"""Phase 2/3 tests: expressions, scheduler semantics, policies."""

from __future__ import annotations

import asyncio
from types import SimpleNamespace
from typing import Any

import pytest

from app.gateway.workflow_deep_research_adapter import WorkflowDeepResearchAdapter
from deerflow.config.workflow_config import WorkflowConfig
from deerflow.persistence.workflow_events import MemoryWorkflowEventStore
from deerflow.persistence.workflow_runs import MemoryWorkflowRunStore
from deerflow.workflows.errors import WorkflowError
from deerflow.workflows.expressions import collect_referenced_nodes, evaluate_condition, render_template, render_value
from deerflow.workflows.nodes import build_default_registry
from deerflow.workflows.runtime import (
    CancelToken,
    PersistingWorkflowEventSink,
    RunContext,
    WorkflowEngine,
    WorkflowPaused,
    WorkflowRuntimeDeps,
)
from deerflow.workflows.schemas import WorkflowGraph
from deerflow.workflows.security.http_policy import enforce_http_target
from deerflow.workflows.security.sql_policy import assert_read_only, assert_tables_allowed, enforce_limit
from deerflow.workflows.validator import validate_workflow_graph


def _graph(nodes: list[dict[str, Any]], edges: list[dict[str, Any]], **kwargs: Any) -> WorkflowGraph:
    return WorkflowGraph.model_validate(
        {
            "schemaVersion": "1.0",
            "id": "wf-test",
            "name": "test",
            "nodes": nodes,
            "edges": edges,
            **kwargs,
        }
    )


async def _run(
    graph: WorkflowGraph,
    inputs: dict[str, Any] | None = None,
    *,
    deps: WorkflowRuntimeDeps | None = None,
    resume_payload: dict[str, Any] | None = None,
    env: dict[str, Any] | None = None,
    config: WorkflowConfig | None = None,
) -> tuple[Any, list[dict[str, Any]]]:
    run_store = MemoryWorkflowRunStore()
    event_store = MemoryWorkflowEventStore()
    published: list[dict[str, Any]] = []

    async def publish(event: dict[str, Any]) -> None:
        published.append(event)

    sink = PersistingWorkflowEventSink(event_store, run_id="run-1", workflow_id=graph.id, version_id="v1", publish=publish)
    ctx = RunContext(
        run_id="run-1",
        workflow_id=graph.id,
        version_id="v1",
        owner_id="user-a",
        graph=graph,
        inputs=inputs or {},
        deps=deps or WorkflowRuntimeDeps(),
        cancel=CancelToken(),
        emit=sink.emit,
        resume_payload=resume_payload,
        env=env or {},
    )
    engine = WorkflowEngine(build_default_registry(config or WorkflowConfig()), run_store=run_store)
    result = await engine.run(ctx)
    return result, published


# ── expressions ─────────────────────────────────────────────────────────


def test_expression_rendering_and_paths() -> None:
    state = {
        "inputs": {"topic": "储能"},
        "nodes": {"n1": {"data": {"items": [{"title": "A"}, {"title": "B"}], "score": 0.9}}},
        "run": {"id": "r1"},
        "loop": {},
        "env": {},
    }
    assert render_template("主题：{{ inputs.topic }}", state) == "主题：储能"
    assert render_template("{{ nodes.n1.data.items[1].title }}", state) == "B"
    # A lone placeholder keeps the native type.
    assert render_value("{{ nodes.n1.data.score }}", state) == 0.9
    assert render_value({"a": ["{{ inputs.topic }}"]}, state) == {"a": ["储能"]}
    # Missing paths resolve to empty rather than exploding.
    assert render_template("{{ nodes.nope.data.x }}", state) == ""


def test_expression_supports_numeric_canvas_node_ids() -> None:
    state = {
        "inputs": {},
        "nodes": {"100002": {"data": {"text": "流式回复"}}},
        "run": {},
        "loop": {},
        "env": {},
    }
    assert render_template("{{ nodes.100002.data.text }}", state) == "流式回复"
    assert collect_referenced_nodes({"answer": "{{ nodes.100002.data.text }}"}) == {"100002"}


def test_expression_rejects_unknown_roots_and_code() -> None:
    state = {"inputs": {}, "nodes": {}, "run": {}, "loop": {}, "env": {}}
    with pytest.raises(WorkflowError) as exc:
        render_template("{{ __import__('os').system('id') }}", state)
    assert exc.value.code == "WORKFLOW_EXPRESSION_INVALID"
    with pytest.raises(WorkflowError):
        render_template("{{ os.environ.SECRET }}", state)


def test_condition_evaluation() -> None:
    state = {
        "inputs": {"count": 5, "tags": ["a", "b"], "name": "储能报告"},
        "nodes": {"n1": {"data": {"ok": True}}},
        "run": {},
        "loop": {"n1": 2},
        "env": {},
    }
    assert evaluate_condition("inputs.count > 3", state) is True
    assert evaluate_condition("inputs.count > 3 and nodes.n1.data.ok", state) is True
    assert evaluate_condition("inputs.count > 9 or nodes.n1.data.ok == true", state) is True
    assert evaluate_condition("'a' in inputs.tags", state) is True
    assert evaluate_condition("inputs.name contains '储能'", state) is True
    assert evaluate_condition("not nodes.n1.data.ok", state) is False
    assert evaluate_condition("loop.n1 < 5", state) is True


