}",
-        "target": "ChatOutput-BMVN5",
+        "target": "ChatOutput-S4nKr",
-        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-BMVN5œ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}"
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-S4nKrœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}"
       },
       {
         "animated": false,
@@ -121,7 +121,7 @@
         "data": {
           "sourceHandle": {
             "dataType": "Prompt Template",
-            "id": "Prompt Template-Wo6kR",
+            "id": "Prompt Template-OoRfU",
             "name": "prompt",
             "output_types": [
               "Message"
@@ -129,19 +129,19 @@
           },
           "targetHandle": {
             "fieldName": "input_value",
-            "id": "LanguageModelComponent-NSTA6",
+            "id": "LanguageModelComponent-dxtYP",
             "inputTypes": [
               "Message"
             ],
             "type": "str"
           }
         },
-        "id": "xy-edge__Prompt Template-Wo6kR{œdataTypeœ:œPrompt Templateœ,œidœ:œPrompt Template-Wo6kRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-LanguageModelComponent-NSTA6{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-NSTA6œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
+        "id": "reactflow__edge-Prompt Template-OoRfU{œdataTypeœ:œPrompt Templateœ,œidœ:œPrompt Template-OoRfUœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-LanguageModelComponent-dxtYP{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-dxtYPœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
         "selected": false,
-        "source": "Prompt Template-Wo6kR",
+        "source": "Prompt Template-OoRfU",
-        "sourceHandle": "{œdataTypeœ:œPrompt Templateœ,œidœ:œPrompt Template-Wo6kRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}",
+        "sourceHandle": "{œdataTypeœ:œPrompt Templateœ,œidœ:œPrompt Template-OoRfUœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}",
-        "target": "LanguageModelComponent-NSTA6",
+        "target": "LanguageModelComponent-dxtYP",
-        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-NSTA6œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œLanguageModelComponent-dxtYPœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
       },
       {
         "animated": false,
@@ -149,7 +149,7 @@
         "data": {
           "sourceHandle": {
             "dataType": "OpenSearchVectorStoreComponent",
-            "id": "OpenSearch-iYfjf",
+            "id": "OpenSearchVectorStoreComponent-JA880",
             "name": "dataframe",
             "output_types": [
               "DataFrame"
@@ -157,7 +157,7 @@
           },
           "targetHandle": {
             "fieldName": "input_data",
-            "id": "ParserComponent-tZs7s",
+            "id": "ParserComponent-uMBcK",
             "inputTypes": [
               "DataFrame",
               "Data"
@@ -165,12 +165,39 @@
             "type": "other"
           }
         },
-        "id": "xy-edge__OpenSearch-iYfjf{œdataTypeœ:œOpenSearchVectorStoreComponentœ,œidœ:œOpenSearch-iYfjfœ,œnameœ:œdataframeœ,œoutput_typesœ:[œDataFrameœ]}-ParserComponent-tZs7s{œfieldNameœ:œinput_dataœ,œidœ:œParserComponent-tZs7sœ,œinputTypesœ:[œDataFrameœ,œDataœ],œtypeœ:œotherœ}",
+        "id": "reactflow__edge-OpenSearchVectorStoreComponent-JA880{œdataTypeœ:œOpenSearchVectorStoreComponentœ,œidœ:œOpenSearchVectorStoreComponent-JA880œ,œnameœ:œdataframeœ,œoutput_typesœ:[œDataFrameœ]}-ParserComponent-uMBcK{œfieldNameœ:œinput_dataœ,œidœ:œParserComponent-uMBcKœ,œinputTypesœ:[œDataFrameœ,œDataœ],œtypeœ:œotherœ}",
         "selected": false,
-        "source": "OpenSearch-iYfjf",
+        "source": "OpenSearchVectorStoreComponent-JA880",
-        "sourceHandle": "{œdataTypeœ:œOpenSearchVectorStoreComponentœ,œidœ:œOpenSearch-iYfjfœ,œnameœ:œdataframeœ,œoutput_typesœ:[œDataFrameœ]}",
+        "sourceHandle": "{œdataTypeœ:œOpenSearchVectorStoreComponentœ,œidœ:œOpenSearchVectorStoreComponent-JA880œ,œnameœ:œdataframeœ,œoutput_typesœ:[œDataFrameœ]}",
-        "target": "ParserComponent-tZs7s",
+        "target": "ParserComponent-uMBcK",
-        "targetHandle": "{œfieldNameœ:œinput_dataœ,œidœ:œParserComponent-tZs7sœ,œinputTypesœ:[œDataFrameœ,œDataœ],œtypeœ:œotherœ}"
+        "targetHandle": "{œfieldNameœ:œinput_dataœ,œidœ:œParserComponent-uMBcKœ,œinputTypesœ:[œDataFrameœ,œDataœ],œtypeœ:œotherœ}"
+      },
+      {
+        "animated": false,
+        "data": {
+          "sourceHandle": {
+            "dataType": "TextInput",
+            "id": "TextInput-OcjB6",
+            "name": "text",
+            "output_types": [
+              "Message"
+            ]
+          },
+          "targetHandle": {
+            "fieldName": "filter_expression",
+            "id": "OpenSearchVectorStoreComponent-JA880",
+            "inputTypes": [
+              "Message"
+            ],
+            "type": "str"
+          }
+        },
