main nodes renaming

backend/onyx/agents/agent_search/deep_search_a/initial/consolidate_sub_answers/graph_builder.py

@@ -53,8 +53,8 @@ def consolidate_sub_answers_graph_builder() -> StateGraph:
     # raph.add_edge(start_key=START, end_key="base_raw_search_subgraph")
 
     # graph.add_edge(
-    #     start_key="agent_search_start",
-    #     end_key="entity_term_extraction_llm",
+    #     start_key="start_agent_search",
+    #     end_key="extract_entity_term",
     # )
 
     graph.add_edge(

backend/onyx/agents/agent_search/deep_search_a/main/edges.py

@@ -25,7 +25,7 @@ logger = setup_logger()
 
 def route_initial_tool_choice(
     state: MainState, config: RunnableConfig
-) -> Literal["tool_call", "agent_search_start", "logging_node"]:
+) -> Literal["tool_call", "start_agent_search", "logging_node"]:
     agent_config = cast(AgentSearchConfig, config["metadata"]["config"])
     if state.tool_choice is not None:
         if (
@@ -33,7 +33,7 @@ def route_initial_tool_choice(
             and agent_config.search_tool is not None
             and state.tool_choice.tool.name == agent_config.search_tool.name
         ):
-            return "agent_search_start"
+            return "start_agent_search"
         else:
             return "tool_call"
     else:
@@ -83,9 +83,9 @@ def parallelize_initial_sub_question_answering(
 # Define the function that determines whether to continue or not
 def continue_to_refined_answer_or_end(
     state: RequireRefinedAnswerUpdate,
-) -> Literal["refined_sub_question_creation", "logging_node"]:
+) -> Literal["create_refined_sub_questions", "logging_node"]:
     if state.require_refined_answer_eval:
-        return "refined_sub_question_creation"
+        return "create_refined_sub_questions"
     else:
         return "logging_node"
 

backend/onyx/agents/agent_search/deep_search_a/main/graph_builder.py

@@ -14,17 +14,14 @@ from onyx.agents.agent_search.deep_search_a.main.edges import (
 from onyx.agents.agent_search.deep_search_a.main.edges import (
     route_initial_tool_choice,
 )
-from onyx.agents.agent_search.deep_search_a.main.nodes.agent_logging import (
-    agent_logging,
+from onyx.agents.agent_search.deep_search_a.main.nodes.compare_answers import (
+    compare_answers,
 )
-from onyx.agents.agent_search.deep_search_a.main.nodes.agent_search_start import (
-    agent_search_start,
+from onyx.agents.agent_search.deep_search_a.main.nodes.create_refined_sub_questions import (
+    create_refined_sub_questions,
 )
-from onyx.agents.agent_search.deep_search_a.main.nodes.answer_comparison import (
-    answer_comparison,
-)
-from onyx.agents.agent_search.deep_search_a.main.nodes.entity_term_extraction_llm import (
-    entity_term_extraction_llm,
+from onyx.agents.agent_search.deep_search_a.main.nodes.extract_entity_term import (
+    extract_entity_term,
 )
 from onyx.agents.agent_search.deep_search_a.main.nodes.generate_refined_answer import (
     generate_refined_answer,
@@ -32,11 +29,14 @@ from onyx.agents.agent_search.deep_search_a.main.nodes.generate_refined_answer i
 from onyx.agents.agent_search.deep_search_a.main.nodes.ingest_refined_answers import (
     ingest_refined_answers,
 )
-from onyx.agents.agent_search.deep_search_a.main.nodes.refined_answer_decision import (
-    refined_answer_decision,
+from onyx.agents.agent_search.deep_search_a.main.nodes.persist_agent_results import (
+    persist_agent_results,
 )
-from onyx.agents.agent_search.deep_search_a.main.nodes.refined_sub_question_creation import (
-    refined_sub_question_creation,
+from onyx.agents.agent_search.deep_search_a.main.nodes.start_agent_search import (
+    start_agent_search,
+)
+from onyx.agents.agent_search.deep_search_a.main.nodes.validate_refined_answer import (
+    validate_refined_answer,
 )
 from onyx.agents.agent_search.deep_search_a.main.states import MainInput
 from onyx.agents.agent_search.deep_search_a.main.states import MainState
@@ -65,20 +65,6 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
         input=MainInput,
     )
 
