"""Step definitions for the Tool-Calling Actor Runtime feature."""

from __future__ import annotations

import contextlib
from typing import Any

from behave import given, then, when

from cleveragents.infrastructure.events.reactive import ReactiveEventBus
from cleveragents.tool.actor_context import ToolActorContext, ToolCallRecord
from cleveragents.tool.actor_runtime import (
    LLMResponse,
    LLMToolCall,
    ToolCallingRuntime,
    ToolCallRunResult,
)
from cleveragents.tool.registry import ToolRegistry
from cleveragents.tool.router import ToolCallRouter
from cleveragents.tool.runner import ToolRunner
from cleveragents.tool.runtime import ToolSpec

__all__: list[str] = []


# ---------------------------------------------------------------------------
# Mock handlers
# ---------------------------------------------------------------------------


def _rt_echo_handler(inputs: dict[str, Any]) -> dict[str, Any]:
    return {"echoed": inputs}


def _rt_adder_handler(inputs: dict[str, Any]) -> dict[str, Any]:
    return {"sum": inputs.get("a", 0) + inputs.get("b", 0)}


def _rt_failing_handler(inputs: dict[str, Any]) -> dict[str, Any]:
    raise RuntimeError("handler exploded")


def _rt_generic_error_handler(inputs: dict[str, Any]) -> dict[str, Any]:
    raise KeyError("missing_key")


_rt_captured_inputs: dict[str, Any] = {}


def _rt_capturing_handler(inputs: dict[str, Any]) -> dict[str, Any]:
    _rt_captured_inputs.clear()
    _rt_captured_inputs.update(inputs)
    return {"captured": True}


# ---------------------------------------------------------------------------
# Mock LLM callers
# ---------------------------------------------------------------------------


class _SingleToolLLM:
    def __init__(self) -> None:
        self._n = 0

    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        self._n += 1
        if self._n == 1:
            return LLMResponse(
                content="",
                tool_calls=[LLMToolCall(name="test/echo", arguments={"msg": "hello"})],
            )
        return LLMResponse(content="Final answer after tool call", tool_calls=[])


class _TwoToolsLLM:
    def __init__(self) -> None:
        self._n = 0

    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        self._n += 1
        if self._n == 1:
            return LLMResponse(
                content="",
                tool_calls=[LLMToolCall(name="test/echo", arguments={"msg": "first"})],
            )
        if self._n == 2:
            return LLMResponse(
                content="",
                tool_calls=[LLMToolCall(name="test/adder", arguments={"a": 1, "b": 2})],
            )
        return LLMResponse(content="Done after two tool calls", tool_calls=[])


class _AlwaysToolsLLM:
    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        return LLMResponse(
            content="",
            tool_calls=[LLMToolCall(name="test/echo", arguments={"x": "loop"})],
        )


class _NonexistentToolLLM:
    def __init__(self) -> None:
        self._n = 0

    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        self._n += 1
        if self._n == 1:
            return LLMResponse(
                content="",
                tool_calls=[LLMToolCall(name="test/nonexistent", arguments={"x": 1})],
            )
        return LLMResponse(content="Done after error", tool_calls=[])


class _FailingToolLLM:
    def __init__(self) -> None:
        self._n = 0

    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        self._n += 1
        if self._n == 1:
            return LLMResponse(
                content="",
                tool_calls=[LLMToolCall(name="test/fail", arguments={})],
            )
        return LLMResponse(content="Done after failing tool", tool_calls=[])


class _ImmediateLLM:
    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        return LLMResponse(content="No tools needed", tool_calls=[])


class _CapturingToolLLM:
    def __init__(self) -> None:
        self._n = 0

    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        self._n += 1
        if self._n == 1:
            return LLMResponse(
                content="",
                tool_calls=[
                    LLMToolCall(name="test/capture", arguments={"data": "test"})
                ],
            )
        return LLMResponse(content="Done after capture", tool_calls=[])


class _GenericErrorToolLLM:
    def __init__(self) -> None:
        self._n = 0

    def invoke(
        self,
        prompt: str,
        tool_schemas: list[dict[str, Any]],
        tool_results: list[dict[str, Any]] | None = None,
        actor_config: dict[str, Any] | None = None,
    ) -> LLMResponse:
        self._n += 1
        if self._n == 1:
            return LLMResponse(
                content="",
                tool_calls=[LLMToolCall(name="test/generic_error", arguments={"x": 1})],
            )
        return LLMResponse(content="Done after generic error", tool_calls=[])


