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from __future__ import annotations
from dataclasses import dataclass, field
from typing import TypedDict
from langgraph.graph import add_messages
from typing_extensions import Annotated
import operator
from dataclasses import dataclass, field
from typing_extensions import Annotated
class OverallState(TypedDict):
messages: Annotated[list, add_messages]
search_query: Annotated[list, operator.add]
web_research_result: Annotated[list, operator.add]
sources_gathered: Annotated[list, operator.add]
initial_search_query_count: int
max_research_loops: int
research_loop_count: int
reasoning_model: str
class ReflectionState(TypedDict):
is_sufficient: bool
knowledge_gap: str
follow_up_queries: Annotated[list, operator.add]
research_loop_count: int
number_of_ran_queries: int
class Query(TypedDict):
query: str
rationale: str
class QueryGenerationState(TypedDict):
query_list: list[Query]
class WebSearchState(TypedDict):
search_query: str
id: str
@dataclass(kw_only=True)
class SearchStateOutput:
running_summary: str = field(default=None) # Final report
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