Dupe IDs are handled when use_existing_tensors=True

src/marqo/errors.py

@@ -59,7 +59,7 @@ def __str__(self) -> str:
 
 class MarqoWebError(Exception):
 
-    status_code: int = None
+    status_code: int = 500
     error_type: str = None
     message: str = None
     code: str = None

src/marqo/tensor_search/tensor_search.py

@@ -373,6 +373,7 @@ def _infer_opensearch_data_type(
 
 def _get_chunks_for_field(field_name: str, doc_id: str, doc):
     # Find the chunks with a specific __field_name in a doc
+    # Note: for a chunkless doc (nothing was tensorised) --> doc["_source"]["__chunks"] == []
     return [chunk for chunk in doc["_source"]["__chunks"] if chunk["__field_name"] == field_name]
 
 
@@ -456,8 +457,12 @@ def add_documents(config: Config, index_name: str, docs: List[dict], auto_refres
                     f"images for {batch_size} docs using {image_download_thread_count} threads ")
 
     if update_mode == 'replace' and use_existing_tensors:
-        # Get existing documents
-        doc_ids = [doc["_id"] for doc in docs if "_id" in doc]
+        doc_ids = []
+
+        # Iterate through the list in reverse, only latest doc with dupe id gets added.
+        for i in range(len(docs)-1, -1, -1):
+            if ("_id" in docs[i]) and (docs[i]["_id"] not in doc_ids):
+                doc_ids.append(docs[i]["_id"])
         existing_docs = _get_documents_for_upsert(config=config, index_name=index_name, document_ids=doc_ids)
 
     for i, doc in enumerate(docs):
@@ -497,6 +502,8 @@ def add_documents(config: Config, index_name: str, docs: List[dict], auto_refres
                 # have IDs:
                 elif len(matching_doc) == 0:
                     existing_doc = {"found": False}
+                else:
+                    raise errors.InternalError(message= f"Upsert: found {len(matching_doc)} matching docs for {doc_id} when only 1 or 0 should have been found.")
         else:
             indexing_instructions["update"]["_id"] = doc_id
 
@@ -541,7 +548,6 @@ def add_documents(config: Config, index_name: str, docs: List[dict], auto_refres
             # Check if content of this field changed. If no, skip all chunking and vectorisation
             if ((update_mode == 'replace') and use_existing_tensors and existing_doc["found"]
                     and (field in existing_doc["_source"]) and (existing_doc["_source"][field] == field_content)):
-                # logger.info(f"Using existing vectors for doc {doc_id}, field {field}. Content remains unchanged.")
                 chunks_to_append = _get_chunks_for_field(field_name=field, doc_id=doc_id, doc=existing_doc)
 
             # Chunk and vectorise, since content changed.
@@ -651,9 +657,7 @@ def add_documents(config: Config, index_name: str, docs: List[dict], auto_refres
                         TensorField.field_content: text_chunk,
                         TensorField.field_name: field
                     })
-
-            # Add chunks_to_append along with doc metadata to total chunks
-
+
             elif isinstance(field_content, dict):
                 if mappings[field]["type"]=="multimodal_combination":
                     combo_chunk, combo_document_is_valid, unsuccessful_doc_to_append, combo_vectorise_time_to_add,\
@@ -669,9 +673,11 @@ def add_documents(config: Config, index_name: str, docs: List[dict], auto_refres
                         if field not in new_obj_fields:
                             new_obj_fields[field] = set()
                         new_obj_fields[field] = new_obj_fields[field].union(new_fields_from_multimodal_combination)
+                        # TODO: we may want to use chunks_to_append here to make it uniform with use_existing_tensors and normal vectorisation
                         chunks.append({**combo_chunk, **chunk_values_for_filtering})
                         continue
-
+
+            # Add chunks_to_append along with doc metadata to total chunks
             for chunk in chunks_to_append:
                 chunks.append({**chunk, **chunk_values_for_filtering})
 
@@ -893,6 +899,7 @@ def _get_documents_for_upsert(
             f"set by the environment variable `{EnvVars.MARQO_MAX_RETRIEVABLE_DOCS}`")
 
     # Chunk Docs (get field name, field content, vectors)
+
     chunk_docs = [
         {"_index": index_name, "_id": doc_id,
          "_source": {"include": [f"__chunks.__field_content", f"__chunks.__field_name", f"__chunks.__vector_*"]}}
@@ -913,19 +920,21 @@ def _get_documents_for_upsert(
 
     # Combine the 2 query results (loop through each doc id)
     combined_result = []
-    for doc_id in document_ids:
+
+    for doc_id in valid_doc_ids:
         # There should always be 2 results per doc.
         result_list = [doc for doc in res["docs"] if doc["_id"] == doc_id]
+
         if len(result_list) == 0:
             continue
         if len(result_list) not in (2, 0):
-            raise errors.MarqoWebError(f"Bad request for existing documents. "
+            raise errors.InternalError(f"Internal error fetching old documents. "
                                        f"There are {len(result_list)} results for doc id {doc_id}.")
 
         for result in result_list:
             if result["found"]:
                 doc_in_results = True
-                if result["_source"]["__chunks"] == []:
+                if ("__chunks" in result["_source"]) and (result["_source"]["__chunks"] == []):
                     res_data = result
                 else:
                     res_chunks = result
@@ -934,12 +943,14 @@ def _get_documents_for_upsert(
                 dummy_res = result
                 break
 