# ── scheduler ───────────────────────────────────────────────────────────


@pytest.mark.asyncio
async def test_start_output_skeleton_emits_ordered_events() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start", "name": "开始"},
            {"id": "end", "type": "output", "name": "输出", "config": {"mapping": {"echo": "{{ inputs.topic }}"}}},
        ],
        [{"id": "e1", "source": "start", "target": "end"}],
    )
    result, events = await _run(graph, {"topic": "储能"})
    assert result.output == {"echo": "储能"}
    seqs = [e["seq"] for e in events]
    assert seqs == sorted(seqs) and seqs[0] == 1
    kinds = [e["event"] for e in events]
    assert kinds == [
        "node.started",
        "node.completed",
        "node.started",
        "node.completed",
    ]


@pytest.mark.asyncio
async def test_condition_prunes_untaken_branch() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "gate",
                "type": "condition",
                "config": {
                    "branches": [{"name": "big", "expression": "inputs.n > 10"}],
                    "defaultBranch": "small",
                },
            },
            {"id": "big", "type": "transform", "config": {"operations": [{"op": "set", "target": "path", "value": "big"}]}},
            {"id": "small", "type": "transform", "config": {"operations": [{"op": "set", "target": "path", "value": "small"}]}},
            {"id": "end", "type": "output", "config": {"mapping": {"path": "{{ nodes.small.data.path }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "gate"},
            {"id": "e2", "source": "gate", "target": "big", "sourcePort": "big"},
            {"id": "e3", "source": "gate", "target": "small", "sourcePort": "small"},
            {"id": "e4", "source": "small", "target": "end"},
        ],
    )
    result, _ = await _run(graph, {"n": 1})
    assert result.output == {"path": "small"}
    assert "big" not in result.node_results


@pytest.mark.asyncio
async def test_parallel_fanout_joins_at_merge() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "a", "type": "transform", "config": {"operations": [{"op": "set", "target": "v", "value": "A"}]}},
            {"id": "b", "type": "transform", "config": {"operations": [{"op": "set", "target": "v", "value": "B"}]}},
            {"id": "join", "type": "merge", "config": {"strategy": "all"}},
            {"id": "end", "type": "output", "config": {"mapping": {"joined": "{{ nodes.join.data.succeeded }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "a"},
            {"id": "e2", "source": "start", "target": "b"},
            {"id": "e3", "source": "a", "target": "join"},
            {"id": "e4", "source": "b", "target": "join"},
            {"id": "e5", "source": "join", "target": "end"},
        ],
    )
    result, _ = await _run(graph)
    assert sorted(result.output["joined"]) == ["a", "b"]


@pytest.mark.asyncio
async def test_loop_reruns_body_and_respects_cap() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "body", "type": "transform", "config": {"operations": [{"op": "set", "target": "tick", "value": "1"}]}},
            {
                "id": "gate",
                "type": "loop",
                "config": {"maxIterations": 3, "continueWhen": "true", "bodyEntry": "body"},
            },
            {"id": "end", "type": "output", "config": {"mapping": {"iterations": "{{ nodes.gate.data.iteration }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "body"},
            {"id": "e2", "source": "body", "target": "gate"},
            {"id": "e3", "source": "gate", "target": "body", "sourcePort": "continue"},
            {"id": "e4", "source": "gate", "target": "end", "sourcePort": "done"},
        ],
        settings={"maxLoopIterations": 5},
    )
    result, _ = await _run(graph)
    # maxIterations=3 means the gate stops handing out the continue port at 2.
    assert result.output["iterations"] == 2


@pytest.mark.asyncio
async def test_max_steps_limit_is_enforced() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "a", "type": "transform"},
            {"id": "end", "type": "output"},
        ],
        [
            {"id": "e1", "source": "start", "target": "a"},
            {"id": "e2", "source": "a", "target": "end"},
        ],
        settings={"maxSteps": 2},
    )
    with pytest.raises(WorkflowError) as exc:
        await _run(graph)
    assert exc.value.code == "WORKFLOW_MAX_STEPS"


