.

backend/onyx/indexing/adapters/document_indexing_adapter.py

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import contextlib
 from collections.abc import Generator
 
@@ -19,7 +21,8 @@ from onyx.db.document import update_docs_updated_at__no_commit
 from onyx.db.document_set import fetch_document_sets_for_documents
 from onyx.indexing.indexing_pipeline import DocumentBatchPrepareContext
 from onyx.indexing.indexing_pipeline import index_doc_batch_prepare
-from onyx.indexing.models import BuildMetadataAwareChunksResult
+from onyx.indexing.models import ChunkEnrichmentContext
+from onyx.indexing.models import DocAwareChunk
 from onyx.indexing.models import DocMetadataAwareIndexChunk
 from onyx.indexing.models import IndexChunk
 from onyx.indexing.models import UpdatableChunkData
@@ -85,14 +88,21 @@ class DocumentIndexingBatchAdapter:
         ) as transaction:
             yield transaction
 
-    def build_metadata_aware_chunks(
+    def prepare_enrichment(
         self,
-        chunks_with_embeddings: list[IndexChunk],
-        chunk_content_scores: list[float],
-        tenant_id: str,
         context: DocumentBatchPrepareContext,
-    ) -> BuildMetadataAwareChunksResult:
-        """Enrich chunks with access, document sets, boosts, token counts, and hierarchy."""
+        tenant_id: str,
+        chunks: list[DocAwareChunk],
+    ) -> DocumentChunkEnricher:
+        """Do all DB lookups once and return a per-chunk enricher."""
+        updatable_ids = [doc.id for doc in context.updatable_docs]
+
+        doc_id_to_new_chunk_cnt: dict[str, int] = {
+            doc_id: 0 for doc_id in updatable_ids
+        }
+        for chunk in chunks:
+            if chunk.source_document.id in doc_id_to_new_chunk_cnt:
+                doc_id_to_new_chunk_cnt[chunk.source_document.id] += 1
 
         no_access = DocumentAccess.build(
             user_emails=[],
@@ -102,67 +112,30 @@ class DocumentIndexingBatchAdapter:
             is_public=False,
         )
 
-        updatable_ids = [doc.id for doc in context.updatable_docs]
-
-        doc_id_to_access_info = get_access_for_documents(
-            document_ids=updatable_ids, db_session=self.db_session
-        )
-        doc_id_to_document_set = {
-            document_id: document_sets
-            for document_id, document_sets in fetch_document_sets_for_documents(
+        return DocumentChunkEnricher(
+            doc_id_to_access_info=get_access_for_documents(
                 document_ids=updatable_ids, db_session=self.db_session
-            )
-        }
-
-        doc_id_to_previous_chunk_cnt: dict[str, int] = {
-            document_id: chunk_count
-            for document_id, chunk_count in fetch_chunk_counts_for_documents(
-                document_ids=updatable_ids,
-                db_session=self.db_session,
-            )
-        }
-
-        doc_id_to_new_chunk_cnt: dict[str, int] = {
-            doc_id: 0 for doc_id in updatable_ids
-        }
-        for chunk in chunks_with_embeddings:
-            if chunk.source_document.id in doc_id_to_new_chunk_cnt:
-                doc_id_to_new_chunk_cnt[chunk.source_document.id] += 1
-
-        # Get ancestor hierarchy node IDs for each document
-        doc_id_to_ancestor_ids = self._get_ancestor_ids_for_documents(
-            context.updatable_docs, tenant_id
-        )
-
-        access_aware_chunks = [
-            DocMetadataAwareIndexChunk.from_index_chunk(
-                index_chunk=chunk,
-                access=doc_id_to_access_info.get(chunk.source_document.id, no_access),
-                document_sets=set(
-                    doc_id_to_document_set.get(chunk.source_document.id, [])
-                ),
-                user_project=[],
-                personas=[],
-                boost=(
-                    context.id_to_boost_map[chunk.source_document.id]
-                    if chunk.source_document.id in context.id_to_boost_map
-                    else DEFAULT_BOOST
-                ),
-                tenant_id=tenant_id,
-                aggregated_chunk_boost_factor=chunk_content_scores[chunk_num],
-                ancestor_hierarchy_node_ids=doc_id_to_ancestor_ids[
-                    chunk.source_document.id
-                ],
-            )
-            for chunk_num, chunk in enumerate(chunks_with_embeddings)
-        ]
-
-        return BuildMetadataAwareChunksResult(
-            chunks=access_aware_chunks,
-            doc_id_to_previous_chunk_cnt=doc_id_to_previous_chunk_cnt,
-            doc_id_to_new_chunk_cnt=doc_id_to_new_chunk_cnt,
-            user_file_id_to_raw_text={},
-            user_file_id_to_token_count={},
+            ),
+            doc_id_to_document_set={
+                document_id: document_sets
+                for document_id, document_sets in fetch_document_sets_for_documents(
+                    document_ids=updatable_ids, db_session=self.db_session
+                )
+            },
+            doc_id_to_ancestor_ids=self._get_ancestor_ids_for_documents(
+                context.updatable_docs, tenant_id
+            ),
+            id_to_boost_map=context.id_to_boost_map,
+            doc_id_to_previous_chunk_cnt={
+                document_id: chunk_count
+                for document_id, chunk_count in fetch_chunk_counts_for_documents(
+                    document_ids=updatable_ids,
+                    db_session=self.db_session,
+                )
+            },
+            doc_id_to_new_chunk_cnt=dict(doc_id_to_new_chunk_cnt),
+            no_access=no_access,
+            tenant_id=tenant_id,
         )
 
