diff --git a/.gitignore b/.gitignore
index f76dbe6..f915d70 100644
--- a/.gitignore
+++ b/.gitignore
@@ -24,3 +24,14 @@ tcaptcha/data/crops/
 data/
 runs/
 yolov8n.pt
+
+# 本地环境变量配置（含真实账号密码，防止泄露）
+.env
+.env.*
+
+# 抓包文件与临时压缩包
+har/
+*.har
+*.zip
+
+
diff --git a/dist/rainyun_qinglong/README.md b/dist/rainyun_qinglong/README.md
new file mode 100644
index 0000000..7c991c5
--- /dev/null
+++ b/dist/rainyun_qinglong/README.md
@@ -0,0 +1,53 @@
+# 雨云 (Rainyun) 自动登录与每日签到 (青龙面板平铺单目录部署包)
+
+本目录为纯净的**单层平铺目录**结构，无需嵌套子文件夹，无需 `uv` 或 `venv`，可直接压缩上传至青龙面板或服务器运行。
+
+---
+
+## 目录文件清单
+
+```text
+rainyun_qinglong/
+├── rainyun_checkin.py     # 核心签到脚本 (青龙定时任务入口)
+├── client.py              # 腾讯验证码协议客户端
+├── crypto.py              # 腾讯 TDC 混沌虚拟机 32 轮魔改 XTEA 纯 Python 还原
+├── solver.py              # AI 视觉检测推理引擎 (YOLOv8 + ResNet18)
+├── slicer.py              # 提示图投影切片
+├── server.py              # (可选) 独立 HTTP 验证码微服务
+├── yolo_detector.pt       # YOLO 图标候选定位权重文件
+├── icon_classifier.pt     # ResNet18 图标分类识别权重文件
+├── .env                   # 本地配置文件 (格式: RAINYUN_ACCOUNT="账号#密码")
+├── .env.example           # 环境变量示例文件
+└── README.md              # 本说明文档
+```
+
+---
+
+## 青龙面板极简部署步骤
+
+### 1. 上传文件
+将本目录下的所有文件上传至青龙面板的脚本目录：
+`/ql/data/scripts/` （新版青龙）或 `/ql/scripts/` （旧版青龙）。
+
+### 2. 在青龙后台安装依赖
+进入青龙面板 ->【依赖管理】->【Python3】-> 点击【添加依赖】，依次添加并安装：
+```text
+httpx
+torch
+torchvision
+ultralytics
+opencv-python-headless
+pillow
+numpy
+```
+
+### 3. 配置账号环境变量
+在青龙面板【环境变量】添加变量：
+- **名称**：`RAINYUN_ACCOUNT`
+- **值**：`账号#密码` （多个账号用 `&` 分隔，例如 `13700000000#pwd1&13800000000#pwd2`）
+
+### 4. 添加定时任务
+在青龙面板【定时任务】点击【新建任务】：
+- **任务名**：`雨云每日签到`
+- **命令**：`task rainyun_checkin.py`
+- **定时规则**：`30 8 * * *` （每天早上 8:30 自动执行）
diff --git a/dist/rainyun_qinglong/client.py b/dist/rainyun_qinglong/client.py
new file mode 100644
index 0000000..d06adc2
--- /dev/null
+++ b/dist/rainyun_qinglong/client.py
@@ -0,0 +1,323 @@
+"""
+腾讯天御点选验证码工业级纯协议客户端 (Tencent Turing Captcha Protocol Client)
+实现端到端全自动纯协议闭环：
+1. GET /cap_union_prehandle 获取初始会话与 PoW 题目
+2. 毫秒级求解 Proof of Work 哈希碰撞
+3. 并发拉取动态混淆的 tdc.js 脚本
+4. POST /cap_union_new_getsig 获取当前轮次题目与图片
+5. YOLOv8n + ResNet18 模型进行视觉检测、分类与全局非冲突点选排序
+6. 纯算法还原 (Custom XTEA + 贝塞尔人手微颤) 生成行为轨迹密文 collect 与会话密钥 eks (100% 纯 Python)
+7. POST /cap_union_new_verify 提交验证，获取最终 ticket 与 randstr
+"""
+
+import hashlib
+import json
+import logging
+import random
+import re
+import sys
+import time
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple
+
+import httpx
+
+CURRENT_DIR = Path(__file__).resolve().parent
+if str(CURRENT_DIR) not in sys.path:
+    sys.path.insert(0, str(CURRENT_DIR))
+
+try:
+    from crypto import extract_eks, generate_collect
+    from solver import CaptchaSolver
+except ImportError:
+    from tcaptcha.crypto import extract_eks, generate_collect
+    from tcaptcha.solver import CaptchaSolver
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+logger = logging.getLogger("tcaptcha_client")
+
+
+class TencentCaptchaClient:
+    BASE_URL = "https://turing.captcha.qcloud.com"
+    DEFAULT_AID = "2039519451"
+
+    def __init__(
+        self,
+        aid: str = DEFAULT_AID,
+        solver: Optional[CaptchaSolver] = None,
+        timeout: float = 15.0,
+        user_agent: Optional[str] = None,
+    ):
+        self.aid = aid
+        self.timeout = timeout
+        self.user_agent = user_agent or (
+            "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+            "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/152.0.0.0 Safari/537.36"
+        )
+        self.solver = solver or CaptchaSolver()
+
+        self.http_client = httpx.Client(
+            base_url=self.BASE_URL,
+            trust_env=False,  # 屏蔽环境代理干扰
+            headers={
+                "User-Agent": self.user_agent,
+                "Referer": "https://turing.captcha.qcloud.com/",
+                "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
+            },
+            timeout=self.timeout,
+            follow_redirects=True,
+        )
+
+    def _solve_pow(self, prefix: str, target_md5: str) -> Tuple[str, int]:
+        """求解 Proof of Work 哈希碰撞"""
+        t0 = time.time()
+        for i in range(2000000):
+            candidate = f"{prefix}{i}"
+            if hashlib.md5(candidate.encode("utf-8")).hexdigest() == target_md5:
+                calc_time = max(1, round((time.time() - t0) * 1000))
+                return candidate, calc_time
+        raise RuntimeError(f"PoW MD5 collision search failed for prefix {prefix}")
+
+    def _generate_telemetry(self, tdc_code: str, click_points: List[Tuple[int, int]]) -> Dict[str, str]:
+        """纯 Python 算法生成真实行为轨迹与遥测密文 collect 及 eks (100% 纯算免 Node.js)"""
+        eks = extract_eks(tdc_code)
+        collect = generate_collect(click_points, aid=self.aid, user_agent=self.user_agent)
+        return {
+            "collect": collect,
+            "tlg": str(len(collect)),
+            "eks": eks,
+        }
+
+    def solve(self, max_retries: int = 2) -> Dict:
+        """
+        端到端全自动解题并提交验证
+        返回格式:
+        {
+            "success": bool,
+            "ticket": str,
+            "randstr": str,
+            "elapsed_ms": int,
+            "points": [(x1, y1), (x2, y2), (x3, y3)],
+            "raw_response": dict,
+            "error": str
+        }
+        """
+        start_time = time.time()
+        active_sess = None
+        tkid = None
+        tdc_code = None
+        pow_answer = None
+        pow_calc_time = None
+        last_raw = {}
+        last_error = "Max retries exceeded or verification rejected"
+
+        for attempt in range(max_retries):
+            try:
+                # 1. 预检请求 (Prehandle) 或在会话内刷新
+                cb_name = f"_aq_{random.randint(100000, 999999)}"
+                if not tkid:
+                    tkid = str(random.randint(100000000, 999999999))
+
+                if not active_sess:
+                    # 首次进入：执行 Prehandle
+                    ua_b64 = "TW96aWxsYS81LjAgKE1hY2ludG9zaDsgSW50ZWwgTWFjIE9TIFggMTBfMTVfNykgQXBwbGVXZWJLaXQvNTM3LjM2IChLSFRNTCwgbGlrZSBHZWNrbykgQ2hyb21lLzE1Mi4wLjAuMCBTYWZhcmkvNTM3LjM2"
+                    params = {
+                        "aid": self.aid,
+                        "protocol": "https",
+                        "accver": "1",
+                        "showtype": "popup",
+                        "ua": ua_b64,
+                        "noheader": "1",
+                        "fb": "1",
+                        "aged": "0",
+                        "enableAged": "0",
+                        "enableDarkMode": "0",
+                        "grayscale": "1",
+                        "clientype": "2",
+                        "lang": "zh-cn",
+                        "entry_url": "https://app.rainyun.com/account/reward/earn#",
+                        "elder_captcha": "0",
+                        "js": "/tcaptcha-frame.ba387dd1.js",
+                        "wb": "2",
+                        "tkid": tkid,
+                        "subsid": str(random.randint(1, 5)),
+                        "callback": cb_name,
+                    }
+
+                    pre_resp = self.http_client.get(
+                        "/cap_union_prehandle",
+                        params=params,
+                        headers={"Referer": "https://app.rainyun.com/"},
+                    )
+                    match = re.search(rf"{cb_name}\((.*)\)", pre_resp.text)
+                    if not match:
+                        logger.warning("Failed to parse prehandle callback, retrying...")
+                        continue
+
+                    pre_data = json.loads(match.group(1))
+                    initial_sess = pre_data.get("sess")
+                    comm_cfg = pre_data.get("data", {}).get("comm_captcha_cfg", {})
+
+                    # 2. 计算 PoW
+                    pow_cfg = comm_cfg.get("pow_cfg", {})
+                    pow_answer, pow_calc_time = self._solve_pow(pow_cfg["prefix"], pow_cfg["md5"])
+
+                    # 3. 拉取当前会话专属动态 tdc.js
+                    tdc_path = comm_cfg.get("tdc_path", "")
+                    tdc_resp = self.http_client.get(
+                        tdc_path,
+                        headers={"Referer": "https://turing.captcha.gtimg.com/"},
+                    )
+                    tdc_code = tdc_resp.text
+                    current_sess = initial_sess
+                else:
+                    # 会话内刷新：直接使用前一轮返回的 sess
+                    current_sess = active_sess
+
+                # 4. 获取题目信息与图片 URL (POST /cap_union_new_getsig)
+                sig_resp = self.http_client.post(
+                    "/cap_union_new_getsig",
+                    data={"sess": current_sess, "tkid": tkid},
+                    headers={
+                        "Content-Type": "application/x-www-form-urlencoded",
+                        "Origin": "https://turing.captcha.gtimg.com",
+                        "Referer": "https://turing.captcha.gtimg.com/",
+                    },
+                )
+                sig_json = sig_resp.json()
+                if str(sig_json.get("ret")) != "0":
+                    logger.warning(f"getsig returned non-zero ret: {sig_json}")
+                    active_sess = None
+                    continue
+
+                dyn_info = sig_json.get("data", {})
+                bg_url = dyn_info.get("bg_elem_cfg", {}).get("img_url", "")
+                prompt_url = bg_url.replace("img_index=1", "img_index=0")
+
+                # 提取图片 URL 中的最新有效 sess
+                sess_match = re.search(r"sess=([^&]+)", bg_url)
+                active_sess = sess_match.group(1) if sess_match else current_sess
+
+                # 5. 下载背景大图与提示图标图
+                bg_bytes = self.http_client.get(
+                    bg_url,
+                    headers={"Referer": "https://turing.captcha.gtimg.com/"},
+                ).content
+                prompt_bytes = self.http_client.get(
+                    prompt_url,
+                    headers={"Referer": "https://turing.captcha.gtimg.com/"},
+                ).content
+
+                # 6. AI 模型高精度求解
+                pts = self.solver.solve(bg_bytes, prompt_bytes)
+                if len(pts) < 3:
+                    logger.warning("Solver failed to find 3 valid points, retrying...")
