Add integration tests for document set syncing (#1904)

backend/alembic/versions/23957775e5f5_remove_feedback_foreignkey_constraint.py

@@ -79,7 +79,7 @@ def downgrade() -> None:
     )
     op.create_foreign_key(
         "document_retrieval_feedback__chat_message_fk",
-        "document_retrieval",
+        "document_retrieval_feedback",
         "chat_message",
         ["chat_message_id"],
         ["id"],

backend/alembic/versions/27c6ecc08586_permission_framework.py

@@ -160,12 +160,28 @@ def downgrade() -> None:
             nullable=False,
         ),
     )
-    op.drop_constraint(
-        "fk_index_attempt_credential_id", "index_attempt", type_="foreignkey"
-    )
-    op.drop_constraint(
-        "fk_index_attempt_connector_id", "index_attempt", type_="foreignkey"
-    )
+
+    # Check if the constraint exists before dropping
+    conn = op.get_bind()
+    inspector = sa.inspect(conn)
+    constraints = inspector.get_foreign_keys("index_attempt")
+
+    if any(
+        constraint["name"] == "fk_index_attempt_credential_id"
+        for constraint in constraints
+    ):
+        op.drop_constraint(
+            "fk_index_attempt_credential_id", "index_attempt", type_="foreignkey"
+        )
+
+    if any(
+        constraint["name"] == "fk_index_attempt_connector_id"
+        for constraint in constraints
+    ):
+        op.drop_constraint(
+            "fk_index_attempt_connector_id", "index_attempt", type_="foreignkey"
+        )
+
     op.drop_column("index_attempt", "credential_id")
     op.drop_column("index_attempt", "connector_id")
     op.drop_table("connector_credential_pair")

backend/alembic/versions/76b60d407dfb_cc_pair_name_not_unique.py

@@ -28,5 +28,9 @@ def upgrade() -> None:
 
 
 def downgrade() -> None:
-    # This wasn't really required by the code either, no good reason to make it unique again
-    pass
+    op.create_unique_constraint(
+        "connector_credential_pair__name__key", "connector_credential_pair", ["name"]
+    )
+    op.alter_column(
+        "connector_credential_pair", "name", existing_type=sa.String(), nullable=True
+    )

backend/alembic/versions/d5645c915d0e_remove_deletion_attempt_table.py

@@ -19,6 +19,9 @@ depends_on: None = None
 def upgrade() -> None:
     op.drop_table("deletion_attempt")
 
+    # Remove the DeletionStatus enum
+    op.execute("DROP TYPE IF EXISTS deletionstatus;")
+
 
 def downgrade() -> None:
     op.create_table(

backend/alembic/versions/dbaa756c2ccf_embedding_models.py

@@ -136,4 +136,4 @@ def downgrade() -> None:
     )
     op.drop_column("index_attempt", "embedding_model_id")
     op.drop_table("embedding_model")
-    op.execute("DROP TYPE indexmodelstatus;")
+    op.execute("DROP TYPE IF EXISTS indexmodelstatus;")

backend/danswer/db/document.py

@@ -311,7 +311,7 @@ def acquire_document_locks(db_session: Session, document_ids: list[str]) -> bool
 
 
 _NUM_LOCK_ATTEMPTS = 10
-_LOCK_RETRY_DELAY = 30
+_LOCK_RETRY_DELAY = 10
 
 
 @contextlib.contextmanager

backend/danswer/main.py

@@ -47,10 +47,12 @@ from danswer.db.engine import init_sqlalchemy_engine
 from danswer.db.engine import warm_up_connections
 from danswer.db.index_attempt import cancel_indexing_attempts_past_model
 from danswer.db.index_attempt import expire_index_attempts
+from danswer.db.models import EmbeddingModel
 from danswer.db.persona import delete_old_default_personas
 from danswer.db.standard_answer import create_initial_default_standard_answer_category
 from danswer.db.swap_index import check_index_swap
 from danswer.document_index.factory import get_default_document_index
+from danswer.document_index.interfaces import DocumentIndex
 from danswer.llm.llm_initialization import load_llm_providers
 from danswer.natural_language_processing.search_nlp_models import warm_up_encoders
 from danswer.search.retrieval.search_runner import download_nltk_data
@@ -158,6 +160,49 @@ def include_router_with_global_prefix_prepended(
     application.include_router(router, **final_kwargs)
 
