feat(removed): sub_section_writer agent

surfsense_backend/app/agents/researcher/configuration.py

@@ -15,27 +15,16 @@ class SearchMode(Enum):
     DOCUMENTS = "DOCUMENTS"
 
 
-class ResearchMode(Enum):
-    """Enum defining the type of research mode."""
-
-    QNA = "QNA"
-    REPORT_GENERAL = "REPORT_GENERAL"
-    REPORT_DEEP = "REPORT_DEEP"
-    REPORT_DEEPER = "REPORT_DEEPER"
-
-
 @dataclass(kw_only=True)
 class Configuration:
     """The configuration for the agent."""
 
     # Input parameters provided at invocation
     user_query: str
-    num_sections: int
     connectors_to_search: list[str]
     user_id: str
     search_space_id: int
     search_mode: SearchMode
-    research_mode: ResearchMode
     document_ids_to_add_in_context: list[int]
     language: str | None = None
 

surfsense_backend/app/agents/researcher/graph.py

@@ -1,34 +1,23 @@
-from typing import Any, TypedDict
-
 from langgraph.graph import StateGraph
 
-from .configuration import Configuration, ResearchMode
+from .configuration import Configuration
 from .nodes import (
     generate_further_questions,
     handle_qna_workflow,
-    process_sections,
     reformulate_user_query,
-    write_answer_outline,
 )
 from .state import State
 
 
-# Define what keys are in our state dict
-class GraphState(TypedDict):
-    # Intermediate data produced during workflow
-    answer_outline: Any | None
-    # Final output
-    final_written_report: str | None
-
-
 def build_graph():
     """
     Build and return the LangGraph workflow.
 
-    This function constructs the researcher agent graph with conditional routing
-    based on research_mode - QNA mode uses a direct Q&A workflow while other modes
-    use the full report generation pipeline. Both paths generate follow-up questions
-    at the end using the reranked documents from the sub-agents.
+    This function constructs the researcher agent graph for Q&A workflow.
+    The workflow follows a simple path:
+    1. Reformulate user query based on chat history
+    2. Handle QNA workflow (fetch documents and generate answer)
+    3. Generate follow-up questions
 
     Returns:
         A compiled LangGraph workflow
@@ -39,40 +28,12 @@ def build_graph():
     # Add nodes to the graph
     workflow.add_node("reformulate_user_query", reformulate_user_query)
     workflow.add_node("handle_qna_workflow", handle_qna_workflow)
-    workflow.add_node("write_answer_outline", write_answer_outline)
-    workflow.add_node("process_sections", process_sections)
     workflow.add_node("generate_further_questions", generate_further_questions)
 
-    # Define the edges
+    # Define the edges - simple linear flow for QNA
     workflow.add_edge("__start__", "reformulate_user_query")
-
-    # Add conditional edges from reformulate_user_query based on research mode
-    def route_after_reformulate(state: State, config) -> str:
-        """Route based on research_mode after reformulating the query."""
-        configuration = Configuration.from_runnable_config(config)
-
-        if configuration.research_mode == ResearchMode.QNA.value:
-            return "handle_qna_workflow"
-        else:
-            return "write_answer_outline"
-
-    workflow.add_conditional_edges(
-        "reformulate_user_query",
-        route_after_reformulate,
-        {
-            "handle_qna_workflow": "handle_qna_workflow",
-            "write_answer_outline": "write_answer_outline",
-        },
-    )
-
-    # QNA workflow path: handle_qna_workflow -> generate_further_questions -> __end__
+    workflow.add_edge("reformulate_user_query", "handle_qna_workflow")
     workflow.add_edge("handle_qna_workflow", "generate_further_questions")
-
-    # Report generation workflow path: write_answer_outline -> process_sections -> generate_further_questions -> __end__
-    workflow.add_edge("write_answer_outline", "process_sections")
-    workflow.add_edge("process_sections", "generate_further_questions")
-
-    # Both paths end after generating further questions
     workflow.add_edge("generate_further_questions", "__end__")
 
     # Compile the workflow into an executable graph