-    # graph.add_node(
-    #     node="agent_path_decision",
-    #     action=agent_path_decision,
-    # )
-
-    # graph.add_node(
-    #     node="agent_path_routing",
-    #     action=agent_path_routing,
-    # )
-
-    # graph.add_node(
-    #     node="LLM",
-    #     action=direct_llm_handling,
-    # )
     graph.add_node(
         node="prepare_tool_input",
         action=prepare_tool_input,
@@ -97,42 +83,19 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
         action=basic_use_tool_response,
     )
     graph.add_node(
-        node="agent_search_start",
-        action=agent_search_start,
+        node="start_agent_search",
+        action=start_agent_search,
     )
 
-    # graph.add_node(
-    #     node="initial_sub_question_creation",
-    #     action=initial_sub_question_creation,
-    # )
-
     generate_initial_answer_subgraph = generate_initial_answer_graph_builder().compile()
     graph.add_node(
         node="generate_initial_answer_subgraph",
         action=generate_initial_answer_subgraph,
     )
 
-    # answer_query_subgraph = answer_query_graph_builder().compile()
-    # graph.add_node(
-    #     node="answer_query_subgraph",
-    #     action=answer_query_subgraph,
-    # )
-
-    # base_raw_search_subgraph = base_raw_search_graph_builder().compile()
-    # graph.add_node(
-    #     node="base_raw_search_subgraph",
-    #     action=base_raw_search_subgraph,
-    # )
-
-    # refined_answer_subgraph = refined_answers_graph_builder().compile()
-    # graph.add_node(
-    #     node="refined_answer_subgraph",
-    #     action=refined_answer_subgraph,
-    # )
-
     graph.add_node(
-        node="refined_sub_question_creation",
-        action=refined_sub_question_creation,
+        node="create_refined_sub_questions",
+        action=create_refined_sub_questions,
     )
 
     answer_refined_question = answer_refined_query_graph_builder().compile()
@@ -151,70 +114,25 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
         action=generate_refined_answer,
     )
 
-    # graph.add_node(
-    #     node="check_refined_answer",
-    #     action=check_refined_answer,
-    # )
-
-    # graph.add_node(
-    #     node="ingest_initial_retrieval",
-    #     action=ingest_initial_base_retrieval,
-    # )
-
-    # graph.add_node(
-    #     node="retrieval_consolidation",
-    #     action=retrieval_consolidation,
-    # )
-
-    # graph.add_node(
-    #     node="ingest_initial_sub_question_answers",
-    #     action=ingest_initial_sub_question_answers,
-    # )
-    # graph.add_node(
-    #     node="generate_initial_answer",
-    #     action=generate_initial_answer,
-    # )
-
-    # graph.add_node(
-    #     node="initial_answer_quality_check",
-    #     action=initial_answer_quality_check,
-    # )
-
     graph.add_node(
-        node="entity_term_extraction_llm",
-        action=entity_term_extraction_llm,
+        node="extract_entity_term",
+        action=extract_entity_term,
     )
     graph.add_node(
-        node="refined_answer_decision",
-        action=refined_answer_decision,
+        node="validate_refined_answer",
+        action=validate_refined_answer,
     )
     graph.add_node(
-        node="answer_comparison",
-        action=answer_comparison,
+        node="compare_answers",
+        action=compare_answers,
     )
     graph.add_node(
         node="logging_node",
-        action=agent_logging,
+        action=persist_agent_results,
     )
-    # if test_mode:
-    #     graph.add_node(
-    #         node="generate_initial_base_answer",
-    #         action=generate_initial_base_answer,
-    #     )
 
     ### Add edges ###
 
-    # raph.add_edge(start_key=START, end_key="base_raw_search_subgraph")
-
-    # graph.add_edge(
-    #     start_key=START,
-    #     end_key="agent_path_decision",
-    # )
-
-    # graph.add_edge(
-    #     start_key="agent_path_decision",
-    #     end_key="agent_path_routing",
-    # )
     graph.add_edge(start_key=START, end_key="prepare_tool_input")
 
     graph.add_edge(
@@ -225,7 +143,7 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
     graph.add_conditional_edges(
         "initial_tool_choice",
         route_initial_tool_choice,
-        ["tool_call", "agent_search_start", "logging_node"],
+        ["tool_call", "start_agent_search", "logging_node"],
     )
 
