#!/usr/bin/env python3 import argparse import asyncio import base64 import datetime as dt import hashlib import hmac import io import json import logging import mimetypes import os import re import subprocess import tempfile import time import urllib.parse import uuid from dingtalk_stream import AckMessage, CallbackMessage, ChatbotHandler, ChatbotMessage from dingtalk_stream import Credential, DingTalkStreamClient import requests try: from PIL import Image except Exception: Image = None try: import boto3 from botocore.config import Config as BotoConfig except Exception: boto3 = None BotoConfig = None MARKET_HINT_KEYWORDS = ( "市场分析", "市场数据分析", "行业分析", "类目分析", "竞品分析", "趋势分析", ) SALES_HINT_KEYWORDS = ( "销售数据", "销售报表", "销售看板", "公司销售", "业绩报表", "业绩数据", "费比监控", ) SENSITIVE_SALES_KEYWORDS = ( "销售", "业绩", "售后", "退款", "店铺", "发货", "工单", "费比", ) EXPLICIT_AMOUNT_KEYWORDS = ( "金额", "费用", "收入", "利润", "成本", "客单价", "gmv", "销售额", "退款额", "毛利", ) INSTALL_MEDIA_HINT_KEYWORDS = ( "安装图纸", "安装视频", "安装说明书", "图纸地址", "视频地址", "图纸链接", "视频链接", "订单号查图纸", "订单号查视频", ) INSTALL_MEDIA_STITCH_HINT_KEYWORDS = ( "拼接", "合并", "一张图", "整合图", "汇总图", ) VIDEO_ANALYSIS_HINT_KEYWORDS = ( "视频", "video", "短片", "片段", ) VIDEO_ANALYSIS_ACTION_KEYWORDS = ( "分析", "解读", "总结", "提炼", "复盘", "讲解", "评价", "建议", "看看", "看下", "说明", ) VIDEO_SCRIPT_HINT_KEYWORDS = ( "脚本", "分镜", "复刻", "仿拍", "同款", "类似视频", "拍摄方案", "镜头脚本", ) DALONGXIA_ANALYTICS_HINT_KEYWORDS = ( "壹点需求", "需求系统", "任务进度总览", "进度总览", "数据分析总览", "需求统计", "设计师绩效", "流程效率", "预警", "维度分析", "主部门", "designerperformance", "dimensionanalysis", "taskprogressoverview", "designerdeduction", "designerscore", "primarydept", "primarytask", "analytics", ) URL_RE = re.compile( r"https?://[A-Za-z0-9\-._~:/?#\[\]@!$&'()*+,;=%]+", re.IGNORECASE, ) IP_RE = re.compile(r"\b(?:\d{1,3}\.){3}\d{1,3}(?::\d+)?\b") DOMAIN_RE = re.compile(r"\b(?:[a-zA-Z0-9-]+\.)+(?:com|cn|net|ai|org|io)\b", re.IGNORECASE) IMAGE_EXT_RE = re.compile(r"\.(?:png|jpg|jpeg|gif|webp|bmp|svg)(?:$|[?#])", re.IGNORECASE) VIDEO_EXT_RE = re.compile(r"\.(?:mp4|mov|m4v|webm|mkv|avi|flv|wmv|ts|m3u8)(?:$|[?#])", re.IGNORECASE) ORDER_ID_RE = re.compile(r"\b\d{12,24}(?:-\d{2,4})?\b") SMALLTALK_SET = { "你好", "您好", "嗨", "哈喽", "在吗", "在嘛", "早上好", "上午好", "中午好", "下午好", "晚上好", "hi", "hello", } def bool_env(name: str, default: bool) -> bool: raw = os.getenv(name) if raw is None: return default return raw.strip().lower() in {"1", "true", "yes", "on"} class OpenClawDingTalkBot(ChatbotHandler): def __init__(self, logger: logging.Logger): super().__init__() self.logger = logger self.openclaw_bin = os.getenv("OPENCLAW_BIN", "/usr/bin/openclaw") self.openclaw_timeout = int(os.getenv("OPENCLAW_TIMEOUT", "600")) self.market_brief_bin = os.getenv("MARKET_BRIEF_BIN", "/usr/local/bin/market-brief-report") self.market_brief_timeout = int(os.getenv("MARKET_BRIEF_TIMEOUT", "180")) self.install_media_bin = os.getenv("INSTALL_MEDIA_BIN", "/usr/local/bin/install-media-lookup") self.install_media_timeout = int(os.getenv("INSTALL_MEDIA_TIMEOUT", "120")) self.prefix = os.getenv("BOT_PREFIX", "/oc").strip() self.require_prefix = bool_env("REQUIRE_PREFIX", False) self.reply_max_chars = int(os.getenv("REPLY_MAX_CHARS", "3500")) self.session_prefix = os.getenv("OPENCLAW_SESSION_PREFIX", "dingtalk") self.hide_source_urls = bool_env("HIDE_SOURCE_URLS", True) self.send_processing_hint = bool_env("SEND_PROCESSING_HINT", True) self.dedupe_ttl_seconds = int(os.getenv("DEDUPE_TTL_SECONDS", "300")) self.session_max_lines = int(os.getenv("OPENCLAW_SESSION_MAX_LINES", "120")) self.sessions_dir = os.getenv("OPENCLAW_SESSIONS_DIR", "/root/.openclaw/agents/main/sessions") self.unmask_url_hosts = { h.strip().lower() for h in os.getenv( "UNMASK_URL_HOSTS", "img.alicdn.com,static.jiansun.vip,img.jiansuntuzhi.cn,v.youku.com", ).split(",") if h.strip() } self._recent_event_ts = {} self.processing_hint_text = os.getenv( "PROCESSING_HINT_TEXT", "已收到，正在处理你的需求，请稍等1-3分钟。", ).strip() self.reply_style = os.getenv("REPLY_STYLE", "action_card").strip().lower() self.action_card_title = os.getenv("ACTION_CARD_TITLE", "OpenClaw 助理").strip() self.action_card_tips = os.getenv("ACTION_CARD_TIPS", "").strip() self.action_card_logo = os.getenv("ACTION_CARD_LOGO", "").strip() self.action_card_btn_text = os.getenv("ACTION_CARD_BTN_TEXT", "").strip() self.action_card_btn_url = os.getenv("ACTION_CARD_BTN_URL", "").strip() self.smalltalk_reply_text = os.getenv( "SMALLTALK_REPLY_TEXT", "你好，我在。请直接告诉我你的任务目标（例如：查询某店上周售后原因TOP5并给出改进建议）。", ).strip() self.max_parallel_jobs = max(1, min(int(os.getenv("BOT_MAX_PARALLEL_JOBS", "4")), 16)) self._work_semaphore = asyncio.Semaphore(self.max_parallel_jobs) self._conversation_locks = {} self.card_disable_seconds = max(300, min(int(os.getenv("CARD_DISABLE_SECONDS", "43200")), 86400)) self.card_disabled_until = 0.0 self.install_media_stitch_enabled = bool_env("INSTALL_MEDIA_STITCH_ENABLED", True) self.install_media_stitch_min_images = max(2, min(int(os.getenv("INSTALL_MEDIA_STITCH_MIN_IMAGES", "2")), 10)) self.install_media_stitch_max_images = max( self.install_media_stitch_min_images, min(int(os.getenv("INSTALL_MEDIA_STITCH_MAX_IMAGES", "20")), 50), ) self.install_media_fetch_timeout = max(3, min(int(os.getenv("INSTALL_MEDIA_FETCH_TIMEOUT", "12")), 60)) self.install_media_max_width = max(720, min(int(os.getenv("INSTALL_MEDIA_MAX_WIDTH", "1600")), 4000)) self.s3_endpoint = ( os.getenv("INSTALL_MEDIA_S3_ENDPOINT", "").strip() or os.getenv("S3_ENDPOINT", "").strip() ) self.s3_bucket = ( os.getenv("INSTALL_MEDIA_S3_BUCKET", "").strip() or os.getenv("S3_BUCKET", "").strip() ) self.s3_region = ( os.getenv("INSTALL_MEDIA_S3_REGION", "").strip() or os.getenv("S3_REGION", "us-east-1").strip() ) self.s3_access_key = ( os.getenv("INSTALL_MEDIA_S3_ACCESS_KEY_ID", "").strip() or os.getenv("S3_ACCESS_KEY_ID", "").strip() ) self.s3_secret_key = ( os.getenv("INSTALL_MEDIA_S3_SECRET_ACCESS_KEY", "").strip() or os.getenv("S3_SECRET_ACCESS_KEY", "").strip() ) self.s3_public_domain = ( os.getenv("INSTALL_MEDIA_S3_PUBLIC_DOMAIN", "").strip() or os.getenv("S3_PUBLIC_DOMAIN", "").strip() ) self.s3_key_prefix = ( os.getenv("INSTALL_MEDIA_S3_FILE_PATH", "").strip() or os.getenv("S3_FILE_PATH", "").strip() ) self.s3_acl = ( os.getenv("INSTALL_MEDIA_S3_ACL", "").strip() or os.getenv("S3_ACL", "public-read").strip() ) self.s3_path_style = bool_env("INSTALL_MEDIA_S3_PATH_STYLE", bool_env("S3_PATH_STYLE", True)) if self.s3_key_prefix and not self.s3_key_prefix.endswith("/"): self.s3_key_prefix += "/" self.image_analysis_enabled = bool_env("IMAGE_ANALYSIS_ENABLED", True) self.image_analysis_model = os.getenv("IMAGE_ANALYSIS_MODEL", "qwen2.5vl:3b").strip() or "qwen2.5vl:3b" self.image_analysis_timeout = max(10, min(int(os.getenv("IMAGE_ANALYSIS_TIMEOUT", "90")), 300)) self.image_max_images = max(1, min(int(os.getenv("IMAGE_MAX_IMAGES", "3")), 8)) self.image_download_timeout = max(3, min(int(os.getenv("IMAGE_DOWNLOAD_TIMEOUT", "20")), 60)) self.image_max_bytes = max(262144, min(int(os.getenv("IMAGE_MAX_BYTES", "10485760")), 31457280)) self.image_upload_to_s3 = bool_env("IMAGE_UPLOAD_TO_S3", True) self.image_vision_output_max_chars = max(300, min(int(os.getenv("IMAGE_VISION_OUTPUT_MAX_CHARS", "2200")), 6000)) self.video_analysis_enabled = bool_env("VIDEO_ANALYSIS_ENABLED", True) self.video_analysis_model = os.getenv("VIDEO_ANALYSIS_MODEL", "qwen-vl-plus").strip() or "qwen-vl-plus" self.video_analysis_fallback_model = ( os.getenv("VIDEO_ANALYSIS_FALLBACK_MODEL", "qwen-vl-plus").strip() or "qwen-vl-plus" ) self.video_analysis_base_url = ( os.getenv("VIDEO_ANALYSIS_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions").strip() or "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions" ) self.video_analysis_timeout = max(15, min(int(os.getenv("VIDEO_ANALYSIS_TIMEOUT", "360")), 900)) self.video_analysis_max_tokens = max(256, min(int(os.getenv("VIDEO_ANALYSIS_MAX_TOKENS", "1800")), 8192)) self.video_analysis_max_urls = max(1, min(int(os.getenv("VIDEO_ANALYSIS_MAX_URLS", "2")), 3)) def _should_handle(self, msg: ChatbotMessage, text: str) -> bool: if text.startswith(self.prefix): return True if msg.is_in_at_list: return True return not self.require_prefix def _normalize_prompt(self, text: str) -> str: text = text.strip() if self.prefix and text.startswith(self.prefix): text = text[len(self.prefix):].strip() text = re.sub(r"^@\S+\s*", "", text).strip() return text def _is_smalltalk_prompt(self, prompt: str) -> bool: normalized = re.sub(r"[\s，,。.!！?？