首先,我们知道了可以通过 add_conditional_edges 来对边进行条件添加。这部分代码如下: graph.add_conditional_edges("oracle", router, { "multiply": "multiply", "end": END,}) add_conditional_edges接收三个参数: · 第一个为这条边的第一个node的名称 · 第二个为这条边的条件 · 第三个为条件返回...
# We now add a conditional edge workflow.add_conditional_edges( # First, we define the start node. We use `agent`. # This means these are the edges taken after the `agent` node is called. "agent", # Next, we pass in the function that will determine which node is called next. sho...
workflow.add_conditional_edges( "write_tests", should_continue, { "continue": "write_tests", "end": "write_file" } ) add_conditional_edge 函数采用 write_tests 函数、一个根据class_methods条目决定要执行的步骤的should_continue函数,以及将字符串作为键并将其他函数作为值的映射。 边从 write_tests ...
langgraph.add_conditional_edges( "neighbor_select", neighbor_condition, ) langgraph.add_edge("answer_reasoning", END) langgraph = langgraph.compile() 我们首先定义状态图对象,在其中可以定义在 LangGraph 中传递的信息。每个节点都可以通过add_node方法添加。普通的边,其中一步总是跟随另一步,可以通过add...
graph.add_node("action", self.take_action) # 如果有存在action,则执行 graph.add_conditional_edges( "llm", self.exists_action, {True: "action", False: END} ) # llm判断是否有exists_action graph.add_edge("action", "llm") # 将执行后的action与llm连接起来 ...
graph.add_node("summarize_and_prune", summarize_and_prune) graph.add_conditional_edges( "process_query", { "human_intervention": lambda s: s['confidence'] < 0.8, "summarize_and_prune": lambda s: s['confidence'] >= 0.8 } )
workflow.add_conditional_edges( "write_tests", should_continue, { "continue": "write_tests", "end": "write_file" } ) add_conditional_edge 函数采用 write_tests 函数、一个根据class_methods条目决定要执行的步骤的should_continue函数,以及将字符串作为键并将其他函数作为值的映射。边从write_tests ...
LangGraph 构造的是个图的数据结构,有节点(node) 和边(edge),那它的边也可以是带条件的。如何给边加入条件呢?可以通过add_conditional_edges函数添加带条件的边。 1. 完整代码及运行 废话不多说,先上完整代码,和运行结果。先跑起来看看效果再说。
workflow.add_conditional_edges( "agent", should_continue, { "continue":"tools", "exit":END } ) workflow.add_edge('tools','agent') chain= workflow.compile() LangChain 表示,他们过去六个月一直在研发这个功能,并且与用户...
NetworkX 的启发，看起来像这样：from langgraph.graph import END, Graph workflow = Graph()workflow.add_node("agent", agent)workflow.add_node("tools", execute_tools)workflow.set_entry_point("agent")workflow.add_conditional_edges("agent",should_continue,{ "continue": "tools",...