 
+def setup_postgres(db_session: Session) -> None:
+    logger.info("Verifying default connector/credential exist.")
+    create_initial_public_credential(db_session)
+    create_initial_default_connector(db_session)
+    associate_default_cc_pair(db_session)
+
+    logger.info("Verifying default standard answer category exists.")
+    create_initial_default_standard_answer_category(db_session)
+
+    logger.info("Loading LLM providers from env variables")
+    load_llm_providers(db_session)
+
+    logger.info("Loading default Prompts and Personas")
+    delete_old_default_personas(db_session)
+    load_chat_yamls()
+
+    logger.info("Loading built-in tools")
+    load_builtin_tools(db_session)
+    refresh_built_in_tools_cache(db_session)
+    auto_add_search_tool_to_personas(db_session)
+
+
+def setup_vespa(
+    document_index: DocumentIndex,
+    db_embedding_model: EmbeddingModel,
+    secondary_db_embedding_model: EmbeddingModel | None,
+) -> None:
+    # Vespa startup is a bit slow, so give it a few seconds
+    wait_time = 5
+    for _ in range(5):
+        try:
+            document_index.ensure_indices_exist(
+                index_embedding_dim=db_embedding_model.model_dim,
+                secondary_index_embedding_dim=secondary_db_embedding_model.model_dim
+                if secondary_db_embedding_model
+                else None,
+            )
+            break
+        except Exception:
+            logger.info(f"Waiting on Vespa, retrying in {wait_time} seconds...")
+            time.sleep(wait_time)
+
+
 @asynccontextmanager
 async def lifespan(app: FastAPI) -> AsyncGenerator:
     init_sqlalchemy_engine(POSTGRES_WEB_APP_NAME)
@@ -213,26 +258,10 @@ async def lifespan(app: FastAPI) -> AsyncGenerator:
         logger.info("Verifying query preprocessing (NLTK) data is downloaded")
         download_nltk_data()
 
-        logger.info("Verifying default connector/credential exist.")
-        create_initial_public_credential(db_session)
-        create_initial_default_connector(db_session)
-        associate_default_cc_pair(db_session)
-
-        logger.info("Verifying default standard answer category exists.")
-        create_initial_default_standard_answer_category(db_session)
-
-        logger.info("Loading LLM providers from env variables")
-        load_llm_providers(db_session)
-
-        logger.info("Loading default Prompts and Personas")
-        delete_old_default_personas(db_session)
-        load_chat_yamls()
-
-        logger.info("Loading built-in tools")
-        load_builtin_tools(db_session)
-        refresh_built_in_tools_cache(db_session)
-        auto_add_search_tool_to_personas(db_session)
+        # setup Postgres with default credential, llm providers, etc.
+        setup_postgres(db_session)
 
+        # ensure Vespa is setup correctly
         logger.info("Verifying Document Index(s) is/are available.")
         document_index = get_default_document_index(
             primary_index_name=db_embedding_model.index_name,
@@ -240,20 +269,7 @@ async def lifespan(app: FastAPI) -> AsyncGenerator:
             if secondary_db_embedding_model
             else None,
         )
-        # Vespa startup is a bit slow, so give it a few seconds
-        wait_time = 5
-        for attempt in range(5):
-            try:
-                document_index.ensure_indices_exist(
-                    index_embedding_dim=db_embedding_model.model_dim,
-                    secondary_index_embedding_dim=secondary_db_embedding_model.model_dim
-                    if secondary_db_embedding_model
-                    else None,
-                )
-                break
-            except Exception:
-                logger.info(f"Waiting on Vespa, retrying in {wait_time} seconds...")
-                time.sleep(wait_time)
+        setup_vespa(document_index, db_embedding_model, secondary_db_embedding_model)
 
         logger.info(f"Model Server: http://{MODEL_SERVER_HOST}:{MODEL_SERVER_PORT}")
         if db_embedding_model.cloud_provider_id is None:

backend/danswer/server/danswer_api/ingestion.py

@@ -12,6 +12,7 @@ from danswer.db.document import get_ingestion_documents
 from danswer.db.embedding_model import get_current_db_embedding_model
 from danswer.db.embedding_model import get_secondary_db_embedding_model
 from danswer.db.engine import get_session
+from danswer.db.models import User
 from danswer.document_index.document_index_utils import get_both_index_names
 from danswer.document_index.factory import get_default_document_index
 from danswer.indexing.embedder import DefaultIndexingEmbedder
@@ -31,7 +32,7 @@ router = APIRouter(prefix="/danswer-api")
 @router.get("/connector-docs/{cc_pair_id}")
 def get_docs_by_connector_credential_pair(
     cc_pair_id: int,
-    _: str = Depends(api_key_dep),
+    _: User | None = Depends(api_key_dep),
     db_session: Session = Depends(get_session),
 ) -> list[DocMinimalInfo]:
     db_docs = get_documents_by_cc_pair(cc_pair_id=cc_pair_id, db_session=db_session)
@@ -47,7 +48,7 @@ def get_docs_by_connector_credential_pair(
 
 @router.get("/ingestion")
 def get_ingestion_docs(
-    _: str = Depends(api_key_dep),
+    _: User | None = Depends(api_key_dep),
     db_session: Session = Depends(get_session),
 ) -> list[DocMinimalInfo]:
     db_docs = get_ingestion_documents(db_session)
@@ -64,7 +65,7 @@ def get_ingestion_docs(
 @router.post("/ingestion")
 def upsert_ingestion_doc(
     doc_info: IngestionDocument,
-    _: str = Depends(api_key_dep),
+    _: User | None = Depends(api_key_dep),
     db_session: Session = Depends(get_session),
 ) -> IngestionResult:
     doc_info.document.from_ingestion_api = True

backend/danswer/server/gpts/api.py

@@ -7,6 +7,7 @@ from pydantic import BaseModel
 from sqlalchemy.orm import Session
 
 from danswer.db.engine import get_session
+from danswer.db.models import User
 from danswer.llm.factory import get_default_llms
 from danswer.search.models import SearchRequest
 from danswer.search.pipeline import SearchPipeline
@@ -64,7 +65,7 @@ class GptSearchResponse(BaseModel):
 @router.post("/gpt-document-search")
 def gpt_search(
     search_request: GptSearchRequest,
-    _: str | None = Depends(api_key_dep),
+    _: User | None = Depends(api_key_dep),
     db_session: Session = Depends(get_session),
 ) -> GptSearchResponse:
     llm, fast_llm = get_default_llms()

backend/ee/danswer/auth/users.py

@@ -44,7 +44,12 @@ async def optional_user_(
     return user
 
 
-def api_key_dep(request: Request, db_session: Session = Depends(get_session)) -> User:
+def api_key_dep(
+    request: Request, db_session: Session = Depends(get_session)
+) -> User | None:
+    if AUTH_TYPE == AuthType.DISABLED:
+        return None
+
     hashed_api_key = get_hashed_api_key_from_request(request)
     if not hashed_api_key:
         raise HTTPException(status_code=401, detail="Missing API key")

backend/tests/integration/common/constants.py

@@ -0,0 +1 @@
+API_SERVER_URL = "http://localhost:8080"

