v1.8.0 智能截图多视觉大模型接口配置(优先级+失败降级) + 提取历史图示统计
1) 智能截图·视觉大模型配置: - 支持配置多个视觉大模型接口(均含视觉能力), 按列表顺序=优先级调用 - 失败/报错/超时自动降级到下一个接口, 全部失败才保守停止滚动 - 预置两个高优先级接口: 本地18008 Qwen3.8-27B-NVFP4 + SiliconFlow Kimi-K2.6 - 前端弹窗: 接口增删改/启用开关/⬆⬇调整优先级/逐接口🧪测试连接 - /api/smart/test 支持 endpoint_id 测试已保存接口; 旧单接口配置自动迁移为 endpoints[0] - 每步判断记录所用模型名+接口名(详情可见降级链路) 2) 提取历史图示统计: - /api/history/stats?dimension=day|action|backend|status|caller|method&days=N - 前端📊统计弹窗: 6个角度切换 + 7/30/90天范围 + 饼图/柱状图切换 + 汇总(总数/成功率) + 数据表 + 下载PNG - 按天维度缺0补0, caller Top8+其他
This commit is contained in:
@@ -163,10 +163,28 @@ init_db()
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# ===== 按需截图（AI智能判断滚动）配置 =====
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CONFIG_FILE = DATA_DIR / "config.json"
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# 预置视觉大模型接口（按列表顺序 = 优先级，越靠前越优先；失败自动降级到下一个）
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DEFAULT_ENDPOINTS = [
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{
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"id": "ep_local_qwen",
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"name": "本地 Qwen3.8-27B (18008)",
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"base_url": "http://121.40.164.32:18008/v1",
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"api_key": "xxxx",
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"model": "unsloth/Qwen3.8-27B-NVFP4",
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"enabled": True
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},
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{
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"id": "ep_siliconflow_kimi",
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"name": "SiliconFlow Kimi-K2.6",
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"base_url": "https://api.siliconflow.cn/v1",
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"api_key": "sk-fhpoexpptvjghpnphtaxbkhjwulzovoqfffbckcfscjmwhcg",
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"model": "Pro/moonshotai/Kimi-K2.6",
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"enabled": True
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}
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]
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DEFAULT_SMART_CONFIG = {
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"base_url": "https://www.autodl.art/api/v1",
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"api_key": "F9MBfolzuapqTsD4KmUf9qen720rXvUZ3Sp3IrWiCTukqonx",
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"model": "qwen3.6-plus",
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"endpoints": [json.loads(json.dumps(ep)) for ep in DEFAULT_ENDPOINTS],
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"prompt": (
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"你是网页内容完整性判断助手。下面是一张网页滚动截图的当前视口画面。"
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"请判断：这个网页的主题内容（正文/主要内容）是否已经完整截取完成，是否还需要继续向下滚动？\n"
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@@ -182,7 +200,7 @@ DEFAULT_SMART_CONFIG = {
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def load_smart_config():
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"""读取按需截图 LLM 配置（缺省回默认）"""
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"""读取按需截图 LLM 配置（缺省回默认；旧单接口配置自动迁移为 endpoints[0]）"""
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cfg = json.loads(json.dumps(DEFAULT_SMART_CONFIG))
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if CONFIG_FILE.exists():
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try:
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@@ -193,16 +211,49 @@ def load_smart_config():
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cfg[k] = saved[k]
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except Exception:
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pass
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# 兼容旧版单接口配置：没有 endpoints 时，把 base_url/api_key/model 迁移为第一个接口
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eps = cfg.get("endpoints") or []
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if not eps and cfg.get("base_url"):
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eps = [{
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"id": "ep_legacy",
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"name": cfg.get("model") or cfg.get("base_url"),
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"base_url": cfg["base_url"],
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"api_key": cfg.get("api_key", ""),
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"model": cfg.get("model", ""),
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"enabled": True
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}]
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cfg["endpoints"] = eps
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return cfg
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def save_smart_config(cfg):
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"""保存按需截图 LLM 配置"""
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"""保存按需截图 LLM 配置（endpoints 数组顺序 = 优先级）"""
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merged = json.loads(json.dumps(DEFAULT_SMART_CONFIG))
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if isinstance(cfg, dict):
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for k in DEFAULT_SMART_CONFIG:
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# 滚动/提示词参数
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for k in ("prompt", "max_scrolls", "scroll_ratio", "timeout"):
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if k in cfg and cfg[k] not in (None, ""):
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merged[k] = cfg[k]
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# 接口列表：保留有效字段，补 id/name/enabled 默认值
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eps = cfg.get("endpoints")
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if isinstance(eps, list) and eps:
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clean = []
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for i, ep in enumerate(eps):
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if not isinstance(ep, dict) or not ep.get("base_url"):
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continue
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clean.append({
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"id": ep.get("id") or f"ep_{i+1}",
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"name": ep.get("name") or ep.get("model") or f"接口{i+1}",
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"base_url": ep["base_url"],
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"api_key": ep.get("api_key", ""),
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"model": ep.get("model", ""),
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"enabled": bool(ep.get("enabled", True))
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})
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if clean:
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merged["endpoints"] = clean
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elif isinstance(cfg.get("endpoints"), list) and not eps:
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# 显式传空列表 = 清空
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merged["endpoints"] = []
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CONFIG_FILE.parent.mkdir(exist_ok=True)
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CONFIG_FILE.write_text(json.dumps(merged, ensure_ascii=False, indent=2), encoding="utf-8")
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return merged
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@@ -225,17 +276,18 @@ def extract_json_from_content(content):
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return None
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def llm_judge_screenshot(image_path, cfg):
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def llm_call_vision(image_path, cfg, endpoint):
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"""
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调用视觉大模型判断当前截图是否已覆盖主题内容、是否还需滚动
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用单个视觉大模型接口判断截图
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endpoint: {"base_url", "api_key", "model", "name"}
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返回: {"complete": bool, "reason": str}
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异常时抛 ValueError（调用方决定如何处置）
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任何失败（网络/HTTP/解析/格式）都抛 ValueError，由上层降级到下一个接口
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"""
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import requests
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img_b64 = base64.b64encode(Path(image_path).read_bytes()).decode()
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url = cfg["base_url"].rstrip("/") + "/chat/completions"
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url = endpoint["base_url"].rstrip("/") + "/chat/completions"
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payload = {
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"model": cfg["model"],
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"model": endpoint.get("model", ""),
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"messages": [{
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"role": "user",
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"content": [
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@@ -245,20 +297,45 @@ def llm_judge_screenshot(image_path, cfg):
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}],
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"max_tokens": 300
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}
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headers = {"Authorization": f"Bearer {cfg['api_key']}", "Content-Type": "application/json"}
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headers = {"Authorization": f"Bearer {endpoint.get('api_key', '')}", "Content-Type": "application/json"}
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resp = requests.post(url, headers=headers, json=payload, timeout=int(cfg.get("timeout", 120)))
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if resp.status_code != 200:
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raise ValueError(f"LLM 接口返回 {resp.status_code}: {resp.text[:200]}")
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raise ValueError(f"HTTP {resp.status_code}: {resp.text[:200]}")
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try:
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content = resp.json()["choices"][0]["message"]["content"]
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except Exception:
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raise ValueError(f"LLM 响应格式异常: {resp.text[:200]}")
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raise ValueError(f"响应格式异常: {resp.text[:200]}")
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parsed = extract_json_from_content(content)
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if not parsed or "complete" not in parsed:
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raise ValueError(f"LLM 判断结果解析失败，原始输出: {content[:200]}")
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raise ValueError(f"判断结果解析失败，原始输出: {content[:200]}")
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return {"complete": bool(parsed["complete"]), "reason": str(parsed.get("reason", ""))}
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def llm_judge_screenshot(image_path, cfg):
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"""
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调用视觉大模型判断当前截图是否已覆盖主题内容、是否还需滚动。
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按 endpoints 列表顺序（高→低优先级）逐个尝试，失败/报错/超时自动降级到下一个；
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全部失败才抛 ValueError（调用方保守停止滚动）。
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返回: {"complete": bool, "reason": str, "model": str, "used_endpoint": str}
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"""
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import requests # noqa: F401 (确保模块可用，实际在 llm_call_vision 中导入)
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endpoints = cfg.get("endpoints") or []
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enabled = [ep for ep in endpoints if ep.get("enabled", True)]
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if not enabled:
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raise ValueError("未配置可用的视觉大模型接口（请到「⚙️ 智能配置」添加）")
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errors = []
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for ep in enabled:
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ep_name = ep.get("name") or ep.get("model") or ep.get("base_url", "")
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try:
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result = llm_call_vision(image_path, cfg, ep)
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result["model"] = ep.get("model", "")
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result["used_endpoint"] = ep_name
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return result
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except Exception as e:
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errors.append(f"{ep_name}: {e}")
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raise ValueError("全部视觉大模型接口调用失败 → " + " | ".join(errors))
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def stitch_images(image_paths, out_path):
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"""把多张视口截图纵向拼接成一张长图（所有图对齐到最宽宽度）"""
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from PIL import Image
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@@ -764,7 +841,8 @@ def smart_capture_agent_browser(url, cfg, wait_time, viewport):
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# 视觉大模型实时判断
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try:
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judge = llm_judge_screenshot(shot, cfg)
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steps.append({"step": step_no, "complete": judge["complete"], "reason": judge["reason"]})
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steps.append({"step": step_no, "complete": judge["complete"], "reason": judge["reason"],
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"model": judge.get("model", ""), "endpoint": judge.get("used_endpoint", "")})
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except ValueError as ve:
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# 判断失败：保守停止，保留已截内容
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steps.append({"step": step_no, "complete": True, "reason": f"⚠️ 大模型判断失败，停止滚动: {ve}"})
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@@ -902,7 +980,8 @@ async def smart_capture_playwright(url, cfg, wait_time, viewport):
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try:
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judge = llm_judge_screenshot(shot, cfg)
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steps.append({"step": step_no, "complete": judge["complete"], "reason": judge["reason"]})
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steps.append({"step": step_no, "complete": judge["complete"], "reason": judge["reason"],
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"model": judge.get("model", ""), "endpoint": judge.get("used_endpoint", "")})
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except ValueError as ve:
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steps.append({"step": step_no, "complete": True, "reason": f"⚠️ 大模型判断失败，停止滚动: {ve}"})
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stop_reason = str(ve)
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@@ -1145,7 +1224,10 @@ def api_info():
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"endpoints": {
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"/api/capture": "POST - Capture webpage (screenshot/html/text/smart) + 自动入库历史(记录调用者/方式/原始HTML)",
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"/api/backends": "GET - 可用后端列表与默认顺序(供前端渲染后端选择器)",
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"/api/smart/config": "GET/POST - 智能截图视觉大模型多接口配置(列表顺序=优先级,失败自动降级)",
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"/api/smart/test": "POST - 测试指定视觉接口连通性({endpoint_id} / {endpoint} / 旧版{config})",
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"/api/history": "GET - 历史记录分页列表 (?page&page_size&action&search)",
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"/api/history/stats": "GET - 历史图示统计 (?dimension=day|action|backend|status|caller|method&days=30)",
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"/api/history/<id>": "GET - 历史记录详情 / DELETE - 删除记录",
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"/api/history/<id>/file": "GET - 读取历史截图文件",
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"/api/history/<id>/html": "GET - 读取保存的原始HTML文件",
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@@ -1197,6 +1279,78 @@ def history_list():
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})
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@app.route('/api/history/stats', methods=['GET'])
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def history_stats():
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"""
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提取历史图示统计
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参数:
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dimension: day(按天趋势) | action(操作类型) | backend(后端) | status(状态) | caller(调用者) | method(调用方式)
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days: 按天维度的天数范围(1-365, 默认30); 其他维度默认全量(也可传 days 只统计最近N天)
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返回: {success, dimension, days, total, success_count, success_rate, items:[{label, value}]}
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"""
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dimension = request.args.get('dimension', 'action')
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valid = ('day', 'action', 'backend', 'status', 'caller', 'method')
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if dimension not in valid:
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return jsonify({"success": False, "error": f"dimension 需为 {'/'.join(valid)}"}), 400
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days = min(365, max(1, int(request.args.get('days', 30))))
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# 时间下限（可选）：非 day 维度也可按 days 过滤
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from datetime import timedelta
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cutoff = (datetime.now() - timedelta(days=days)).strftime("%Y-%m-%d %H:%M:%S")
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conn = get_db()
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# 总量 / 成功率
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total = conn.execute("SELECT COUNT(*) c FROM captures").fetchone()["c"]
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sc = conn.execute("SELECT COUNT(*) c FROM captures WHERE status='success'").fetchone()["c"]
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items = []
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if dimension == 'day':
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# 最近 days 天的每日提取量（缺0补0）
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rows = conn.execute(
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"SELECT substr(created_at,1,10) d, COUNT(*) c FROM captures WHERE created_at >= ? GROUP BY d ORDER BY d",
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(cutoff,)
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).fetchall()
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m = {r["d"]: r["c"] for r in rows}
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date_list = []
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for i in range(days - 1, -1, -1):
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date_list.append((datetime.now() - timedelta(days=i)).strftime("%Y-%m-%d"))
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items = [{"label": d, "value": m.get(d, 0)} for d in date_list]
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else:
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col = {"action": "action", "backend": "backend", "status": "status",
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"caller": "caller", "method": "call_method"}[dimension]
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rows = conn.execute(
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f"SELECT {col} k, COUNT(*) c FROM captures WHERE created_at >= ? GROUP BY {col} ORDER BY c DESC",
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(cutoff,)
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).fetchall()
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# caller 太多时只保留 Top 8 + 其他
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if dimension == 'caller':
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top = rows[:8]
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rest = sum(r["c"] for r in rows[8:])
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items = [{"label": r["k"] or "未知", "value": r["c"]} for r in top]
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if rest:
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items.append({"label": "其他", "value": rest})
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else:
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for r in rows:
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label = r["k"] or "(空)"
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if dimension == 'status':
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label = "成功" if r["k"] == "success" else ("失败" if r["k"] == "failed" else r["k"])
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elif dimension == 'action':
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label = {"screenshot": "📸 截图", "html": "📄 HTML", "text": "📝 文本", "smart": "🧠 按需截图"}.get(r["k"], r["k"])
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items.append({"label": label, "value": r["c"]})
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conn.close()
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# 按天维度去 emoji（保持纯净日期标签）
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return jsonify({
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"success": True,
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"dimension": dimension,
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"days": days,
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"total": total,
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"success_count": sc,
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"success_rate": round(sc / total, 4) if total else 0,
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"items": items
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})
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@app.route('/api/history/<int:rid>', methods=['GET'])
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def history_detail(rid):
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"""历史记录详情（含完整内容）"""
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@@ -1277,25 +1431,46 @@ def smart_config_endpoint():
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@app.route('/api/smart/test', methods=['POST'])
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def smart_test_endpoint():
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"""测试按需截图 LLM 接口连通性（发一条小文本消息验证 base_url/api_key/model）"""
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"""测试视觉大模型接口连通性（发一条小文本消息验证 base_url/api_key/model）。
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入参（三选一）：
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{endpoint_id: "ep_xxx"} → 测试已保存配置中的某个接口
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{endpoint: {base_url, api_key, model}} → 直接测试传入的接口
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{config: {...}} 或 {base_url,...} → 兼容旧版单接口测试
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"""
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import requests
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data = request.get_json() or {}
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cfg = dict(load_smart_config())
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if data.get("config"):
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for k in DEFAULT_SMART_CONFIG:
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if k in data["config"] and data["config"][k] not in (None, ""):
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cfg[k] = data["config"][k]
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elif data.get("base_url") or data.get("api_key") or data.get("model"):
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for k in ("base_url", "api_key", "model"):
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if data.get(k):
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cfg[k] = data[k]
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ep = None
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url = cfg["base_url"].rstrip("/") + "/chat/completions"
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payload = {"model": cfg["model"], "messages": [{"role": "user", "content": "ping"}], "max_tokens": 5}
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headers = {"Authorization": f"Bearer {cfg['api_key']}", "Content-Type": "application/json"}
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# 1) endpoint_id：从已保存配置里找
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if data.get("endpoint_id"):
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saved = load_smart_config()
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for e in (saved.get("endpoints") or []):
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if e.get("id") == data["endpoint_id"]:
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ep = e
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break
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if not ep:
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return jsonify({"success": False, "error": f"接口 {data['endpoint_id']} 不存在"}), 404
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# 2) endpoint 对象：直接测试
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elif isinstance(data.get("endpoint"), dict) and data["endpoint"].get("base_url"):
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ep = data["endpoint"]
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# 3) 兼容旧版：config 或平铺字段
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else:
|
||||
cfg = dict(load_smart_config())
|
||||
override = data.get("config") or data
|
||||
if isinstance(override, dict):
|
||||
for k in ("base_url", "api_key", "model", "timeout"):
|
||||
if k in override and override[k] not in (None, ""):
|
||||
cfg[k] = override[k]
|
||||
ep = {"base_url": cfg["base_url"], "api_key": cfg.get("api_key", ""),
|
||||
"model": cfg.get("model", ""), "name": cfg.get("model", "")}
|
||||
|
||||
url = ep["base_url"].rstrip("/") + "/chat/completions"
|
||||
payload = {"model": ep.get("model", ""), "messages": [{"role": "user", "content": "ping"}], "max_tokens": 5}
|
||||
headers = {"Authorization": f"Bearer {ep.get('api_key', '')}", "Content-Type": "application/json"}
|
||||
timeout = int(data.get("timeout") or 60)
|
||||
t0 = time.time()
|
||||
try:
|
||||
resp = requests.post(url, headers=headers, json=payload, timeout=int(cfg.get("timeout", 120)))
|
||||
resp = requests.post(url, headers=headers, json=payload, timeout=timeout)
|
||||
cost = round(time.time() - t0, 2)
|
||||
if resp.status_code != 200:
|
||||
return jsonify({"success": False, "error": f"HTTP {resp.status_code}: {resp.text[:200]}", "latency": cost}), 400
|
||||
@@ -1304,7 +1479,7 @@ def smart_test_endpoint():
|
||||
reply = d["choices"][0]["message"]["content"][:80]
|
||||
except Exception:
|
||||
reply = "(无内容)"
|
||||
return jsonify({"success": True, "latency": cost, "model": cfg["model"], "reply": reply})
|
||||
return jsonify({"success": True, "latency": cost, "model": ep.get("model", ""), "reply": reply})
|
||||
except Exception as e:
|
||||
return jsonify({"success": False, "error": str(e)}), 400
|
||||
|
||||
|
||||
Reference in New Issue
Block a user