from typing import Optional
from unittest.mock import Mock

import pytest

from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
from invokeai.app.invocations.collections import RangeInvocation
from invokeai.app.invocations.logic import IfInvocation, IfInvocationOutput
from invokeai.app.invocations.math import AddInvocation, MultiplyInvocation
from invokeai.app.services.shared.graph import (
    CollectInvocation,
    Graph,
    GraphExecutionState,
    IterateInvocation,
)

# This import must happen before other invoke imports or test in other files(!!) break
from tests.test_nodes import (
    PromptCollectionTestInvocation,
    PromptTestInvocation,
    TextToImageTestInvocation,
    create_edge,
)


@pytest.fixture
def simple_graph() -> Graph:
    g = Graph()
    g.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
    g.add_node(TextToImageTestInvocation(id="2"))
    g.add_edge(create_edge("1", "prompt", "2", "prompt"))
    return g


def invoke_next(g: GraphExecutionState) -> tuple[Optional[BaseInvocation], Optional[BaseInvocationOutput]]:
    n = g.next()
    if n is None:
        return (None, None)

    print(f"invoking {n.id}: {type(n)}")
    o = n.invoke(Mock(InvocationContext))
    g.complete(n.id, o)

    return (n, o)


def test_graph_state_executes_in_order(simple_graph: Graph):
    g = GraphExecutionState(graph=simple_graph)

    n1 = invoke_next(g)
    n2 = invoke_next(g)
    n3 = g.next()

    assert g.prepared_source_mapping[n1[0].id] == "1"
    assert g.prepared_source_mapping[n2[0].id] == "2"
    assert n3 is None
    assert g.results[n1[0].id].prompt == n1[0].prompt
    assert n2[0].prompt == n1[0].prompt


def test_graph_is_complete(simple_graph: Graph):
    g = GraphExecutionState(graph=simple_graph)
    _ = invoke_next(g)
    _ = invoke_next(g)
    _ = g.next()

    assert g.is_complete()


def test_graph_is_not_complete(simple_graph: Graph):
    g = GraphExecutionState(graph=simple_graph)
    _ = invoke_next(g)
    _ = g.next()

    assert not g.is_complete()


# TODO: test completion with iterators/subgraphs


def test_graph_state_expands_iterator():
    graph = Graph()
    graph.add_node(RangeInvocation(id="0", start=0, stop=3, step=1))
    graph.add_node(IterateInvocation(id="1"))
    graph.add_node(MultiplyInvocation(id="2", b=10))
    graph.add_node(AddInvocation(id="3", b=1))
    graph.add_edge(create_edge("0", "collection", "1", "collection"))
    graph.add_edge(create_edge("1", "item", "2", "a"))
    graph.add_edge(create_edge("2", "value", "3", "a"))

    g = GraphExecutionState(graph=graph)
    while not g.is_complete():
        invoke_next(g)

    prepared_add_nodes = g.source_prepared_mapping["3"]
    results = {g.results[n].value for n in prepared_add_nodes}
    expected = {1, 11, 21}
    assert results == expected


def test_graph_state_collects():
    graph = Graph()
    test_prompts = ["Banana sushi", "Cat sushi"]
    graph.add_node(PromptCollectionTestInvocation(id="1", collection=list(test_prompts)))
    graph.add_node(IterateInvocation(id="2"))
    graph.add_node(PromptTestInvocation(id="3"))
    graph.add_node(CollectInvocation(id="4"))
    graph.add_edge(create_edge("1", "collection", "2", "collection"))
    graph.add_edge(create_edge("2", "item", "3", "prompt"))
    graph.add_edge(create_edge("3", "prompt", "4", "item"))

    g = GraphExecutionState(graph=graph)
    _ = invoke_next(g)
    _ = invoke_next(g)
    _ = invoke_next(g)
    _ = invoke_next(g)
    _ = invoke_next(g)
    n6 = invoke_next(g)

    assert isinstance(n6[0], CollectInvocation)

    assert sorted(g.results[n6[0].id].collection) == sorted(test_prompts)


def test_graph_state_prepares_eagerly():
    """Tests that all prepareable nodes are prepared"""
    graph = Graph()

    test_prompts = ["Banana sushi", "Cat sushi"]
    graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
    graph.add_node(IterateInvocation(id="iterate"))
    graph.add_node(PromptTestInvocation(id="prompt_iterated"))
    graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
    graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))