backend/tests/integration/common/reset.py

@@ -0,0 +1,164 @@
+import logging
+import time
+
+import psycopg2
+import requests
+
+from alembic import command
+from alembic.config import Config
+from danswer.configs.app_configs import POSTGRES_HOST
+from danswer.configs.app_configs import POSTGRES_PASSWORD
+from danswer.configs.app_configs import POSTGRES_PORT
+from danswer.configs.app_configs import POSTGRES_USER
+from danswer.db.embedding_model import get_current_db_embedding_model
+from danswer.db.engine import build_connection_string
+from danswer.db.engine import get_session_context_manager
+from danswer.db.engine import SYNC_DB_API
+from danswer.db.swap_index import check_index_swap
+from danswer.document_index.vespa.index import DOCUMENT_ID_ENDPOINT
+from danswer.document_index.vespa.index import VespaIndex
+from danswer.main import setup_postgres
+from danswer.main import setup_vespa
+
+
+def _run_migrations(
+    database_url: str, direction: str = "upgrade", revision: str = "head"
+) -> None:
+    # hide info logs emitted during migration
+    logging.getLogger("alembic").setLevel(logging.CRITICAL)
+
+    # Create an Alembic configuration object
+    alembic_cfg = Config("alembic.ini")
+    alembic_cfg.set_section_option("logger_alembic", "level", "WARN")
+
+    # Set the SQLAlchemy URL in the Alembic configuration
+    alembic_cfg.set_main_option("sqlalchemy.url", database_url)
+
+    # Run the migration
+    if direction == "upgrade":
+        command.upgrade(alembic_cfg, revision)
+    elif direction == "downgrade":
+        command.downgrade(alembic_cfg, revision)
+    else:
+        raise ValueError(
+            f"Invalid direction: {direction}. Must be 'upgrade' or 'downgrade'."
+        )
+
+    logging.getLogger("alembic").setLevel(logging.INFO)
+
+
+def reset_postgres(database: str = "postgres") -> None:
+    """Reset the Postgres database."""
+
+    # NOTE: need to delete all rows to allow migrations to be rolled back
+    # as there are a few downgrades that don't properly handle data in tables
+    conn = psycopg2.connect(
+        dbname=database,
+        user=POSTGRES_USER,
+        password=POSTGRES_PASSWORD,
+        host=POSTGRES_HOST,
+        port=POSTGRES_PORT,
+    )
+    cur = conn.cursor()
+
+    # Disable triggers to prevent foreign key constraints from being checked
+    cur.execute("SET session_replication_role = 'replica';")
+
+    # Fetch all table names in the current database
+    cur.execute(
+        """
+        SELECT tablename
+        FROM pg_tables
+        WHERE schemaname = 'public'
+    """
+    )
+
+    tables = cur.fetchall()
+
+    for table in tables:
+        table_name = table[0]
+
+        # Don't touch migration history
+        if table_name == "alembic_version":
+            continue
+
+        cur.execute(f'DELETE FROM "{table_name}"')
+
+    # Re-enable triggers
+    cur.execute("SET session_replication_role = 'origin';")
+
+    conn.commit()
+    cur.close()
+    conn.close()
+
+    # downgrade to base + upgrade back to head
+    conn_str = build_connection_string(
+        db=database,
+        user=POSTGRES_USER,
+        password=POSTGRES_PASSWORD,
+        host=POSTGRES_HOST,
+        port=POSTGRES_PORT,
+        db_api=SYNC_DB_API,
+    )
+    _run_migrations(
+        conn_str,
+        direction="downgrade",
+        revision="base",
+    )
+    _run_migrations(
+        conn_str,
+        direction="upgrade",
+        revision="head",
+    )
+
+    # do the same thing as we do on API server startup
+    with get_session_context_manager() as db_session:
+        setup_postgres(db_session)
+
+
+def reset_vespa() -> None:
+    """Wipe all data from the Vespa index."""
+    with get_session_context_manager() as db_session:
+        # swap to the correct default model
+        check_index_swap(db_session)
+
+        current_model = get_current_db_embedding_model(db_session)
+        index_name = current_model.index_name
+
+    setup_vespa(
+        document_index=VespaIndex(index_name=index_name, secondary_index_name=None),
+        db_embedding_model=current_model,
+        secondary_db_embedding_model=None,
+    )
+
+    for _ in range(5):
+        try:
+            continuation = None
+            should_continue = True
+            while should_continue:
+                params = {"selection": "true", "cluster": "danswer_index"}
+                if continuation:
+                    params = {**params, "continuation": continuation}
+                response = requests.delete(
+                    DOCUMENT_ID_ENDPOINT.format(index_name=index_name), params=params
+                )
+                response.raise_for_status()
+
+                response_json = response.json()
+
+                continuation = response_json.get("continuation")
+                should_continue = bool(continuation)
+
+            break
+        except Exception as e:
+            print(f"Error deleting documents: {e}")
+            time.sleep(5)
+
+
+def reset_all() -> None:
+    """Reset both Postgres and Vespa."""
+    print("Resetting Postgres...")
+    reset_postgres()
+    print("Resetting Vespa...")
+    reset_vespa()
+    print("Finished resetting all.")