+        "id": "xy-edge__TextInput-OcjB6{œdataTypeœ:œTextInputœ,œidœ:œTextInput-OcjB6œ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-OpenSearchVectorStoreComponent-JA880{œfieldNameœ:œfilter_expressionœ,œidœ:œOpenSearchVectorStoreComponent-JA880œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}",
+        "selected": false,
+        "source": "TextInput-OcjB6",
+        "sourceHandle": "{œdataTypeœ:œTextInputœ,œidœ:œTextInput-OcjB6œ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}",
+        "target": "OpenSearchVectorStoreComponent-JA880",
+        "targetHandle": "{œfieldNameœ:œfilter_expressionœ,œidœ:œOpenSearchVectorStoreComponent-JA880œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"
       }
     ],
     "nodes": [
@@ -178,7 +205,7 @@
         "data": {
           "description": "Get chat inputs from the Playground.",
           "display_name": "Chat Input",
-          "id": "ChatInput-bqH7H",
+          "id": "ChatInput-kYraY",
           "node": {
             "base_classes": [
               "Message"
@@ -419,9 +446,9 @@
           "type": "ChatInput"
         },
         "dragging": false,
-        "id": "ChatInput-bqH7H",
+        "id": "ChatInput-kYraY",
         "measured": {
-          "height": 48,
+          "height": 57,
           "width": 192
         },
         "position": {
@@ -435,7 +462,7 @@
         "data": {
           "description": "Display a chat message in the Playground.",
           "display_name": "Chat Output",
-          "id": "ChatOutput-BMVN5",
+          "id": "ChatOutput-S4nKr",
           "node": {
             "base_classes": [
               "Message"
@@ -680,9 +707,9 @@
           "type": "ChatOutput"
         },
         "dragging": false,
-        "id": "ChatOutput-BMVN5",
+        "id": "ChatOutput-S4nKr",
         "measured": {
-          "height": 48,
+          "height": 57,
           "width": 192
         },
         "position": {
@@ -694,7 +721,7 @@
       },
       {
         "data": {
-          "id": "OpenSearch-iYfjf",
+          "id": "OpenSearchVectorStoreComponent-JA880",
           "node": {
             "base_classes": [
               "Data",
@@ -1303,7 +1330,7 @@
           "type": "OpenSearchVectorStoreComponent"
         },
         "dragging": false,
-        "id": "OpenSearch-iYfjf",
+        "id": "OpenSearchVectorStoreComponent-JA880",
         "measured": {
           "height": 822,
           "width": 320
@@ -1317,7 +1344,7 @@
       },
       {
         "data": {
-          "id": "EmbeddingModel-eZ6bT",
+          "id": "EmbeddingModel-rofSg",
           "node": {
             "base_classes": [
               "Embeddings"
@@ -1343,7 +1370,7 @@
             ],
             "frozen": false,
             "icon": "binary",
-            "last_updated": "2025-10-01T20:14:43.010Z",
+            "last_updated": "2025-11-03T19:42:29.170Z",
             "legacy": false,
             "metadata": {
               "code_hash": "8607e963fdef",
@@ -1614,9 +1641,9 @@
           "type": "EmbeddingModel"
         },
         "dragging": false,
-        "id": "EmbeddingModel-eZ6bT",
+        "id": "EmbeddingModel-rofSg",
         "measured": {
-          "height": 369,
+          "height": 378,
           "width": 320
         },
         "position": {
@@ -1628,7 +1655,7 @@
       },
       {
         "data": {
-          "id": "Prompt Template-Wo6kR",
+          "id": "Prompt Template-OoRfU",
           "node": {
             "base_classes": [
               "Message"
@@ -1801,7 +1828,7 @@
           "type": "Prompt Template"
         },
         "dragging": false,
-        "id": "Prompt Template-Wo6kR",
+        "id": "Prompt Template-OoRfU",
         "measured": {
           "height": 449,
           "width": 320
@@ -1815,7 +1842,7 @@
       },
       {
         "data": {
-          "id": "ParserComponent-tZs7s",
+          "id": "ParserComponent-uMBcK",
           "node": {
             "base_classes": [
               "Message"
@@ -1987,7 +2014,7 @@
           "type": "ParserComponent"
         },
         "dragging": false,
-        "id": "ParserComponent-tZs7s",
+        "id": "ParserComponent-uMBcK",
         "measured": {
           "height": 329,
           "width": 320
@@ -2001,7 +2028,7 @@
       },
       {
         "data": {
-          "id": "LanguageModelComponent-NSTA6",
+          "id": "LanguageModelComponent-dxtYP",
           "node": {
             "base_classes": [
               "LanguageModel",
@@ -2025,7 +2052,7 @@
             ],
             "frozen": false,
             "icon": "brain-circuit",
-            "last_updated": "2025-10-01T20:14:43.010Z",
+            "last_updated": "2025-11-03T19:42:41.996Z",
             "legacy": false,
             "metadata": {
               "code_hash": "bb5f8714781b",
@@ -2200,7 +2227,7 @@
                 "tool_mode": false,
                 "trace_as_metadata": true,
                 "type": "str",
-                "value": "gpt-4o-mini"
+                "value": "gpt-4o"