@pytest.mark.asyncio
async def test_human_input_pauses_then_resumes() -> None:
    nodes = [
        {"id": "start", "type": "start"},
        {
            "id": "ask",
            "type": "human_input",
            "config": {"prompt": "请确认 {{ inputs.topic }}", "formSchema": {"required": ["comment"]}, "actions": ["submit"]},
        },
        {"id": "end", "type": "output", "config": {"mapping": {"comment": "{{ nodes.ask.data.values.comment }}"}}},
    ]
    edges = [
        {"id": "e1", "source": "start", "target": "ask"},
        {"id": "e2", "source": "ask", "target": "end"},
    ]
    graph = _graph(nodes, edges)
    with pytest.raises(WorkflowPaused) as paused:
        await _run(graph, {"topic": "储能"})
    assert paused.value.node_id == "ask"
    assert paused.value.pending_input["prompt"] == "请确认 储能"
    assert paused.value.pending_input["formSchema"]["required"] == ["comment"]

    result, _ = await _run(
        graph,
        {"topic": "储能"},
        resume_payload={"nodeId": "ask", "action": "submit", "values": {"comment": "同意"}},
    )
    assert result.output == {"comment": "同意"}


@pytest.mark.asyncio
async def test_human_input_rejects_missing_required_field() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "ask", "type": "human_input", "config": {"formSchema": {"required": ["comment"]}}},
            {"id": "end", "type": "output"},
        ],
        [
            {"id": "e1", "source": "start", "target": "ask"},
            {"id": "e2", "source": "ask", "target": "end"},
        ],
    )
    with pytest.raises(WorkflowError) as exc:
        await _run(graph, resume_payload={"nodeId": "ask", "action": "submit", "values": {}})
    assert exc.value.code == "WORKFLOW_HUMAN_INPUT_INVALID"


@pytest.mark.asyncio
async def test_human_input_exposes_natural_language_reply_to_downstream_nodes() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "ask", "type": "human_input", "config": {"actions": ["submit"]}},
            {"id": "end", "type": "output", "config": {"mapping": {"reply": "{{ nodes.ask.data.values.message }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "ask"},
            {"id": "e2", "source": "ask", "target": "end"},
        ],
    )

    result, _ = await _run(
        graph,
        resume_payload={"nodeId": "ask", "action": "submit", "values": {}, "message": "目标客户是连锁零售商"},
    )

    assert result.output == {"reply": "目标客户是连锁零售商"}


@pytest.mark.asyncio
async def test_evidence_normalizer_builds_a_bounded_traceable_evidence_pack() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "sales_research",
                "type": "transform",
                "config": {"operations": [{"op": "set", "target": "text", "value": "近四周新客转化率下降 12%"}]},
            },
            {
                "id": "voc_research",
                "type": "transform",
                "config": {"operations": [{"op": "set", "target": "text", "value": "用户反馈显示结算流程复杂"}]},
            },
            {
                "id": "evidence",
                "type": "evidence_normalizer",
                "config": {
                    "sources": [
                        {"nodeId": "sales_research", "label": "销售数据"},
                        {"nodeId": "voc_research", "label": "用户反馈"},
                    ]
                },
            },
            {
                "id": "end",
                "type": "output",
                "config": {"mapping": {"evidence": "{{ nodes.evidence.data.evidencePack }}"}},
            },
        ],
        [
            {"id": "e1", "source": "start", "target": "sales_research"},
            {"id": "e2", "source": "start", "target": "voc_research"},
            {"id": "e3", "source": "sales_research", "target": "evidence"},
            {"id": "e4", "source": "voc_research", "target": "evidence"},
            {"id": "e5", "source": "evidence", "target": "end"},
        ],
    )

    result, events = await _run(graph)

    pack = result.output["evidence"]
    assert [item["role"] for item in pack["items"]] == ["销售数据", "用户反馈"]
    assert pack["items"][0]["claim"] == "近四周新客转化率下降 12%"
    assert pack["items"][0]["source"]["uri"] == "workflow://run-1/nodes/sales_research"
    assert pack["assumptions"] == [] and pack["gaps"] == []
    assert any(
        event["event"] == "node.progress"
        and event["data"].get("phase") == "evidence.normalized"
        for event in events
    )


@pytest.mark.asyncio
async def test_deep_research_writer_streams_report_and_registers_markdown_artifact() -> None:
    async def run_deep_research(**kwargs: Any) -> dict[str, Any]:
        await kwargs["on_event"](
            {"type": "phase_changed", "phase": "writing", "payload": {}}
        )
        await kwargs["on_event"](
            {"type": "report_delta", "phase": "writing", "payload": {"delta": "# 储能报告"}}
        )
        assert kwargs["topic"] == "储能"
        assert kwargs["evidence_pack"]["items"][0]["role"] == "行业研究"
        return {
            "session_id": "drs_wf_1",
            "job_id": "drj_wf_1",
            "report_markdown": "# 储能报告\n\n基于已提供材料。",
            "source_count": 1,
        }

    async def save_artifact(**kwargs: Any) -> dict[str, Any]:
        return {"id": "artifact-report", **kwargs}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "report",
                "type": "deep_research_write",
                "config": {
                    "topicTemplate": "{{ inputs.topic }}",
                    "evidenceBinding": {
                        "items": [{"claim": "市场需求上升", "role": "行业研究"}],
                    },
                    "reportInstructionTemplate": "写成正式报告",
                },
            },
            {"id": "end", "type": "output", "config": {"mapping": {"text": "{{ nodes.report.data.text }}"}}},
        ],
        [
            {"id": "s-r", "source": "start", "target": "report"},
            {"id": "r-e", "source": "report", "target": "end"},
        ],
    )