# ---------------------------------------------------------------------------
# Given steps — registry & runner
# ---------------------------------------------------------------------------


@given("a tool registry with an echo tool")
def step_given_registry_echo(context: Any) -> None:
    if not hasattr(context, "registry"):
        context.registry = ToolRegistry()
    with contextlib.suppress(Exception):
        context.registry.register(
            ToolSpec(
                name="test/echo", description="Echo tool", handler=_rt_echo_handler
            )
        )


@given("a tool registry with an adder tool")
def step_given_registry_adder(context: Any) -> None:
    if not hasattr(context, "registry"):
        context.registry = ToolRegistry()
    with contextlib.suppress(Exception):
        context.registry.register(
            ToolSpec(
                name="test/adder", description="Adder tool", handler=_rt_adder_handler
            )
        )


@given("a tool registry with a failing tool")
def step_given_registry_failing(context: Any) -> None:
    if not hasattr(context, "registry"):
        context.registry = ToolRegistry()
    with contextlib.suppress(Exception):
        context.registry.register(
            ToolSpec(
                name="test/fail",
                description="Failing tool",
                handler=_rt_failing_handler,
            )
        )


@given("a tool registry with an input-capturing tool")
def step_given_registry_capturing(context: Any) -> None:
    if not hasattr(context, "registry"):
        context.registry = ToolRegistry()
    with contextlib.suppress(Exception):
        context.registry.register(
            ToolSpec(
                name="test/capture",
                description="Capturing tool",
                handler=_rt_capturing_handler,
            )
        )


@given("a tool registry with a tool that raises a generic exception")
def step_given_registry_generic_error(context: Any) -> None:
    if not hasattr(context, "registry"):
        context.registry = ToolRegistry()
    with contextlib.suppress(Exception):
        context.registry.register(
            ToolSpec(
                name="test/generic_error",
                description="Generic error tool",
                handler=_rt_generic_error_handler,
            )
        )


@given("an empty actor tool registry")
def step_given_empty_registry(context: Any) -> None:
    context.registry = ToolRegistry()


@given("a tool runner for the actor registry")
def step_given_runner(context: Any) -> None:
    context.runner = ToolRunner(context.registry)


# ---------------------------------------------------------------------------
# Given steps — mock LLM callers
# ---------------------------------------------------------------------------


@given("a mock LLM caller that requests one tool call then responds")
def step_given_mock_llm_single(context: Any) -> None:
    context.llm_caller = _SingleToolLLM()


@given("a mock LLM caller that requests two sequential tool calls then responds")
def step_given_mock_llm_two(context: Any) -> None:
    context.llm_caller = _TwoToolsLLM()


@given("a mock LLM caller that always requests tool calls")
def step_given_mock_llm_always(context: Any) -> None:
    context.llm_caller = _AlwaysToolsLLM()


@given("a mock LLM caller that requests a nonexistent tool then responds")
def step_given_mock_llm_nonexistent(context: Any) -> None:
    context.llm_caller = _NonexistentToolLLM()


@given("a mock LLM caller that requests the failing tool then responds")
def step_given_mock_llm_failing(context: Any) -> None:
    context.llm_caller = _FailingToolLLM()


@given("a mock LLM caller that responds immediately without tool calls")
def step_given_mock_llm_immediate(context: Any) -> None:
    context.llm_caller = _ImmediateLLM()


@given("a mock LLM caller that requests the capturing tool then responds")
def step_given_mock_llm_capturing(context: Any) -> None:
    context.llm_caller = _CapturingToolLLM()


@given("a mock LLM caller that requests the generic-error tool then responds")
def step_given_mock_llm_generic_error(context: Any) -> None:
    context.llm_caller = _GenericErrorToolLLM()


