"""
pipeline-service: platform_ability — 平台内部 agent 能力包（pipeline_id=platform_general）

产线平台自身的运维/管理 agent：拥有平台应用和各模块的技能，
核心能力是「通读模型 API 文档 → 自动生成模型治理配置（供应商/适配模板/模型/定价）」。

权限模型（代码层硬门禁，不依赖 prompt）：
  所有工具 handler 入口校验调用者的 RBAC 角色 ∈ {owner.superuser, owner.admin}。
  内部 agent 只服务管理员——普通用户即使打开页面也调不动任何工具。

配置生成链路（用户给定 API 文档 → 完成配置）：
  ① fetch_model_doc：抓取文档页面（SSRF 防护：仅 http(s) 公网域名）
  ② extract_llm_api_spec：LLM 从文档提取端点/协议/请求响应格式/定价
  ③ apply_llm_config：写库——复用 pipeline-llm 模块的 CRUD 函数
     （llm_vendor.endpoints + llm_api_profile 模板 + llm_model 含四价）
"""

import json
import logging
import re

from pipeline_core import (
    ToolDefinition,
    PipelineAbility,
    register_ability,
)

logger = logging.getLogger("pipeline.platform_ability")

PLATFORM_PIPELINE_ID = "platform_general"

# 管理角色：内部 agent 仅管理员可用
ADMIN_ROLES = ("owner.superuser", "owner.admin")

# 当前运行时调用链支持的协议（llm_bridge 固定 OpenAI 兼容路径）。
# 其他协议的适配模板会存入 llm_api_profile 备查，但运行时暂不渲染。
RUNTIME_PROTOCOLS = ("openai_compat",)


# ────────────────────── 权限门禁（代码层） ──────────────────────

async def _require_admin(sor, ctx) -> str:
    """校验当前用户是管理员。返回 ''=通过，否则错误信息。"""
    uid = ctx.get("user_id", "") or ""
    if not uid:
        return "无法识别当前用户身份（未登录），内部 agent 仅管理员可用"
    recs = await sor.sqlExe(
        "SELECT r.orgtypeid, r.name FROM userrole ur JOIN role r ON ur.roleid=r.id "
        "WHERE ur.userid=${u}$", {"u": uid})
    await sor.sqlExe("COMMIT", {})
    roles = set()
    for r in (recs or []):
        o = getattr(r, "orgtypeid", "") or ""
        n = getattr(r, "name", "") or ""
        if o and n:
            roles.add("%s.%s" % (o, n))
    if roles & set(ADMIN_ROLES):
        return ""
    return "权限不足：内部 agent 工具仅管理员（%s）可用，当前角色 %s" % (
        "/".join(ADMIN_ROLES), sorted(roles) or "无")


def _row(r):
    """sqlor row → dict（容忍属性访问）。"""
    if hasattr(r, "__dict__"):
        return {k: v for k, v in r.__dict__.items() if not k.startswith("_")}
    return {}


# ────────────────────── 工具 1：模型治理状态 ──────────────────────

async def _h_platform_llm_status(sor, params, ctx):
    """供应商/账号/模型/用量概览（管理员诊断配置用）。"""
    err = await _require_admin(sor, ctx)
    if err:
        return err
    out = {}
    for tbl in ("llm_vendor", "llm_account", "llm_model"):
        recs = await sor.sqlExe(
            "SELECT status, COUNT(*) AS c FROM " + tbl + " GROUP BY status", {})
        await sor.sqlExe("COMMIT", {})
        out[tbl] = {getattr(r, "status", ""): int(getattr(r, "c", 0)) for r in (recs or [])}
    accs = await sor.sqlExe(
        "SELECT name, balance, status FROM llm_account ORDER BY balance DESC LIMIT 20", {})
    await sor.sqlExe("COMMIT", {})
    out["accounts"] = [
        {"name": getattr(r, "name", ""), "balance": float(getattr(r, "balance", 0) or 0),
         "status": getattr(r, "status", "")} for r in (accs or [])]
    models = await sor.sqlExe(
        "SELECT name, vendor_model_id, capability, price_input, price_output, status "
        "FROM llm_model ORDER BY created_at DESC LIMIT 30", {})
    await sor.sqlExe("COMMIT", {})
    out["models"] = [
        {"name": getattr(r, "name", ""), "vendor_model_id": getattr(r, "vendor_model_id", ""),
         "capability": getattr(r, "capability", ""),
         "price_input": float(getattr(r, "price_input", 0) or 0),
         "price_output": float(getattr(r, "price_output", 0) or 0),
         "status": getattr(r, "status", "")} for r in (models or [])]
    return json.dumps(out, ensure_ascii=False)


# ────────────────────── 工具 2：抓取模型 API 文档 ──────────────────────

_MAX_DOC_CHARS = 60000


def _validate_doc_url(url: str) -> str:
    """SSRF 防护：仅允许 http(s) + 公网域名。返回 ''=通过，否则错误。"""
    if not re.match(r"^https?://", url or ""):
        return "文档 URL 必须是 http/https 链接"
    host = re.sub(r"^https?://", "", url).split("/")[0].split(":")[0].lower()
    if not re.match(r"^[a-z0-9][a-z0-9.-]+\.[a-z]{2,}$", host):
        return "文档 URL 域名非法（不接受 IP/内网地址）"
    if host in ("localhost",) or host.endswith((".local", ".internal", ".localhost")):
        return "文档 URL 不允许指向内网/本地地址"
    return ""


def _html_to_text(html: str) -> str:
    """粗暴去标签提取文本（文档页面用，不追求完美排版）。"""
    txt = re.sub(r"(?is)<(script|style|noscript)[^>]*>.*?</\1>", " ", html or "")
    txt = re.sub(r"(?is)<[^>]+>", " ", txt)
    txt = re.sub(r"&nbsp;", " ", txt)
    txt = re.sub(r"&lt;", "<", txt)
    txt = re.sub(r"&gt;", ">", txt)
    txt = re.sub(r"&amp;", "&", txt)
    txt = re.sub(r"&quot;", '"', txt)
    txt = re.sub(r"[ \t]+", " ", txt)
    txt = re.sub(r"\n\s*\n+", "\n", txt)
    return txt.strip()


async def _h_fetch_model_doc(sor, params, ctx):
    """抓取模型 API 文档页面 → 纯文本（供 LLM 提取配置规格）。"""
    err = await _require_admin(sor, ctx)
    if err:
        return err
    url = (params.get("url") or "").strip()
    verr = _validate_doc_url(url)
    if verr:
        return verr
    import aiohttp
    try:
        timeout = aiohttp.ClientTimeout(total=30)
        async with aiohttp.ClientSession(timeout=timeout) as sess:
            async with sess.get(url, headers={"User-Agent": "Mozilla/5.0"},
                                allow_redirects=True, ssl=False) as resp:
                if resp.status != 200:
                    return "抓取失败：HTTP %d" % resp.status
                ctype = resp.headers.get("Content-Type", "")
                raw = await resp.text(errors="replace")
    except Exception as e:
        return "抓取失败：%s" % str(e)[:200]
    if "html" in ctype.lower() or raw.lstrip()[:15].lower().startswith(("<!doctype", "<html")):
        text = _html_to_text(raw)
    else:
        text = raw
    if len(text) > _MAX_DOC_CHARS:
        text = text[:_MAX_DOC_CHARS] + "\n[文档过长已截断，共 %d 字符]" % len(text)
    return text


# ────────────────────── 工具 3：提取配置规格（LLM） ──────────────────────

_EXTRACT_PROMPT = """你是大模型 API 配置专家。通读下面这份模型 API 文档，提取配置规格。

只输出一个 JSON 对象（不要 markdown 代码块），字段：
{
  "vendor_name": "供应商名称",
  "base_url": "API 基础地址（如 https://dashscope.aliyuncs.com/compatible-mode/v1）",
  "protocol": "openai_compat | dashscope_async | custom（能走 /chat/completions 的填 openai_compat）",
  "endpoints": [{"base_url": "...", "region": "domestic|international", "timeout": 60}],
  "chat_path": "对话接口路径（如 /chat/completions）",
  "auth_header": "认证头格式说明（如 Bearer API_KEY）",
  "request_fields": ["请求体字段名列表"],
  "response_format": "响应格式说明（content 字段路径 + usage 字段路径）",
  "models": [{"vendor_model_id": "供应商侧模型ID", "capability": "t2t|t2i|i2t|t2v|embedding|rerank|tts|asr",
              "price_input": 输入价元/千token或null, "price_output": 输出价元/千token或null,
              "cost_input": 输入成本元/千token或null, "cost_output": 输出成本元/千token或null,
              "description": "一句话说明"}],
  "doc_notes": "文档中影响配置的关键注意点"
}

定价规则：
- 文档给的单位若是「元/百万tokens」，换算为「元/千tokens」= 原价/1000，保留6位小数
- 文档没写价格的模型：价格字段填 null（禁止编造价格），在 description 注明
- cost_* 未知时与 price_* 相同（无供应商折扣时成本=售价）

文档内容：
"""


async def _h_extract_llm_api_spec(sor, params, ctx):
    """LLM 通读文档文本 → 结构化配置规格（JSON）。"""
    err = await _require_admin(sor, ctx)
    if err:
        return err
    doc_text = (params.get("doc_text") or "").strip()
    if len(doc_text) < 100:
        return "文档文本太短（<100字符），无法提取配置——先用 fetch_model_doc 抓取"
    try:
        from pipeline_service.llm_bridge import llm_call_msgs
        raw = await llm_call_msgs(
            [{"role": "system", "content": _EXTRACT_PROMPT},
             {"role": "user", "content": doc_text[:48000]}],
            temperature=0.1, org_id="0", user_id=ctx.get("user_id", ""))
    except Exception as e:
        return "LLM 提取失败：%s" % str(e)[:200]
    txt = (raw or "").strip()
    if txt.startswith("```"):
        txt = txt.split("\n", 1)[1] if "\n" in txt else txt
        txt = txt.rsplit("```", 1)[0]
    try:
        spec = json.loads(txt)
    except Exception:
        m = re.search(r"\{.*\}", txt, re.S)
        if not m:
            return "LLM 输出不是合法 JSON：%s" % txt[:300]
        try:
            spec = json.loads(m.group(0))
        except Exception:
            return "LLM 输出不是合法 JSON：%s" % txt[:300]
    return json.dumps(spec, ensure_ascii=False)


# ────────────────────── 工具 4：写入配置（幂等） ──────────────────────

def _f(v, default=0.0):
    try:
        return float(v)
    except (TypeError, ValueError):
        return default


async def _h_apply_llm_config(sor, params, ctx):
    """按提取的规格写库：供应商（复用/新建）+ 适配模板 + 模型（含定价）。

    幂等：供应商按名称复用；模型按 (vendor, vendor_model_id) 复用——
    已存在则更新定价，不重复创建。
    """
    err = await _require_admin(sor, ctx)
    if err:
        return err
    try:
        spec = json.loads(params.get("spec") or "{}")
    except Exception:
        return "spec 不是合法 JSON"
    vendor_name = (spec.get("vendor_name") or "").strip()
    if not vendor_name:
        return "spec 缺少 vendor_name"
    endpoints = spec.get("endpoints") or []
    if not endpoints and spec.get("base_url"):
        endpoints = [{"base_url": spec["base_url"], "region": "domestic", "timeout": 60}]
    if not endpoints:
        return "spec 缺少 endpoints/base_url"
    protocol = (spec.get("protocol") or "openai_compat").strip() or "openai_compat"
    models = spec.get("models") or []
    if not models:
        return "spec.models 为空——文档里没有可配置的模型？"

    from appPublic.uniqueID import getID

    # 1. 供应商：按名称复用
    recs = await sor.sqlExe(
        "SELECT id, endpoints FROM llm_vendor WHERE name=${n}$", {"n": vendor_name})
    await sor.sqlExe("COMMIT", {})
    if recs:
        vendor_id = getattr(recs[0], "id", "")
        eps_old = []
        try:
            eps_old = json.loads(getattr(recs[0], "endpoints", "") or "[]")
        except Exception:
            eps_old = []
        merged = list(eps_old)
        added_eps = []
        for ep in endpoints:
            bu = (ep.get("base_url") or "").rstrip("/")
            if bu and bu not in [(e.get("base_url") or "").rstrip("/") for e in merged]:
                merged.append({"base_url": bu, "region": ep.get("region") or "domestic",
                               "timeout": int(_f(ep.get("timeout"), 60))})
                added_eps.append(bu)
        await sor.sqlExe(
            "UPDATE llm_vendor SET endpoints=${e}$, protocol=${p}$, updated_at=NOW() "
            "WHERE id=${i}$",
            {"e": json.dumps(merged, ensure_ascii=False), "p": protocol, "i": vendor_id})
        await sor.sqlExe("COMMIT", {})
        vendor_action = "复用供应商 %s（新增端点 %d 个）" % (vendor_id, len(added_eps))
    else:
        vendor_id = getID()
        eps_norm = [{"base_url": (ep.get("base_url") or "").rstrip("/"),
                     "region": ep.get("region") or "domestic",
                     "timeout": int(_f(ep.get("timeout"), 60))} for ep in endpoints]
        await sor.C("llm_vendor", {
            "id": vendor_id, "name": vendor_name, "protocol": protocol,
            "endpoints": json.dumps(eps_norm, ensure_ascii=False),
            "description": spec.get("doc_notes", "") or "",
            "status": "active", "org_id": "0"})
        vendor_action = "新建供应商 %s（%s）" % (vendor_id, vendor_name)

    # 2. 适配模板：按 (协议×能力) 复用，缺则新建
    profile_ids = {}
    caps = sorted(set((m.get("capability") or "t2t") for m in models))
    for cap in caps:
        recs = await sor.sqlExe(
            "SELECT id FROM llm_api_profile WHERE protocol=${p}$ AND capability=${c}$ "
            "AND status='active' ORDER BY created_at DESC LIMIT 1",
            {"p": protocol, "c": cap})
        await sor.sqlExe("COMMIT", {})
        if recs:
            profile_ids[cap] = getattr(recs[0], "id", "")
            continue
        req_tpl, resp_tpl = _default_templates(protocol, cap, spec)
        pid = getID()
        await sor.C("llm_api_profile", {
            "id": pid, "name": "%s-%s-自动配置" % (protocol, cap),
            "protocol": protocol, "capability": cap,
            "request_template": req_tpl, "response_template": resp_tpl,
            "param_schema": json.dumps([{"name": "prompt", "label": "提示词",
                                         "uitype": "textarea", "required": True}],
                                       ensure_ascii=False),
            "status": "active"})
        profile_ids[cap] = pid

    # 3. 模型：按 (vendor, vendor_model_id) 幂等
    created, updated, skipped = [], [], []
    for m in models:
        vmid = (m.get("vendor_model_id") or "").strip()
        if not vmid:
            skipped.append("(缺 vendor_model_id)")
            continue
        cap = m.get("capability") or "t2t"
        price_in, price_out = _f(m.get("price_input")), _f(m.get("price_output"))
        cost_in = _f(m.get("cost_input"), price_in)
        cost_out = _f(m.get("cost_output"), price_out)
        recs = await sor.sqlExe(
            "SELECT id FROM llm_model WHERE vendor_id=${v}$ AND vendor_model_id=${m}$",
            {"v": vendor_id, "m": vmid})
        await sor.sqlExe("COMMIT", {})
        if recs:
            mid = getattr(recs[0], "id", "")
            await sor.sqlExe(
                "UPDATE llm_model SET price_input=${pi}$, price_output=${po}$, "
                "cost_input=${ci}$, cost_output=${co}$, description=${d}$, updated_at=NOW() "
                "WHERE id=${i}$",
                {"pi": price_in, "po": price_out, "ci": cost_in, "co": cost_out,
                 "d": m.get("description", "") or "", "i": mid})
            await sor.sqlExe("COMMIT", {})
            updated.append(vmid)
            continue
        mid = getID()
        await sor.C("llm_model", {
            "id": mid, "vendor_id": vendor_id, "account_id": "",
            "name": vmid, "vendor_model_id": vmid, "capability": cap,
            "sync_mode": "sync", "profile_id": profile_ids.get(cap, ""),
            "ppid": "", "price_input": price_in, "price_output": price_out,
            "cost_input": cost_in, "cost_output": cost_out,
            "default_params": "{}", "status": "active",
            "description": m.get("description", "") or "", "org_id": "0"})
        created.append(vmid)

    rt_note = ""
    if protocol not in RUNTIME_PROTOCOLS:
        rt_note = ("⚠️ 协议「%s」的适配模板已存档，但当前运行时调用链仅支持 %s——"
                   "该供应商模型暂不可被产线直接调用" % (protocol, "/".join(RUNTIME_PROTOCOLS)))
    return json.dumps({
        "vendor": vendor_action, "profiles": profile_ids,
        "models_created": created, "models_updated": updated, "models_skipped": skipped,
        "runtime_note": rt_note,
    }, ensure_ascii=False)


def _default_templates(protocol: str, capability: str, spec: dict) -> tuple:
    """生成适配模板默认值（headers/data/response）。

    OpenAI 兼容协议用平台标准模板；其他协议按文档格式生成骨架供人工微调。
    """
    chat_path = (spec.get("chat_path") or "/chat/completions").strip()
    if protocol == "openai_compat":
        req = json.dumps({
            "path": chat_path, "method": "POST",
            "headers": {"Authorization": "Bearer {{api_key}}",
                        "Content-Type": "application/json"},
            "params": {},
            "data": {"model": "{{model}}", "messages": "{{messages}}",
                     "temperature": "{{temperature}}", "stream": False},
        }, ensure_ascii=False)
        resp = json.dumps({
            "content": "choices[0].message.content",
            "usage": {"prompt_tokens": "usage.prompt_tokens",
                      "completion_tokens": "usage.completion_tokens"},
        }, ensure_ascii=False)
        return req, resp
    # 非标准协议：骨架模板（字段路径来自文档提取），标注需人工核对
    req = json.dumps({
        "path": chat_path, "method": "POST",
        "headers": {"Authorization": "Bearer {{api_key}}",
                    "Content-Type": "application/json"},
        "params": {},
        "data": {"__from_doc__": spec.get("request_fields") or []},
        "__note__": "非 openai_compat 协议骨架模板，需按文档人工核对",
    }, ensure_ascii=False)
    resp = json.dumps({
        "content": spec.get("response_format", "") or "待按文档填写",
        "__note__": "需人工核对",
    }, ensure_ascii=False)
    return req, resp


# ────────────────────── 工具 5：模块/应用信息查询 ──────────────────────

async def _h_platform_modules(sor, params, ctx):
    """列出平台已装载的业务模块（内部 agent 了解平台构成用）。"""
    err = await _require_admin(sor, ctx)
    if err:
        return err
    mods = []
    for name, title in [
        ("pipeline_core", "产线核心（会话/技能/项目）"),
        ("pipeline_service", "执行引擎（任务链/角色/治理）"),
        ("pipeline-llm", "模型治理（供应商/账号/模型/定价/记账）"),
        ("pipeline-bidding", "投标产线"),
        ("pipeline-opportunity", "商机产线"),
        ("pipeline-sdlc", "开发产线前端"),
        ("pipeline-ops", "运维"),
        ("pipeline-dist", "分销"),
        ("pipeline-task", "任务中心"),
    ]:
        try:
            __import__(name.replace("-", "_"))
            loaded = True
        except Exception:
            loaded = False
        mods.append({"module": name, "title": title, "loaded": loaded})
    return json.dumps(mods, ensure_ascii=False)


# ────────────────────── 工具定义 ──────────────────────

PLATFORM_TOOLS = [
    ToolDefinition(
        name="platform_llm_status",
        description="查看模型治理状态：供应商/账号余额/模型定价/各状态分布。用户问「模型配置状态/账号余额」时调用。仅管理员可用。",
        parameters={},
        category="platform",
    ),
    ToolDefinition(
        name="fetch_model_doc",
        description="抓取大模型供应商的 API 文档页面（返回纯文本）。配置新模型前先用此抓取官方文档。仅管理员可用。",
        parameters={"url": "文档页面 URL（必须是公网 http/https）"},
        category="platform",
    ),
    ToolDefinition(
        name="extract_llm_api_spec",
        description="通读文档文本，LLM 提取 API 配置规格（端点/协议/请求响应格式/定价）。配合 fetch_model_doc 使用。仅管理员可用。",
        parameters={"doc_text": "fetch_model_doc 返回的文档文本"},
        category="platform",
    ),
    ToolDefinition(
        name="apply_llm_config",
        description="按提取的规格写入模型治理配置：供应商/端点/适配模板/模型（含定价）。幂等——已有模型只更新定价。仅管理员可用。",
        parameters={"spec": "extract_llm_api_spec 返回的 JSON 规格"},
        category="platform",
        requires_confirmation=True,
    ),
    ToolDefinition(
        name="platform_modules",
        description="列出平台已装载的业务模块清单。用户问「平台有哪些模块」时调用。仅管理员可用。",
        parameters={},
        category="platform",
    ),
]

PLATFORM_PROMPT = """
你是产线平台的内部运维 agent，服务对象是平台管理员。

## 模型自动配置工作流（用户给你文档 URL 要求配置模型时）
1. `fetch_model_doc` 抓取官方文档页面
2. `extract_llm_api_spec` 通读文档提取配置规格——**定价只允许来自文档原文**，文档没写的价格一律 null，禁止编造
3. 把提取结果摘要给用户确认（尤其定价和端点），用户确认后
4. `apply_llm_config` 写入（幂等：已有模型只更新定价）

## 硬规则
- 定价单位统一「元/千tokens」（文档给百万价要 ÷1000）
- cost_*（供应商成本）未知时与 price_* 相同
- 非 openai_compat 协议的模型：模板会存档但运行时暂不可调用，必须如实告知
- 文档抓取失败/内容不足时如实说明，不要凭记忆编造 API 格式
- 所有工具仅管理员可用，权限报错时如实转告用户

## 平台知识
平台模块清单用 `platform_modules` 查询；技能库中「平台」相关技能（skills_library/all/ 与
pipelines/platform_general/）包含各模块的开发规范与踩坑记录，需要时用 load_skill 加载。
"""

PLATFORM_HANDLERS = {
    "platform_llm_status": _h_platform_llm_status,
    "fetch_model_doc": _h_fetch_model_doc,
    "extract_llm_api_spec": _h_extract_llm_api_spec,
    "apply_llm_config": _h_apply_llm_config,
    "platform_modules": _h_platform_modules,
}


def register_platform_ability():
    """注册平台内部 agent 能力包（幂等）。"""
    ability = PipelineAbility(
        pipeline_id=PLATFORM_PIPELINE_ID,
        name="平台内部 agent",
        tools=PLATFORM_TOOLS,
        system_prompt=PLATFORM_PROMPT,
        handlers=PLATFORM_HANDLERS,
        roles=[],
        menus=[
            {"label": "📊 模型治理", "icon": "", "url": "/pipeline-llm",
             "type": "tab"},
        ],
    )
    register_ability(ability)
    return ability


register_platform_ability()