     def _get_ancestor_ids_for_documents(
@@ -203,7 +176,7 @@ class DocumentIndexingBatchAdapter:
         context: DocumentBatchPrepareContext,
         updatable_chunk_data: list[UpdatableChunkData],
         filtered_documents: list[Document],
-        result: BuildMetadataAwareChunksResult,
+        enrichment: ChunkEnrichmentContext,
     ) -> None:
         """Finalize DB updates, store plaintext, and mark docs as indexed."""
         updatable_ids = [doc.id for doc in context.updatable_docs]
@@ -227,7 +200,7 @@ class DocumentIndexingBatchAdapter:
 
         update_docs_chunk_count__no_commit(
             document_ids=updatable_ids,
-            doc_id_to_chunk_count=result.doc_id_to_new_chunk_cnt,
+            doc_id_to_chunk_count=enrichment.doc_id_to_new_chunk_cnt,
             db_session=self.db_session,
         )
 
@@ -249,3 +222,52 @@ class DocumentIndexingBatchAdapter:
         )
 
         self.db_session.commit()
+
+
+class DocumentChunkEnricher:
+    """Pre-computed metadata for per-chunk enrichment of connector documents."""
+
+    def __init__(
+        self,
+        doc_id_to_access_info: dict[str, DocumentAccess],
+        doc_id_to_document_set: dict[str, list[str]],
+        doc_id_to_ancestor_ids: dict[str, list[int]],
+        id_to_boost_map: dict[str, int],
+        doc_id_to_previous_chunk_cnt: dict[str, int],
+        doc_id_to_new_chunk_cnt: dict[str, int],
+        no_access: DocumentAccess,
+        tenant_id: str,
+    ) -> None:
+        self._doc_id_to_access_info = doc_id_to_access_info
+        self._doc_id_to_document_set = doc_id_to_document_set
+        self._doc_id_to_ancestor_ids = doc_id_to_ancestor_ids
+        self._id_to_boost_map = id_to_boost_map
+        self._no_access = no_access
+        self._tenant_id = tenant_id
+        self.doc_id_to_previous_chunk_cnt = doc_id_to_previous_chunk_cnt
+        self.doc_id_to_new_chunk_cnt = doc_id_to_new_chunk_cnt
+
+    def enrich_chunk(
+        self, chunk: IndexChunk, score: float
+    ) -> DocMetadataAwareIndexChunk:
+        return DocMetadataAwareIndexChunk.from_index_chunk(
+            index_chunk=chunk,
+            access=self._doc_id_to_access_info.get(
+                chunk.source_document.id, self._no_access
+            ),
+            document_sets=set(
+                self._doc_id_to_document_set.get(chunk.source_document.id, [])
+            ),
+            user_project=[],
+            personas=[],
+            boost=(
+                self._id_to_boost_map[chunk.source_document.id]
+                if chunk.source_document.id in self._id_to_boost_map
+                else DEFAULT_BOOST
+            ),
+            tenant_id=self._tenant_id,
+            aggregated_chunk_boost_factor=score,
+            ancestor_hierarchy_node_ids=self._doc_id_to_ancestor_ids[
+                chunk.source_document.id
+            ],
+        )