               },
               "provider": {
                 "_input_type": "DropdownInput",
@@ -2318,7 +2345,7 @@
           "type": "LanguageModelComponent"
         },
         "dragging": false,
-        "id": "LanguageModelComponent-NSTA6",
+        "id": "LanguageModelComponent-dxtYP",
         "measured": {
           "height": 534,
           "width": 320
@@ -2329,19 +2356,119 @@
         },
         "selected": false,
         "type": "genericNode"
+      },
+      {
+        "data": {
+          "id": "TextInput-OcjB6",
+          "node": {
+            "base_classes": [
+              "Message"
+            ],
+            "beta": false,
+            "conditional_paths": [],
+            "custom_fields": {},
+            "description": "Get user text inputs.",
+            "display_name": "Text Input",
+            "documentation": "https://docs.langflow.org/components-io#text-input",
+            "edited": true,
+            "field_order": [
+              "input_value"
+            ],
+            "frozen": false,
+            "icon": "type",
+            "legacy": false,
+            "lf_version": "1.6.0",
+            "metadata": {},
+            "minimized": false,
+            "output_types": [],
+            "outputs": [
+              {
+                "allows_loop": false,
+                "cache": true,
+                "display_name": "Output Text",
+                "group_outputs": false,
+                "hidden": null,
+                "method": "text_response",
+                "name": "text",
+                "options": null,
+                "required_inputs": null,
+                "selected": "Message",
+                "tool_mode": true,
+                "types": [
+                  "Message"
+                ],
+                "value": "__UNDEFINED__"
+              }
+            ],
+            "pinned": false,
+            "template": {
+              "_type": "Component",
+              "code": {
+                "advanced": true,
+                "dynamic": true,
+                "fileTypes": [],
+                "file_path": "",
+                "info": "",
+                "list": false,
+                "load_from_db": false,
+                "multiline": true,
+                "name": "code",
+                "password": false,
+                "placeholder": "",
+                "required": true,
+                "show": true,
+                "title_case": false,
+                "type": "code",
+                "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import SecretStrInput, Output\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n    display_name = \"Text Input\"\n    description = \"Get user text inputs.\"\n    documentation: str = \"https://docs.langflow.org/components-io#text-input\"\n    icon = \"type\"\n    name = \"TextInput\"\n\n    inputs = [\n        SecretStrInput(\n            name=\"input_value\",\n            display_name=\"Text\",\n            info=\"Text to be passed as input.\",\n        ),\n    ]\n    outputs = [\n        Output(display_name=\"Output Text\", name=\"text\", method=\"text_response\"),\n    ]\n\n    def text_response(self) -> Message:\n        return Message(\n            text=self.input_value,\n        )\n"
+              },
+              "input_value": {
+                "_input_type": "SecretStrInput",
+                "advanced": false,
+                "display_name": "Text",
+                "dynamic": false,
+                "info": "Text to be passed as input.",
+                "input_types": [],
+                "load_from_db": true,
+                "name": "input_value",
+                "password": true,
+                "placeholder": "",
+                "required": false,
+                "show": true,
+                "title_case": false,
+                "type": "str",
+                "value": "OPENRAG-QUERY-FILTER"
+              }
+            },
+            "tool_mode": false
+          },
+          "showNode": true,
+          "type": "TextInput"
+        },
+        "dragging": false,
+        "id": "TextInput-OcjB6",
+        "measured": {
+          "height": 204,
+          "width": 320
+        },
+        "position": {
+          "x": 474.45113226548517,
+          "y": 697.8781609303677
+        },
+        "selected": false,
+        "type": "genericNode"
       }
     ],
     "viewport": {
-      "x": -196.5855347896957,
+      "x": -195.10601766576656,
-      "y": 78.13813811398654,
+      "y": 70.4638443501205,
-      "zoom": 0.5380793988167256
+      "zoom": 0.5524404935324336
     }
   },
   "description": "OpenRAG OpenSearch Nudges generator, based on the OpenSearch documents and the chat history.",
   "endpoint_name": null,
   "id": "ebc01d31-1976-46ce-a385-b0240327226c",
   "is_component": false,
-  "last_tested_version": "1.6.0",
+  "last_tested_version": "1.6.5.dev9",
   "name": "OpenRAG OpenSearch Nudges",
   "tags": [
     "assistants",