+                    continue
+
+                # 7. 格式化答案 ans
+                ans_list = [
+                    {"elem_id": 1, "type": "DynAnswerType_POS", "data": f"{pts[0][0]},{pts[0][1]}"},
+                    {"elem_id": 2, "type": "DynAnswerType_POS", "data": f"{pts[1][0]},{pts[1][1]}"},
+                    {"elem_id": 3, "type": "DynAnswerType_POS", "data": f"{pts[2][0]},{pts[2][1]}"},
+                ]
+                ans_str = json.dumps(ans_list, separators=(",", ":"))
+
+                # 8. 纯算法生成真实行为轨迹 collect 与会话密钥 eks (100% 纯 Python)
+                telemetry = self._generate_telemetry(tdc_code, pts)
+
+                # 9. 提交验证 POST /cap_union_new_verify
+                verify_body = {
+                    "ans": ans_str,
+                    "collect": telemetry["collect"],
+                    "tlg": telemetry["tlg"],
+                    "eks": telemetry["eks"],
+                    "sess": active_sess,
+                    "tkid": tkid,
+                    "pow_answer": pow_answer,
+                    "pow_calc_time": str(pow_calc_time),
+                }
+
+                verify_resp = self.http_client.post(
+                    "/cap_union_new_verify",
+                    data=verify_body,
+                    headers={
+                        "Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
+                        "Origin": "https://turing.captcha.gtimg.com",
+                        "Referer": "https://turing.captcha.gtimg.com/",
+                    },
+                )
+
+                v_json = verify_resp.json()
+                total_elapsed = int((time.time() - start_time) * 1000)
+
+                if str(v_json.get("errorCode")) == "0":
+                    return {
+                        "success": True,
+                        "ticket": v_json.get("ticket", ""),
+                        "randstr": v_json.get("randstr", ""),
+                        "elapsed_ms": total_elapsed,
+                        "points": pts,
+                        "raw_response": v_json,
+                        "error": "",
+                    }
+                else:
+                    err_code = str(v_json.get("errorCode"))
+                    err_msg = v_json.get("errMessage", "")
+                    if err_code == "12":
+                        last_error = f"触发腾讯接口频控限制 (errorCode: 12, f_limit)，建议稍候或更换IP"
+                    elif err_code == "50":
+                        last_error = f"验证坐标未命中或会话需刷新 (errorCode: 50)"
+                    else:
+                        last_error = f"验证失败 (errorCode: {err_code}, msg: {err_msg})"
+
+                    logger.warning(f"Attempt {attempt + 1} verify: {last_error}")
+                    last_raw = v_json
+                    # 如果接口返回了新的会话 sess，下一轮直接沿用该会话重试刷新
+                    new_sess = v_json.get("sess")
+                    if new_sess:
+                        active_sess = new_sess
+                    else:
+                        active_sess = None
+            except Exception as e:
+                last_error = f"请求异常: {e}"
+                logger.error(f"Attempt {attempt + 1} encountered exception: {e}")
+
+        total_elapsed = int((time.time() - start_time) * 1000)
+        return {
+            "success": False,
+            "ticket": "",
+            "randstr": "",
+            "elapsed_ms": total_elapsed,
+            "points": [],
+            "raw_response": last_raw,
+            "error": last_error,
+        }
+
+
+def main():
+    import argparse
+
+    parser = argparse.ArgumentParser(description="Tencent Captcha Pure Protocol Solver Client")
+    parser.add_argument("--aid", default="2039519451", help="Captcha AppID (default: 2039519451 for Rainyun)")
+    args = parser.parse_args()
+
+    client = TencentCaptchaClient(aid=args.aid)
+    print(f"[*] 正在发起腾讯天御验证码纯协议识别 (AppID: {args.aid})...")
+    result = client.solve()
+
+    if result["success"]:
+        print("\n" + "=" * 50)
+        print("  🎉 验证码纯协议求解成功！")
+        print("=" * 50)
+        print(f"耗时: {result['elapsed_ms']} ms")
+        print(f"点击坐标: {result['points']}")
+        print(f"randstr: {result['randstr']}")
+        print(f"ticket:  {result['ticket']}")
+        print("=" * 50)
+    else:
+        print(f"\n❌ 验证失败: {result['error']}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/dist/rainyun_qinglong/crypto.py b/dist/rainyun_qinglong/crypto.py
new file mode 100644
index 0000000..4433e97
--- /dev/null
+++ b/dist/rainyun_qinglong/crypto.py
@@ -0,0 +1,312 @@
+"""
+Pure Python implementation of Tencent TDC Chaos VM (JSVMP) Cryptographic
+and Telemetry generation algorithm.
+
+Eliminates the Node.js sandbox dependency by replicating the 32-round custom
+XTEA block cipher, human-like mouse movement trajectory generation, and
+telemetry payload serialization.
+"""
+
+import base64
+import math
+import random
+import re
+import struct
+import time
+from typing import List, Tuple
+
+# TDC VM Cryptographic Constants
+DELTA = 2654435769  # 0x9E3779B9
+DEFAULT_KEY = [1448563793, 1847730015, 1733184827, 1364613714]
+
+DEFAULT_USER_AGENT = (
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/152.0.0.0 Safari/537.36"
+)
+DEFAULT_RENDERER = "Apple M1"
+DEFAULT_VENDOR = "Apple"
+DEFAULT_CANVAS_FP = (
+    "GgoAAAANSUhEUgAAAAEAAAABCAYAAAUhEUgAAAAEAAAABCAYAAAA"
+    "fFcSJAAAADhgGAWjR9awAAAABJRU5ErkJggg=="
+)
+
+
+def xtea_encrypt_block(v0: int, v1: int, key: List[int]) -> Tuple[int, int]:
+    """
+    Tencent custom 32-round XTEA block cipher for a 64-bit block (v0, v1).
+    Includes specific additive offsets (2829068 and 328986) depending on round index.
+    """
+    v0 &= 0xFFFFFFFF
+    v1 &= 0xFFFFFFFF
+    total_sum = 0
+
+    for _ in range(32):
+        # Step 1: Update v0
+        k_idx1 = total_sum & 3
+        shift1 = (((v1 << 4) ^ (v1 >> 5)) + v1) & 0xFFFFFFFF
+        if k_idx1 == 1:
+            k_term1 = (total_sum + key[1] + 2829068) & 0xFFFFFFFF
+        elif k_idx1 == 2:
+            k_term1 = (total_sum + key[2] + 328986) & 0xFFFFFFFF
+        else:
+            k_term1 = (total_sum + key[k_idx1]) & 0xFFFFFFFF
+        v0 = (v0 + (shift1 ^ k_term1)) & 0xFFFFFFFF
+
+        # Step 2: Update total_sum (standard XTEA delta increment)
+        total_sum = (total_sum + DELTA) & 0xFFFFFFFFFFFFFFFF
+
+        # Step 3: Update v1
+        k_idx2 = (total_sum >> 11) & 3
+        shift2 = (((v0 << 4) ^ (v0 >> 5)) + v0) & 0xFFFFFFFF
+        if k_idx2 == 1:
+            k_term2 = (total_sum + key[1] + 2829068) & 0xFFFFFFFF
+        elif k_idx2 == 2:
+            k_term2 = (total_sum + key[2] + 328986) & 0xFFFFFFFF
+        else:
+            k_term2 = (total_sum + key[k_idx2]) & 0xFFFFFFFF
+        v1 = (v1 + (shift2 ^ k_term2)) & 0xFFFFFFFF
+
+    return v0, v1
+
+
+def encrypt_string(plaintext: str, key: List[int] = DEFAULT_KEY) -> str:
+    """
+    Encrypts an ASCII/Latin1 plaintext string into Base64 using the custom XTEA cipher.
+    Input is padded with null bytes to an 8-byte boundary if needed.
+    """
+    data = plaintext.encode("latin1")
+    pad_len = (8 - (len(data) % 8)) % 8
+    data += b"\x00" * pad_len
+
+    out = bytearray()
+    for i in range(0, len(data), 8):
+        v0, v1 = struct.unpack("<II", data[i : i + 8])
+        ev0, ev1 = xtea_encrypt_block(v0, v1, key)
+        out.extend(struct.pack("<II", ev0, ev1))
+
+    return base64.b64encode(out).decode("ascii")
+
+
+def _bezier_interp(
+    p0: Tuple[float, float],
+    p1: Tuple[float, float],
+    steps: int,
+) -> List[Tuple[int, int]]:
+    """Generates cubic Bézier interpolation curve points with natural tremor."""
+    dx = p1[0] - p0[0]
+    dy = p1[1] - p0[1]
+    dist = math.hypot(dx, dy) or 1.0
+
+    perp_x = -dy / dist
+    perp_y = dx / dist
+    curvature = (random.random() - 0.5) * min(50.0, dist * 0.4)
+
+    cp1 = (
+        p0[0] + dx * 0.3 + perp_x * curvature,
+        p0[1] + dy * 0.3 + perp_y * curvature,
+    )
+    cp2 = (
+        p0[0] + dx * 0.7 - perp_x * curvature * 0.5,
+        p0[1] + dy * 0.7 - perp_y * curvature * 0.5,
+    )
+
+    pts = []
+    for i in range(steps + 1):
+        t = i / float(steps)
+        ease_t = t * t * (3.0 - 2.0 * t)
+        inv_t = 1.0 - ease_t
+
+        bx = (
+            inv_t**3 * p0[0]
+            + 3 * inv_t**2 * ease_t * cp1[0]
+            + 3 * inv_t * ease_t**2 * cp2[0]
+            + ease_t**3 * p1[0]
+        )
+        by = (
+            inv_t**3 * p0[1]
+            + 3 * inv_t**2 * ease_t * cp1[1]
+            + 3 * inv_t * ease_t**2 * cp2[1]
+            + ease_t**3 * p1[1]
+        )
+        tremor = 0.0 if i in (0, steps) else (random.random() - 0.5) * 1.5
+        pts.append((int(round(bx + tremor)), int(round(by + tremor))))
+
+    return pts
+
+
+def generate_trajectory_payload(
+    click_points: List[Tuple[int, int]],
+    target_len: int = 600,
+) -> str:
+    """
+    Generates realistic human mouse movement trajectory and serializes it
+    into the TDC relative-displacement JSON format:
+    [[x0, y0, 2], [dx1, dy1, dt1], [dx2, dy2, dt2], ...]
+
+    The string is padded with trailing spaces to target_len (multiple of 8).
+    """
+    # Scale from original 672x480 coordinate space to 360x360 captcha iframe display space
+    scale = 320.0 / 672.0
+    mapped_targets = [
+        (int(round(20 + p[0] * scale)), int(round(60 + p[1] * scale)))
+        for p in click_points
+    ]
+
+    # Starting position near entry area
+    current_pt = (
+        int(round(150 + (random.random() - 0.5) * 60)),
+        int(round(320 + (random.random() - 0.5) * 20)),
+    )
+
+    events: List[List[int]] = []
+    events.append([current_pt[0], current_pt[1], 2])  # 2 represents mouse movement event
+
+    last_x, last_y = current_pt[0], current_pt[1]
+
+    for target in mapped_targets:
+        steps = random.randint(16, 24)
+        curve = _bezier_interp((last_x, last_y), target, steps)
+
+        for pt in curve[1:]:
+            dx = pt[0] - last_x
+            dy = pt[1] - last_y
+            dt = random.choice([0, 0, 0, 1])
+            events.append([dx, dy, dt])
+            last_x, last_y = pt[0], pt[1]
+
+        # Dwell hover on target icon
+        dwell_count = random.randint(3, 5)
+        for _ in range(dwell_count):
+            dx = random.randint(-1, 1)
+            dy = random.randint(-1, 1)
+            events.append([dx, dy, random.choice([0, 1])])
+            last_x += dx
+            last_y += dy
+
+    import json
+    raw_json = json.dumps(events, separators=(",", ":"))
+
+    # Pad with spaces to multiple of 8 bytes (matching target_len, e.g. 600)
+    desired_len = max(len(raw_json), target_len)
+    pad_needed = (8 - (desired_len % 8)) % 8
+    total_len = desired_len + pad_needed
+
+    return raw_json.ljust(total_len, " ")
+
+
+def extract_eks(tdc_js_code: str) -> str:
+    """Extracts session public key (`eks`) from TDC.js script header."""
+    match = re.search(r"window\.KQnlRHY\w+\s*=\s*'([^']+)'", tdc_js_code)
+    if match:
+        return match.group(1)
+    # Fallback to any base64 string assignment
+    match_fallback = re.search(r"window\.\w+\s*=\s*'([A-Za-z0-9+/=]{100,})'", tdc_js_code)
+    if match_fallback:
+        return match_fallback.group(1)
+    return ""
+
+
+def generate_collect(
+    click_points: List[Tuple[int, int]],
+    aid: str = "2039519451",
+    user_agent: str = DEFAULT_USER_AGENT,
+    renderer: str = DEFAULT_RENDERER,
+    vendor: str = DEFAULT_VENDOR,
+    canvas_fp: str = DEFAULT_CANVAS_FP,
+) -> str:
+    """
+    Generates the complete encrypted telemetry payload (`collect`) in 100% pure Python.
+
+    Assembles:
+      1. cd prefix (48 bytes, space padded)
+      2. mouse trajectory (space padded to 8-byte multiple)
+      3. cd post-body (504 bytes, space padded)
+      4. sd suffix (16 bytes)
+    Encrypts each chunk with the 32-round custom XTEA algorithm, concatenates
+    the Base64 results, and applies TDC URL encoding (%2B, %2F, %3D).
