tests fixed

* ux consistent

* nit

* Update web/src/app/admin/configuration/llm/interfaces.ts

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

---------

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

.github/workflows/pr-python-connector-tests.yml

@@ -1,6 +1,7 @@
 name: Connector Tests
 
 on:
+  merge_group:
   pull_request:
     branches: [main]
   schedule:
@@ -51,7 +52,7 @@ env:
 jobs:
   connectors-check:
     # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
+    runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
 
     env:
       PYTHONPATH: ./backend
@@ -76,7 +77,7 @@ jobs:
           pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
           playwright install chromium
           playwright install-deps chromium
-          
+
       - name: Run Tests
         shell: script -q -e -c "bash --noprofile --norc -eo pipefail {0}"
         run: py.test -o junit_family=xunit2 -xv --ff backend/tests/daily/connectors

backend/alembic/versions/3934b1bc7b62_update_github_connector_repo_name_to_.py

@@ -0,0 +1,125 @@
+"""Update GitHub connector repo_name to repositories
+
+Revision ID: 3934b1bc7b62
+Revises: b7c2b63c4a03
+Create Date: 2025-03-05 10:50:30.516962
+
+"""
+from alembic import op
+import sqlalchemy as sa
+import json
+import logging
+
+# revision identifiers, used by Alembic.
+revision = "3934b1bc7b62"
+down_revision = "b7c2b63c4a03"
+branch_labels = None
+depends_on = None
+
+logger = logging.getLogger("alembic.runtime.migration")
+
+
+def upgrade() -> None:
+    # Get all GitHub connectors
+    conn = op.get_bind()
+
+    # First get all GitHub connectors
+    github_connectors = conn.execute(
+        sa.text(
+            """
+            SELECT id, connector_specific_config
+            FROM connector
+            WHERE source = 'GITHUB'
+            """
+        )
+    ).fetchall()
+
+    # Update each connector's config
+    updated_count = 0
+    for connector_id, config in github_connectors:
+        try:
+            if not config:
+                logger.warning(f"Connector {connector_id} has no config, skipping")
+                continue
+
+            # Parse the config if it's a string
+            if isinstance(config, str):
+                config = json.loads(config)
+
+            if "repo_name" not in config:
+                continue
+
+            # Create new config with repositories instead of repo_name
+            new_config = dict(config)
+            repo_name_value = new_config.pop("repo_name")
+            new_config["repositories"] = repo_name_value
+
+            # Update the connector with the new config
+            conn.execute(
+                sa.text(
+                    """
+                    UPDATE connector
+                    SET connector_specific_config = :new_config
+                    WHERE id = :connector_id
+                    """
+                ),
+                {"connector_id": connector_id, "new_config": json.dumps(new_config)},
+            )
+            updated_count += 1
+        except Exception as e:
+            logger.error(f"Error updating connector {connector_id}: {str(e)}")
+
+
+def downgrade() -> None:
+    # Get all GitHub connectors
+    conn = op.get_bind()
+
+    logger.debug(
+        "Starting rollback of GitHub connectors from repositories to repo_name"
+    )
+
+    github_connectors = conn.execute(
+        sa.text(
+            """
+            SELECT id, connector_specific_config
+            FROM connector
+            WHERE source = 'GITHUB'
+            """
+        )
+    ).fetchall()
+
+    logger.debug(f"Found {len(github_connectors)} GitHub connectors to rollback")
+
+    # Revert each GitHub connector to use repo_name instead of repositories
+    reverted_count = 0
+    for connector_id, config in github_connectors:
+        try:
+            if not config:
+                continue
+
+            # Parse the config if it's a string
+            if isinstance(config, str):
+                config = json.loads(config)
+
+            if "repositories" not in config:
+                continue
+
+            # Create new config with repo_name instead of repositories
+            new_config = dict(config)
+            repositories_value = new_config.pop("repositories")
+            new_config["repo_name"] = repositories_value
+
+            # Update the connector with the new config
+            conn.execute(
+                sa.text(
+                    """
+                    UPDATE connector
+                    SET connector_specific_config = :new_config
+                    WHERE id = :connector_id
+                    """
+                ),
+                {"new_config": json.dumps(new_config), "connector_id": connector_id},
+            )
+            reverted_count += 1
+        except Exception as e:
+            logger.error(f"Error reverting connector {connector_id}: {str(e)}")

backend/alembic/versions/3bd4c84fe72f_improved_index.py

@@ -6,8 +6,7 @@ Create Date: 2025-02-26 13:07:56.217791
 
 """
 from alembic import op
-import time
-from sqlalchemy import text
+
 
 # revision identifiers, used by Alembic.
 revision = "3bd4c84fe72f"
@@ -28,357 +27,45 @@ depends_on = None
 # 4. Adds indexes to both chat_message and chat_session tables for comprehensive search
 
 
-def upgrade():
-    # --- PART 1: chat_message table ---
-    # Step 1: Add nullable column (quick, minimal locking)
-    # op.execute("ALTER TABLE chat_message DROP COLUMN IF EXISTS message_tsv")
-    # op.execute("DROP TRIGGER IF EXISTS chat_message_tsv_trigger ON chat_message")
-    # op.execute("DROP FUNCTION IF EXISTS update_chat_message_tsv()")
-    # op.execute("ALTER TABLE chat_message DROP COLUMN IF EXISTS message_tsv")
-    # # Drop chat_session tsv trigger if it exists
-    # op.execute("DROP TRIGGER IF EXISTS chat_session_tsv_trigger ON chat_session")
-    # op.execute("DROP FUNCTION IF EXISTS update_chat_session_tsv()")
-    # op.execute("ALTER TABLE chat_session DROP COLUMN IF EXISTS title_tsv")
-    # raise Exception("Stop here")
-    time.time()
-    op.execute("ALTER TABLE chat_message ADD COLUMN IF NOT EXISTS message_tsv tsvector")
-
-    # Step 2: Create function and trigger for new/updated rows
+def upgrade() -> None:
+    # Create a GIN index for full-text search on chat_message.message
     op.execute(
         """
-    CREATE OR REPLACE FUNCTION update_chat_message_tsv()
-    RETURNS TRIGGER AS $$
-    BEGIN
-      NEW.message_tsv = to_tsvector('english', NEW.message);
-      RETURN NEW;
-    END;
-    $$ LANGUAGE plpgsql
-    """
+        ALTER TABLE chat_message
+        ADD COLUMN message_tsv tsvector
+        GENERATED ALWAYS AS (to_tsvector('english', message)) STORED;
+        """
     )
 
-    # Create trigger in a separate execute call
+    # Commit the current transaction before creating concurrent indexes
+    op.execute("COMMIT")
+
     op.execute(
         """
-    CREATE TRIGGER chat_message_tsv_trigger
-    BEFORE INSERT OR UPDATE ON chat_message
-    FOR EACH ROW EXECUTE FUNCTION update_chat_message_tsv()
-    """
+        CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv
+        ON chat_message
+        USING GIN (message_tsv)
+        """
     )
 
-    # Step 3: Update existing rows in batches using Python
-    time.time()
-
-    # Get connection and count total rows
-    connection = op.get_bind()
-    total_count_result = connection.execute(
-        text("SELECT COUNT(*) FROM chat_message")
-    ).scalar()
-    total_count = total_count_result if total_count_result is not None else 0
-    batch_size = 5000
-    batches = 0
-
-    # Calculate total batches needed
-    total_batches = (
-        (total_count + batch_size - 1) // batch_size if total_count > 0 else 0
+    # Also add a stored tsvector column for chat_session.description
+    op.execute(
+        """
+        ALTER TABLE chat_session
+        ADD COLUMN description_tsv tsvector
+        GENERATED ALWAYS AS (to_tsvector('english', coalesce(description, ''))) STORED;
+        """
     )
 
-    # Process in batches - properly handling UUIDs by using OFFSET/LIMIT approach
-    for batch_num in range(total_batches):
-        offset = batch_num * batch_size
+    # Commit again before creating the second concurrent index
+    op.execute("COMMIT")
 