backend/onyx/indexing/adapters/user_file_indexing_adapter.py

@@ -1,6 +1,9 @@
+from __future__ import annotations
+
 import contextlib
 import datetime
 import time
+from collections import defaultdict
 from collections.abc import Generator
 from uuid import UUID
 
@@ -24,7 +27,8 @@ from onyx.db.user_file import fetch_persona_ids_for_user_files
 from onyx.db.user_file import fetch_user_project_ids_for_user_files
 from onyx.file_store.utils import store_user_file_plaintext
 from onyx.indexing.indexing_pipeline import DocumentBatchPrepareContext
-from onyx.indexing.models import BuildMetadataAwareChunksResult
+from onyx.indexing.models import ChunkEnrichmentContext
+from onyx.indexing.models import DocAwareChunk
 from onyx.indexing.models import DocMetadataAwareIndexChunk
 from onyx.indexing.models import IndexChunk
 from onyx.indexing.models import UpdatableChunkData
@@ -101,13 +105,20 @@ class UserFileIndexingAdapter:
                 f"Failed to acquire locks after {_NUM_LOCK_ATTEMPTS} attempts for user files: {[doc.id for doc in documents]}"
             )
 
-    def build_metadata_aware_chunks(
+    def prepare_enrichment(
         self,
-        chunks_with_embeddings: list[IndexChunk],
-        chunk_content_scores: list[float],
-        tenant_id: str,
         context: DocumentBatchPrepareContext,
-    ) -> BuildMetadataAwareChunksResult:
+        tenant_id: str,
+        chunks: list[DocAwareChunk],
+    ) -> UserFileChunkEnricher:
+        """Do all DB lookups and pre-compute file metadata from chunks."""
+        updatable_ids = [doc.id for doc in context.updatable_docs]
+
+        doc_id_to_new_chunk_cnt: dict[str, int] = defaultdict(int)
+        content_by_file: dict[str, list[str]] = defaultdict(list)
+        for chunk in chunks:
+            doc_id_to_new_chunk_cnt[chunk.source_document.id] += 1
+            content_by_file[chunk.source_document.id].append(chunk.content)
 
         no_access = DocumentAccess.build(
             user_emails=[],
@@ -117,7 +128,6 @@ class UserFileIndexingAdapter:
             is_public=False,
         )
 
-        updatable_ids = [doc.id for doc in context.updatable_docs]
         user_file_id_to_project_ids = fetch_user_project_ids_for_user_files(
             user_file_ids=updatable_ids,
             db_session=self.db_session,
@@ -138,17 +148,6 @@ class UserFileIndexingAdapter:
             )
         }
 
-        user_file_id_to_new_chunk_cnt: dict[str, int] = {
-            user_file_id: len(
-                [
-                    chunk
-                    for chunk in chunks_with_embeddings
-                    if chunk.source_document.id == user_file_id
-                ]
-            )
-            for user_file_id in updatable_ids
-        }
-
         # Initialize tokenizer used for token count calculation
         try:
             llm = get_default_llm()
@@ -163,15 +162,9 @@ class UserFileIndexingAdapter:
         user_file_id_to_raw_text: dict[str, str] = {}
         user_file_id_to_token_count: dict[str, int | None] = {}
         for user_file_id in updatable_ids:
-            user_file_chunks = [
-                chunk
-                for chunk in chunks_with_embeddings
-                if chunk.source_document.id == user_file_id
-            ]
-            if user_file_chunks:
-                combined_content = " ".join(
-                    [chunk.content for chunk in user_file_chunks]
-                )
+            contents = content_by_file.get(user_file_id)
+            if contents:
+                combined_content = " ".join(contents)
                 user_file_id_to_raw_text[str(user_file_id)] = combined_content
                 token_count = (
                     len(llm_tokenizer.encode(combined_content)) if llm_tokenizer else 0
@@ -181,28 +174,16 @@ class UserFileIndexingAdapter:
                 user_file_id_to_raw_text[str(user_file_id)] = ""
                 user_file_id_to_token_count[str(user_file_id)] = None
 