-        # Put the chunks list in res_data, so it's complete
+        # Put the chunks list in res_data, so it contains all doc data
         if doc_in_results:
-            res_data["_source"]["__chunks"] = res_chunks["_source"]["__chunks"]
+            # Only add chunks if not a chunkless doc
+            if res_chunks["_source"]:
+                res_data["_source"]["__chunks"] = res_chunks["_source"]["__chunks"]
             combined_result.append(res_data)
         else:
-            # This result just says that the doc was not found
+            # This result just says that the doc was not found ("found": False)
             combined_result.append(dummy_res)
 
     res["docs"] = combined_result

tests/tensor_search/test_add_documents.py

@@ -66,6 +66,51 @@ def test_add_plain_id_field(self):
                 "title 1": "content 1",
                 "desc 2": "content 2. blah blah blah"
             }
+
+    def test_add_documents_dupe_ids(self):
+        """ 
+        Should only use the latest inserted ID. Make sure it doesn't get the first/middle one
+        """
+
+        tensor_search.add_documents(config=self.config, index_name=self.index_name_1, docs=[
+            {
+                "_id": "3",
+                "title": "doc 3b"
+            },
+
+        ], auto_refresh=True)
+
+        doc_3_solo = tensor_search.get_document_by_id(
+            config=self.config, index_name=self.index_name_1,
+            document_id="3", show_vectors=True)
+
+        tensor_search.delete_index(config=self.config, index_name=self.index_name_1)
+        tensor_search.add_documents(config=self.config, index_name=self.index_name_1, docs=[
+            {
+                "_id": "1",
+                "title": "doc 1"
+            },
+            {
+                "_id": "2",
+                "title": "doc 2",
+            },
+            {
+                "_id": "3",
+                "title": "doc 3a",
+            },
+            {
+                "_id": "3",
+                "title": "doc 3b"
+            },
+
+        ], auto_refresh=True)
+
+        doc_3_duped = tensor_search.get_document_by_id(
+            config=self.config, index_name=self.index_name_1,
+            document_id="3", show_vectors=True)
+
+        self.assertEqual(doc_3_solo, doc_3_duped)
+
 
     def test_update_docs_update_chunks(self):
         """Updating a doc needs to update the corresponding chunks"
@@ -259,16 +304,74 @@ def test_add_documents_validation(self):
              {"_id": "to_fail_567", "some other obj": AssertionError}],
             [{"_id": "to_fail_567", "blahblah": max}]
         ]
-        for update_mode in ('replace', 'update'):
+
+        # For update
+        for bad_doc_arg in bad_doc_args:
+            add_res = tensor_search.add_documents(
+                config=self.config, index_name=self.index_name_1,
+                docs=bad_doc_arg, auto_refresh=True, update_mode='update')
+            assert add_res['errors'] is True
+            assert all(['error' in item for item in add_res['items'] if item['_id'].startswith('to_fail')])
+            assert all(['result' in item
+                        for item in add_res['items'] if item['_id'].startswith('to_pass')])
+
+        # For replace, check with use_existing_tensors True and False
+        for use_existing_tensors_flag in (True, False):
             for bad_doc_arg in bad_doc_args:
                 add_res = tensor_search.add_documents(
                     config=self.config, index_name=self.index_name_1,
-                    docs=bad_doc_arg, auto_refresh=True, update_mode=update_mode)
+                    docs=bad_doc_arg, auto_refresh=True, update_mode='replace', use_existing_tensors=use_existing_tensors_flag)
                 assert add_res['errors'] is True
                 assert all(['error' in item for item in add_res['items'] if item['_id'].startswith('to_fail')])
                 assert all(['result' in item
                             for item in add_res['items'] if item['_id'].startswith('to_pass')])
 
+
+    def test_add_documents_id_validation(self):
+        """These bad docs should return errors"""
+        bad_doc_args = [
+            # Wrong data types for ID
+            # Tuple: (doc_list, number of docs that should succeed)
+            ([{"_id": {}, "field_1": 1234}], 0),
+            ([{"_id": dict(), "field_1": 1234}], 0),
+            ([{"_id": [1, 2, 3], "field_1": 1234}], 0),
+            ([{"_id": 4, "field_1": 1234}], 0),
+            ([{"_id": None, "field_1": 1234}], 0),
+
+            ([{"_id": "proper id", "field_1": 5678},
+            {"_id": ["bad", "id"], "field_1": "zzz"},
+            {"_id": "proper id 2", "field_1": 90}], 2)
+        ]
+
+        # For update
+        for bad_doc_arg in bad_doc_args:
+            add_res = tensor_search.add_documents(
+                config=self.config, index_name=self.index_name_1,
+                docs=bad_doc_arg[0], auto_refresh=True, update_mode='update')
+
+            assert add_res['errors'] is True
+
+            succeeded_count = 0
+            for item in add_res['items']:
+                if 'result' in item:
+                    succeeded_count += 1
+
+            assert succeeded_count == bad_doc_arg[1]
+
+        # For replace, check with use_existing_tensors True and False
+        for use_existing_tensors_flag in (True, False):
+            for bad_doc_arg in bad_doc_args:
+                add_res = tensor_search.add_documents(
+                    config=self.config, index_name=self.index_name_1,
+                    docs=bad_doc_arg[0], auto_refresh=True, update_mode='replace', use_existing_tensors=use_existing_tensors_flag)
+                assert add_res['errors'] is True
+                succeeded_count = 0
+                for item in add_res['items']:
+                    if 'result' in item:
+                        succeeded_count += 1
+
+                assert succeeded_count == bad_doc_arg[1]
+
     def test_add_documents_list_non_tensor_validation(self):
         """This doc is valid but should return error because my_field is not marked non-tensor"""
         bad_doc_args = [