-        # Execute update for this batch using OFFSET/LIMIT which works with UUIDs
-        connection.execute(
-            text(
-                """
-            UPDATE chat_message
-            SET message_tsv = to_tsvector('english', message)
-            WHERE id IN (
-                SELECT id FROM chat_message
-                WHERE message_tsv IS NULL
-                ORDER BY id
-                LIMIT :batch_size OFFSET :offset
-            )
-            """
-            ).bindparams(batch_size=batch_size, offset=offset)
-        )
-
-        # Commit each batch
-        connection.execute(text("COMMIT"))
-        # Start a new transaction
-        connection.execute(text("BEGIN"))
-
-        batches += 1
-
-    # Final check for any remaining NULL values
-    connection.execute(
-        text(
-            """
-    UPDATE chat_message SET message_tsv = to_tsvector('english', message)
-    WHERE message_tsv IS NULL
-    """
-        )
-    )
-
-    # Create GIN index concurrently
-    connection.execute(text("COMMIT"))
-
-    time.time()
-
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv
-    ON chat_message USING GIN (message_tsv)
-    """
-        )
-    )
-
-    # First drop the trigger as it won't be needed anymore
-    connection.execute(
-        text(
-            """
-    DROP TRIGGER IF EXISTS chat_message_tsv_trigger ON chat_message;
-    """
-        )
-    )
-
-    connection.execute(
-        text(
-            """
-    DROP FUNCTION IF EXISTS update_chat_message_tsv();
-    """
-        )
-    )
-
-    # Add new generated column
-    time.time()
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_message
-    ADD COLUMN message_tsv_gen tsvector
-    GENERATED ALWAYS AS (to_tsvector('english', message)) STORED;
-    """
-        )
-    )
-
-    connection.execute(text("COMMIT"))
-
-    time.time()
-
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv_gen
-    ON chat_message USING GIN (message_tsv_gen)
-    """
-        )
-    )
-
-    # Drop old index and column
-    connection.execute(text("COMMIT"))
-
-    connection.execute(
-        text(
-            """
-    DROP INDEX CONCURRENTLY IF EXISTS idx_chat_message_tsv;
-    """
-        )
-    )
-    connection.execute(text("COMMIT"))
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_message DROP COLUMN message_tsv;
-    """
-        )
-    )
-
-    # Rename new column to old name
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_message RENAME COLUMN message_tsv_gen TO message_tsv;
-    """
-        )
-    )
-
-    # --- PART 2: chat_session table ---
-
-    # Step 1: Add nullable column (quick, minimal locking)
-    time.time()
-    connection.execute(
-        text(
-            "ALTER TABLE chat_session ADD COLUMN IF NOT EXISTS description_tsv tsvector"
-        )
-    )
-
-    # Step 2: Create function and trigger for new/updated rows - SPLIT INTO SEPARATE CALLS
-    connection.execute(
-        text(
-            """
-    CREATE OR REPLACE FUNCTION update_chat_session_tsv()
-    RETURNS TRIGGER AS $$
-    BEGIN
-      NEW.description_tsv = to_tsvector('english', COALESCE(NEW.description, ''));
-      RETURN NEW;
-    END;
-    $$ LANGUAGE plpgsql
-    """
-        )
-    )
-
-    # Create trigger in a separate execute call
-    connection.execute(
-        text(
-            """
-    CREATE TRIGGER chat_session_tsv_trigger
-    BEFORE INSERT OR UPDATE ON chat_session
-    FOR EACH ROW EXECUTE FUNCTION update_chat_session_tsv()
-    """
-        )
-    )
-
-    # Step 3: Update existing rows in batches using Python
-    time.time()
-
-    # Get the maximum ID to determine batch count
-    # Cast id to text for MAX function since it's a UUID
-    max_id_result = connection.execute(
-        text("SELECT COALESCE(MAX(id::text), '0') FROM chat_session")
-    ).scalar()
-    max_id_result if max_id_result is not None else "0"
-    batch_size = 5000
-    batches = 0
-
-    # Get all IDs ordered to process in batches
-    rows = connection.execute(
-        text("SELECT id FROM chat_session ORDER BY id")
-    ).fetchall()
-    total_rows = len(rows)
-
-    # Process in batches
-    for batch_num, batch_start in enumerate(range(0, total_rows, batch_size)):
-        batch_end = min(batch_start + batch_size, total_rows)
-        batch_ids = [row[0] for row in rows[batch_start:batch_end]]
-
-        if not batch_ids:
-            continue
-
-        # Use IN clause instead of BETWEEN for UUIDs
-        placeholders = ", ".join([f":id{i}" for i in range(len(batch_ids))])
-        params = {f"id{i}": id_val for i, id_val in enumerate(batch_ids)}
-
-        # Execute update for this batch
-        connection.execute(
-            text(
-                f"""
-            UPDATE chat_session
-            SET description_tsv = to_tsvector('english', COALESCE(description, ''))
-            WHERE id IN ({placeholders})
-            AND description_tsv IS NULL
-            """
-            ).bindparams(**params)
-        )
-
-        # Commit each batch
-        connection.execute(text("COMMIT"))
-        # Start a new transaction
-        connection.execute(text("BEGIN"))
-
-        batches += 1
-
-    # Final check for any remaining NULL values
-    connection.execute(
-        text(
-            """
-    UPDATE chat_session SET description_tsv = to_tsvector('english', COALESCE(description, ''))
-    WHERE description_tsv IS NULL
-    """
-        )
-    )
-
-    # Create GIN index concurrently
-    connection.execute(text("COMMIT"))
-
-    time.time()
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv
-    ON chat_session USING GIN (description_tsv)
-    """
-        )
-    )
-
-    # After Final check for chat_session
-    # First drop the trigger as it won't be needed anymore
-    connection.execute(
-        text(
-            """
-    DROP TRIGGER IF EXISTS chat_session_tsv_trigger ON chat_session;
-    """
-        )
-    )
-
-    connection.execute(
-        text(
-            """
-    DROP FUNCTION IF EXISTS update_chat_session_tsv();
-    """
-        )
-    )
-    # Add new generated column
-    time.time()
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_session
-    ADD COLUMN description_tsv_gen tsvector
-    GENERATED ALWAYS AS (to_tsvector('english', COALESCE(description, ''))) STORED;
-    """
-        )
-    )
-
-    # Create new index on generated column
-    connection.execute(text("COMMIT"))
-
-    time.time()
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv_gen
-    ON chat_session USING GIN (description_tsv_gen)
-    """
-        )
-    )
-
-    # Drop old index and column
-    connection.execute(text("COMMIT"))
-
-    connection.execute(
-        text(
-            """
-    DROP INDEX CONCURRENTLY IF EXISTS idx_chat_session_desc_tsv;
-    """
-        )
-    )
-    connection.execute(text("COMMIT"))
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_session DROP COLUMN description_tsv;
-    """
-        )
-    )
-
-    # Rename new column to old name
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_session RENAME COLUMN description_tsv_gen TO description_tsv;
-    """
-        )
+    op.execute(
+        """
+        CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv
+        ON chat_session
+        USING GIN (description_tsv)
+        """
     )
 
 

backend/ee/onyx/main.py

@@ -15,7 +15,7 @@ from ee.onyx.server.enterprise_settings.api import (
 )
 from ee.onyx.server.manage.standard_answer import router as standard_answer_router
 from ee.onyx.server.middleware.tenant_tracking import add_tenant_id_middleware
-from ee.onyx.server.oauth.api import router as oauth_router
+from ee.onyx.server.oauth.api import router as ee_oauth_router
 from ee.onyx.server.query_and_chat.chat_backend import (
     router as chat_router,
 )
@@ -128,7 +128,7 @@ def get_application() -> FastAPI:
     include_router_with_global_prefix_prepended(application, query_router)
     include_router_with_global_prefix_prepended(application, chat_router)
     include_router_with_global_prefix_prepended(application, standard_answer_router)
-    include_router_with_global_prefix_prepended(application, oauth_router)
+    include_router_with_global_prefix_prepended(application, ee_oauth_router)
 
     # Enterprise-only global settings
     include_router_with_global_prefix_prepended(

backend/ee/onyx/server/oauth/confluence_cloud.py

@@ -80,6 +80,7 @@ class ConfluenceCloudOAuth:
         "search:confluence%20"
         # granular scope
         "read:attachment:confluence%20"  # possibly unneeded unless calling v2 attachments api
+        "read:content-details:confluence%20"  # for permission sync
         "offline_access"
     )
 

backend/ee/onyx/server/tenants/product_gating.py

@@ -48,4 +48,5 @@ def store_product_gating(tenant_id: str, application_status: ApplicationStatus)
 
 def get_gated_tenants() -> set[str]:
     redis_client = get_redis_replica_client(tenant_id=ONYX_CLOUD_TENANT_ID)
-    return cast(set[str], redis_client.smembers(GATED_TENANTS_KEY))
+    gated_tenants_bytes = cast(set[bytes], redis_client.smembers(GATED_TENANTS_KEY))
+    return {tenant_id.decode("utf-8") for tenant_id in gated_tenants_bytes}

backend/ee/onyx/server/tenants/provisioning.py

@@ -55,7 +55,11 @@ logger = logging.getLogger(__name__)
 async def get_or_provision_tenant(
     email: str, referral_source: str | None = None, request: Request | None = None
 ) -> str:
-    """Get existing tenant ID for an email or create a new tenant if none exists."""
+    """
+    Get existing tenant ID for an email or create a new tenant if none exists.
+    This function should only be called after we have verified we want this user's tenant to exist.
+    It returns the tenant ID associated with the email, creating a new tenant if necessary.
+    """
     if not MULTI_TENANT:
         return POSTGRES_DEFAULT_SCHEMA
 

backend/onyx/agents/agent_search/deep_search/initial/generate_initial_answer/nodes/generate_initial_answer.py

@@ -153,8 +153,9 @@ def generate_initial_answer(
     )
     for tool_response in yield_search_responses(
         query=question,
-        reranked_sections=answer_generation_documents.streaming_documents,
-        final_context_sections=answer_generation_documents.context_documents,
+        get_retrieved_sections=lambda: answer_generation_documents.context_documents,
+        get_reranked_sections=lambda: answer_generation_documents.streaming_documents,
+        get_final_context_sections=lambda: answer_generation_documents.context_documents,
         search_query_info=query_info,
         get_section_relevance=lambda: relevance_list,
         search_tool=graph_config.tooling.search_tool,

backend/onyx/agents/agent_search/deep_search/main/nodes/generate_validate_refined_answer.py

@@ -179,8 +179,9 @@ def generate_validate_refined_answer(
     )
     for tool_response in yield_search_responses(
         query=question,
-        reranked_sections=answer_generation_documents.streaming_documents,
-        final_context_sections=answer_generation_documents.context_documents,
+        get_retrieved_sections=lambda: answer_generation_documents.context_documents,
+        get_reranked_sections=lambda: answer_generation_documents.streaming_documents,
+        get_final_context_sections=lambda: answer_generation_documents.context_documents,
         search_query_info=query_info,
         get_section_relevance=lambda: relevance_list,
         search_tool=graph_config.tooling.search_tool,

backend/onyx/agents/agent_search/deep_search/main/operations.py

@@ -13,7 +13,6 @@ from onyx.chat.models import StreamStopInfo
 from onyx.chat.models import StreamStopReason
 from onyx.chat.models import StreamType
 from onyx.chat.models import SubQuestionPiece
-from onyx.context.search.models import IndexFilters
 from onyx.tools.models import SearchQueryInfo
 from onyx.utils.logger import setup_logger
 
@@ -144,8 +143,6 @@ def get_query_info(results: list[QueryRetrievalResult]) -> SearchQueryInfo:
         if result.query_info is not None:
             query_info = result.query_info
             break
-    return query_info or SearchQueryInfo(
-        predicted_search=None,
-        final_filters=IndexFilters(access_control_list=None),
-        recency_bias_multiplier=1.0,
-    )
+
+    assert query_info is not None, "must have query info"
+    return query_info

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/format_results.py

@@ -56,8 +56,9 @@ def format_results(
         relevance_list = relevance_from_docs(reranked_documents)
         for tool_response in yield_search_responses(
             query=state.question,
-            reranked_sections=state.retrieved_documents,
-            final_context_sections=reranked_documents,
+            get_retrieved_sections=lambda: reranked_documents,
+            get_reranked_sections=lambda: state.retrieved_documents,
+            get_final_context_sections=lambda: reranked_documents,
             search_query_info=query_info,
             get_section_relevance=lambda: relevance_list,
             search_tool=graph_config.tooling.search_tool,

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/retrieve_documents.py

@@ -91,7 +91,7 @@ def retrieve_documents(
     retrieved_docs = retrieved_docs[:AGENT_MAX_QUERY_RETRIEVAL_RESULTS]
 
     if AGENT_RETRIEVAL_STATS:
-        pre_rerank_docs = callback_container[0]
+        pre_rerank_docs = callback_container[0] if callback_container else []
         fit_scores = get_fit_scores(
             pre_rerank_docs,
             retrieved_docs,

backend/onyx/agents/agent_search/orchestration/nodes/call_tool.py

@@ -44,7 +44,9 @@ def call_tool(
     tool = tool_choice.tool
     tool_args = tool_choice.tool_args
     tool_id = tool_choice.id
-    tool_runner = ToolRunner(tool, tool_args)
+    tool_runner = ToolRunner(
+        tool, tool_args, override_kwargs=tool_choice.search_tool_override_kwargs
+    )
     tool_kickoff = tool_runner.kickoff()
 
     emit_packet(tool_kickoff, writer)

backend/onyx/agents/agent_search/orchestration/nodes/choose_tool.py

@@ -15,8 +15,17 @@ from onyx.chat.tool_handling.tool_response_handler import get_tool_by_name
 from onyx.chat.tool_handling.tool_response_handler import (
     get_tool_call_for_non_tool_calling_llm_impl,
 )
+from onyx.context.search.preprocessing.preprocessing import query_analysis
+from onyx.context.search.retrieval.search_runner import get_query_embedding
+from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.tool import Tool
+from onyx.tools.tool_implementations.search.search_tool import SearchTool
 from onyx.utils.logger import setup_logger
+from onyx.utils.threadpool_concurrency import run_in_background
+from onyx.utils.threadpool_concurrency import TimeoutThread
+from onyx.utils.threadpool_concurrency import wait_on_background
+from onyx.utils.timing import log_function_time
+from shared_configs.model_server_models import Embedding
 
 logger = setup_logger()
 