# ---------------------------------------------------------------------------
# Given steps — runtime construction
# ---------------------------------------------------------------------------


@given("a tool-calling runtime with the mock LLM caller")
def step_given_runtime(context: Any) -> None:
    context.runtime = ToolCallingRuntime(
        registry=context.registry,
        runner=context.runner,
        llm_caller=context.llm_caller,
        event_bus=ReactiveEventBus(),
    )


@given("a tool-calling runtime with max iterations {n:d}")
def step_given_runtime_max_iter(context: Any, n: int) -> None:
    context.runtime = ToolCallingRuntime(
        registry=context.registry,
        runner=context.runner,
        llm_caller=context.llm_caller,
        max_iterations=n,
        event_bus=ReactiveEventBus(),
    )


@given("a tool-calling runtime with the mock LLM caller and router")
def step_given_runtime_with_router(context: Any) -> None:
    context.runtime = ToolCallingRuntime(
        registry=context.registry,
        runner=context.runner,
        llm_caller=context.llm_caller,
        router=context.router,
        event_bus=ReactiveEventBus(),
    )


# ---------------------------------------------------------------------------
# Given steps — actor context
# ---------------------------------------------------------------------------


@given('an actor context with plan "{plan_id}" phase "{phase}"')
def step_given_actor_ctx_plan_phase(context: Any, plan_id: str, phase: str) -> None:
    context.actor_context = ToolActorContext(plan_id=plan_id, phase=phase)


@given('an actor context with plan "{plan_id}" sandbox "{root}"')
def step_given_actor_ctx_plan_sandbox(context: Any, plan_id: str, root: str) -> None:
    context.actor_context = ToolActorContext(plan_id=plan_id, sandbox_root=root)


@given('an actor context with plan "{plan_id}"')
def step_given_actor_ctx_plan(context: Any, plan_id: str) -> None:
    context.actor_context = ToolActorContext(plan_id=plan_id)


@given('an actor context with sandbox root "{root}"')
def step_given_actor_ctx_sandbox(context: Any, root: str) -> None:
    context.actor_context = ToolActorContext(
        plan_id="plan-test",
        phase="execute",
        sandbox_root=root,
    )


@given("an actor context with resource bindings")
def step_given_actor_ctx_bindings(context: Any) -> None:
    context.actor_context = ToolActorContext(
        plan_id="plan-test",
        phase="execute",
        resource_bindings={"source": {"type": "git-checkout", "path": "/repo"}},
    )


@given("an actor context with all optional fields")
def step_given_actor_ctx_all_fields(context: Any) -> None:
    context.actor_context = ToolActorContext(
        plan_id="plan-full",
        phase="execute",
        sandbox_root="/tmp/sand",
        automation_profile="auto-profile",
        resource_bindings={"src": {"path": "/src"}},
        project_resources={"repo": "/home/repo"},
        metadata={"version": "1.0"},
    )
    # Pre-add a record so we can test clear_history
    context.actor_context.record_tool_call(
        ToolCallRecord(
            tool_name="test/dummy",
            success=True,
            duration_ms=1.0,
            iteration=1,
        )
    )


@given('a tool call router with plan id "{plan_id}"')
def step_given_router(context: Any, plan_id: str) -> None:
    context.router = ToolCallRouter(
        registry=context.registry,
        runner=context.runner,
        plan_id=plan_id,
    )


@given('a tool call record with name "{name}" and duration {duration:g}')
def step_given_tool_call_record(context: Any, name: str, duration: float) -> None:
    context.tool_call_record = ToolCallRecord(tool_name=name, duration_ms=duration)


# ---------------------------------------------------------------------------
# When steps
# ---------------------------------------------------------------------------


@when('I run the tool loop with prompt "{prompt}"')
def step_when_run_loop(context: Any, prompt: str) -> None:
    context.run_result = context.runtime.run_tool_loop(prompt=prompt)


@when('I run the tool loop with prompt "{prompt}" and the actor context')
def step_when_run_loop_with_context(context: Any, prompt: str) -> None:
    context.run_result = context.runtime.run_tool_loop(
        prompt=prompt,
        context=context.actor_context,
    )