-        access_aware_chunks = [
-            DocMetadataAwareIndexChunk.from_index_chunk(
-                index_chunk=chunk,
-                access=user_file_id_to_access.get(chunk.source_document.id, no_access),
-                document_sets=set(),
-                user_project=user_file_id_to_project_ids.get(
-                    chunk.source_document.id, []
-                ),
-                personas=user_file_id_to_persona_ids.get(chunk.source_document.id, []),
-                boost=DEFAULT_BOOST,
-                tenant_id=tenant_id,
-                aggregated_chunk_boost_factor=chunk_content_scores[chunk_num],
-            )
-            for chunk_num, chunk in enumerate(chunks_with_embeddings)
-        ]
-
-        return BuildMetadataAwareChunksResult(
-            chunks=access_aware_chunks,
+        return UserFileChunkEnricher(
+            user_file_id_to_access=user_file_id_to_access,
+            user_file_id_to_project_ids=user_file_id_to_project_ids,
+            user_file_id_to_persona_ids=user_file_id_to_persona_ids,
             doc_id_to_previous_chunk_cnt=user_file_id_to_previous_chunk_cnt,
-            doc_id_to_new_chunk_cnt=user_file_id_to_new_chunk_cnt,
+            doc_id_to_new_chunk_cnt=dict(doc_id_to_new_chunk_cnt),
             user_file_id_to_raw_text=user_file_id_to_raw_text,
             user_file_id_to_token_count=user_file_id_to_token_count,
+            no_access=no_access,
+            tenant_id=tenant_id,
         )
 
     def _notify_assistant_owners_if_files_ready(
@@ -246,8 +227,9 @@ class UserFileIndexingAdapter:
         context: DocumentBatchPrepareContext,
         updatable_chunk_data: list[UpdatableChunkData],  # noqa: ARG002
         filtered_documents: list[Document],  # noqa: ARG002
-        result: BuildMetadataAwareChunksResult,
+        enrichment: ChunkEnrichmentContext,
     ) -> None:
+        assert isinstance(enrichment, UserFileChunkEnricher)
         user_file_ids = [doc.id for doc in context.updatable_docs]
 
         user_files = (
@@ -263,8 +245,10 @@ class UserFileIndexingAdapter:
             user_file.last_project_sync_at = datetime.datetime.now(
                 datetime.timezone.utc
             )
-            user_file.chunk_count = result.doc_id_to_new_chunk_cnt[str(user_file.id)]
-            user_file.token_count = result.user_file_id_to_token_count[
+            user_file.chunk_count = enrichment.doc_id_to_new_chunk_cnt.get(
+                str(user_file.id), 0
+            )
+            user_file.token_count = enrichment.user_file_id_to_token_count[
                 str(user_file.id)
             ]
 