@@ -25,6 +34,7 @@ logger = setup_logger()
 # and a function that handles extracting the necessary fields
 # from the state and config
 # TODO: fan-out to multiple tool call nodes? Make this configurable?
+@log_function_time(print_only=True)
 def choose_tool(
     state: ToolChoiceState,
     config: RunnableConfig,
@@ -37,6 +47,31 @@ def choose_tool(
     should_stream_answer = state.should_stream_answer
 
     agent_config = cast(GraphConfig, config["metadata"]["config"])
+
+    force_use_tool = agent_config.tooling.force_use_tool
+
+    embedding_thread: TimeoutThread[Embedding] | None = None
+    keyword_thread: TimeoutThread[tuple[bool, list[str]]] | None = None
+    override_kwargs: SearchToolOverrideKwargs | None = None
+    if (
+        not agent_config.behavior.use_agentic_search
+        and agent_config.tooling.search_tool is not None
+        and (
+            not force_use_tool.force_use or force_use_tool.tool_name == SearchTool.name
+        )
+    ):
+        override_kwargs = SearchToolOverrideKwargs()
+        # Run in a background thread to avoid blocking the main thread
+        embedding_thread = run_in_background(
+            get_query_embedding,
+            agent_config.inputs.search_request.query,
+            agent_config.persistence.db_session,
+        )
+        keyword_thread = run_in_background(
+            query_analysis,
+            agent_config.inputs.search_request.query,
+        )
+
     using_tool_calling_llm = agent_config.tooling.using_tool_calling_llm
     prompt_builder = state.prompt_snapshot or agent_config.inputs.prompt_builder
 
@@ -47,7 +82,6 @@ def choose_tool(
     tools = [
         tool for tool in (agent_config.tooling.tools or []) if tool.name in state.tools
     ]
-    force_use_tool = agent_config.tooling.force_use_tool
 
     tool, tool_args = None, None
     if force_use_tool.force_use and force_use_tool.args is not None:
@@ -71,11 +105,22 @@ def choose_tool(
     # If we have a tool and tool args, we are ready to request a tool call.
     # This only happens if the tool call was forced or we are using a non-tool calling LLM.
     if tool and tool_args:
+        if embedding_thread and tool.name == SearchTool._NAME:
+            # Wait for the embedding thread to finish
+            embedding = wait_on_background(embedding_thread)
+            assert override_kwargs is not None, "must have override kwargs"
+            override_kwargs.precomputed_query_embedding = embedding
+        if keyword_thread and tool.name == SearchTool._NAME:
+            is_keyword, keywords = wait_on_background(keyword_thread)
+            assert override_kwargs is not None, "must have override kwargs"
+            override_kwargs.precomputed_is_keyword = is_keyword
+            override_kwargs.precomputed_keywords = keywords
         return ToolChoiceUpdate(
             tool_choice=ToolChoice(
                 tool=tool,
                 tool_args=tool_args,
                 id=str(uuid4()),
+                search_tool_override_kwargs=override_kwargs,
             ),
         )
 
@@ -153,10 +198,22 @@ def choose_tool(
     logger.debug(f"Selected tool: {selected_tool.name}")
     logger.debug(f"Selected tool call request: {selected_tool_call_request}")
 
+    if embedding_thread and selected_tool.name == SearchTool._NAME:
+        # Wait for the embedding thread to finish
+        embedding = wait_on_background(embedding_thread)
+        assert override_kwargs is not None, "must have override kwargs"
+        override_kwargs.precomputed_query_embedding = embedding
+    if keyword_thread and selected_tool.name == SearchTool._NAME:
+        is_keyword, keywords = wait_on_background(keyword_thread)
+        assert override_kwargs is not None, "must have override kwargs"
+        override_kwargs.precomputed_is_keyword = is_keyword
+        override_kwargs.precomputed_keywords = keywords
+
     return ToolChoiceUpdate(
         tool_choice=ToolChoice(
             tool=selected_tool,
             tool_args=selected_tool_call_request["args"],
             id=selected_tool_call_request["id"],
+            search_tool_override_kwargs=override_kwargs,
         ),
     )

backend/onyx/agents/agent_search/orchestration/nodes/use_tool_response.py

@@ -9,18 +9,23 @@ from onyx.agents.agent_search.basic.states import BasicState
 from onyx.agents.agent_search.basic.utils import process_llm_stream
 from onyx.agents.agent_search.models import GraphConfig
 from onyx.chat.models import LlmDoc
-from onyx.chat.models import OnyxContexts
 from onyx.tools.tool_implementations.search.search_tool import (
-    SEARCH_DOC_CONTENT_ID,
+    SEARCH_RESPONSE_SUMMARY_ID,
+)
+from onyx.tools.tool_implementations.search.search_tool import SearchResponseSummary
+from onyx.tools.tool_implementations.search.search_utils import (
+    context_from_inference_section,
 )
 from onyx.tools.tool_implementations.search_like_tool_utils import (
     FINAL_CONTEXT_DOCUMENTS_ID,
 )
 from onyx.utils.logger import setup_logger
+from onyx.utils.timing import log_function_time
 
 logger = setup_logger()
 
 
+@log_function_time(print_only=True)
 def basic_use_tool_response(
     state: BasicState, config: RunnableConfig, writer: StreamWriter = lambda _: None
 ) -> BasicOutput:
@@ -50,11 +55,13 @@ def basic_use_tool_response(
     for yield_item in tool_call_responses:
         if yield_item.id == FINAL_CONTEXT_DOCUMENTS_ID:
             final_search_results = cast(list[LlmDoc], yield_item.response)
-        elif yield_item.id == SEARCH_DOC_CONTENT_ID:
-            search_contexts = cast(OnyxContexts, yield_item.response).contexts
-            for doc in search_contexts:
-                if doc.document_id not in initial_search_results:
-                    initial_search_results.append(doc)
+        elif yield_item.id == SEARCH_RESPONSE_SUMMARY_ID:
+            search_response_summary = cast(SearchResponseSummary, yield_item.response)
+            for section in search_response_summary.top_sections:
+                if section.center_chunk.document_id not in initial_search_results:
+                    initial_search_results.append(
+                        context_from_inference_section(section)
+                    )
 
     new_tool_call_chunk = AIMessageChunk(content="")
     if not agent_config.behavior.skip_gen_ai_answer_generation:

backend/onyx/agents/agent_search/orchestration/states.py

@@ -2,6 +2,7 @@ from pydantic import BaseModel
 
 from onyx.chat.prompt_builder.answer_prompt_builder import PromptSnapshot
 from onyx.tools.message import ToolCallSummary
+from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.models import ToolCallFinalResult
 from onyx.tools.models import ToolCallKickoff
 from onyx.tools.models import ToolResponse
@@ -35,6 +36,7 @@ class ToolChoice(BaseModel):
     tool: Tool
     tool_args: dict
     id: str | None
+    search_tool_override_kwargs: SearchToolOverrideKwargs | None = None
 
     class Config:
         arbitrary_types_allowed = True

backend/onyx/agents/agent_search/shared_graph_utils/constants.py

@@ -13,6 +13,11 @@ AGENT_NEGATIVE_VALUE_STR = "no"
 AGENT_ANSWER_SEPARATOR = "Answer:"
 
 
+EMBEDDING_KEY = "embedding"
+IS_KEYWORD_KEY = "is_keyword"
+KEYWORDS_KEY = "keywords"
+
+
 class AgentLLMErrorType(str, Enum):
     TIMEOUT = "timeout"
     RATE_LIMIT = "rate_limit"

backend/onyx/auth/users.py

@@ -587,14 +587,20 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
     ) -> Optional[User]:
         email = credentials.username
 
-        # Get tenant_id from mapping table
-        tenant_id = await fetch_ee_implementation_or_noop(
-            "onyx.server.tenants.provisioning",
-            "get_or_provision_tenant",
-            async_return_default_schema,
-        )(
-            email=email,
-        )
+        tenant_id: str | None = None
+        try:
+            tenant_id = fetch_ee_implementation_or_noop(
+                "onyx.server.tenants.provisioning",
+                "get_tenant_id_for_email",
+                None,
+            )(
+                email=email,
+            )
+        except Exception as e:
+            logger.warning(
+                f"User attempted to login with invalid credentials: {str(e)}"
+            )
+
         if not tenant_id:
             # User not found in mapping
             self.password_helper.hash(credentials.password)

backend/onyx/chat/llm_response_handler.py

@@ -15,6 +15,8 @@ from onyx.chat.stream_processing.answer_response_handler import (
 from onyx.chat.tool_handling.tool_response_handler import ToolResponseHandler
 
 
+# This is Legacy code that is not used anymore.
+# It is kept here for reference.
 class LLMResponseHandlerManager:
     """
     This class is responsible for postprocessing the LLM response stream.

backend/onyx/chat/stream_processing/citation_processing.py

@@ -90,97 +90,97 @@ class CitationProcessor:
                     next(group for group in citation.groups() if group is not None)
                 )
 
-                if 1 <= numerical_value <= self.max_citation_num:
-                    context_llm_doc = self.context_docs[numerical_value - 1]
-                    final_citation_num = self.final_order_mapping[
+                if not (1 <= numerical_value <= self.max_citation_num):
+                    continue
+
+                context_llm_doc = self.context_docs[numerical_value - 1]
+                final_citation_num = self.final_order_mapping[
+                    context_llm_doc.document_id
+                ]
+
+                if final_citation_num not in self.citation_order:
+                    self.citation_order.append(final_citation_num)
+
+                citation_order_idx = self.citation_order.index(final_citation_num) + 1
+
+                # get the value that was displayed to user, should always
+                # be in the display_doc_order_dict. But check anyways
+                if context_llm_doc.document_id in self.display_order_mapping:
+                    displayed_citation_num = self.display_order_mapping[
                         context_llm_doc.document_id
                     ]
-
-                    if final_citation_num not in self.citation_order:
-                        self.citation_order.append(final_citation_num)
-
-                    citation_order_idx = (
-                        self.citation_order.index(final_citation_num) + 1
+                else:
+                    displayed_citation_num = final_citation_num
+                    logger.warning(
+                        f"Doc {context_llm_doc.document_id} not in display_doc_order_dict. Used LLM citation number instead."
                     )
 