    result, events = await _run(
        graph,
        {"topic": "储能"},
        deps=WorkflowRuntimeDeps(
            run_deep_research=run_deep_research,
            save_artifact=save_artifact,
        ),
    )

    assert result.output["text"].startswith("# 储能报告")
    assert result.node_results["report"]["data"]["deepResearchJobId"] == "drj_wf_1"
    assert result.node_results["report"]["artifacts"][0]["artifact_id"] == "artifact-report"
    assert any(
        event["event"] == "node.output.delta" and event["data"].get("delta") == "# 储能报告"
        for event in events
    )


def test_deep_research_writer_requires_evidence_pack_and_rejects_nested_multi_agent() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "report", "type": "deep_research_write", "config": {"researchConfig": {"mode": "multi_agent"}}},
            {"id": "end", "type": "output"},
        ],
        [
            {"id": "s-r", "source": "start", "target": "report"},
            {"id": "r-e", "source": "report", "target": "end"},
        ],
    )
    issues = validate_workflow_graph(graph)
    assert {issue.code for issue in issues} >= {"WORKFLOW_SCHEMA_INVALID"}
    assert any("Evidence Pack" in issue.message for issue in issues)
    assert any("multi_agent" in issue.message for issue in issues)


@pytest.mark.asyncio
async def test_workflow_deep_research_adapter_reuses_durable_job_contract() -> None:
    class Sessions:
        def __init__(self) -> None:
            self.rows: dict[str, dict[str, Any]] = {}

        async def get(self, session_id: str, *, user_id: str) -> dict[str, Any] | None:
            return self.rows.get(session_id)

        async def create(self, **fields: Any) -> dict[str, Any]:
            row = {"status": "draft", "active_job_id": None, **fields}
            self.rows[row["id"]] = row
            return row

        async def update(self, session_id: str, *, user_id: str, **fields: Any) -> dict[str, Any] | None:
            row = self.rows.get(session_id)
            if row is not None:
                row.update(fields)
            return row

        async def count_active_by_user(self, *, user_id: str) -> int:
            return 0

    class Sources:
        def __init__(self) -> None:
            self.rows: list[dict[str, Any]] = []

        async def upsert(self, **fields: Any) -> dict[str, Any]:
            self.rows.append(fields)
            return fields

    class Jobs:
        def __init__(self, sessions: Sessions) -> None:
            self.sessions = sessions
            self.row: dict[str, Any] | None = None

        async def get_active_for_session(self, session_id: str, *, user_id: str) -> dict[str, Any] | None:
            return self.row if self.row and self.row["status"] not in {"completed", "failed", "cancelled"} else None

        async def try_create_or_get_active(self, **fields: Any) -> tuple[dict[str, Any], bool]:
            self.row = {"id": fields["id"], "status": "queued", "phase": "initializing", **fields}
            return self.row, True

        async def get(self, job_id: str, *, user_id: str) -> dict[str, Any] | None:
            assert self.row is not None and self.row["id"] == job_id
            self.row["status"] = "completed"
            session = self.sessions.rows[self.row["session_id"]]
            session.update({"status": "completed", "report_markdown": "# 可追溯报告"})
            return self.row

        async def request_cancel(self, job_id: str, *, user_id: str) -> None:
            raise AssertionError("test should not cancel")

    class Events:
        async def list_after(self, job_id: str, *, after: int, limit: int) -> list[dict[str, Any]]:
            return [{"seq": 1, "event_type": "report_chunk", "phase": "writing", "payload": {"delta": "# 可追溯报告"}}] if after == 0 else []

    class Dispatcher:
        nudges = 0

        def nudge(self) -> None:
            self.nudges += 1

    sessions = Sessions()
    sources = Sources()
    jobs = Jobs(sessions)
    dispatcher = Dispatcher()
    app = SimpleNamespace(
        state=SimpleNamespace(
            deep_research_session_store=sessions,
            deep_research_job_store=jobs,
            deep_research_event_store=Events(),
            deep_research_source_store=sources,
            deep_research_dispatcher=dispatcher,
            deep_research_live_hub=None,
        )
    )
    events: list[dict[str, Any]] = []

    async def on_event(event: dict[str, Any]) -> None:
        events.append(event)

    outcome = await WorkflowDeepResearchAdapter(app).run(
        run_id="run-1",
        node_id="report",
        owner_id="user-a",
        topic="储能产业趋势",
        evidence_pack={
            "items": [
                {
                    "claim": "上游研究指出储能装机需求增长。",
                    "role": "行业研究",
                    "source": {"nodeId": "research", "uri": "workflow://run-1/nodes/research"},
                }
            ]
        },
        research_config={"mode": "detailed"},
        report_instruction="写成正式报告",
        cancel=CancelToken(),
        on_event=on_event,
    )