@@ -276,8 +260,54 @@ class UserFileIndexingAdapter:
         # Store the plaintext in the file store for faster retrieval
         # NOTE: this creates its own session to avoid committing the overall
         # transaction.
-        for user_file_id, raw_text in result.user_file_id_to_raw_text.items():
+        for user_file_id, raw_text in enrichment.user_file_id_to_raw_text.items():
             store_user_file_plaintext(
                 user_file_id=UUID(user_file_id),
                 plaintext_content=raw_text,
             )
+
+
+class UserFileChunkEnricher:
+    """Pre-computed metadata for per-chunk enrichment of user-uploaded files."""
+
+    def __init__(
+        self,
+        user_file_id_to_access: dict[str, DocumentAccess],
+        user_file_id_to_project_ids: dict[str, list[int]],
+        user_file_id_to_persona_ids: dict[str, list[int]],
+        doc_id_to_previous_chunk_cnt: dict[str, int],
+        doc_id_to_new_chunk_cnt: dict[str, int],
+        user_file_id_to_raw_text: dict[str, str],
+        user_file_id_to_token_count: dict[str, int | None],
+        no_access: DocumentAccess,
+        tenant_id: str,
+    ) -> None:
+        self._user_file_id_to_access = user_file_id_to_access
+        self._user_file_id_to_project_ids = user_file_id_to_project_ids
+        self._user_file_id_to_persona_ids = user_file_id_to_persona_ids
+        self._no_access = no_access
+        self._tenant_id = tenant_id
+        self.doc_id_to_previous_chunk_cnt = doc_id_to_previous_chunk_cnt
+        self.doc_id_to_new_chunk_cnt = doc_id_to_new_chunk_cnt
+        self.user_file_id_to_raw_text = user_file_id_to_raw_text
+        self.user_file_id_to_token_count = user_file_id_to_token_count
+
+    def enrich_chunk(
+        self, chunk: IndexChunk, score: float
+    ) -> DocMetadataAwareIndexChunk:
+        return DocMetadataAwareIndexChunk.from_index_chunk(
+            index_chunk=chunk,
+            access=self._user_file_id_to_access.get(
+                chunk.source_document.id, self._no_access
+            ),
+            document_sets=set(),
+            user_project=self._user_file_id_to_project_ids.get(
+                chunk.source_document.id, []
+            ),
+            personas=self._user_file_id_to_persona_ids.get(
+                chunk.source_document.id, []
+            ),
+            boost=DEFAULT_BOOST,
+            tenant_id=self._tenant_id,
+            aggregated_chunk_boost_factor=score,
+        )

backend/onyx/indexing/indexing_pipeline.py

@@ -1,5 +1,7 @@
 from collections import defaultdict
 from collections.abc import Callable
+from collections.abc import Iterable
+from typing import cast
 from typing import Protocol
 
 from pydantic import BaseModel
@@ -47,6 +49,7 @@ from onyx.indexing.chunker import Chunker
 from onyx.indexing.embedder import embed_chunks_with_failure_handling
 from onyx.indexing.embedder import IndexingEmbedder
 from onyx.indexing.models import DocAwareChunk
+from onyx.indexing.models import DocMetadataAwareIndexChunk
 from onyx.indexing.models import IndexingBatchAdapter
 from onyx.indexing.models import UpdatableChunkData
 from onyx.indexing.vector_db_insertion import write_chunks_to_vector_db_with_backoff
@@ -91,6 +94,15 @@ class IndexingPipelineResult(BaseModel):
 
     failures: list[ConnectorFailure]
 
+    @classmethod
+    def empty(cls, total_docs: int) -> "IndexingPipelineResult":
+        return cls(
+            new_docs=0,
+            total_docs=total_docs,
+            total_chunks=0,
+            failures=[],
+        )
+
 
 class IndexingPipelineProtocol(Protocol):
     def __call__(
@@ -672,12 +684,7 @@ def index_doc_batch(
     filtered_documents = filter_fnc(document_batch)
     context = adapter.prepare(filtered_documents, ignore_time_skip)
     if not context:
-        return IndexingPipelineResult(
-            new_docs=0,
-            total_docs=len(filtered_documents),
-            total_chunks=0,
-            failures=[],
-        )
+        return IndexingPipelineResult.empty(len(filtered_documents))
 
     # Convert documents to IndexingDocument objects with processed section
     # logger.debug("Processing image sections")
@@ -748,19 +755,29 @@ def index_doc_batch(
         # we still write data here for the immediate and most likely correct sync, but
         # to resolve this, an update of the last modified field at the end of this loop
         # always triggers a final metadata sync via the celery queue
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=chunks_with_embeddings,
-            chunk_content_scores=chunk_content_scores,
-            tenant_id=tenant_id,
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id=tenant_id,
+            chunks=cast(list[DocAwareChunk], chunks_with_embeddings),
         )
 