-                    # get the value that was displayed to user, should always
-                    # be in the display_doc_order_dict. But check anyways
-                    if context_llm_doc.document_id in self.display_order_mapping:
-                        displayed_citation_num = self.display_order_mapping[
-                            context_llm_doc.document_id
-                        ]
-                    else:
-                        displayed_citation_num = final_citation_num
-                        logger.warning(
-                            f"Doc {context_llm_doc.document_id} not in display_doc_order_dict. Used LLM citation number instead."
-                        )
-
-                    # Skip consecutive citations of the same work
-                    if final_citation_num in self.current_citations:
-                        start, end = citation.span()
-                        real_start = length_to_add + start
-                        diff = end - start
-                        self.curr_segment = (
-                            self.curr_segment[: length_to_add + start]
-                            + self.curr_segment[real_start + diff :]
-                        )
-                        length_to_add -= diff
-                        continue
-
-                    # Handle edge case where LLM outputs citation itself
-                    if self.curr_segment.startswith("[["):
-                        match = re.match(r"\[\[(\d+)\]\]", self.curr_segment)
-                        if match:
-                            try:
-                                doc_id = int(match.group(1))
-                                context_llm_doc = self.context_docs[doc_id - 1]
-                                yield CitationInfo(
-                                    # citation_num is now the number post initial ranking, i.e. as displayed to user
-                                    citation_num=displayed_citation_num,
-                                    document_id=context_llm_doc.document_id,
-                                )
-                            except Exception as e:
-                                logger.warning(
-                                    f"Manual LLM citation didn't properly cite documents {e}"
-                                )
-                        else:
-                            logger.warning(
-                                "Manual LLM citation wasn't able to close brackets"
-                            )
-                        continue
-
-                    link = context_llm_doc.link
-
-                    self.past_cite_count = len(self.llm_out)
-                    self.current_citations.append(final_citation_num)
-
-                    if citation_order_idx not in self.cited_inds:
-                        self.cited_inds.add(citation_order_idx)
-                        yield CitationInfo(
-                            # citation number is now the one that was displayed to user
-                            citation_num=displayed_citation_num,
-                            document_id=context_llm_doc.document_id,
-                        )
-
+                # Skip consecutive citations of the same work
+                if final_citation_num in self.current_citations:
                     start, end = citation.span()
-                    if link:
-                        prev_length = len(self.curr_segment)
-                        self.curr_segment = (
-                            self.curr_segment[: start + length_to_add]
-                            + f"[[{displayed_citation_num}]]({link})"  # use the value that was displayed to user
-                            + self.curr_segment[end + length_to_add :]
-                        )
-                        length_to_add += len(self.curr_segment) - prev_length
-                    else:
-                        prev_length = len(self.curr_segment)
-                        self.curr_segment = (
-                            self.curr_segment[: start + length_to_add]
-                            + f"[[{displayed_citation_num}]]()"  # use the value that was displayed to user
-                            + self.curr_segment[end + length_to_add :]
-                        )
-                        length_to_add += len(self.curr_segment) - prev_length
+                    real_start = length_to_add + start
+                    diff = end - start
+                    self.curr_segment = (
+                        self.curr_segment[: length_to_add + start]
+                        + self.curr_segment[real_start + diff :]
+                    )
+                    length_to_add -= diff
+                    continue
 
-                    last_citation_end = end + length_to_add
+                # Handle edge case where LLM outputs citation itself
+                if self.curr_segment.startswith("[["):
+                    match = re.match(r"\[\[(\d+)\]\]", self.curr_segment)
+                    if match:
+                        try:
+                            doc_id = int(match.group(1))
+                            context_llm_doc = self.context_docs[doc_id - 1]
+                            yield CitationInfo(
+                                # citation_num is now the number post initial ranking, i.e. as displayed to user
+                                citation_num=displayed_citation_num,
+                                document_id=context_llm_doc.document_id,
+                            )
+                        except Exception as e:
+                            logger.warning(
+                                f"Manual LLM citation didn't properly cite documents {e}"
+                            )
+                    else:
+                        logger.warning(
+                            "Manual LLM citation wasn't able to close brackets"
+                        )
+                    continue
+
+                link = context_llm_doc.link
+
+                self.past_cite_count = len(self.llm_out)
+                self.current_citations.append(final_citation_num)
+
+                if citation_order_idx not in self.cited_inds:
+                    self.cited_inds.add(citation_order_idx)
+                    yield CitationInfo(
+                        # citation number is now the one that was displayed to user
+                        citation_num=displayed_citation_num,
+                        document_id=context_llm_doc.document_id,
+                    )
+
+                start, end = citation.span()
+                if link:
+                    prev_length = len(self.curr_segment)
+                    self.curr_segment = (
+                        self.curr_segment[: start + length_to_add]
+                        + f"[[{displayed_citation_num}]]({link})"  # use the value that was displayed to user
+                        + self.curr_segment[end + length_to_add :]
+                    )
+                    length_to_add += len(self.curr_segment) - prev_length
+                else:
+                    prev_length = len(self.curr_segment)
+                    self.curr_segment = (
+                        self.curr_segment[: start + length_to_add]
+                        + f"[[{displayed_citation_num}]]()"  # use the value that was displayed to user
+                        + self.curr_segment[end + length_to_add :]
+                    )
+                    length_to_add += len(self.curr_segment) - prev_length
+
+                last_citation_end = end + length_to_add
 
             if last_citation_end > 0:
                 result += self.curr_segment[:last_citation_end]

backend/onyx/connectors/confluence/connector.py

@@ -240,7 +240,7 @@ class ConfluenceConnector(
             # Extract basic page information
             page_id = page["id"]
             page_title = page["title"]
-            page_url = f"{self.wiki_base}/wiki{page['_links']['webui']}"
+            page_url = f"{self.wiki_base}{page['_links']['webui']}"
 
             # Get the page content
             page_content = extract_text_from_confluence_html(
@@ -305,7 +305,7 @@ class ConfluenceConnector(
 
             # Create the document
             return Document(
-                id=build_confluence_document_id(self.wiki_base, page_id, self.is_cloud),
+                id=build_confluence_document_id(self.wiki_base, page["_links"]["webui"], self.is_cloud),
                 sections=sections,
                 source=DocumentSource.CONFLUENCE,
                 semantic_identifier=page_title,
@@ -376,7 +376,7 @@ class ConfluenceConnector(
                     content_text, file_storage_name = response
 
                     object_url = build_confluence_document_id(
-                        self.wiki_base, page["_links"]["webui"], self.is_cloud
+                        self.wiki_base, attachment["_links"]["webui"], self.is_cloud
                     )
 
                     if content_text:

backend/onyx/connectors/github/connector.py

@@ -124,14 +124,14 @@ class GithubConnector(LoadConnector, PollConnector):
     def __init__(
         self,
         repo_owner: str,
-        repo_name: str | None = None,
+        repositories: str | None = None,
         batch_size: int = INDEX_BATCH_SIZE,
         state_filter: str = "all",
         include_prs: bool = True,
         include_issues: bool = False,
     ) -> None:
         self.repo_owner = repo_owner
-        self.repo_name = repo_name
+        self.repositories = repositories
         self.batch_size = batch_size
         self.state_filter = state_filter
         self.include_prs = include_prs
@@ -157,11 +157,42 @@ class GithubConnector(LoadConnector, PollConnector):
             )
 
         try:
-            return github_client.get_repo(f"{self.repo_owner}/{self.repo_name}")
+            return github_client.get_repo(f"{self.repo_owner}/{self.repositories}")
         except RateLimitExceededException:
             _sleep_after_rate_limit_exception(github_client)
             return self._get_github_repo(github_client, attempt_num + 1)
 
+    def _get_github_repos(
+        self, github_client: Github, attempt_num: int = 0
+    ) -> list[Repository.Repository]:
+        """Get specific repositories based on comma-separated repo_name string."""
+        if attempt_num > _MAX_NUM_RATE_LIMIT_RETRIES:
+            raise RuntimeError(
+                "Re-tried fetching repos too many times. Something is going wrong with fetching objects from Github"
+            )
+
+        try:
+            repos = []
+            # Split repo_name by comma and strip whitespace
+            repo_names = [
+                name.strip() for name in (cast(str, self.repositories)).split(",")
+            ]
+
+            for repo_name in repo_names:
+                if repo_name:  # Skip empty strings
+                    try:
+                        repo = github_client.get_repo(f"{self.repo_owner}/{repo_name}")
+                        repos.append(repo)
+                    except GithubException as e:
+                        logger.warning(
+                            f"Could not fetch repo {self.repo_owner}/{repo_name}: {e}"
+                        )
+
+            return repos
+        except RateLimitExceededException:
+            _sleep_after_rate_limit_exception(github_client)
+            return self._get_github_repos(github_client, attempt_num + 1)
+
     def _get_all_repos(
         self, github_client: Github, attempt_num: int = 0
     ) -> list[Repository.Repository]:
@@ -189,11 +220,17 @@ class GithubConnector(LoadConnector, PollConnector):
         if self.github_client is None:
             raise ConnectorMissingCredentialError("GitHub")
 
-        repos = (
-            [self._get_github_repo(self.github_client)]
-            if self.repo_name
-            else self._get_all_repos(self.github_client)
-        )
+        repos = []
+        if self.repositories:
+            if "," in self.repositories:
+                # Multiple repositories specified
+                repos = self._get_github_repos(self.github_client)
+            else:
+                # Single repository (backward compatibility)
+                repos = [self._get_github_repo(self.github_client)]
+        else:
+            # All repositories
+            repos = self._get_all_repos(self.github_client)
 
         for repo in repos:
             if self.include_prs:
@@ -268,11 +305,48 @@ class GithubConnector(LoadConnector, PollConnector):
             )
 
         try:
-            if self.repo_name:
-                test_repo = self.github_client.get_repo(
-                    f"{self.repo_owner}/{self.repo_name}"
-                )
-                test_repo.get_contents("")
+            if self.repositories:
+                if "," in self.repositories:
+                    # Multiple repositories specified
+                    repo_names = [name.strip() for name in self.repositories.split(",")]
+                    if not repo_names:
+                        raise ConnectorValidationError(
+                            "Invalid connector settings: No valid repository names provided."
+                        )
+
+                    # Validate at least one repository exists and is accessible
+                    valid_repos = False
+                    validation_errors = []
+
+                    for repo_name in repo_names:
+                        if not repo_name:
+                            continue
+
+                        try:
+                            test_repo = self.github_client.get_repo(
+                                f"{self.repo_owner}/{repo_name}"
+                            )
+                            test_repo.get_contents("")
+                            valid_repos = True
+                            # If at least one repo is valid, we can proceed
+                            break
+                        except GithubException as e:
+                            validation_errors.append(
+                                f"Repository '{repo_name}': {e.data.get('message', str(e))}"
+                            )
+
+                    if not valid_repos:
+                        error_msg = (
+                            "None of the specified repositories could be accessed: "
+                        )
+                        error_msg += ", ".join(validation_errors)
+                        raise ConnectorValidationError(error_msg)
+                else:
+                    # Single repository (backward compatibility)
+                    test_repo = self.github_client.get_repo(
+                        f"{self.repo_owner}/{self.repositories}"
+                    )
+                    test_repo.get_contents("")
             else:
                 # Try to get organization first
                 try:
@@ -298,10 +372,15 @@ class GithubConnector(LoadConnector, PollConnector):
                     "Your GitHub token does not have sufficient permissions for this repository (HTTP 403)."
                 )
             elif e.status == 404:
-                if self.repo_name:
-                    raise ConnectorValidationError(
-                        f"GitHub repository not found with name: {self.repo_owner}/{self.repo_name}"
-                    )
+                if self.repositories:
+                    if "," in self.repositories:
+                        raise ConnectorValidationError(
+                            f"None of the specified GitHub repositories could be found for owner: {self.repo_owner}"
+                        )
+                    else:
+                        raise ConnectorValidationError(
+                            f"GitHub repository not found with name: {self.repo_owner}/{self.repositories}"
+                        )
                 else:
                     raise ConnectorValidationError(
                         f"GitHub user or organization not found: {self.repo_owner}"
@@ -310,6 +389,7 @@ class GithubConnector(LoadConnector, PollConnector):
                 raise ConnectorValidationError(
                     f"Unexpected GitHub error (status={e.status}): {e.data}"
                 )
+
         except Exception as exc:
             raise Exception(
                 f"Unexpected error during GitHub settings validation: {exc}"
@@ -321,7 +401,7 @@ if __name__ == "__main__":
 