~～]+", "", (prompt or "").strip().lower()) if not normalized: return False if normalized in SMALLTALK_SET: return True if normalized.startswith(("你好", "您好", "hi", "hello")) and len(normalized) <= 6: return True return False def _safe_session_component(self, raw: str) -> str: original = (raw or "default").strip().replace(" ", "_") safe = re.sub(r"[^A-Za-z0-9_-]+", "-", original) safe = re.sub(r"-{2,}", "-", safe).strip("-") if not safe: safe = "default" if safe != original: digest = hashlib.sha1(original.encode("utf-8")).hexdigest()[:8] safe = f"{safe}-{digest}" return safe[:96] def _session_id(self, msg: ChatbotMessage) -> str: raw_conversation_id = str(msg.conversation_id or "default") safe_conversation_id = self._safe_session_component(raw_conversation_id) base_session = f"{self.session_prefix}-{safe_conversation_id}" session_file = os.path.join(self.sessions_dir, f"{base_session}.jsonl") if self.session_max_lines > 0 and os.path.exists(session_file): try: with open(session_file, "rb") as fh: line_count = sum(1 for _ in fh) if line_count >= self.session_max_lines: rotate_suffix = time.strftime("%Y%m%d%H%M") rotated = f"{base_session}-{rotate_suffix}" self.logger.info( "session auto-rotated: base=%s lines=%s rotated=%s", base_session, line_count, rotated, ) return rotated except Exception: self.logger.exception("failed to inspect session file: %s", session_file) return base_session def _event_key(self, callback: CallbackMessage, msg: ChatbotMessage, prompt: str) -> str: if getattr(msg, "message_id", None): return f"msg:{msg.message_id}" data = callback.data if isinstance(callback.data, dict) else {} for key in ("msgId", "messageId", "eventId", "processQueryKey"): value = data.get(key) if value: return f"data:{key}:{value}" headers = getattr(callback, "headers", {}) or {} for key in ("messageId", "eventId", "processQueryKey"): value = headers.get(key) if value: return f"hdr:{key}:{value}" raw = "|".join( [ str(getattr(msg, "conversation_id", "") or ""), str(getattr(msg, "sender_id", "") or ""), str(getattr(msg, "sender_staff_id", "") or ""), str(getattr(msg, "create_at", "") or ""), prompt[:200], ] ) return "fp:" + hashlib.sha1(raw.encode("utf-8")).hexdigest() def _seen_or_mark_event(self, key: str) -> bool: now = time.time() expire_before = now - max(self.dedupe_ttl_seconds, 30) stale_keys = [k for k, ts in self._recent_event_ts.items() if ts < expire_before] for stale_key in stale_keys: self._recent_event_ts.pop(stale_key, None) if key in self._recent_event_ts: return True self._recent_event_ts[key] = now return False def _is_market_prompt(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", prompt) if any(k in normalized for k in SALES_HINT_KEYWORDS): return False if "电脑桌" in normalized: return True if any(k in normalized for k in MARKET_HINT_KEYWORDS): return True if "市场" in normalized and any( k in normalized for k in ("搜索", "飙升词", "热词", "需求供给比", "价格带", "客单价", "洞察", "趋势") ): return True if "市场" in normalized and "分析" in normalized: return True return False def _is_install_media_prompt(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", prompt) if not normalized: return False if any(k in normalized for k in INSTALL_MEDIA_HINT_KEYWORDS): return True if "安装" in normalized and ("图纸" in normalized or "视频" in normalized): return True return False def _is_install_media_stitch_prompt(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", prompt) if not normalized: return False return any(k in normalized for k in INSTALL_MEDIA_STITCH_HINT_KEYWORDS) def _is_video_url(self, raw_url: str) -> bool: try: parsed = urllib.parse.urlparse(raw_url) except Exception: return False if parsed.scheme not in {"http", "https"}: return False host = (parsed.hostname or "").lower() target = f"{parsed.path or ''}?{parsed.query or ''}" if VIDEO_EXT_RE.search(target): return True video_hosts = ( "douyin.com", "iesdouyin.com", "bilibili.com", "youku.com", "qq.com", "weixin.qq.com", "ixigua.com", "kuaishou.com", "mgtv.com", "1905.com", "xiaohongshu.com", "xhslink.com", "tiktok.com", "youtube.com", "youtu.be", ) return any(host == h or host.endswith(f".{h}") for h in video_hosts) def _extract_video_urls(self, text: str, limit: int = 2) -> list: urls = [] seen = set() for match in URL_RE.finditer(text or ""): raw = match.group(0).rstrip(".,;!?") if not self._is_video_url(raw): continue if raw in seen: continue seen.add(raw) urls.append(raw) if len(urls) >= limit: break return urls def _extract_any_urls(self, text: str, limit: int = 5) -> list: urls = [] seen = set() for match in URL_RE.finditer(text or ""): raw = match.group(0).rstrip(".,;!?") if raw in seen: continue seen.add(raw) urls.append(raw) if len(urls) >= limit: break return urls def _is_video_analysis_prompt(self, prompt: str) -> bool: if self._is_install_media_prompt(prompt): return False normalized = re.sub(r"\s+", "", (prompt or "")).lower() if not normalized: return False has_video_word = ("视频" in normalized) or ("video" in normalized) has_video_intent = any(k in normalized for k in VIDEO_ANALYSIS_HINT_KEYWORDS) or any( k in normalized for k in VIDEO_ANALYSIS_ACTION_KEYWORDS ) if has_video_word and has_video_intent: return True video_urls = self._extract_video_urls(prompt, limit=1) if not video_urls: return False if has_video_intent: return True return len(normalized) <= 120 def _needs_video_script(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", (prompt or "")).lower() if not normalized: return False return any(k in normalized for k in VIDEO_SCRIPT_HINT_KEYWORDS) def _is_dalongxia_analytics_prompt(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", (prompt or "")).lower() if not normalized: return False if any(k in normalized for k in DALONGXIA_ANALYTICS_HINT_KEYWORDS): return True if "任务进度" in normalized and ("总览" in normalized or "overview" in normalized): return True if "设计师绩效" in normalized or "流程效率" in normalized: return True if "primary" in normalized and ("dept" in normalized or "task" in normalized): return True return False def _parse_analytics_mode(self, prompt: str) -> str: normalized = re.sub(r"\s+", "", (prompt or "")).lower() compact = re.sub(r"[^a-z0-9\u4e00-\u9fa5]+", "", normalized) mode_aliases = ( ("primarytaskbranddistribution", "primary_task_brand_distribution"), ("primarytaskflowefficiency", "primary_task_flow_efficiency"), ("primarydeptstatistics", "primary_dept_statistics"), ("primarydeptuserranking", "primary_dept_user_ranking"), ("primarydeptranking", "primary_dept_ranking"), ("primarytask", "primary_task_flow_efficiency"), ("primarydept", "primary_dept_ranking"), ("designerdeductiondetails", "designer_deduction"), ("designerscoredetails", "designer_score"), ("designerdeduction", "designer_deduction"), ("designerscore", "designer_score"), ("taskprogressoverview", "task_progress_overview"), ("taskprogress", "task_progress_overview"), ("progress", "task_progress_overview"), ("demandstatistics", "demand_statistics"), ("designerperformance", "designer_performance"), ("processefficiency", "process_efficiency"), ("dimensionanalysis", "dimension_analysis"), ("overview", "overview"), ("warnings", "warnings"), ) for token, mode in mode_aliases: if token in compact: return mode if "主部门" in normalized and "人员" in normalized and "排名" in normalized: return "primary_dept_user_ranking" if "主部门" in normalized and "品牌" in normalized and "分布" in normalized: return "primary_task_brand_distribution" if "主部门" in normalized and "任务流程" in normalized and "效率" in normalized: return "primary_task_flow_efficiency" if "主部门" in normalized and "统计" in normalized: return "primary_dept_statistics" if "主部门" in normalized and "排名" in normalized: return "primary_dept_ranking" if "设计师" in normalized and ("扣分明细" in normalized or "扣分详情" in normalized): return "designer_deduction" if "设计师" in normalized and ("评分明细" in normalized or "得分明细" in normalized): return "designer_score" if "维度" in normalized and "分析" in normalized: return "dimension_analysis" if "流程效率" in normalized: return "process_efficiency" if "设计师绩效" in normalized: return "designer_performance" if "需求统计" in normalized: return "demand_statistics" if "预警" in normalized: return "warnings" if "任务进度" in normalized and ("总览" in normalized or "overview" in normalized): return "task_progress_overview" if "数据分析" in normalized and "总览" in normalized: return "overview" return "overview" def _parse_analytics_date_range(self, prompt: str) -> str: normalized = re.sub(r"\s+", "", (prompt or "")).lower() if any(k in normalized for k in ("all", "全部", "全量", "所有时间")): return "all" if any(k in normalized for k in ("quarter", "季度", "q1", "q2", "q3", "q4")): return "quarter" if any(k in normalized for k in ("week", "本周", "上周", "近7天", "最近7天", "7天")): return "week" return "month" def _parse_analytics_month(self, prompt: str) -> str: text = prompt or "" m = re.search(r"(20\d{2})[年/-](\d{1,2})", text) if not m: m = re.search(r"(20\d{2})(\d{2})", text) if m: year = int(m.group(1)) month = int(m.group(2)) if 1 <= month <= 12: return f"{year:04d}-{month:02d}" now = time.localtime() return f"{now.tm_year:04d}-{now.tm_mon:02d}" def _parse_analytics_ids(self, prompt: str) -> tuple: text = prompt or "" dept_id = "" user_id = "" m = re.search(r"(?:部门ID|deptId|dept_id)[：:\s]*([0-9]{1,20})", text, re.IGNORECASE) if m: dept_id = m.group(1) m = re.search(r"(?:用户ID|设计师ID|成员ID|userId|user_id)[：:\s]*([0-9]{1,20})", text, re.IGNORECASE) if m: user_id = m.group(1) return dept_id, user_id def _normalize_analytics_datetime(self, raw: str, end_of_day: bool = False) -> str: text = (raw or "").strip() if not text: return "" text = text.replace("/", "-").replace(" ", "T") if re.match(r"^\d{4}-\d{1,2}-\d{1,2}$", text): suffix = "23:59:59" if end_of_day else "00:00:00" return f"{text}T{suffix}" if re.match(r"^\d{4}-\d{1,2}-\d{1,2}T\d{1,2}$", text): return f"{text}:00:00" if re.match(r"^\d{4}-\d{1,2}-\d{1,2}T\d{1,2}:\d{1,2}$", text): return f"{text}:00" if re.match(r"^\d{4}-\d{1,2}-\d{1,2}T\d{1,2}:\d{1,2}:\d{1,2}$", text): return text return "" def _parse_analytics_time_window(self, prompt: str, month: str) -> tuple: text = prompt or "" start_time = "" end_time = "" range_match = re.search( r"(20\d{2}[/-]\d{1,2}[/-]\d{1,2})\s*(?:到|至|~|-)\s*(20\d{2}[/-]\d{1,2}[/-]\d{1,2})", text, ) if range_match: start_time = self._normalize_analytics_datetime(range_match.group(1), end_of_day=False) end_time = self._normalize_analytics_datetime(range_match.group(2), end_of_day=True) if not start_time: m = re.search(r"(?:startTime|start_time|开始时间)[：:=\s]*([0-9/:\- T]{8,25})", text, re.IGNORECASE) if m: start_time = self._normalize_analytics_datetime(m.group(1), end_of_day=False) if not end_time: m = re.search(r"(?:endTime|end_time|结束时间)[：:=\s]*([0-9/:\- T]{8,25})", text, re.IGNORECASE) if m: end_time = self._normalize_analytics_datetime(m.group(1), end_of_day=True) if start_time and end_time: return start_time, end_time month_match = re.match(r"^(20\d{2})-(\d{2})$", month or "") if month_match: year = int(month_match.group(1)) mon = int(month_match.group(2)) first = dt.datetime(year, mon, 1, 0, 0, 0) if mon == 12: next_first = dt.datetime(year + 1, 1, 1, 0, 0, 0) else: next_first = dt.datetime(year, mon + 1, 1, 0, 0, 0) last = next_first - dt.timedelta(seconds=1) return first.strftime("%Y-%m-%dT%H:%M:%S"), last.strftime("%Y-%m-%dT%H:%M:%S") now = dt.datetime.now() first = now.replace(day=1, hour=0, minute=0, second=0, microsecond=0) last = now.replace(hour=23, minute=59, second=59, microsecond=0) return first.strftime("%Y-%m-%dT%H:%M:%S"), last.strftime("%Y-%m-%dT%H:%M:%S") def _parse_include_task_progress(self, prompt: str) -> bool: return bool( re.search( r"(含|包含|带上|带|include)\s*任务进度|includeTaskProgress\s*[:=]\s*true", prompt or "", re.IGNORECASE, ) ) def _build_dalongxia_analytics_request(self, mode: str, app_key: str, app_secret: str, params: dict) -> tuple: timestamp = str(int(time.time() * 1000)) date_range = params.get("date_range", "month") month = params.get("month", "") dept_id = str(params.get("dept_id", "") or "") user_id = str(params.get("user_id", "") or "") include_task_progress = bool(params.get("include_task_progress", False)) include_str = str(include_task_progress).lower() start_time = params.get("start_time", "") end_time = params.get("end_time", "") if mode == "task_progress_overview": action = "analytics_task_progress_overview" payload = "|".join([action, app_key, date_range, month, dept_id, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "dateRange": date_range, "month": month, } if dept_id: body["deptId"] = dept_id return "/api/open/analytics/task-progress/overview", "壹点需求系统：任务进度总览", body if mode == "demand_statistics": action = "analytics_demand_statistics" payload = "|".join([action, app_key, date_range, month, dept_id, user_id, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "dateRange": date_range, "month": month, } if dept_id: body["deptId"] = dept_id if user_id: body["userId"] = user_id return "/api/open/analytics/demand-statistics", "壹点需求系统：需求统计", body if mode == "designer_performance": action = "analytics_designer_performance" payload = "|".join([action, app_key, month, dept_id, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "month": month, } if dept_id: body["deptId"] = dept_id return "/api/open/analytics/designer-performance", "壹点需求系统：设计师绩效", body if mode == "process_efficiency": action = "analytics_process_efficiency" payload = "|".join([action, app_key, month, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "month": month, } return "/api/open/analytics/process-efficiency", "壹点需求系统：流程效率", body if mode == "warnings": action = "analytics_warnings" payload = "|".join([action, app_key, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), } return "/api/open/analytics/warnings", "壹点需求系统：预警信息", body if mode == "dimension_analysis": action = "analytics_dimension_analysis" payload = "|".join([action, app_key, date_range, month, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "dateRange": date_range, "month": month, } return "/api/open/analytics/dimension-analysis", "壹点需求系统：维度分析", body if mode == "designer_deduction": action = "analytics_designer_deduction_details" detail_user_id = user_id or os.getenv("ANALYTICS_DEFAULT_USER_ID", "38").strip() payload = "|".join([action, app_key, str(detail_user_id), month, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "userId": str(detail_user_id), "month": month, } return "/api/open/analytics/designer-deduction-details", "壹点需求系统：设计师扣分明细", body if mode == "designer_score": action = "analytics_designer_score_details" detail_user_id = user_id or os.getenv("ANALYTICS_DEFAULT_USER_ID", "38").strip() payload = "|".join([action, app_key, str(detail_user_id), month, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "userId": str(detail_user_id), "month": month, } return "/api/open/analytics/designer-score-details", "壹点需求系统：设计师得分明细", body if mode == "primary_dept_statistics": action = "analytics_primary_dept_statistics" payload = "|".join([action, app_key, start_time, end_time, dept_id, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "startTime": start_time, "endTime": end_time, } if dept_id: body["deptId"] = dept_id return "/api/open/analytics/primary-dept/statistics", "壹点需求系统：主部门统计", body if mode == "primary_dept_ranking": action = "analytics_primary_dept_ranking" payload = "|".join([action, app_key, start_time, end_time, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "startTime": start_time, "endTime": end_time, } return "/api/open/analytics/primary-dept/ranking", "壹点需求系统：主部门排名", body if mode == "primary_task_flow_efficiency": action = "analytics_primary_task_flow_efficiency" payload = "|".join([action, app_key, start_time, end_time, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "startTime": start_time, "endTime": end_time, } return "/api/open/analytics/primary-task/flow-efficiency", "壹点需求系统：主部门任务流转效率", body if mode == "primary_task_brand_distribution": action = "analytics_primary_task_brand_distribution" payload = "|".join([action, app_key, start_time, end_time, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "startTime": start_time, "endTime": end_time, } return "/api/open/analytics/primary-task/brand-distribution", "壹点需求系统：主部门任务品牌分布", body if mode == "primary_dept_user_ranking": action = "analytics_primary_dept_user_ranking" payload = "|".join([action, app_key, start_time, end_time, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "startTime": start_time, "endTime": end_time, } return "/api/open/analytics/primary-dept/user-ranking", "壹点需求系统：主部门成员排名", body action = "analytics_overview" payload = "|".join([action, app_key, date_range, month, dept_id, user_id, include_str, timestamp]) body = { "appKey": app_key, "timestamp": timestamp, "sign": self._build_open_api_sign(app_secret, payload), "dateRange": date_range, "month": month, "includeTaskProgress": include_task_progress, } if dept_id: body["deptId"] = dept_id if user_id: body["userId"] = user_id return "/api/open/analytics/overview", "壹点需求系统：数据分析总览", body def _format_dalongxia_analytics_result(self, mode: str, title: str, body: dict, data: dict) -> str: def _f(v): if v is None: return "-" if isinstance(v, float): s = f"{v:.2f}" return s.rstrip("0").rstrip(".") return str(v) def _is_num(v): return isinstance(v, (int, float)) def _sum_num(items, key): total = 0 found = False