frontend/lib/upload-utils.ts

@@ -122,11 +122,6 @@ export async function uploadFile(
   file: File,
   replace = false
 ): Promise<UploadFileResult> {
-  window.dispatchEvent(
-    new CustomEvent("fileUploadStart", {
-      detail: { filename: file.name },
-    })
-  );
 
   try {
     const formData = new FormData();

frontend/src/app/api/queries/useGetNudgesQuery.ts

@@ -1,47 +1,83 @@
 import {
-  useQuery,
+	type UseQueryOptions,
-  useQueryClient,
+	useQuery,
-  UseQueryOptions,
+	useQueryClient,
 } from "@tanstack/react-query";
 
 type Nudge = string;
 
 const DEFAULT_NUDGES: Nudge[] = [];
 
+export interface NudgeFilters {
+	data_sources?: string[];
+	document_types?: string[];
+	owners?: string[];
+}
+
+export interface NudgeQueryParams {
+	chatId?: string | null;
+	filters?: NudgeFilters;
+	limit?: number;
+	scoreThreshold?: number;
+}
+
 export const useGetNudgesQuery = (
-  chatId?: string | null,
+	params: NudgeQueryParams | null = {},
-  options?: Omit<UseQueryOptions, "queryKey" | "queryFn">
+	options?: Omit<UseQueryOptions, "queryKey" | "queryFn">,
 ) => {
-  const queryClient = useQueryClient();
+	const { chatId, filters, limit, scoreThreshold } = params ?? {};
+	const queryClient = useQueryClient();
 
-  function cancel() {
+	function cancel() {
-    queryClient.removeQueries({ queryKey: ["nudges", chatId] });
+		queryClient.removeQueries({ queryKey: ["nudges", chatId, filters, limit, scoreThreshold] });
-  }
+	}
 
-  async function getNudges(): Promise<Nudge[]> {
+	async function getNudges(): Promise<Nudge[]> {
-    try {
+		try {
-      const response = await fetch(`/api/nudges${chatId ? `/${chatId}` : ""}`);
+			const requestBody: {
-      const data = await response.json();
+				filters?: NudgeFilters;
+				limit?: number;
+				score_threshold?: number;
+			} = {};
 