     connector = GithubConnector(
         repo_owner=os.environ["REPO_OWNER"],
-        repo_name=os.environ["REPO_NAME"],
+        repositories=os.environ["REPOSITORIES"],
     )
     connector.load_credentials(
         {"github_access_token": os.environ["GITHUB_ACCESS_TOKEN"]}

backend/onyx/connectors/google_drive/connector.py

@@ -316,7 +316,9 @@ class GoogleDriveConnector(
         # validate that the user has access to the drive APIs by performing a simple
         # request and checking for a 401
         try:
-            retry_builder()(get_root_folder_id)(drive_service)
+            # default is ~17mins of retries, don't do that here for cases so we don't
+            # waste 17mins everytime we run into a user without access to drive APIs
+            retry_builder(tries=3, delay=1)(get_root_folder_id)(drive_service)
         except HttpError as e:
             if e.status_code == 401:
                 # fail gracefully, let the other impersonations continue

backend/onyx/context/search/models.py

@@ -16,7 +16,7 @@ from onyx.db.models import SearchSettings
 from onyx.indexing.models import BaseChunk
 from onyx.indexing.models import IndexingSetting
 from shared_configs.enums import RerankerProvider
-
+from shared_configs.model_server_models import Embedding
 
 MAX_METRICS_CONTENT = (
     200  # Just need enough characters to identify where in the doc the chunk is
@@ -151,6 +151,10 @@ class SearchRequest(ChunkContext):
     evaluation_type: LLMEvaluationType = LLMEvaluationType.UNSPECIFIED
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
+    precomputed_query_embedding: Embedding | None = None
+    precomputed_is_keyword: bool | None = None
+    precomputed_keywords: list[str] | None = None
+
 
 class SearchQuery(ChunkContext):
     "Processed Request that is directly passed to the SearchPipeline"
@@ -175,6 +179,8 @@ class SearchQuery(ChunkContext):
     offset: int = 0
     model_config = ConfigDict(frozen=True)
 
+    precomputed_query_embedding: Embedding | None = None
+
 
 class RetrievalDetails(ChunkContext):
     # Use LLM to determine whether to do a retrieval or only rely on existing history

backend/onyx/context/search/pipeline.py

@@ -331,6 +331,14 @@ class SearchPipeline:
         self._retrieved_sections = expanded_inference_sections
         return expanded_inference_sections
 
+    @property
+    def retrieved_sections(self) -> list[InferenceSection]:
+        if self._retrieved_sections is not None:
+            return self._retrieved_sections
+
+        self._retrieved_sections = self._get_sections()
+        return self._retrieved_sections
+
     @property
     def reranked_sections(self) -> list[InferenceSection]:
         """Reranking is always done at the chunk level since section merging could create arbitrarily
@@ -343,7 +351,7 @@ class SearchPipeline:
         if self._reranked_sections is not None:
             return self._reranked_sections
 
-        retrieved_sections = self._get_sections()
+        retrieved_sections = self.retrieved_sections
         if self.retrieved_sections_callback is not None:
             self.retrieved_sections_callback(retrieved_sections)
 

backend/onyx/context/search/preprocessing/preprocessing.py

@@ -117,8 +117,12 @@ def retrieval_preprocessing(
         else None
     )
 
+    # Sometimes this is pre-computed in parallel with other heavy tasks to improve
+    # latency, and in that case we don't need to run the model again
     run_query_analysis = (
-        None if skip_query_analysis else FunctionCall(query_analysis, (query,), {})
+        None
+        if (skip_query_analysis or search_request.precomputed_is_keyword is not None)
+        else FunctionCall(query_analysis, (query,), {})
     )
 
     functions_to_run = [
@@ -143,11 +147,12 @@ def retrieval_preprocessing(
 
     # The extracted keywords right now are not very reliable, not using for now
     # Can maybe use for highlighting
-    is_keyword, extracted_keywords = (
-        parallel_results[run_query_analysis.result_id]
-        if run_query_analysis
-        else (False, None)
-    )
+    is_keyword, _extracted_keywords = False, None
+    if search_request.precomputed_is_keyword is not None:
+        is_keyword = search_request.precomputed_is_keyword
+        _extracted_keywords = search_request.precomputed_keywords
+    elif run_query_analysis:
+        is_keyword, _extracted_keywords = parallel_results[run_query_analysis.result_id]
 
     all_query_terms = query.split()
     processed_keywords = (
@@ -247,4 +252,5 @@ def retrieval_preprocessing(
         chunks_above=chunks_above,
         chunks_below=chunks_below,
         full_doc=search_request.full_doc,
+        precomputed_query_embedding=search_request.precomputed_query_embedding,
     )

backend/onyx/context/search/retrieval/search_runner.py

@@ -31,7 +31,7 @@ from onyx.utils.timing import log_function_time
 from shared_configs.configs import MODEL_SERVER_HOST
 from shared_configs.configs import MODEL_SERVER_PORT
 from shared_configs.enums import EmbedTextType
-
+from shared_configs.model_server_models import Embedding
 
 logger = setup_logger()
 
@@ -109,6 +109,20 @@ def combine_retrieval_results(
     return sorted_chunks
 
 
+def get_query_embedding(query: str, db_session: Session) -> Embedding:
+    search_settings = get_current_search_settings(db_session)
+
+    model = EmbeddingModel.from_db_model(
+        search_settings=search_settings,
+        # The below are globally set, this flow always uses the indexing one
+        server_host=MODEL_SERVER_HOST,
+        server_port=MODEL_SERVER_PORT,
+    )
+
+    query_embedding = model.encode([query], text_type=EmbedTextType.QUERY)[0]
+    return query_embedding
+
+
 @log_function_time(print_only=True)
 def doc_index_retrieval(
     query: SearchQuery,
@@ -121,17 +135,10 @@ def doc_index_retrieval(
     from the large chunks to the referenced chunks,
     dedupes the chunks, and cleans the chunks.
     """
-    search_settings = get_current_search_settings(db_session)
-
-    model = EmbeddingModel.from_db_model(
-        search_settings=search_settings,
-        # The below are globally set, this flow always uses the indexing one
-        server_host=MODEL_SERVER_HOST,
-        server_port=MODEL_SERVER_PORT,
+    query_embedding = query.precomputed_query_embedding or get_query_embedding(
+        query.query, db_session
     )
 
-    query_embedding = model.encode([query.query], text_type=EmbedTextType.QUERY)[0]
-
     top_chunks = document_index.hybrid_retrieval(
         query=query.query,
         query_embedding=query_embedding,
@@ -250,6 +257,9 @@ def retrieve_chunks(
             simplified_queries.add(simplified_rephrase)
 
             q_copy = query.copy(update={"query": rephrase}, deep=True)
+            q_copy.precomputed_query_embedding = (
+                None  # need to recompute for each rephrase
+            )
             run_queries.append(
                 (
                     doc_index_retrieval,

backend/onyx/indexing/indexing_pipeline.py

@@ -464,12 +464,29 @@ def index_doc_batch(
             ),
         )
 
-        successful_doc_ids = {record.document_id for record in insertion_records}
-        if successful_doc_ids != set(updatable_ids):
+        all_returned_doc_ids = (
+            {record.document_id for record in insertion_records}
+            .union(
+                {
+                    record.failed_document.document_id
+                    for record in vector_db_write_failures
+                    if record.failed_document
+                }
+            )
+            .union(
+                {
+                    record.failed_document.document_id
+                    for record in embedding_failures
+                    if record.failed_document
+                }
+            )
+        )
+        if all_returned_doc_ids != set(updatable_ids):
             raise RuntimeError(
                 f"Some documents were not successfully indexed. "
                 f"Updatable IDs: {updatable_ids}, "
-                f"Successful IDs: {successful_doc_ids}"
+                f"Returned IDs: {all_returned_doc_ids}. "
+                "This should never happen."
             )
 
         last_modified_ids = []

backend/onyx/main.py

@@ -51,6 +51,7 @@ from onyx.server.documents.cc_pair import router as cc_pair_router
 from onyx.server.documents.connector import router as connector_router
 from onyx.server.documents.credential import router as credential_router
 from onyx.server.documents.document import router as document_router
+from onyx.server.documents.standard_oauth import router as standard_oauth_router
 from onyx.server.features.document_set.api import router as document_set_router
 from onyx.server.features.folder.api import router as folder_router
 from onyx.server.features.input_prompt.api import (
@@ -322,6 +323,7 @@ def get_application() -> FastAPI:
     )
     include_router_with_global_prefix_prepended(application, long_term_logs_router)
     include_router_with_global_prefix_prepended(application, api_key_router)
+    include_router_with_global_prefix_prepended(application, standard_oauth_router)
 
     if AUTH_TYPE == AuthType.DISABLED:
         # Server logs this during auth setup verification step

backend/onyx/tools/models.py

@@ -9,6 +9,7 @@ from sqlalchemy.orm import Session
 from onyx.context.search.enums import SearchType
 from onyx.context.search.models import IndexFilters
 from onyx.context.search.models import InferenceSection
+from shared_configs.model_server_models import Embedding
 
 
 class ToolResponse(BaseModel):
@@ -60,11 +61,15 @@ class SearchQueryInfo(BaseModel):
     recency_bias_multiplier: float
 