     graph.add_edge(
@@ -238,96 +156,38 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
     )
 
     graph.add_edge(
+<<<<<<< HEAD
         start_key="agent_search_start",
         end_key="generate_initial_answer_subgraph",
-    )
-    # graph.add_edge(
-    #     start_key="agent_search_start",
-    #     end_key="base_raw_search_subgraph",
-    # )
-
-    graph.add_edge(
-        start_key="agent_search_start",
-        end_key="entity_term_extraction_llm",
+=======
+        start_key="start_agent_search",
+        end_key="initial_search_sq_subgraph",
+>>>>>>> ab2510c4d (main nodes renaming)
     )
 
-    # graph.add_edge(
-    #     start_key="agent_search_start",
-    #     end_key="initial_sub_question_creation",
-    # )
-
-    # graph.add_edge(
-    #     start_key="base_raw_search_subgraph",
-    #     end_key="ingest_initial_retrieval",
-    # )
-
-    # graph.add_edge(
-    #     start_key=["ingest_initial_retrieval", "ingest_initial_sub_question_answers"],
-    #     end_key="retrieval_consolidation",
-    # )
-
-    # graph.add_edge(
-    #     start_key="retrieval_consolidation",
-    #     end_key="generate_initial_answer",
-    # )
-
-    # graph.add_edge(
-    #     start_key="LLM",
-    #     end_key=END,
-    # )
-
-    # graph.add_edge(
-    #     start_key=START,
-    #     end_key="initial_sub_question_creation",
-    # )
-
-    # graph.add_conditional_edges(
-    #     source="initial_sub_question_creation",
-    #     path=parallelize_initial_sub_question_answering,
-    #     path_map=["answer_query_subgraph"],
-    # )
-    # graph.add_edge(
-    #     start_key="answer_query_subgraph",
-    #     end_key="ingest_initial_sub_question_answers",
-    # )
-
-    # graph.add_edge(
-    #     start_key="retrieval_consolidation",
-    #     end_key="generate_initial_answer",
-    # )
-
-    # graph.add_edge(
-    #     start_key="generate_initial_answer",
-    #     end_key="entity_term_extraction_llm",
-    # )
-
-    # graph.add_edge(
-    #     start_key="generate_initial_answer",
-    #     end_key="initial_answer_quality_check",
-    # )
-
-    # graph.add_edge(
-    #     start_key=["initial_answer_quality_check", "entity_term_extraction_llm"],
-    #     end_key="refined_answer_decision",
-    # )
-    # graph.add_edge(
-    #     start_key="initial_answer_quality_check",
-    #     end_key="refined_answer_decision",
-    # )
+    graph.add_edge(
+        start_key="start_agent_search",
+        end_key="extract_entity_term",
+    )
 
     graph.add_edge(
+<<<<<<< HEAD
         start_key=["generate_initial_answer_subgraph", "entity_term_extraction_llm"],
         end_key="refined_answer_decision",
+=======
+        start_key=["initial_search_sq_subgraph", "extract_entity_term"],
+        end_key="validate_refined_answer",
+>>>>>>> ab2510c4d (main nodes renaming)
     )
 
     graph.add_conditional_edges(
-        source="refined_answer_decision",
+        source="validate_refined_answer",
         path=continue_to_refined_answer_or_end,
-        path_map=["refined_sub_question_creation", "logging_node"],
+        path_map=["create_refined_sub_questions", "logging_node"],
     )
 
     graph.add_conditional_edges(
-        source="refined_sub_question_creation",  # DONE
+        source="create_refined_sub_questions",  # DONE
         path=parallelize_refined_sub_question_answering,
         path_map=["answer_refined_question"],
     )
@@ -341,23 +201,12 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
         end_key="generate_refined_answer",
     )
 
-    # graph.add_conditional_edges(
-    #     source="refined_answer_decision",
-    #     path=continue_to_refined_answer_or_end,
-    #     path_map=["refined_answer_subgraph", END],
-    # )
-
-    # graph.add_edge(
-    #     start_key="refined_answer_subgraph",
-    #     end_key="generate_refined_answer",
-    # )
-
     graph.add_edge(
         start_key="generate_refined_answer",
-        end_key="answer_comparison",
+        end_key="compare_answers",
     )
     graph.add_edge(
-        start_key="answer_comparison",
+        start_key="compare_answers",
         end_key="logging_node",
     )
 