@when('I run the tool loop with prompt "{prompt}" and no context')
def step_when_run_loop_no_context(context: Any, prompt: str) -> None:
    context.run_result = context.runtime.run_tool_loop(prompt=prompt, context=None)


@when('I record a tool call with name "{name}" and success {success}')
def step_when_record_tool_call(context: Any, name: str, success: str) -> None:
    record = ToolCallRecord(tool_name=name, success=success == "True")
    context.actor_context.record_tool_call(record)


# ---------------------------------------------------------------------------
# Then steps
# ---------------------------------------------------------------------------


@then('the run result content should be "{expected}"')
def step_then_content(context: Any, expected: str) -> None:
    result: ToolCallRunResult = context.run_result
    assert result.content == expected, f"Expected '{expected}', got '{result.content}'"


@then("the run result should have {count:d} tool call records")
def step_then_tool_call_count(context: Any, count: int) -> None:
    result: ToolCallRunResult = context.run_result
    actual = len(result.tool_call_history)
    assert actual == count, f"Expected {count} records, got {actual}"


@then("the run result iterations should be {expected:d}")
def step_then_iterations(context: Any, expected: int) -> None:
    result: ToolCallRunResult = context.run_result
    assert result.iterations == expected, (
        f"Expected {expected}, got {result.iterations}"
    )


@then("the run result should not be terminated by limit")
def step_then_not_terminated(context: Any) -> None:
    assert not context.run_result.terminated_by_limit


@then("the run result should be terminated by limit")
def step_then_terminated(context: Any) -> None:
    assert context.run_result.terminated_by_limit


@then("the first tool call record should have success {expected}")
def step_then_first_record_success(context: Any, expected: str) -> None:
    record = context.run_result.tool_call_history[0]
    assert record.success == (expected == "True")


@then("the first tool call record should have an error message")
def step_then_first_record_has_error(context: Any) -> None:
    record = context.run_result.tool_call_history[0]
    assert record.error is not None and len(record.error) > 0


@then('the first tool call record error should contain "{fragment}"')
def step_then_first_record_error_contains(context: Any, fragment: str) -> None:
    record = context.run_result.tool_call_history[0]
    assert record.error is not None
    assert fragment in record.error, f"Expected '{fragment}' in '{record.error}'"


@then('the first tool call record tool name should be "{name}"')
def step_then_first_record_name(context: Any, name: str) -> None:
    assert context.run_result.tool_call_history[0].tool_name == name


@then("the first tool call record inputs should not be empty")
def step_then_first_record_inputs(context: Any) -> None:
    assert len(context.run_result.tool_call_history[0].inputs) > 0


@then("the first tool call record output should not be empty")
def step_then_first_record_output(context: Any) -> None:
    assert len(context.run_result.tool_call_history[0].output) > 0


@then("the first tool call record duration should be greater than 0")
def step_then_first_record_duration(context: Any) -> None:
    assert context.run_result.tool_call_history[0].duration_ms >= 0.0


@then("the first tool call record iteration should be {expected:d}")
def step_then_first_record_iteration(context: Any, expected: int) -> None:
    assert context.run_result.tool_call_history[0].iteration == expected


@then('the captured tool inputs should contain sandbox root "{root}"')
def step_then_captured_sandbox(context: Any, root: str) -> None:
    assert _rt_captured_inputs.get("sandbox_root") == root


@then("the captured tool inputs should contain resource bindings")
def step_then_captured_bindings(context: Any) -> None:
    assert isinstance(_rt_captured_inputs.get("resource_bindings"), dict)


@then("creating a runtime with max iterations 0 should raise ValueError")
def step_then_invalid_max_iter(context: Any) -> None:
    try:
        ToolCallingRuntime(
            registry=context.registry,
            runner=context.runner,
            llm_caller=context.llm_caller,
            max_iterations=0,
        )
        raise AssertionError("Expected ValueError")
    except ValueError:
        pass