 
+# None indicates that the default value should be used
 class SearchToolOverrideKwargs(BaseModel):
-    force_no_rerank: bool
-    alternate_db_session: Session | None
-    retrieved_sections_callback: Callable[[list[InferenceSection]], None] | None
-    skip_query_analysis: bool
+    force_no_rerank: bool | None = None
+    alternate_db_session: Session | None = None
+    retrieved_sections_callback: Callable[[list[InferenceSection]], None] | None = None
+    skip_query_analysis: bool | None = None
+    precomputed_query_embedding: Embedding | None = None
+    precomputed_is_keyword: bool | None = None
+    precomputed_keywords: list[str] | None = None
 
     class Config:
         arbitrary_types_allowed = True

backend/onyx/tools/tool_implementations/search/search_tool.py

@@ -3,6 +3,7 @@ from collections.abc import Callable
 from collections.abc import Generator
 from typing import Any
 from typing import cast
+from typing import TypeVar
 
 from sqlalchemy.orm import Session
 
@@ -11,7 +12,6 @@ from onyx.chat.models import AnswerStyleConfig
 from onyx.chat.models import ContextualPruningConfig
 from onyx.chat.models import DocumentPruningConfig
 from onyx.chat.models import LlmDoc
-from onyx.chat.models import OnyxContext
 from onyx.chat.models import OnyxContexts
 from onyx.chat.models import PromptConfig
 from onyx.chat.models import SectionRelevancePiece
@@ -42,6 +42,9 @@ from onyx.tools.models import SearchQueryInfo
 from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.models import ToolResponse
 from onyx.tools.tool import Tool
+from onyx.tools.tool_implementations.search.search_utils import (
+    context_from_inference_section,
+)
 from onyx.tools.tool_implementations.search.search_utils import llm_doc_to_dict
 from onyx.tools.tool_implementations.search_like_tool_utils import (
     build_next_prompt_for_search_like_tool,
@@ -281,16 +284,23 @@ class SearchTool(Tool[SearchToolOverrideKwargs]):
         self, override_kwargs: SearchToolOverrideKwargs | None = None, **llm_kwargs: Any
     ) -> Generator[ToolResponse, None, None]:
         query = cast(str, llm_kwargs[QUERY_FIELD])
+        precomputed_query_embedding = None
+        precomputed_is_keyword = None
+        precomputed_keywords = None
         force_no_rerank = False
         alternate_db_session = None
         retrieved_sections_callback = None
         skip_query_analysis = False
         if override_kwargs:
-            force_no_rerank = override_kwargs.force_no_rerank
+            force_no_rerank = use_alt_not_None(override_kwargs.force_no_rerank, False)
             alternate_db_session = override_kwargs.alternate_db_session
             retrieved_sections_callback = override_kwargs.retrieved_sections_callback
-            skip_query_analysis = override_kwargs.skip_query_analysis
-
+            skip_query_analysis = use_alt_not_None(
+                override_kwargs.skip_query_analysis, False
+            )
+            precomputed_query_embedding = override_kwargs.precomputed_query_embedding
+            precomputed_is_keyword = override_kwargs.precomputed_is_keyword
+            precomputed_keywords = override_kwargs.precomputed_keywords
         if self.selected_sections:
             yield from self._build_response_for_specified_sections(query)
             return
@@ -327,6 +337,9 @@ class SearchTool(Tool[SearchToolOverrideKwargs]):
                     if self.retrieval_options
                     else None
                 ),
+                precomputed_query_embedding=precomputed_query_embedding,
+                precomputed_is_keyword=precomputed_is_keyword,
+                precomputed_keywords=precomputed_keywords,
             ),
             user=self.user,
             llm=self.llm,
@@ -345,8 +358,9 @@ class SearchTool(Tool[SearchToolOverrideKwargs]):
         )
         yield from yield_search_responses(
             query,
-            search_pipeline.reranked_sections,
-            search_pipeline.final_context_sections,
+            lambda: search_pipeline.retrieved_sections,
+            lambda: search_pipeline.reranked_sections,
+            lambda: search_pipeline.final_context_sections,
             search_query_info,
             lambda: search_pipeline.section_relevance,
             self,
@@ -383,10 +397,16 @@ class SearchTool(Tool[SearchToolOverrideKwargs]):
 # SearchTool passed in to allow for access to SearchTool properties.
 # We can't just call SearchTool methods in the graph because we're operating on
 # the retrieved docs (reranking, deduping, etc.) after the SearchTool has run.
+#
+# The various inference sections are passed in as functions to allow for lazy
+# evaluation. The SearchPipeline object properties that they correspond to are
+# actually functions defined with @property decorators, and passing them into
+# this function causes them to get evaluated immediately which is undesirable.
 def yield_search_responses(
     query: str,
-    reranked_sections: list[InferenceSection],
-    final_context_sections: list[InferenceSection],
+    get_retrieved_sections: Callable[[], list[InferenceSection]],
+    get_reranked_sections: Callable[[], list[InferenceSection]],
+    get_final_context_sections: Callable[[], list[InferenceSection]],
     search_query_info: SearchQueryInfo,
     get_section_relevance: Callable[[], list[SectionRelevancePiece] | None],
     search_tool: SearchTool,
@@ -395,7 +415,7 @@ def yield_search_responses(
         id=SEARCH_RESPONSE_SUMMARY_ID,
         response=SearchResponseSummary(
             rephrased_query=query,
-            top_sections=final_context_sections,
+            top_sections=get_retrieved_sections(),
             predicted_flow=QueryFlow.QUESTION_ANSWER,
             predicted_search=search_query_info.predicted_search,
             final_filters=search_query_info.final_filters,
@@ -407,13 +427,8 @@ def yield_search_responses(
         id=SEARCH_DOC_CONTENT_ID,
         response=OnyxContexts(
             contexts=[
-                OnyxContext(
-                    content=section.combined_content,
-                    document_id=section.center_chunk.document_id,
-                    semantic_identifier=section.center_chunk.semantic_identifier,
-                    blurb=section.center_chunk.blurb,
-                )
-                for section in reranked_sections
+                context_from_inference_section(section)
+                for section in get_reranked_sections()
             ]
         ),
     )
@@ -424,6 +439,7 @@ def yield_search_responses(
         response=section_relevance,
     )
 
+    final_context_sections = get_final_context_sections()
     pruned_sections = prune_sections(
         sections=final_context_sections,
         section_relevance_list=section_relevance_list_impl(
@@ -438,3 +454,10 @@ def yield_search_responses(
     llm_docs = [llm_doc_from_inference_section(section) for section in pruned_sections]
 
     yield ToolResponse(id=FINAL_CONTEXT_DOCUMENTS_ID, response=llm_docs)
+
+
+T = TypeVar("T")
+
+
+def use_alt_not_None(value: T | None, alt: T) -> T:
+    return value if value is not None else alt

backend/onyx/tools/tool_implementations/search/search_utils.py

@@ -1,4 +1,5 @@
 from onyx.chat.models import LlmDoc
+from onyx.chat.models import OnyxContext
 from onyx.context.search.models import InferenceSection
 from onyx.prompts.prompt_utils import clean_up_source
 
@@ -29,3 +30,12 @@ def section_to_dict(section: InferenceSection, section_num: int) -> dict:
             "%B %d, %Y %H:%M"
         )
     return doc_dict
+
+
+def context_from_inference_section(section: InferenceSection) -> OnyxContext:
+    return OnyxContext(
+        content=section.combined_content,
+        document_id=section.center_chunk.document_id,
+        semantic_identifier=section.center_chunk.semantic_identifier,
+        blurb=section.center_chunk.blurb,
+    )

backend/onyx/tools/tool_runner.py

@@ -1,6 +1,8 @@
 from collections.abc import Callable
 from collections.abc import Generator
 from typing import Any
+from typing import Generic
+from typing import TypeVar
 
 from onyx.llm.interfaces import LLM
 from onyx.llm.models import PreviousMessage
@@ -11,10 +13,16 @@ from onyx.tools.tool import Tool
 from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
 
 
-class ToolRunner:
-    def __init__(self, tool: Tool, args: dict[str, Any]):
+R = TypeVar("R")
+
+
+class ToolRunner(Generic[R]):
+    def __init__(
+        self, tool: Tool[R], args: dict[str, Any], override_kwargs: R | None = None
+    ):
         self.tool = tool
         self.args = args
+        self.override_kwargs = override_kwargs
 
         self._tool_responses: list[ToolResponse] | None = None
 
@@ -27,7 +35,9 @@ class ToolRunner:
             return
 
         tool_responses: list[ToolResponse] = []
-        for tool_response in self.tool.run(**self.args):
+        for tool_response in self.tool.run(
+            override_kwargs=self.override_kwargs, **self.args
+        ):
             yield tool_response
             tool_responses.append(tool_response)
 

backend/onyx/utils/threadpool_concurrency.py

@@ -118,7 +118,7 @@ def run_functions_in_parallel(
     return results
 
 
-class TimeoutThread(threading.Thread):
+class TimeoutThread(threading.Thread, Generic[R]):
     def __init__(
         self, timeout: float, func: Callable[..., R], *args: Any, **kwargs: Any
     ):
@@ -159,3 +159,34 @@ def run_with_timeout(
         task.end()
 
     return task.result
+
+
+# NOTE: this function should really only be used when run_functions_tuples_in_parallel is
+# difficult to use. It's up to the programmer to call wait_on_background on the thread after
+# the code you want to run in parallel is finished. As with all python thread parallelism,
+# this is only useful for I/O bound tasks.
+def run_in_background(
+    func: Callable[..., R], *args: Any, **kwargs: Any
+) -> TimeoutThread[R]:
+    """
+    Runs a function in a background thread. Returns a TimeoutThread object that can be used
+    to wait for the function to finish with wait_on_background.
+    """
+    context = contextvars.copy_context()
+    # Timeout not used in the non-blocking case
+    task = TimeoutThread(-1, context.run, func, *args, **kwargs)
+    task.start()
+    return task
+
+
+def wait_on_background(task: TimeoutThread[R]) -> R:
+    """
+    Used in conjunction with run_in_background. blocks until the task is finished,
+    then returns the result of the task.
+    """
+    task.join()
+
+    if task.exception is not None:
+        raise task.exception
+
+    return task.result

backend/tests/daily/connectors/confluence/test_confluence_basic.py

@@ -45,55 +45,43 @@ def test_confluence_connector_basic(
     with pytest.raises(StopIteration):
         next(doc_batch_generator)
 
-    assert len(doc_batch) == 3
+    assert len(doc_batch) == 2
 
     page_within_a_page_doc: Document | None = None
     page_doc: Document | None = None
-    txt_doc: Document | None = None
 
     for doc in doc_batch:
         if doc.semantic_identifier == "DailyConnectorTestSpace Home":
             page_doc = doc
-        elif ".txt" in doc.semantic_identifier:
-            txt_doc = doc
         elif doc.semantic_identifier == "Page Within A Page":
             page_within_a_page_doc = doc
 
     assert page_within_a_page_doc is not None
     assert page_within_a_page_doc.semantic_identifier == "Page Within A Page"
     assert page_within_a_page_doc.primary_owners
-    assert page_within_a_page_doc.primary_owners[0].email == "hagen@danswer.ai"
+    # Updated to check for display_name instead of email
+    assert page_within_a_page_doc.primary_owners[0].display_name == "Hagen O'Neill"
+    assert page_within_a_page_doc.primary_owners[0].email is None
     assert len(page_within_a_page_doc.sections) == 1
 
     page_within_a_page_section = page_within_a_page_doc.sections[0]
     page_within_a_page_text = "@Chris Weaver loves cherry pie"
     assert page_within_a_page_section.text == page_within_a_page_text
+    # Updated link assertion
     assert (
-        page_within_a_page_section.link
-        == "https://danswerai.atlassian.net/wiki/spaces/DailyConne/pages/200769540/Page+Within+A+Page"
+        page_within_a_page_section.link.endswith(
+            "/wiki/spaces/DailyConne/pages/200769540/Page+Within+A+Page"
+        )
     )
 
     assert page_doc is not None
     assert page_doc.semantic_identifier == "DailyConnectorTestSpace Home"
     assert page_doc.metadata["labels"] == ["testlabel"]
     assert page_doc.primary_owners
-    assert page_doc.primary_owners[0].email == "hagen@danswer.ai"
-    assert len(page_doc.sections) == 1
+    assert page_doc.primary_owners[0].display_name == "Hagen O'Neill"
+    assert page_doc.primary_owners[0].email is None
+    assert len(page_doc.sections) == 2
 
     page_section = page_doc.sections[0]
     assert page_section.text == "test123 " + page_within_a_page_text
-    assert (
-        page_section.link
-        == "https://danswerai.atlassian.net/wiki/spaces/DailyConne/overview"
-    )
-
-    assert txt_doc is not None
-    assert txt_doc.semantic_identifier == "small-file.txt"
-    assert len(txt_doc.sections) == 1
-    assert txt_doc.sections[0].text == "small"
-    assert txt_doc.primary_owners
-    assert txt_doc.primary_owners[0].email == "chris@onyx.app"
-    assert (
-        txt_doc.sections[0].link
-        == "https://danswerai.atlassian.net/wiki/pages/viewpageattachments.action?pageId=52494430&preview=%2F52494430%2F52527123%2Fsmall-file.txt"
-    )
+    assert page_section.link.endswith("/wiki/spaces/DailyConne/overview")

backend/tests/daily/connectors/confluence/test_confluence_permissions_basic.py

@@ -41,5 +41,9 @@ def test_confluence_connector_permissions(
     for slim_doc_batch in confluence_connector.retrieve_all_slim_documents():
         all_slim_doc_ids.update([doc.id for doc in slim_doc_batch])
 