for it in items: v = it.get(key) if isinstance(it, dict) else None if _is_num(v): total += v found = True return total if found else None query_params = [] for key in ("dateRange", "month", "deptId", "userId", "includeTaskProgress", "startTime", "endTime"): if key in body and body[key] not in ("", None): query_params.append(f"{key}={body[key]}") lines = [title] if query_params: lines.append(f"- 查询参数: {', '.join(query_params)}") if isinstance(data, dict): if data.get("time"): lines.append(f"- 统计时间: {data.get('time')}") if data.get("traceId"): lines.append(f"- traceId: {data.get('traceId')}") root = (data or {}).get("data") if isinstance(data, dict) else None if root is None: root = data if mode == "task_progress_overview" and isinstance(root, dict): metrics = root.get("metrics") or {} status = root.get("statusDistribution") or {} trend = (root.get("trend") or [])[:5] lines.append( "- 核心指标: " f"总任务={_f(metrics.get('totalTasks'))}，完成={_f(metrics.get('completedTasks'))}，" f"处理中={_f(metrics.get('inProgressTasks'))}，逾期={_f(metrics.get('overdueTasks'))}，" f"完成率={_f(metrics.get('completionRate'))}%" ) if status: parts = [f"{k}={_f(v)}" for k, v in status.items() if _is_num(v)] if parts: lines.append(f"- 状态分布: {'，'.join(parts[:8])}") if trend: lines.append("- 趋势(最近5个点):") for t in trend: lines.append( f" - {_f(t.get('date'))}: 新建={_f(t.get('createdCount'))}，完成={_f(t.get('completedCount'))}" ) return "\n".join(lines) if mode == "designer_performance" and isinstance(root, dict): items = root.get("designerStats") or [] if not isinstance(items, list): items = [] items = sorted( [it for it in items if isinstance(it, dict)], key=lambda x: (x.get("completedCount") or 0, x.get("receivedCount") or 0), reverse=True, ) total_received = _sum_num(items, "receivedCount") total_completed = _sum_num(items, "completedCount") total_score = _sum_num(items, "totalScore") total_net_score = _sum_num(items, "netScore") lines.append( "- 汇总: " f"设计师数={len(items)}，接收任务={_f(total_received)}，完成任务={_f(total_completed)}，" f"总积分={_f(total_score)}，净积分={_f(total_net_score)}" ) lines.append("- TOP设计师(按完成量，含每人积分):") for idx, it in enumerate(items[:10], 1): total_score_item = it.get("totalScore") net_score_item = it.get("netScore") point_value = net_score_item if _is_num(net_score_item) else total_score_item lines.append( f" {idx}. {_f(it.get('realName') or it.get('userName'))}｜{_f(it.get('deptName'))}｜" f"完成={_f(it.get('completedCount'))}｜积分={_f(point_value)}｜" f"扣分={_f(it.get('deductionScore'))}｜目标={_f(it.get('targetScore'))}｜" f"准时率={_f(it.get('onTimeRate'))}%｜完成率={_f(it.get('completionRate'))}%" ) return "\n".join(lines) if mode == "dimension_analysis" and isinstance(root, dict): items = root.get("categoryAnalysis") or [] if not isinstance(items, list): items = [] items = sorted( [it for it in items if isinstance(it, dict)], key=lambda x: (x.get("totalTasks") or 0), reverse=True, ) lines.append(f"- 类目数: {len(items)}") lines.append("- TOP类目(按任务量):") for idx, it in enumerate(items[:10], 1): lines.append( f" {idx}. {_f(it.get('categoryName'))}｜任务={_f(it.get('totalTasks'))}｜" f"完成={_f(it.get('completedTasks'))}｜进行中={_f(it.get('inProgressTasks'))}｜完成率={_f(it.get('completionRate'))}%" ) return "\n".join(lines) if mode == "overview" and isinstance(root, dict): module_keys = list(root.keys()) lines.append(f"- 模块: {', '.join(module_keys[:8]) if module_keys else '-'}") demand = root.get("demandStatistics") or {} user_stats = demand.get("userStats") if isinstance(demand, dict) else [] if isinstance(user_stats, list) and user_stats: lines.append(f"- 需求统计: 用户数={len(user_stats)}") top = sorted( [it for it in user_stats if isinstance(it, dict)], key=lambda x: (x.get("totalDemands") or 0), reverse=True, )[:5] lines.append("- 需求量TOP5:") for idx, it in enumerate(top, 1): lines.append( f" {idx}. {_f(it.get('realName') or it.get('userName'))}｜{_f(it.get('deptName'))}｜" f"总需求={_f(it.get('totalDemands'))}｜完成={_f(it.get('completedDemands'))}" ) task_progress = root.get("taskProgressOverview") or root.get("taskProgress") or {} if isinstance(task_progress, dict) and task_progress.get("metrics"): m = task_progress.get("metrics") or {} lines.append( "- 任务进度: " f"总任务={_f(m.get('totalTasks'))}，完成={_f(m.get('completedTasks'))}，逾期={_f(m.get('overdueTasks'))}" ) return "\n".join(lines) if mode in { "primary_dept_ranking", "primary_dept_statistics", "primary_task_flow_efficiency", "primary_task_brand_distribution", "primary_dept_user_ranking", }: items = root if isinstance(root, list) else [] if not items and isinstance(root, dict): for key in ("items", "list", "rows", "data"): if isinstance(root.get(key), list): items = root.get(key) break items = [it for it in items if isinstance(it, dict)] lines.append(f"- 条数: {len(items)}") lines.append("- TOP10:") for idx, it in enumerate(items[:10], 1): name = it.get("deptName") or it.get("userName") or it.get("brandName") or it.get("name") task_count = it.get("taskCount") or it.get("totalTasks") or it.get("count") rate = it.get("approvalRate") or it.get("completionRate") or it.get("onTimeRate") extra = it.get("avgResponseHours") or it.get("avgCycleHours") part = f" {idx}. {_f(name)}｜任务={_f(task_count)}" if rate is not None: part += f"｜比率={_f(rate)}%" if extra is not None: part += f"｜时长={_f(extra)}h" lines.append(part) return "\n".join(lines) if mode == "warnings": items = root if isinstance(root, list) else [] if isinstance(root, dict): for key in ("warnings", "items", "list", "rows"): if isinstance(root.get(key), list): items = root.get(key) break if isinstance(items, list): lines.append(f"- 预警条数: {len(items)}") for idx, it in enumerate(items[:10], 1): if isinstance(it, dict): msg = it.get("message") or it.get("warnMsg") or it.get("content") or it.get("title") lines.append(f" {idx}. {_f(msg)}") else: lines.append(f" {idx}. {_f(it)}") return "\n".join(lines) if mode in {"designer_deduction", "designer_score"}: items = root if isinstance(root, list) else [] if isinstance(root, dict): for key in ("details", "items", "list", "rows", "data"): if isinstance(root.get(key), list): items = root.get(key) break items = [it for it in items if isinstance(it, dict)] lines.append(f"- 记录数: {len(items)}") lines.append("- 前10条:") for idx, it in enumerate(items[:10], 1): lines.append( f" {idx}. 时间={_f(it.get('time') or it.get('createTime') or it.get('date'))}｜" f"分值={_f(it.get('score') or it.get('deductionScore') or it.get('value'))}｜" f"原因={_f(it.get('reason') or it.get('remark') or it.get('content'))}" ) return "\n".join(lines) # fallback fallback = json.dumps(data, ensure_ascii=False, indent=2) if len(fallback) > 1800: fallback = fallback[:1800] + "\n...(已截断)" lines.append("- 结果预览:") lines.append(fallback) return "\n".join(lines) def _build_open_api_sign(self, secret: str, payload: str) -> str: return hmac.new(secret.encode("utf-8"), payload.encode("utf-8"), hashlib.sha256).hexdigest() def _post_open_api_json(self, base_url: str, path: str, body: dict) -> dict: url = f"{base_url.rstrip('/')}{path}" timeout = max(10, min(int(os.getenv("OPEN_API_TIMEOUT", "60")), 300)) last_err = None def _parse_response(resp): content_type = (resp.headers.get("Content-Type") or "").lower() if "json" not in content_type: text = (resp.text or "").strip() raise RuntimeError(f"HTTP {resp.status_code} 非JSON响应: {text[:300]}") data = resp.json() if not resp.ok: code = data.get("code", "unknown") msg = data.get("message", data) raise RuntimeError(f"HTTP {resp.status_code} / code={code} / msg={msg}") if data.get("code") != 200: raise RuntimeError(f"code={data.get('code')} / msg={data.get('message')}") return data.get("data") try: resp = requests.post(url, json=body, timeout=timeout) return _parse_response(resp) except Exception as exc: last_err = exc self.logger.warning("open api request attempt1 failed: %s", exc) try: with requests.Session() as session: session.trust_env = False resp = session.post(url, json=body, timeout=timeout) return _parse_response(resp) except Exception as exc: last_err = exc self.logger.warning("open api request attempt2 failed: %s", exc) raise last_err or RuntimeError("open api request failed") def _run_dalongxia_analytics(self, prompt: str) -> str: base_url = ( os.getenv("OPEN_API_BASE_URL", "").strip() or os.getenv("OPEN_API_BASE", "").strip() or "https://qd.yydd.ai" ) app_key = os.getenv("OPEN_API_APP_KEY", "").strip() app_secret = os.getenv("OPEN_API_APP_SECRET", "").strip() if not app_key or not app_secret: return "壹点需求系统查询失败：缺少 OPEN_API_APP_KEY / OPEN_API_APP_SECRET。" mode = self._parse_analytics_mode(prompt) date_range = self._parse_analytics_date_range(prompt) month = self._parse_analytics_month(prompt) dept_id, user_id = self._parse_analytics_ids(prompt) include_task_progress = self._parse_include_task_progress(prompt) start_time, end_time = self._parse_analytics_time_window(prompt, month) try: path, title, body = self._build_dalongxia_analytics_request( mode=mode, app_key=app_key, app_secret=app_secret, params={ "date_range": date_range, "month": month, "dept_id": dept_id, "user_id": user_id, "include_task_progress": include_task_progress, "start_time": start_time, "end_time": end_time, }, ) data = self._post_open_api_json(base_url, path, body) wrapped = data if isinstance(data, dict) and ("data" in data or "traceId" in data or "time" in data) else {"data": data} return self._format_dalongxia_analytics_result(mode=mode, title=title, body=body, data=wrapped) except Exception as exc: return f"壹点需求系统查询失败: {exc}" def _is_sales_prompt(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", prompt).lower() return any(k.lower() in normalized for k in SENSITIVE_SALES_KEYWORDS) def _explicit_amount_requested(self, prompt: str) -> bool: normalized = re.sub(r"\s+", "", prompt).lower() return any(k.lower() in normalized for k in EXPLICIT_AMOUNT_KEYWORDS) def _mask_sensitive_amounts(self, prompt: str, answer: str) -> str: if not self._is_sales_prompt(prompt): return answer if self._explicit_amount_requested(prompt): return answer filtered_lines = [] removed = 0 for line in answer.splitlines(): if re.search(r"(金额|退款率|费比|收入|利润|成本|客单价|GMV|毛利|\d[\d,\.]*\s*(元|万元|万|亿))", line, re.IGNORECASE): removed += 1 continue filtered_lines.append(line) cleaned = "\n".join(filtered_lines).strip() if removed > 0: note = "（已按配置自动隐藏金额类敏感指标，仅保留件数/订单维度。）" if cleaned: cleaned = f"{cleaned}\n\n{note}" else: cleaned = note return cleaned or "已按配置隐藏金额类敏感指标，请改问件数/订单/原因结构维度。" def _extract_market_subject(self, prompt: str) -> str: normalized = prompt.strip() def clean_subject(raw: str) -> str: v = raw.strip().replace("\u201c", "").replace("\u201d", "").strip("\"'") v = re.sub(r"\s+", "", v) v = re.sub(r"^(帮我|请|麻烦|给我|我想|想要|想看|想做|分析|查看|查询|关于|整理一份|整理|输出|生成)+", "", v) v = re.sub(r"^(近(?:[一二三四五六七八九十两半0-9]+)(?:天|周|个月|月|年)|过去(?:[一二三四五六七八九十两半0-9]+)(?:天|周|个月|月|年)|近30天|近7天|近15天|近一个月|近三个月|近半年|近一年)+", "", v) v = re.sub(r"(的|情况|数据|分析)+$", "", v) return v.strip() def pick(raw: str): v = clean_subject(raw) if len(v) < 2: return None if v in {"市场", "行业", "类目", "竞品", "趋势", "市场数据", "关键词", "搜索"}: return None return v if "电脑桌" in normalized: return "电脑桌" m = re.search(r"[\"\u201c\u201d']([^\"\u201c\u201d']{2,30})[\"\u201c\u201d']", normalized) if m: v = pick(m.group(1)) if v: return v m = re.search( r"关于([\u4e00-\u9fa5A-Za-z0-9]{2,20})(?:的)?(?:市场数据分析|市场分析|行业分析|类目分析|竞品分析|趋势分析|市场数据|市场情况)", normalized, ) if m: v = pick(m.group(1)) if v: return v m = re.search( r"([\u4e00-\u9fa5A-Za-z0-9]{2,20})(?:的)?(?:市场数据分析|市场分析|行业分析|类目分析|竞品分析|趋势分析|市场数据)", normalized, ) if m: v = pick(m.group(1)) if v: return v m = re.search(r"([\u4e00-\u9fa5A-Za-z0-9]{2,20})类目", normalized) if m: v = pick(m.group(1)) if v: return v m = re.search(r"([\u4e00-\u9fa5A-Za-z0-9]{2,20})(?:市场|市场搜索|关键词|飙升词|热词)", normalized) if m: v = pick(m.group(1)) if v: return v m = re.search(r"分析(?:一下|下)?([\u4e00-\u9fa5A-Za-z0-9]{2,20})", normalized) if m: v = pick(m.group(1)) if v: return v m = re.search(r"查(?:一下|下)?([\u4e00-\u9fa5A-Za-z0-9]{2,20})", normalized) if m: v = pick(m.group(1)) if v: return v return "市场主题" def _extract_order_id(self, prompt: str) -> str: text = prompt.strip() for pattern in ( r"订单号[：:\s]*([A-Za-z0-9-]{8,40})", r"订单编号[：:\s]*([A-Za-z0-9-]{8,40})", r"订单[：:\s]*([A-Za-z0-9-]{8,40})", ): m = re.search(pattern, text, re.IGNORECASE) if m: return m.group(1).strip() m2 = ORDER_ID_RE.search(text) if m2: return m2.group(0).strip() return "" def _extract_product_no(self, prompt: str) -> str: text = prompt.strip() for pattern in ( r"(?:产品货号|货号|商品货号|SKU编码|SKUID|sku编码|skuid|sku)[：:\s]*([A-Za-z0-9_-]{5,40})", ): m = re.search(pattern, text, re.IGNORECASE) if m: return m.group(1).strip() m2 = re.search(r"\b[A-Za-z]{1,4}\d{4,}[A-Za-z0-9_-]{2,}\b", text) if m2: return m2.group(0).strip() return "" def _is_code_prompt(self, prompt: str) -> bool: normalized = (prompt or "").lower() hints = ( "代码", "sql", "python", "java", "javascript", "脚本", "bash", "shell", "命令", "函数", "class", "yaml", "json", "正则", ) return any(h in normalized for h in hints) def _clean_dialog_noise(self, answer: str) -> str: if not answer: return answer cleaned = [] for raw in answer.splitlines(): line = raw.strip() lower = line.lower() if not line: cleaned.append(raw) continue if line.startswith("[plugins]"): continue if "registered" in lower and "tool" in lower: continue if "no toolbeencalled" in lower: continue if "without a preceding text-to-speech" in lower: continue if line.startswith("原始输出:"): continue if line.startswith("{") and "\"runId\"" in line: continue cleaned.append(raw) out = "\n".join(cleaned).strip() return out or answer def _trim_noncode_blocks(self, prompt: str, answer: str) -> str: if not answer or self._is_code_prompt(prompt): return answer pattern = re.compile(r"```[\s\S]*?```", re.MULTILINE) def _repl(match): block = match.group(0) lines = [ln for ln in block.splitlines() if ln.strip()] if len(lines) <= 12: return block return "```text\n[代码块已省略，如需完整代码请明确说明]\n```" return pattern.sub(_repl, answer) def _disable_card_temporarily(self, reason: str) -> None: self.card_disabled_until = time.time() + self.card_disable_seconds self.logger.warning("card reply disabled for %ss, reason=%s", self.card_disable_seconds, reason) def _extract_incoming_download_codes(self, msg: ChatbotMessage) -> list: try: raw_codes = msg.get_image_list() or [] except Exception: self.logger.exception("failed to read incoming image list") return [] seen = set() codes = [] for raw in raw_codes: code = str(raw or "").strip() if not code or code in seen: continue seen.add(code) codes.append(code) if len(codes) >= self.image_max_images: break return codes def _guess_image_ext(self, content_type: str, source_url: str) -> str: ctype = (content_type or "").split(";")[0].strip().lower() ext = "" if ctype: ext = mimetypes.guess_extension(ctype) or "" if not ext: path = urllib.parse.urlparse(source_url or "").path _, path_ext = os.path.splitext(path) ext = path_ext ext = (ext or ".jpg").lower() if ext.startswith("."): ext = ext[1:] if ext == "jpeg": return "jpg" if ext not in {"jpg", "png", "webp", "gif", "bmp"}: return "jpg" return ext def _upload_chat_image_bytes(self, image_bytes: bytes, ext: str, conversation_id: str) -> str: if not self.image_upload_to_s3: return "" if boto3 is None or BotoConfig is None: return "" if not (self.s3_bucket and self.s3_access_key and self.s3_secret_key): return "" safe_conv = self._safe_session_component(str(conversation_id or "chat")) stamp = time.strftime("%Y%m%d%H%M%S") filename = f"{safe_conv}_{stamp}_{uuid.uuid4().hex[:8]}.{ext}" object_key = f"{self.s3_key_prefix}chat-images/{filename}" content_type = f"image/{'jpeg' if ext == 'jpg' else ext}" with tempfile.TemporaryDirectory(prefix="chat_image_") as tmpdir: local_path = os.path.join(tmpdir, filename) with open(local_path, "wb") as fh: fh.write(image_bytes) self._upload_to_s3(local_path, object_key, content_type) return self._build_public_s3_url(object_key) def _analyze_image_with_local_vlm(self, image_bytes: bytes, user_prompt: str, image_index: int) -> str: if not self.image_analysis_enabled: return "" payload = { "model": self.image_analysis_model, "stream": False, "messages": [ { "role": "user", "content": ( "你现在只做OCR和画面客观描述，不做任何分析和建议。\n" "请输出格式：\n" "OCR_TEXT_BEGIN\n" "<逐行文字，尽量保留原样，包含中文/英文/数字/LOGO字母>\n" "OCR_TEXT_END\n" "SCENE_DESC_BEGIN\n" "<画面客观描述：人物/物体/场景/颜色/布局；若无法判断写 UNKNOWN_SCENE>\n" "SCENE_DESC_END\n" "规则：\n" "- 只能输出OCR和画面描述，不要解释；\n" "- 不确定字符用 ? 标记；\n" "- 完全无文字时输出 NO_TEXT；\n" "- 画面描述不得给建议、结论或推断。\n" f"图片序号：{image_index}\n" f"用户问题：{user_prompt or '请识别并分析图片'}" ), "images": [base64.b64encode(image_bytes).decode("ascii")], } ], } try: resp = requests.post( "http://127.0.0.1:11434/api/chat", json=payload, timeout=self.image_analysis_timeout, ) resp.raise_for_status() data = resp.json() text = str((data.get("message") or {}).get("content", "")).strip() if not text: return "" return text[: self.image_vision_output_max_chars] except Exception as exc: self.logger.warning("image vlm analysis failed image=%s err=%s", image_index, exc) return "" def _build_image_context_from_dingtalk(self, msg: ChatbotMessage, prompt: str, download_codes: list) -> dict: blocks = [] uploaded_urls = [] warnings = [] used_images = 0 for idx, code in enumerate(download_codes, 1): try: download_url = self.get_image_download_url(code) if not download_url: warnings.append(f"图片{idx}下载地址获取失败") continue resp = requests.get(download_url, timeout=self.image_download_timeout) resp.raise_for_status() image_bytes = resp.content or b"" if not image_bytes: warnings.append(f"图片{idx}为空内容") continue if len(image_bytes) > self.image_max_bytes: warnings.append(f"图片{idx}过大，已跳过") continue ext = self._guess_image_ext(resp.headers.get("Content-Type", ""), download_url) s3_url = "" try: s3_url = self._upload_chat_image_bytes(image_bytes, ext, str(getattr(msg, "conversation_id", ""))) except Exception as exc: self.logger.warning("upload incoming image failed idx=%s err=%s", idx, exc) if s3_url: uploaded_urls.append(s3_url) vision = self._analyze_image_with_local_vlm(image_bytes, prompt, idx) if not vision: warnings.append(f"图片{idx}识别失败") continue item_lines = [f"图片{idx}感知结果（OCR+场景）:"] item_lines.append(vision) blocks.append("\n".join(item_lines)) used_images += 1 except Exception as exc: warnings.append(f"图片{idx}处理异常: {exc}") result = { "used_images": used_images, "context_text": "\n\n".join(blocks).strip(), "uploaded_urls": uploaded_urls, "warnings": warnings, } self.logger.info( "image context built: incoming=%s used=%s uploaded=%s warnings=%s", len(download_codes), used_images, len(uploaded_urls), len(warnings), ) return result def _merge_prompt_with_image_context(self, prompt: str, image_context: str) -> str: base = (prompt or "").strip() or "请识别并分析我上传的图片内容。" return ( f"{base}\n\n" "【图片OCR与场景结果（本地模型）】\n" f"{image_context}\n\n" "请仅基于以上OCR文本和场景描述做理解、分析和建议。\n" "注意：图片已完成本地识别，不要再尝试访问图片URL，也不要调用browser/image工具。" ).strip() def _sanitize_answer(self, prompt: str, answer: str) -> str: if self._is_market_prompt(prompt) or self._is_install_media_prompt(prompt): return answer if not self.hide_source_urls: return answer keep_map = {} def _keep_or_mask_url(match): raw = match.group(0) try: host = (urllib.parse.urlparse(raw).hostname or "").lower() except Exception: host = "" if host and ( host in self.unmask_url_hosts or host == "feishu.cn" or host.endswith(".feishu.cn") ): token = f"__KEEP_URL_{len(keep_map)}__" keep_map[token] = raw return token return "[内部数据源地址已脱敏]" out = URL_RE.sub(_keep_or_mask_url, answer) out = IP_RE.sub("[内部地址已脱敏]", out) out = DOMAIN_RE.sub("[内部域名已脱敏]", out) # 保底脱敏（防止某些格式未被正则覆盖） for token in ("hq.yucekj.com", "yucekj.com", "218.93.9.141"): out = out.replace(token, "[内部数据源已脱敏]") for token, raw in keep_map.items(): out = out.replace(token, raw) return out def _run_market_brief(self, subject: str) -> str: cmd = [self.market_brief_bin, subject] self.logger.info("market-brief call: subject=%s", subject) proc = subprocess.run( cmd, capture_output=True, text=True, timeout=self.market_brief_timeout, ) output = (proc.stdout or "").strip() if proc.returncode != 0: err = (proc.stderr or output or "market brief error").strip() return f"市场分析执行失败: {err[:500]}" if not output: return "市场分析执行完成，但未返回文本结果。" return output def _parse_install_media_output(self, output: str) -> dict: parsed = {"status": "", "mappings": [], "media": [], "warnings": []} current_set = "" in_warnings = False for raw in (output or "").splitlines(): line = raw.strip() if not line: continue if line.startswith("STATUS:"): parsed["status"] = line.split(":", 1)[1].strip() in_warnings = False continue if line.startswith("NAME:"): current_set = line.split(":", 1)[1].strip() in_warnings = False continue if line == "WARNINGS:": in_warnings = True current_set = "" continue if in_warnings and line.startswith("- "): parsed["warnings"].append(line[2:].strip()) continue if not line.startswith("{"): continue try: obj = json.loads(line) except Exception: continue if current_set == "order_to_product_mapping": parsed["mappings"].append(obj) elif current_set == "install_media_links": parsed["media"].append(obj) return parsed def _run_install_media_lookup(self, prompt: str) -> str: order_id = self._extract_order_id(prompt) product_no = self._extract_product_no(prompt) if not order_id and not product_no: return "请提供订单号（或产品货号），我将按“订单号 -> 货号 -> 安装图纸/视频库”流程查询。" cmd = [self.install_media_bin] if order_id: cmd += ["--order-id", order_id] if product_no: cmd += ["--sku-id", product_no] cmd += ["--mysql-schema", "jiansunblueprint", "--limit", "200"] self.logger.info("install-media call: order_id=%s product_no=%s", order_id or "-", product_no or "-") try: proc = subprocess.run( cmd, capture_output=True, text=True, timeout=self.install_media_timeout, ) except subprocess.TimeoutExpired: return f"安装资源查询超时（>{self.install_media_timeout}秒），请重试。" raw_output = (proc.stdout or "").strip() if proc.returncode != 0 and not raw_output: err = (proc.stderr or "install media lookup error").strip() return f"安装资源查询失败: {err[:500]}" parsed = self._parse_install_media_output(raw_output) mappings = parsed.get("mappings", []) media_rows = parsed.get("media", []) warnings = parsed.get("warnings", []) product_nos = sorted( { str(x.get("product_no", "")).strip() for x in mappings if str(x.get("product_no", "")).strip() and str(x.get("product_no", "")).strip() != "(none)" } ) drawing_rows = [x for x in media_rows if str(x.get("media_type", "")).lower() == "drawing"] video_rows = [x for x in media_rows if str(x.get("media_type", "")).lower() == "video"] stitch_required = self.install_media_stitch_enabled or self._is_install_media_stitch_prompt(prompt) stitch_url = "" stitch_note = "" if stitch_required and drawing_rows: drawing_urls = [] seen_urls = set() for row in drawing_rows: url = str(row.get("media_url", "")).strip() if not url or url in seen_urls: continue seen_urls.add(url) drawing_urls.append(url) if len(drawing_urls) >= self.install_media_stitch_min_images: product_hint = ( (product_nos[0] if product_nos else "") or product_no or order_id or "unknown" ) stitch_url, stitch_note = self._stitch_and_upload_install_media( drawing_urls=drawing_urls[: self.install_media_stitch_max_images], product_hint=product_hint, ) lines = ["安装资源查询结果"] if order_id: lines.append(f"- 订单号: {order_id}") if product_nos: lines.append(f"- 命中货号: {', '.join(product_nos[:8])}") elif product_no: lines.append(f"- 输入货号: {product_no}") lines.append(f"- 图纸: {len(drawing_rows)} 条，视频: {len(video_rows)} 条") if stitch_url: lines.append(f"- 拼接图: {stitch_url}") elif stitch_note and self._is_install_media_stitch_prompt(prompt): lines.append(f"- 拼接图: {stitch_note}") display_rows = media_rows if stitch_url: # 用户要求仅返回拼接图，不再返回原始多条图纸链接；视频链接保留 display_rows = [x for x in media_rows if str(x.get("media_type", "")).lower() != "drawing"] if display_rows: lines.append("- 资源链接（前20条）:") for i, row in enumerate(display_rows[:20], 1): mtype = str(row.get("media_type", "")).lower() tag = "图纸" if mtype == "drawing" else ("视频" if mtype == "video" else "资源") url = str(row.get("media_url", "")).strip() if url: lines.append(f"{i}. [{tag}] {url}") if len(display_rows) > 20: lines.append(f"- 其余 {len(display_rows) - 20} 条已省略。") else: if stitch_url: lines.append("- 原始图纸链接已按配置隐藏。") else: lines.append("- 未查到安装图纸/视频链接。") if warnings: lines.append("- 警告:") for w in warnings[:3]: lines.append(f" - {w}") return "\n".join(lines) def _run_video_analysis(self, prompt: str) -> str: if not self.video_analysis_enabled: return "视频分析功能未启用。" video_urls = self._extract_video_urls(prompt, limit=self.video_analysis_max_urls) if not video_urls: any_urls = self._extract_any_urls(prompt, limit=self.video_analysis_max_urls) if any_urls: video_urls = any_urls self.logger.warning("video-analysis fallback to raw url(s): %s", ",".join(video_urls)) else: return "请提供可访问的视频链接（http/https），我再开始分析。" api_key = ( os.getenv("DASHSCOPE_API_KEY", "").strip() or os.getenv("BAILIAN_API_KEY", "").strip() or os.getenv("QWEN_API_KEY", "").strip() ) if not api_key: return "视频分析未配置API Key，请设置 DASHSCOPE_API_KEY 后重试。" model_name = (self.video_analysis_model or "").strip() lower_model = model_name.lower() if ( ("vl" not in lower_model and "omni" not in lower_model) and self.video_analysis_fallback_model and self.video_analysis_fallback_model != model_name ): self.logger.warning( "video-analysis model may not support video input, auto fallback: %s -> %s", model_name, self.video_analysis_fallback_model, ) model_name = self.video_analysis_fallback_model need_script = self._needs_video_script(prompt) user_goal = self._remove_image_urls(prompt, video_urls).strip() if not user_goal: if need_script: user_goal = "请深度拆解该视频，并输出可直接复刻的分镜脚本和拍摄执行方案。" else: user_goal = "请分析该视频的核心内容、关键信息和可执行建议。" elif "视频" not in user_goal and "video" not in user_goal.lower(): user_goal = f"{user_goal}\n请围绕视频内容输出结论。" content_items = [{"type": "video_url", "video_url": {"url": video_urls[0]}}] content_items.append({"type": "text", "text": user_goal}) system_prompt = ( "你是视频内容分析助手。请基于视频画面和字幕内容输出结构化结论，避免臆测。" ) if need_script: system_prompt = ( "你是资深短视频导演与编剧。请基于视频内容做可执行复刻拆解。\n" "输出必须包含：\n" "1) 视频定位与核心卖点（1-2句）\n" "2) 时间轴分镜脚本表（时间段/镜头景别/画面内容/人物动作/机位与运镜/字幕或口播/BGM与音效）\n" "3) 拍摄执行清单（场景、道具、服装、灯光、设备）\n" "4) 剪辑脚本（节奏点、转场、卡点、字幕样式）\n" "5) 复刻风险与规避建议（至少3条）\n" "6) 可直接给拍摄团队的最终脚本（按步骤）\n" "要求：具体、可落地、少空话。" ) payload = { "model": model_name, "messages": [ { "role": "system", "content": system_prompt, }, { "role": "user", "content": content_items, }, ], "temperature": 0.2, "max_tokens": self.video_analysis_max_tokens, } headers = { "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", } self.logger.info("video-analysis call: model=%s url_count=%s urls=%s", model_name, len(video_urls), ",".join(video_urls)) try: resp = requests.post( self.video_analysis_base_url, headers=headers, json=payload, timeout=self.video_analysis_timeout, ) except Exception as exc: self.logger.error("video-analysis request failed: %s", exc) return f"视频分析调用失败：{exc}" text = "" if resp.status_code >= 400: try: err_data = resp.json() err_msg = ( err_data.get("error", {}).get("message") or err_data.get("message") or resp.text ) except Exception: err_msg = resp.text self.logger.error( "video-analysis http error: status=%s model=%s body=%s", resp.status_code, model_name, (str(err_msg) or "")[:800], ) hint = "" em = (str(err_msg) or "").lower() if ( "video" in em and ("not support" in em or "invalid" in em or "unsupported" in em) and "vl" not in model_name.lower() ): hint = "（当前模型可能不支持视频输入，建议改为 qwen-vl-plus / qwen-vl-max）" return f"视频分析失败（HTTP {resp.status_code}）：{str(err_msg).strip()[:300]}{hint}" try: data = resp.json() choices = data.get("choices") or [] message = (choices[0] or {}).get("message", {}) if choices else {} content = message.get("content", "") if isinstance(content, list): chunks = [] for item in content: if isinstance(item, dict): t = str(item.get("text", "")).strip() if t: chunks.append(t) text = "\n".join(chunks).strip() else: text = str(content or "").strip() except Exception as exc: self.logger.exception("video-analysis parse failed") self.logger.error("video-analysis raw body: %s", (resp.text or "")[:1000]) return f"视频分析返回解析失败：{exc}" if not text: return "视频分析完成，但未返回有效文本结果。" if len(video_urls) > 1: return f"{text}\n\n（已按配置先分析第1个视频链接；如需逐条分析请分别发送。）" return text def _stitch_and_upload_install_media(self, drawing_urls: list, product_hint: str) -> tuple: if Image is None: return "", "未执行（缺少 Pillow 依赖）" if boto3 is None or BotoConfig is None: return "", "未执行（缺少 boto3 依赖）" if not (self.s3_bucket and self.s3_access_key and self.s3_secret_key): return "", "未执行（S3 配置不完整）" images = [] try: for url in drawing_urls: try: resp = requests.get(url, timeout=self.install_media_fetch_timeout) resp.raise_for_status() with Image.open(io.BytesIO(resp.content)) as img: images.append(img.convert("RGB")) except Exception as exc: self.logger.warning("install-media image download failed: %s %s", url, exc) if len(images) < self.install_media_stitch_min_images: return "", "未执行（可下载图纸不足）" target_width = min(max(img.width for img in images), self.install_media_max_width) resized_images = [] total_height = 0 for img in images: if img.width != target_width: new_height = max(1, int(img.height * target_width / img.width)) if hasattr(Image, "Resampling"): resized = img.resize((target_width, new_height), Image.Resampling.LANCZOS) else: resized = img.resize((target_width, new_height), Image.LANCZOS) else: resized = img.copy() resized_images.append(resized) total_height += resized.height stitched = Image.new("RGB", (target_width, total_height), (255, 255, 255)) y = 0 for img in resized_images: stitched.paste(img, (0, y)) y += img.height safe_product = re.sub(r"[^A-Za-z0-9_-]+", "-", (product_hint or "unknown")).strip("-")[:40] or "unknown" stamp = time.strftime("%Y%m%d%H%M%S") filename = f"{safe_product}_{stamp}_{uuid.uuid4().hex[:8]}.jpg" object_key = f"{self.s3_key_prefix}install-media/{filename}" with tempfile.TemporaryDirectory(prefix="install_media_") as tmpdir: local_path = os.path.join(tmpdir, filename) stitched.save(local_path, format="JPEG", quality=88, optimize=True) self._upload_to_s3(local_path, object_key, "image/jpeg") return self._build_public_s3_url(object_key), "" except Exception as exc: self.logger.exception("install-media stitch/upload failed") return "", f"未执行（{exc}）" finally: for img in images: try: img.close() except Exception: pass def _upload_to_s3(self, file_path: str, object_key: str, content_type: str) -> None: endpoint = self.s3_endpoint or None config = BotoConfig(s3={"addressing_style": "path" if self.s3_path_style else "virtual"}) client = boto3.client( "s3", endpoint_url=endpoint, region_name=self.s3_region, aws_access_key_id=self.s3_access_key, aws_secret_access_key=self.s3_secret_key, config=config, ) with open(file_path, "rb") as fh: kwargs = { "Bucket": self.s3_bucket, "Key": object_key, "Body": fh, "ContentType": content_type, } if self.s3_acl: kwargs["ACL"] = self.s3_acl client.put_object(**kwargs) def _build_public_s3_url(self, object_key: str) -> str: safe_key = urllib.parse.quote(object_key, safe="/-_.~") if self.s3_public_domain: return f"{self.s3_public_domain.rstrip('/')}/{safe_key}" if self.s3_endpoint: base = self.s3_endpoint.rstrip("/") if self.s3_path_style: return f"{base}/{self.s3_bucket}/{safe_key}" return f"{base}/{safe_key}" return safe_key def _run_openclaw(self, session_id: str, prompt: str) -> str: cmd = [ self.openclaw_bin, "agent", "--session-id", session_id, "--message", prompt, "--json", "--timeout", str(self.openclaw_timeout), ] self.logger.info("openclaw call: session=%s", session_id) try: proc = subprocess.run( cmd, capture_output=True, text=True, timeout=self.openclaw_timeout + 20, ) except subprocess.TimeoutExpired: self.logger.error("openclaw call timeout: session=%s timeout=%ss", session_id, self.openclaw_timeout) return f"OpenClaw 调用超时（>{self.openclaw_timeout}秒），请重试。" if proc.returncode != 0: err = (proc.stderr or proc.stdout or "openclaw error").strip() return f"OpenClaw 调用失败: {err[:500]}" try: raw_stdout = (proc.stdout or "").strip() decoder = json.JSONDecoder() data = None parse_error = None try: data, _ = decoder.raw_decode(raw_stdout) except Exception as exc: parse_error = exc idx = raw_stdout.find("{") while idx != -1: candidate = raw_stdout[idx:] try: data, _ = decoder.raw_decode(candidate) break except Exception: idx = raw_stdout.find("{", idx + 1) if data is None: raise parse_error payloads = data.get("result", {}).get("payloads", []) text_items = [p.get("text", "") for p in payloads if isinstance(p, dict)] answer = "\n".join(t for t in text_items if t).strip() if not answer: answer = "任务已执行，但未返回文本结果。" market_fallback_hints = ( "无法直接从页面抓取", "需要登录后的操作", "工具版本不支持点击交互", "无法正常访问该系统", "您没有权限访问此页面", "尚未登录", "请先前往登录页登录", "device identity required", "控制用户界面需要HTTPS", ) if self._is_market_prompt(prompt) and any(h in answer for h in market_fallback_hints): subject = self._extract_market_subject(prompt) fallback = self._run_market_brief(subject) return f"已切换为市场分析直连模式（{subject}）：\n\n{fallback}" return answer except Exception as exc: self.logger.exception("parse openclaw output failed") raw = (proc.stdout or "").strip() return f"结果解析失败: {exc}.\n原始输出: {raw[:500]}" def _is_image_url(self, raw_url: str) -> bool: try: parsed = urllib.parse.urlparse(raw_url) except Exception: return False host = (parsed.hostname or "").lower() path = (parsed.path or "").lower() if IMAGE_EXT_RE.search(path): return True if host.startswith("img.") or "image" in host: return True return False def _extract_image_urls(self, text: str, limit: int = 5) -> list: urls = [] seen = set() for match in URL_RE.finditer(text or ""): raw = match.group(0).rstrip(".,;!?") if not self._is_image_url(raw): continue if raw in seen: continue seen.add(raw) urls.append(raw) if len(urls) >= limit: break return urls def _remove_image_urls(self, text: str, urls: list) -> str: out = text for u in urls: out = out.replace(u, "") out = re.sub(r"\n{3,}", "\n\n", out) return out.strip() def _build_action_buttons(self) -> list: if not self.action_card_btn_url: return [] return [ { "text": self.action_card_btn_text or "打开链接", "url": self.action_card_btn_url, "iosUrl": self.action_card_btn_url, "color": "gray", } ] def _is_card_reply_ok(self, reply_obj) -> bool: if reply_obj is None: return False card_instance_id = getattr(reply_obj, "card_instance_id", None) if isinstance(card_instance_id, str): return bool(card_instance_id.strip()) return bool(card_instance_id) def _reply_message(self, msg: ChatbotMessage, text: str, prefer_card: bool = True) -> bool: payload = (text or "").strip() or "任务已执行，但未返回文本结果。" if self.reply_style != "action_card": prefer_card = False if self.card_disabled_until > time.time(): prefer_card = False if prefer_card: image_urls = self._extract_image_urls(payload, limit=5) if image_urls: slider = [(f"图片{i + 1}", u) for i, u in enumerate(image_urls)] markdown = self._remove_image_urls(payload, image_urls) if not markdown: markdown = "已整理相关图片如下：" try: card = self.reply_carousel_card( incoming_message=msg, markdown=markdown, image_slider=slider, button_text=self.action_card_btn_text or "查看", title=self.action_card_title, logo=self.action_card_logo, ) if self._is_card_reply_ok(card): return True self.logger.warning("carousel card reply returned empty id, fallback to action card/text") self._disable_card_temporarily("carousel_card_empty_id") except Exception as exc: self.logger.exception("carousel card reply failed, fallback to action card") if "Card.Instance.Write" in str(exc) or "AccessDenied" in str(exc): self._disable_card_temporarily("card_permission_denied") markdown = payload if self.action_card_title: markdown = f"### {self.action_card_title}\n\n{payload}" try: card = self.reply_markdown_button( incoming_message=msg, markdown=markdown, button_list=self._build_action_buttons(), tips=self.action_card_tips, title=self.action_card_title, logo=self.action_card_logo, ) if self._is_card_reply_ok(card): return True self.logger.warning("action card reply returned empty id, fallback to text") self._disable_card_temporarily("action_card_empty_id") except Exception as exc: self.logger.exception("action card reply failed, fallback to text") if "Card.Instance.Write" in str(exc) or "AccessDenied" in str(exc): self._disable_card_temporarily("card_permission_denied") resp = self.reply_text(payload, msg) if resp is None: self.logger.error("text reply failed") return False return True async def process(self, callback: CallbackMessage): try: msg = ChatbotMessage.from_dict(callback.data) except Exception: self.logger.exception("invalid callback payload") return AckMessage.STATUS_BAD_REQUEST, "bad payload" text = "" if msg.text and getattr(msg.text, "content", None): text = msg.text.content.strip() else: text_list = msg.get_text_list() or [] text = text_list[0].strip() if text_list else "" incoming_image_codes = self._extract_incoming_download_codes(msg) if not text and not incoming_image_codes: return AckMessage.STATUS_OK, "ignored" if not self._should_handle(msg, text): return AckMessage.STATUS_OK, "ignored" prompt = self._normalize_prompt(text) if not prompt: if incoming_image_codes: prompt = "请识别并分析我上传的图片内容，输出结论和建议。" else: self._reply_message( msg, f"用法: {self.prefix} 你的问题\n例如: {self.prefix} 查询亿家达旗舰店上周业绩", prefer_card=False, ) return AckMessage.STATUS_OK, "ok" event_key = self._event_key(callback, msg, prompt) if self._seen_or_mark_event(event_key): self.logger.info( "duplicate callback ignored: key=%s conversation=%s sender=%s", event_key, getattr(msg, "conversation_id", ""), getattr(msg, "sender_id", ""), ) return AckMessage.STATUS_OK, "duplicate_ignored" if self._is_smalltalk_prompt(prompt): try: self._reply_message(msg, self.smalltalk_reply_text, prefer_card=False) except Exception: self.logger.exception("failed to send smalltalk reply") return AckMessage.STATUS_OK, "smalltalk_ok" if self.send_processing_hint: hint = self.processing_hint_text or "已收到，正在处理，请稍等。" try: self.reply_text(hint, msg) except Exception: self.logger.exception("failed to send processing hint") conversation_key = re.sub(r"[^A-Za-z0-9_-]+", "-", str(getattr(msg, "conversation_id", "") or "default")) conv_lock = self._conversation_locks.setdefault(conversation_key, asyncio.Lock()) async with conv_lock: session_id = self._session_id(msg) image_context_result = {"used_images": 0, "context_text": "", "uploaded_urls": [], "warnings": []} prompt_for_exec = prompt try: async with self._work_semaphore: self.logger.info( "worker acquired: session=%s conversation=%s max_parallel=%s", session_id, conversation_key, self.max_parallel_jobs, ) if incoming_image_codes and not self._is_install_media_prompt(prompt): image_context_result = await asyncio.to_thread( self._build_image_context_from_dingtalk, msg, prompt, incoming_image_codes, ) context_text = image_context_result.get("context_text", "") if context_text: prompt_for_exec = self._merge_prompt_with_image_context(prompt, context_text) if self._is_install_media_prompt(prompt): answer = await asyncio.to_thread(self._run_install_media_lookup, prompt) elif self._is_dalongxia_analytics_prompt(prompt): answer = await asyncio.to_thread(self._run_dalongxia_analytics, prompt) elif self._is_video_analysis_prompt(prompt): answer = await asyncio.to_thread(self._run_video_analysis, prompt) elif self._is_market_prompt(prompt): subject = self._extract_market_subject(prompt) answer = await asyncio.to_thread(self._run_market_brief, subject) else: answer = await asyncio.to_thread(self._run_openclaw, session_id, prompt_for_exec) except Exception: self.logger.exception("worker execution failed: session=%s", session_id) answer = "系统执行异常，请稍后重试。" if incoming_image_codes and image_context_result.get("used_images", 0) == 0: warnings = image_context_result.get("warnings", []) warn_text = "；".join(warnings[:2]) if warnings else "图片下载或识别失败" answer = f"已收到图片，但未完成识别：{warn_text}。请重发清晰图片后再试。" elif image_context_result.get("warnings"): answer = f"{answer}\n\n（图片处理提示：{'；'.join(image_context_result['warnings'][:2])}）" answer = self._clean_dialog_noise(answer) answer = self._trim_noncode_blocks(prompt, answer) answer = self._sanitize_answer(prompt, answer) answer = self._mask_sensitive_amounts(prompt, answer) if len(answer) > self.reply_max_chars: answer = answer[: self.reply_max_chars] + "\n...(已截断)" try: prefer_card = not self._is_install_media_prompt(prompt) sent = self._reply_message(msg, answer, prefer_card=prefer_card) if sent: self.logger.info("reply sent: session=%s chars=%s", session_id, len(answer)) else: self.logger.error("reply failed: session=%s chars=%s", session_id, len(answer)) except Exception: self.logger.exception("failed to send final reply: session=%s", session_id) return AckMessage.STATUS_OK, "ok" def build_client(logger: logging.Logger) -> DingTalkStreamClient: client_id = os.getenv("DINGTALK_CLIENT_ID", "").strip() client_secret = os.getenv("DINGTALK_CLIENT_SECRET", "").strip() if not client_id or not client_secret: raise RuntimeError("DINGTALK_CLIENT_ID / DINGTALK_CLIENT_SECRET 未配置") credential = Credential(client_id, client_secret) client = DingTalkStreamClient(credential, logger=logger) bot = OpenClawDingTalkBot(logger) client.register_callback_handler(ChatbotMessage.TOPIC, bot) if bool_env("REGISTER_DELEGATE_TOPIC", False): client.register_callback_handler(ChatbotMessage.DELEGATE_TOPIC, bot) logger.info("delegate topic enabled") else: logger.info("delegate topic disabled (default)") return client def self_check(logger: logging.Logger) -> int: required = ["DINGTALK_CLIENT_ID", "DINGTALK_CLIENT_SECRET"] missing = [k for k in required if not os.getenv(k)] if missing: logger.error("missing env: %s", ", ".join(missing)) return 2 openclaw_bin = os.getenv("OPENCLAW_BIN", "/usr/bin/openclaw") proc = subprocess.run([openclaw_bin, "--version"], capture_output=True, text=True) if proc.returncode != 0: logger.error("openclaw check failed: %s", (proc.stderr or proc.stdout).strip()) return 3 market_brief_bin = os.getenv("MARKET_BRIEF_BIN", "/usr/local/bin/market-brief-report") if not os.path.exists(market_brief_bin): logger.error("market brief bin not found: %s", market_brief_bin) return 4 install_media_bin = os.getenv("INSTALL_MEDIA_BIN", "/usr/local/bin/install-media-lookup") if not os.path.exists(install_media_bin): logger.error("install media bin not found: %s", install_media_bin) return 5 logger.info("self-check ok, openclaw=%s", (proc.stdout or "").strip()) return 0 def main() -> int: parser = argparse.ArgumentParser(description="OpenClaw DingTalk Bridge") parser.add_argument("--check", action="store_true", help="run checks and exit") args = parser.parse_args() logging.basicConfig( level=os.getenv("LOG_LEVEL", "INFO").upper(), format="%(asctime)s %(levelname)s %(name)s: %(message)s", ) logger = logging.getLogger("openclaw-dingtalk-bridge") if args.check: return self_check(logger) client = build_client(logger) logger.info("bridge started, listening DingTalk stream") client.start_forever() return 0 if __name__ == "__main__": raise SystemExit(main())