@@ -366,16 +215,6 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
         end_key=END,
     )
 
-    # graph.add_edge(
-    #     start_key="generate_refined_answer",
-    #     end_key="check_refined_answer",
-    # )
-
-    # graph.add_edge(
-    #     start_key="check_refined_answer",
-    #     end_key=END,
-    # )
-
     return graph
 
 

backend/onyx/agents/agent_search/deep_search_a/main/nodes/agent_path_decision.py

@@ -1,36 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.runnables import RunnableConfig
-
-from onyx.agents.agent_search.deep_search_a.main.operations import logger
-from onyx.agents.agent_search.deep_search_a.main.states import MainState
-from onyx.agents.agent_search.deep_search_a.main.states import RoutingDecision
-from onyx.agents.agent_search.models import AgentSearchConfig
-
-
-def agent_path_decision(state: MainState, config: RunnableConfig) -> RoutingDecision:
-    now_start = datetime.now()
-
-    cast(AgentSearchConfig, config["metadata"]["config"])
-
-    # perform_initial_search_path_decision = (
-    #    agent_a_config.perform_initial_search_path_decision
-    # )
-
-    logger.info(f"--------{now_start}--------DECIDING TO SEARCH OR GO TO LLM---")
-
-    routing = "agent_search"
-
-    now_end = datetime.now()
-
-    logger.debug(
-        f"--------{now_end}--{now_end - now_start}--------DECIDING TO SEARCH OR GO TO LLM END---"
-    )
-    return RoutingDecision(
-        # Decide which route to take
-        routing_decision=routing,
-        log_messages=[
-            f"{now_end} -- Path decision: {routing},  Time taken: {now_end - now_start}"
-        ],
-    )

backend/onyx/agents/agent_search/deep_search_a/main/nodes/agent_path_routing.py

@@ -1,31 +0,0 @@
-from datetime import datetime
-from typing import Literal
-
-from langgraph.types import Command
-
-from onyx.agents.agent_search.deep_search_a.main.states import MainState
-
-
-def agent_path_routing(
-    state: MainState,
-) -> Command[Literal["agent_search_start", "LLM"]]:
-    now_start = datetime.now()
-    routing = state.routing_decision if hasattr(state, "routing") else "agent_search"
-
-    if routing == "agent_search":
-        agent_path = "agent_search_start"
-    else:
-        agent_path = "LLM"
-
-    now_end = datetime.now()
-
-    return Command(
-        # state update
-        update={
-            "log_messages": [
-                f"{now_start} -- Main - Path routing: {agent_path},  Time taken: {now_end - now_start}"
-            ]
-        },
-        # control flow
-        goto=agent_path,
-    )

backend/onyx/agents/agent_search/deep_search_a/main/nodes/compare_answers.py

@@ -13,7 +13,7 @@ from onyx.agents.agent_search.shared_graph_utils.prompts import ANSWER_COMPARISO
 from onyx.chat.models import RefinedAnswerImprovement
 
 
-def answer_comparison(state: MainState, config: RunnableConfig) -> AnswerComparison:
+def compare_answers(state: MainState, config: RunnableConfig) -> AnswerComparison:
     now_start = datetime.now()
 
     agent_a_config = cast(AgentSearchConfig, config["metadata"]["config"])
@@ -23,11 +23,11 @@ def answer_comparison(state: MainState, config: RunnableConfig) -> AnswerCompari
 
     logger.info(f"--------{now_start}--------ANSWER COMPARISON STARTED--")
 
-    answer_comparison_prompt = ANSWER_COMPARISON_PROMPT.format(
+    compare_answers_prompt = ANSWER_COMPARISON_PROMPT.format(
         question=question, initial_answer=initial_answer, refined_answer=refined_answer
     )
 
-    msg = [HumanMessage(content=answer_comparison_prompt)]
+    msg = [HumanMessage(content=compare_answers_prompt)]
 
     # Get the rewritten queries in a defined format
     model = agent_a_config.fast_llm

backend/onyx/agents/agent_search/deep_search_a/main/nodes/create_refined_sub_questions.py