    # separated, fully-preparable chain of nodes
    graph.add_node(PromptTestInvocation(id="prompt_chain_1", prompt="Dinosaur sushi"))
    graph.add_node(PromptTestInvocation(id="prompt_chain_2"))
    graph.add_node(PromptTestInvocation(id="prompt_chain_3"))
    graph.add_edge(create_edge("prompt_chain_1", "prompt", "prompt_chain_2", "prompt"))
    graph.add_edge(create_edge("prompt_chain_2", "prompt", "prompt_chain_3", "prompt"))

    g = GraphExecutionState(graph=graph)
    g.next()

    assert "prompt_collection" in g.source_prepared_mapping
    assert "prompt_chain_1" in g.source_prepared_mapping
    assert "prompt_chain_2" in g.source_prepared_mapping
    assert "prompt_chain_3" in g.source_prepared_mapping
    assert "iterate" not in g.source_prepared_mapping
    assert "prompt_iterated" not in g.source_prepared_mapping


def test_graph_executes_depth_first():
    """Tests that the graph executes depth-first, executing a branch as far as possible before moving to the next branch"""

    def assert_topo_order_and_all_executed(state: GraphExecutionState, order: list[str]):
        """
        Validates:
          1) Every materialized exec node executed exactly once.
          2) Execution order respects all exec-graph dependencies (u→v ⇒ u before v).
        """
        # order must be EXEC node ids in run order
        exec_nodes = set(state.execution_graph.nodes.keys())

        # 1) coverage: all exec nodes ran, and no duplicates
        pos = {nid: i for i, nid in enumerate(order)}
        assert set(pos.keys()) == exec_nodes, (
            f"Executed {len(pos)} of {len(exec_nodes)} nodes. Missing: {sorted(exec_nodes - set(pos))[:10]}"
        )
        assert len(pos) == len(order), "Duplicate execution detected"

        # 2) topo order: parents before children
        for e in state.execution_graph.edges:
            u = e.source.node_id
            v = e.destination.node_id
            assert pos[u] < pos[v], f"child {v} ran before parent {u}"

    graph = Graph()

    test_prompts = ["Banana sushi", "Cat sushi"]
    graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
    graph.add_node(IterateInvocation(id="iterate"))
    graph.add_node(PromptTestInvocation(id="prompt_iterated"))
    graph.add_node(PromptTestInvocation(id="prompt_successor"))
    graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
    graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))
    graph.add_edge(create_edge("prompt_iterated", "prompt", "prompt_successor", "prompt"))

    g = GraphExecutionState(graph=graph)
    order: list[str] = []

    while True:
        n = g.next()
        if n is None:
            break
        o = n.invoke(Mock(InvocationContext))
        g.complete(n.id, o)
        order.append(n.id)

    assert_topo_order_and_all_executed(g, order)


# Because this tests deterministic ordering, we run it multiple times
@pytest.mark.parametrize("execution_number", range(5))
def test_graph_iterate_execution_order(execution_number: int):
    """Tests that iterate nodes execution is ordered by the order of the collection"""

    graph = Graph()

    test_prompts = ["Banana sushi", "Cat sushi", "Strawberry Sushi", "Dinosaur Sushi"]
    graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
    graph.add_node(IterateInvocation(id="iterate"))
    graph.add_node(PromptTestInvocation(id="prompt_iterated"))
    graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
    graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))

    g = GraphExecutionState(graph=graph)
    _ = invoke_next(g)
    _ = invoke_next(g)
    assert _[1].item == "Banana sushi"
    _ = invoke_next(g)
    assert _[1].item == "Cat sushi"
    _ = invoke_next(g)
    assert _[1].item == "Strawberry Sushi"
    _ = invoke_next(g)
    assert _[1].item == "Dinosaur Sushi"
    _ = invoke_next(g)


# Because this tests deterministic ordering, we run it multiple times
@pytest.mark.parametrize("execution_number", range(5))
def test_graph_nested_iterate_execution_order(execution_number: int):
    """
    Validates best-effort in-order execution for nodes expanded under nested iterators.
    Expected lexicographic order by (outer_index, inner_index), subject to readiness.
    """
    graph = Graph()

