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| from langchain_core.messages import AnyMessage, BaseMessage, AIMessage, HumanMessage | |
| from langgraph.graph import START, END, StateGraph | |
| from langgraph.graph.message import add_messages | |
| from langgraph.prebuilt import ToolNode, tools_condition | |
| from typing import Annotated, Any, Dict, List, Literal, Optional, TypedDict | |
| import logging | |
| from pathlib import Path | |
| from args import Args | |
| class State(TypedDict): | |
| """State class for the agent graph.""" | |
| initial_query: str | |
| # messages: List[Dict[str, Any]] | |
| messages: Annotated[list[AnyMessage], add_messages] | |
| nr_interactions: int | |
| final_response: Optional[str] | |
| class Nodes: | |
| """ | |
| Collection of node functions for the agent graph. | |
| """ | |
| def manager_node(self, state: State) -> State: | |
| """ | |
| Orchestrates the workflow by delegating tasks to specialized nodes and integrating their outputs | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def final_answer_node(self, state: State) -> State: | |
| """ | |
| Formats and delivers the final response to the user | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def auditor_node(self, state: State) -> State: | |
| """ | |
| Reviews manager's outputs for accuracy, safety, and quality | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def solver_node(self, state: State) -> State: | |
| """ | |
| Central problem-solving node that coordinates with specialized experts based on task requirements | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def researcher_node(self, state: State) -> State: | |
| """ | |
| Retrieves and synthesizes information from various sources to answer knowledge-based questions | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def reasoner_node(self, state: State) -> State: | |
| """ | |
| Performs logical reasoning, inference, and step-by-step problem-solving | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def image_handler_node(self, state: State) -> State: | |
| """ | |
| Processes, analyzes, and generates information related to images | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def video_handler_node(self, state: State) -> State: | |
| """ | |
| Processes, analyzes, and generates information related to videos | |
| """ | |
| # TODO: To implement... | |
| pass | |
| class Edges: | |
| """ | |
| Collection of conditional edge functions for the agent graph. | |
| """ | |
| def manager_edge(self, state: State) -> Literal["solver", "auditor", "final_answer"]: | |
| """ | |
| Conditional edge for manager node. | |
| Returns one of: "solver", "auditor", "final_answer" | |
| """ | |
| # TODO: To implement... | |
| pass | |
| def solver_edge(self, state: State) -> Literal["manager", "researcher", "reasoner", "image_handler", "video_handler"]: | |
| """ | |
| Conditional edge for solver node. | |
| Returns one of: "manager", "researcher", "encryption_expert", "math_expert", "reasoner", "image_handler", "video_handler" | |
| """ | |
| # TODO: To implement... | |
| pass | |