@@ -32,7 +32,7 @@ from onyx.agents.agent_search.shared_graph_utils.utils import make_question_id
 from onyx.tools.models import ToolCallKickoff
 
 
-def refined_sub_question_creation(
+def create_refined_sub_questions(
     state: MainState, config: RunnableConfig
 ) -> FollowUpSubQuestionsUpdate:
     """ """

backend/onyx/agents/agent_search/deep_search_a/main/nodes/direct_llm_handling.py

@@ -1,83 +0,0 @@
-from datetime import datetime
-from typing import Any
-from typing import cast
-
-from langchain_core.callbacks.manager import dispatch_custom_event
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_content
-from langchain_core.runnables import RunnableConfig
-
-from onyx.agents.agent_search.deep_search_a.main.operations import logger
-from onyx.agents.agent_search.deep_search_a.main.states import (
-    InitialAnswerUpdate,
-)
-from onyx.agents.agent_search.deep_search_a.main.states import MainState
-from onyx.agents.agent_search.models import AgentSearchConfig
-from onyx.agents.agent_search.shared_graph_utils.prompts import DIRECT_LLM_PROMPT
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_persona_agent_prompt_expressions,
-)
-from onyx.chat.models import AgentAnswerPiece
-
-
-def direct_llm_handling(
-    state: MainState, config: RunnableConfig
-) -> InitialAnswerUpdate:
-    now_start = datetime.now()
-
-    agent_a_config = cast(AgentSearchConfig, config["metadata"]["config"])
-    question = agent_a_config.search_request.query
-    persona_contextualialized_prompt = get_persona_agent_prompt_expressions(
-        agent_a_config.search_request.persona
-    ).contextualized_prompt
-
-    logger.info(f"--------{now_start}--------LLM HANDLING START---")
-
-    model = agent_a_config.fast_llm
-
-    msg = [
-        HumanMessage(
-            content=DIRECT_LLM_PROMPT.format(
-                persona_specification=persona_contextualialized_prompt,
-                question=question,
-            )
-        )
-    ]
-
-    streamed_tokens: list[str | list[str | dict[str, Any]]] = [""]
-
-    for message in model.stream(msg):
-        # TODO: in principle, the answer here COULD contain images, but we don't support that yet
-        content = message.content
-        if not isinstance(content, str):
-            raise ValueError(
-                f"Expected content to be a string, but got {type(content)}"
-            )
-        dispatch_custom_event(
-            "initial_agent_answer",
-            AgentAnswerPiece(
-                answer_piece=content,
-                level=0,
-                level_question_nr=0,
-                answer_type="agent_level_answer",
-            ),
-        )
-        streamed_tokens.append(content)
-
-    response = merge_content(*streamed_tokens)
-    answer = cast(str, response)
-
-    now_end = datetime.now()
-
-    logger.info(f"--------{now_end}--{now_end - now_start}--------LLM HANDLING END---")
-
-    return InitialAnswerUpdate(
-        initial_answer=answer,
-        initial_agent_stats=None,
-        generated_sub_questions=[],
-        agent_base_end_time=now_end,
-        agent_base_metrics=None,
-        log_messages=[
-            f"{now_start} -- Main - LLM handling: {answer},  Time taken: {now_end - now_start}"
-        ],
-    )

backend/onyx/agents/agent_search/deep_search_a/main/nodes/extract_entity_term.py

@@ -25,7 +25,7 @@ from onyx.agents.agent_search.shared_graph_utils.prompts import ENTITY_TERM_PROM
 from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
 
 
-def entity_term_extraction_llm(
+def extract_entity_term(
     state: MainState, config: RunnableConfig
 ) -> EntityTermExtractionUpdate:
     now_start = datetime.now()

backend/onyx/agents/agent_search/deep_search_a/main/nodes/generate_initial_base_search_only_answer.py

