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Fix: use a root document's effective content for the LLM index and pr… (#14423)
* Fix: use a root document's effective content for the LLM index and prompts The search index and the document views use the newest version's content as a root document's content, but everything the LLM side reads used the root's own content: the text embedded in the LLM index, the content in the classification prompt, the context blocks from similar documents, and the text that is searched for similar documents. After a document was replaced by a new version the LLM kept answering from the old text. Read get_effective_content() in those four places. The index update annotates the content in the query like the search index does, and the similar-document lookup annotates it for the documents it fetches, so no query is made per document. Entries already in the LLM index keep the old text until the document next changes or the index is rebuilt. * Chore: test the LLM query text and bulk annotation use effective content * Removes the query count testing. It's flakey from local to CI and workers, doesn't really add much imo
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@@ -6,6 +6,7 @@ from django.contrib.auth.models import User
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from documents.models import Document
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from documents.permissions import permitted_document_ids
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from documents.permissions import user_is_unrestricted
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from documents.versioning import annotate_effective_content
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from paperless.config import AIConfig
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from paperless_ai.base_model import ClassificationSuggestions
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from paperless_ai.base_model import TaxonomyChoiceDict
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@@ -111,7 +112,7 @@ def build_prompt_without_rag(
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) -> str:
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filename = document.filename or ""
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content = truncate_content(
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document.content[:4000] or "",
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(document.get_effective_content() or "")[:4000],
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chunk_size=config.llm_embedding_chunk_size,
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context_size=config.llm_context_size,
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)
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@@ -225,7 +226,9 @@ def get_taxonomy_context(
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# similar_documents is already ordered by descending weight; don't lose it.
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similar_document_ids = [s["document_id"] for s in similar_documents]
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similar_documents_by_id = Document.objects.in_bulk(similar_document_ids)
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similar_documents_by_id = annotate_effective_content(
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Document.objects.all(),
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).in_bulk(similar_document_ids)
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similar_docs = [
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similar_documents_by_id[document_id]
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for document_id in similar_document_ids
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@@ -233,7 +236,7 @@ def get_taxonomy_context(
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][:max_docs]
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context_blocks = []
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for similar in similar_docs:
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text = similar.content[:1000] or ""
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text = (similar.get_effective_content() or "")[:1000]
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title = similar.title or similar.filename or "Untitled"
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context_blocks.append(f"TITLE: {title}\n{text}")
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except Exception:
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@@ -135,6 +135,6 @@ def build_llm_index_text(doc: Document) -> str:
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lines.append(f"Custom Field - {instance.field.name}: {instance}")
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lines.append("\nContent:\n")
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lines.append(doc.content or "")
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lines.append(doc.get_effective_content() or "")
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return _normalize_llm_index_text("\n".join(lines))
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@@ -17,6 +17,7 @@ from documents.models import PaperlessTask
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from documents.utils import IterWrapper
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from documents.utils import QuerySetStream
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from documents.utils import identity
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from documents.versioning import annotate_effective_content
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from documents.versioning import root_document_ids
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from paperless.config import AIConfig
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from paperless_ai.db import db_connection_released
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@@ -444,10 +445,10 @@ def update_llm_index(
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"Skipping LLM index update: migration check deferred; "
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"will retry next run."
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)
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documents = (
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documents = annotate_effective_content(
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Document.objects.filter(root_document__isnull=True)
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.select_related("correspondent", "document_type", "storage_path")
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.prefetch_related("tags", "notes", "custom_fields__field")
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.prefetch_related("tags", "notes", "custom_fields__field"),
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)
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no_documents = not documents.exists()
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@@ -694,7 +695,7 @@ def retrieve_similar_nodes(
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)
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query_text = truncate_embedding_query(
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(document.title or "") + "\n" + (document.content or ""),
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(document.title or "") + "\n" + (document.get_effective_content() or ""),
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chunk_size=config.llm_embedding_chunk_size,
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)
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# Hold the shared read lock for the whole retrieval so the connection is
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@@ -55,6 +55,7 @@ def mock_document():
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doc.storage_path = None
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doc.archive_serial_number = "12345"
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doc.content = "This is the document content."
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doc.get_effective_content.return_value = "This is the document content."
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cf1 = MagicMock(__str__=lambda x: "Value1")
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cf1.field = MagicMock()
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@@ -434,6 +435,55 @@ def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents(
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)
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@pytest.mark.django_db
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class TestClassifierEffectiveContent:
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"""A root document's text for the LLM is its newest version's content."""