-        short_descriptor_list = [chunk.to_short_descriptor() for chunk in result.chunks]
+        metadata_aware_chunks = [
+            enricher.enrich_chunk(chunk, score)
+            for chunk, score in zip(chunks_with_embeddings, chunk_content_scores)
+        ]
+
+        short_descriptor_list = [
+            chunk.to_short_descriptor() for chunk in metadata_aware_chunks
+        ]
         short_descriptor_log = str(short_descriptor_list)[:1024]
         logger.debug(f"Indexing the following chunks: {short_descriptor_log}")
 
         primary_doc_idx_insertion_records: list[DocumentInsertionRecord] | None = None
         primary_doc_idx_vector_db_write_failures: list[ConnectorFailure] | None = None
+
+        def chunk_iterable_creator() -> Iterable[DocMetadataAwareIndexChunk]:
+            return metadata_aware_chunks
+
         for document_index in document_indices:
             # A document will not be spread across different batches, so all the
             # documents with chunks in this set, are fully represented by the chunks
@@ -770,10 +787,10 @@ def index_doc_batch(
                 vector_db_write_failures,
             ) = write_chunks_to_vector_db_with_backoff(
                 document_index=document_index,
-                chunks=result.chunks,
+                make_chunks=chunk_iterable_creator,
                 index_batch_params=IndexBatchParams(
-                    doc_id_to_previous_chunk_cnt=result.doc_id_to_previous_chunk_cnt,
-                    doc_id_to_new_chunk_cnt=result.doc_id_to_new_chunk_cnt,
+                    doc_id_to_previous_chunk_cnt=enricher.doc_id_to_previous_chunk_cnt,
+                    doc_id_to_new_chunk_cnt=enricher.doc_id_to_new_chunk_cnt,
                     tenant_id=tenant_id,
                     large_chunks_enabled=chunker.enable_large_chunks,
                 ),
@@ -802,7 +819,7 @@ def index_doc_batch(
                     f"Updatable IDs: {updatable_ids}, "
                     f"Returned IDs: {all_returned_doc_ids}. "
                     "This should never happen."
-                    f"This occured for document index {document_index.__class__.__name__}"
+                    f"This occurred for document index {document_index.__class__.__name__}"
                 )
             # We treat the first document index we got as the primary one used
             # for reporting the state of indexing.
@@ -815,7 +832,7 @@ def index_doc_batch(
             context=context,
             updatable_chunk_data=updatable_chunk_data,
             filtered_documents=filtered_documents,
-            result=result,
+            enrichment=enricher,
         )
 
     assert primary_doc_idx_insertion_records is not None

backend/onyx/indexing/models.py

@@ -235,12 +235,16 @@ class UpdatableChunkData(BaseModel):
     boost_score: float
 
 
-class BuildMetadataAwareChunksResult(BaseModel):
-    chunks: list[DocMetadataAwareIndexChunk]
+class ChunkEnrichmentContext(Protocol):
+    """Returned by prepare_enrichment. Holds pre-computed metadata lookups
+    and provides per-chunk enrichment."""
+
     doc_id_to_previous_chunk_cnt: dict[str, int]
     doc_id_to_new_chunk_cnt: dict[str, int]
-    user_file_id_to_raw_text: dict[str, str]
-    user_file_id_to_token_count: dict[str, int | None]
+
+    def enrich_chunk(
+        self, chunk: IndexChunk, score: float
+    ) -> DocMetadataAwareIndexChunk: ...
 
 
 class IndexingBatchAdapter(Protocol):
@@ -254,18 +258,24 @@ class IndexingBatchAdapter(Protocol):
     ) -> Generator[TransactionalContext, None, None]:
         """Provide a transaction/row-lock context for critical updates."""
 