+    # Find IDs that are in full but not in slim
+    difference = all_full_doc_ids - all_slim_doc_ids
+
     # The set of full doc IDs should be always be a subset of the slim doc IDs
-    assert all_full_doc_ids.issubset(all_slim_doc_ids)
+    assert all_full_doc_ids.issubset(all_slim_doc_ids), \
+        f"Full doc IDs are not a subset of slim doc IDs. Found {len(difference)} IDs in full docs but not in slim docs."

backend/tests/unit/onyx/utils/test_threadpool_concurrency.py

@@ -1,8 +1,14 @@
+import contextvars
 import time
 
 import pytest
 
+from onyx.utils.threadpool_concurrency import run_in_background
 from onyx.utils.threadpool_concurrency import run_with_timeout
+from onyx.utils.threadpool_concurrency import wait_on_background
+
+# Create a context variable for testing
+test_context_var = contextvars.ContextVar("test_var", default="default")
 
 
 def test_run_with_timeout_completes() -> None:
@@ -59,3 +65,86 @@ def test_run_with_timeout_with_args_and_kwargs() -> None:
     # Test with positional and keyword args
     result2 = run_with_timeout(1.0, complex_function, x=5, y=3, multiply=True)
     assert result2 == 15
+
+
+def test_run_in_background_and_wait_success() -> None:
+    """Test that run_in_background and wait_on_background work correctly for successful execution"""
+
+    def background_function(x: int) -> int:
+        time.sleep(0.1)  # Small delay to ensure it's actually running in background
+        return x * 2
+
+    # Start the background task
+    task = run_in_background(background_function, 21)
+
+    # Verify we can do other work while task is running
+    start_time = time.time()
+    result = wait_on_background(task)
+    elapsed = time.time() - start_time
+
+    assert result == 42
+    assert elapsed >= 0.1  # Verify we actually waited for the sleep
+
+
+@pytest.mark.filterwarnings("ignore::pytest.PytestUnhandledThreadExceptionWarning")
+def test_run_in_background_propagates_exceptions() -> None:
+    """Test that exceptions in background tasks are properly propagated"""
+
+    def error_function() -> None:
+        time.sleep(0.1)  # Small delay to ensure it's actually running in background
+        raise ValueError("Test background error")
+
+    task = run_in_background(error_function)
+
+    with pytest.raises(ValueError) as exc_info:
+        wait_on_background(task)
+
+    assert "Test background error" in str(exc_info.value)
+
+
+def test_run_in_background_with_args_and_kwargs() -> None:
+    """Test that args and kwargs are properly passed to the background function"""
+
+    def complex_function(x: int, y: int, multiply: bool = False) -> int:
+        time.sleep(0.1)  # Small delay to ensure it's actually running in background
+        if multiply:
+            return x * y
+        return x + y
+
+    # Test with args
+    task1 = run_in_background(complex_function, 5, 3)
+    result1 = wait_on_background(task1)
+    assert result1 == 8
+
+    # Test with args and kwargs
+    task2 = run_in_background(complex_function, 5, 3, multiply=True)
+    result2 = wait_on_background(task2)
+    assert result2 == 15
+
+
+def test_multiple_background_tasks() -> None:
+    """Test running multiple background tasks concurrently"""
+
+    def slow_add(x: int, y: int) -> int:
+        time.sleep(0.2)  # Make each task take some time
+        return x + y
+
+    # Start multiple tasks
+    start_time = time.time()
+    task1 = run_in_background(slow_add, 1, 2)
+    task2 = run_in_background(slow_add, 3, 4)
+    task3 = run_in_background(slow_add, 5, 6)
+
+    # Wait for all results
+    result1 = wait_on_background(task1)
+    result2 = wait_on_background(task2)
+    result3 = wait_on_background(task3)
+    elapsed = time.time() - start_time
+
+    # Verify results
+    assert result1 == 3
+    assert result2 == 7
+    assert result3 == 11
+
+    # Verify tasks ran in parallel (total time should be ~0.2s, not ~0.6s)
+    assert 0.2 <= elapsed < 0.4  # Allow some buffer for test environment variations

backend/tests/unit/onyx/utils/test_threadpool_contextvars.py

@@ -4,7 +4,9 @@ import time
 from onyx.utils.threadpool_concurrency import FunctionCall
 from onyx.utils.threadpool_concurrency import run_functions_in_parallel
 from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
+from onyx.utils.threadpool_concurrency import run_in_background
 from onyx.utils.threadpool_concurrency import run_with_timeout
+from onyx.utils.threadpool_concurrency import wait_on_background
 
 # Create a test contextvar
 test_var = contextvars.ContextVar("test_var", default="default")
@@ -129,3 +131,39 @@ def test_contextvar_isolation_between_runs() -> None:
 
     # Verify second run results
     assert all(result in ["thread3", "thread4"] for result in second_results)
+
+
+def test_run_in_background_preserves_contextvar() -> None:
+    """Test that run_in_background preserves contextvar values and modifications are isolated"""
+
+    def modify_and_sleep() -> tuple[str, str]:
+        """Modifies contextvar, sleeps, and returns original, modified, and final values"""
+        original = test_var.get()
+        test_var.set("modified_in_background")
+        time.sleep(0.1)  # Ensure we can check main thread during execution
+        final = test_var.get()
+        return original, final
+
+    # Set initial value in main thread
+    token = test_var.set("initial_value")
+    try:
+        # Start background task
+        task = run_in_background(modify_and_sleep)
+
+        # Verify main thread value remains unchanged while task runs
+        assert test_var.get() == "initial_value"
+
+        # Get results from background thread
+        original, modified = wait_on_background(task)
+
+        # Verify the background thread:
+        # 1. Saw the initial value
+        assert original == "initial_value"
+        # 2. Successfully modified its own copy
+        assert modified == "modified_in_background"
+
+        # Verify main thread value is still unchanged after task completion
+        assert test_var.get() == "initial_value"
+    finally:
+        # Clean up
+        test_var.reset(token)

deployment/README.md

@@ -80,3 +80,13 @@ prod cluster**
    - `kubectl delete -f .`
    - To not delete the persistent volumes (Document indexes and Users), specify the specific `.yaml` files instead of
      `.` without specifying delete on persistent-volumes.yaml.
+
+### Using Helm to deploy to an existing cluster
+
+Onyx has a helm chart that is convenient to install all services to an existing Kubernetes cluster. To install:
+
+* Currently the helm chart is not published so to install, clone the repo.
+* Configure access to the cluster via kubectl. Ensure the kubectl context is set to the cluster that you want to use
+* The default secrets, environment variables and other service level configuration are stored in `deployment/helm/charts/onyx/values.yml`. You may create another `override.yml`
+* `cd deployment/helm/charts/onyx` and run `helm install onyx -n onyx -f override.yaml .`. This will install onyx on the cluster under the `onyx` namespace.
+* Check the status of the deploy using `kubectl get pods -n onyx`

deployment/helm/charts/onyx/templates/ingress-api.yaml

@@ -0,0 +1,27 @@
+{{- if .Values.ingress.enabled -}}
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  name: {{ include "onyx-stack.fullname" . }}-ingress-api
+  annotations:
+    kubernetes.io/ingress.class: nginx
+    nginx.ingress.kubernetes.io/rewrite-target: /$2
+    nginx.ingress.kubernetes.io/use-regex: "true"
+    cert-manager.io/cluster-issuer: {{ include "onyx-stack.fullname" . }}-letsencrypt
+spec:
+  rules:
+    - host: {{ .Values.ingress.api.host }}
+      http:
+        paths:
+          - path: /api(/|$)(.*)
+            pathType: Prefix
+            backend:
+              service:
+                name: {{ include "onyx-stack.fullname" . }}-api-service
+                port:
+                  number: {{ .Values.api.service.servicePort }}
+  tls:
+    - hosts:
+        - {{ .Values.ingress.api.host }}
+      secretName: {{ include "onyx-stack.fullname" . }}-ingress-api-tls
+{{- end }}

deployment/helm/charts/onyx/templates/ingress-webserver.yaml

@@ -0,0 +1,26 @@
+{{- if .Values.ingress.enabled -}}
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  name: {{ include "onyx-stack.fullname" . }}-ingress-webserver
+  annotations:
+    kubernetes.io/ingress.class: nginx
+    cert-manager.io/cluster-issuer: {{ include "onyx-stack.fullname" . }}-letsencrypt
+    kubernetes.io/tls-acme: "true"
+spec:
+  rules:
+    - host: {{ .Values.ingress.webserver.host }}
+      http:
+        paths:
+          - path: /
+            pathType: Prefix
+            backend:
+              service:
+                name: {{ include "onyx-stack.fullname" . }}-webserver
+                port:
+                  number: {{ .Values.webserver.service.servicePort }}
+  tls:
+    - hosts:
+        - {{ .Values.ingress.webserver.host }}
+      secretName: {{ include "onyx-stack.fullname" . }}-ingress-webserver-tls
+{{- end }}

deployment/helm/charts/onyx/templates/lets-encrypt.yaml

@@ -0,0 +1,20 @@
+{{- if .Values.letsencrypt.enabled -}}
+apiVersion: cert-manager.io/v1
+kind: ClusterIssuer
+metadata:
+  name: {{ include "onyx-stack.fullname" . }}-letsencrypt
+spec:
+  acme:
+    # The ACME server URL
+    server: https://acme-v02.api.letsencrypt.org/directory
+    # Email address used for ACME registration
+    email: {{ .Values.letsencrypt.email }}
+    # Name of a secret used to store the ACME account private key
+    privateKeySecretRef:
+      name: {{ include "onyx-stack.fullname" . }}-letsencrypt
+    # Enable the HTTP-01 challenge provider
+    solvers:
+      - http01:
+          ingress:
+            class: nginx
+{{- end }}

deployment/helm/charts/onyx/values.yaml

@@ -376,22 +376,17 @@ redis:
     existingSecret: onyx-secrets
     existingSecretPasswordKey: redis_password
 