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@staticmethod
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def _root_with_version() -> Document:
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root = DocumentFactory(title="Statement", content="stale text")
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DocumentFactory(root_document=root, version_index=1, content="latest text")
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return root
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def test_prompt_uses_the_newest_versions_content(self) -> None:
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"""
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GIVEN:
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- A root document with a version
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WHEN:
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- The classification prompt is built for the root
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THEN:
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- It contains the newest version's content
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"""
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prompt = build_prompt_without_rag(self._root_with_version(), AIConfig())
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assert "latest text" in prompt
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assert "stale text" not in prompt
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@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
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def test_similar_document_context_uses_the_newest_versions_content(self) -> None:
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"""
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GIVEN:
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- A similar root document with a version
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WHEN:
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- The similar-document context is built
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THEN:
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- It contains the newest version's content
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"""
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similar = self._root_with_version()
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document = DocumentFactory(content="Some content")
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fake_nodes = [
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SimpleNamespace(metadata={"document_id": str(similar.pk)}, score=0.9),
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]
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with patch(
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"paperless_ai.ai_classifier.retrieve_similar_nodes",
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return_value=fake_nodes,
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):
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_candidates, context = get_taxonomy_context(document, user=None)
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assert context == "TITLE: Statement\nlatest text"
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@pytest.mark.django_db
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@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
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def test_get_taxonomy_context_no_similar_docs():
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@@ -438,6 +438,31 @@ class TestLlmIndexVersions:
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assert set(indexed) == {str(root.pk)}
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def test_rebuild_indexes_the_newest_versions_content(
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self,
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temp_llm_index_dir: Path,
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mock_embed_model: FakeEmbedding,
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mocker: pytest_mock.MockerFixture,
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) -> None:
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"""
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GIVEN:
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- A root document with a version
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WHEN:
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- The LLM index is rebuilt
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THEN:
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- The root's text for the index is the version's content, answered
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from the query rather than a query per document
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"""
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root = DocumentFactory(content="stale text")
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DocumentFactory(root_document=root, version_index=1, content="latest text")
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spy = mocker.spy(indexing, "build_document_node")
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indexing.update_llm_index(rebuild=True)
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indexed = spy.call_args.args[0]
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assert indexed.pk == root.pk
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assert indexed.effective_content == "latest text"
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def test_incremental_update_by_version_id_refreshes_the_root(
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self,
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temp_llm_index_dir: Path,
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@@ -601,6 +626,39 @@ def test_retrieve_similar_nodes_truncates_query_to_embedding_chunk_size(
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assert "word199" not in query_text
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@pytest.mark.django_db
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@override_settings(
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LLM_EMBEDDING_BACKEND="huggingface",
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LLM_BACKEND="ollama",
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)
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def test_retrieve_similar_nodes_queries_with_newest_versions_content(
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temp_llm_index_dir: Path,
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) -> None:
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"""
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GIVEN:
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- A root document whose newest version carries different content
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WHEN:
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- Documents similar to the root are retrieved
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THEN:
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- The query text holds the newest version's content, not the root's own
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"""
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root = DocumentFactory(title="Statement", content="stale root text")
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DocumentFactory(root_document=root, version_index=1, content="latest version text")
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with (
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patch("paperless_ai.indexing.load_or_build_index"),
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patch("paperless_ai.indexing.llm_index_exists", return_value=True),
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patch("llama_index.core.retrievers.VectorIndexRetriever") as mock_retriever_cls,
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):
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mock_retriever_cls.return_value.retrieve.return_value = []
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indexing.retrieve_similar_nodes(root, top_k=3)
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query_text = mock_retriever_cls.return_value.retrieve.call_args.args[0]
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assert "latest version text" in query_text
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assert "stale root text" not in query_text
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class TestUpdateLlmIndexEmptyDocumentSet:
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"""update_llm_index must clear the vector store table when all documents are deleted.
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@@ -12,6 +12,7 @@ from paperless_ai.embedding import _normalize_llm_index_text
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from paperless_ai.embedding import build_llm_index_text
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from paperless_ai.embedding import get_configured_model_name
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from paperless_ai.embedding import get_embedding_model
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from paperless_testing.factories import DocumentFactory
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@pytest.fixture
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@@ -46,6 +47,7 @@ def mock_document():
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doc.correspondent.name = "Test Correspondent"
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doc.archive_serial_number = "12345"
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doc.content = "This is the document content."
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doc.get_effective_content.return_value = "This is the document content."
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cf1 = MagicMock(__str__=lambda x: "Value1")
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cf1.field = MagicMock()
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@@ -280,7 +282,7 @@ def test_build_llm_index_text(mock_document):
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def test_build_llm_index_text_normalizes_ocr_punctuation_runs(mock_document):
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mock_document.content = (
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mock_document.get_effective_content.return_value = (
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"Introduction ................................................ 7\n"
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"Hardware Limitation ________________________________________ 9\n"
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"Keep short punctuation like INV-100 and ellipses..."
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@@ -294,6 +296,43 @@ def test_build_llm_index_text_normalizes_ocr_punctuation_runs(mock_document):
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assert "ellipses..." in result
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@pytest.mark.django_db
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class TestBuildLlmIndexTextVersions:
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"""A root document is indexed with its effective content, like in the search index."""
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def test_root_uses_the_newest_versions_content(self) -> None:
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"""
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GIVEN:
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- A root document with two versions
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WHEN:
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- The LLM index text is built for the root
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THEN:
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- It contains the newest version's content and not the others'
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"""
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root = DocumentFactory(content="stale text")
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DocumentFactory(root_document=root, version_index=1, content="older text")
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DocumentFactory(root_document=root, version_index=2, content="latest text")
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text = build_llm_index_text(root)
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assert "latest text" in text
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assert "stale text" not in text
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assert "older text" not in text
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def test_root_without_versions_uses_its_own_content(self) -> None:
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"""
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GIVEN:
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- A root document without versions
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WHEN:
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- The LLM index text is built for it
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THEN:
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- It contains the document's own content
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"""
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root = DocumentFactory(content="own text")
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assert "own text" in build_llm_index_text(root)
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def test_normalize_llm_index_text_collapses_ocr_leaders_without_joining_lines():
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assert _normalize_llm_index_text("A........B\nC____D----E") == "A B\nC D E"
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