@then("running the tool loop with empty prompt should raise ValueError")
def step_then_empty_prompt(context: Any) -> None:
    try:
        context.runtime.run_tool_loop(prompt="")
        raise AssertionError("Expected ValueError")
    except ValueError:
        pass


@then('the actor context plan id should be "{expected}"')
def step_then_actor_plan_id(context: Any, expected: str) -> None:
    assert context.actor_context.plan_id == expected


@then('the actor context phase should be "{expected}"')
def step_then_actor_phase(context: Any, expected: str) -> None:
    assert context.actor_context.phase == expected


@then("the actor context tool call history should be empty")
def step_then_actor_history_empty(context: Any) -> None:
    assert len(context.actor_context.tool_call_history) == 0


@then("the actor context tool call history should have {count:d} records")
def step_then_actor_history_count(context: Any, count: int) -> None:
    assert len(context.actor_context.tool_call_history) == count


@then("creating a tool actor context with empty plan id should raise ValueError")
def step_then_empty_plan_id(context: Any) -> None:
    try:
        ToolActorContext(plan_id="")
        raise AssertionError("Expected ValueError")
    except ValueError:
        pass


@then('the actor context summary should contain plan id "{plan_id}"')
def step_then_summary_plan_id(context: Any, plan_id: str) -> None:
    assert context.actor_context.as_summary()["plan_id"] == plan_id


@then('the actor context summary should contain sandbox root "{root}"')
def step_then_summary_sandbox(context: Any, root: str) -> None:
    assert context.actor_context.as_summary()["sandbox_root"] == root


@then('the tool call record tool name should be "{name}"')
def step_then_record_name(context: Any, name: str) -> None:
    assert context.tool_call_record.tool_name == name


@then("the tool call record duration should be {expected:g}")
def step_then_record_duration(context: Any, expected: float) -> None:
    assert context.tool_call_record.duration_ms == expected


# -- Actor Context additional property steps --


@then('the actor context automation profile should be "{expected}"')
def step_then_actor_automation_profile(context: Any, expected: str) -> None:
    assert context.actor_context.automation_profile == expected


@then('the actor context project resources should have key "{key}"')
def step_then_actor_project_resources_key(context: Any, key: str) -> None:
    assert key in context.actor_context.project_resources


@then('the actor context metadata should have key "{key}"')
def step_then_actor_metadata_key(context: Any, key: str) -> None:
    assert key in context.actor_context.metadata


@then("the actor context clear history should empty the history")
def step_then_actor_clear_history(context: Any) -> None:
    assert len(context.actor_context.tool_call_history) > 0
    context.actor_context.clear_history()
    assert len(context.actor_context.tool_call_history) == 0


@then("recording a non-ToolCallRecord should raise TypeError")
def step_then_invalid_record_type(context: Any) -> None:
    try:
        context.actor_context.record_tool_call("not a record")  # type: ignore[arg-type]
        raise AssertionError("Expected TypeError")
    except TypeError:
        pass


# -- Runtime constructor type validation steps --


@then("creating a runtime with a non-ToolRegistry should raise TypeError")
def step_then_invalid_registry_type(context: Any) -> None:
    try:
        ToolCallingRuntime(
            registry="not a registry",  # type: ignore[arg-type]
            runner=ToolRunner(ToolRegistry()),
            llm_caller=_ImmediateLLM(),
        )
        raise AssertionError("Expected TypeError")
    except TypeError:
        pass


@then("creating a runtime with a non-ToolRunner should raise TypeError")
def step_then_invalid_runner_type(context: Any) -> None:
    try:
        ToolCallingRuntime(
            registry=context.registry,
            runner="not a runner",  # type: ignore[arg-type]
            llm_caller=_ImmediateLLM(),
        )
        raise AssertionError("Expected TypeError")
    except TypeError:
        pass


# -- Runtime property accessors steps --


@then("the runtime max iterations should be {expected:d}")
def step_then_runtime_max_iter(context: Any, expected: int) -> None:
    assert context.runtime.max_iterations == expected


@then("the runtime provider format should not be None")
def step_then_runtime_provider_format(context: Any) -> None:
    assert context.runtime.provider_format is not None