-    def build_metadata_aware_chunks(
+    def prepare_enrichment(
         self,
-        chunks_with_embeddings: list[IndexChunk],
-        chunk_content_scores: list[float],
-        tenant_id: str,
         context: "DocumentBatchPrepareContext",
-    ) -> BuildMetadataAwareChunksResult: ...
+        tenant_id: str,
+        chunks: list[DocAwareChunk],
+    ) -> ChunkEnrichmentContext:
+        """Prepare per-chunk enrichment data (access, document sets, boost, etc.).
+
+        Precondition: ``chunks`` have already been through the embedding step
+        (i.e. they are ``IndexChunk`` instances with populated embeddings,
+        passed here as the base ``DocAwareChunk`` type).
+        """
+        ...
 
     def post_index(
         self,
         context: "DocumentBatchPrepareContext",
         updatable_chunk_data: list[UpdatableChunkData],
         filtered_documents: list[Document],
-        result: BuildMetadataAwareChunksResult,
+        enrichment: ChunkEnrichmentContext,
     ) -> None: ...

backend/onyx/indexing/vector_db_insertion.py

@@ -1,6 +1,9 @@
 import time
-from collections import defaultdict
+from collections.abc import Callable
+from collections.abc import Iterable
 from http import HTTPStatus
+from itertools import chain
+from itertools import groupby
 
 import httpx
 
@@ -28,22 +31,22 @@ def _log_insufficient_storage_error(e: Exception) -> None:
 
 def write_chunks_to_vector_db_with_backoff(
     document_index: DocumentIndex,
-    chunks: list[DocMetadataAwareIndexChunk],
+    make_chunks: Callable[[], Iterable[DocMetadataAwareIndexChunk]],
     index_batch_params: IndexBatchParams,
 ) -> tuple[list[DocumentInsertionRecord], list[ConnectorFailure]]:
     """Tries to insert all chunks in one large batch. If that batch fails for any reason,
     goes document by document to isolate the failure(s).
 
     IMPORTANT: must pass in whole documents at a time not individual chunks, since the
-    vector DB interface assumes that all chunks for a single document are present.
+    vector DB interface assumes that all chunks for a single document are present. The
+    chunks must also be in contiguous batches
     """
-
     # first try to write the chunks to the vector db
     try:
         return (
             list(
                 document_index.index(
-                    chunks=chunks,
+                    chunks=make_chunks(),
                     index_batch_params=index_batch_params,
                 )
             ),
@@ -60,14 +63,16 @@ def write_chunks_to_vector_db_with_backoff(
         # wait a couple seconds just to give the vector db a chance to recover
         time.sleep(2)
 
-    # try writing each doc one by one
-    chunks_for_docs: dict[str, list[DocMetadataAwareIndexChunk]] = defaultdict(list)
-    for chunk in chunks:
-        chunks_for_docs[chunk.source_document.id].append(chunk)
-
     insertion_records: list[DocumentInsertionRecord] = []
     failures: list[ConnectorFailure] = []
-    for doc_id, chunks_for_doc in chunks_for_docs.items():
+
+    def key(chunk: DocMetadataAwareIndexChunk) -> str:
+        return chunk.source_document.id
+
+    for doc_id, chunks_for_doc in groupby(make_chunks(), key=key):
+        first_chunk = next(chunks_for_doc)
+        chunks_for_doc = chain([first_chunk], chunks_for_doc)
+
         try:
             insertion_records.extend(
                 document_index.index(
@@ -87,9 +92,7 @@ def write_chunks_to_vector_db_with_backoff(
                 ConnectorFailure(
                     failed_document=DocumentFailure(
                         document_id=doc_id,
-                        document_link=(
-                            chunks_for_doc[0].get_link() if chunks_for_doc else None
-                        ),
+                        document_link=first_chunk.get_link(),
                     ),
                     failure_message=str(e),
                     exception=e,

backend/tests/external_dependency_unit/celery/test_user_file_indexing_adapter.py

@@ -153,15 +153,13 @@ class TestAdapterWritesBothMetadataFields:
         doc = chunk.source_document
         context = DocumentBatchPrepareContext(updatable_docs=[doc], id_to_boost_map={})
 
