from typing import TypedDict, Annotated
from langgraph.graph import StateGraph, END
from langgraph.graph.message import add_messages

# Define state schema
class AgentState(TypedDict):
    messages: Annotated[list, add_messages]
    current_step: str
    iteration: int

# Create nodes
def agent_node(state: AgentState) -> AgentState:
    # Process state and return updates
    return {"current_step": "processed", "iteration": state["iteration"] + 1}

def tool_node(state: AgentState) -> AgentState:
    # Execute tools based on agent decisions
    return {"current_step": "tools_executed"}

# Build graph
graph = StateGraph(AgentState)
graph.add_node("agent", agent_node)
graph.add_node("tools", tool_node)

# Define edges
graph.set_entry_point("agent")
graph.add_edge("agent", "tools")
graph.add_conditional_edges(
    "tools",
    lambda state: "end" if state["iteration"] >= 3 else "continue",
    {"end": END, "continue": "agent"}
)

# Compile
app = graph.compile()

def router(state: AgentState) -> str:
    """Route based on state conditions."""
    last_message = state["messages"][-1]

    if hasattr(last_message, "tool_calls") and last_message.tool_calls:
        return "tools"
    elif state["iteration"] >= state.get("max_iterations", 10):
        return "end"
    else:
        return "agent"

graph.add_conditional_edges(
    "agent",
    router,
    {
        "tools": "tool_executor",
        "agent": "agent",
        "end": END
    }
)

from langgraph.checkpoint.sqlite import SqliteSaver

# Configure checkpointer
memory = SqliteSaver.from_conn_string(":memory:")

# Compile with persistence
app = graph.compile(checkpointer=memory)

# Run with thread_id for persistence
config = {"configurable": {"thread_id": "conversation-1"}}
result = app.invoke(initial_state, config=config)

# Resume from checkpoint
result = app.invoke(None, config=config)  # Continues from last state

from langgraph.graph import StateGraph

graph = StateGraph(AgentState)
# ... add nodes ...

# Compile with interrupt points
app = graph.compile(
    checkpointer=memory,
    interrupt_before=["tool_executor"]  # Pause before tool execution
)

# First invocation - pauses at interrupt
result = app.invoke(initial_state, config)

# After human approval, resume
result = app.invoke(None, config)  # Continues past interrupt

const langgraphStateGraphTask = defineTask({
  name: 'langgraph-state-graph-design',
  description: 'Design and implement a LangGraph StateGraph workflow',

  inputs: {
    workflowName: { type: 'string', required: true },
    stateSchema: { type: 'object', required: true },
    nodes: { type: 'array', required: true },
    edges: { type: 'array', required: true },
    enablePersistence: { type: 'boolean', default: true },
    interruptPoints: { type: 'array', default: [] }
  },

  outputs: {
    graphCode: { type: 'string' },
    stateSchemaCode: { type: 'string' },
    compiledGraph: { type: 'boolean' },
    artifacts: { type: 'array' }
  },

  async run(inputs, taskCtx) {
    return {
      kind: 'skill',
      title: `Design StateGraph: ${inputs.workflowName}`,
      skill: {
        name: 'langgraph-state-graph',
        context: {
          workflowName: inputs.workflowName,
          stateSchema: inputs.stateSchema,
          nodes: inputs.nodes,
          edges: inputs.edges,
          enablePersistence: inputs.enablePersistence,
          interruptPoints: inputs.interruptPoints,
          instructions: [
            'Analyze workflow requirements and state needs',
            'Design state schema with proper typing',
            'Create node functions with state transformations',
            'Define edges and conditional routing logic',
            'Configure persistence if enabled',
            'Add interrupt points for human-in-the-loop',
            'Compile and validate the graph'
          ]
        }
      },
      io: {
        inputJsonPath: `tasks/${taskCtx.effectId}/input.json`,
        outputJsonPath: `tasks/${taskCtx.effectId}/result.json`
      }
    };
  }
});