MCP Wikipedia Server

from __future__ import annotations from collections import defaultdict from collections.abc import Mapping, Sequence from typing import Any, cast from langchain_core.runnables.config import RunnableConfig from langchain_core.runnables.graph import Graph, Node from langgraph._internal._constants import CONF, CONFIG_KEY_SEND, INPUT from langgraph.channels.base import BaseChannel from langgraph.checkpoint.base import BaseCheckpointSaver from langgraph.constants import END, START from langgraph.managed.base import ManagedValueSpec from langgraph.pregel._algo import ( PregelTaskWrites, apply_writes, increment, prepare_next_tasks, ) from langgraph.pregel._checkpoint import channels_from_checkpoint, empty_checkpoint from langgraph.pregel._io import map_input from langgraph.pregel._read import PregelNode from langgraph.pregel._write import ChannelWrite from langgraph.types import All, Checkpointer def draw_graph( config: RunnableConfig, *, nodes: dict[str, PregelNode], specs: dict[str, BaseChannel | ManagedValueSpec], input_channels: str | Sequence[str], interrupt_after_nodes: All | Sequence[str], interrupt_before_nodes: All | Sequence[str], trigger_to_nodes: Mapping[str, Sequence[str]], checkpointer: Checkpointer, subgraphs: dict[str, Graph], limit: int = 250, ) -> Graph: """Get the graph for this Pregel instance. Args: config: The configuration to use for the graph. subgraphs: The subgraphs to include in the graph. checkpointer: The checkpointer to use for the graph. Returns: The graph for this Pregel instance. """ # (src, dest, is_conditional, label) edges: set[tuple[str, str, bool, str | None]] = set() step = -1 checkpoint = empty_checkpoint() get_next_version = ( checkpointer.get_next_version if isinstance(checkpointer, BaseCheckpointSaver) else increment ) channels, managed = channels_from_checkpoint( specs, checkpoint, ) static_seen: set[Any] = set() sources: dict[str, set[tuple[str, bool, str | None]]] = {} step_sources: dict[str, set[tuple[str, bool, str | None]]] = {} # remove node mappers nodes = { k: v.copy(update={"mapper": None}) if v.mapper is not None else v for k, v in nodes.items() } # apply input writes input_writes = list(map_input(input_channels, {})) updated_channels = apply_writes( checkpoint, channels, [ PregelTaskWrites((), INPUT, input_writes, []), ], get_next_version, trigger_to_nodes, ) # prepare first tasks tasks = prepare_next_tasks( checkpoint, [], nodes, channels, managed, config, step, -1, for_execution=True, store=None, checkpointer=None, manager=None, trigger_to_nodes=trigger_to_nodes, updated_channels=updated_channels, ) start_tasks = tasks # run the pregel loop for step in range(step, limit): if not tasks: break conditionals: dict[tuple[str, str, Any], str | None] = {} # run task writers for task in tasks.values(): for w in task.writers: # apply regular writes if isinstance(w, ChannelWrite): empty_input = ( cast(BaseChannel, specs["__root__"]).ValueType() if "__root__" in specs else None ) w.invoke(empty_input, task.config) # apply conditional writes declared for static analysis, only once if w not in static_seen: static_seen.add(w) # apply static writes if writes := ChannelWrite.get_static_writes(w): # END writes are not written, but become edges directly for t in writes: if t[0] == END: edges.add((task.name, t[0], True, t[2])) writes = [t for t in writes if t[0] != END] conditionals.update( {(task.name, t[0], t[1] or None): t[2] for t in writes} ) task.config[CONF][CONFIG_KEY_SEND]([t[:2] for t in writes]) # collect sources step_sources = { task.name: { ( w[0], (task.name, w[0], w[1] or None) in conditionals, conditionals.get((task.name, w[0], w[1] or None)), ) for w in task.writes } for task in tasks.values() } sources.update(step_sources) # invert triggers trigger_to_sources: dict[str, set[tuple[str, bool, str | None]]] = defaultdict( set ) for src, triggers in sources.items(): for trigger, cond, label in triggers: trigger_to_sources[trigger].add((src, cond, label)) # apply writes updated_channels = apply_writes( checkpoint, channels, tasks.values(), get_next_version, trigger_to_nodes ) # prepare next tasks tasks = prepare_next_tasks( checkpoint, [], nodes, channels, managed, config, step, limit, for_execution=True, store=None, checkpointer=None, manager=None, trigger_to_nodes=trigger_to_nodes, updated_channels=updated_channels, ) # collect edges for task in tasks.values(): added = False for trigger in task.triggers: for src, cond, label in sorted(trigger_to_sources[trigger]): edges.add((src, task.name, cond, label)) # if the edge is from this step, skip adding the implicit edges if (trigger, cond, label) in step_sources.get(src, set()): added = True else: sources[src].discard((trigger, cond, label)) # if no edges from this step, add implicit edges from all previous tasks if not added: for src in step_sources: edges.add((src, task.name, True, None)) # assemble the graph graph = Graph() # add nodes for name, node in nodes.items(): metadata = dict(node.metadata or {}) if name in interrupt_before_nodes and name in interrupt_after_nodes: metadata["__interrupt"] = "before,after" elif name in interrupt_before_nodes: metadata["__interrupt"] = "before" elif name in interrupt_after_nodes: metadata["__interrupt"] = "after" graph.add_node(node.bound, name, metadata=metadata or None) # add start node if START not in nodes: graph.add_node(None, START) for task in start_tasks.values(): add_edge(graph, START, task.name) # add discovered edges for src, dest, is_conditional, label in sorted(edges): add_edge( graph, src, dest, data=label if label != dest else None, conditional=is_conditional, ) # add end edges termini = {d for _, d, _, _ in edges if d != END}.difference( s for s, _, _, _ in edges ) if termini: for src in sorted(termini): add_edge(graph, src, END) elif len(step_sources) == 1: for src in sorted(step_sources): add_edge(graph, src, END, conditional=True) # replace subgraphs for name, subgraph in subgraphs.items(): if ( len(subgraph.nodes) > 1 and name in graph.nodes and subgraph.first_node() and subgraph.last_node() ): subgraph.trim_first_node() subgraph.trim_last_node() # replace the node with the subgraph graph.nodes.pop(name) first, last = graph.extend(subgraph, prefix=name) for idx, edge in enumerate(graph.edges): if edge.source == name: edge = edge.copy(source=cast(Node, last).id) if edge.target == name: edge = edge.copy(target=cast(Node, first).id) graph.edges[idx] = edge return graph def add_edge( graph: Graph, source: str, target: str, *, data: Any | None = None, conditional: bool = False, ) -> None: """Add an edge to the graph.""" for edge in graph.edges: if edge.source == source and edge.target == target: return if target not in graph.nodes and target == END: graph.add_node(None, END) graph.add_edge(graph.nodes[source], graph.nodes[target], data, conditional)