-# ingress:
-#  enabled: false
-#  className: ""
-#  annotations: {}
-#    # kubernetes.io/ingress.class: nginx
-#    # kubernetes.io/tls-acme: "true"
-#  hosts:
-#    - host: chart-example.local
-#      paths:
-#        - path: /
-#          pathType: ImplementationSpecific
-#  tls: []
-#  #  - secretName: chart-example-tls
-#  #    hosts:
-#  #      - chart-example.local
+ingress:
+  enabled: false
+  className: ""
+  api:
+    host: onyx.local
+  webserver:
+    host: onyx.local
 
+letsencrypt:
+  enabled: false
+  email: "abc@abc.com"
 
 auth:
   # existingSecret onyx-secret for storing smtp, oauth, slack, and other secrets

web/src/app/admin/configuration/llm/interfaces.ts

@@ -1,17 +1,14 @@
 import {
   AnthropicIcon,
   AmazonIcon,
-  AWSIcon,
-  AzureIcon,
   CPUIcon,
   MicrosoftIconSVG,
   MistralIcon,
   MetaIcon,
   GeminiIcon,
-  AnthropicSVG,
   IconProps,
-  OpenAIISVG,
   DeepseekIcon,
+  OpenAISVG,
 } from "@/components/icons/icons";
 
 export interface CustomConfigKey {
@@ -74,7 +71,7 @@ export interface LLMProviderDescriptor {
 }
 
 export const getProviderIcon = (providerName: string, modelName?: string) => {
-  const modelIconMap: Record<
+  const iconMap: Record<
     string,
     ({ size, className }: IconProps) => JSX.Element
   > = {
@@ -86,34 +83,30 @@ export const getProviderIcon = (providerName: string, modelName?: string) => {
     gemini: GeminiIcon,
     deepseek: DeepseekIcon,
     claude: AnthropicIcon,
+    anthropic: AnthropicIcon,
+    openai: OpenAISVG,
+    microsoft: MicrosoftIconSVG,
+    meta: MetaIcon,
+    google: GeminiIcon,
   };
 
-  const modelNameToIcon = (
-    modelName: string,
-    fallbackIcon: ({ size, className }: IconProps) => JSX.Element
-  ): (({ size, className }: IconProps) => JSX.Element) => {
-    const lowerModelName = modelName?.toLowerCase();
-    for (const [key, icon] of Object.entries(modelIconMap)) {
-      if (lowerModelName?.includes(key)) {
+  // First check if provider name directly matches an icon
+  if (providerName.toLowerCase() in iconMap) {
+    return iconMap[providerName.toLowerCase()];
+  }
+
+  // Then check if model name contains any of the keys
+  if (modelName) {
+    const lowerModelName = modelName.toLowerCase();
+    for (const [key, icon] of Object.entries(iconMap)) {
+      if (lowerModelName.includes(key)) {
         return icon;
       }
     }
-    return fallbackIcon;
-  };
-
-  switch (providerName) {
-    case "openai":
-      // Special cases for openai based on modelName
-      return modelNameToIcon(modelName || "", OpenAIISVG);
-    case "anthropic":
-      return AnthropicSVG;
-    case "bedrock":
-      return AWSIcon;
-    case "azure":
-      return AzureIcon;
-    default:
-      return modelNameToIcon(modelName || "", CPUIcon);
   }
+
+  // Fallback to CPU icon if no matches
+  return CPUIcon;
 };
 
 export const isAnthropic = (provider: string, modelName: string) =>

web/src/app/admin/indexing/status/FilterComponent.tsx

@@ -185,7 +185,10 @@ export const FilterComponent = forwardRef<
               hasActiveFilters ? "border-primary bg-primary/5" : ""
             }`}
           >
-            <SortIcon size={20} className="text-neutral-800" />
+            <SortIcon
+              size={20}
+              className="text-neutral-800 dark:text-neutral-200"
+            />
           </Button>
         </DropdownMenuTrigger>
         <DropdownMenuContent
@@ -365,7 +368,7 @@ export const FilterComponent = forwardRef<
 
       {hasActiveFilters && (
         <div className="absolute -top-1 -right-1">
-          <Badge className="h-2 bg-red-400 border-red-400 w-2 p-0 border-2 flex items-center justify-center" />
+          <Badge className="h-2 !bg-red-400 !border-red-400 w-2 p-0 border-2 flex items-center justify-center" />
         </div>
       )}
     </div>

web/src/app/admin/settings/SettingsForm.tsx

@@ -290,21 +290,24 @@ export function SettingsForm() {
             id="chatRetentionInput"
             placeholder="Infinite Retention"
           />
-          <Button
-            onClick={handleSetChatRetention}
-            variant="submit"
-            size="sm"
-            className="mr-3"
-          >
-            Set Retention Limit
-          </Button>
-          <Button
-            onClick={handleClearChatRetention}
-            variant="default"
-            size="sm"
-          >
-            Retain All
-          </Button>
+          <div className="mr-auto flex gap-2">
+            <Button
+              onClick={handleSetChatRetention}
+              variant="submit"
+              size="sm"
+              className="mr-auto"
+            >
+              Set Retention Limit
+            </Button>
+            <Button
+              onClick={handleClearChatRetention}
+              variant="default"
+              size="sm"
+              className="mr-auto"
+            >
+              Retain All
+            </Button>
+          </div>
         </>
       )}
 

web/src/app/auth/login/EmailPasswordForm.tsx

@@ -61,6 +61,7 @@ export function EmailPasswordForm({
 
             if (!response.ok) {
               setIsWorking(false);
+
               const errorDetail = (await response.json()).detail;
               let errorMsg = "Unknown error";
               if (typeof errorDetail === "object" && errorDetail.reason) {
@@ -96,12 +97,13 @@ export function EmailPasswordForm({
           } else {
             setIsWorking(false);
             const errorDetail = (await loginResponse.json()).detail;
-
             let errorMsg = "Unknown error";
             if (errorDetail === "LOGIN_BAD_CREDENTIALS") {
               errorMsg = "Invalid email or password";
             } else if (errorDetail === "NO_WEB_LOGIN_AND_HAS_NO_PASSWORD") {
               errorMsg = "Create an account to set a password";
+            } else if (typeof errorDetail === "string") {
+              errorMsg = errorDetail;
             }
             if (loginResponse.status === 429) {
               errorMsg = "Too many requests. Please try again later.";

web/src/app/chat/folders/FolderDropdown.tsx

@@ -191,6 +191,7 @@ export const FolderDropdown = forwardRef<HTMLDivElement, FolderDropdownProps>(
                     onChange={(e) => setNewFolderName(e.target.value)}
                     className="text-sm font-medium bg-transparent outline-none w-full pb-1 border-b border-background-500 transition-colors duration-200"
                     onKeyDown={(e) => {
+                      e.stopPropagation();
                       if (e.key === "Enter") {
                         handleEdit();
                       }

web/src/app/chat/folders/FolderList.tsx

@@ -303,7 +303,6 @@ const FolderItem = ({
               key={chatSession.id}
               chatSession={chatSession}
               isSelected={chatSession.id === currentChatId}
-              skipGradient={isDragOver}
               showShareModal={showShareModal}
               showDeleteModal={showDeleteModal}
             />

web/src/app/chat/sessionSidebar/ChatSessionDisplay.tsx

@@ -32,21 +32,17 @@ export function ChatSessionDisplay({
   chatSession,
   search,
   isSelected,
-  skipGradient,
   closeSidebar,
   showShareModal,
   showDeleteModal,
-  foldersExisting,
   isDragging,
 }: {
   chatSession: ChatSession;
   isSelected: boolean;
   search?: boolean;
-  skipGradient?: boolean;
   closeSidebar?: () => void;
   showShareModal?: (chatSession: ChatSession) => void;
   showDeleteModal?: (chatSession: ChatSession) => void;
-  foldersExisting?: boolean;
   isDragging?: boolean;
 }) {
   const router = useRouter();
@@ -238,8 +234,12 @@ export function ChatSessionDisplay({
                           e.preventDefault();
                           e.stopPropagation();
                         }}
-                        onChange={(e) => setChatName(e.target.value)}
+                        onChange={(e) => {
+                          setChatName(e.target.value);
+                        }}
                         onKeyDown={(event) => {
+                          event.stopPropagation();
+
                           if (event.key === "Enter") {
                             onRename();
                             event.preventDefault();

web/src/app/chat/sessionSidebar/PagesTab.tsx

@@ -264,7 +264,6 @@ export function PagesTab({
         >
           <ChatSessionDisplay
             chatSession={chat}
-            foldersExisting={foldersExisting}
             isSelected={currentChatId === chat.id}
             showShareModal={showShareModal}
             showDeleteModal={showDeleteModal}

web/src/components/admin/connectors/ConnectorTitle.tsx

@@ -40,8 +40,12 @@ export const ConnectorTitle = ({
     const typedConnector = connector as Connector<GithubConfig>;
     additionalMetadata.set(
       "Repo",
-      typedConnector.connector_specific_config.repo_name
-        ? `${typedConnector.connector_specific_config.repo_owner}/${typedConnector.connector_specific_config.repo_name}`
+      typedConnector.connector_specific_config.repositories
+        ? `${typedConnector.connector_specific_config.repo_owner}/${
+            typedConnector.connector_specific_config.repositories.includes(",")
+              ? "multiple repos"
+              : typedConnector.connector_specific_config.repositories
+          }`
         : `${typedConnector.connector_specific_config.repo_owner}/*`
     );
   } else if (connector.source === "gitlab") {

web/src/components/icons/icons.tsx

@@ -3102,27 +3102,6 @@ export const OpenAISVG = ({
   );
 };
 
-export const AnthropicSVG = ({
-  size = 16,
-  className = defaultTailwindCSS,
-}: IconProps) => {
-  return (
-    <svg
-      style={{ width: `${size}px`, height: `${size}px` }}
-      className={`w-[${size}px] h-[${size}px] ` + className}
-      xmlns="http://www.w3.org/2000/svg"
-      viewBox="0 0 92.2 65"
-      xmlSpace="preserve"
-      fill="currentColor"
-    >
-      <path
-        fill="currentColor"
-        d="M66.5,0H52.4l25.7,65h14.1L66.5,0z M25.7,0L0,65h14.4l5.3-13.6h26.9L51.8,65h14.4L40.5,0C40.5,0,25.7,0,25.7,0z M24.3,39.3l8.8-22.8l8.8,22.8H24.3z"
-      />
-    </svg>
-  );
-};
-
 export const SourcesIcon = ({
   size = 16,
   className = defaultTailwindCSS,

web/src/lib/connectors/connectors.tsx

@@ -190,10 +190,12 @@ export const connectorConfigs: Record<
             fields: [
               {
                 type: "text",
-                query: "Enter the repository name:",
-                label: "Repository Name",
-                name: "repo_name",
+                query: "Enter the repository name(s):",
+                label: "Repository Name(s)",
+                name: "repositories",
                 optional: false,
+                description:
+                  "For multiple repositories, enter comma-separated names (e.g., repo1,repo2,repo3)",
               },
             ],
           },
@@ -1358,7 +1360,7 @@ export interface WebConfig {
 
 export interface GithubConfig {
   repo_owner: string;
-  repo_name: string;
+  repositories: string; // Comma-separated list of repository names
   include_prs: boolean;
   include_issues: boolean;
 }