    assert outcome["report_markdown"] == "# 可追溯报告"
    assert jobs.row is not None and jobs.row["input_snapshot"]["entry"] == "regenerate"
    assert jobs.row["input_snapshot"]["config"]["collection_mode"] == "legacy"
    assert sources.rows[0]["selected"] is True
    assert "工作流 Evidence Pack" in sources.rows[0]["raw_content"]
    assert dispatcher.nudges == 1
    assert any(event["type"] == "report_chunk" for event in events)


def test_evidence_normalizer_rejects_non_upstream_or_unknown_sources() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "evidence", "type": "evidence_normalizer", "config": {"sources": [{"nodeId": "end"}, {"nodeId": "missing"}]}},
            {"id": "end", "type": "output"},
        ],
        [
            {"id": "e1", "source": "start", "target": "evidence"},
            {"id": "e2", "source": "evidence", "target": "end"},
        ],
    )

    issues = validate_workflow_graph(graph)

    assert {issue.code for issue in issues} >= {
        "WORKFLOW_EXPRESSION_INVALID",
        "WORKFLOW_NODE_NOT_FOUND",
    }


@pytest.mark.asyncio
async def test_node_failure_can_be_tolerated_with_on_error_continue() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "boom",
                "type": "transform",
                "config": {"onError": "continue", "operations": [{"op": "not_a_real_op"}]},
            },
            {"id": "end", "type": "output", "config": {"mapping": {"ok": "true"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "boom"},
            {"id": "e2", "source": "boom", "target": "end"},
        ],
    )
    result, events = await _run(graph)
    assert result.output == {"ok": "true"}
    assert result.node_results["boom"]["metadata"]["failed"] is True
    assert any(e["event"] == "node.failed" for e in events)


@pytest.mark.asyncio
async def test_agent_node_streams_deltas_and_parses_json() -> None:
    async def run_agent(**kwargs: Any) -> dict[str, Any]:
        on_delta = kwargs["on_delta"]
        await on_delta("思考")
        await on_delta("完成")
        assert "储能" in kwargs["prompt"]
        return {"text": '```json\n{"title": "储能报告"}\n```', "usage": {"tokens": 12}}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "writer",
                "type": "agent",
                "config": {
                    "agentId": "a1",
                    "promptTemplate": "写一份关于 {{ inputs.topic }} 的报告",
                    "responseMode": "json",
                    "responseSchema": {"required": ["title"]},
                    "parallelGroupId": "round-1",
                    "roundIndex": 1,
                    "agentName": "报告撰写智能体",
                    "agentAvatarUrl": "https://assets.example.com/writer.png",
                },
            },
            {"id": "end", "type": "output", "config": {"mapping": {"title": "{{ nodes.writer.data.json.title }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "writer"},
            {"id": "e2", "source": "writer", "target": "end"},
        ],
    )
    result, events = await _run(graph, {"topic": "储能"}, deps=WorkflowRuntimeDeps(run_agent=run_agent))
    assert result.output == {"title": "储能报告"}
    deltas = [(e["data"].get("delta") or e["data"].get("text")) for e in events if e["event"] == "node.output.delta"]
    assert "".join(deltas) == "思考完成"
    assert all(e["data"].get("channel") == "answer" for e in events if e["event"] == "node.output.delta")
    started = next(event for event in events if event["event"] == "node.started" and event["nodeId"] == "writer")
    assert started["data"]["nodeKind"] == "agent"
    assert started["data"]["parallelGroupId"] == "round-1"
    assert started["data"]["roundIndex"] == 1
    assert started["data"]["agent"] == {
        "agentId": "a1",
        "name": "报告撰写智能体",
        "avatarUrl": "https://assets.example.com/writer.png",
    }


@pytest.mark.asyncio
async def test_agent_clarification_pauses_and_resume_is_routed_to_the_same_node() -> None:
    seen_resume_payloads: list[dict[str, Any] | None] = []

    async def run_agent(**kwargs: Any) -> dict[str, Any]:
        resume_payload = kwargs.get("resume_payload")
        seen_resume_payloads.append(resume_payload)
        if resume_payload is None:
            return {
                "awaiting_input": {
                    "toolCallId": "clarify-1",
                    "prompt": "请确认分析的地域范围。",
                    "actions": ["submit"],
                }
            }
        assert resume_payload["values"] == {"answer": "中国市场"}
        return {"text": "已按中国市场范围完成分析。"}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "research",
                "type": "agent",
                "config": {"agentId": "researcher", "promptTemplate": "分析 {{ inputs.topic }}"},
            },
            {"id": "end", "type": "output", "config": {"mapping": {"text": "{{ nodes.research.data.text }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "research"},
            {"id": "e2", "source": "research", "target": "end"},
        ],
    )
    deps = WorkflowRuntimeDeps(run_agent=run_agent)

    with pytest.raises(WorkflowPaused) as paused:
        await _run(graph, {"topic": "新能源车"}, deps=deps)
    assert paused.value.node_id == "research"
    assert paused.value.pending_input["toolCallId"] == "clarify-1"

    result, _events = await _run(
        graph,
        {"topic": "新能源车"},
        deps=deps,
        resume_payload={
            "nodeId": "research",
            "values": {"answer": "中国市场"},
            "message": "只分析中国市场",
        },
    )
    assert result.output == {"text": "已按中国市场范围完成分析。"}
    assert seen_resume_payloads == [None, {"nodeId": "research", "values": {"answer": "中国市场"}, "message": "只分析中国市场"}]


