fix: Accept appropriate types in OpenSearch mm (#12547)

* fix: Accept appropriate types in OpenSearch mm

* [autofix.ci] apply automated fixes

* Update opensearch_multimodal.py

* [autofix.ci] apply automated fixes

* [autofix.ci] apply automated fixes

* [autofix.ci] apply automated fixes (attempt 2/3)

* [autofix.ci] apply automated fixes (attempt 3/3)

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

Author: 2 people

src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json

@@ -3103,7 +3103,8 @@
                 "info": "",
                 "input_types": [
                   "Data",
-                  "DataFrame"
+                  "DataFrame",
+                  "Table"
                 ],
                 "list": true,
                 "list_add_label": "Add More",

src/backend/base/langflow/initial_setup/starter_projects/Nvidia Remix.json

@@ -106,7 +106,8 @@
             "id": "FAISS-Ugchq",
             "inputTypes": [
               "Data",
-              "DataFrame"
+              "DataFrame",
+              "Table"
             ],
             "type": "other"
           }
@@ -116,7 +117,7 @@
         "source": "RemixDocumentation-aT7Gm",
         "sourceHandle": "{œdataTypeœ: œRemixDocumentationœ, œidœ: œRemixDocumentation-aT7Gmœ, œnameœ: œdataframe_outputœ, œoutput_typesœ: [œTableœ]}",
         "target": "FAISS-Ugchq",
-        "targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œFAISS-Ugchqœ, œinputTypesœ: [œDataœ, œDataFrameœ], œtypeœ: œotherœ}"
+        "targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œFAISS-Ugchqœ, œinputTypesœ: [œDataœ, œDataFrameœ, œTableœ], œtypeœ: œotherœ}"
       },
       {
         "animated": false,
@@ -2103,7 +2104,8 @@
                 "info": "",
                 "input_types": [
                   "Data",
-                  "DataFrame"
+                  "DataFrame",
+                  "Table"
                 ],
                 "list": true,
                 "list_add_label": "Add More",

src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json

@@ -164,45 +164,18 @@
             "id": "AstraDB-mJvb6",
             "inputTypes": [
               "Data",
-              "DataFrame"
+              "DataFrame",
+              "Table"
             ],
             "type": "other"
           }
         },
         "id": "reactflow__edge-SplitText-NTQIl{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-NTQIlœ,œnameœ:œdataframeœ,œoutput_typesœ:[œDataFrameœ]}-AstraDB-mJvb6{œfieldNameœ:œingest_dataœ,œidœ:œAstraDB-mJvb6œ,œinputTypesœ:[œDataœ,œDataFrameœ],œtypeœ:œotherœ}",
         "selected": false,
-        "source": "SplitText-NTQIl",
-        "sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-NTQIlœ, œnameœ: œdataframeœ, œoutput_typesœ: [œDataFrameœ]}",
-        "target": "AstraDB-mJvb6",
-        "targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œAstraDB-mJvb6œ, œinputTypesœ: [œDataœ, œDataFrameœ], œtypeœ: œotherœ}"
-      },
-      {
-        "animated": false,
-        "className": "",
-        "data": {
-          "sourceHandle": {
-            "dataType": "ChatInput",
-            "id": "ChatInput-z5C0I",
-            "name": "message",
-            "output_types": [
-              "Message"
-            ]
-          },
-          "targetHandle": {
-            "fieldName": "search_query",
-            "id": "AstraDB-ZiGZI",
-            "inputTypes": [
-              "Message"
-            ],
-            "type": "query"
-          }
-        },
-        "id": "reactflow__edge-ChatInput-z5C0I{œdataTypeœ:œChatInputœ,œidœ:œChatInput-z5C0Iœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-ZiGZI{œfieldNameœ:œsearch_queryœ,œidœ:œAstraDB-ZiGZIœ,œinputTypesœ:[œMessageœ],œtypeœ:œqueryœ}",
-        "selected": false,
-        "source": "ChatInput-z5C0I",
-        "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-z5C0Iœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}",
-        "target": "AstraDB-ZiGZI",
-        "targetHandle": "{œfieldNameœ: œsearch_queryœ, œidœ: œAstraDB-ZiGZIœ, œinputTypesœ: [œMessageœ], œtypeœ: œqueryœ}"
+        "source": "SplitText-dswy4",
+        "sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-dswy4œ, œnameœ: œdataframeœ, œoutput_typesœ: [œTableœ]}",
+        "target": "AstraDB-2kFlp",
+        "targetHandle": "{œfieldNameœ: œingest_dataœ, œidœ: œAstraDB-2kFlpœ, œinputTypesœ: [œDataœ, œDataFrameœ, œTableœ], œtypeœ: œotherœ}"
       },
       {
         "animated": false,
@@ -3461,7 +3434,8 @@
                 "info": "",
                 "input_types": [
                   "Data",
-                  "DataFrame"
+                  "DataFrame",
+                  "Table"
                 ],
                 "list": true,
                 "list_add_label": "Add More",
@@ -4296,7 +4270,8 @@
                 "info": "",
                 "input_types": [
                   "Data",
-                  "DataFrame"
+                  "DataFrame",
+                  "Table"
                 ],
                 "list": true,
                 "list_add_label": "Add More",

src/lfx/src/lfx/_assets/component_index.json

@@ -60,7 +60,7 @@ def __init_subclass__(cls, **kwargs):
         HandleInput(
             name="ingest_data",
             display_name="Ingest Data",
-            input_types=["Data", "DataFrame"],
+            input_types=["Data", "DataFrame", "Table"],
             is_list=True,
         ),
         QueryInput(

src/lfx/src/lfx/base/vectorstores/model.py

@@ -25,6 +25,7 @@
 )
 from lfx.log import logger
 from lfx.schema.data import Data
+from lfx.schema.dataframe import Table
 
 REQUEST_TIMEOUT = 60
 MAX_RETRIES = 5
@@ -154,7 +155,7 @@ class OpenSearchVectorStoreComponentMultimodalMultiEmbedding(LCVectorStoreCompon
                 },
             ],
             value=[],
-            input_types=["Data"],
+            input_types=["Data", "JSON"],
         ),
         StrInput(
             name="opensearch_url",
@@ -1981,17 +1982,17 @@ def search(self, query: str | None = None) -> list[dict[str, Any]]:
             for hit in hits
         ]
 
-    def search_documents(self) -> list[Data]:
+    def search_documents(self) -> Table:
         """Search documents and return results as Data objects.
 
         This is the main interface method that performs the multi-model search using the
-        configured search_query and returns results in Langflow's Data format.
+        configured search_query and returns results in Langflow's Table format.
 
         Always builds the vector store (triggering ingestion if needed), then performs
         search only if a query is provided.
 
         Returns:
-            List of Data objects containing search results with text and metadata
+            Table: A table containing search results with text and metadata
 
         Raises:
             Exception: If search operation fails
@@ -2010,7 +2011,9 @@ def search_documents(self) -> list[Data]:
 
             # Perform search with the provided query
             raw = self.search(search_query)
-            return [Data(text=hit["page_content"], **hit["metadata"]) for hit in raw]
+            raw_list = [Data(text=hit["page_content"], **hit["metadata"]) for hit in raw]
+
+            return Table(data=raw_list)
         except Exception as e:
             self.log(f"search_documents error: {e}")
             raise