-      if (data.response && typeof data.response === "string") {
+			if (filters) {
-        return data.response.split("\n").filter(Boolean);
+				requestBody.filters = filters;
-      }
+			}
+			if (limit !== undefined) {
+				requestBody.limit = limit;
+			}
+			if (scoreThreshold !== undefined) {
+				requestBody.score_threshold = scoreThreshold;
+			}
 
-      return DEFAULT_NUDGES;
+			const response = await fetch(`/api/nudges${chatId ? `/${chatId}` : ""}`, {
-    } catch (error) {
+				method: "POST",
-      console.error("Error getting nudges", error);
+				headers: {
-      return DEFAULT_NUDGES;
+					"Content-Type": "application/json",
-    }
+				},
-  }
+				body: JSON.stringify(requestBody),
+			});
+			const data = await response.json();
 
-  const queryResult = useQuery(
+			if (data.response && typeof data.response === "string") {
-    {
+				return data.response.split("\n").filter(Boolean);
-      queryKey: ["nudges", chatId],
+			}
-      queryFn: getNudges,
-      ...options,
-    },
-    queryClient
-  );
 
-  return { ...queryResult, cancel };
+			return DEFAULT_NUDGES;
+		} catch (error) {
+			console.error("Error getting nudges", error);
+			return DEFAULT_NUDGES;
+		}
+	}
+
+	const queryResult = useQuery(
+		{
+			queryKey: ["nudges", chatId, filters, limit, scoreThreshold],
+			queryFn: getNudges,
+			...options,
+		},
+		queryClient,
+	);
+
+	return { ...queryResult, cancel };
 };

frontend/src/app/chat/page.tsx

@@ -588,32 +588,12 @@ function ChatPage() {
       setLoading(true);
       setIsUploading(true);
       setUploadedFile(null); // Clear previous file
-
-      // Add initial upload message
-      const uploadStartMessage: Message = {
-        role: "assistant",
-        content: `🔄 Starting upload of **${filename}**...`,
-        timestamp: new Date(),
-      };
-      setMessages((prev) => [...prev, uploadStartMessage]);
     };
 
     const handleFileUploaded = (event: CustomEvent) => {
       const { result } = event.detail;
       console.log("Chat page received file upload event:", result);
 
-      // Replace the last message with upload complete message
-      const uploadMessage: Message = {
-        role: "assistant",
-        content: `📄 Document uploaded: **${result.filename}** (${
-          result.pages
-        } pages, ${result.content_length.toLocaleString()} characters)\n\n${
-          result.confirmation
-        }`,
-        timestamp: new Date(),
-      };
-
-      setMessages((prev) => [...prev.slice(0, -1), uploadMessage]);
       setUploadedFile(null); // Clear file after upload
 
       // Update the response ID for this endpoint
@@ -708,8 +688,38 @@ function ChatPage() {
     return () => clearInterval(interval);
   }, []);
 
+  // Prepare filters for nudges (same as chat)
+  const processedFiltersForNudges = parsedFilterData?.filters
+    ? (() => {
+        const filters = parsedFilterData.filters;
+        const processed: SelectedFilters = {
+          data_sources: [],
+          document_types: [],
+          owners: [],
+        };
+        processed.data_sources = filters.data_sources.includes("*")
+          ? []
+          : filters.data_sources;
+        processed.document_types = filters.document_types.includes("*")
+          ? []
+          : filters.document_types;
+        processed.owners = filters.owners.includes("*") ? [] : filters.owners;
+
+        const hasFilters =
+          processed.data_sources.length > 0 ||
+          processed.document_types.length > 0 ||
+          processed.owners.length > 0;
+        return hasFilters ? processed : undefined;
+      })()
+    : undefined;
+
   const { data: nudges = [], cancel: cancelNudges } = useGetNudgesQuery(
-    previousResponseIds[endpoint],
+    {
+      chatId: previousResponseIds[endpoint],
+      filters: processedFiltersForNudges,
+      limit: parsedFilterData?.limit ?? 3,
+      scoreThreshold: parsedFilterData?.scoreThreshold ?? 0,
+    },
     {
       enabled: isOnboardingComplete, // Only fetch nudges after onboarding is complete
     },

frontend/src/app/onboarding/components/onboarding-upload.tsx

@@ -1,5 +1,7 @@
 import { AnimatePresence, motion } from "motion/react";
-import { type ChangeEvent, useRef, useState } from "react";
+import { type ChangeEvent, useEffect, useRef, useState } from "react";
+import { useGetNudgesQuery } from "@/app/api/queries/useGetNudgesQuery";
+import { useGetTasksQuery } from "@/app/api/queries/useGetTasksQuery";
 import { AnimatedProviderSteps } from "@/app/onboarding/components/animated-provider-steps";
 import { Button } from "@/components/ui/button";
 import { uploadFile } from "@/lib/upload-utils";
@@ -15,6 +17,46 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
 
 	const STEP_LIST = ["Uploading your document", "Processing your document"];
 