@pytest.mark.asyncio
async def test_agent_node_includes_rendered_workflow_input_bindings() -> None:
    seen: dict[str, Any] = {}

    async def run_agent(**kwargs: Any) -> dict[str, Any]:
        seen.update(kwargs)
        return {"text": "已按任务完成"}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "writer",
                "type": "agent",
                "config": {
                    "agentId": "a1",
                    "promptTemplate": "请完成用户的请求。",
                    "inputBindings": {
                        "task": "{{ inputs.query }}",
                        "allInputs": "{{ inputs }}",
                    },
                },
            },
            {"id": "end", "type": "output", "config": {"mapping": {"text": "{{ nodes.writer.data.text }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "writer"},
            {"id": "e2", "source": "writer", "target": "end"},
        ],
    )

    result, _ = await _run(
        graph,
        {"query": "分析本周销售数据", "region": "华东"},
        deps=WorkflowRuntimeDeps(run_agent=run_agent),
    )

    assert result.output == {"text": "已按任务完成"}
    assert '"task": "分析本周销售数据"' in seen["prompt"]
    assert '"region": "华东"' in seen["prompt"]
    assert "<workflow-input>" in seen["prompt"]


@pytest.mark.asyncio
async def test_agent_node_receives_feedback_only_when_its_revision_targets_it() -> None:
    prompts: list[str] = []

    async def run_agent(**kwargs: Any) -> dict[str, Any]:
        prompts.append(kwargs["prompt"])
        return {"text": "已修订"}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "research", "type": "agent", "config": {"agentId": "a1", "promptTemplate": "分析 {{ inputs.topic }}"}},
            {"id": "other", "type": "agent", "config": {"agentId": "a2", "promptTemplate": "不应接收反馈"}},
            {"id": "end", "type": "output", "config": {"mapping": {"text": "{{ nodes.research.data.text }}"}}},
        ],
        [
            {"id": "s-r", "source": "start", "target": "research"},
            {"id": "s-o", "source": "start", "target": "other"},
            {"id": "r-e", "source": "research", "target": "end"},
        ],
    )
    await _run(
        graph,
        {"topic": "储能"},
        deps=WorkflowRuntimeDeps(run_agent=run_agent),
        env={"nodeFeedback": {"research": {"message": "请改从成本和风险角度分析"}}},
    )

    feedback_prompt = next(prompt for prompt in prompts if "分析" in prompt)
    other_prompt = next(prompt for prompt in prompts if "不应接收反馈" in prompt)
    assert "<workflow-user-feedback>" in feedback_prompt
    assert "成本和风险" in feedback_prompt
    assert "<workflow-user-feedback>" not in other_prompt


@pytest.mark.asyncio
async def test_missing_capability_becomes_typed_error() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "writer", "type": "agent", "config": {"agentId": "a1", "promptTemplate": "hi"}},
        ],
        [{"id": "e1", "source": "start", "target": "writer"}],
    )
    with pytest.raises(WorkflowError) as exc:
        await _run(graph)
    assert exc.value.code == "WORKFLOW_RESOURCE_MISSING"


@pytest.mark.asyncio
async def test_cancellation_stops_the_run() -> None:
    run_store = MemoryWorkflowRunStore()
    event_store = MemoryWorkflowEventStore()
    graph = _graph(
        [{"id": "start", "type": "start"}, {"id": "end", "type": "output"}],
        [{"id": "e1", "source": "start", "target": "end"}],
    )
    sink = PersistingWorkflowEventSink(event_store, run_id="run-x", workflow_id=graph.id, version_id="v1")
    cancel = CancelToken()
    cancel.cancel()
    ctx = RunContext(
        run_id="run-x",
        workflow_id=graph.id,
        version_id="v1",
        owner_id="u",
        graph=graph,
        inputs={},
        deps=WorkflowRuntimeDeps(),
        cancel=cancel,
        emit=sink.emit,
    )
    engine = WorkflowEngine(build_default_registry(), run_store=run_store)
    with pytest.raises(WorkflowError) as exc:
        await engine.run(ctx)
    assert exc.value.code == "WORKFLOW_CANCELLED"