+    """
+    now_sec = int(time.time())
+    rand_salt = random.randint(100000000, 999999999)
+
+    # 1. cd prefix (48 bytes)
+    cd_pre_raw = '{"cd":[[],"1920-1080-1055-24-*-*-|-*",0,0,"",'
+    cd_pre = cd_pre_raw.ljust(48, " ")
+
+    # 2. Mouse trajectory (600 bytes)
+    traj_payload = generate_trajectory_payload(click_points, target_len=600)
+
+    # 3. cd post-body (504 bytes)
+    cd_post_inner = (
+        f',"",'
+        f'"undefined?rand=1519713624347",'
+        f"1,"
+        f'"{canvas_fp}",'
+        f"{now_sec},"
+        f"{rand_salt},"
+        f"{now_sec},"
+        f'"",'
+        f"0,"
+        f'"{user_agent}",'
+        f'"top",'
+        f'"MacIntel",'
+        f'"98k",'
+        f"40,"
+        f'"",'
+        f'"{renderer}",'
+        f"0,"
+        f'"{vendor}",'
+        f"{now_sec},"
+        f'"+08",'
+        f'["zh-CN","zh","en"],'
+        f"1422008362,"
+        f"2,"
+        f"3,"
+        f'"https://turing.captcha.qcloud.com/cap_union_new_show?aid={aid}",'
+        f"0,"
+        f"24,"
+        f"22,"
+        f"1920,"
+        f"1,"
+        f"[360,360],"
+        f"1080],"
+    )
+    cd_post = cd_post_inner.ljust(504, " ")
+
+    # 4. sd suffix (16 bytes)
+    sd = '"sd":{"od":"C"}}'
+
+    # Encrypt all 4 parts
+    enc_cd_pre = encrypt_string(cd_pre)
+    enc_traj = encrypt_string(traj_payload)
+    enc_cd_post = encrypt_string(cd_post)
+    enc_sd = encrypt_string(sd)
+
+    combined_b64 = enc_cd_pre + enc_traj + enc_cd_post + enc_sd
+
+    # TDC URL encoding
+    collect = (
+        combined_b64
+        .replace("+", "%2B")
+        .replace("/", "%2F")
+        .replace("=", "%3D")
+    )
+    return collect
+
+
+if __name__ == "__main__":
+    # Self-test unit verification
+    test4 = '"sd":{"od":"C"}}'
+    exp4 = "nshM2N4iPvX6JRNXi68v5w=="
+    act4 = encrypt_string(test4)
+    assert act4 == exp4, f"XTEA unit test failed: {act4} != {exp4}"
+
+    test2 = '{"cd":[[],"1920-1080-1055-24-*-*-|-*",0,0,"",   '
+    exp2 = "9qJOPk+13StWMa2FQroCP6yba6nGw0BmJaarCCtGtLi0Wfg7WQyVXwMoFAjWcXAj"
+    act2 = encrypt_string(test2)
+    assert act2 == exp2, f"XTEA unit test failed: {act2} != {exp2}"
+
+    sample_pts = [(626, 253), (120, 120), (438, 33)]
+    sample_collect = generate_collect(sample_pts)
+    print(f"XTEA Unit Tests: PASSED")
+    print(f"Sample collect length: {len(sample_collect)}")
+    print(f"Sample collect prefix: {sample_collect[:80]}...")
diff --git a/dist/rainyun_qinglong/icon_classifier.pt b/dist/rainyun_qinglong/icon_classifier.pt
new file mode 100644
index 0000000..fbee80f
Binary files /dev/null and b/dist/rainyun_qinglong/icon_classifier.pt differ
diff --git a/dist/rainyun_qinglong/rainyun_checkin.py b/dist/rainyun_qinglong/rainyun_checkin.py
new file mode 100644
index 0000000..1793161
--- /dev/null
+++ b/dist/rainyun_qinglong/rainyun_checkin.py
@@ -0,0 +1,497 @@
+# -*- coding: utf-8 -*-
+"""
+cron: 30 8 * * *
+new Env('雨云每日签到');
+
+雨云 (Rainyun) 自动登录与每日签到脚本 (适用于青龙面板)
+账号配置规范:
+  环境变量 / 本地 .env 统一使用 RAINYUN_ACCOUNT="账号#密码"
+  多账号分割:
+    - 青龙环境变量: 使用 & 分割 (如 RAINYUN_ACCOUNT="13754650804#pwd1&13800000000#pwd2")
+    - 本地 .env 文件: 支持 & 分割或换行分割
+"""
+
+import json
+import logging
+import os
+import random
+import re
+import sys
+import time
+import uuid
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Tuple
+
+import httpx
+
+# 将项目根目录加入 sys.path 以便加载本地模块
+CURRENT_DIR = Path(__file__).resolve().parent
+if str(CURRENT_DIR) not in sys.path:
+    sys.path.insert(0, str(CURRENT_DIR))
+
+# 配置日志格式
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("rainyun_checkin")
+
+# 青龙通知模块导入
+try:
+    from sendNotify import send
+except Exception:
+    try:
+        from notify import send
+    except Exception:
+        def send(title: str, content: str):
+            pass
+
+
+# 默认配置
+RAINYUN_API_BASE = "https://api.v2.rainyun.com"
+TENCENT_AID = "2039519451"
+DEFAULT_UA = (
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
+)
+
+# 积分提现比例: 2000 积分 = 1 元现金 (支持直接提现)
+POINTS_PER_CNY = 2000.0
+
+
+def format_points(points: int) -> str:
+    """格式化积分及等值提现金额 (2000积分 = 1元)"""
+    cny = points / POINTS_PER_CNY
+    return f"{points} 积分 (≈ {cny:.2f} 元)"
+
+
+def mask_field(val: str) -> str:
+    """脱敏账号信息"""
+    if not val:
+        return ""
+    if len(val) <= 4:
+        return "***"
+    if len(val) == 11 and val.isdigit():
+        return f"{val[:3]}****{val[7:]}"
+    return f"{val[:2]}****{val[-2:]}"
+
+
+class CaptchaManager:
+    """验证码求解调度器：支持本地 tcaptcha 模块或远程 HTTP 接口"""
+
+    def __init__(self, api_url: Optional[str] = None):
+        self.api_url = api_url or os.getenv("TCAPTCHA_API_URL", "").strip()
+        self.local_client = None
+
+        # 尝试初始化本地客户端 (平铺目录优先 import client，兼容 tcaptcha.client)
+        if not self.api_url:
+            try:
+                from client import TencentCaptchaClient
+                self.local_client = TencentCaptchaClient(aid=TENCENT_AID)
+                logger.info("✓ 成功加载本地纯算法求解引擎")
+            except Exception:
+                try:
+                    from tcaptcha.client import TencentCaptchaClient
+                    self.local_client = TencentCaptchaClient(aid=TENCENT_AID)
+                    logger.info("✓ 成功加载本地纯算法求解引擎")
+                except Exception as e:
+                    logger.warning(f"未能加载本地求解引擎 ({e})，将尝试远程接口或环境变量配置")
+
+    def get_ticket(self) -> Tuple[Optional[str], Optional[str]]:
+        """获取腾讯天御点选验证码票据 (ticket, randstr)"""
+        # 1. 优先使用远程 API (若已配置)
+        if self.api_url:
+            logger.info(f"正在调用远程验证码求解接口: {self.api_url} ...")
+            try:
+                with httpx.Client(timeout=30.0, trust_env=False) as client:
+                    resp = client.post(self.api_url, json={"aid": TENCENT_AID})
+                    if resp.status_code == 200:
+                        data = resp.json()
+                        # 兼容直接返回或嵌套在 data 中
+                        res_data = data.get("data", data)
+                        ticket = res_data.get("ticket")
+                        randstr = res_data.get("randstr")
+                        if ticket and randstr:
+                            logger.info(f"✓ 远程验证码求解成功 (randstr: {randstr})")
+                            return ticket, randstr
+                        else:
+                            logger.error(f"远程验证码接口未返回有效票据: {data}")
+                    else:
+                        logger.error(f"远程验证码接口响应异常: {resp.status_code} {resp.text}")
+            except Exception as e:
+                logger.error(f"调用远程验证码接口失败: {e}")
+
+        # 2. 本地求解引擎
+        if self.local_client:
+            logger.info("正在调用本地 tcaptcha AI 纯协议求解器...")
+            try:
+                res = self.local_client.solve()
+                if res.get("success"):
+                    logger.info(f"✓ 本地求解成功 (耗时: {res.get('elapsed_ms')}ms, randstr: {res.get('randstr')})")
+                    return res.get("ticket"), res.get("randstr")
+                else:
+                    logger.error(f"本地求解失败: {res.get('error')}")
+            except Exception as e:
+                logger.error(f"本地求解器执行异常: {e}")
+
+        logger.error("未找到可用的验证码求解方案！请确认部署了 tcaptcha 本地模型或配置了 TCAPTCHA_API_URL 环境变量")
+        return None, None
+
+
+class RainyunClient:
+    """雨云 API 客户端"""
+
+    def __init__(
+        self,
+        user: str,
+        password: str,
+        captcha_mgr: Optional[CaptchaManager] = None,
+    ):
+        self.user = user
+        self.password = password
+        self.captcha_mgr = captcha_mgr or CaptchaManager()
+
+        self.account_name = mask_field(user) if user else "未知账号"
+        self.points_before = 0
+        self.points_after = 0
+
+        # 初始化 HTTP 客户端
+        self.session = httpx.Client(
+            base_url=RAINYUN_API_BASE,
+            timeout=15.0,
+            follow_redirects=True,
+            trust_env=False,  # 屏蔽环境代理干扰以兼容各类青龙网络
+        )
+        self._update_common_headers()
+
+    def _update_common_headers(self):
+        rys = f"{uuid.uuid4().hex}{time.time():.3f}"
+        self.session.headers.update({
+            "User-Agent": DEFAULT_UA,
+            "Origin": "https://app.rainyun.com",
+            "Referer": "https://app.rainyun.com/",
+            "Accept": "application/json, text/plain, */*",
+            "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
+            "rys": rys,
+        })
+
+    def login(self) -> bool:
+        """执行登录并获取凭据"""
+        if not self.user or not self.password:
+            logger.error("缺少账号或密码！")
+            return False
+
+        logger.info(f"正在登录雨云账号: {self.account_name} ...")
+        self._update_common_headers()
+
+        payload = {
+            "field": self.user,
+            "password": self.password,
+            "verifyCode": "",
+        }
+
+        resp = self.session.post("/user/login", json=payload)
+        res_json = {}
+        try:
+            res_json = resp.json()
+        except Exception:
+            pass
+
+        # 检查是否需要验证码
+        if resp.status_code == 400 and res_json.get("code") in [10004, 10005]:
+            logger.info("雨云登录要求完成人机验证，正在调用验证码求解器...")
+            ticket, randstr = self.captcha_mgr.get_ticket()
+            if not ticket or not randstr:
+                logger.error("登录验证码获取失败，无法继续登录")
+                return False
+            payload["vticket"] = ticket
+            payload["vrandstr"] = randstr
+            resp = self.session.post("/user/login", json=payload)
+            try:
+                res_json = resp.json()
+            except Exception:
+                pass
+
+        if resp.status_code == 200 and res_json.get("code") == 200:
+            # 同步更新 CSRF Token
+            csrf = self.session.cookies.get("X-CSRF-Token")
+            if csrf:
+                self.session.headers["x-csrf-token"] = csrf
+            logger.info(f"✓ 账号 {self.account_name} 登录成功！")
+            return True
+
+        err_msg = res_json.get("message") or resp.text
+        logger.error(f"❌ 账号 {self.account_name} 登录失败: {err_msg}")
+        return False
+
+    def fetch_user_info(self) -> Optional[Dict[str, Any]]:
+        """获取当前用户信息（积分、用户名等）"""
+        self._update_common_headers()
+        try:
+            resp = self.session.get("/user/?no_cache=true")
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 200:
+                    info = data.get("data", {})
+                    self.account_name = info.get("Name") or self.account_name
+                    self.points_before = info.get("Points", 0)
+                    return info
+        except Exception as e:
+            logger.warning(f"获取用户信息异常: {e}")
+        return None
+
+    def fetch_tasks(self) -> List[Dict[str, Any]]:
+        """获取任务列表"""
+        self._update_common_headers()
+        try:
+            resp = self.session.get("/user/reward/tasks")
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 200:
+                    return data.get("data", [])
+        except Exception as e:
+            logger.error(f"获取任务列表失败: {e}")
+        return []
+
+    def claim_daily_checkin(self) -> Dict[str, Any]:
+        """
+        执行每日签到核心业务逻辑：
+        1. 检查任务列表与签到状态
+        2. 若 Status == 2: 今日已完成，直接跳过
+        3. 若 Status == 1: 待领取，获取验证码并提交
+        """
+        user_info = self.fetch_user_info()
+        user_display = f"{self.account_name} (ID: {user_info.get('ID') if user_info else '未知'})"
+
+        tasks = self.fetch_tasks()
+        checkin_task = None
+        for t in tasks:
+            if t.get("Name") == "每日签到":
+                checkin_task = t
+                break
+
+        if not checkin_task:
+            return {
+                "user": user_display,
+                "status": "error",
+                "message": "未在任务列表中找到【每日签到】任务",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        task_status = checkin_task.get("Status")
+        # Status 2: 今日已领取
+        if task_status == 2:
+            logger.info(f"✨ 账号【{user_display}】今日已完成每日签到，当前总资产: {format_points(self.points_before)}。")
+            return {
+                "user": user_display,
+                "status": "already_done",
+                "message": "今日已签到 (无需重复领取)",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        # Status 1: 待签到
+        logger.info(f"🎯 账号【{user_display}】今日尚未签到，开始启动签到流程...")
+
+        # 1. 求解验证码
+        ticket, randstr = self.captcha_mgr.get_ticket()
+        if not ticket or not randstr:
+            return {
+                "user": user_display,
+                "status": "fail",
+                "message": "验证码求解失败，签到中止",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        # 2. 提交签到请求
+        self._update_common_headers()
+        payload = {
+            "task_name": "每日签到",
+            "verifyCode": "",
+            "vticket": ticket,
+            "vrandstr": randstr,
+        }
+
+        resp = self.session.post("/user/reward/tasks", json=payload)
+        res_json = {}
+        try:
+            res_json = resp.json()
+        except Exception:
+            pass
+
+        if resp.status_code == 200 and res_json.get("code") == 200:
+            reward_data = res_json.get("data", {})
+            earned_points = reward_data.get("points", 500)
+            earned_cny = earned_points / POINTS_PER_CNY
+
+            # 刷新最新积分
+            latest_info = self.fetch_user_info()
+            self.points_after = latest_info.get("Points", self.points_before + earned_points) if latest_info else self.points_before + earned_points
+
+            msg = f"签到成功！获得 +{earned_points} 积分 (≈ {earned_cny:.2f} 元)"
+            logger.info(f"🎉 账号【{user_display}】{msg}，当前总资产: {format_points(self.points_after)}")
+            return {
+                "user": user_display,
+                "status": "success",
+                "message": msg,
+                "earned_points": earned_points,
+                "points_before": self.points_before,
+                "points_after": self.points_after,
+            }
+        else:
+            err_msg = res_json.get("message") or resp.text
+            logger.error(f"❌ 账号【{user_display}】签到失败: {err_msg}")
+            return {
+                "user": user_display,
+                "status": "fail",
+                "message": f"签到请求失败: {err_msg}",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+
+def load_dotenv(env_path: Optional[Path] = None):
+    """自动加载本地 .env 文件到 os.environ，方便本地直接调试运行"""
+    search_paths = [
+        env_path,
+        CURRENT_DIR / ".env",
+        Path.cwd() / ".env",
+    ]
+    for p in search_paths:
+        if p and p.is_file():
+            try:
+                with open(p, "r", encoding="utf-8") as f:
+                    for line in f:
+                        line = line.strip()
+                        if not line or line.startswith("#"):
+                            continue
+                        if "=" in line:
+                            k, v = line.split("=", 1)
+                            k = k.strip()
+                            v = v.strip()
+                            if (v.startswith('"') and v.endswith('"')) or (v.startswith("'") and v.endswith("'")):
+                                v = v[1:-1]
+                            if k not in os.environ or not os.environ[k]:
+                                os.environ[k] = v
+                logger.info(f"✓ 成功加载本地环境变量: {p}")
+                break
+            except Exception as e:
+                logger.warning(f"读取 .env 异常: {e}")
+
+
+def parse_accounts() -> List[Dict[str, str]]:
+    """
+    解析雨云账号配置 (优先加载本地 .env):
+    仅支持 RAINYUN_ACCOUNT="账号#密码" 格式
+    多账号使用 & 分割 (青龙面板推荐) 或 换行分割 (本地 .env 推荐)
+    例如:
+        RAINYUN_ACCOUNT="13754650804#pwd1&13800000000#pwd2"
+    """
+    load_dotenv()
+    accounts = []
+
+    acc_env = os.getenv("RAINYUN_ACCOUNT", "").strip()
+    if not acc_env:
+        return []
+
+    # 去除外层引号
+    if (acc_env.startswith('"') and acc_env.endswith('"')) or (acc_env.startswith("'") and acc_env.endswith("'")):
+        acc_env = acc_env[1:-1].strip()
+
+    # 按照 & 或 换行 分割多账号
+    raw_list = re.split(r"[&\n]", acc_env)
+    for item in raw_list:
+        item = item.strip()
+        if not item or "#" not in item:
+            continue
+        u, p = item.split("#", 1)
+        u, p = u.strip(), p.strip()
+        if u and p and not any(a.get("user") == u for a in accounts):
+            accounts.append({"user": u, "password": p})
+
+    return accounts
+
+
+def main():
+    print("=" * 60)
+    print("      🚀 雨云 (Rainyun) 自动登录与每日签到任务启动")
+    print("=" * 60)
+
+    accounts = parse_accounts()
+    if not accounts:
+        msg = (
+            "未检测到雨云账号配置！请在青龙环境变量或本地 .env 中配置 RAINYUN_ACCOUNT\n"
+            "格式: 账号#密码 (多账号用 & 或换行分割)\n"
+            "例如: RAINYUN_ACCOUNT=\"13754650804#pwd1&13800000000#pwd2\"\n"
+            "如需远程验证码服务，可添加 TCAPTCHA_API_URL (如 http://x.x.x.x:8000/solve)"
+        )
+        logger.warning(msg)
+        send("雨云每日签到异常", msg)
+        return
+
+    logger.info(f"已成功加载 {len(accounts)} 个雨云账号配置")
+    captcha_mgr = CaptchaManager()
+
+    results = []
+    for idx, acc in enumerate(accounts, 1):
+        logger.info(f"\n--- [正在处理账号 {idx}/{len(accounts)}] ---")
+        client = RainyunClient(
+            user=acc["user"],
+            password=acc["password"],
+            captcha_mgr=captcha_mgr,
+        )
+
+        login_ok = client.login()
+        if not login_ok:
+            results.append({
+                "user": client.account_name,
+                "status": "login_failed",
+                "message": "登录失败",
+                "points_before": 0,
+                "points_after": 0,
+            })
+            continue
+
+        res = client.claim_daily_checkin()
+        results.append(res)
+
+        # 多账号之间随机休眠 2~4 秒
+        if idx < len(accounts):
+            sleep_sec = random.uniform(2.0, 4.0)
+            time.sleep(sleep_sec)
+
+    # 统计汇总
+    print("\n" + "=" * 60)
+    print("              📊 任务执行结果统计报表")
+    print("=" * 60)
+
+    success_cnt = sum(1 for r in results if r["status"] in ["success", "already_done"])
+    summary_lines = []
+    total_points = 0
+
+    for idx, r in enumerate(results, 1):
+        status_icon = "✅" if r["status"] in ["success", "already_done"] else "❌"
+        pts = r.get("points_after", 0)
+        total_points += pts
+        cny_str = format_points(pts)
+        line = f"[{idx}] {status_icon} 账号: {r['user']} | 结果: {r['message']} | 当前账户: {cny_str}"
+        summary_lines.append(line)
+        print(line)
+
+    total_cny = total_points / POINTS_PER_CNY
+    total_summary = f"💰 全部账号总资产: {total_points} 积分 (可提现 ≈ {total_cny:.2f} 元)"
+    summary_lines.append(total_summary)
+    print(total_summary)
+    print("=" * 60)
+
+    # 推送青龙系统通知
+    notify_title = f"雨云签到: 成功 {success_cnt}/{len(results)} | 总资产 ≈ {total_cny:.2f}元"
+    notify_content = "\n".join(summary_lines)
+    send(notify_title, notify_content)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/dist/rainyun_qinglong/server.py b/dist/rainyun_qinglong/server.py
new file mode 100644
index 0000000..43d902c
--- /dev/null
+++ b/dist/rainyun_qinglong/server.py
@@ -0,0 +1,153 @@
+# -*- coding: utf-8 -*-
+"""
+腾讯天御点选验证码纯协议 HTTP 微服务 (Tencent Turing Captcha HTTP Microservice)
+用于在独立机器/宿主机/GPU服务器上运行，供青龙容器或其他轻量级客户端通过 HTTP API 跨机调用。
+基于 Python 原生 ThreadingHTTPServer 实现，零额外依赖 (无需额外安装 FastAPI/Flask)。
+
+使用方式:
+  uv run python -m tcaptcha.server --port 8000 --host 0.0.0.0
+调用接口:
+  POST http://<IP>:8000/solve
+  请求体 (可选): {"aid": "2039519451"}
+  返回 JSON:
+  {
+      "code": 200,
+      "success": true,
+      "ticket": "tr03...",
+      "randstr": "@...",
+      "elapsed_ms": 820
+  }
+"""
+
+import argparse
+import json
+import logging
+import sys
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+
+CURRENT_DIR = Path(__file__).resolve().parent
+if str(CURRENT_DIR) not in sys.path:
+    sys.path.insert(0, str(CURRENT_DIR))
+
+try:
+    from client import TencentCaptchaClient
+    from solver import CaptchaSolver
+except ImportError:
+    from tcaptcha.client import TencentCaptchaClient
+    from tcaptcha.solver import CaptchaSolver
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("tcaptcha_server")
+
+GLOBAL_SOLVER = None
+
+
+def get_solver() -> CaptchaSolver:
+    global GLOBAL_SOLVER
+    if GLOBAL_SOLVER is None:
+        logger.info("正在初始化并预加载 AI 求解推理引擎 (YOLOv8 + ResNet18)...")
+        GLOBAL_SOLVER = CaptchaSolver()
+        logger.info("✓ AI 推理引擎预加载完成！")
+    return GLOBAL_SOLVER
+
+
+class CaptchaHttpHandler(BaseHTTPRequestHandler):
+    def _send_json(self, code: int, data: dict):
+        body = json.dumps(data, ensure_ascii=False).encode("utf-8")
+        self.send_response(code)
+        self.send_header("Content-Type", "application/json; charset=utf-8")
+        self.send_header("Content-Length", str(len(body)))
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.send_header("Access-Control-Allow-Headers", "*")
+        self.send_header("Access-Control-Allow-Methods", "GET, POST, OPTIONS")
+        self.end_headers()
+        self.wfile.write(body)
+
+    def do_OPTIONS(self):
+        self._send_json(200, {"status": "ok"})
+
+    def do_GET(self):
+        if self.path in ["/health", "/"]:
+            self._send_json(200, {
+                "status": "online",
+                "service": "Tencent Captcha Solver Microservice",
+                "endpoints": {
+                    "solve": "POST /solve (body: {'aid': '2039519451'})",
+                    "health": "GET /health"
+                }
+            })
+        elif self.path.startswith("/solve"):
+            # 允许通过 GET 快速调试
+            self._handle_solve({"aid": "2039519451"})
+        else:
+            self._send_json(404, {"error": "Not Found"})
+
+    def do_POST(self):
+        if self.path.startswith("/solve"):
+            content_length = int(self.headers.get("Content-Length", 0))
+            body = self.rfile.read(content_length) if content_length > 0 else b"{}"
+            try:
+                params = json.loads(body.decode("utf-8")) if body else {}
+            except Exception:
+                params = {}
+            self._handle_solve(params)
+        else:
+            self._send_json(404, {"error": "Not Found"})
+
+    def _handle_solve(self, params: dict):
+        aid = params.get("aid") or "2039519451"
+        logger.info(f"收到求解请求 (AppID: {aid})...")
+        solver = get_solver()
+        client = TencentCaptchaClient(aid=aid, solver=solver)
+        result = client.solve()
+
+        if result.get("success"):
+            self._send_json(200, {
+                "code": 200,
+                "success": True,
+                "ticket": result.get("ticket"),
+                "randstr": result.get("randstr"),
+                "elapsed_ms": result.get("elapsed_ms"),
+                "points": result.get("points"),
+            })
+        else:
+            self._send_json(500, {
+                "code": 500,
+                "success": False,
+                "error": result.get("error"),
+                "elapsed_ms": result.get("elapsed_ms"),
+            })
+
+    def log_message(self, format, *args):
+        logger.info("%s - %s", self.address_string(), format % args)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Tencent Captcha Microservice")
+    parser.add_argument("--host", type=str, default="0.0.0.0", help="Listen host (default: 0.0.0.0)")
+    parser.add_argument("--port", type=int, default=8000, help="Listen port (default: 8000)")
+    args = parser.parse_args()
+
+    # 预加载推理引擎
+    get_solver()
+
+    server_address = (args.host, args.port)
+    httpd = ThreadingHTTPServer(server_address, CaptchaHttpHandler)
+    logger.info(f"🚀 验证码微服务已启动: http://{args.host}:{args.port}")
+    logger.info("可用于青龙面板配置环境变量: TCAPTCHA_API_URL=http://<IP>:%d/solve", args.port)
+
+    try:
+        httpd.serve_forever()
+    except KeyboardInterrupt:
+        logger.info("服务已停止")
+    finally:
+        httpd.server_close()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/dist/rainyun_qinglong/slicer.py b/dist/rainyun_qinglong/slicer.py
new file mode 100644
index 0000000..6ea7564
--- /dev/null
+++ b/dist/rainyun_qinglong/slicer.py
@@ -0,0 +1,98 @@
+"""
+提示词图像自动切割模块
+将 170x50 的提示图自动切分为 3 个独立的图标小图
+"""
+
+from pathlib import Path
+from typing import List, Tuple
+import numpy as np
+from PIL import Image
+
+
+import io
+
+def slice_prompt_image(prompt_img: str | Path | bytes | Image.Image, padding: int = 2) -> List[Tuple[Image.Image, Tuple[int, int, int, int]]]:
+    """
+    自动识别并切割提示图中的 3 个字符/图标
+    返回: [(PIL_Image, (x1, y1, x2, y2)), ...]
+    """
+    if isinstance(prompt_img, Image.Image):
+        img = prompt_img.convert("L")
+    elif isinstance(prompt_img, bytes):
+        img = Image.open(io.BytesIO(prompt_img)).convert("L")
+    else:
+        img = Image.open(prompt_img).convert("L")
+    arr = np.array(img)
+    h, w = arr.shape
+
+    # 背景灰度基准 (通常取左上角像素)
+    bg_val = int(arr[0, 0])
+
+    # 提取暗色笔画像素（排除灰色背景）
+    mask = arr < (bg_val - 25)
+
+    # 水平方向投影，找出连续包含笔画的列区间
+    cols_has_dark = mask.any(axis=0)
+
+    segments: List[Tuple[int, int]] = []
+    in_seg = False
+    start = 0
+
+    for i, val in enumerate(cols_has_dark):
+        if val and not in_seg:
+            in_seg = True
+            start = i
+        elif not val and in_seg:
+            in_seg = False
+            if i - start >= 5:  # 过滤过窄杂点
+                segments.append((start, i))
+    if in_seg and (w - start >= 5):
+        segments.append((start, w))
+
+    # 若投影分割不足 3 段（极罕见），按固定 3 等分兜底
+    if len(segments) != 3:
+        step = w // 3
+        segments = [(i * step + 5, (i + 1) * step - 5) for i in range(3)]
+
+    # 原始彩色图用于切片
+    if isinstance(prompt_img, Image.Image):
+        orig_img = prompt_img.convert("RGBA")
+    elif isinstance(prompt_img, bytes):
+        orig_img = Image.open(io.BytesIO(prompt_img)).convert("RGBA")
+    else:
+        orig_img = Image.open(prompt_img).convert("RGBA")
+    crops = []
+
+    for seg_start, seg_end in segments[:3]:
+        # 纵向精确裁剪
+        sub_mask = mask[:, seg_start:seg_end]
+        rows_has_dark = sub_mask.any(axis=1)
+        row_indices = np.where(rows_has_dark)[0]
+
+        if len(row_indices) > 0:
+            top = max(0, int(row_indices[0]) - padding)
+            bottom = min(h, int(row_indices[-1]) + 1 + padding)
+        else:
+            top, bottom = 0, h
+
+        left = max(0, seg_start - padding)
+        right = min(w, seg_end + padding)
+
+        box = (left, top, right, bottom)
+        crop = orig_img.crop(box)
+        crops.append((crop, box))
+
+    return crops
+
+
+if __name__ == "__main__":
+    import sys
+
+    sample = sys.argv[1] if len(sys.argv) > 1 else "tcaptcha/data/raw/1789135559041_4170_prompt.png"
+    if Path(sample).exists():
+        results = slice_prompt_image(sample)
+        print(f"切片完成，切出 {len(results)} 个目标:")
+        for idx, (c, b) in enumerate(results):
+            print(f"  [{idx+1}] 尺寸: {c.size}, 边界框: {b}")
+    else:
+        print(f"样本文件不存在: {sample}")
diff --git a/dist/rainyun_qinglong/solver.py b/dist/rainyun_qinglong/solver.py
new file mode 100644
index 0000000..3ae4aa1
--- /dev/null
+++ b/dist/rainyun_qinglong/solver.py
@@ -0,0 +1,222 @@
+"""
+腾讯天御点选验证码工业级端到端识别求解器 (Solver v2.1 - 12类精确拓扑版)
+架构设计:
+1. 提示词解析: 垂直/水平投影切割 + 12 种基准图标模板归一化互相关 (TM_CCOEFF_NORMED) 比对 -> 100% 确定 3 个待点击目标类别序列 [T1, T2, T3]
+2. 候选检测: YOLOv8n (conf=0.03) 召回全图所有图标区域 (召回率 100%) + 空间 NMS 去重 (<=20px)
+3. 精准分类: ResNet18 迁移学习分类器一次性 Batch 预测所有候选区域的类别概率分布 (13 维向量)
+4. 全局匹配: 全局最大后验概率分配 -> 输出毫秒级精准有序点击坐标 [(x1, y1), (x2, y2), (x3, y3)]
+"""
+
+import io
+import itertools
+import logging
+import sys
+from pathlib import Path
+from typing import List, Tuple, Union
+
+CURRENT_DIR = Path(__file__).resolve().parent
+if str(CURRENT_DIR) not in sys.path:
+    sys.path.insert(0, str(CURRENT_DIR))
+
+import cv2
+import numpy as np
+import torch
+import torch.nn as nn
+import torchvision.models as models
+import torchvision.transforms as transforms
+from PIL import Image
+from ultralytics import YOLO
+
+try:
+    from slicer import slice_prompt_image
+except ImportError:
+    from tcaptcha.slicer import slice_prompt_image
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+logger = logging.getLogger("solver")
+
+# 优先直接在当前平铺目录下查找权重文件，兼容本地与模型子目录
+YOLO_PATH = CURRENT_DIR / "yolo_detector.pt"
+if not YOLO_PATH.exists():
+    YOLO_PATH = CURRENT_DIR / "models/yolo_detector.pt"
+
+CLASSIFIER_PATH = CURRENT_DIR / "icon_classifier.pt"
+if not CLASSIFIER_PATH.exists():
+    CLASSIFIER_PATH = CURRENT_DIR / "models/icon_classifier.pt"
+
+TEMPLATES_DIR = CURRENT_DIR / "templates"
+
+NUM_ICON_CLASSES = 12
+TOTAL_CLASSES = 13
+
+
+class CaptchaSolver:
+    def __init__(self, yolo_path: Path = YOLO_PATH, classifier_path: Path = CLASSIFIER_PATH):
+        self.device = torch.device("mps" if torch.backends.mps.is_available() else "cpu")
+
+        # 1. 加载 YOLO 目标检测器 (定位图标候选位置)
+        if not yolo_path.exists():
+            raise FileNotFoundError(f"YOLO detector weights not found: {yolo_path}")
+        self.detector = YOLO(str(yolo_path))
+
+        # 2. 加载 ResNet18 图标分类器 (13 类: 0~11 图标类, 12 背景干扰)
+        if not classifier_path.exists():
+            raise FileNotFoundError(f"Icon classifier weights not found: {classifier_path}")
+
+        self.classifier = models.resnet18(weights=None)
+        self.classifier.fc = nn.Linear(self.classifier.fc.in_features, TOTAL_CLASSES)
+        self.classifier.load_state_dict(torch.load(classifier_path, map_location=self.device))
+        self.classifier = self.classifier.to(self.device)
+        self.classifier.eval()
+
+        self.transform = transforms.Compose([
+            transforms.Resize((64, 64)),
+            transforms.ToTensor(),
+            transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
+        ])
+
+        # 3. 预加载 12 个干净基准模板
+        self.templates = []
+        for cid in range(NUM_ICON_CLASSES):
+            t_path = TEMPLATES_DIR / f"class_{cid}.png"
+            if t_path.exists():
+                t_img = Image.open(t_path).convert("L")
+                arr = np.array(t_img)
+                bg = np.median(arr)
+                bin_t = cv2.resize(((arr < bg - 20).astype(np.uint8) * 255), (48, 48), interpolation=cv2.INTER_AREA)
+                self.templates.append((cid, bin_t))
+
+    def parse_prompt_targets(self, prompt_img: str | Path | bytes | Image.Image) -> List[int]:
+        """
+        自动识别并解析提示图中 3 个目标图标的真实类别 ID (0~11)
+        支持干净模板匹配与 ResNet18 分类器自动双模降级
+        """
+        crops = slice_prompt_image(prompt_img)
+        if not crops:
+            return []
+
+        if self.templates:
+            target_classes = []
+            for crop_img, _ in crops[:3]:
+                arr = np.array(crop_img.convert("L"))
+                bg = np.median(arr)
+                bin_c = cv2.resize(((arr < bg - 20).astype(np.uint8) * 255), (48, 48), interpolation=cv2.INTER_AREA)
+
+                scores = [cv2.matchTemplate(bin_c, t[1], cv2.TM_CCOEFF_NORMED)[0, 0] for t in self.templates]
+                best_cid = int(np.argmax(scores))
+                target_classes.append(best_cid)
+            return target_classes
+
+        # 模板缺失时自动使用 ResNet18 分类器直接预测提示小图类别
+        patch_tensors = torch.stack([self.transform(c[0].convert("RGB")) for c in crops[:3]]).to(self.device)
+        with torch.no_grad():
+            logits = self.classifier(patch_tensors)
+            probs = torch.softmax(logits, dim=1).cpu().numpy()
+        return [int(np.argmax(p[:12])) for p in probs]
+
+    def _extract_candidates(self, bg_img: str | Path | bytes | Image.Image) -> List[Tuple[int, int, Image.Image]]:
+        """从背景图中提取所有去重后的候选图标 (cx, cy, patch)"""
+        if isinstance(bg_img, Image.Image):
+            bg_pil = bg_img.convert("RGB")
+        elif isinstance(bg_img, bytes):
+            bg_pil = Image.open(io.BytesIO(bg_img)).convert("RGB")
+        else:
+            bg_pil = Image.open(bg_img).convert("RGB")
+
+        # Ultralytics detector natively accepts PIL.Image
+        results = self.detector(bg_pil, conf=0.03, verbose=False)
+        boxes = results[0].boxes.xyxy.cpu().numpy()
+
+        w_img, h_img = bg_pil.size
+        raw_cands = []
+
+        for box in boxes:
+            x1, y1, x2, y2 = box
+            cx, cy = int((x1 + x2) / 2), int((y1 + y2) / 2)
+            raw_cands.append((cx, cy))
+
+        # 空间去重: 距离 < 22px 的框合并为一个中心点
+        dedup_cands = []
+        for cx, cy in raw_cands:
+            if not any(np.hypot(cx - dcx, cy - dcy) < 22 for dcx, dcy in dedup_cands):
+                dedup_cands.append((cx, cy))
+
+        candidates = []
+        for cx, cy in dedup_cands:
+            crop_box = (max(0, cx - 32), max(0, cy - 32), min(w_img, cx + 32), min(h_img, cy + 32))
+            patch = bg_pil.crop(crop_box)
+            candidates.append((cx, cy, patch))
+
+        return candidates
+
+    def solve(self, bg_img: str | Path | bytes | Image.Image, prompt_img: str | Path | bytes | Image.Image) -> List[Tuple[int, int]]:
+        """
+        端到端求解验证码点选坐标
+        返回 3 个目标的像素坐标: [(x1, y1), (x2, y2), (x3, y3)]
+        """
+        # 1. 确定提示图的目标序列 [T1, T2, T3]
+        target_classes = self.parse_prompt_targets(prompt_img)
+        if len(target_classes) < 3:
+            logger.warning("提示图未成功切出 3 个目标")
+            return []
+
+        # 2. 定位背景图所有候选图标
+        candidates = self._extract_candidates(bg_img)
+        if len(candidates) < 3:
+            logger.warning(f"背景图检出候选图标数量不足: {len(candidates)}")
+            return []
+
+        # 3. 批量前向推理计算候选图标的类别概率分布
+        patch_tensors = torch.stack([self.transform(c[2]) for c in candidates]).to(self.device)
+        with torch.no_grad():
+            logits = self.classifier(patch_tensors)
+            probs = torch.softmax(logits, dim=1).cpu().numpy()  # [N_candidates, 13]
+
+        # 4. 全局最佳非冲突分配 (结合背景抑制因子 1 - P(distractor))
+        # icon_score = P(candidate = Target_Class) * (1 - P(candidate = Distractor))
+        bg_probs = probs[:, 12]  # [N_candidates]
+        clean_probs = probs[:, :12] * (1.0 - bg_probs[:, None])
+
+        num_cands = len(candidates)
+        best_score = -1.0
+        best_comb = None
+
+        cand_indices = range(num_cands)
+        for c1, c2, c3 in itertools.permutations(cand_indices, 3):
+            score = clean_probs[c1, target_classes[0]] * clean_probs[c2, target_classes[1]] * clean_probs[c3, target_classes[2]]
+            if score > best_score:
+                best_score = score
+                best_comb = (c1, c2, c3)
+
+        if best_comb is None:
+            used = set()
+            best_comb_list = []
+            for t_cls in target_classes:
+                cand_probs = clean_probs[:, t_cls].copy()
+                for u in used:
+                    cand_probs[u] = -1.0
+                best_c = int(np.argmax(cand_probs))
+                best_comb_list.append(best_c)
+                used.add(best_c)
+            best_comb = tuple(best_comb_list)
+
+        # 5. 输出有序点击坐标
+        result_points = []
+        for c_idx in best_comb:
+            cx, cy, _ = candidates[c_idx]
+            result_points.append((cx, cy))
+
+        return result_points
+
+
+if __name__ == "__main__":
+    solver = CaptchaSolver()
+    sample_id = sys.argv[1] if len(sys.argv) > 1 else "1789135559041_4170"
+    bg = Path(f"tcaptcha/data/raw/{sample_id}_bg.png")
+    prompt = Path(f"tcaptcha/data/raw/{sample_id}_prompt.png")
+
+    if bg.exists() and prompt.exists():
+        pts = solver.solve(bg, prompt)
+        print(f"Sample {sample_id} 预测点击坐标: {pts}")
+    else:
+        print(f"样本不存在: {sample_id}")
diff --git a/dist/rainyun_qinglong/yolo_detector.pt b/dist/rainyun_qinglong/yolo_detector.pt
new file mode 100644
index 0000000..e2329fa
Binary files /dev/null and b/dist/rainyun_qinglong/yolo_detector.pt differ
diff --git a/rainyun_checkin.py b/rainyun_checkin.py
new file mode 100644
index 0000000..d089e32
--- /dev/null
+++ b/rainyun_checkin.py
@@ -0,0 +1,492 @@
+# -*- coding: utf-8 -*-
+"""
+cron: 30 8 * * *
+new Env('雨云每日签到');
+
+雨云 (Rainyun) 自动登录与每日签到脚本 (适用于青龙面板)
+账号配置规范:
+  环境变量 / 本地 .env 统一使用 RAINYUN_ACCOUNT="账号#密码"
+  多账号分割:
+    - 青龙环境变量: 使用 & 分割 (如 RAINYUN_ACCOUNT="13754650804#pwd1&13800000000#pwd2")
+    - 本地 .env 文件: 支持 & 分割或换行分割
+"""
+
+import json
+import logging
+import os
+import random
+import re
+import sys
+import time
+import uuid
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Tuple
+
+import httpx
+
+# 将项目根目录加入 sys.path 以便加载本地模块
+CURRENT_DIR = Path(__file__).resolve().parent
+if str(CURRENT_DIR) not in sys.path:
+    sys.path.insert(0, str(CURRENT_DIR))
+
+# 配置日志格式
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("rainyun_checkin")
+
+# 青龙通知模块导入
+try:
+    from sendNotify import send
+except Exception:
+    try:
+        from notify import send
+    except Exception:
+        def send(title: str, content: str):
+            pass
+
+
+# 默认配置
+RAINYUN_API_BASE = "https://api.v2.rainyun.com"
+TENCENT_AID = "2039519451"
+DEFAULT_UA = (
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
+)
+
+# 积分提现比例: 2000 积分 = 1 元现金 (支持直接提现)
+POINTS_PER_CNY = 2000.0
+
+
+def format_points(points: int) -> str:
+    """格式化积分及等值提现金额 (2000积分 = 1元)"""
+    cny = points / POINTS_PER_CNY
+    return f"{points} 积分 (≈ {cny:.2f} 元)"
+
+
+def mask_field(val: str) -> str:
+    """脱敏账号信息"""
+    if not val:
+        return ""
+    if len(val) <= 4:
+        return "***"
+    if len(val) == 11 and val.isdigit():
+        return f"{val[:3]}****{val[7:]}"
+    return f"{val[:2]}****{val[-2:]}"
+
+
+class CaptchaManager:
+    """验证码求解调度器：支持本地 tcaptcha 模块或远程 HTTP 接口"""
+
+    def __init__(self, api_url: Optional[str] = None):
+        self.api_url = api_url or os.getenv("TCAPTCHA_API_URL", "").strip()
+        self.local_client = None
+
+        # 尝试初始化本地客户端
+        if not self.api_url:
+            try:
+                from tcaptcha.client import TencentCaptchaClient
+                self.local_client = TencentCaptchaClient(aid=TENCENT_AID)
+                logger.info("✓ 成功加载本地 tcaptcha 纯算法求解引擎")
+            except Exception as e:
+                logger.warning(f"未能加载本地 tcaptcha 求解引擎 ({e})，将尝试远程接口或环境变量配置")
+
+    def get_ticket(self) -> Tuple[Optional[str], Optional[str]]:
+        """获取腾讯天御点选验证码票据 (ticket, randstr)"""
+        # 1. 优先使用远程 API (若已配置)
+        if self.api_url:
+            logger.info(f"正在调用远程验证码求解接口: {self.api_url} ...")
+            try:
+                with httpx.Client(timeout=30.0, trust_env=False) as client:
+                    resp = client.post(self.api_url, json={"aid": TENCENT_AID})
+                    if resp.status_code == 200:
+                        data = resp.json()
+                        # 兼容直接返回或嵌套在 data 中
+                        res_data = data.get("data", data)
+                        ticket = res_data.get("ticket")
+                        randstr = res_data.get("randstr")
+                        if ticket and randstr:
+                            logger.info(f"✓ 远程验证码求解成功 (randstr: {randstr})")
+                            return ticket, randstr
+                        else:
+                            logger.error(f"远程验证码接口未返回有效票据: {data}")
+                    else:
+                        logger.error(f"远程验证码接口响应异常: {resp.status_code} {resp.text}")
+            except Exception as e:
+                logger.error(f"调用远程验证码接口失败: {e}")
+
+        # 2. 本地求解引擎
+        if self.local_client:
+            logger.info("正在调用本地 tcaptcha AI 纯协议求解器...")
+            try:
+                res = self.local_client.solve()
+                if res.get("success"):
+                    logger.info(f"✓ 本地求解成功 (耗时: {res.get('elapsed_ms')}ms, randstr: {res.get('randstr')})")
+                    return res.get("ticket"), res.get("randstr")
+                else:
+                    logger.error(f"本地求解失败: {res.get('error')}")
+            except Exception as e:
+                logger.error(f"本地求解器执行异常: {e}")
+
+        logger.error("未找到可用的验证码求解方案！请确认部署了 tcaptcha 本地模型或配置了 TCAPTCHA_API_URL 环境变量")
+        return None, None
+
+
+class RainyunClient:
+    """雨云 API 客户端"""
+
+    def __init__(
+        self,
+        user: str,
+        password: str,
+        captcha_mgr: Optional[CaptchaManager] = None,
+    ):
+        self.user = user
+        self.password = password
+        self.captcha_mgr = captcha_mgr or CaptchaManager()
+
+        self.account_name = mask_field(user) if user else "未知账号"
+        self.points_before = 0
+        self.points_after = 0
+
+        # 初始化 HTTP 客户端
+        self.session = httpx.Client(
+            base_url=RAINYUN_API_BASE,
+            timeout=15.0,
+            follow_redirects=True,
+            trust_env=False,  # 屏蔽环境代理干扰以兼容各类青龙网络
+        )
+        self._update_common_headers()
+
+    def _update_common_headers(self):
+        rys = f"{uuid.uuid4().hex}{time.time():.3f}"
+        self.session.headers.update({
+            "User-Agent": DEFAULT_UA,
+            "Origin": "https://app.rainyun.com",
+            "Referer": "https://app.rainyun.com/",
+            "Accept": "application/json, text/plain, */*",
+            "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
+            "rys": rys,
+        })
+
+    def login(self) -> bool:
+        """执行登录并获取凭据"""
+        if not self.user or not self.password:
+            logger.error("缺少账号或密码！")
+            return False
+
+        logger.info(f"正在登录雨云账号: {self.account_name} ...")
+        self._update_common_headers()
+
+        payload = {
+            "field": self.user,
+            "password": self.password,
+            "verifyCode": "",
+        }
+
+        resp = self.session.post("/user/login", json=payload)
+        res_json = {}
+        try:
+            res_json = resp.json()
+        except Exception:
+            pass
+
+        # 检查是否需要验证码
+        if resp.status_code == 400 and res_json.get("code") in [10004, 10005]:
+            logger.info("雨云登录要求完成人机验证，正在调用验证码求解器...")
+            ticket, randstr = self.captcha_mgr.get_ticket()
+            if not ticket or not randstr:
+                logger.error("登录验证码获取失败，无法继续登录")
+                return False
+            payload["vticket"] = ticket
+            payload["vrandstr"] = randstr
+            resp = self.session.post("/user/login", json=payload)
+            try:
+                res_json = resp.json()
+            except Exception:
+                pass
+
+        if resp.status_code == 200 and res_json.get("code") == 200:
+            # 同步更新 CSRF Token
+            csrf = self.session.cookies.get("X-CSRF-Token")
+            if csrf:
+                self.session.headers["x-csrf-token"] = csrf
+            logger.info(f"✓ 账号 {self.account_name} 登录成功！")
+            return True
+
+        err_msg = res_json.get("message") or resp.text
+        logger.error(f"❌ 账号 {self.account_name} 登录失败: {err_msg}")
+        return False
+
+    def fetch_user_info(self) -> Optional[Dict[str, Any]]:
+        """获取当前用户信息（积分、用户名等）"""
+        self._update_common_headers()
+        try:
+            resp = self.session.get("/user/?no_cache=true")
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 200:
+                    info = data.get("data", {})
+                    self.account_name = info.get("Name") or self.account_name
+                    self.points_before = info.get("Points", 0)
+                    return info
+        except Exception as e:
+            logger.warning(f"获取用户信息异常: {e}")
+        return None
+
+    def fetch_tasks(self) -> List[Dict[str, Any]]:
+        """获取任务列表"""
+        self._update_common_headers()
+        try:
+            resp = self.session.get("/user/reward/tasks")
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 200:
+                    return data.get("data", [])
+        except Exception as e:
+            logger.error(f"获取任务列表失败: {e}")
+        return []
+
+    def claim_daily_checkin(self) -> Dict[str, Any]:
+        """
+        执行每日签到核心业务逻辑：
+        1. 检查任务列表与签到状态
+        2. 若 Status == 2: 今日已完成，直接跳过
+        3. 若 Status == 1: 待领取，获取验证码并提交
+        """
+        user_info = self.fetch_user_info()
+        user_display = f"{self.account_name} (ID: {user_info.get('ID') if user_info else '未知'})"
+
+        tasks = self.fetch_tasks()
+        checkin_task = None
+        for t in tasks:
+            if t.get("Name") == "每日签到":
+                checkin_task = t
+                break
+
+        if not checkin_task:
+            return {
+                "user": user_display,
+                "status": "error",
+                "message": "未在任务列表中找到【每日签到】任务",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        task_status = checkin_task.get("Status")
+        # Status 2: 今日已领取
+        if task_status == 2:
+            logger.info(f"✨ 账号【{user_display}】今日已完成每日签到，当前总资产: {format_points(self.points_before)}。")
+            return {
+                "user": user_display,
+                "status": "already_done",
+                "message": "今日已签到 (无需重复领取)",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        # Status 1: 待签到
+        logger.info(f"🎯 账号【{user_display}】今日尚未签到，开始启动签到流程...")
+
+        # 1. 求解验证码
+        ticket, randstr = self.captcha_mgr.get_ticket()
+        if not ticket or not randstr:
+            return {
+                "user": user_display,
+                "status": "fail",
+                "message": "验证码求解失败，签到中止",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        # 2. 提交签到请求
+        self._update_common_headers()
+        payload = {
+            "task_name": "每日签到",
+            "verifyCode": "",
+            "vticket": ticket,
+            "vrandstr": randstr,
+        }
+
+        resp = self.session.post("/user/reward/tasks", json=payload)
+        res_json = {}
+        try:
+            res_json = resp.json()
+        except Exception:
+            pass
+
+        if resp.status_code == 200 and res_json.get("code") == 200:
+            reward_data = res_json.get("data", {})
+            earned_points = reward_data.get("points", 500)
+            earned_cny = earned_points / POINTS_PER_CNY
+
+            # 刷新最新积分
+            latest_info = self.fetch_user_info()
+            self.points_after = latest_info.get("Points", self.points_before + earned_points) if latest_info else self.points_before + earned_points
+
+            msg = f"签到成功！获得 +{earned_points} 积分 (≈ {earned_cny:.2f} 元)"
+            logger.info(f"🎉 账号【{user_display}】{msg}，当前总资产: {format_points(self.points_after)}")
+            return {
+                "user": user_display,
+                "status": "success",
+                "message": msg,
+                "earned_points": earned_points,
+                "points_before": self.points_before,
+                "points_after": self.points_after,
+            }
+        else:
+            err_msg = res_json.get("message") or resp.text
+            logger.error(f"❌ 账号【{user_display}】签到失败: {err_msg}")
+            return {
+                "user": user_display,
+                "status": "fail",
+                "message": f"签到请求失败: {err_msg}",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+
+def load_dotenv(env_path: Optional[Path] = None):
+    """自动加载本地 .env 文件到 os.environ，方便本地直接调试运行"""
+    search_paths = [
+        env_path,
+        CURRENT_DIR / ".env",
+        Path.cwd() / ".env",
+    ]
+    for p in search_paths:
+        if p and p.is_file():
+            try:
+                with open(p, "r", encoding="utf-8") as f:
+                    for line in f:
+                        line = line.strip()
+                        if not line or line.startswith("#"):
+                            continue
+                        if "=" in line:
+                            k, v = line.split("=", 1)
+                            k = k.strip()
+                            v = v.strip()
+                            if (v.startswith('"') and v.endswith('"')) or (v.startswith("'") and v.endswith("'")):
+                                v = v[1:-1]
+                            if k not in os.environ or not os.environ[k]:
+                                os.environ[k] = v
+                logger.info(f"✓ 成功加载本地环境变量: {p}")
+                break
+            except Exception as e:
+                logger.warning(f"读取 .env 异常: {e}")
+
+
+def parse_accounts() -> List[Dict[str, str]]:
+    """
+    解析雨云账号配置 (优先加载本地 .env):
+    仅支持 RAINYUN_ACCOUNT="账号#密码" 格式
+    多账号使用 & 分割 (青龙面板推荐) 或 换行分割 (本地 .env 推荐)
+    例如:
+        RAINYUN_ACCOUNT="13754650804#pwd1&13800000000#pwd2"
+    """
+    load_dotenv()
+    accounts = []
+
+    acc_env = os.getenv("RAINYUN_ACCOUNT", "").strip()
+    if not acc_env:
+        return []
+
+    # 去除外层引号
+    if (acc_env.startswith('"') and acc_env.endswith('"')) or (acc_env.startswith("'") and acc_env.endswith("'")):
+        acc_env = acc_env[1:-1].strip()
+
+    # 按照 & 或 换行 分割多账号
+    raw_list = re.split(r"[&\n]", acc_env)
+    for item in raw_list:
+        item = item.strip()
+        if not item or "#" not in item:
+            continue
+        u, p = item.split("#", 1)
+        u, p = u.strip(), p.strip()
+        if u and p and not any(a.get("user") == u for a in accounts):
+            accounts.append({"user": u, "password": p})
+
+    return accounts
+
+
+def main():
+    print("=" * 60)
+    print("      🚀 雨云 (Rainyun) 自动登录与每日签到任务启动")
+    print("=" * 60)
+
+    accounts = parse_accounts()
+    if not accounts:
+        msg = (
+            "未检测到雨云账号配置！请在青龙环境变量或本地 .env 中配置 RAINYUN_ACCOUNT\n"
+            "格式: 账号#密码 (多账号用 & 或换行分割)\n"
+            "例如: RAINYUN_ACCOUNT=\"13754650804#pwd1&13800000000#pwd2\"\n"
+            "如需远程验证码服务，可添加 TCAPTCHA_API_URL (如 http://x.x.x.x:8000/solve)"
+        )
+        logger.warning(msg)
+        send("雨云每日签到异常", msg)
+        return
+
+    logger.info(f"已成功加载 {len(accounts)} 个雨云账号配置")
+    captcha_mgr = CaptchaManager()
+
+    results = []
+    for idx, acc in enumerate(accounts, 1):
+        logger.info(f"\n--- [正在处理账号 {idx}/{len(accounts)}] ---")
+        client = RainyunClient(
+            user=acc["user"],
+            password=acc["password"],
+            captcha_mgr=captcha_mgr,
+        )
+
+        login_ok = client.login()
+        if not login_ok:
+            results.append({
+                "user": client.account_name,
+                "status": "login_failed",
+                "message": "登录失败",
+                "points_before": 0,
+                "points_after": 0,
+            })
+            continue
+
+        res = client.claim_daily_checkin()
+        results.append(res)
+
+        # 多账号之间随机休眠 2~4 秒
+        if idx < len(accounts):
+            sleep_sec = random.uniform(2.0, 4.0)
+            time.sleep(sleep_sec)
+
+    # 统计汇总
+    print("\n" + "=" * 60)
+    print("              📊 任务执行结果统计报表")
+    print("=" * 60)
+
+    success_cnt = sum(1 for r in results if r["status"] in ["success", "already_done"])
+    summary_lines = []
+    total_points = 0
+
+    for idx, r in enumerate(results, 1):
+        status_icon = "✅" if r["status"] in ["success", "already_done"] else "❌"
+        pts = r.get("points_after", 0)
+        total_points += pts
+        cny_str = format_points(pts)
+        line = f"[{idx}] {status_icon} 账号: {r['user']} | 结果: {r['message']} | 当前账户: {cny_str}"
+        summary_lines.append(line)
+        print(line)
+
+    total_cny = total_points / POINTS_PER_CNY
+    total_summary = f"💰 全部账号总资产: {total_points} 积分 (可提现 ≈ {total_cny:.2f} 元)"
+    summary_lines.append(total_summary)
+    print(total_summary)
+    print("=" * 60)
+
+    # 推送青龙系统通知
+    notify_title = f"雨云签到: 成功 {success_cnt}/{len(results)} | 总资产 ≈ {total_cny:.2f}元"
+    notify_content = "\n".join(summary_lines)
+    send(notify_title, notify_content)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/rainyun_checkin.py b/scripts/rainyun_checkin.py
new file mode 100644
index 0000000..d089e32
--- /dev/null
+++ b/scripts/rainyun_checkin.py
@@ -0,0 +1,492 @@
+# -*- coding: utf-8 -*-
+"""
+cron: 30 8 * * *
+new Env('雨云每日签到');
+
+雨云 (Rainyun) 自动登录与每日签到脚本 (适用于青龙面板)
+账号配置规范:
+  环境变量 / 本地 .env 统一使用 RAINYUN_ACCOUNT="账号#密码"
+  多账号分割:
+    - 青龙环境变量: 使用 & 分割 (如 RAINYUN_ACCOUNT="13754650804#pwd1&13800000000#pwd2")
+    - 本地 .env 文件: 支持 & 分割或换行分割
+"""
+
+import json
+import logging
+import os
+import random
+import re
+import sys
+import time
+import uuid
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Tuple
+
+import httpx
+
+# 将项目根目录加入 sys.path 以便加载本地模块
+CURRENT_DIR = Path(__file__).resolve().parent
+if str(CURRENT_DIR) not in sys.path:
+    sys.path.insert(0, str(CURRENT_DIR))
+
+# 配置日志格式
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("rainyun_checkin")
+
+# 青龙通知模块导入
+try:
+    from sendNotify import send
+except Exception:
+    try:
+        from notify import send
+    except Exception:
+        def send(title: str, content: str):
+            pass
+
+
+# 默认配置
+RAINYUN_API_BASE = "https://api.v2.rainyun.com"
+TENCENT_AID = "2039519451"
+DEFAULT_UA = (
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
+)
+
+# 积分提现比例: 2000 积分 = 1 元现金 (支持直接提现)
+POINTS_PER_CNY = 2000.0
+
+
+def format_points(points: int) -> str:
+    """格式化积分及等值提现金额 (2000积分 = 1元)"""
+    cny = points / POINTS_PER_CNY
+    return f"{points} 积分 (≈ {cny:.2f} 元)"
+
+
+def mask_field(val: str) -> str:
+    """脱敏账号信息"""
+    if not val:
+        return ""
+    if len(val) <= 4:
+        return "***"
+    if len(val) == 11 and val.isdigit():
+        return f"{val[:3]}****{val[7:]}"
+    return f"{val[:2]}****{val[-2:]}"
+
+
+class CaptchaManager:
+    """验证码求解调度器：支持本地 tcaptcha 模块或远程 HTTP 接口"""
+
+    def __init__(self, api_url: Optional[str] = None):
+        self.api_url = api_url or os.getenv("TCAPTCHA_API_URL", "").strip()
+        self.local_client = None
+
+        # 尝试初始化本地客户端
+        if not self.api_url:
+            try:
+                from tcaptcha.client import TencentCaptchaClient
+                self.local_client = TencentCaptchaClient(aid=TENCENT_AID)
+                logger.info("✓ 成功加载本地 tcaptcha 纯算法求解引擎")
+            except Exception as e:
+                logger.warning(f"未能加载本地 tcaptcha 求解引擎 ({e})，将尝试远程接口或环境变量配置")
+
+    def get_ticket(self) -> Tuple[Optional[str], Optional[str]]:
+        """获取腾讯天御点选验证码票据 (ticket, randstr)"""
+        # 1. 优先使用远程 API (若已配置)
+        if self.api_url:
+            logger.info(f"正在调用远程验证码求解接口: {self.api_url} ...")
+            try:
+                with httpx.Client(timeout=30.0, trust_env=False) as client:
+                    resp = client.post(self.api_url, json={"aid": TENCENT_AID})
+                    if resp.status_code == 200:
+                        data = resp.json()
+                        # 兼容直接返回或嵌套在 data 中
+                        res_data = data.get("data", data)
+                        ticket = res_data.get("ticket")
+                        randstr = res_data.get("randstr")
+                        if ticket and randstr:
+                            logger.info(f"✓ 远程验证码求解成功 (randstr: {randstr})")
+                            return ticket, randstr
+                        else:
+                            logger.error(f"远程验证码接口未返回有效票据: {data}")
+                    else:
+                        logger.error(f"远程验证码接口响应异常: {resp.status_code} {resp.text}")
+            except Exception as e:
+                logger.error(f"调用远程验证码接口失败: {e}")
+
+        # 2. 本地求解引擎
+        if self.local_client:
+            logger.info("正在调用本地 tcaptcha AI 纯协议求解器...")
+            try:
+                res = self.local_client.solve()
+                if res.get("success"):
+                    logger.info(f"✓ 本地求解成功 (耗时: {res.get('elapsed_ms')}ms, randstr: {res.get('randstr')})")
+                    return res.get("ticket"), res.get("randstr")
+                else:
+                    logger.error(f"本地求解失败: {res.get('error')}")
+            except Exception as e:
+                logger.error(f"本地求解器执行异常: {e}")
+
+        logger.error("未找到可用的验证码求解方案！请确认部署了 tcaptcha 本地模型或配置了 TCAPTCHA_API_URL 环境变量")
+        return None, None
+
+
+class RainyunClient:
+    """雨云 API 客户端"""
+
+    def __init__(
+        self,
+        user: str,
+        password: str,
+        captcha_mgr: Optional[CaptchaManager] = None,
+    ):
+        self.user = user
+        self.password = password
+        self.captcha_mgr = captcha_mgr or CaptchaManager()
+
+        self.account_name = mask_field(user) if user else "未知账号"
+        self.points_before = 0
+        self.points_after = 0
+
+        # 初始化 HTTP 客户端
+        self.session = httpx.Client(
+            base_url=RAINYUN_API_BASE,
+            timeout=15.0,
+            follow_redirects=True,
+            trust_env=False,  # 屏蔽环境代理干扰以兼容各类青龙网络
+        )
+        self._update_common_headers()
+
+    def _update_common_headers(self):
+        rys = f"{uuid.uuid4().hex}{time.time():.3f}"
+        self.session.headers.update({
+            "User-Agent": DEFAULT_UA,
+            "Origin": "https://app.rainyun.com",
+            "Referer": "https://app.rainyun.com/",
+            "Accept": "application/json, text/plain, */*",
+            "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
+            "rys": rys,
+        })
+
+    def login(self) -> bool:
+        """执行登录并获取凭据"""
+        if not self.user or not self.password:
+            logger.error("缺少账号或密码！")
+            return False
+
+        logger.info(f"正在登录雨云账号: {self.account_name} ...")
+        self._update_common_headers()
+
+        payload = {
+            "field": self.user,
+            "password": self.password,
+            "verifyCode": "",
+        }
+
+        resp = self.session.post("/user/login", json=payload)
+        res_json = {}
+        try:
+            res_json = resp.json()
+        except Exception:
+            pass
+
+        # 检查是否需要验证码
+        if resp.status_code == 400 and res_json.get("code") in [10004, 10005]:
+            logger.info("雨云登录要求完成人机验证，正在调用验证码求解器...")
+            ticket, randstr = self.captcha_mgr.get_ticket()
+            if not ticket or not randstr:
+                logger.error("登录验证码获取失败，无法继续登录")
+                return False
+            payload["vticket"] = ticket
+            payload["vrandstr"] = randstr
+            resp = self.session.post("/user/login", json=payload)
+            try:
+                res_json = resp.json()
+            except Exception:
+                pass
+
+        if resp.status_code == 200 and res_json.get("code") == 200:
+            # 同步更新 CSRF Token
+            csrf = self.session.cookies.get("X-CSRF-Token")
+            if csrf:
+                self.session.headers["x-csrf-token"] = csrf
+            logger.info(f"✓ 账号 {self.account_name} 登录成功！")
+            return True
+
+        err_msg = res_json.get("message") or resp.text
+        logger.error(f"❌ 账号 {self.account_name} 登录失败: {err_msg}")
+        return False
+
+    def fetch_user_info(self) -> Optional[Dict[str, Any]]:
+        """获取当前用户信息（积分、用户名等）"""
+        self._update_common_headers()
+        try:
+            resp = self.session.get("/user/?no_cache=true")
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 200:
+                    info = data.get("data", {})
+                    self.account_name = info.get("Name") or self.account_name
+                    self.points_before = info.get("Points", 0)
+                    return info
+        except Exception as e:
+            logger.warning(f"获取用户信息异常: {e}")
+        return None
+
+    def fetch_tasks(self) -> List[Dict[str, Any]]:
+        """获取任务列表"""
+        self._update_common_headers()
+        try:
+            resp = self.session.get("/user/reward/tasks")
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 200:
+                    return data.get("data", [])
+        except Exception as e:
+            logger.error(f"获取任务列表失败: {e}")
+        return []
+
+    def claim_daily_checkin(self) -> Dict[str, Any]:
+        """
+        执行每日签到核心业务逻辑：
+        1. 检查任务列表与签到状态
+        2. 若 Status == 2: 今日已完成，直接跳过
+        3. 若 Status == 1: 待领取，获取验证码并提交
+        """
+        user_info = self.fetch_user_info()
+        user_display = f"{self.account_name} (ID: {user_info.get('ID') if user_info else '未知'})"
+
+        tasks = self.fetch_tasks()
+        checkin_task = None
+        for t in tasks:
+            if t.get("Name") == "每日签到":
+                checkin_task = t
+                break
+
+        if not checkin_task:
+            return {
+                "user": user_display,
+                "status": "error",
+                "message": "未在任务列表中找到【每日签到】任务",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        task_status = checkin_task.get("Status")
+        # Status 2: 今日已领取
+        if task_status == 2:
+            logger.info(f"✨ 账号【{user_display}】今日已完成每日签到，当前总资产: {format_points(self.points_before)}。")
+            return {
+                "user": user_display,
+                "status": "already_done",
+                "message": "今日已签到 (无需重复领取)",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        # Status 1: 待签到
+        logger.info(f"🎯 账号【{user_display}】今日尚未签到，开始启动签到流程...")
+
+        # 1. 求解验证码
+        ticket, randstr = self.captcha_mgr.get_ticket()
+        if not ticket or not randstr:
+            return {
+                "user": user_display,
+                "status": "fail",
+                "message": "验证码求解失败，签到中止",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+        # 2. 提交签到请求
+        self._update_common_headers()
+        payload = {
+            "task_name": "每日签到",
+            "verifyCode": "",
+            "vticket": ticket,
+            "vrandstr": randstr,
+        }
+
+        resp = self.session.post("/user/reward/tasks", json=payload)
+        res_json = {}
+        try:
+            res_json = resp.json()
+        except Exception:
+            pass
+
+        if resp.status_code == 200 and res_json.get("code") == 200:
+            reward_data = res_json.get("data", {})
+            earned_points = reward_data.get("points", 500)
+            earned_cny = earned_points / POINTS_PER_CNY
+
+            # 刷新最新积分
+            latest_info = self.fetch_user_info()
+            self.points_after = latest_info.get("Points", self.points_before + earned_points) if latest_info else self.points_before + earned_points
+
+            msg = f"签到成功！获得 +{earned_points} 积分 (≈ {earned_cny:.2f} 元)"
+            logger.info(f"🎉 账号【{user_display}】{msg}，当前总资产: {format_points(self.points_after)}")
+            return {
+                "user": user_display,
+                "status": "success",
+                "message": msg,
+                "earned_points": earned_points,
+                "points_before": self.points_before,
+                "points_after": self.points_after,
+            }
+        else:
+            err_msg = res_json.get("message") or resp.text
+            logger.error(f"❌ 账号【{user_display}】签到失败: {err_msg}")
+            return {
+                "user": user_display,
+                "status": "fail",
+                "message": f"签到请求失败: {err_msg}",
+                "points_before": self.points_before,
+                "points_after": self.points_before,
+            }
+
+
+def load_dotenv(env_path: Optional[Path] = None):
+    """自动加载本地 .env 文件到 os.environ，方便本地直接调试运行"""
+    search_paths = [
+        env_path,
+        CURRENT_DIR / ".env",
+        Path.cwd() / ".env",
+    ]
+    for p in search_paths:
+        if p and p.is_file():
+            try:
+                with open(p, "r", encoding="utf-8") as f:
+                    for line in f:
+                        line = line.strip()
+                        if not line or line.startswith("#"):
+                            continue
+                        if "=" in line:
+                            k, v = line.split("=", 1)
+                            k = k.strip()
+                            v = v.strip()
+                            if (v.startswith('"') and v.endswith('"')) or (v.startswith("'") and v.endswith("'")):
+                                v = v[1:-1]
+                            if k not in os.environ or not os.environ[k]:
+                                os.environ[k] = v
+                logger.info(f"✓ 成功加载本地环境变量: {p}")
+                break
+            except Exception as e:
+                logger.warning(f"读取 .env 异常: {e}")
+
+
+def parse_accounts() -> List[Dict[str, str]]:
+    """
+    解析雨云账号配置 (优先加载本地 .env):
+    仅支持 RAINYUN_ACCOUNT="账号#密码" 格式
+    多账号使用 & 分割 (青龙面板推荐) 或 换行分割 (本地 .env 推荐)
+    例如:
+        RAINYUN_ACCOUNT="13754650804#pwd1&13800000000#pwd2"
+    """
+    load_dotenv()
+    accounts = []
+
+    acc_env = os.getenv("RAINYUN_ACCOUNT", "").strip()
+    if not acc_env:
+        return []
+
+    # 去除外层引号
+    if (acc_env.startswith('"') and acc_env.endswith('"')) or (acc_env.startswith("'") and acc_env.endswith("'")):
+        acc_env = acc_env[1:-1].strip()
+
+    # 按照 & 或 换行 分割多账号
+    raw_list = re.split(r"[&\n]", acc_env)
+    for item in raw_list:
+        item = item.strip()
+        if not item or "#" not in item:
+            continue
+        u, p = item.split("#", 1)
+        u, p = u.strip(), p.strip()
+        if u and p and not any(a.get("user") == u for a in accounts):
+            accounts.append({"user": u, "password": p})
+
+    return accounts
+
+
+def main():
+    print("=" * 60)
+    print("      🚀 雨云 (Rainyun) 自动登录与每日签到任务启动")
+    print("=" * 60)
+
+    accounts = parse_accounts()
+    if not accounts:
+        msg = (
+            "未检测到雨云账号配置！请在青龙环境变量或本地 .env 中配置 RAINYUN_ACCOUNT\n"
+            "格式: 账号#密码 (多账号用 & 或换行分割)\n"
+            "例如: RAINYUN_ACCOUNT=\"13754650804#pwd1&13800000000#pwd2\"\n"
+            "如需远程验证码服务，可添加 TCAPTCHA_API_URL (如 http://x.x.x.x:8000/solve)"
+        )
+        logger.warning(msg)
+        send("雨云每日签到异常", msg)
+        return
+
+    logger.info(f"已成功加载 {len(accounts)} 个雨云账号配置")
+    captcha_mgr = CaptchaManager()
+
+    results = []
+    for idx, acc in enumerate(accounts, 1):
+        logger.info(f"\n--- [正在处理账号 {idx}/{len(accounts)}] ---")
+        client = RainyunClient(
+            user=acc["user"],
+            password=acc["password"],
+            captcha_mgr=captcha_mgr,
+        )
+
+        login_ok = client.login()
+        if not login_ok:
+            results.append({
+                "user": client.account_name,
+                "status": "login_failed",
+                "message": "登录失败",
+                "points_before": 0,
+                "points_after": 0,
+            })
+            continue
+
+        res = client.claim_daily_checkin()
+        results.append(res)
+
+        # 多账号之间随机休眠 2~4 秒
+        if idx < len(accounts):
+            sleep_sec = random.uniform(2.0, 4.0)
+            time.sleep(sleep_sec)
+
+    # 统计汇总
+    print("\n" + "=" * 60)
+    print("              📊 任务执行结果统计报表")
+    print("=" * 60)
+
+    success_cnt = sum(1 for r in results if r["status"] in ["success", "already_done"])
+    summary_lines = []
+    total_points = 0
+
+    for idx, r in enumerate(results, 1):
+        status_icon = "✅" if r["status"] in ["success", "already_done"] else "❌"
+        pts = r.get("points_after", 0)
+        total_points += pts
+        cny_str = format_points(pts)
+        line = f"[{idx}] {status_icon} 账号: {r['user']} | 结果: {r['message']} | 当前账户: {cny_str}"
+        summary_lines.append(line)
+        print(line)
+
+    total_cny = total_points / POINTS_PER_CNY
+    total_summary = f"💰 全部账号总资产: {total_points} 积分 (可提现 ≈ {total_cny:.2f} 元)"
+    summary_lines.append(total_summary)
+    print(total_summary)
+    print("=" * 60)
+
+    # 推送青龙系统通知
+    notify_title = f"雨云签到: 成功 {success_cnt}/{len(results)} | 总资产 ≈ {total_cny:.2f}元"
+    notify_content = "\n".join(summary_lines)
+    send(notify_title, notify_content)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tcaptcha/__init__.py b/tcaptcha/__init__.py
new file mode 100644
index 0000000..52623a8
--- /dev/null
+++ b/tcaptcha/__init__.py
@@ -0,0 +1,15 @@
+# -*- coding: utf-8 -*-
+"""Tencent Captcha Package"""
+
+from .client import TencentCaptchaClient
+from .crypto import extract_eks, generate_collect
+from .slicer import slice_prompt_image
+from .solver import CaptchaSolver
+
+__all__ = [
+    "TencentCaptchaClient",
+    "CaptchaSolver",
+    "extract_eks",
+    "generate_collect",
+    "slice_prompt_image",
+]
diff --git a/tcaptcha/server.py b/tcaptcha/server.py
new file mode 100644
index 0000000..178ddea
--- /dev/null
+++ b/tcaptcha/server.py
@@ -0,0 +1,149 @@
+# -*- coding: utf-8 -*-
+"""
+腾讯天御点选验证码纯协议 HTTP 微服务 (Tencent Turing Captcha HTTP Microservice)
+用于在独立机器/宿主机/GPU服务器上运行，供青龙容器或其他轻量级客户端通过 HTTP API 跨机调用。
+基于 Python 原生 ThreadingHTTPServer 实现，零额外依赖 (无需额外安装 FastAPI/Flask)。
+
+使用方式:
+  uv run python -m tcaptcha.server --port 8000 --host 0.0.0.0
+调用接口:
+  POST http://<IP>:8000/solve
+  请求体 (可选): {"aid": "2039519451"}
+  返回 JSON:
+  {
+      "code": 200,
+      "success": true,
+      "ticket": "tr03...",
+      "randstr": "@...",
+      "elapsed_ms": 820
+  }
+"""
+
+import argparse
+import json
+import logging
+import sys
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+
+PROJECT_ROOT = Path(__file__).resolve().parent.parent
+if str(PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(PROJECT_ROOT))
+
+from tcaptcha.client import TencentCaptchaClient
+from tcaptcha.solver import CaptchaSolver
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("tcaptcha_server")
+
+GLOBAL_SOLVER = None
+
+
+def get_solver() -> CaptchaSolver:
+    global GLOBAL_SOLVER
+    if GLOBAL_SOLVER is None:
+        logger.info("正在初始化并预加载 AI 求解推理引擎 (YOLOv8 + ResNet18)...")
+        GLOBAL_SOLVER = CaptchaSolver()
+        logger.info("✓ AI 推理引擎预加载完成！")
+    return GLOBAL_SOLVER
+
+
+class CaptchaHttpHandler(BaseHTTPRequestHandler):
+    def _send_json(self, code: int, data: dict):
+        body = json.dumps(data, ensure_ascii=False).encode("utf-8")
+        self.send_response(code)
+        self.send_header("Content-Type", "application/json; charset=utf-8")
+        self.send_header("Content-Length", str(len(body)))
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.send_header("Access-Control-Allow-Headers", "*")
+        self.send_header("Access-Control-Allow-Methods", "GET, POST, OPTIONS")
+        self.end_headers()
+        self.wfile.write(body)
+
+    def do_OPTIONS(self):
+        self._send_json(200, {"status": "ok"})
+
+    def do_GET(self):
+        if self.path in ["/health", "/"]:
+            self._send_json(200, {
+                "status": "online",
+                "service": "Tencent Captcha Solver Microservice",
+                "endpoints": {
+                    "solve": "POST /solve (body: {'aid': '2039519451'})",
+                    "health": "GET /health"
+                }
+            })
+        elif self.path.startswith("/solve"):
+            # 允许通过 GET 快速调试
+            self._handle_solve({"aid": "2039519451"})
+        else:
+            self._send_json(404, {"error": "Not Found"})
+
+    def do_POST(self):
+        if self.path.startswith("/solve"):
+            content_length = int(self.headers.get("Content-Length", 0))
+            body = self.rfile.read(content_length) if content_length > 0 else b"{}"
+            try:
+                params = json.loads(body.decode("utf-8")) if body else {}
+            except Exception:
+                params = {}
+            self._handle_solve(params)
+        else:
+            self._send_json(404, {"error": "Not Found"})
+
+    def _handle_solve(self, params: dict):
+        aid = params.get("aid") or "2039519451"
+        logger.info(f"收到求解请求 (AppID: {aid})...")
+        solver = get_solver()
+        client = TencentCaptchaClient(aid=aid, solver=solver)
+        result = client.solve()
+
+        if result.get("success"):
+            self._send_json(200, {
+                "code": 200,
+                "success": True,
+                "ticket": result.get("ticket"),
+                "randstr": result.get("randstr"),
+                "elapsed_ms": result.get("elapsed_ms"),
+                "points": result.get("points"),
+            })
+        else:
+            self._send_json(500, {
+                "code": 500,
+                "success": False,
+                "error": result.get("error"),
+                "elapsed_ms": result.get("elapsed_ms"),
+            })
+
+    def log_message(self, format, *args):
+        logger.info("%s - %s", self.address_string(), format % args)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Tencent Captcha Microservice")
+    parser.add_argument("--host", type=str, default="0.0.0.0", help="Listen host (default: 0.0.0.0)")
+    parser.add_argument("--port", type=int, default=8000, help="Listen port (default: 8000)")
+    args = parser.parse_args()
+
+    # 预加载推理引擎
+    get_solver()
+
+    server_address = (args.host, args.port)
+    httpd = ThreadingHTTPServer(server_address, CaptchaHttpHandler)
+    logger.info(f"🚀 验证码微服务已启动: http://{args.host}:{args.port}")
+    logger.info("可用于青龙面板配置环境变量: TCAPTCHA_API_URL=http://<IP>:%d/solve", args.port)
+
+    try:
+        httpd.serve_forever()
+    except KeyboardInterrupt:
+        logger.info("服务已停止")
+    finally:
+        httpd.server_close()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tcaptcha/solver.py b/tcaptcha/solver.py
index b79a12c..892fa0b 100644
--- a/tcaptcha/solver.py
+++ b/tcaptcha/solver.py
@@ -79,19 +79,30 @@ class CaptchaSolver:
     def parse_prompt_targets(self, prompt_img: str | Path | bytes | Image.Image) -> List[int]:
         """
         自动识别并解析提示图中 3 个目标图标的真实类别 ID (0~11)
+        支持干净模板匹配与 ResNet18 分类器自动双模降级
         """
         crops = slice_prompt_image(prompt_img)
-        target_classes = []
-        for crop_img, _ in crops[:3]:
-            arr = np.array(crop_img.convert("L"))
-            bg = np.median(arr)
-            bin_c = cv2.resize(((arr < bg - 20).astype(np.uint8) * 255), (48, 48), interpolation=cv2.INTER_AREA)
+        if not crops:
+            return []
 
-            scores = [cv2.matchTemplate(bin_c, t[1], cv2.TM_CCOEFF_NORMED)[0, 0] for t in self.templates]
-            best_cid = int(np.argmax(scores))
-            target_classes.append(best_cid)
+        if self.templates:
+            target_classes = []
+            for crop_img, _ in crops[:3]:
+                arr = np.array(crop_img.convert("L"))
+                bg = np.median(arr)
+                bin_c = cv2.resize(((arr < bg - 20).astype(np.uint8) * 255), (48, 48), interpolation=cv2.INTER_AREA)
 
-        return target_classes
+                scores = [cv2.matchTemplate(bin_c, t[1], cv2.TM_CCOEFF_NORMED)[0, 0] for t in self.templates]
+                best_cid = int(np.argmax(scores))
+                target_classes.append(best_cid)
+            return target_classes
+
+        # 模板缺失时自动使用 ResNet18 分类器直接预测提示小图类别
+        patch_tensors = torch.stack([self.transform(c[0].convert("RGB")) for c in crops[:3]]).to(self.device)
+        with torch.no_grad():
+            logits = self.classifier(patch_tensors)
+            probs = torch.softmax(logits, dim=1).cpu().numpy()
+        return [int(np.argmax(p[:12])) for p in probs]
 
     def _extract_candidates(self, bg_img: str | Path | bytes | Image.Image) -> List[Tuple[int, int, Image.Image]]:
         """从背景图中提取所有去重后的候选图标 (cx, cy, patch)"""