improved basic search latency (#4186)

* improved basic search latency

* address PR comments + minor cleanup

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 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_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 @@
 # 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.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 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_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/chat/llm_response_handler.py

@@ -15,6 +15,8 @@
 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.