# ── policies ────────────────────────────────────────────────────────────


def test_sql_policy_blocks_writes_and_stacked_statements() -> None:
    assert assert_read_only("SELECT id FROM t WHERE x = :x").startswith("SELECT")
    assert assert_read_only("WITH c AS (SELECT 1) SELECT * FROM c").startswith("WITH")
    for bad in (
        "DELETE FROM t",
        "SELECT 1; DROP TABLE t",
        "SELECT 1 -- ;\n; DROP TABLE t",
        "SELECT * FROM t INTO OUTFILE '/tmp/x'",
        "SELECT pg_sleep(10)",
        "UPDATE t SET a = 1",
    ):
        with pytest.raises(WorkflowError) as exc:
            assert_read_only(bad)
        assert exc.value.code == "WORKFLOW_SQL_POLICY_DENIED"


def test_sql_limit_is_appended_once() -> None:
    assert enforce_limit("SELECT 1", 10) == "SELECT 1 LIMIT 10"
    assert enforce_limit("SELECT 1 LIMIT 5", 10) == "SELECT 1 LIMIT 5"


def test_sql_table_allowlist_blocks_unlisted_tables() -> None:
    assert_tables_allowed("SELECT id FROM report_source", ["report_source"])
    with pytest.raises(WorkflowError) as exc:
        assert_tables_allowed("SELECT id FROM secrets", ["report_source"])
    assert exc.value.code == "WORKFLOW_SQL_POLICY_DENIED"


def test_downstream_node_reference_is_rejected_at_publish() -> None:
    issues = validate_workflow_graph(
        {
            "schemaVersion": "1.0",
            "id": "wf_ref",
            "nodes": [
                {"id": "start", "type": "start"},
                {
                    "id": "early",
                    "type": "transform",
                    "config": {"operations": [{"op": "set", "target": "x", "value": "{{ nodes.late.data.x }}"}]},
                },
                {
                    "id": "late",
                    "type": "transform",
                    "config": {"operations": [{"op": "set", "target": "x", "value": "1"}]},
                },
                {"id": "end", "type": "output", "config": {"mapping": {"x": "{{ nodes.late.data.x }}"}}},
            ],
            "edges": [
                {"id": "e1", "source": "start", "target": "early"},
                {"id": "e2", "source": "early", "target": "late"},
                {"id": "e3", "source": "late", "target": "end"},
            ],
        }
    )
    assert any(i.code == "WORKFLOW_EXPRESSION_INVALID" and i.node_id == "early" for i in issues)


@pytest.mark.asyncio
async def test_http_policy_blocks_private_and_metadata_targets() -> None:
    policy = WorkflowConfig().http
    for url in (
        "http://127.0.0.1:8001/admin",
        "http://169.254.169.254/latest/meta-data/",
        "http://localhost/",
        "file:///etc/passwd",
        "http://example.com:22/",
    ):
        with pytest.raises(WorkflowError) as exc:
            await enforce_http_target(url, policy)
        assert exc.value.code in ("WORKFLOW_HTTP_POLICY_DENIED", "WORKFLOW_HTTP_FAILED")


@pytest.mark.asyncio
async def test_http_policy_allows_private_when_configured() -> None:
    policy = WorkflowConfig().http.model_copy(update={"allow_private_networks": True, "allowed_ports": [8001]})
    target = await enforce_http_target("http://127.0.0.1:8001/ping", policy)
    assert target["host"] == "127.0.0.1"


@pytest.mark.asyncio
async def test_event_sink_persists_before_publishing() -> None:
    store = MemoryWorkflowEventStore()
    seen: list[int] = []

    async def publish(event: dict[str, Any]) -> None:
        # Persisted rows must already be readable when the live copy arrives.
        rows = await store.list_after("r1", after_seq=0)
        seen.append(len(rows))

    sink = PersistingWorkflowEventSink(store, run_id="r1", workflow_id="w1", version_id="v1", publish=publish)
    await sink.emit("run.started")
    await sink.emit("run.completed")
    assert seen == [1, 2]
    assert [r["seq"] for r in await store.list_after("r1")] == [1, 2]


@pytest.mark.asyncio
async def test_run_store_lease_and_idempotency() -> None:
    from datetime import UTC, datetime, timedelta

    store = MemoryWorkflowRunStore()
    payload = {
        "workflow_id": "w1",
        "workflow_version_id": "v1",
        "owner_id": "u1",
        "idempotency_key": "k1",
        "input": {"a": 1},
    }
    run, created = await store.create_run(payload)
    assert created is True
    again, created_again = await store.create_run(payload)
    assert created_again is False and again["id"] == run["id"]

    until = datetime.now(UTC) + timedelta(seconds=30)
    claimed = await store.claim_run(run["id"], lease_owner="w-a", lease_until=until)
    assert claimed is not None and claimed["status"] == "running"
    # A second worker cannot steal a live lease.
    assert await store.claim_run(run["id"], lease_owner="w-b", lease_until=until) is None
    assert await store.renew_lease(run["id"], lease_owner="w-a", lease_until=until) is True
    assert await store.renew_lease(run["id"], lease_owner="w-b", lease_until=until) is False