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=[chunk],
-            chunk_content_scores=[1.0],
-            tenant_id=TEST_TENANT_ID,
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id=TEST_TENANT_ID,
+            chunks=[chunk],
         )
+        aware_chunk = enricher.enrich_chunk(chunk, 1.0)
 
-        assert len(result.chunks) == 1
-        aware_chunk = result.chunks[0]
         assert persona.id in aware_chunk.personas
         assert aware_chunk.user_project == []
 
@@ -190,15 +188,13 @@ class TestAdapterWritesBothMetadataFields:
             updatable_docs=[chunk.source_document], id_to_boost_map={}
         )
 
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=[chunk],
-            chunk_content_scores=[1.0],
-            tenant_id=TEST_TENANT_ID,
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id=TEST_TENANT_ID,
+            chunks=[chunk],
         )
+        aware_chunk = enricher.enrich_chunk(chunk, 1.0)
 
-        assert len(result.chunks) == 1
-        aware_chunk = result.chunks[0]
         assert project.id in aware_chunk.user_project
         assert aware_chunk.personas == []
 
@@ -229,14 +225,13 @@ class TestAdapterWritesBothMetadataFields:
             updatable_docs=[chunk.source_document], id_to_boost_map={}
         )
 
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=[chunk],
-            chunk_content_scores=[1.0],
-            tenant_id=TEST_TENANT_ID,
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id=TEST_TENANT_ID,
+            chunks=[chunk],
         )
+        aware_chunk = enricher.enrich_chunk(chunk, 1.0)
 
-        aware_chunk = result.chunks[0]
         assert persona.id in aware_chunk.personas
         assert project.id in aware_chunk.user_project
 
@@ -261,14 +256,13 @@ class TestAdapterWritesBothMetadataFields:
             updatable_docs=[chunk.source_document], id_to_boost_map={}
         )
 
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=[chunk],
-            chunk_content_scores=[1.0],
-            tenant_id=TEST_TENANT_ID,
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id=TEST_TENANT_ID,
+            chunks=[chunk],
         )
+        aware_chunk = enricher.enrich_chunk(chunk, 1.0)
 
-        aware_chunk = result.chunks[0]
         assert aware_chunk.personas == []
         assert aware_chunk.user_project == []
 
@@ -300,12 +294,11 @@ class TestAdapterWritesBothMetadataFields:
             updatable_docs=[chunk.source_document], id_to_boost_map={}
         )
 
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=[chunk],
-            chunk_content_scores=[1.0],
-            tenant_id=TEST_TENANT_ID,
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id=TEST_TENANT_ID,
+            chunks=[chunk],
         )
+        aware_chunk = enricher.enrich_chunk(chunk, 1.0)
 
-        aware_chunk = result.chunks[0]
         assert set(aware_chunk.personas) == {persona_a.id, persona_b.id}

backend/tests/unit/onyx/indexing/test_personas_in_chunks.py

@@ -116,7 +116,7 @@ def _run_adapter_build(
     project_ids_map: dict[str, list[int]],
     persona_ids_map: dict[str, list[int]],
 ) -> list[DocMetadataAwareIndexChunk]:
-    """Helper that runs UserFileIndexingAdapter.build_metadata_aware_chunks
+    """Helper that runs UserFileIndexingAdapter.prepare_enrichment + enrich_chunk
     with all external dependencies mocked."""
     from onyx.indexing.adapters.user_file_indexing_adapter import (
         UserFileIndexingAdapter,
@@ -155,14 +155,12 @@ def _run_adapter_build(
             side_effect=Exception("no LLM in tests"),
         ),
     ):
-        result = adapter.build_metadata_aware_chunks(
-            chunks_with_embeddings=[chunk],
-            chunk_content_scores=[1.0],
-            tenant_id="test_tenant",
+        enricher = adapter.prepare_enrichment(
             context=context,
+            tenant_id="test_tenant",
+            chunks=[chunk],
         )
-
-    return result.chunks
+        return [enricher.enrich_chunk(chunk, 1.0)]
 
 
 def test_build_metadata_aware_chunks_includes_persona_ids() -> None: