"""
AIGC-Channel 平台实现（9 个中文平台）

后端：aigc-channel.aiddit.com
平台：xhs / gzh / sph / github / toutiao / douyin / bili / zhihu / weibo
"""

import json
import re
from typing import Any, Dict, List, Optional

import httpx

from agent.tools.models import ToolResult
from agent.tools.utils.image import build_image_grid, encode_base64, load_images
from agent.tools.builtin.content.registry import (
    PlatformDef, ParamSpec, register_platform,
)

BASE_URL = "http://aigc-channel.aiddit.com/aigc/channel"
DEFAULT_TIMEOUT = 60.0

# aigc-channel returns search-highlighted titles like
# '<em class="highlight">关键词</em>'. Strip before any rendering / scoring use.
_HTML_TAG_RE = re.compile(r"<[^>]+>")


def _strip_html(text: Optional[str]) -> str:
    if not text:
        return ""
    return _HTML_TAG_RE.sub("", text)


_SPH_TITLE_MAX = 20  # sph normalized title 截断字符数


def _normalize_sph_post(post: Dict[str, Any]) -> None:
    """In-place: 视频号没有独立 title，后端把 caption 塞进 title 字段而 body_text 留空。

    把整段 title 搬到 body_text，title 取剥 HTML 后前 20 字 + '...' 作为短摘要。
    幂等：如果 body_text 已经有内容则不动，避免重复迁移或覆盖；title 已经 <=20 字
    也不强加省略号。
    """
    if not isinstance(post, dict):
        return
    raw_title = post.get("title") or ""
    body = post.get("body_text") or ""
    body = body.strip() if isinstance(body, str) else ""
    if not raw_title or body:
        return
    clean = _strip_html(raw_title).strip()
    if not clean:
        return
    post["body_text"] = clean
    if len(clean) > _SPH_TITLE_MAX:
        post["title"] = clean[:_SPH_TITLE_MAX] + "..."
    else:
        post["title"] = clean


# ── 平台注册 ──

_XHS_SEARCH_PARAMS = {
    "sort_type": ParamSpec(
        values=["综合排序", "最新发布", "最多点赞"],
        default="综合排序",
    ),
    "publish_time": ParamSpec(
        values=["不限", "近1天", "近7天", "近30天"],
        default="不限",
    ),
    "content_type": ParamSpec(
        values=["不限", "图文", "视频", "文章"],
        default="不限",
    ),
    "filter_note_range": ParamSpec(
        values=["不限", "1分钟以内", "1-5分钟", "5分钟以上"],
        default="不限",
        note="仅视频内容生效",
    ),
}

_COMMON_CONTENT_TYPE = {
    "content_type": ParamSpec(
        values=["视频", "图文"],
        default="",
        note="留空不限",
    ),
}

# 9 个中文平台定义
_AIGC_PLATFORMS = [
    PlatformDef(id="xhs",     name="小红书",   aliases=["RED", "xiaohongshu"], search_params=_XHS_SEARCH_PARAMS, supports_suggest=True),
    PlatformDef(id="gzh",     name="公众号",   aliases=["微信公众号", "wechat"], search_params=_COMMON_CONTENT_TYPE),
    PlatformDef(id="sph",     name="视频号",   aliases=["微信视频号"], search_params=_COMMON_CONTENT_TYPE),
    PlatformDef(id="github",  name="GitHub",   aliases=["gh"], search_params=_COMMON_CONTENT_TYPE),
    PlatformDef(id="toutiao", name="头条",     aliases=["今日头条", "toutiao"], search_params=_COMMON_CONTENT_TYPE, supports_suggest=True),
    PlatformDef(id="douyin",  name="抖音",     aliases=["TikTok"], search_params=_COMMON_CONTENT_TYPE, supports_suggest=True),
    PlatformDef(id="bili",    name="B站",      aliases=["哔哩哔哩", "bilibili"], search_params=_COMMON_CONTENT_TYPE, supports_suggest=True),
    PlatformDef(id="zhihu",   name="知乎",     aliases=[], search_params=_COMMON_CONTENT_TYPE, supports_suggest=True),
    PlatformDef(id="weibo",   name="微博",     aliases=["sina"], search_params=_COMMON_CONTENT_TYPE),
]

# suggest API 额外支持 wx（微信搜一搜），但它不是搜索平台
_SUGGEST_ONLY_CHANNELS = {"wx": "微信"}


# ── 搜索实现 ──

async def search(
    platform_id: str,
    keyword: str,
    max_count: int = 20,
    cursor: str = "",
    extras: Optional[Dict[str, Any]] = None,
) -> ToolResult:
    """AIGC-Channel 统一搜索"""
    extras = extras or {}

    if platform_id == "xhs":
        payload = {
            "type": platform_id,
            "keyword": keyword,
            "cursor": cursor,
            "content_type": extras.get("content_type", "不限"),
            "sort_type": extras.get("sort_type", "综合排序"),
            "publish_time": extras.get("publish_time", "不限"),
            "filter_note_range": extras.get("filter_note_range", "不限"),
        }
    else:
        payload = {
            "type": platform_id,
            "keyword": keyword,
            "cursor": cursor or "0",
            "max_count": max_count,
            "content_type": extras.get("content_type", ""),
        }

    try:
        async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as client:
            response = await client.post(
                f"{BASE_URL}/data",
                json=payload,
                headers={"Content-Type": "application/json"},
            )
            response.raise_for_status()
            data = response.json()
    except httpx.HTTPStatusError as e:
        return ToolResult(title="搜索失败", output="", error=f"HTTP {e.response.status_code}: {e.response.text}")
    except Exception as e:
        return ToolResult(title="搜索失败", output="", error=str(e))

    posts = data.get("data", [])

    # sph 字段 normalization：title 太长（后端把 caption 塞进 title），
    # 把它搬到 body_text，title 取前 20 字。在评分 / summary / cache 之前做。
    if platform_id == "sph":
        for p in posts:
            _normalize_sph_post(p)

    # 构建概览摘要
    summary_list = []

    # 动态导入评价模块
    try:
        from examples.process_pipeline.script.evaluate_source_quality import SourceQualityEvaluator
        evaluator = SourceQualityEvaluator()
    except ImportError:
        evaluator = None

    # 视频帖在评分前先并发探测 mp4 duration（HTTP Range，不下载视频流），
    # 让 evaluator 用真实时长替代 body 长度作为内容信号。
    if evaluator and posts:
        try:
            from agent.tools.builtin.content.transcription import probe_durations_for_posts
            await probe_durations_for_posts(platform_id, posts, concurrency=8)
        except Exception as e:
            import logging
            logging.getLogger(__name__).info("duration probe failed: %s", e)

    for idx, post in enumerate(posts, 1):
        body = post.get("body_text", "") or ""
        title = post.get("title") or body[:20] or ""
        
        score_info = {}
        if evaluator:
            try:
                eval_res = evaluator.evaluate_post(post)
                score_info = {
                    "quality_score": eval_res["total_score"],
                    "quality_grade": eval_res["grade"]
                }
                post["_quality_score"] = eval_res["total_score"]
                post["_quality_grade"] = eval_res["grade"]
            except Exception:
                pass
                
        summary_item = {
            "index": idx,
            "title": title,
            "body_text": body[:100] + ("..." if len(body) > 100 else ""),
            "like_count": post.get("like_count"),
            "comment_count": post.get("comment_count"),
            "channel": post.get("channel"),
            "link": post.get("link"),
            "content_type": post.get("content_type"),
        }
        summary_item.update(score_info)
        summary_list.append(summary_item)

    # 封面拼图
    images = []
    try:
        collage_obj = await _build_collage(posts)
        if collage_obj:
            images.append(collage_obj)
    except Exception as e:
        import logging
        logging.getLogger(__name__).warning("Error generating collage: %s", e)

    return ToolResult(
        title=f"搜索: {keyword} ({platform_id})",
        output=json.dumps({"data": summary_list}, ensure_ascii=False, indent=2),
        long_term_memory=f"Searched '{keyword}' on {platform_id}, {len(posts)} results. Use content_detail to view full details.",
        images=images,
        metadata={"posts": posts},  # 完整数据传给上层缓存
    )


# ── 详情实现（从缓存获取，不需要额外 HTTP） ──

MAX_DETAIL_IMAGES = 10  # detail 中保留的图片总数上限（含拼图）
KEEP_INDIVIDUAL = 8     # 单张图片保留数量；剩余图片合并为 1 张拼图


async def _build_images_collage(urls: List[str]) -> Optional[Dict[str, Any]]:
    """将一组图片 URL 拼成单张网格图"""
    if not urls:
        return None

    loaded = await load_images(urls)
    valid_images = [img for (_, img) in loaded if img is not None]
    if not valid_images:
        return None

    grid = build_image_grid(images=valid_images, labels=None)
    import io
    buf = io.BytesIO()
    grid.save(buf, format="PNG")
    img_bytes = buf.getvalue()

    try:
        from agent.tools.builtin.file.image_cdn import _upload_bytes_to_oss
        import hashlib

        md5_hash = hashlib.md5(img_bytes).hexdigest()[:12]
        filename = f"collage_detail_{md5_hash}.png"
        cdn_url = await _upload_bytes_to_oss(img_bytes, filename)
        return {"type": "url", "url": cdn_url}
    except Exception as e:
        import logging
        logging.getLogger(__name__).warning("Failed to upload detail collage to CDN: %s", e)
        b64, _ = encode_base64(grid, format="PNG")
        return {"type": "base64", "media_type": "image/png", "data": b64}


async def detail(
    post: Dict[str, Any],
    extras: Optional[Dict[str, Any]] = None,
    platform_id: str = "",
) -> ToolResult:
    """返回单条帖子的完整内容；sph/douyin 视频会通过 Deepgram 自动转写。"""
    title = post.get("title") or post.get("body_text", "")[:30] or "无标题"

    img_urls = [u for u in post.get("images", []) if u]
    images = []
    if len(img_urls) > MAX_DETAIL_IMAGES:
        # 保留前 KEEP_INDIVIDUAL 张原图，剩余拼成 1 张网格图
        for u in img_urls[:KEEP_INDIVIDUAL]:
            images.append({"type": "url", "url": u})
        collage = await _build_images_collage(img_urls[KEEP_INDIVIDUAL:])
        if collage:
            images.append(collage)
    else:
        for u in img_urls:
            images.append({"type": "url", "url": u})

    # 视频字幕：任何 aigc-channel 平台只要 post.videos 字段非空就触发 Deepgram 转写。
    # 下载策略在 transcription._download_video 里按 platform 分支，未指定的平台走
    # "yt-dlp on page URL → httpx direct" 两步兜底。
    #
    # 三态语义（跟 extract_sources._needs_transcribe 对齐）：
    #   字段缺失     → 没尝试过，跑 Deepgram
    #   字段 = ""    → 尝试过但失败，跳过（保护 Deepgram 额度）
    #   字段 = text  → 已成功，复用
    extras_d = extras or {}
    has_video = bool(post.get("videos"))
    field_present = "video_transcript" in post
    transcript_text: Optional[str] = post.get("video_transcript") or None

    if (
        not field_present
        and has_video
        and extras_d.get("include_transcript", True)
    ):
        from agent.tools.builtin.content.transcription import transcribe_video_from_post
        transcribe_error: Optional[str] = None
        try:
            transcript_text = await transcribe_video_from_post(platform_id, post)
        except Exception as e:
            transcript_text = None
            transcribe_error = f"{type(e).__name__}: {e}"
            import logging as _logging
            _logging.getLogger(__name__).warning(
                "transcribe_video_from_post raised for %s: %s", platform_id, e
            )

        # 三态写回：成功 = text；失败/None = "" 作为"已尝试"标记，下次 cache hit 直接短路。
        final_value = transcript_text or ""
        post["video_transcript"] = final_value
        if not final_value:
            # 失败原因暴露到 output JSON，方便 agent/用户判断要不要重试或换平台
            post["_transcribe_error"] = (
                transcribe_error
                or "transcribe returned None (下载/抽音/Deepgram 任一步失败，见 logger.warning)"
            )

        # cache writeback 不再以"成功"为前提：失败的 "" 也写回，让下次 cache hit 短路掉
        import os as _os
        from agent.tools.builtin.content import cache as _cache
        trace_id = extras_d.get("__trace_id__") or _os.getenv("TRACE_ID")
        content_id = (
            post.get("channel_content_id")
            or post.get("content_id")
            or post.get("video_id")
        )
        if trace_id and content_id:
            _cache.update_post_field(
                trace_id, platform_id, content_id, "video_transcript", final_value
            )

    # transcript already embedded as post["video_transcript"] inside the JSON dump;
    # no need to repeat as a separate section.
    output_text = json.dumps(post, ensure_ascii=False, indent=2)

    memory_suffix = " +transcript" if transcript_text else ""
    return ToolResult(
        title=f"详情: {title}",
        output=output_text,
        long_term_memory=f"Viewed detail: {title}{memory_suffix}",
        images=images,
    )


# ── 建议词实现 ──

async def suggest(channel: str, keyword: str) -> ToolResult:
    """获取搜索建议词"""
    try:
        async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as client:
            response = await client.post(
                f"{BASE_URL}/suggest",
                json={"type": channel, "keyword": keyword},
                headers={"Content-Type": "application/json"},
            )
            response.raise_for_status()
            data = response.json()
    except Exception as e:
        return ToolResult(title="建议词获取失败", output="", error=str(e))

    suggestion_count = sum(len(item.get("list", [])) for item in data.get("data", []))
    return ToolResult(
        title=f"建议词: {keyword} ({channel})",
        output=json.dumps(data, ensure_ascii=False, indent=2),
        long_term_memory=f"Got {suggestion_count} suggestions for '{keyword}' on {channel}",
    )


# ── 拼图辅助 ──

async def _build_collage(posts: List[Dict[str, Any]]) -> Optional[str]:
    """封面图网格拼图"""
    urls, titles = [], []
    for post in posts:
        imgs = post.get("images", [])
        if imgs and imgs[0]:
            urls.append(imgs[0])
            base_title = _strip_html(post.get("title", ""))
            score = post.get("_quality_score")
            if score is not None:
                title_with_score = f"[{score}分] {base_title}"
            else:
                title_with_score = base_title
            titles.append(title_with_score)

    if not urls:
        return None

    loaded = await load_images(urls)
    valid_images, valid_labels = [], []
    for (_, img), title in zip(loaded, titles):
        if img is not None:
            valid_images.append(img)
            valid_labels.append(title)

    if not valid_images:
        return None

    grid = build_image_grid(images=valid_images, labels=valid_labels)
    import io
    buf = io.BytesIO()
    grid.save(buf, format="PNG")
    img_bytes = buf.getvalue()
    
    # 尝试上传到 CDN，替换冗长的 base64
    try:
        from agent.tools.builtin.file.image_cdn import _upload_bytes_to_oss
        import hashlib
        
        md5_hash = hashlib.md5(img_bytes).hexdigest()[:12]
        filename = f"collage_search_{md5_hash}.png"
        cdn_url = await _upload_bytes_to_oss(img_bytes, filename)
        return {"type": "url", "url": cdn_url}
    except Exception as e:
        import logging
        logging.getLogger(__name__).warning("Failed to upload collage to CDN: %s", e)
        # 降级：还是用 base64 但可能会超长
        b64, _ = encode_base64(grid, format="PNG")
        return {"type": "base64", "media_type": "image/png", "data": b64}


# ── 注册所有 AIGC 平台 ──

def _register_all():
    for p in _AIGC_PLATFORMS:
        p.search_impl = search
        # Bind each platform's id into detail_impl so the shared detail() knows
        # whether to trigger video transcription (only for sph/douyin).
        p.detail_impl = (
            lambda post, extras, _pid=p.id: detail(post, extras, _pid)  # noqa: B023 (default-arg captures pid)
        )
        if p.supports_suggest:
            p.suggest_impl = suggest
            p.suggest_channels = [p.id]
        register_platform(p)

    # wx 只有 suggest，没有搜索
    # suggest 调用时 channel 传 "wx"，但不注册为独立平台

_register_all()