    # Expired lease is reclaimable (crash recovery).
    await store.renew_lease(run["id"], lease_owner="w-a", lease_until=datetime.now(UTC) - timedelta(seconds=1))
    assert await store.claim_run(run["id"], lease_owner="w-b", lease_until=until) is not None

    paused = await store.set_awaiting_input(run["id"], lease_owner="w-b", pending_input={"nodeId": "ask"}, resume_token="t1")
    assert paused is not None and paused["status"] == "awaiting_input"
    assert await store.consume_resume_token(run["id"], "wrong") is None
    resumed = await store.consume_resume_token(run["id"], "t1")
    assert resumed is not None and resumed["status"] == "queued"
    # One-shot: the same token cannot be replayed.
    assert await store.consume_resume_token(run["id"], "t1") is None


@pytest.mark.asyncio
async def test_code_node_disabled_by_default() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {"id": "calc", "type": "code", "config": {"source": "output['x'] = 1"}},
        ],
        [{"id": "e1", "source": "start", "target": "calc"}],
    )
    with pytest.raises(WorkflowError) as exc:
        await _run(graph)
    assert exc.value.code == "WORKFLOW_CODE_SANDBOX_FAILED"


@pytest.mark.asyncio
async def test_code_node_executes_when_enabled() -> None:
    config = WorkflowConfig()
    config.code.enabled = True
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "calc",
                "type": "code",
                "config": {
                    "source": "output['doubled'] = inputs['n'] * 2",
                    "inputs": {"n": "{{ inputs.n }}"},
                },
            },
            {"id": "end", "type": "output", "config": {"mapping": {"doubled": "{{ nodes.calc.data.doubled }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "calc"},
            {"id": "e2", "source": "calc", "target": "end"},
        ],
    )
    result, _ = await _run(graph, {"n": 21}, config=config)
    assert result.output == {"doubled": 42}


@pytest.mark.asyncio
async def test_code_node_cannot_open_sockets() -> None:
    config = WorkflowConfig()
    config.code.enabled = True
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "calc",
                "type": "code",
                "config": {"source": "import socket\nsocket.socket()"},
            },
        ],
        [{"id": "e1", "source": "start", "target": "calc"}],
    )
    with pytest.raises(WorkflowError) as exc:
        await _run(graph, config=config)
    assert exc.value.code == "WORKFLOW_CODE_SANDBOX_FAILED"


def test_asyncio_smoke() -> None:
    # Guards against an event-loop policy regression on Windows runners.
    assert asyncio.get_event_loop_policy() is not None


@pytest.mark.asyncio
async def test_skill_node_invokes_agent_with_restricted_skills() -> None:
    seen: dict[str, Any] = {}

    async def run_agent(**kwargs: Any) -> dict[str, Any]:
        seen.update(kwargs)
        return {"text": "已完成检索", "thread_id": "thr-1"}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "skill",
                "type": "skill",
                "config": {
                    "agentId": "collector",
                    "skillNames": ["web_search"],
                    "promptTemplate": "查 {{ inputs.topic }}",
                    "mode": "agent_skill",
                },
            },
            {"id": "end", "type": "output", "config": {"mapping": {"text": "{{ nodes.skill.data.text }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "skill"},
            {"id": "e2", "source": "skill", "target": "end"},
        ],
    )
    result, _published = await _run(graph, {"topic": "储能"}, deps=WorkflowRuntimeDeps(run_agent=run_agent))
    assert result.output == {"text": "已完成检索"}
    assert seen["agent_id"] == "collector"
    assert seen["skill_names"] == ["web_search"]
    assert "储能" in seen["prompt"]


@pytest.mark.asyncio
async def test_callable_skill_mode_is_rejected() -> None:
    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "skill",
                "type": "skill",
                "config": {"agentId": "collector", "skillNames": ["web_search"], "mode": "callable_skill"},
            },
        ],
        [{"id": "e1", "source": "start", "target": "skill"}],
    )
    with pytest.raises(WorkflowError) as exc:
        await _run(graph)
    assert exc.value.code == "WORKFLOW_SKILL_FAILED"


@pytest.mark.asyncio
async def test_subworkflow_node_folds_child_output() -> None:
    async def run_subworkflow(**kwargs: Any) -> dict[str, Any]:
        assert kwargs["workflow_id"] == "child-wf"
        assert kwargs["version_id"] == "child-v1"
        assert kwargs["inputs"] == {"topic": "储能"}
        return {"run_id": "child-run", "status": "completed", "output": {"title": "子报告"}}

    graph = _graph(
        [
            {"id": "start", "type": "start"},
            {
                "id": "child",
                "type": "subworkflow",
                "config": {
                    "workflowId": "child-wf",
                    "versionId": "child-v1",
                    "inputMapping": {"topic": "{{ inputs.topic }}"},
                },
            },
            {"id": "end", "type": "output", "config": {"mapping": {"title": "{{ nodes.child.data.title }}"}}},
        ],
        [
            {"id": "e1", "source": "start", "target": "child"},
            {"id": "e2", "source": "child", "target": "end"},
        ],
    )
    result, _ = await _run(graph, {"topic": "储能"}, deps=WorkflowRuntimeDeps(run_subworkflow=run_subworkflow))
    assert result.output == {"title": "子报告"}