from __future__ import annotations

from types import SimpleNamespace

import pytest
from fastapi import FastAPI
from httpx import ASGITransport, AsyncClient

from app.api.ai_steward_api import routes_capture
from app.api.ai_steward_api.schemas import ProjectFromTextResponse
from app.core.database import get_db
from app.dependencies.auth import get_current_user
from app.dependencies.tenant import get_tenant_id
from app.services.ai_steward_service import AIStewardService


@pytest.mark.asyncio
async def test_project_from_text_returns_enveloped_signal_sources(monkeypatch) -> None:
    async def fake_create_project_from_natural_language(self, **kwargs):  # noqa: ANN001
        _ = (self, kwargs)
        return {
            "project": {"id": "11", "name": "AI 客服", "title": "AI 客服平台", "description": "demo", "status": "active"},
            "signal": {"id": "21", "content": "main signal", "impact_score": 0.91},
            "charter": {"id": "31", "title": "宪章", "content": {"summary": "demo"}},
            "tasks": [],
            "risks": [],
            "analysis": {
                "project_name": "AI 客服",
                "project_title": "AI 客服平台",
                "tech_stack": ["FastAPI", "React"],
                "timeline": "3 周",
                "primary_role": "backend",
                "requirement_items": [
                    {
                        "section": "核心痛点",
                        "title": "内容本地化",
                        "description": "翻译公司贵、慢、不地道",
                    }
                ],
            },
            "signal_sources": [
                {
                    "id": "101",
                    "source_kind": "custom",
                    "source_name": "核心痛点 - 内容本地化",
                    "source_identifier": "custom:core-pain-content-localization",
                    "display_source_kind": "自定义来源",
                    "technical_identifier": "custom:core-pain-content-localization",
                    "description": "翻译公司贵、慢、不地道",
                    "section": "核心痛点",
                }
            ],
        }

    async def _fake_get_db():
        yield object()

    monkeypatch.setattr(AIStewardService, "create_project_from_natural_language", fake_create_project_from_natural_language)

    app = FastAPI()
    app.include_router(routes_capture.router)
    app.dependency_overrides[get_db] = _fake_get_db
    app.dependency_overrides[get_tenant_id] = lambda: 1
    app.dependency_overrides[get_current_user] = lambda: SimpleNamespace(
        id=9,
        tenant_id=1,
        name="管理员",
        username="admin",
        role="ADMIN",
    )

    transport = ASGITransport(app=app)
    async with AsyncClient(transport=transport, base_url="http://test") as client:
        response = await client.post("/ai-steward/project-from-text", json={"input_text": "我们要做一个 AI 客服工具"})

    assert response.status_code == 200
    payload = response.json()
    assert payload["code"] == 0
    assert payload["message"] == "success"
    assert payload["data"]["project"]["id"] == "11"
    assert payload["data"]["signal_sources"][0]["source_name"] == "核心痛点 - 内容本地化"
    assert payload["data"]["signal_sources"][0]["display_source_kind"] == "自定义来源"
    assert payload["data"]["signal_sources"][0]["technical_identifier"] == "custom:core-pain-content-localization"


def test_project_from_text_response_schema_exposes_signal_source_display_fields() -> None:
    schema = ProjectFromTextResponse.model_json_schema()
    signal_source = schema["$defs"]["ProjectFromTextSignalSource"]

    assert "display_source_kind" in signal_source["properties"]
    assert "technical_identifier" in signal_source["properties"]


@pytest.mark.asyncio
async def test_project_requirement_analysis_uses_canonical_function_name(monkeypatch) -> None:
    service = AIStewardService(object())
    captured: dict[str, object] = {}

    async def fake_generate(prompt: str, **kwargs):  # noqa: ANN001
        _ = prompt
        captured["function_name"] = kwargs.get("function_name")
        return '{"project_title":"AI 客服","requirement_items":[]}'

    monkeypatch.setattr(service.llm, "generate", fake_generate)

    analysis = await service._analyze_project_input("请创建一个 AI 客服项目", tenant_id=1)

    assert analysis["project_title"] == "AI 客服"
    assert captured["function_name"] == "project_requirement_extraction"