backend/tests/integration/common/seed_documents.py

@@ -0,0 +1,83 @@
+import uuid
+from typing import cast
+
+import requests
+from pydantic import BaseModel
+
+from danswer.configs.constants import DocumentSource
+from tests.integration.common.constants import API_SERVER_URL
+
+
+class SeedDocumentResponse(BaseModel):
+    cc_pair_id: int
+    document_ids: list[str]
+
+
+class TestDocumentClient:
+    @staticmethod
+    def seed_documents(num_docs: int = 5) -> SeedDocumentResponse:
+        unique_id = uuid.uuid4()
+
+        # Create a connector
+        connector_name = f"test_connector_{unique_id}"
+        connector_data = {
+            "name": connector_name,
+            "source": DocumentSource.NOT_APPLICABLE,
+            "input_type": "load_state",
+            "connector_specific_config": {},
+            "refresh_freq": 60,
+            "disabled": True,
+        }
+        response = requests.post(
+            f"{API_SERVER_URL}/manage/admin/connector",
+            json=connector_data,
+        )
+        response.raise_for_status()
+        connector_id = response.json()["id"]
+
+        # Associate the credential with the connector
+        cc_pair_metadata = {"name": f"test_cc_pair_{unique_id}", "is_public": True}
+        response = requests.put(
+            f"{API_SERVER_URL}/manage/connector/{connector_id}/credential/0",
+            json=cc_pair_metadata,
+        )
+        response.raise_for_status()
+        cc_pair_id = cast(int, response.json()["data"])
+
+        # Create and ingest some documents
+        document_ids: list[str] = []
+        for _ in range(num_docs):
+            document_id = f"test-doc-{uuid.uuid4()}"
+            document_ids.append(document_id)
+
+            document = {
+                "document": {
+                    "id": document_id,
+                    "sections": [
+                        {
+                            "text": f"This is test document {document_id}",
+                            "link": f"{document_id}",
+                        }
+                    ],
+                    "source": DocumentSource.NOT_APPLICABLE,
+                    "metadata": {},
+                    "semantic_identifier": f"Test Document {document_id}",
+                    "from_ingestion_api": True,
+                },
+                "cc_pair_id": cc_pair_id,
+            }
+            response = requests.post(
+                f"{API_SERVER_URL}/danswer-api/ingestion",
+                json=document,
+            )
+            response.raise_for_status()
+
+        print("Seeding completed successfully.")
+        return SeedDocumentResponse(
+            cc_pair_id=cc_pair_id,
+            document_ids=document_ids,
+        )
+
+
+if __name__ == "__main__":
+    seed_documents_resp = TestDocumentClient.seed_documents()

backend/tests/integration/common/vespa.py

@@ -0,0 +1,27 @@
+import requests
+
+from danswer.document_index.vespa.index import DOCUMENT_ID_ENDPOINT
+
+
+class TestVespaClient:
+    def __init__(self, index_name: str):
+        self.index_name = index_name
+        self.vespa_document_url = DOCUMENT_ID_ENDPOINT.format(index_name=index_name)
+
+    def get_documents_by_id(
+        self, document_ids: list[str], wanted_doc_count: int = 1_000
+    ) -> dict:
+        selection = " or ".join(
+            f"{self.index_name}.document_id=='{document_id}'"
+            for document_id in document_ids
+        )
+        params = {
+            "selection": selection,
+            "wantedDocumentCount": wanted_doc_count,
+        }
+        response = requests.get(
+            self.vespa_document_url,
+            params=params,  # type: ignore
+        )
+        response.raise_for_status()
+        return response.json()

backend/tests/integration/conftest.py

@@ -0,0 +1,26 @@
+from collections.abc import Generator
+
+import pytest
+from sqlalchemy.orm import Session
+
+from danswer.db.embedding_model import get_current_db_embedding_model
+from danswer.db.engine import get_session_context_manager
+from tests.integration.common.reset import reset_all
+from tests.integration.common.vespa import TestVespaClient
+
+
+@pytest.fixture
+def db_session() -> Generator[Session, None, None]:
+    with get_session_context_manager() as session:
+        yield session
+
+
+@pytest.fixture
+def vespa_client(db_session: Session) -> TestVespaClient:
+    current_model = get_current_db_embedding_model(db_session)
+    return TestVespaClient(index_name=current_model.index_name)
+
+
+@pytest.fixture
+def reset() -> None:
+    reset_all()

backend/tests/integration/document_set/test_syncing.py

@@ -0,0 +1,79 @@
+import time
+
+from danswer.server.features.document_set.models import DocumentSetCreationRequest
+from tests.integration.common.seed_documents import TestDocumentClient
+from tests.integration.common.vespa import TestVespaClient
+from tests.integration.document_set.utils import create_document_set
+from tests.integration.document_set.utils import fetch_document_sets
+
+
+def test_multiple_document_sets_syncing_same_connnector(
+    reset: None, vespa_client: TestVespaClient
+) -> None:
+    # Seed documents
+    seed_result = TestDocumentClient.seed_documents(num_docs=5)
+    cc_pair_id = seed_result.cc_pair_id
+
+    # Create first document set
+    doc_set_1_id = create_document_set(
+        DocumentSetCreationRequest(
+            name="Test Document Set 1",
+            description="First test document set",
+            cc_pair_ids=[cc_pair_id],
+            is_public=True,
+            users=[],
+            groups=[],
+        )
+    )
+
+    doc_set_2_id = create_document_set(
+        DocumentSetCreationRequest(
+            name="Test Document Set 2",
+            description="Second test document set",
+            cc_pair_ids=[cc_pair_id],
+            is_public=True,
+            users=[],
+            groups=[],
+        )
+    )
+
+    # wait for syncing to be complete
+    max_delay = 45
+    start = time.time()
+    while True:
+        doc_sets = fetch_document_sets()
+        doc_set_1 = next(
+            (doc_set for doc_set in doc_sets if doc_set.id == doc_set_1_id), None
+        )
+        doc_set_2 = next(
+            (doc_set for doc_set in doc_sets if doc_set.id == doc_set_2_id), None
+        )
+
+        if not doc_set_1 or not doc_set_2:
+            raise RuntimeError("Document set not found")
+
+        if doc_set_1.is_up_to_date and doc_set_2.is_up_to_date:
+            assert [ccp.id for ccp in doc_set_1.cc_pair_descriptors] == [
+                ccp.id for ccp in doc_set_2.cc_pair_descriptors
+            ]
+            break
+
+        if time.time() - start > max_delay:
+            raise TimeoutError("Document sets were not synced within the max delay")
+
+        time.sleep(2)
+
+    # get names so we can compare to what is in vespa
+    doc_sets = fetch_document_sets()
+    doc_set_names = {doc_set.name for doc_set in doc_sets}
+
+    # make sure documents are as expected
+    result = vespa_client.get_documents_by_id(seed_result.document_ids)
+    documents = result["documents"]
+    assert len(documents) == len(seed_result.document_ids)
+    assert all(
+        doc["fields"]["document_id"] in seed_result.document_ids for doc in documents
+    )
+    assert all(
+        set(doc["fields"]["document_sets"].keys()) == doc_set_names for doc in documents
+    )

backend/tests/integration/document_set/utils.py

@@ -0,0 +1,26 @@
+from typing import cast
+
+import requests
+
+from danswer.server.features.document_set.models import DocumentSet
+from danswer.server.features.document_set.models import DocumentSetCreationRequest
+from tests.integration.common.constants import API_SERVER_URL
+
+
+def create_document_set(doc_set_creation_request: DocumentSetCreationRequest) -> int:
+    response = requests.post(
+        f"{API_SERVER_URL}/manage/admin/document-set",
+        json=doc_set_creation_request.dict(),
+    )
+    response.raise_for_status()
+    return cast(int, response.json())
+
+
+def fetch_document_sets() -> list[DocumentSet]:
+    response = requests.get(f"{API_SERVER_URL}/manage/admin/document-set")
+    response.raise_for_status()
+
+    document_sets = [
+        DocumentSet.parse_obj(doc_set_data) for doc_set_data in response.json()
+    ]
+    return document_sets