    # Outer iterator: [0, 1]
    graph.add_node(RangeInvocation(id="outer_range", start=0, stop=2, step=1))
    graph.add_node(IterateInvocation(id="outer_iter"))

    # Inner iterator is derived from the outer item:
    # start = outer_item * 10
    # stop  = start + 2  => yields 2 items per outer item
    graph.add_node(MultiplyInvocation(id="mul10", b=10))
    graph.add_node(AddInvocation(id="stop_plus2", b=2))
    graph.add_node(RangeInvocation(id="inner_range", start=0, stop=1, step=1))
    graph.add_node(IterateInvocation(id="inner_iter"))

    # Observe inner items (they encode outer via start=outer*10)
    graph.add_node(AddInvocation(id="sum", b=0))

    graph.add_edge(create_edge("outer_range", "collection", "outer_iter", "collection"))
    graph.add_edge(create_edge("outer_iter", "item", "mul10", "a"))
    graph.add_edge(create_edge("mul10", "value", "stop_plus2", "a"))
    graph.add_edge(create_edge("mul10", "value", "inner_range", "start"))
    graph.add_edge(create_edge("stop_plus2", "value", "inner_range", "stop"))
    graph.add_edge(create_edge("inner_range", "collection", "inner_iter", "collection"))
    graph.add_edge(create_edge("inner_iter", "item", "sum", "a"))

    g = GraphExecutionState(graph=graph)
    sum_values: list[int] = []

    while True:
        n, o = invoke_next(g)
        if n is None:
            break
        if g.prepared_source_mapping[n.id] == "sum":
            sum_values.append(o.value)

    assert sum_values == [0, 1, 10, 11]


def test_graph_validate_self_iterator_without_collection_input_raises_invalid_edge_error():
    """Iterator nodes with no collection input should fail validation cleanly.

    This test exposes the bug where validation crashes with IndexError instead of raising InvalidEdgeError.
    """
    from invokeai.app.services.shared.graph import InvalidEdgeError

    graph = Graph()
    graph.add_node(IterateInvocation(id="iterate"))

    with pytest.raises(InvalidEdgeError):
        graph.validate_self()


def test_graph_validate_self_collector_without_item_inputs_raises_invalid_edge_error():
    """Collector nodes with no item inputs should fail validation cleanly.

    This test exposes the bug where validation can crash (e.g. StopIteration) instead of raising InvalidEdgeError.
    """
    from invokeai.app.services.shared.graph import InvalidEdgeError

    graph = Graph()
    graph.add_node(CollectInvocation(id="collect"))

    with pytest.raises(InvalidEdgeError):
        graph.validate_self()


def test_if_invocation_selects_true_input_value():
    invocation = IfInvocation(id="if", condition=True, true_input="true", false_input="false")

    output = invocation.invoke(Mock(InvocationContext))

    assert output.value == "true"


def test_if_invocation_outputs_none_when_selected_input_is_missing():
    invocation = IfInvocation(id="if", condition=False, true_input="true")

    output = invocation.invoke(Mock(InvocationContext))

    assert output.value is None


def test_if_invocation_output_allows_missing_value_on_deserialization():
    output = IfInvocationOutput.model_validate({"type": "if_output"})

    assert output.value is None


def test_if_invocation_output_connects_to_downstream_input():
    graph = Graph()
    graph.add_node(IfInvocation(id="if", condition=True, true_input="connected value", false_input="unused"))
    graph.add_node(PromptTestInvocation(id="prompt"))
    graph.add_edge(create_edge("if", "value", "prompt", "prompt"))

    g = GraphExecutionState(graph=graph)
    while not g.is_complete():
        invoke_next(g)

    prepared_prompt_nodes = g.source_prepared_mapping["prompt"]
    assert len(prepared_prompt_nodes) == 1
    prepared_prompt_node_id = next(iter(prepared_prompt_nodes))
    assert g.results[prepared_prompt_node_id].prompt == "connected value"


def test_are_connection_types_compatible_accepts_subclass_to_base():
    """A subclass output should be connectable to a base-class input.

    This test exposes the bug where non-Union targets reject valid subclass connections.
    """
    from invokeai.app.services.shared.graph import are_connection_types_compatible

    class Base:
        pass

    class Child(Base):
        pass

    assert are_connection_types_compatible(Child, Base) is True