@@ -1,58 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import HumanMessage
-from langchain_core.runnables import RunnableConfig
-
-from onyx.agents.agent_search.deep_search_a.main.operations import logger
-from onyx.agents.agent_search.deep_search_a.main.states import (
-    InitialAnswerBASEUpdate,
-)
-from onyx.agents.agent_search.deep_search_a.main.states import MainState
-from onyx.agents.agent_search.models import AgentSearchConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    trim_prompt_piece,
-)
-from onyx.agents.agent_search.shared_graph_utils.prompts import INITIAL_RAG_BASE_PROMPT
-from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
-
-
-def generate_initial_base_search_only_answer(
-    state: MainState,
-    config: RunnableConfig,
-) -> InitialAnswerBASEUpdate:
-    now_start = datetime.now()
-
-    logger.info(f"--------{now_start}--------GENERATE INITIAL BASE ANSWER---")
-
-    agent_a_config = cast(AgentSearchConfig, config["metadata"]["config"])
-    question = agent_a_config.search_request.query
-    original_question_docs = state.all_original_question_documents
-
-    model = agent_a_config.fast_llm
-
-    doc_context = format_docs(original_question_docs)
-    doc_context = trim_prompt_piece(
-        model.config, doc_context, INITIAL_RAG_BASE_PROMPT + question
-    )
-
-    msg = [
-        HumanMessage(
-            content=INITIAL_RAG_BASE_PROMPT.format(
-                question=question,
-                context=doc_context,
-            )
-        )
-    ]
-
-    # Grader
-    response = model.invoke(msg)
-    answer = response.pretty_repr()
-
-    now_end = datetime.now()
-
-    logger.debug(
-        f"--------{now_end}--{now_end - now_start}--------INITIAL BASE ANSWER END---\n\n"
-    )
-
-    return InitialAnswerBASEUpdate(initial_base_answer=answer)

backend/onyx/agents/agent_search/deep_search_a/main/nodes/persist_agent_results.py

@@ -16,7 +16,7 @@ from onyx.db.chat import log_agent_metrics
 from onyx.db.chat import log_agent_sub_question_results
 
 
-def agent_logging(state: MainState, config: RunnableConfig) -> MainOutput:
+def persist_agent_results(state: MainState, config: RunnableConfig) -> MainOutput:
     now_start = datetime.now()
 
     logger.info(f"--------{now_start}--------LOGGING NODE---")
@@ -94,16 +94,6 @@ def agent_logging(state: MainState, config: RunnableConfig) -> MainOutput:
                 sub_question_answer_results=sub_question_answer_results,
             )
 
-        # if chat_session_id is not None and primary_message_id is not None and sub_question_id is not None:
-        #     create_sub_answer(
-        #         db_session=db_session,
-        #         chat_session_id=chat_session_id,
-        #         primary_message_id=primary_message_id,
-        #         sub_question_id=sub_question_id,
-        #         answer=answer_str,
-        # #     )
-        # pass
-
     now_end = datetime.now()
     main_output = MainOutput(
         log_messages=[

backend/onyx/agents/agent_search/deep_search_a/main/nodes/start_agent_search.py

@@ -17,7 +17,7 @@ from onyx.configs.agent_configs import AGENT_EXPLORATORY_SEARCH_RESULTS
 from onyx.context.search.models import InferenceSection
 
 
-def agent_search_start(
+def start_agent_search(
     state: MainState, config: RunnableConfig
 ) -> ExploratorySearchUpdate:
     now_start = datetime.now()

backend/onyx/agents/agent_search/deep_search_a/main/nodes/validate_refined_answer.py

@@ -11,7 +11,7 @@ from onyx.agents.agent_search.deep_search_a.main.states import (
 from onyx.agents.agent_search.models import AgentSearchConfig
 
 
-def refined_answer_decision(
+def validate_refined_answer(
     state: MainState, config: RunnableConfig
 ) -> RequireRefinedAnswerUpdate:
     now_start = datetime.now()
@@ -19,12 +19,8 @@ def refined_answer_decision(
     logger.info(f"--------{now_start}--------REFINED ANSWER DECISION---")
 
     agent_a_config = cast(AgentSearchConfig, config["metadata"]["config"])
-    if "?" in agent_a_config.search_request.query:
-        decision = False
-    else:
-        decision = True
 
-    decision = True
+    decision = True  # TODO: just for current testing purposes
 
     now_end = datetime.now()
 

backend/onyx/agents/agent_search/deep_search_a/refinement/consolidate_sub_answers/models.py

@@ -14,6 +14,5 @@ class QuestionAnswerResults(BaseModel):
     question: str
     answer: str
     quality: str
-    # expanded_retrieval_results: list[QueryResult]
     documents: list[InferenceSection]
     sub_question_retrieval_stats: AgentChunkStats