+	// Query tasks to track completion
+	const { data: tasks } = useGetTasksQuery({
+		enabled: currentStep !== null, // Only poll when upload has started
+		refetchInterval: currentStep !== null ? 1000 : false, // Poll every 1 second during upload
+	});
+
+	const { refetch: refetchNudges } = useGetNudgesQuery(null);
+
+	// Monitor tasks and call onComplete when file processing is done
+	useEffect(() => {
+		if (currentStep === null || !tasks) {
+			return;
+		}
+
+		// Check if there are any active tasks (pending, running, or processing)
+		const activeTasks = tasks.find(
+			(task) =>
+				task.status === "pending" ||
+				task.status === "running" ||
+				task.status === "processing",
+		);
+
+		// If no active tasks and we have more than 1 task (initial + new upload), complete it
+		if (
+			(!activeTasks || (activeTasks.processed_files ?? 0) > 0) &&
+			tasks.length > 1
+		) {
+			// Set to final step to show "Done"
+			setCurrentStep(STEP_LIST.length);
+
+			// Refetch nudges to get new ones
+			refetchNudges();
+
+			// Wait a bit before completing
+			setTimeout(() => {
+				onComplete();
+			}, 1000);
+		}
+	}, [tasks, currentStep, onComplete, refetchNudges]);
+
 	const resetFileInput = () => {
 		if (fileInputRef.current) {
 			fileInputRef.current.value = "";
@@ -30,15 +72,17 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
 		try {
 			setCurrentStep(0);
 			await uploadFile(file, true);
-			console.log("Document uploaded successfully");
+			console.log("Document upload task started successfully");
+			// Move to processing step - task monitoring will handle completion
+			setTimeout(() => {
+				setCurrentStep(1);
+			}, 1500);
 		} catch (error) {
 			console.error("Upload failed", (error as Error).message);
+			// Reset on error
+			setCurrentStep(null);
 		} finally {
 			setIsUploading(false);
-			await new Promise((resolve) => setTimeout(resolve, 1000));
-			setCurrentStep(STEP_LIST.length);
-			await new Promise((resolve) => setTimeout(resolve, 500));
-			onComplete();
 		}
 	};
 

src/api/nudges.py

@@ -12,9 +12,23 @@ async def nudges_from_kb_endpoint(request: Request, chat_service, session_manage
     jwt_token = session_manager.get_effective_jwt_token(user_id, request.state.jwt_token)
 
     try:
+        # Parse request body for filters
+        body = {}
+        try:
+            body = await request.json()
+        except Exception:
+            body = {}
+
+        filters = body.get("filters")
+        limit = body.get("limit")
+        score_threshold = body.get("score_threshold")
+
         result = await chat_service.langflow_nudges_chat(
             user_id,
             jwt_token,
+            filters=filters,
+            limit=limit,
+            score_threshold=score_threshold,
         )
         return JSONResponse(result)
     except Exception as e:
@@ -32,10 +46,24 @@ async def nudges_from_chat_id_endpoint(request: Request, chat_service, session_m
     jwt_token = session_manager.get_effective_jwt_token(user_id, request.state.jwt_token)
 
     try:
+        # Parse request body for filters
+        body = {}
+        try:
+            body = await request.json()
+        except Exception:
+            body = {}
+
+        filters = body.get("filters")
+        limit = body.get("limit")
+        score_threshold = body.get("score_threshold")
+
         result = await chat_service.langflow_nudges_chat(
             user_id,
             jwt_token,
             previous_response_id=chat_id,
+            filters=filters,
+            limit=limit,
+            score_threshold=score_threshold,
         )
         return JSONResponse(result)
     except Exception as e:

src/main.py

@@ -370,6 +370,7 @@ async def _ingest_default_documents_langflow(services, file_paths):
                 {"key": "owner_name", "value": anonymous_user.name},
                 {"key": "owner_email", "value": anonymous_user.email},
                 {"key": "connector_type", "value": "system_default"},
+                {"key": "is_sample_data", "value": "true"},
             ]
         }
     }
@@ -413,6 +414,7 @@ async def _ingest_default_documents_openrag(services, file_paths):
         jwt_token=None,
         owner_name=None,
         owner_email=None,
+        is_sample_data=True,  # Mark as sample data
     )
 
     task_id = await services["task_service"].create_custom_task(
@@ -1057,7 +1059,7 @@ async def create_app():
                     session_manager=services["session_manager"],
                 )
             ),
-            methods=["GET"],
+            methods=["POST"],
         ),
         Route(
             "/nudges/{chat_id}",
@@ -1068,7 +1070,7 @@ async def create_app():
                     session_manager=services["session_manager"],
                 )
             ),
-            methods=["GET"],
+            methods=["POST"],
         ),
         Route(
             "/reset-flow/{flow_type}",

src/models/processors.py

@@ -157,6 +157,7 @@ class TaskProcessor:
         file_size: int = None,
         connector_type: str = "local",
         embedding_model: str = None,
+        is_sample_data: bool = False,
     ):
         """
         Standard processing pipeline for non-Langflow processors:
@@ -240,6 +241,10 @@ class TaskProcessor:
                 chunk_doc["owner_name"] = owner_name
             if owner_email is not None:
                 chunk_doc["owner_email"] = owner_email
+
+            # Mark as sample data if specified
+            if is_sample_data:
+                chunk_doc["is_sample_data"] = "true"
             chunk_id = f"{file_hash}_{i}"
             try:
                 await opensearch_client.index(
@@ -286,12 +291,14 @@ class DocumentFileProcessor(TaskProcessor):
         jwt_token: str = None,
         owner_name: str = None,
         owner_email: str = None,
+        is_sample_data: bool = False,
     ):
         super().__init__(document_service)
         self.owner_user_id = owner_user_id
         self.jwt_token = jwt_token
         self.owner_name = owner_name
         self.owner_email = owner_email
+        self.is_sample_data = is_sample_data
 
     async def process_item(
         self, upload_task: UploadTask, item: str, file_task: FileTask
@@ -326,6 +333,7 @@ class DocumentFileProcessor(TaskProcessor):
                 owner_email=self.owner_email,
                 file_size=file_size,
                 connector_type="local",
+                is_sample_data=self.is_sample_data,
             )
 
             file_task.status = TaskStatus.COMPLETED

src/services/chat_service.py

@@ -158,8 +158,11 @@ class ChatService:
         user_id: str = None,
         jwt_token: str = None,
         previous_response_id: str = None,
+        filters: dict = None,
+        limit: int = None,
+        score_threshold: float = None,
     ):
-        """Handle Langflow chat requests"""
+        """Handle Langflow nudges chat requests with knowledge filters"""
 
         if not LANGFLOW_URL or not NUDGES_FLOW_ID:
             raise ValueError(
@@ -171,6 +174,67 @@ class ChatService:
         if jwt_token:
             extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
 
+        # Build the complete filter expression like the chat service does
+        filter_expression = {}
+        has_user_filters = False
+        filter_clauses = []
+
+        if filters:
+            # 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:
+                has_user_filters = True
+
+        # If no user filters are active, exclude sample data from nudges
+        if not has_user_filters:
+            # Add a bool query with must_not to exclude sample data
+            filter_clauses.append({
+                "bool": {
+                    "must_not": [
+                        {"term": {"is_sample_data": "true"}}
+                    ]
+                }
+            })
+            logger.info("Excluding sample data from nudges (no user filters active)")
+
+        # Set the filter clauses if we have any
+        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)
+        logger.info(
+            "Sending OpenRAG query filter to Langflow nudges",
+            filter_expression=filter_expression,
+        )
+        extra_headers["X-LANGFLOW-GLOBAL-VAR-OPENRAG-QUERY-FILTER"] = json.dumps(
+            filter_expression
+        )
+        logger.info(f"[NUDGES] Extra headers {extra_headers}")
+
         # Ensure the Langflow client exists; try lazy init if needed
         langflow_client = await clients.ensure_langflow_client()
         if not langflow_client: