From 4a1fae3cb4ab99d0e69376ce89655916d59e9efb Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 15:21:28 +0800 Subject: [PATCH 01/11] chore: the bot directory was changed to models --- agent/tools/memory/memory_get.py | 2 +- bridge/agent_bridge.py | 2 +- bridge/bridge.py | 2 +- {bot => models}/ali/ali_qwen_bot.py | 6 ++-- {bot => models}/ali/ali_qwen_session.py | 2 +- {bot => models}/baidu/baidu_unit_bot.py | 2 +- {bot => models}/baidu/baidu_wenxin.py | 6 ++-- {bot => models}/baidu/baidu_wenxin_session.py | 2 +- {bot => models}/bot.py | 0 {bot => models}/bot_factory.py | 32 +++++++++---------- {bot => models}/chatgpt/chat_gpt_bot.py | 12 +++---- {bot => models}/chatgpt/chat_gpt_session.py | 2 +- {bot => models}/claudeapi/claude_api_bot.py | 8 ++--- {bot => models}/dashscope/dashscope_bot.py | 4 +-- .../dashscope/dashscope_session.py | 2 +- {bot => models}/gemini/google_gemini_bot.py | 8 ++--- {bot => models}/linkai/link_ai_bot.py | 8 ++--- {bot => models}/minimax/minimax_bot.py | 8 ++--- {bot => models}/minimax/minimax_session.py | 2 +- {bot => models}/modelscope/modelscope_bot.py | 4 +-- .../modelscope/modelscope_session.py | 2 +- {bot => models}/moonshot/moonshot_bot.py | 4 +-- {bot => models}/moonshot/moonshot_session.py | 2 +- {bot => models}/openai/open_ai_bot.py | 10 +++--- {bot => models}/openai/open_ai_image.py | 2 +- {bot => models}/openai/open_ai_session.py | 2 +- {bot => models}/openai/openai_compat.py | 0 {bot => models}/openai_compatible_bot.py | 0 {bot => models}/session_manager.py | 0 {bot => models}/xunfei/xunfei_spark_bot.py | 6 ++-- {bot => models}/zhipuai/zhipu_ai_image.py | 0 {bot => models}/zhipuai/zhipu_ai_session.py | 2 +- {bot => models}/zhipuai/zhipuai_bot.py | 8 ++--- 33 files changed, 76 insertions(+), 76 deletions(-) rename {bot => models}/ali/ali_qwen_bot.py (98%) rename {bot => models}/ali/ali_qwen_session.py (98%) rename {bot => models}/baidu/baidu_unit_bot.py (98%) rename {bot => models}/baidu/baidu_wenxin.py (97%) rename {bot => models}/baidu/baidu_wenxin_session.py (97%) rename {bot => models}/bot.py (100%) rename {bot => models}/bot_factory.py (60%) rename {bot => models}/chatgpt/chat_gpt_bot.py (97%) rename {bot => models}/chatgpt/chat_gpt_session.py (99%) rename {bot => models}/claudeapi/claude_api_bot.py (98%) rename {bot => models}/dashscope/dashscope_bot.py (98%) rename {bot => models}/dashscope/dashscope_session.py (97%) rename {bot => models}/gemini/google_gemini_bot.py (99%) rename {bot => models}/linkai/link_ai_bot.py (99%) rename {bot => models}/minimax/minimax_bot.py (97%) rename {bot => models}/minimax/minimax_session.py (98%) rename {bot => models}/modelscope/modelscope_bot.py (99%) rename {bot => models}/modelscope/modelscope_session.py (97%) rename {bot => models}/moonshot/moonshot_bot.py (98%) rename {bot => models}/moonshot/moonshot_session.py (97%) rename {bot => models}/openai/open_ai_bot.py (97%) rename {bot => models}/openai/open_ai_image.py (96%) rename {bot => models}/openai/open_ai_session.py (98%) rename {bot => models}/openai/openai_compat.py (100%) rename {bot => models}/openai_compatible_bot.py (100%) rename {bot => models}/session_manager.py (100%) rename {bot => models}/xunfei/xunfei_spark_bot.py (98%) rename {bot => models}/zhipuai/zhipu_ai_image.py (100%) rename {bot => models}/zhipuai/zhipu_ai_session.py (97%) rename {bot => models}/zhipuai/zhipuai_bot.py (97%) diff --git a/agent/tools/memory/memory_get.py b/agent/tools/memory/memory_get.py index d828386..50ca639 100644 --- a/agent/tools/memory/memory_get.py +++ b/agent/tools/memory/memory_get.py @@ -22,7 +22,7 @@ class MemoryGetTool(BaseTool): "properties": { "path": { "type": "string", - "description": "Relative path to the memory file (e.g., 'MEMORY.md', 'memory/2024-01-29.md')" + "description": "Relative path to the memory file (e.g., 'MEMORY.md', 'memory/2026-01-01.md')" }, "start_line": { "type": "integer", diff --git a/bridge/agent_bridge.py b/bridge/agent_bridge.py index 34535bb..9054a64 100644 --- a/bridge/agent_bridge.py +++ b/bridge/agent_bridge.py @@ -5,7 +5,7 @@ Agent Bridge - Integrates Agent system with existing COW bridge from typing import Optional, List from agent.protocol import Agent, LLMModel, LLMRequest -from bot.openai_compatible_bot import OpenAICompatibleBot +from models.openai_compatible_bot import OpenAICompatibleBot from bridge.bridge import Bridge from bridge.context import Context from bridge.reply import Reply, ReplyType diff --git a/bridge/bridge.py b/bridge/bridge.py index a7b93c4..4c686f9 100644 --- a/bridge/bridge.py +++ b/bridge/bridge.py @@ -1,4 +1,4 @@ -from bot.bot_factory import create_bot +from models.bot_factory import create_bot from bridge.context import Context from bridge.reply import Reply from common import const diff --git a/bot/ali/ali_qwen_bot.py b/models/ali/ali_qwen_bot.py similarity index 98% rename from bot/ali/ali_qwen_bot.py rename to models/ali/ali_qwen_bot.py index ae9d767..5dbdc89 100644 --- a/bot/ali/ali_qwen_bot.py +++ b/models/ali/ali_qwen_bot.py @@ -9,9 +9,9 @@ import openai.error import broadscope_bailian from broadscope_bailian import ChatQaMessage -from bot.bot import Bot -from bot.ali.ali_qwen_session import AliQwenSession -from bot.session_manager import SessionManager +from models.bot import Bot +from models.ali.ali_qwen_session import AliQwenSession +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/ali/ali_qwen_session.py b/models/ali/ali_qwen_session.py similarity index 98% rename from bot/ali/ali_qwen_session.py rename to models/ali/ali_qwen_session.py index 0eb1c4a..48c5eea 100644 --- a/bot/ali/ali_qwen_session.py +++ b/models/ali/ali_qwen_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger """ diff --git a/bot/baidu/baidu_unit_bot.py b/models/baidu/baidu_unit_bot.py similarity index 98% rename from bot/baidu/baidu_unit_bot.py rename to models/baidu/baidu_unit_bot.py index f7714e4..35319e2 100644 --- a/bot/baidu/baidu_unit_bot.py +++ b/models/baidu/baidu_unit_bot.py @@ -2,7 +2,7 @@ import requests -from bot.bot import Bot +from models.bot import Bot from bridge.reply import Reply, ReplyType diff --git a/bot/baidu/baidu_wenxin.py b/models/baidu/baidu_wenxin.py similarity index 97% rename from bot/baidu/baidu_wenxin.py rename to models/baidu/baidu_wenxin.py index dd660af..341f482 100644 --- a/bot/baidu/baidu_wenxin.py +++ b/models/baidu/baidu_wenxin.py @@ -3,13 +3,13 @@ import requests import json from common import const -from bot.bot import Bot -from bot.session_manager import SessionManager +from models.bot import Bot +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger from config import conf -from bot.baidu.baidu_wenxin_session import BaiduWenxinSession +from models.baidu.baidu_wenxin_session import BaiduWenxinSession BAIDU_API_KEY = conf().get("baidu_wenxin_api_key") BAIDU_SECRET_KEY = conf().get("baidu_wenxin_secret_key") diff --git a/bot/baidu/baidu_wenxin_session.py b/models/baidu/baidu_wenxin_session.py similarity index 97% rename from bot/baidu/baidu_wenxin_session.py rename to models/baidu/baidu_wenxin_session.py index 5ba2f17..52b5c93 100644 --- a/bot/baidu/baidu_wenxin_session.py +++ b/models/baidu/baidu_wenxin_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger """ diff --git a/bot/bot.py b/models/bot.py similarity index 100% rename from bot/bot.py rename to models/bot.py diff --git a/bot/bot_factory.py b/models/bot_factory.py similarity index 60% rename from bot/bot_factory.py rename to models/bot_factory.py index 05cf0ea..2fb56dd 100644 --- a/bot/bot_factory.py +++ b/models/bot_factory.py @@ -12,64 +12,64 @@ def create_bot(bot_type): """ if bot_type == const.BAIDU: # 替换Baidu Unit为Baidu文心千帆对话接口 - # from bot.baidu.baidu_unit_bot import BaiduUnitBot + # from models.baidu.baidu_unit_bot import BaiduUnitBot # return BaiduUnitBot() - from bot.baidu.baidu_wenxin import BaiduWenxinBot + from models.baidu.baidu_wenxin import BaiduWenxinBot return BaiduWenxinBot() elif bot_type == const.CHATGPT: # ChatGPT 网页端web接口 - from bot.chatgpt.chat_gpt_bot import ChatGPTBot + from models.chatgpt.chat_gpt_bot import ChatGPTBot return ChatGPTBot() elif bot_type == const.OPEN_AI: # OpenAI 官方对话模型API - from bot.openai.open_ai_bot import OpenAIBot + from models.openai.open_ai_bot import OpenAIBot return OpenAIBot() elif bot_type == const.CHATGPTONAZURE: # Azure chatgpt service https://azure.microsoft.com/en-in/products/cognitive-services/openai-service/ - from bot.chatgpt.chat_gpt_bot import AzureChatGPTBot + from models.chatgpt.chat_gpt_bot import AzureChatGPTBot return AzureChatGPTBot() elif bot_type == const.XUNFEI: - from bot.xunfei.xunfei_spark_bot import XunFeiBot + from models.xunfei.xunfei_spark_bot import XunFeiBot return XunFeiBot() elif bot_type == const.LINKAI: - from bot.linkai.link_ai_bot import LinkAIBot + from models.linkai.link_ai_bot import LinkAIBot return LinkAIBot() elif bot_type == const.CLAUDEAI: - from bot.claude.claude_ai_bot import ClaudeAIBot + from models.claude.claude_ai_bot import ClaudeAIBot return ClaudeAIBot() elif bot_type == const.CLAUDEAPI: - from bot.claudeapi.claude_api_bot import ClaudeAPIBot + from models.claudeapi.claude_api_bot import ClaudeAPIBot return ClaudeAPIBot() elif bot_type == const.QWEN: - from bot.ali.ali_qwen_bot import AliQwenBot + from models.ali.ali_qwen_bot import AliQwenBot return AliQwenBot() elif bot_type == const.QWEN_DASHSCOPE: - from bot.dashscope.dashscope_bot import DashscopeBot + from models.dashscope.dashscope_bot import DashscopeBot return DashscopeBot() elif bot_type == const.GEMINI: - from bot.gemini.google_gemini_bot import GoogleGeminiBot + from models.gemini.google_gemini_bot import GoogleGeminiBot return GoogleGeminiBot() elif bot_type == const.ZHIPU_AI: - from bot.zhipuai.zhipuai_bot import ZHIPUAIBot + from models.zhipuai.zhipuai_bot import ZHIPUAIBot return ZHIPUAIBot() elif bot_type == const.MOONSHOT: - from bot.moonshot.moonshot_bot import MoonshotBot + from models.moonshot.moonshot_bot import MoonshotBot return MoonshotBot() elif bot_type == const.MiniMax: - from bot.minimax.minimax_bot import MinimaxBot + from models.minimax.minimax_bot import MinimaxBot return MinimaxBot() elif bot_type == const.MODELSCOPE: - from bot.modelscope.modelscope_bot import ModelScopeBot + from models.modelscope.modelscope_bot import ModelScopeBot return ModelScopeBot() diff --git a/bot/chatgpt/chat_gpt_bot.py b/models/chatgpt/chat_gpt_bot.py similarity index 97% rename from bot/chatgpt/chat_gpt_bot.py rename to models/chatgpt/chat_gpt_bot.py index cfe3246..5907667 100644 --- a/bot/chatgpt/chat_gpt_bot.py +++ b/models/chatgpt/chat_gpt_bot.py @@ -7,17 +7,17 @@ import openai import openai.error import requests from common import const -from bot.bot import Bot -from bot.openai_compatible_bot import OpenAICompatibleBot -from bot.chatgpt.chat_gpt_session import ChatGPTSession -from bot.openai.open_ai_image import OpenAIImage -from bot.session_manager import SessionManager +from models.bot import Bot +from models.openai_compatible_bot import OpenAICompatibleBot +from models.chatgpt.chat_gpt_session import ChatGPTSession +from models.openai.open_ai_image import OpenAIImage +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger from common.token_bucket import TokenBucket from config import conf, load_config -from bot.baidu.baidu_wenxin_session import BaiduWenxinSession +from models.baidu.baidu_wenxin_session import BaiduWenxinSession # OpenAI对话模型API (可用) class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot): diff --git a/bot/chatgpt/chat_gpt_session.py b/models/chatgpt/chat_gpt_session.py similarity index 99% rename from bot/chatgpt/chat_gpt_session.py rename to models/chatgpt/chat_gpt_session.py index 5f524a3..d25b093 100644 --- a/bot/chatgpt/chat_gpt_session.py +++ b/models/chatgpt/chat_gpt_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger from common import const diff --git a/bot/claudeapi/claude_api_bot.py b/models/claudeapi/claude_api_bot.py similarity index 98% rename from bot/claudeapi/claude_api_bot.py rename to models/claudeapi/claude_api_bot.py index 804ae4c..eaf08ae 100644 --- a/bot/claudeapi/claude_api_bot.py +++ b/models/claudeapi/claude_api_bot.py @@ -5,9 +5,9 @@ import time import requests -from bot.baidu.baidu_wenxin_session import BaiduWenxinSession -from bot.bot import Bot -from bot.session_manager import SessionManager +from models.baidu.baidu_wenxin_session import BaiduWenxinSession +from models.bot import Bot +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common import const @@ -16,7 +16,7 @@ from config import conf # Optional OpenAI image support try: - from bot.openai.open_ai_image import OpenAIImage + from models.openai.open_ai_image import OpenAIImage _openai_image_available = True except Exception as e: logger.warning(f"OpenAI image support not available: {e}") diff --git a/bot/dashscope/dashscope_bot.py b/models/dashscope/dashscope_bot.py similarity index 98% rename from bot/dashscope/dashscope_bot.py rename to models/dashscope/dashscope_bot.py index 07554c4..75f4ea0 100644 --- a/bot/dashscope/dashscope_bot.py +++ b/models/dashscope/dashscope_bot.py @@ -1,7 +1,7 @@ # encoding:utf-8 -from bot.bot import Bot -from bot.session_manager import SessionManager +from models.bot import Bot +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/dashscope/dashscope_session.py b/models/dashscope/dashscope_session.py similarity index 97% rename from bot/dashscope/dashscope_session.py rename to models/dashscope/dashscope_session.py index 0de57b9..042334e 100644 --- a/bot/dashscope/dashscope_session.py +++ b/models/dashscope/dashscope_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger diff --git a/bot/gemini/google_gemini_bot.py b/models/gemini/google_gemini_bot.py similarity index 99% rename from bot/gemini/google_gemini_bot.py rename to models/gemini/google_gemini_bot.py index 422ec2e..cf46ef8 100644 --- a/bot/gemini/google_gemini_bot.py +++ b/models/gemini/google_gemini_bot.py @@ -9,15 +9,15 @@ Google gemini bot import json import time import requests -from bot.bot import Bot +from models.bot import Bot import google.generativeai as genai -from bot.session_manager import SessionManager +from models.session_manager import SessionManager from bridge.context import ContextType, Context from bridge.reply import Reply, ReplyType from common.log import logger from config import conf -from bot.chatgpt.chat_gpt_session import ChatGPTSession -from bot.baidu.baidu_wenxin_session import BaiduWenxinSession +from models.chatgpt.chat_gpt_session import ChatGPTSession +from models.baidu.baidu_wenxin_session import BaiduWenxinSession from google.generativeai.types import HarmCategory, HarmBlockThreshold diff --git a/bot/linkai/link_ai_bot.py b/models/linkai/link_ai_bot.py similarity index 99% rename from bot/linkai/link_ai_bot.py rename to models/linkai/link_ai_bot.py index 9410062..28be2d1 100644 --- a/bot/linkai/link_ai_bot.py +++ b/models/linkai/link_ai_bot.py @@ -6,10 +6,10 @@ import time import requests import json import config -from bot.bot import Bot -from bot.openai_compatible_bot import OpenAICompatibleBot -from bot.chatgpt.chat_gpt_session import ChatGPTSession -from bot.session_manager import SessionManager +from models.bot import Bot +from models.openai_compatible_bot import OpenAICompatibleBot +from models.chatgpt.chat_gpt_session import ChatGPTSession +from models.session_manager import SessionManager from bridge.context import Context, ContextType from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/minimax/minimax_bot.py b/models/minimax/minimax_bot.py similarity index 97% rename from bot/minimax/minimax_bot.py rename to models/minimax/minimax_bot.py index 40112d8..53265fb 100644 --- a/bot/minimax/minimax_bot.py +++ b/models/minimax/minimax_bot.py @@ -4,14 +4,14 @@ import time import openai import openai.error -from bot.bot import Bot -from bot.minimax.minimax_session import MinimaxSession -from bot.session_manager import SessionManager +from models.bot import Bot +from models.minimax.minimax_session import MinimaxSession +from models.session_manager import SessionManager from bridge.context import Context, ContextType from bridge.reply import Reply, ReplyType from common.log import logger from config import conf, load_config -from bot.chatgpt.chat_gpt_session import ChatGPTSession +from models.chatgpt.chat_gpt_session import ChatGPTSession import requests from common import const diff --git a/bot/minimax/minimax_session.py b/models/minimax/minimax_session.py similarity index 98% rename from bot/minimax/minimax_session.py rename to models/minimax/minimax_session.py index 1925b4b..7479170 100644 --- a/bot/minimax/minimax_session.py +++ b/models/minimax/minimax_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger """ diff --git a/bot/modelscope/modelscope_bot.py b/models/modelscope/modelscope_bot.py similarity index 99% rename from bot/modelscope/modelscope_bot.py rename to models/modelscope/modelscope_bot.py index 238ac59..80e86cb 100644 --- a/bot/modelscope/modelscope_bot.py +++ b/models/modelscope/modelscope_bot.py @@ -4,8 +4,8 @@ import time import json import openai import openai.error -from bot.bot import Bot -from bot.session_manager import SessionManager +from models.bot import Bot +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/modelscope/modelscope_session.py b/models/modelscope/modelscope_session.py similarity index 97% rename from bot/modelscope/modelscope_session.py rename to models/modelscope/modelscope_session.py index 726d683..fc349ed 100644 --- a/bot/modelscope/modelscope_session.py +++ b/models/modelscope/modelscope_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger diff --git a/bot/moonshot/moonshot_bot.py b/models/moonshot/moonshot_bot.py similarity index 98% rename from bot/moonshot/moonshot_bot.py rename to models/moonshot/moonshot_bot.py index 61eb26d..8da05b7 100644 --- a/bot/moonshot/moonshot_bot.py +++ b/models/moonshot/moonshot_bot.py @@ -4,8 +4,8 @@ import time import openai import openai.error -from bot.bot import Bot -from bot.session_manager import SessionManager +from models.bot import Bot +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/moonshot/moonshot_session.py b/models/moonshot/moonshot_session.py similarity index 97% rename from bot/moonshot/moonshot_session.py rename to models/moonshot/moonshot_session.py index 63e08f5..a5a1842 100644 --- a/bot/moonshot/moonshot_session.py +++ b/models/moonshot/moonshot_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger diff --git a/bot/openai/open_ai_bot.py b/models/openai/open_ai_bot.py similarity index 97% rename from bot/openai/open_ai_bot.py rename to models/openai/open_ai_bot.py index e5501d0..5c8911e 100644 --- a/bot/openai/open_ai_bot.py +++ b/models/openai/open_ai_bot.py @@ -5,11 +5,11 @@ import time import openai import openai.error -from bot.bot import Bot -from bot.openai_compatible_bot import OpenAICompatibleBot -from bot.openai.open_ai_image import OpenAIImage -from bot.openai.open_ai_session import OpenAISession -from bot.session_manager import SessionManager +from models.bot import Bot +from models.openai_compatible_bot import OpenAICompatibleBot +from models.openai.open_ai_image import OpenAIImage +from models.openai.open_ai_session import OpenAISession +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/openai/open_ai_image.py b/models/openai/open_ai_image.py similarity index 96% rename from bot/openai/open_ai_image.py rename to models/openai/open_ai_image.py index 07a8e47..fb113a0 100644 --- a/bot/openai/open_ai_image.py +++ b/models/openai/open_ai_image.py @@ -1,7 +1,7 @@ import time import openai -from bot.openai.openai_compat import RateLimitError +from models.openai.openai_compat import RateLimitError from common.log import logger from common.token_bucket import TokenBucket diff --git a/bot/openai/open_ai_session.py b/models/openai/open_ai_session.py similarity index 98% rename from bot/openai/open_ai_session.py rename to models/openai/open_ai_session.py index 8f6aa4f..76023f8 100644 --- a/bot/openai/open_ai_session.py +++ b/models/openai/open_ai_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger diff --git a/bot/openai/openai_compat.py b/models/openai/openai_compat.py similarity index 100% rename from bot/openai/openai_compat.py rename to models/openai/openai_compat.py diff --git a/bot/openai_compatible_bot.py b/models/openai_compatible_bot.py similarity index 100% rename from bot/openai_compatible_bot.py rename to models/openai_compatible_bot.py diff --git a/bot/session_manager.py b/models/session_manager.py similarity index 100% rename from bot/session_manager.py rename to models/session_manager.py diff --git a/bot/xunfei/xunfei_spark_bot.py b/models/xunfei/xunfei_spark_bot.py similarity index 98% rename from bot/xunfei/xunfei_spark_bot.py rename to models/xunfei/xunfei_spark_bot.py index 06e5501..d2662f9 100644 --- a/bot/xunfei/xunfei_spark_bot.py +++ b/models/xunfei/xunfei_spark_bot.py @@ -1,9 +1,9 @@ # encoding:utf-8 import requests, json -from bot.bot import Bot -from bot.session_manager import SessionManager -from bot.chatgpt.chat_gpt_session import ChatGPTSession +from models.bot import Bot +from models.session_manager import SessionManager +from models.chatgpt.chat_gpt_session import ChatGPTSession from bridge.context import ContextType, Context from bridge.reply import Reply, ReplyType from common.log import logger diff --git a/bot/zhipuai/zhipu_ai_image.py b/models/zhipuai/zhipu_ai_image.py similarity index 100% rename from bot/zhipuai/zhipu_ai_image.py rename to models/zhipuai/zhipu_ai_image.py diff --git a/bot/zhipuai/zhipu_ai_session.py b/models/zhipuai/zhipu_ai_session.py similarity index 97% rename from bot/zhipuai/zhipu_ai_session.py rename to models/zhipuai/zhipu_ai_session.py index 846d36a..afb30cc 100644 --- a/bot/zhipuai/zhipu_ai_session.py +++ b/models/zhipuai/zhipu_ai_session.py @@ -1,4 +1,4 @@ -from bot.session_manager import Session +from models.session_manager import Session from common.log import logger diff --git a/bot/zhipuai/zhipuai_bot.py b/models/zhipuai/zhipuai_bot.py similarity index 97% rename from bot/zhipuai/zhipuai_bot.py rename to models/zhipuai/zhipuai_bot.py index d8eed4d..59adccc 100644 --- a/bot/zhipuai/zhipuai_bot.py +++ b/models/zhipuai/zhipuai_bot.py @@ -4,10 +4,10 @@ import time import openai import openai.error -from bot.bot import Bot -from bot.zhipuai.zhipu_ai_session import ZhipuAISession -from bot.zhipuai.zhipu_ai_image import ZhipuAIImage -from bot.session_manager import SessionManager +from models.bot import Bot +from models.zhipuai.zhipu_ai_session import ZhipuAISession +from models.zhipuai.zhipu_ai_image import ZhipuAIImage +from models.session_manager import SessionManager from bridge.context import ContextType from bridge.reply import Reply, ReplyType from common.log import logger From c693e3919666caddf298b1682288de4354a45f95 Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 17:04:46 +0800 Subject: [PATCH 02/11] feat: improve the memory system --- agent/memory/__init__.py | 3 +- agent/memory/config.py | 4 + agent/memory/embedding.py | 133 ++++------ agent/memory/manager.py | 47 ++-- agent/memory/summarizer.py | 70 +++-- agent/prompt/builder.py | 19 +- agent/protocol/agent_stream.py | 28 +- agent/tools/__init__.py | 12 - agent/tools/calculator/calculator.py | 58 ---- agent/tools/edit/edit.py | 2 +- agent/tools/find/__init__.py | 3 - agent/tools/find/find.py | 177 ------------- agent/tools/grep/__init__.py | 3 - agent/tools/grep/grep.py | 248 ----------------- agent/tools/memory/memory_get.py | 7 +- agent/tools/web_fetch/README.md | 212 --------------- agent/tools/web_fetch/__init__.py | 3 - agent/tools/web_fetch/install_deps.sh | 47 ---- agent/tools/web_fetch/web_fetch.py | 365 -------------------------- bridge/agent_bridge.py | 111 ++++++-- models/openai/open_ai_bot.py | 2 +- plugins/bdunit/README.md | 30 --- plugins/bdunit/__init__.py | 1 - plugins/bdunit/bdunit.py | 252 ------------------ plugins/bdunit/config.json.template | 5 - plugins/config.json.template | 11 - skills/skill-creator/SKILL.md | 13 + skills/web-fetch/SKILL.md | 49 ++++ skills/web-fetch/scripts/fetch.sh | 54 ++++ 29 files changed, 373 insertions(+), 1596 deletions(-) delete mode 100644 agent/tools/calculator/calculator.py delete mode 100644 agent/tools/find/__init__.py delete mode 100644 agent/tools/find/find.py delete mode 100644 agent/tools/grep/__init__.py delete mode 100644 agent/tools/grep/grep.py delete mode 100644 agent/tools/web_fetch/README.md delete mode 100644 agent/tools/web_fetch/__init__.py delete mode 100644 agent/tools/web_fetch/install_deps.sh delete mode 100644 agent/tools/web_fetch/web_fetch.py delete mode 100644 plugins/bdunit/README.md delete mode 100644 plugins/bdunit/__init__.py delete mode 100644 plugins/bdunit/bdunit.py delete mode 100644 plugins/bdunit/config.json.template create mode 100644 skills/web-fetch/SKILL.md create mode 100755 skills/web-fetch/scripts/fetch.sh diff --git a/agent/memory/__init__.py b/agent/memory/__init__.py index 4179bea..f638a9d 100644 --- a/agent/memory/__init__.py +++ b/agent/memory/__init__.py @@ -6,5 +6,6 @@ Provides long-term memory capabilities with hybrid search (vector + keyword) from agent.memory.manager import MemoryManager from agent.memory.config import MemoryConfig, get_default_memory_config, set_global_memory_config +from agent.memory.embedding import create_embedding_provider -__all__ = ['MemoryManager', 'MemoryConfig', 'get_default_memory_config', 'set_global_memory_config'] +__all__ = ['MemoryManager', 'MemoryConfig', 'get_default_memory_config', 'set_global_memory_config', 'create_embedding_provider'] diff --git a/agent/memory/config.py b/agent/memory/config.py index 758611d..63d945b 100644 --- a/agent/memory/config.py +++ b/agent/memory/config.py @@ -41,6 +41,10 @@ class MemoryConfig: enable_auto_sync: bool = True sync_on_search: bool = True + # Memory flush config (独立于模型 context window) + flush_token_threshold: int = 50000 # 50K tokens 触发 flush + flush_turn_threshold: int = 20 # 20 轮对话触发 flush (用户+AI各一条为一轮) + def get_workspace(self) -> Path: """Get workspace root directory""" return Path(self.workspace_root) diff --git a/agent/memory/embedding.py b/agent/memory/embedding.py index 4a71828..509370b 100644 --- a/agent/memory/embedding.py +++ b/agent/memory/embedding.py @@ -4,20 +4,19 @@ Embedding providers for memory Supports OpenAI and local embedding models """ -from typing import List, Optional -from abc import ABC, abstractmethod import hashlib -import json +from abc import ABC, abstractmethod +from typing import List, Optional class EmbeddingProvider(ABC): """Base class for embedding providers""" - + @abstractmethod def embed(self, text: str) -> List[float]: """Generate embedding for text""" pass - + @abstractmethod def embed_batch(self, texts: List[str]) -> List[List[float]]: """Generate embeddings for multiple texts""" @@ -31,7 +30,7 @@ class EmbeddingProvider(ABC): class OpenAIEmbeddingProvider(EmbeddingProvider): - """OpenAI embedding provider""" + """OpenAI embedding provider using REST API""" def __init__(self, model: str = "text-embedding-3-small", api_key: Optional[str] = None, api_base: Optional[str] = None): """ @@ -45,87 +44,58 @@ class OpenAIEmbeddingProvider(EmbeddingProvider): self.model = model self.api_key = api_key self.api_base = api_base or "https://api.openai.com/v1" - - # Lazy import to avoid dependency issues - try: - from openai import OpenAI - self.client = OpenAI(api_key=api_key, base_url=api_base) - except ImportError: - raise ImportError("OpenAI package not installed. Install with: pip install openai") - + + if not self.api_key: + raise ValueError("OpenAI API key is required") + # Set dimensions based on model self._dimensions = 1536 if "small" in model else 3072 - + + def _call_api(self, input_data): + """Call OpenAI embedding API using requests""" + import requests + + url = f"{self.api_base}/embeddings" + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {self.api_key}" + } + data = { + "input": input_data, + "model": self.model + } + + response = requests.post(url, headers=headers, json=data, timeout=30) + response.raise_for_status() + return response.json() + def embed(self, text: str) -> List[float]: """Generate embedding for text""" - response = self.client.embeddings.create( - input=text, - model=self.model - ) - return response.data[0].embedding - + result = self._call_api(text) + return result["data"][0]["embedding"] + def embed_batch(self, texts: List[str]) -> List[List[float]]: """Generate embeddings for multiple texts""" if not texts: return [] - - response = self.client.embeddings.create( - input=texts, - model=self.model - ) - return [item.embedding for item in response.data] - + + result = self._call_api(texts) + return [item["embedding"] for item in result["data"]] + @property def dimensions(self) -> int: return self._dimensions -class LocalEmbeddingProvider(EmbeddingProvider): - """Local embedding provider using sentence-transformers""" - - def __init__(self, model: str = "all-MiniLM-L6-v2"): - """ - Initialize local embedding provider - - Args: - model: Model name from sentence-transformers - """ - self.model_name = model - - try: - from sentence_transformers import SentenceTransformer - self.model = SentenceTransformer(model) - self._dimensions = self.model.get_sentence_embedding_dimension() - except ImportError: - raise ImportError( - "sentence-transformers not installed. " - "Install with: pip install sentence-transformers" - ) - - def embed(self, text: str) -> List[float]: - """Generate embedding for text""" - embedding = self.model.encode(text, convert_to_numpy=True) - return embedding.tolist() - - def embed_batch(self, texts: List[str]) -> List[List[float]]: - """Generate embeddings for multiple texts""" - if not texts: - return [] - - embeddings = self.model.encode(texts, convert_to_numpy=True) - return embeddings.tolist() - - @property - def dimensions(self) -> int: - return self._dimensions +# LocalEmbeddingProvider removed - only use OpenAI embedding or keyword search class EmbeddingCache: """Cache for embeddings to avoid recomputation""" - + def __init__(self): self.cache = {} - + def get(self, text: str, provider: str, model: str) -> Optional[List[float]]: """Get cached embedding""" key = self._compute_key(text, provider, model) @@ -156,20 +126,23 @@ def create_embedding_provider( """ Factory function to create embedding provider + Only supports OpenAI embedding via REST API. + If initialization fails, caller should fall back to keyword-only search. + Args: - provider: Provider name ("openai" or "local") - model: Model name (provider-specific) - api_key: API key for remote providers - api_base: API base URL for remote providers + provider: Provider name (only "openai" is supported) + model: Model name (default: text-embedding-3-small) + api_key: OpenAI API key (required) + api_base: API base URL (default: https://api.openai.com/v1) Returns: EmbeddingProvider instance + + Raises: + ValueError: If provider is not "openai" or api_key is missing """ - if provider == "openai": - model = model or "text-embedding-3-small" - return OpenAIEmbeddingProvider(model=model, api_key=api_key, api_base=api_base) - elif provider == "local": - model = model or "all-MiniLM-L6-v2" - return LocalEmbeddingProvider(model=model) - else: - raise ValueError(f"Unknown embedding provider: {provider}") + if provider != "openai": + raise ValueError(f"Only 'openai' provider is supported, got: {provider}") + + model = model or "text-embedding-3-small" + return OpenAIEmbeddingProvider(model=model, api_key=api_key, api_base=api_base) diff --git a/agent/memory/manager.py b/agent/memory/manager.py index b313e82..1e47811 100644 --- a/agent/memory/manager.py +++ b/agent/memory/manager.py @@ -70,8 +70,9 @@ class MemoryManager: except Exception as e: # Embedding provider failed, but that's OK # We can still use keyword search and file operations - print(f"⚠️ Warning: Embedding provider initialization failed: {e}") - print(f"ℹ️ Memory will work with keyword search only (no semantic search)") + from common.log import logger + logger.warning(f"[MemoryManager] Embedding provider initialization failed: {e}") + logger.info(f"[MemoryManager] Memory will work with keyword search only (no vector search)") # Initialize memory flush manager workspace_dir = self.config.get_workspace() @@ -135,13 +136,19 @@ class MemoryManager: # Perform vector search (if embedding provider available) vector_results = [] if self.embedding_provider: - query_embedding = self.embedding_provider.embed(query) - vector_results = self.storage.search_vector( - query_embedding=query_embedding, - user_id=user_id, - scopes=scopes, - limit=max_results * 2 # Get more candidates for merging - ) + try: + from common.log import logger + query_embedding = self.embedding_provider.embed(query) + vector_results = self.storage.search_vector( + query_embedding=query_embedding, + user_id=user_id, + scopes=scopes, + limit=max_results * 2 # Get more candidates for merging + ) + logger.info(f"[MemoryManager] Vector search found {len(vector_results)} results for query: {query}") + except Exception as e: + from common.log import logger + logger.warning(f"[MemoryManager] Vector search failed: {e}") # Perform keyword search keyword_results = self.storage.search_keyword( @@ -150,6 +157,8 @@ class MemoryManager: scopes=scopes, limit=max_results * 2 ) + from common.log import logger + logger.info(f"[MemoryManager] Keyword search found {len(keyword_results)} results for query: {query}") # Merge results merged = self._merge_results( @@ -356,30 +365,30 @@ class MemoryManager: def should_flush_memory( self, - current_tokens: int, - context_window: int = 128000, - reserve_tokens: int = 20000, - soft_threshold: int = 4000 + current_tokens: int = 0 ) -> bool: """ Check if memory flush should be triggered + 独立的 flush 触发机制，不依赖模型 context window。 + 使用配置中的阈值: flush_token_threshold 和 flush_turn_threshold + Args: current_tokens: Current session token count - context_window: Model's context window size (default: 128K) - reserve_tokens: Reserve tokens for compaction overhead (default: 20K) - soft_threshold: Trigger N tokens before threshold (default: 4K) Returns: True if memory flush should run """ return self.flush_manager.should_flush( current_tokens=current_tokens, - context_window=context_window, - reserve_tokens=reserve_tokens, - soft_threshold=soft_threshold + token_threshold=self.config.flush_token_threshold, + turn_threshold=self.config.flush_turn_threshold ) + def increment_turn(self): + """增加对话轮数计数（每次用户消息+AI回复算一轮）""" + self.flush_manager.increment_turn() + async def execute_memory_flush( self, agent_executor, diff --git a/agent/memory/summarizer.py b/agent/memory/summarizer.py index 4b102ab..46b2b59 100644 --- a/agent/memory/summarizer.py +++ b/agent/memory/summarizer.py @@ -41,46 +41,42 @@ class MemoryFlushManager: # Tracking self.last_flush_token_count: Optional[int] = None self.last_flush_timestamp: Optional[datetime] = None + self.turn_count: int = 0 # 对话轮数计数器 def should_flush( self, - current_tokens: int, - context_window: int, - reserve_tokens: int = 20000, - soft_threshold: int = 4000 + current_tokens: int = 0, + token_threshold: int = 50000, + turn_threshold: int = 20 ) -> bool: """ Determine if memory flush should be triggered - Similar to clawdbot's shouldRunMemoryFlush logic: - threshold = contextWindow - reserveTokens - softThreshold + 独立的 flush 触发机制，不依赖模型 context window: + - Token 阈值: 达到 50K tokens 时触发 + - 轮次阈值: 达到 20 轮对话时触发 Args: current_tokens: Current session token count - context_window: Model's context window size - reserve_tokens: Reserve tokens for compaction overhead - soft_threshold: Trigger flush N tokens before threshold + token_threshold: Token threshold to trigger flush (default: 50K) + turn_threshold: Turn threshold to trigger flush (default: 20) Returns: True if flush should run """ - if current_tokens <= 0: - return False + # 检查 token 阈值 + if current_tokens > 0 and current_tokens >= token_threshold: + # 避免重复 flush + if self.last_flush_token_count is not None: + if current_tokens <= self.last_flush_token_count + 5000: + return False + return True - threshold = max(0, context_window - reserve_tokens - soft_threshold) - if threshold <= 0: - return False + # 检查轮次阈值 + if self.turn_count >= turn_threshold: + return True - # Check if we've crossed the threshold - if current_tokens < threshold: - return False - - # Avoid duplicate flush in same compaction cycle - if self.last_flush_token_count is not None: - if current_tokens <= self.last_flush_token_count + soft_threshold: - return False - - return True + return False def get_today_memory_file(self, user_id: Optional[str] = None) -> Path: """ @@ -130,7 +126,12 @@ class MemoryFlushManager: f"Pre-compaction memory flush. " f"Store durable memories now (use memory/{today}.md for daily notes; " f"create memory/ if needed). " - f"If nothing to store, reply with NO_REPLY." + f"\n\n" + f"重要提示:\n" + f"- MEMORY.md: 记录最核心、最常用的信息（例如重要规则、偏好、决策、要求等）\n" + f" 如果 MEMORY.md 过长，可以精简或移除不再重要的内容。避免冗长描述，用关键词和要点形式记录\n" + f"- memory/{today}.md: 记录当天发生的事件、关键信息、经验教训、对话过程摘要等，突出重点\n" + f"- 如果没有重要内容需要记录，回复 NO_REPLY\n" ) def create_flush_system_prompt(self) -> str: @@ -142,6 +143,20 @@ class MemoryFlushManager: return ( "Pre-compaction memory flush turn. " "The session is near auto-compaction; capture durable memories to disk. " + "\n\n" + "记忆写入原则:\n" + "1. MEMORY.md 精简原则: 只记录核心信息（<2000 tokens）\n" + " - 记录重要规则、偏好、决策、要求等需要长期记住的关键信息，无需记录过多细节\n" + " - 如果 MEMORY.md 过长，可以根据需要精简或删除过时内容\n" + "\n" + "2. 天级记忆 (memory/YYYY-MM-DD.md):\n" + " - 记录当天的重要事件、关键信息、经验教训、对话过程摘要等，确保核心信息点被完整记录\n" + "\n" + "3. 判断标准:\n" + " - 这个信息未来会经常用到吗？→ MEMORY.md\n" + " - 这是今天的重要事件或决策吗？→ memory/YYYY-MM-DD.md\n" + " - 这是临时性的、不重要的内容吗？→ 不记录\n" + "\n" "You may reply, but usually NO_REPLY is correct." ) @@ -180,6 +195,7 @@ class MemoryFlushManager: # Track flush self.last_flush_token_count = current_tokens self.last_flush_timestamp = datetime.now() + self.turn_count = 0 # 重置轮数计数器 return True @@ -187,6 +203,10 @@ class MemoryFlushManager: print(f"Memory flush failed: {e}") return False + def increment_turn(self): + """增加对话轮数计数""" + self.turn_count += 1 + def get_status(self) -> dict: """Get memory flush status""" return { diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py index 6d8fc80..9134e02 100644 --- a/agent/prompt/builder.py +++ b/agent/prompt/builder.py @@ -179,8 +179,8 @@ def _build_tooling_section(tools: List[Any], language: str) -> List[str]: tool_map = {} tool_descriptions = { "read": "读取文件内容", - "write": "创建或覆盖文件", - "edit": "精确编辑文件内容", + "write": "创建新文件或完全覆盖现有文件（会删除原内容！追加内容请用 edit）", + "edit": "精确编辑文件（追加、修改、删除部分内容）", "ls": "列出目录内容", "grep": "在文件中搜索内容", "find": "按照模式查找文件", @@ -305,17 +305,18 @@ def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], langu "", "在回答关于以前的工作、决定、日期、人物、偏好或待办事项的任何问题之前：", "", - "1. 使用 `memory_search` 在 MEMORY.md 和 memory/*.md 中搜索", - "2. 然后使用 `memory_get` 只拉取需要的行", - "3. 如果搜索后仍然信心不足，告诉用户你已经检查过了", + "1. 不确定信息位置 → 先用 `memory_search` 通过关键词和语义检索相关内容", + "2. 已知文件和大致位置 → 直接用 `memory_get` 读取相应的行", + "3. search 无结果 → 尝试用 `memory_get` 读取最近两天的记忆文件", "", "**记忆文件结构**:", - "- `MEMORY.md`: 长期记忆，包含重要的背景信息", - "- `memory/YYYY-MM-DD.md`: 每日记忆，记录当天的对话和事件", + "- `MEMORY.md`: 长期记忆（已自动加载，无需主动读取）", + "- `memory/YYYY-MM-DD.md`: 每日记忆，记录当天的事件和对话信息", "", "**使用原则**:", - "- 自然使用记忆，就像你本来就知道", - "- 不要主动提起或列举记忆，除非用户明确询问", + "- 自然使用记忆，就像你本来就知道; 不用刻意提起或列举记忆，除非用户提起相关内容", + "- 追加内容到现有记忆文件 → 必须用 `edit` 工具（先 read 读取，再 edit 追加）", + "- 创建新的记忆文件 → 可以用 `write` 工具（已有记忆文件不可直接write，会覆盖删除）", "", ] diff --git a/agent/protocol/agent_stream.py b/agent/protocol/agent_stream.py index 3ad6eb5..8289c15 100644 --- a/agent/protocol/agent_stream.py +++ b/agent/protocol/agent_stream.py @@ -7,9 +7,9 @@ import json import time from typing import List, Dict, Any, Optional, Callable -from common.log import logger from agent.protocol.models import LLMRequest, LLMModel from agent.tools.base_tool import BaseTool, ToolResult +from common.log import logger class AgentStreamExecutor: @@ -164,30 +164,24 @@ class AgentStreamExecutor: self._emit_event("turn_start", {"turn": turn}) # Check if memory flush is needed (before calling LLM) + # 使用独立的 flush 阈值（50K tokens 或 20 轮） if self.agent.memory_manager and hasattr(self.agent, 'last_usage'): usage = self.agent.last_usage if usage and 'input_tokens' in usage: current_tokens = usage.get('input_tokens', 0) - context_window = self.agent._get_model_context_window() - # Use configured reserve_tokens or calculate based on context window - reserve_tokens = self.agent._get_context_reserve_tokens() - # Use smaller soft_threshold to trigger flush earlier (e.g., at 50K tokens) - soft_threshold = 10000 # Trigger 10K tokens before limit if self.agent.memory_manager.should_flush_memory( - current_tokens=current_tokens, - context_window=context_window, - reserve_tokens=reserve_tokens, - soft_threshold=soft_threshold + current_tokens=current_tokens ): self._emit_event("memory_flush_start", { "current_tokens": current_tokens, - "threshold": context_window - reserve_tokens - soft_threshold + "turn_count": self.agent.memory_manager.flush_manager.turn_count }) # TODO: Execute memory flush in background # This would require async support - logger.info(f"Memory flush recommended at {current_tokens} tokens") + logger.info( + f"Memory flush recommended: tokens={current_tokens}, turns={self.agent.memory_manager.flush_manager.turn_count}") # Call LLM assistant_msg, tool_calls = self._call_llm_stream() @@ -321,6 +315,10 @@ class AgentStreamExecutor: logger.info(f"🏁 完成({turn}轮)") self._emit_event("agent_end", {"final_response": final_response}) + # 每轮对话结束后增加计数（用户消息+AI回复=1轮） + if self.agent.memory_manager: + self.agent.memory_manager.increment_turn() + return final_response def _call_llm_stream(self, retry_on_empty=True, retry_count=0, max_retries=3) -> tuple[str, List[Dict]]: @@ -664,9 +662,11 @@ class AgentStreamExecutor: if not self.messages or not self.agent: return - # Get context window and reserve tokens from agent + # Get context window from agent (based on model) context_window = self.agent._get_model_context_window() - reserve_tokens = self.agent._get_context_reserve_tokens() + + # Reserve 10% for response generation + reserve_tokens = int(context_window * 0.1) max_tokens = context_window - reserve_tokens # Estimate current tokens diff --git a/agent/tools/__init__.py b/agent/tools/__init__.py index 76f7e2e..fd3e3b0 100644 --- a/agent/tools/__init__.py +++ b/agent/tools/__init__.py @@ -2,25 +2,17 @@ from agent.tools.base_tool import BaseTool from agent.tools.tool_manager import ToolManager -# Import basic tools (no external dependencies) -from agent.tools.calculator.calculator import Calculator - # Import file operation tools from agent.tools.read.read import Read from agent.tools.write.write import Write from agent.tools.edit.edit import Edit from agent.tools.bash.bash import Bash -from agent.tools.grep.grep import Grep -from agent.tools.find.find import Find from agent.tools.ls.ls import Ls # Import memory tools from agent.tools.memory.memory_search import MemorySearchTool from agent.tools.memory.memory_get import MemoryGetTool -# Import web tools -from agent.tools.web_fetch.web_fetch import WebFetch - # Import tools with optional dependencies def _import_optional_tools(): """Import tools that have optional dependencies""" @@ -80,17 +72,13 @@ BrowserTool = _import_browser_tool() __all__ = [ 'BaseTool', 'ToolManager', - 'Calculator', 'Read', 'Write', 'Edit', 'Bash', - 'Grep', - 'Find', 'Ls', 'MemorySearchTool', 'MemoryGetTool', - 'WebFetch', # Optional tools (may be None if dependencies not available) 'GoogleSearch', 'FileSave', diff --git a/agent/tools/calculator/calculator.py b/agent/tools/calculator/calculator.py deleted file mode 100644 index 092343d..0000000 --- a/agent/tools/calculator/calculator.py +++ /dev/null @@ -1,58 +0,0 @@ -import math - -from agent.tools.base_tool import BaseTool, ToolResult - - -class Calculator(BaseTool): - name: str = "calculator" - description: str = "A tool to perform basic mathematical calculations." - params: dict = { - "type": "object", - "properties": { - "expression": { - "type": "string", - "description": "The mathematical expression to evaluate (e.g., '2 + 2', '5 * 3', 'sqrt(16)'). " - "Ensure your input is a valid Python expression, it will be evaluated directly." - } - }, - "required": ["expression"] - } - config: dict = {} - - def execute(self, args: dict) -> ToolResult: - try: - # Get the expression - expression = args["expression"] - - # Create a safe local environment containing only basic math functions - safe_locals = { - "abs": abs, - "round": round, - "max": max, - "min": min, - "pow": pow, - "sqrt": math.sqrt, - "sin": math.sin, - "cos": math.cos, - "tan": math.tan, - "pi": math.pi, - "e": math.e, - "log": math.log, - "log10": math.log10, - "exp": math.exp, - "floor": math.floor, - "ceil": math.ceil - } - - # Safely evaluate the expression - result = eval(expression, {"__builtins__": {}}, safe_locals) - - return ToolResult.success({ - "result": result, - "expression": expression - }) - except Exception as e: - return ToolResult.success({ - "error": str(e), - "expression": args.get("expression", "") - }) diff --git a/agent/tools/edit/edit.py b/agent/tools/edit/edit.py index 566309b..b07c8f1 100644 --- a/agent/tools/edit/edit.py +++ b/agent/tools/edit/edit.py @@ -33,7 +33,7 @@ class Edit(BaseTool): }, "oldText": { "type": "string", - "description": "Exact text to find and replace (must match exactly)" + "description": "Exact text to find and replace (must match exactly, cannot be empty). To append to end of file, include the last few lines as oldText." }, "newText": { "type": "string", diff --git a/agent/tools/find/__init__.py b/agent/tools/find/__init__.py deleted file mode 100644 index f2af14f..0000000 --- a/agent/tools/find/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .find import Find - -__all__ = ['Find'] diff --git a/agent/tools/find/find.py b/agent/tools/find/find.py deleted file mode 100644 index 7a2c4a1..0000000 --- a/agent/tools/find/find.py +++ /dev/null @@ -1,177 +0,0 @@ -""" -Find tool - Search for files by glob pattern -""" - -import os -import glob as glob_module -from typing import Dict, Any, List - -from agent.tools.base_tool import BaseTool, ToolResult -from agent.tools.utils.truncate import truncate_head, format_size, DEFAULT_MAX_BYTES - - -DEFAULT_LIMIT = 1000 - - -class Find(BaseTool): - """Tool for finding files by pattern""" - - name: str = "find" - description: str = f"Search for files by glob pattern. Returns matching file paths relative to the search directory. Respects .gitignore. Output is truncated to {DEFAULT_LIMIT} results or {DEFAULT_MAX_BYTES // 1024}KB (whichever is hit first)." - - params: dict = { - "type": "object", - "properties": { - "pattern": { - "type": "string", - "description": "Glob pattern to match files, e.g. '*.ts', '**/*.json', or 'src/**/*.spec.ts'" - }, - "path": { - "type": "string", - "description": "Directory to search in (default: current directory)" - }, - "limit": { - "type": "integer", - "description": f"Maximum number of results (default: {DEFAULT_LIMIT})" - } - }, - "required": ["pattern"] - } - - def __init__(self, config: dict = None): - self.config = config or {} - self.cwd = self.config.get("cwd", os.getcwd()) - - def execute(self, args: Dict[str, Any]) -> ToolResult: - """ - Execute file search - - :param args: Search parameters - :return: Search results or error - """ - pattern = args.get("pattern", "").strip() - search_path = args.get("path", ".").strip() - limit = args.get("limit", DEFAULT_LIMIT) - - if not pattern: - return ToolResult.fail("Error: pattern parameter is required") - - # Resolve search path - absolute_path = self._resolve_path(search_path) - - if not os.path.exists(absolute_path): - return ToolResult.fail(f"Error: Path not found: {search_path}") - - if not os.path.isdir(absolute_path): - return ToolResult.fail(f"Error: Not a directory: {search_path}") - - try: - # Load .gitignore patterns - ignore_patterns = self._load_gitignore(absolute_path) - - # Search for files - results = [] - search_pattern = os.path.join(absolute_path, pattern) - - # Use glob with recursive support - for file_path in glob_module.glob(search_pattern, recursive=True): - # Skip if matches ignore patterns - if self._should_ignore(file_path, absolute_path, ignore_patterns): - continue - - # Get relative path - relative_path = os.path.relpath(file_path, absolute_path) - - # Add trailing slash for directories - if os.path.isdir(file_path): - relative_path += '/' - - results.append(relative_path) - - if len(results) >= limit: - break - - if not results: - return ToolResult.success({"message": "No files found matching pattern", "files": []}) - - # Sort results - results.sort() - - # Format output - raw_output = '\n'.join(results) - truncation = truncate_head(raw_output, max_lines=999999) # Only limit by bytes - - output = truncation.content - details = {} - notices = [] - - result_limit_reached = len(results) >= limit - if result_limit_reached: - notices.append(f"{limit} results limit reached. Use limit={limit * 2} for more, or refine pattern") - details["result_limit_reached"] = limit - - if truncation.truncated: - notices.append(f"{format_size(DEFAULT_MAX_BYTES)} limit reached") - details["truncation"] = truncation.to_dict() - - if notices: - output += f"\n\n[{'. '.join(notices)}]" - - return ToolResult.success({ - "output": output, - "file_count": len(results), - "details": details if details else None - }) - - except Exception as e: - return ToolResult.fail(f"Error executing find: {str(e)}") - - def _resolve_path(self, path: str) -> str: - """Resolve path to absolute path""" - # Expand ~ to user home directory - path = os.path.expanduser(path) - if os.path.isabs(path): - return path - return os.path.abspath(os.path.join(self.cwd, path)) - - def _load_gitignore(self, directory: str) -> List[str]: - """Load .gitignore patterns from directory""" - patterns = [] - gitignore_path = os.path.join(directory, '.gitignore') - - if os.path.exists(gitignore_path): - try: - with open(gitignore_path, 'r', encoding='utf-8') as f: - for line in f: - line = line.strip() - if line and not line.startswith('#'): - patterns.append(line) - except: - pass - - # Add common ignore patterns - patterns.extend([ - '.git', - '__pycache__', - '*.pyc', - 'node_modules', - '.DS_Store' - ]) - - return patterns - - def _should_ignore(self, file_path: str, base_path: str, patterns: List[str]) -> bool: - """Check if file should be ignored based on patterns""" - relative_path = os.path.relpath(file_path, base_path) - - for pattern in patterns: - # Simple pattern matching - if pattern in relative_path: - return True - - # Check if it's a directory pattern - if pattern.endswith('/'): - if relative_path.startswith(pattern.rstrip('/')): - return True - - return False diff --git a/agent/tools/grep/__init__.py b/agent/tools/grep/__init__.py deleted file mode 100644 index e4d57b0..0000000 --- a/agent/tools/grep/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .grep import Grep - -__all__ = ['Grep'] diff --git a/agent/tools/grep/grep.py b/agent/tools/grep/grep.py deleted file mode 100644 index 1e7d95e..0000000 --- a/agent/tools/grep/grep.py +++ /dev/null @@ -1,248 +0,0 @@ -""" -Grep tool - Search file contents for patterns -Uses ripgrep (rg) for fast searching -""" - -import os -import re -import subprocess -import json -from typing import Dict, Any, List, Optional - -from agent.tools.base_tool import BaseTool, ToolResult -from agent.tools.utils.truncate import ( - truncate_head, truncate_line, format_size, - DEFAULT_MAX_BYTES, GREP_MAX_LINE_LENGTH -) - - -DEFAULT_LIMIT = 100 - - -class Grep(BaseTool): - """Tool for searching file contents""" - - name: str = "grep" - description: str = f"Search file contents for a pattern. Returns matching lines with file paths and line numbers. Respects .gitignore. Output is truncated to {DEFAULT_LIMIT} matches or {DEFAULT_MAX_BYTES // 1024}KB (whichever is hit first). Long lines are truncated to {GREP_MAX_LINE_LENGTH} chars." - - params: dict = { - "type": "object", - "properties": { - "pattern": { - "type": "string", - "description": "Search pattern (regex or literal string)" - }, - "path": { - "type": "string", - "description": "Directory or file to search (default: current directory)" - }, - "glob": { - "type": "string", - "description": "Filter files by glob pattern, e.g. '*.ts' or '**/*.spec.ts'" - }, - "ignoreCase": { - "type": "boolean", - "description": "Case-insensitive search (default: false)" - }, - "literal": { - "type": "boolean", - "description": "Treat pattern as literal string instead of regex (default: false)" - }, - "context": { - "type": "integer", - "description": "Number of lines to show before and after each match (default: 0)" - }, - "limit": { - "type": "integer", - "description": f"Maximum number of matches to return (default: {DEFAULT_LIMIT})" - } - }, - "required": ["pattern"] - } - - def __init__(self, config: dict = None): - self.config = config or {} - self.cwd = self.config.get("cwd", os.getcwd()) - self.rg_path = self._find_ripgrep() - - def _find_ripgrep(self) -> Optional[str]: - """Find ripgrep executable""" - try: - result = subprocess.run(['which', 'rg'], capture_output=True, text=True) - if result.returncode == 0: - return result.stdout.strip() - except: - pass - return None - - def execute(self, args: Dict[str, Any]) -> ToolResult: - """ - Execute grep search - - :param args: Search parameters - :return: Search results or error - """ - if not self.rg_path: - return ToolResult.fail("Error: ripgrep (rg) is not installed. Please install it first.") - - pattern = args.get("pattern", "").strip() - search_path = args.get("path", ".").strip() - glob = args.get("glob") - ignore_case = args.get("ignoreCase", False) - literal = args.get("literal", False) - context = args.get("context", 0) - limit = args.get("limit", DEFAULT_LIMIT) - - if not pattern: - return ToolResult.fail("Error: pattern parameter is required") - - # Resolve search path - absolute_path = self._resolve_path(search_path) - - if not os.path.exists(absolute_path): - return ToolResult.fail(f"Error: Path not found: {search_path}") - - # Build ripgrep command - cmd = [ - self.rg_path, - '--json', - '--line-number', - '--color=never', - '--hidden' - ] - - if ignore_case: - cmd.append('--ignore-case') - - if literal: - cmd.append('--fixed-strings') - - if glob: - cmd.extend(['--glob', glob]) - - cmd.extend([pattern, absolute_path]) - - try: - # Execute ripgrep - result = subprocess.run( - cmd, - cwd=self.cwd, - capture_output=True, - text=True, - timeout=30 - ) - - # Parse JSON output - matches = [] - match_count = 0 - - for line in result.stdout.splitlines(): - if not line.strip(): - continue - - try: - event = json.loads(line) - if event.get('type') == 'match': - data = event.get('data', {}) - file_path = data.get('path', {}).get('text') - line_number = data.get('line_number') - - if file_path and line_number: - matches.append({ - 'file': file_path, - 'line': line_number - }) - match_count += 1 - - if match_count >= limit: - break - except json.JSONDecodeError: - continue - - if match_count == 0: - return ToolResult.success({"message": "No matches found", "matches": []}) - - # Format output with context - output_lines = [] - lines_truncated = False - is_directory = os.path.isdir(absolute_path) - - for match in matches: - file_path = match['file'] - line_number = match['line'] - - # Format file path - if is_directory: - relative_path = os.path.relpath(file_path, absolute_path) - else: - relative_path = os.path.basename(file_path) - - # Read file and get context - try: - with open(file_path, 'r', encoding='utf-8') as f: - file_lines = f.read().split('\n') - - # Calculate context range - start = max(0, line_number - 1 - context) if context > 0 else line_number - 1 - end = min(len(file_lines), line_number + context) if context > 0 else line_number - - # Format lines with context - for i in range(start, end): - line_text = file_lines[i].replace('\r', '') - - # Truncate long lines - truncated_text, was_truncated = truncate_line(line_text) - if was_truncated: - lines_truncated = True - - # Format output - current_line = i + 1 - if current_line == line_number: - output_lines.append(f"{relative_path}:{current_line}: {truncated_text}") - else: - output_lines.append(f"{relative_path}-{current_line}- {truncated_text}") - - except Exception: - output_lines.append(f"{relative_path}:{line_number}: (unable to read file)") - - # Apply byte truncation - raw_output = '\n'.join(output_lines) - truncation = truncate_head(raw_output, max_lines=999999) # Only limit by bytes - - output = truncation.content - details = {} - notices = [] - - if match_count >= limit: - notices.append(f"{limit} matches limit reached. Use limit={limit * 2} for more, or refine pattern") - details["match_limit_reached"] = limit - - if truncation.truncated: - notices.append(f"{format_size(DEFAULT_MAX_BYTES)} limit reached") - details["truncation"] = truncation.to_dict() - - if lines_truncated: - notices.append(f"Some lines truncated to {GREP_MAX_LINE_LENGTH} chars. Use read tool to see full lines") - details["lines_truncated"] = True - - if notices: - output += f"\n\n[{'. '.join(notices)}]" - - return ToolResult.success({ - "output": output, - "match_count": match_count, - "details": details if details else None - }) - - except subprocess.TimeoutExpired: - return ToolResult.fail("Error: Search timed out after 30 seconds") - except Exception as e: - return ToolResult.fail(f"Error executing grep: {str(e)}") - - def _resolve_path(self, path: str) -> str: - """Resolve path to absolute path""" - # Expand ~ to user home directory - path = os.path.expanduser(path) - if os.path.isabs(path): - return path - return os.path.abspath(os.path.join(self.cwd, path)) diff --git a/agent/tools/memory/memory_get.py b/agent/tools/memory/memory_get.py index 50ca639..bf5b708 100644 --- a/agent/tools/memory/memory_get.py +++ b/agent/tools/memory/memory_get.py @@ -4,8 +4,6 @@ Memory get tool Allows agents to read specific sections from memory files """ -from typing import Dict, Any -from pathlib import Path from agent.tools.base_tool import BaseTool @@ -22,7 +20,7 @@ class MemoryGetTool(BaseTool): "properties": { "path": { "type": "string", - "description": "Relative path to the memory file (e.g., 'MEMORY.md', 'memory/2026-01-01.md')" + "description": "Relative path to the memory file (e.g. 'memory/2026-01-01.md')" }, "start_line": { "type": "integer", @@ -70,7 +68,8 @@ class MemoryGetTool(BaseTool): workspace_dir = self.memory_manager.config.get_workspace() # Auto-prepend memory/ if not present and not absolute path - if not path.startswith('memory/') and not path.startswith('/'): + # Exception: MEMORY.md is in the root directory + if not path.startswith('memory/') and not path.startswith('/') and path != 'MEMORY.md': path = f'memory/{path}' file_path = workspace_dir / path diff --git a/agent/tools/web_fetch/README.md b/agent/tools/web_fetch/README.md deleted file mode 100644 index 6fc192f..0000000 --- a/agent/tools/web_fetch/README.md +++ /dev/null @@ -1,212 +0,0 @@ -# WebFetch Tool - -免费的网页抓取工具，无需 API Key，可直接抓取网页内容并提取可读文本。 - -## 功能特性 - -- ✅ **完全免费** - 无需任何 API Key -- 🌐 **智能提取** - 自动提取网页主要内容 -- 📝 **格式转换** - 支持 HTML → Markdown/Text -- 🚀 **高性能** - 内置请求重试和超时控制 -- 🎯 **智能降级** - 优先使用 Readability，可降级到基础提取 - -## 安装依赖 - -### 基础功能（必需） -```bash -pip install requests -``` - -### 增强功能（推荐） -```bash -# 安装 readability-lxml 以获得更好的内容提取效果 -pip install readability-lxml - -# 安装 html2text 以获得更好的 Markdown 转换 -pip install html2text -``` - -## 使用方法 - -### 1. 在代码中使用 - -```python -from agent.tools.web_fetch import WebFetch - -# 创建工具实例 -tool = WebFetch() - -# 抓取网页（默认返回 Markdown 格式） -result = tool.execute({ - "url": "https://example.com" -}) - -# 抓取并转换为纯文本 -result = tool.execute({ - "url": "https://example.com", - "extract_mode": "text", - "max_chars": 5000 -}) - -if result.status == "success": - data = result.result - print(f"标题: {data['title']}") - print(f"内容: {data['text']}") -``` - -### 2. 在 Agent 中使用 - -工具会自动加载到 Agent 的工具列表中： - -```python -from agent.tools import WebFetch - -tools = [ - WebFetch(), - # ... 其他工具 -] - -agent = create_agent(tools=tools) -``` - -### 3. 通过 Skills 使用 - -创建一个 skill 文件 `skills/web-fetch/SKILL.md`： - -```markdown ---- -name: web-fetch -emoji: 🌐 -always: true ---- - -# 网页内容获取 - -使用 web_fetch 工具获取网页内容。 - -## 使用场景 - -- 需要读取某个网页的内容 -- 需要提取文章正文 -- 需要获取网页信息 - -## 示例 - - -用户: 帮我看看 https://example.com 这个网页讲了什么 -助手: - https://example.com - markdown - - -``` - -## 参数说明 - -| 参数 | 类型 | 必需 | 默认值 | 说明 | -|------|------|------|--------|------| -| `url` | string | ✅ | - | 要抓取的 URL（http/https） | -| `extract_mode` | string | ❌ | `markdown` | 提取模式：`markdown` 或 `text` | -| `max_chars` | integer | ❌ | `50000` | 最大返回字符数（最小 100） | - -## 返回结果 - -```python -{ - "url": "https://example.com", # 最终 URL（处理重定向后） - "status": 200, # HTTP 状态码 - "content_type": "text/html", # 内容类型 - "title": "Example Domain", # 页面标题 - "extractor": "readability", # 提取器：readability/basic/raw - "extract_mode": "markdown", # 提取模式 - "text": "# Example Domain\n\n...", # 提取的文本内容 - "length": 1234, # 文本长度 - "truncated": false, # 是否被截断 - "warning": "..." # 警告信息（如果有） -} -``` - -## 与其他搜索工具的对比 - -| 工具 | 需要 API Key | 功能 | 成本 | -|------|-------------|------|------| -| `web_fetch` | ❌ 不需要 | 抓取指定 URL 的内容 | 免费 | -| `web_search` (Brave) | ✅ 需要 | 搜索引擎查询 | 有免费额度 | -| `web_search` (Perplexity) | ✅ 需要 | AI 搜索 + 引用 | 付费 | -| `browser` | ❌ 不需要 | 完整浏览器自动化 | 免费但资源占用大 | -| `google_search` | ✅ 需要 | Google 搜索 API | 付费 | - -## 技术细节 - -### 内容提取策略 - -1. **Readability 模式**（推荐） - - 使用 Mozilla 的 Readability 算法 - - 自动识别文章主体内容 - - 过滤广告、导航栏等噪音 - -2. **Basic 模式**（降级） - - 简单的 HTML 标签清理 - - 正则表达式提取文本 - - 适用于简单页面 - -3. **Raw 模式** - - 用于非 HTML 内容 - - 直接返回原始内容 - -### 错误处理 - -工具会自动处理以下情况： -- ✅ HTTP 重定向（最多 3 次） -- ✅ 请求超时（默认 30 秒） -- ✅ 网络错误自动重试 -- ✅ 内容提取失败降级 - -## 测试 - -运行测试脚本： - -```bash -cd agent/tools/web_fetch -python test_web_fetch.py -``` - -## 配置选项 - -在创建工具时可以传入配置： - -```python -tool = WebFetch(config={ - "timeout": 30, # 请求超时时间（秒） - "max_redirects": 3, # 最大重定向次数 - "user_agent": "..." # 自定义 User-Agent -}) -``` - -## 常见问题 - -### Q: 为什么推荐安装 readability-lxml？ - -A: readability-lxml 提供更好的内容提取质量，能够： -- 自动识别文章主体 -- 过滤广告和导航栏 -- 保留文章结构 - -没有它也能工作，但提取质量会下降。 - -### Q: 与 clawdbot 的 web_fetch 有什么区别？ - -A: 本实现参考了 clawdbot 的设计，主要区别： -- Python 实现（clawdbot 是 TypeScript） -- 简化了一些高级特性（如 Firecrawl 集成） -- 保留了核心的免费功能 -- 更容易集成到现有项目 - -### Q: 可以抓取需要登录的页面吗？ - -A: 当前版本不支持。如需抓取需要登录的页面，请使用 `browser` 工具。 - -## 参考 - -- [Mozilla Readability](https://github.com/mozilla/readability) -- [Clawdbot Web Tools](https://github.com/moltbot/moltbot) diff --git a/agent/tools/web_fetch/__init__.py b/agent/tools/web_fetch/__init__.py deleted file mode 100644 index 545f87c..0000000 --- a/agent/tools/web_fetch/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .web_fetch import WebFetch - -__all__ = ['WebFetch'] diff --git a/agent/tools/web_fetch/install_deps.sh b/agent/tools/web_fetch/install_deps.sh deleted file mode 100644 index 3c2a553..0000000 --- a/agent/tools/web_fetch/install_deps.sh +++ /dev/null @@ -1,47 +0,0 @@ -#!/bin/bash - -# WebFetch 工具依赖安装脚本 - -echo "==================================" -echo "WebFetch 工具依赖安装" -echo "==================================" -echo "" - -# 检查 Python 版本 -python_version=$(python3 --version 2>&1 | awk '{print $2}') -echo "✓ Python 版本: $python_version" -echo "" - -# 安装基础依赖 -echo "📦 安装基础依赖..." -python3 -m pip install requests - -# 检查是否成功 -if [ $? -eq 0 ]; then - echo "✅ requests 安装成功" -else - echo "❌ requests 安装失败" - exit 1 -fi - -echo "" - -# 安装推荐依赖 -echo "📦 安装推荐依赖（提升内容提取质量）..." -python3 -m pip install readability-lxml html2text - -# 检查是否成功 -if [ $? -eq 0 ]; then - echo "✅ readability-lxml 和 html2text 安装成功" -else - echo "⚠️ 推荐依赖安装失败，但不影响基础功能" -fi - -echo "" -echo "==================================" -echo "安装完成！" -echo "==================================" -echo "" -echo "运行测试：" -echo " python3 agent/tools/web_fetch/test_web_fetch.py" -echo "" diff --git a/agent/tools/web_fetch/web_fetch.py b/agent/tools/web_fetch/web_fetch.py deleted file mode 100644 index b87b95e..0000000 --- a/agent/tools/web_fetch/web_fetch.py +++ /dev/null @@ -1,365 +0,0 @@ -""" -Web Fetch tool - Fetch and extract readable content from URLs -Supports HTML to Markdown/Text conversion using Mozilla's Readability -""" - -import os -import re -from typing import Dict, Any, Optional -from urllib.parse import urlparse -import requests -from requests.adapters import HTTPAdapter -from urllib3.util.retry import Retry - -from agent.tools.base_tool import BaseTool, ToolResult -from common.log import logger - - -class WebFetch(BaseTool): - """Tool for fetching and extracting readable content from web pages""" - - name: str = "web_fetch" - description: str = "Fetch and extract readable content from a URL (HTML → markdown/text). Use for lightweight page access without browser automation. Returns title, content, and metadata." - - params: dict = { - "type": "object", - "properties": { - "url": { - "type": "string", - "description": "HTTP or HTTPS URL to fetch" - }, - "extract_mode": { - "type": "string", - "description": "Extraction mode: 'markdown' (default) or 'text'", - "enum": ["markdown", "text"], - "default": "markdown" - }, - "max_chars": { - "type": "integer", - "description": "Maximum characters to return (default: 50000)", - "minimum": 100, - "default": 50000 - } - }, - "required": ["url"] - } - - def __init__(self, config: dict = None): - self.config = config or {} - self.timeout = self.config.get("timeout", 20) - self.max_redirects = self.config.get("max_redirects", 3) - self.user_agent = self.config.get( - "user_agent", - "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36" - ) - - # Setup session with retry strategy - self.session = self._create_session() - - # Check if readability-lxml is available - self.readability_available = self._check_readability() - - def _create_session(self) -> requests.Session: - """Create a requests session with retry strategy""" - session = requests.Session() - - # Retry strategy - handles failed requests, not redirects - retry_strategy = Retry( - total=3, - backoff_factor=1, - status_forcelist=[429, 500, 502, 503, 504], - allowed_methods=["GET", "HEAD"] - ) - - # HTTPAdapter handles retries; requests handles redirects via allow_redirects - adapter = HTTPAdapter(max_retries=retry_strategy) - session.mount("http://", adapter) - session.mount("https://", adapter) - - # Set max redirects on session - session.max_redirects = self.max_redirects - - return session - - def _check_readability(self) -> bool: - """Check if readability-lxml is available""" - try: - from readability import Document - return True - except ImportError: - logger.warning( - "readability-lxml not installed. Install with: pip install readability-lxml\n" - "Falling back to basic HTML extraction." - ) - return False - - def execute(self, args: Dict[str, Any]) -> ToolResult: - """ - Execute web fetch operation - - :param args: Contains url, extract_mode, and max_chars parameters - :return: Extracted content or error message - """ - url = args.get("url", "").strip() - extract_mode = args.get("extract_mode", "markdown").lower() - max_chars = args.get("max_chars", 50000) - - if not url: - return ToolResult.fail("Error: url parameter is required") - - # Validate URL - if not self._is_valid_url(url): - return ToolResult.fail(f"Error: Invalid URL (must be http or https): {url}") - - # Validate extract_mode - if extract_mode not in ["markdown", "text"]: - extract_mode = "markdown" - - # Validate max_chars - if not isinstance(max_chars, int) or max_chars < 100: - max_chars = 50000 - - try: - # Fetch the URL - response = self._fetch_url(url) - - # Extract content - result = self._extract_content( - html=response.text, - url=response.url, - status_code=response.status_code, - content_type=response.headers.get("content-type", ""), - extract_mode=extract_mode, - max_chars=max_chars - ) - - return ToolResult.success(result) - - except requests.exceptions.Timeout: - return ToolResult.fail(f"Error: Request timeout after {self.timeout} seconds") - except requests.exceptions.TooManyRedirects: - return ToolResult.fail(f"Error: Too many redirects (limit: {self.max_redirects})") - except requests.exceptions.RequestException as e: - return ToolResult.fail(f"Error fetching URL: {str(e)}") - except Exception as e: - logger.error(f"Web fetch error: {e}", exc_info=True) - return ToolResult.fail(f"Error: {str(e)}") - - def _is_valid_url(self, url: str) -> bool: - """Validate URL format""" - try: - result = urlparse(url) - return result.scheme in ["http", "https"] and bool(result.netloc) - except Exception: - return False - - def _fetch_url(self, url: str) -> requests.Response: - """ - Fetch URL with proper headers and error handling - - :param url: URL to fetch - :return: Response object - """ - headers = { - "User-Agent": self.user_agent, - "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", - "Accept-Language": "en-US,en;q=0.9,zh-CN,zh;q=0.8", - "Accept-Encoding": "gzip, deflate", - "Connection": "keep-alive", - } - - # Note: requests library handles redirects automatically - # The max_redirects is set in the session's adapter (HTTPAdapter) - response = self.session.get( - url, - headers=headers, - timeout=self.timeout, - allow_redirects=True - ) - - response.raise_for_status() - return response - - def _extract_content( - self, - html: str, - url: str, - status_code: int, - content_type: str, - extract_mode: str, - max_chars: int - ) -> Dict[str, Any]: - """ - Extract readable content from HTML - - :param html: HTML content - :param url: Original URL - :param status_code: HTTP status code - :param content_type: Content type header - :param extract_mode: 'markdown' or 'text' - :param max_chars: Maximum characters to return - :return: Extracted content and metadata - """ - # Check content type - if "text/html" not in content_type.lower(): - # Non-HTML content - text = html[:max_chars] - truncated = len(html) > max_chars - - return { - "url": url, - "status": status_code, - "content_type": content_type, - "extractor": "raw", - "text": text, - "length": len(text), - "truncated": truncated, - "message": f"Non-HTML content (type: {content_type})" - } - - # Extract readable content from HTML - if self.readability_available: - return self._extract_with_readability( - html, url, status_code, content_type, extract_mode, max_chars - ) - else: - return self._extract_basic( - html, url, status_code, content_type, extract_mode, max_chars - ) - - def _extract_with_readability( - self, - html: str, - url: str, - status_code: int, - content_type: str, - extract_mode: str, - max_chars: int - ) -> Dict[str, Any]: - """Extract content using Mozilla's Readability""" - try: - from readability import Document - - # Parse with Readability - doc = Document(html) - title = doc.title() - content_html = doc.summary() - - # Convert to markdown or text - if extract_mode == "markdown": - text = self._html_to_markdown(content_html) - else: - text = self._html_to_text(content_html) - - # Truncate if needed - truncated = len(text) > max_chars - if truncated: - text = text[:max_chars] - - return { - "url": url, - "status": status_code, - "content_type": content_type, - "title": title, - "extractor": "readability", - "extract_mode": extract_mode, - "text": text, - "length": len(text), - "truncated": truncated - } - - except Exception as e: - logger.warning(f"Readability extraction failed: {e}") - # Fallback to basic extraction - return self._extract_basic( - html, url, status_code, content_type, extract_mode, max_chars - ) - - def _extract_basic( - self, - html: str, - url: str, - status_code: int, - content_type: str, - extract_mode: str, - max_chars: int - ) -> Dict[str, Any]: - """Basic HTML extraction without Readability""" - # Extract title - title_match = re.search(r']*>(.*?)', html, re.IGNORECASE | re.DOTALL) - title = title_match.group(1).strip() if title_match else "Untitled" - - # Remove script and style tags - text = re.sub(r']*>.*?', '', html, flags=re.DOTALL | re.IGNORECASE) - text = re.sub(r']*>.*?', '', text, flags=re.DOTALL | re.IGNORECASE) - - # Remove HTML tags - text = re.sub(r'<[^>]+>', ' ', text) - - # Clean up whitespace - text = re.sub(r'\s+', ' ', text) - text = text.strip() - - # Truncate if needed - truncated = len(text) > max_chars - if truncated: - text = text[:max_chars] - - return { - "url": url, - "status": status_code, - "content_type": content_type, - "title": title, - "extractor": "basic", - "extract_mode": extract_mode, - "text": text, - "length": len(text), - "truncated": truncated, - "warning": "Using basic extraction. Install readability-lxml for better results." - } - - def _html_to_markdown(self, html: str) -> str: - """Convert HTML to Markdown (basic implementation)""" - try: - # Try to use html2text if available - import html2text - h = html2text.HTML2Text() - h.ignore_links = False - h.ignore_images = False - h.body_width = 0 # Don't wrap lines - return h.handle(html) - except ImportError: - # Fallback to basic conversion - return self._html_to_text(html) - - def _html_to_text(self, html: str) -> str: - """Convert HTML to plain text""" - # Remove script and style tags - text = re.sub(r']*>.*?', '', html, flags=re.DOTALL | re.IGNORECASE) - text = re.sub(r']*>.*?', '', text, flags=re.DOTALL | re.IGNORECASE) - - # Convert common tags to text equivalents - text = re.sub(r'', '\n', text, flags=re.IGNORECASE) - text = re.sub(r']*>', '\n\n', text, flags=re.IGNORECASE) - text = re.sub(r'

', '', text, flags=re.IGNORECASE) - text = re.sub(r']*>', '\n\n', text, flags=re.IGNORECASE) - text = re.sub(r'', '\n', text, flags=re.IGNORECASE) - - # Remove all other HTML tags - text = re.sub(r'<[^>]+>', '', text) - - # Decode HTML entities - import html - text = html.unescape(text) - - # Clean up whitespace - text = re.sub(r'\n\s*\n\s*\n+', '\n\n', text) - text = re.sub(r' +', ' ', text) - text = text.strip() - - return text - - def close(self): - """Close the session""" - if hasattr(self, 'session'): - self.session.close() diff --git a/bridge/agent_bridge.py b/bridge/agent_bridge.py index 9054a64..56f9a75 100644 --- a/bridge/agent_bridge.py +++ b/bridge/agent_bridge.py @@ -283,14 +283,53 @@ class AgentBridge: from agent.memory import MemoryManager, MemoryConfig from agent.tools import MemorySearchTool, MemoryGetTool - memory_config = MemoryConfig( - workspace_root=workspace_root, - embedding_provider="local", # Use local embedding (no API key needed) - embedding_model="all-MiniLM-L6-v2" - ) + # 从 config.json 读取 OpenAI 配置 + openai_api_key = conf().get("open_ai_api_key", "") + openai_api_base = conf().get("open_ai_api_base", "") - # Create memory manager with the config - memory_manager = MemoryManager(memory_config) + # 尝试初始化 OpenAI embedding provider + embedding_provider = None + if openai_api_key: + try: + from agent.memory import create_embedding_provider + embedding_provider = create_embedding_provider( + provider="openai", + model="text-embedding-3-small", + api_key=openai_api_key, + api_base=openai_api_base or "https://api.openai.com/v1" + ) + logger.info(f"[AgentBridge] OpenAI embedding initialized") + except Exception as embed_error: + logger.warning(f"[AgentBridge] OpenAI embedding failed: {embed_error}") + logger.info(f"[AgentBridge] Using keyword-only search") + else: + logger.info(f"[AgentBridge] No OpenAI API key, using keyword-only search") + + # 创建 memory config + memory_config = MemoryConfig(workspace_root=workspace_root) + + # 创建 memory manager + memory_manager = MemoryManager(memory_config, embedding_provider=embedding_provider) + + # 初始化时执行一次 sync，确保数据库有数据 + import asyncio + try: + # 尝试在当前事件循环中执行 + loop = asyncio.get_event_loop() + if loop.is_running(): + # 如果事件循环正在运行，创建任务 + asyncio.create_task(memory_manager.sync()) + logger.info("[AgentBridge] Memory sync scheduled") + else: + # 如果没有运行的循环，直接执行 + loop.run_until_complete(memory_manager.sync()) + logger.info("[AgentBridge] Memory synced successfully") + except RuntimeError: + # 没有事件循环，创建新的 + asyncio.run(memory_manager.sync()) + logger.info("[AgentBridge] Memory synced successfully") + except Exception as e: + logger.warning(f"[AgentBridge] Memory sync failed: {e}") # Create memory tools memory_tools = [ @@ -420,23 +459,65 @@ class AgentBridge: memory_tools = [] try: - from agent.memory import MemoryManager, MemoryConfig + from agent.memory import MemoryManager, MemoryConfig, create_embedding_provider from agent.tools import MemorySearchTool, MemoryGetTool - memory_config = MemoryConfig( - workspace_root=workspace_root, - embedding_provider="local", - embedding_model="all-MiniLM-L6-v2" - ) + # 从 config.json 读取 OpenAI 配置 + openai_api_key = conf().get("open_ai_api_key", "") + openai_api_base = conf().get("open_ai_api_base", "") + + # 尝试初始化 OpenAI embedding provider + embedding_provider = None + if openai_api_key: + try: + embedding_provider = create_embedding_provider( + provider="openai", + model="text-embedding-3-small", + api_key=openai_api_key, + api_base=openai_api_base or "https://api.openai.com/v1" + ) + logger.info(f"[AgentBridge] OpenAI embedding initialized for session {session_id}") + except Exception as embed_error: + logger.warning(f"[AgentBridge] OpenAI embedding failed for session {session_id}: {embed_error}") + logger.info(f"[AgentBridge] Using keyword-only search for session {session_id}") + else: + logger.info(f"[AgentBridge] No OpenAI API key, using keyword-only search for session {session_id}") + + # 创建 memory config + memory_config = MemoryConfig(workspace_root=workspace_root) + + # 创建 memory manager + memory_manager = MemoryManager(memory_config, embedding_provider=embedding_provider) + + # 初始化时执行一次 sync，确保数据库有数据 + import asyncio + try: + # 尝试在当前事件循环中执行 + loop = asyncio.get_event_loop() + if loop.is_running(): + # 如果事件循环正在运行，创建任务 + asyncio.create_task(memory_manager.sync()) + logger.info(f"[AgentBridge] Memory sync scheduled for session {session_id}") + else: + # 如果没有运行的循环，直接执行 + loop.run_until_complete(memory_manager.sync()) + logger.info(f"[AgentBridge] Memory synced successfully for session {session_id}") + except RuntimeError: + # 没有事件循环，创建新的 + asyncio.run(memory_manager.sync()) + logger.info(f"[AgentBridge] Memory synced successfully for session {session_id}") + except Exception as sync_error: + logger.warning(f"[AgentBridge] Memory sync failed for session {session_id}: {sync_error}") - memory_manager = MemoryManager(memory_config) memory_tools = [ MemorySearchTool(memory_manager), MemoryGetTool(memory_manager) ] except Exception as e: - logger.debug(f"[AgentBridge] Memory system not available for session {session_id}: {e}") + logger.warning(f"[AgentBridge] Memory system not available for session {session_id}: {e}") + import traceback + logger.warning(f"[AgentBridge] Memory init traceback: {traceback.format_exc()}") # Load tools from agent.tools import ToolManager diff --git a/models/openai/open_ai_bot.py b/models/openai/open_ai_bot.py index 5c8911e..8885948 100644 --- a/models/openai/open_ai_bot.py +++ b/models/openai/open_ai_bot.py @@ -158,7 +158,7 @@ class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot): # Build request parameters for ChatCompletion request_params = { - "model": kwargs.get("model", conf().get("model") or "gpt-3.5-turbo"), + "model": kwargs.get("model", conf().get("model") or "gpt-4.1"), "messages": messages, "temperature": kwargs.get("temperature", conf().get("temperature", 0.9)), "top_p": kwargs.get("top_p", 1), diff --git a/plugins/bdunit/README.md b/plugins/bdunit/README.md deleted file mode 100644 index a2f2c78..0000000 --- a/plugins/bdunit/README.md +++ /dev/null @@ -1,30 +0,0 @@ -## 插件说明 - -利用百度UNIT实现智能对话 - -- 1.解决问题：chatgpt无法处理的指令，交给百度UNIT处理如：天气，日期时间，数学运算等 -- 2.如问时间：现在几点钟，今天几号 -- 3.如问天气：明天广州天气怎么样，这个周末深圳会不会下雨 -- 4.如问数学运算：23+45=多少，100-23=多少，35转化为二进制是多少？ - -## 使用说明 - -### 获取apikey - -在百度UNIT官网上自己创建应用，申请百度机器人,可以把预先训练好的模型导入到自己的应用中， - -see https://ai.baidu.com/unit/home#/home?track=61fe1b0d3407ce3face1d92cb5c291087095fc10c8377aaf https://console.bce.baidu.com/ai平台申请 - -### 配置文件 - -将文件夹中`config.json.template`复制为`config.json`。 - -在其中填写百度UNIT官网上获取应用的API Key和Secret Key - -``` json - { - "service_id": "s...", #"机器人ID" - "api_key": "", - "secret_key": "" - } -``` \ No newline at end of file diff --git a/plugins/bdunit/__init__.py b/plugins/bdunit/__init__.py deleted file mode 100644 index 28f44b4..0000000 --- a/plugins/bdunit/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .bdunit import * diff --git a/plugins/bdunit/bdunit.py b/plugins/bdunit/bdunit.py deleted file mode 100644 index 33194e3..0000000 --- a/plugins/bdunit/bdunit.py +++ /dev/null @@ -1,252 +0,0 @@ -# encoding:utf-8 -import json -import os -import uuid -from uuid import getnode as get_mac - -import requests - -import plugins -from bridge.context import ContextType -from bridge.reply import Reply, ReplyType -from common.log import logger -from plugins import * - -"""利用百度UNIT实现智能对话 - 如果命中意图，返回意图对应的回复，否则返回继续交付给下个插件处理 -""" - - -@plugins.register( - name="BDunit", - desire_priority=0, - hidden=True, - desc="Baidu unit bot system", - version="0.1", - author="jackson", -) -class BDunit(Plugin): - def __init__(self): - super().__init__() - try: - conf = super().load_config() - if not conf: - raise Exception("config.json not found") - self.service_id = conf["service_id"] - self.api_key = conf["api_key"] - self.secret_key = conf["secret_key"] - self.access_token = self.get_token() - self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context - logger.info("[BDunit] inited") - except Exception as e: - logger.warn("[BDunit] init failed, ignore ") - raise e - - def on_handle_context(self, e_context: EventContext): - if e_context["context"].type != ContextType.TEXT: - return - - content = e_context["context"].content - logger.debug("[BDunit] on_handle_context. content: %s" % content) - parsed = self.getUnit2(content) - intent = self.getIntent(parsed) - if intent: # 找到意图 - logger.debug("[BDunit] Baidu_AI Intent= %s", intent) - reply = Reply() - reply.type = ReplyType.TEXT - reply.content = self.getSay(parsed) - e_context["reply"] = reply - e_context.action = EventAction.BREAK_PASS # 事件结束，并跳过处理context的默认逻辑 - else: - e_context.action = EventAction.CONTINUE # 事件继续，交付给下个插件或默认逻辑 - - def get_help_text(self, **kwargs): - help_text = "本插件会处理询问实时日期时间，天气，数学运算等问题，这些技能由您的百度智能对话UNIT决定\n" - return help_text - - def get_token(self): - """获取访问百度UUNIT 的access_token - #param api_key: UNIT apk_key - #param secret_key: UNIT secret_key - Returns: - string: access_token - """ - url = "https://aip.baidubce.com/oauth/2.0/token?client_id={}&client_secret={}&grant_type=client_credentials".format(self.api_key, self.secret_key) - payload = "" - headers = {"Content-Type": "application/json", "Accept": "application/json"} - - response = requests.request("POST", url, headers=headers, data=payload) - - # print(response.text) - return response.json()["access_token"] - - def getUnit(self, query): - """ - NLU 解析version 3.0 - :param query: 用户的指令字符串 - :returns: UNIT 解析结果。如果解析失败，返回 None - """ - - url = "https://aip.baidubce.com/rpc/2.0/unit/service/v3/chat?access_token=" + self.access_token - request = { - "query": query, - "user_id": str(get_mac())[:32], - "terminal_id": "88888", - } - body = { - "log_id": str(uuid.uuid1()), - "version": "3.0", - "service_id": self.service_id, - "session_id": str(uuid.uuid1()), - "request": request, - } - try: - headers = {"Content-Type": "application/json"} - response = requests.post(url, json=body, headers=headers) - return json.loads(response.text) - except Exception: - return None - - def getUnit2(self, query): - """ - NLU 解析 version 2.0 - - :param query: 用户的指令字符串 - :returns: UNIT 解析结果。如果解析失败，返回 None - """ - url = "https://aip.baidubce.com/rpc/2.0/unit/service/chat?access_token=" + self.access_token - request = {"query": query, "user_id": str(get_mac())[:32]} - body = { - "log_id": str(uuid.uuid1()), - "version": "2.0", - "service_id": self.service_id, - "session_id": str(uuid.uuid1()), - "request": request, - } - try: - headers = {"Content-Type": "application/json"} - response = requests.post(url, json=body, headers=headers) - return json.loads(response.text) - except Exception: - return None - - def getIntent(self, parsed): - """ - 提取意图 - - :param parsed: UNIT 解析结果 - :returns: 意图数组 - """ - if parsed and "result" in parsed and "response_list" in parsed["result"]: - try: - return parsed["result"]["response_list"][0]["schema"]["intent"] - except Exception as e: - logger.warning(e) - return "" - else: - return "" - - def hasIntent(self, parsed, intent): - """ - 判断是否包含某个意图 - - :param parsed: UNIT 解析结果 - :param intent: 意图的名称 - :returns: True: 包含; False: 不包含 - """ - if parsed and "result" in parsed and "response_list" in parsed["result"]: - response_list = parsed["result"]["response_list"] - for response in response_list: - if "schema" in response and "intent" in response["schema"] and response["schema"]["intent"] == intent: - return True - return False - else: - return False - - def getSlots(self, parsed, intent=""): - """ - 提取某个意图的所有词槽 - - :param parsed: UNIT 解析结果 - :param intent: 意图的名称 - :returns: 词槽列表。你可以通过 name 属性筛选词槽， - 再通过 normalized_word 属性取出相应的值 - """ - if parsed and "result" in parsed and "response_list" in parsed["result"]: - response_list = parsed["result"]["response_list"] - if intent == "": - try: - return parsed["result"]["response_list"][0]["schema"]["slots"] - except Exception as e: - logger.warning(e) - return [] - for response in response_list: - if "schema" in response and "intent" in response["schema"] and "slots" in response["schema"] and response["schema"]["intent"] == intent: - return response["schema"]["slots"] - return [] - else: - return [] - - def getSlotWords(self, parsed, intent, name): - """ - 找出命中某个词槽的内容 - - :param parsed: UNIT 解析结果 - :param intent: 意图的名称 - :param name: 词槽名 - :returns: 命中该词槽的值的列表。 - """ - slots = self.getSlots(parsed, intent) - words = [] - for slot in slots: - if slot["name"] == name: - words.append(slot["normalized_word"]) - return words - - def getSayByConfidence(self, parsed): - """ - 提取 UNIT 置信度最高的回复文本 - - :param parsed: UNIT 解析结果 - :returns: UNIT 的回复文本 - """ - if parsed and "result" in parsed and "response_list" in parsed["result"]: - response_list = parsed["result"]["response_list"] - answer = {} - for response in response_list: - if ( - "schema" in response - and "intent_confidence" in response["schema"] - and (not answer or response["schema"]["intent_confidence"] > answer["schema"]["intent_confidence"]) - ): - answer = response - return answer["action_list"][0]["say"] - else: - return "" - - def getSay(self, parsed, intent=""): - """ - 提取 UNIT 的回复文本 - - :param parsed: UNIT 解析结果 - :param intent: 意图的名称 - :returns: UNIT 的回复文本 - """ - if parsed and "result" in parsed and "response_list" in parsed["result"]: - response_list = parsed["result"]["response_list"] - if intent == "": - try: - return response_list[0]["action_list"][0]["say"] - except Exception as e: - logger.warning(e) - return "" - for response in response_list: - if "schema" in response and "intent" in response["schema"] and response["schema"]["intent"] == intent: - try: - return response["action_list"][0]["say"] - except Exception as e: - logger.warning(e) - return "" - return "" - else: - return "" diff --git a/plugins/bdunit/config.json.template b/plugins/bdunit/config.json.template deleted file mode 100644 index c3bad56..0000000 --- a/plugins/bdunit/config.json.template +++ /dev/null @@ -1,5 +0,0 @@ -{ - "service_id": "s...", - "api_key": "", - "secret_key": "" -} diff --git a/plugins/config.json.template b/plugins/config.json.template index f11fb93..7cc3dcd 100644 --- a/plugins/config.json.template +++ b/plugins/config.json.template @@ -8,17 +8,6 @@ "reply_filter": true, "reply_action": "ignore" }, - "tool": { - "tools": [ - "url-get", - "meteo-weather" - ], - "kwargs": { - "top_k_results": 2, - "no_default": false, - "model_name": "gpt-3.5-turbo" - } - }, "linkai": { "group_app_map": { "测试群1": "default", diff --git a/skills/skill-creator/SKILL.md b/skills/skill-creator/SKILL.md index 3729055..4a09bc4 100644 --- a/skills/skill-creator/SKILL.md +++ b/skills/skill-creator/SKILL.md @@ -214,6 +214,19 @@ These files contain established best practices for effective skill design. To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`. +**Available Base Tools**: + +The agent has access to these core tools that you can leverage in your skill: +- **bash**: Execute shell commands (use for curl, ls, grep, sed, awk, bc for calculations, etc.) +- **read**: Read file contents +- **write**: Write files +- **edit**: Edit files with search/replace + +**Minimize Dependencies**: +- ✅ **Prefer bash + curl** for HTTP API calls (no Python dependencies) +- ✅ **Use bash tools** (grep, sed, awk) for text processing +- ✅ **Keep scripts simple** - if bash can do it, no need for Python (document packages/versions if Python is used) + **Important Guidelines**: - **scripts/**: Only create scripts that will be executed. Test all scripts before including. - **references/**: ONLY create if documentation is too large for SKILL.md (>500 lines). Most skills don't need this. diff --git a/skills/web-fetch/SKILL.md b/skills/web-fetch/SKILL.md new file mode 100644 index 0000000..05d9650 --- /dev/null +++ b/skills/web-fetch/SKILL.md @@ -0,0 +1,49 @@ +--- +name: web-fetch +description: Fetch and extract readable content from web pages +homepage: https://github.com/zhayujie/chatgpt-on-wechat +metadata: + emoji: 🌐 + requires: + bins: ["curl"] +--- + +# Web Fetch + +Fetch and extract readable content from web pages using curl and basic text processing. + +## Usage + +Use the provided script to fetch a URL and extract its content: + +```bash +bash scripts/fetch.sh [output_file] +``` + +**Parameters:** +- `url`: The HTTP/HTTPS URL to fetch (required) +- `output_file`: Optional file to save the output (default: stdout) + +**Returns:** +- Extracted page content with title and text + +## Examples + +### Fetch a web page +```bash +bash scripts/fetch.sh "https://example.com" +``` + +### Save to file +```bash +bash scripts/fetch.sh "https://example.com" output.txt +cat output.txt +``` + +## Notes + +- Uses curl for HTTP requests (timeout: 20s) +- Extracts title and basic text content +- Removes HTML tags and scripts +- Works with any standard web page +- No external dependencies beyond curl diff --git a/skills/web-fetch/scripts/fetch.sh b/skills/web-fetch/scripts/fetch.sh new file mode 100755 index 0000000..b13a41d --- /dev/null +++ b/skills/web-fetch/scripts/fetch.sh @@ -0,0 +1,54 @@ +#!/usr/bin/env bash +# Fetch and extract readable content from a web page + +set -euo pipefail + +url="${1:-}" +output_file="${2:-}" + +if [ -z "$url" ]; then + echo "Error: URL is required" + echo "Usage: bash fetch.sh [output_file]" + exit 1 +fi + +# Validate URL +if [[ ! "$url" =~ ^https?:// ]]; then + echo "Error: Invalid URL (must start with http:// or https://)" + exit 1 +fi + +# Fetch the page with curl +html=$(curl -sS -L --max-time 20 \ + -H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36" \ + -H "Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8" \ + "$url" 2>&1) || { + echo "Error: Failed to fetch URL: $url" + exit 1 +} + +# Extract title +title=$(echo "$html" | grep -oP '(?<=).*?(?=)' | head -1 || echo "Untitled") + +# Remove script and style tags +text=$(echo "$html" | sed 's/]*>.*<\/script>//gI' | sed 's/]*>.*<\/style>//gI') + +# Remove HTML tags +text=$(echo "$text" | sed 's/<[^>]*>//g') + +# Clean up whitespace +text=$(echo "$text" | tr -s ' ' | sed 's/^[[:space:]]*//;s/[[:space:]]*$//') + +# Format output +result="Title: $title + +Content: +$text" + +# Output to file or stdout +if [ -n "$output_file" ]; then + echo "$result" > "$output_file" + echo "Content saved to: $output_file" +else + echo "$result" +fi From 6f70a8efda966de9f2de39daef789c54f3ce48e2 Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 17:08:02 +0800 Subject: [PATCH 03/11] fix: fts5 not available bug --- agent/memory/storage.py | 110 ++++++++++++++++++++++++---------------- 1 file changed, 65 insertions(+), 45 deletions(-) diff --git a/agent/memory/storage.py b/agent/memory/storage.py index b8fccf0..373512b 100644 --- a/agent/memory/storage.py +++ b/agent/memory/storage.py @@ -46,14 +46,32 @@ class MemoryStorage: def __init__(self, db_path: Path): self.db_path = db_path self.conn: Optional[sqlite3.Connection] = None + self.fts5_available = False # Track FTS5 availability self._init_db() + def _check_fts5_support(self) -> bool: + """Check if SQLite has FTS5 support""" + try: + self.conn.execute("CREATE VIRTUAL TABLE IF NOT EXISTS fts5_test USING fts5(test)") + self.conn.execute("DROP TABLE IF EXISTS fts5_test") + return True + except sqlite3.OperationalError as e: + if "no such module: fts5" in str(e): + return False + raise + def _init_db(self): """Initialize database with schema""" try: self.conn = sqlite3.connect(str(self.db_path), check_same_thread=False) self.conn.row_factory = sqlite3.Row + # Check FTS5 support + self.fts5_available = self._check_fts5_support() + if not self.fts5_available: + from common.log import logger + logger.warning("[MemoryStorage] FTS5 not available, using LIKE-based keyword search") + # Check database integrity try: result = self.conn.execute("PRAGMA integrity_check").fetchone() @@ -125,43 +143,44 @@ class MemoryStorage: ON chunks(path, hash) """) - # Create FTS5 virtual table for keyword search - # Use default unicode61 tokenizer (stable and compatible) - # For CJK support, we'll use LIKE queries as fallback - self.conn.execute(""" - CREATE VIRTUAL TABLE IF NOT EXISTS chunks_fts USING fts5( - text, - id UNINDEXED, - user_id UNINDEXED, - path UNINDEXED, - source UNINDEXED, - scope UNINDEXED, - content='chunks', - content_rowid='rowid' - ) - """) - - # Create triggers to keep FTS in sync - self.conn.execute(""" - CREATE TRIGGER IF NOT EXISTS chunks_ai AFTER INSERT ON chunks BEGIN - INSERT INTO chunks_fts(rowid, text, id, user_id, path, source, scope) - VALUES (new.rowid, new.text, new.id, new.user_id, new.path, new.source, new.scope); - END - """) - - self.conn.execute(""" - CREATE TRIGGER IF NOT EXISTS chunks_ad AFTER DELETE ON chunks BEGIN - DELETE FROM chunks_fts WHERE rowid = old.rowid; - END - """) - - self.conn.execute(""" - CREATE TRIGGER IF NOT EXISTS chunks_au AFTER UPDATE ON chunks BEGIN - UPDATE chunks_fts SET text = new.text, id = new.id, - user_id = new.user_id, path = new.path, source = new.source, scope = new.scope - WHERE rowid = new.rowid; - END - """) + # Create FTS5 virtual table for keyword search (only if supported) + if self.fts5_available: + # Use default unicode61 tokenizer (stable and compatible) + # For CJK support, we'll use LIKE queries as fallback + self.conn.execute(""" + CREATE VIRTUAL TABLE IF NOT EXISTS chunks_fts USING fts5( + text, + id UNINDEXED, + user_id UNINDEXED, + path UNINDEXED, + source UNINDEXED, + scope UNINDEXED, + content='chunks', + content_rowid='rowid' + ) + """) + + # Create triggers to keep FTS in sync + self.conn.execute(""" + CREATE TRIGGER IF NOT EXISTS chunks_ai AFTER INSERT ON chunks BEGIN + INSERT INTO chunks_fts(rowid, text, id, user_id, path, source, scope) + VALUES (new.rowid, new.text, new.id, new.user_id, new.path, new.source, new.scope); + END + """) + + self.conn.execute(""" + CREATE TRIGGER IF NOT EXISTS chunks_ad AFTER DELETE ON chunks BEGIN + DELETE FROM chunks_fts WHERE rowid = old.rowid; + END + """) + + self.conn.execute(""" + CREATE TRIGGER IF NOT EXISTS chunks_au AFTER UPDATE ON chunks BEGIN + UPDATE chunks_fts SET text = new.text, id = new.id, + user_id = new.user_id, path = new.path, source = new.source, scope = new.scope + WHERE rowid = new.rowid; + END + """) # Create files metadata table self.conn.execute(""" @@ -301,21 +320,22 @@ class MemoryStorage: Keyword search using FTS5 + LIKE fallback Strategy: - 1. Try FTS5 search first (good for English and word-based languages) - 2. If no results and query contains CJK characters, use LIKE search + 1. If FTS5 available: Try FTS5 search first (good for English and word-based languages) + 2. If no FTS5 or no results and query contains CJK: Use LIKE search """ if scopes is None: scopes = ["shared"] if user_id: scopes.append("user") - # Try FTS5 search first - fts_results = self._search_fts5(query, user_id, scopes, limit) - if fts_results: - return fts_results + # Try FTS5 search first (if available) + if self.fts5_available: + fts_results = self._search_fts5(query, user_id, scopes, limit) + if fts_results: + return fts_results - # Fallback to LIKE search for CJK characters - if MemoryStorage._contains_cjk(query): + # Fallback to LIKE search (always for CJK, or if FTS5 not available) + if not self.fts5_available or MemoryStorage._contains_cjk(query): return self._search_like(query, user_id, scopes, limit) return [] From 85578a06b7460813ffce88eb5ca0fc9182eda0aa Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 17:13:32 +0800 Subject: [PATCH 04/11] fix: memory edit bug --- agent/prompt/builder.py | 8 ++++++-- agent/tools/read/read.py | 18 ++++++++++++------ 2 files changed, 18 insertions(+), 8 deletions(-) diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py index 9134e02..168018c 100644 --- a/agent/prompt/builder.py +++ b/agent/prompt/builder.py @@ -315,8 +315,12 @@ def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], langu "", "**使用原则**:", "- 自然使用记忆，就像你本来就知道; 不用刻意提起或列举记忆，除非用户提起相关内容", - "- 追加内容到现有记忆文件 → 必须用 `edit` 工具（先 read 读取，再 edit 追加）", - "- 创建新的记忆文件 → 可以用 `write` 工具（已有记忆文件不可直接write，会覆盖删除）", + "", + "**写入记忆的正确方式**:", + "- 追加到现有文件末尾 → 用 `read` 读取文件最后几行（offset=-10），然后用 `edit` 追加", + " 例: read(path=memory/2026-02-01.md, offset=-10) → 看到最后内容 → edit(oldText=最后几行完整文本, newText=最后几行+新内容)", + "- 创建新文件 → 用 `write`", + "- ⚠️ 不要用 `memory_get` 读取后再 `edit`，因为会截断长文本", "", ] diff --git a/agent/tools/read/read.py b/agent/tools/read/read.py index 4810890..6ecae07 100644 --- a/agent/tools/read/read.py +++ b/agent/tools/read/read.py @@ -26,7 +26,7 @@ class Read(BaseTool): }, "offset": { "type": "integer", - "description": "Line number to start reading from (1-indexed, optional)" + "description": "Line number to start reading from (1-indexed, optional). Use negative values to read from end (e.g. -20 for last 20 lines)" }, "limit": { "type": "integer", @@ -167,11 +167,17 @@ class Read(BaseTool): # Apply offset (if specified) start_line = 0 if offset is not None: - start_line = max(0, offset - 1) # Convert to 0-indexed - if start_line >= total_file_lines: - return ToolResult.fail( - f"Error: Offset {offset} is beyond end of file ({total_file_lines} lines total)" - ) + if offset < 0: + # Negative offset: read from end + # -20 means "last 20 lines" → start from (total - 20) + start_line = max(0, total_file_lines + offset) + else: + # Positive offset: read from start (1-indexed) + start_line = max(0, offset - 1) # Convert to 0-indexed + if start_line >= total_file_lines: + return ToolResult.fail( + f"Error: Offset {offset} is beyond end of file ({total_file_lines} lines total)" + ) start_line_display = start_line + 1 # For display (1-indexed) From 99c273a2936a59280254f895b077740bab8e14fc Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 17:29:48 +0800 Subject: [PATCH 05/11] fix: write too long file --- agent/prompt/builder.py | 2 +- agent/protocol/agent_stream.py | 57 +++++++++++++++++++++++++--------- agent/tools/write/write.py | 2 +- 3 files changed, 44 insertions(+), 17 deletions(-) diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py index 168018c..44a4eee 100644 --- a/agent/prompt/builder.py +++ b/agent/prompt/builder.py @@ -179,7 +179,7 @@ def _build_tooling_section(tools: List[Any], language: str) -> List[str]: tool_map = {} tool_descriptions = { "read": "读取文件内容", - "write": "创建新文件或完全覆盖现有文件（会删除原内容！追加内容请用 edit）", + "write": "创建新文件或完全覆盖现有文件（会删除原内容！追加内容请用 edit）。注意：单次 write 内容不要超过 10KB，超大文件请分步创建", "edit": "精确编辑文件（追加、修改、删除部分内容）", "ls": "列出目录内容", "grep": "在文件中搜索内容", diff --git a/agent/protocol/agent_stream.py b/agent/protocol/agent_stream.py index 8289c15..7ea1eeb 100644 --- a/agent/protocol/agent_stream.py +++ b/agent/protocol/agent_stream.py @@ -78,12 +78,15 @@ class AgentStreamExecutor: args_str = json.dumps(args, sort_keys=True, ensure_ascii=False) return hashlib.md5(args_str.encode()).hexdigest()[:8] - def _check_consecutive_failures(self, tool_name: str, args: dict) -> tuple[bool, str]: + def _check_consecutive_failures(self, tool_name: str, args: dict) -> tuple[bool, str, bool]: """ Check if tool has failed too many times consecutively Returns: - (should_stop, reason) + (should_stop, reason, is_critical) + - should_stop: Whether to stop tool execution + - reason: Reason for stopping + - is_critical: Whether to abort entire conversation (True for 8+ failures) """ args_hash = self._hash_args(args) @@ -99,7 +102,7 @@ class AgentStreamExecutor: break # Different tool or args, stop counting if same_args_failures >= 3: - return True, f"Tool '{tool_name}' with same arguments failed {same_args_failures} times consecutively. Stopping to prevent infinite loop." + return True, f"工具 '{tool_name}' 使用相同参数连续失败 {same_args_failures} 次，停止执行以防止无限循环", False # Count consecutive failures for same tool (any args) same_tool_failures = 0 @@ -112,10 +115,15 @@ class AgentStreamExecutor: else: break # Different tool, stop counting - if same_tool_failures >= 6: - return True, f"Tool '{tool_name}' failed {same_tool_failures} times consecutively (with any arguments). Stopping to prevent infinite loop." + # Hard stop at 8 failures - abort with critical message + if same_tool_failures >= 8: + return True, f"抱歉，我没能完成这个任务。可能是我理解有误或者当前方法不太合适。\n\n建议你：\n• 换个方式描述需求试试\n• 把任务拆分成更小的步骤\n• 或者换个思路来解决", True - return False, "" + # Warning at 6 failures + if same_tool_failures >= 6: + return True, f"工具 '{tool_name}' 连续失败 {same_tool_failures} 次（使用不同参数），停止执行以防止无限循环", False + + return False, "", False def _record_tool_result(self, tool_name: str, args: dict, success: bool): """Record tool execution result for failure tracking""" @@ -227,6 +235,12 @@ class AgentStreamExecutor: result = self._execute_tool(tool_call) tool_results.append(result) + # Check for critical error - abort entire conversation + if result.get("status") == "critical_error": + logger.error(f"💥 检测到严重错误，终止对话") + final_response = result.get('result', '任务执行失败') + return final_response + # Log tool result in compact format status_emoji = "✅" if result.get("status") == "success" else "❌" result_data = result.get('result', '') @@ -467,15 +481,19 @@ class AgentStreamExecutor: try: arguments = json.loads(tc["arguments"]) if tc["arguments"] else {} except json.JSONDecodeError as e: - logger.error(f"Failed to parse tool arguments: {tc['arguments']}") + args_preview = tc['arguments'][:200] if len(tc['arguments']) > 200 else tc['arguments'] + logger.error(f"Failed to parse tool arguments for {tc['name']}") + logger.error(f"Arguments length: {len(tc['arguments'])} chars") + logger.error(f"Arguments preview: {args_preview}...") logger.error(f"JSON decode error: {e}") + # Return a clear error message to the LLM instead of empty dict # This helps the LLM understand what went wrong tool_calls.append({ "id": tc["id"], "name": tc["name"], "arguments": {}, - "_parse_error": f"Invalid JSON in tool arguments: {tc['arguments'][:100]}... Error: {str(e)}" + "_parse_error": f"Invalid JSON in tool arguments: {args_preview}... Error: {str(e)}. Tip: For large content, consider splitting into smaller chunks or using a different approach." }) continue @@ -558,16 +576,25 @@ class AgentStreamExecutor: return result # Check for consecutive failures (retry protection) - should_stop, stop_reason = self._check_consecutive_failures(tool_name, arguments) + should_stop, stop_reason, is_critical = self._check_consecutive_failures(tool_name, arguments) if should_stop: logger.error(f"🛑 {stop_reason}") self._record_tool_result(tool_name, arguments, False) - # 返回错误给 LLM,让它尝试其他方法 - result = { - "status": "error", - "result": f"{stop_reason}\n\nThis approach is not working. Please try a completely different method or ask the user for more information/clarification.", - "execution_time": 0 - } + + if is_critical: + # Critical failure - abort entire conversation + result = { + "status": "critical_error", + "result": stop_reason, + "execution_time": 0 + } + else: + # Normal failure - let LLM try different approach + result = { + "status": "error", + "result": f"{stop_reason}\n\n当前方法行不通，请尝试完全不同的方法或向用户询问更多信息。", + "execution_time": 0 + } return result self._emit_event("tool_execution_start", { diff --git a/agent/tools/write/write.py b/agent/tools/write/write.py index 9836564..49e01c8 100644 --- a/agent/tools/write/write.py +++ b/agent/tools/write/write.py @@ -14,7 +14,7 @@ class Write(BaseTool): """Tool for writing file content""" name: str = "write" - description: str = "Write content to a file. Creates the file if it doesn't exist, overwrites if it does. Automatically creates parent directories." + description: str = "Write content to a file. Creates the file if it doesn't exist, overwrites if it does. Automatically creates parent directories. IMPORTANT: Single write should not exceed 10KB. For large files, create a skeleton first, then use edit to add content in chunks." params: dict = { "type": "object", From d337140577acfd1c2f123a50182be19ef0af968e Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 17:46:43 +0800 Subject: [PATCH 06/11] feat: optimize editing tools --- agent/prompt/builder.py | 10 +++--- agent/tools/edit/edit.py | 67 +++++++++++++++++++++++----------------- 2 files changed, 44 insertions(+), 33 deletions(-) diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py index 44a4eee..d80af06 100644 --- a/agent/prompt/builder.py +++ b/agent/prompt/builder.py @@ -305,8 +305,8 @@ def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], langu "", "在回答关于以前的工作、决定、日期、人物、偏好或待办事项的任何问题之前：", "", - "1. 不确定信息位置 → 先用 `memory_search` 通过关键词和语义检索相关内容", - "2. 已知文件和大致位置 → 直接用 `memory_get` 读取相应的行", + "1. 不确定记忆文件位置 → 先用 `memory_search` 通过关键词和语义检索相关内容", + "2. 已知文件位置 → 直接用 `memory_get` 读取相应的行", "3. search 无结果 → 尝试用 `memory_get` 读取最近两天的记忆文件", "", "**记忆文件结构**:", @@ -317,10 +317,10 @@ def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], langu "- 自然使用记忆，就像你本来就知道; 不用刻意提起或列举记忆，除非用户提起相关内容", "", "**写入记忆的正确方式**:", - "- 追加到现有文件末尾 → 用 `read` 读取文件最后几行（offset=-10），然后用 `edit` 追加", - " 例: read(path=memory/2026-02-01.md, offset=-10) → 看到最后内容 → edit(oldText=最后几行完整文本, newText=最后几行+新内容)", + "- 追加到现有文件末尾 → 用 `edit` 工具，oldText 留空", + " 例: edit(path=memory/2026-02-01.md, oldText=\"\", newText=\"\\n## 新内容\\n...\")", + "- 修改文件中的某段文字 → 用 `edit` 工具，oldText 填写要替换的文本", "- 创建新文件 → 用 `write`", - "- ⚠️ 不要用 `memory_get` 读取后再 `edit`，因为会截断长文本", "", ] diff --git a/agent/tools/edit/edit.py b/agent/tools/edit/edit.py index b07c8f1..e17e624 100644 --- a/agent/tools/edit/edit.py +++ b/agent/tools/edit/edit.py @@ -22,7 +22,7 @@ class Edit(BaseTool): """Tool for precise file editing""" name: str = "edit" - description: str = "Edit a file by replacing exact text. The oldText must match exactly (including whitespace). Use this for precise, surgical edits." + description: str = "Edit a file by replacing exact text, or append to end if oldText is empty. For append: use empty oldText. For replace: oldText must match exactly (including whitespace)." params: dict = { "type": "object", @@ -33,7 +33,7 @@ class Edit(BaseTool): }, "oldText": { "type": "string", - "description": "Exact text to find and replace (must match exactly, cannot be empty). To append to end of file, include the last few lines as oldText." + "description": "Text to find and replace. Use empty string to append to end of file. For replacement: must match exactly including whitespace." }, "newText": { "type": "string", @@ -89,34 +89,45 @@ class Edit(BaseTool): normalized_old_text = normalize_to_lf(old_text) normalized_new_text = normalize_to_lf(new_text) - # Use fuzzy matching to find old text (try exact match first, then fuzzy match) - match_result = fuzzy_find_text(normalized_content, normalized_old_text) - - if not match_result.found: - return ToolResult.fail( - f"Error: Could not find the exact text in {path}. " - "The old text must match exactly including all whitespace and newlines." + # Special case: empty oldText means append to end of file + if not old_text or not old_text.strip(): + # Append mode: add newText to the end + # Add newline before newText if file doesn't end with one + if normalized_content and not normalized_content.endswith('\n'): + new_content = normalized_content + '\n' + normalized_new_text + else: + new_content = normalized_content + normalized_new_text + base_content = normalized_content # For verification + else: + # Normal edit mode: find and replace + # Use fuzzy matching to find old text (try exact match first, then fuzzy match) + match_result = fuzzy_find_text(normalized_content, normalized_old_text) + + if not match_result.found: + return ToolResult.fail( + f"Error: Could not find the exact text in {path}. " + "The old text must match exactly including all whitespace and newlines." + ) + + # Calculate occurrence count (use fuzzy normalized content for consistency) + fuzzy_content = normalize_for_fuzzy_match(normalized_content) + fuzzy_old_text = normalize_for_fuzzy_match(normalized_old_text) + occurrences = fuzzy_content.count(fuzzy_old_text) + + if occurrences > 1: + return ToolResult.fail( + f"Error: Found {occurrences} occurrences of the text in {path}. " + "The text must be unique. Please provide more context to make it unique." + ) + + # Execute replacement (use matched text position) + base_content = match_result.content_for_replacement + new_content = ( + base_content[:match_result.index] + + normalized_new_text + + base_content[match_result.index + match_result.match_length:] ) - # Calculate occurrence count (use fuzzy normalized content for consistency) - fuzzy_content = normalize_for_fuzzy_match(normalized_content) - fuzzy_old_text = normalize_for_fuzzy_match(normalized_old_text) - occurrences = fuzzy_content.count(fuzzy_old_text) - - if occurrences > 1: - return ToolResult.fail( - f"Error: Found {occurrences} occurrences of the text in {path}. " - "The text must be unique. Please provide more context to make it unique." - ) - - # Execute replacement (use matched text position) - base_content = match_result.content_for_replacement - new_content = ( - base_content[:match_result.index] + - normalized_new_text + - base_content[match_result.index + match_result.match_length:] - ) - # Verify replacement actually changed content if base_content == new_content: return ToolResult.fail( From 4c8712d683c1d02d78b0b590e85fb2bf9b2d8f22 Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 19:21:12 +0800 Subject: [PATCH 07/11] feat: key management and scheduled task tools --- agent/prompt/builder.py | 2 + agent/skills/config.py | 51 +-- agent/skills/formatter.py | 1 + agent/skills/frontmatter.py | 23 +- agent/skills/manager.py | 18 +- agent/tools/__init__.py | 13 + agent/tools/env_config/__init__.py | 3 + agent/tools/env_config/env_config.py | 283 +++++++++++++ agent/tools/scheduler/README.md | 286 ++++++++++++++ agent/tools/scheduler/__init__.py | 7 + agent/tools/scheduler/integration.py | 239 +++++++++++ agent/tools/scheduler/scheduler_service.py | 192 +++++++++ agent/tools/scheduler/scheduler_tool.py | 439 +++++++++++++++++++++ agent/tools/scheduler/task_store.py | 200 ++++++++++ bridge/agent_bridge.py | 220 ++++++++++- requirements.txt | 3 + skills/bocha-search/SKILL.md | 91 +++++ skills/bocha-search/scripts/search.sh | 75 ++++ skills/skill-creator/SKILL.md | 71 +++- skills/web-fetch/SKILL.md | 19 +- skills/web-fetch/scripts/fetch.sh | 2 +- 21 files changed, 2170 insertions(+), 68 deletions(-) create mode 100644 agent/tools/env_config/__init__.py create mode 100644 agent/tools/env_config/env_config.py create mode 100644 agent/tools/scheduler/README.md create mode 100644 agent/tools/scheduler/__init__.py create mode 100644 agent/tools/scheduler/integration.py create mode 100644 agent/tools/scheduler/scheduler_service.py create mode 100644 agent/tools/scheduler/scheduler_tool.py create mode 100644 agent/tools/scheduler/task_store.py create mode 100644 skills/bocha-search/SKILL.md create mode 100755 skills/bocha-search/scripts/search.sh diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py index d80af06..25179ba 100644 --- a/agent/prompt/builder.py +++ b/agent/prompt/builder.py @@ -242,6 +242,8 @@ def _build_tooling_section(tools: List[Any], language: str) -> List[str]: "- 每次工具调用后，评估是否已获得足够信息来推进或完成任务", "- 避免重复调用相同的工具和相同参数获取相同的信息，除非用户明确要求", "", + "**安全提醒**: 回复中涉及密钥、令牌、密码等敏感信息时，必须脱敏处理，禁止直接显示完整内容。", + "", ]) return lines diff --git a/agent/skills/config.py b/agent/skills/config.py index bbcd9f6..21e1737 100644 --- a/agent/skills/config.py +++ b/agent/skills/config.py @@ -70,33 +70,27 @@ def should_include_skill( entry: SkillEntry, config: Optional[Dict] = None, current_platform: Optional[str] = None, - lenient: bool = True, ) -> bool: """ Determine if a skill should be included based on requirements. - Similar to clawdbot's shouldIncludeSkill logic, but with lenient mode: - - In lenient mode (default): Only check explicit disable and platform, ignore missing requirements - - In strict mode: Check all requirements (binary, env vars, config) + Simple rule: Skills are auto-enabled if their requirements are met. + - Has required API keys → enabled + - Missing API keys → disabled + - Wrong keys → enabled but will fail at runtime (LLM will handle error) :param entry: SkillEntry to check - :param config: Configuration dictionary + :param config: Configuration dictionary (currently unused, reserved for future) :param current_platform: Current platform (default: auto-detect) - :param lenient: If True, ignore missing requirements and load all skills (default: True) :return: True if skill should be included """ metadata = entry.metadata - skill_name = entry.skill.name - skill_config = get_skill_config(config, skill_name) - - # Always check if skill is explicitly disabled in config - if skill_config and skill_config.get('enabled') is False: - return False + # No metadata = always include (no requirements) if not metadata: return True - # Always check platform requirements (can't work on wrong platform) + # Check platform requirements (can't work on wrong platform) if metadata.os: platform_name = current_platform or resolve_runtime_platform() # Map common platform names @@ -114,12 +108,7 @@ def should_include_skill( if metadata.always: return True - # In lenient mode, skip requirement checks and load all skills - # Skills will fail gracefully at runtime if requirements are missing - if lenient: - return True - - # Strict mode: Check all requirements + # Check requirements if metadata.requires: # Check required binaries (all must be present) required_bins = metadata.requires.get('bins', []) @@ -133,29 +122,13 @@ def should_include_skill( if not has_any_binary(any_bins): return False - # Check environment variables (with config fallback) + # Check environment variables (API keys) + # Simple rule: All required env vars must be set required_env = metadata.requires.get('env', []) if required_env: for env_name in required_env: - # Check in order: 1) env var, 2) skill config env, 3) skill config apiKey (if primaryEnv) - if has_env_var(env_name): - continue - if skill_config: - # Check skill config env dict - skill_env = skill_config.get('env', {}) - if isinstance(skill_env, dict) and env_name in skill_env: - continue - # Check skill config apiKey (if this is the primaryEnv) - if metadata.primary_env == env_name and skill_config.get('apiKey'): - continue - # Requirement not satisfied - return False - - # Check config paths - required_config = metadata.requires.get('config', []) - if required_config and config: - for config_path in required_config: - if not is_config_path_truthy(config, config_path): + if not has_env_var(env_name): + # Missing required API key → disable skill return False return True diff --git a/agent/skills/formatter.py b/agent/skills/formatter.py index e77d7d6..7868e09 100644 --- a/agent/skills/formatter.py +++ b/agent/skills/formatter.py @@ -34,6 +34,7 @@ def format_skills_for_prompt(skills: List[Skill]) -> str: lines.append(f" {_escape_xml(skill.name)}") lines.append(f" {_escape_xml(skill.description)}") lines.append(f" {_escape_xml(skill.file_path)}") + lines.append(f" {_escape_xml(skill.base_dir)}") lines.append(" ") lines.append("") diff --git a/agent/skills/frontmatter.py b/agent/skills/frontmatter.py index 565c1f7..9905e29 100644 --- a/agent/skills/frontmatter.py +++ b/agent/skills/frontmatter.py @@ -23,7 +23,22 @@ def parse_frontmatter(content: str) -> Dict[str, Any]: frontmatter_text = match.group(1) - # Simple YAML-like parsing (supports key: value format) + # Try to use PyYAML for proper YAML parsing + try: + import yaml + frontmatter = yaml.safe_load(frontmatter_text) + if not isinstance(frontmatter, dict): + frontmatter = {} + return frontmatter + except ImportError: + # Fallback to simple parsing if PyYAML not available + pass + except Exception: + # If YAML parsing fails, fall back to simple parsing + pass + + # Simple YAML-like parsing (supports key: value format only) + # This is a fallback for when PyYAML is not available for line in frontmatter_text.split('\n'): line = line.strip() if not line or line.startswith('#'): @@ -72,10 +87,8 @@ def parse_metadata(frontmatter: Dict[str, Any]) -> Optional[SkillMetadata]: if not isinstance(metadata_raw, dict): return None - # Support both 'moltbot' and 'cow' keys for compatibility - meta_obj = metadata_raw.get('moltbot') or metadata_raw.get('cow') - if not meta_obj or not isinstance(meta_obj, dict): - return None + # Use metadata_raw directly (COW format) + meta_obj = metadata_raw # Parse install specs install_specs = [] diff --git a/agent/skills/manager.py b/agent/skills/manager.py index 580dc0f..acc3b17 100644 --- a/agent/skills/manager.py +++ b/agent/skills/manager.py @@ -82,32 +82,24 @@ class SkillManager: self, skill_filter: Optional[List[str]] = None, include_disabled: bool = False, - check_requirements: bool = False, # Changed default to False for lenient loading - lenient: bool = True, # New parameter for lenient mode ) -> List[SkillEntry]: """ Filter skills based on criteria. - By default (lenient=True), all skills are loaded regardless of missing requirements. - Skills will fail gracefully at runtime if requirements are not met. + Simple rule: Skills are auto-enabled if requirements are met. + - Has required API keys → included + - Missing API keys → excluded :param skill_filter: List of skill names to include (None = all) :param include_disabled: Whether to include skills with disable_model_invocation=True - :param check_requirements: Whether to check skill requirements (default: False) - :param lenient: If True, ignore missing requirements (default: True) :return: Filtered list of skill entries """ from agent.skills.config import should_include_skill entries = list(self.skills.values()) - # Check requirements (platform, explicit disable, etc.) - # In lenient mode, only checks platform and explicit disable - if check_requirements or not lenient: - entries = [e for e in entries if should_include_skill(e, self.config, lenient=lenient)] - else: - # Lenient mode: only check explicit disable and platform - entries = [e for e in entries if should_include_skill(e, self.config, lenient=True)] + # Check requirements (platform, binaries, env vars) + entries = [e for e in entries if should_include_skill(e, self.config)] # Apply skill filter if skill_filter is not None: diff --git a/agent/tools/__init__.py b/agent/tools/__init__.py index fd3e3b0..fb9d828 100644 --- a/agent/tools/__init__.py +++ b/agent/tools/__init__.py @@ -13,11 +13,21 @@ from agent.tools.ls.ls import Ls from agent.tools.memory.memory_search import MemorySearchTool from agent.tools.memory.memory_get import MemoryGetTool +# Import env config tool +from agent.tools.env_config.env_config import EnvConfig + # Import tools with optional dependencies def _import_optional_tools(): """Import tools that have optional dependencies""" tools = {} + # Scheduler Tool (requires croniter) + try: + from agent.tools.scheduler.scheduler_tool import SchedulerTool + tools['SchedulerTool'] = SchedulerTool + except ImportError: + pass + # Google Search (requires requests) try: from agent.tools.google_search.google_search import GoogleSearch @@ -43,6 +53,7 @@ def _import_optional_tools(): # Load optional tools _optional_tools = _import_optional_tools() +SchedulerTool = _optional_tools.get('SchedulerTool') GoogleSearch = _optional_tools.get('GoogleSearch') FileSave = _optional_tools.get('FileSave') Terminal = _optional_tools.get('Terminal') @@ -79,6 +90,8 @@ __all__ = [ 'Ls', 'MemorySearchTool', 'MemoryGetTool', + 'EnvConfig', + 'SchedulerTool', # Optional tools (may be None if dependencies not available) 'GoogleSearch', 'FileSave', diff --git a/agent/tools/env_config/__init__.py b/agent/tools/env_config/__init__.py new file mode 100644 index 0000000..2e5822f --- /dev/null +++ b/agent/tools/env_config/__init__.py @@ -0,0 +1,3 @@ +from agent.tools.env_config.env_config import EnvConfig + +__all__ = ['EnvConfig'] diff --git a/agent/tools/env_config/env_config.py b/agent/tools/env_config/env_config.py new file mode 100644 index 0000000..a988f42 --- /dev/null +++ b/agent/tools/env_config/env_config.py @@ -0,0 +1,283 @@ +""" +Environment Configuration Tool - Manage API keys and environment variables +""" + +import os +import re +from typing import Dict, Any +from pathlib import Path + +from agent.tools.base_tool import BaseTool, ToolResult +from common.log import logger + + +# API Key 知识库：常见的环境变量及其描述 +API_KEY_REGISTRY = { + # AI 模型服务 + "OPENAI_API_KEY": "OpenAI API 密钥 (用于GPT模型、Embedding模型)", + "GEMINI_API_KEY": "Google Gemini API 密钥", + "CLAUDE_API_KEY": "Claude API 密钥 (用于Claude模型)", + "LINKAI_API_KEY": "LinkAI智能体平台 API 密钥，支持多种模型切换", + # 搜索服务 + "BOCHA_API_KEY": "博查 AI 搜索 API 密钥 ", +} + +class EnvConfig(BaseTool): + """Tool for managing environment variables (API keys, etc.)""" + + name: str = "env_config" + description: str = ( + "Manage API keys and skill configurations stored in the workspace .env file. " + "Use this tool when user wants to configure API keys (like BOCHA_API_KEY, OPENAI_API_KEY), " + "view configured keys, or manage skill settings. " + "Actions: 'set' (add/update key), 'get' (view specific key), 'list' (show all configured keys), 'delete' (remove key). " + "Values are automatically masked for security. Changes take effect immediately via hot reload." + ) + + params: dict = { + "type": "object", + "properties": { + "action": { + "type": "string", + "description": "Action to perform: 'set', 'get', 'list', 'delete'", + "enum": ["set", "get", "list", "delete"] + }, + "key": { + "type": "string", + "description": ( + "Environment variable key name. Common keys:\n" + "- OPENAI_API_KEY: OpenAI API (GPT models)\n" + "- OPENAI_API_BASE: OpenAI API base URL\n" + "- CLAUDE_API_KEY: Anthropic Claude API\n" + "- GEMINI_API_KEY: Google Gemini API\n" + "- LINKAI_API_KEY: LinkAI platform\n" + "- BOCHA_API_KEY: Bocha AI search (博查搜索)\n" + "Use exact key names (case-sensitive, all uppercase with underscores)" + ) + }, + "value": { + "type": "string", + "description": "Value to set for the environment variable (for 'set' action)" + } + }, + "required": ["action"] + } + + def __init__(self, config: dict = None): + self.config = config or {} + self.workspace_dir = self.config.get("workspace_dir", os.path.expanduser("~/cow")) + self.env_path = os.path.join(self.workspace_dir, '.env') + self.agent_bridge = self.config.get("agent_bridge") # Reference to AgentBridge for hot reload + # Don't create .env file in __init__ to avoid issues during tool discovery + # It will be created on first use in execute() + + def _ensure_env_file(self): + """Ensure the .env file exists""" + # Create workspace directory if it doesn't exist + os.makedirs(self.workspace_dir, exist_ok=True) + + if not os.path.exists(self.env_path): + Path(self.env_path).touch() + logger.info(f"[EnvConfig] Created .env file at {self.env_path}") + + def _mask_value(self, value: str) -> str: + """Mask sensitive parts of a value for logging""" + if not value or len(value) <= 10: + return "***" + return f"{value[:6]}***{value[-4:]}" + + def _read_env_file(self) -> Dict[str, str]: + """Read all key-value pairs from .env file""" + env_vars = {} + if os.path.exists(self.env_path): + with open(self.env_path, 'r', encoding='utf-8') as f: + for line in f: + line = line.strip() + # Skip empty lines and comments + if not line or line.startswith('#'): + continue + # Parse KEY=VALUE + match = re.match(r'^([^=]+)=(.*)$', line) + if match: + key, value = match.groups() + env_vars[key.strip()] = value.strip() + return env_vars + + def _write_env_file(self, env_vars: Dict[str, str]): + """Write all key-value pairs to .env file""" + with open(self.env_path, 'w', encoding='utf-8') as f: + f.write("# Environment variables for agent skills\n") + f.write("# Auto-managed by env_config tool\n\n") + for key, value in sorted(env_vars.items()): + f.write(f"{key}={value}\n") + + def _reload_env(self): + """Reload environment variables from .env file""" + env_vars = self._read_env_file() + for key, value in env_vars.items(): + os.environ[key] = value + logger.debug(f"[EnvConfig] Reloaded {len(env_vars)} environment variables") + + def _refresh_skills(self): + """Refresh skills after environment variable changes""" + if self.agent_bridge: + try: + # Reload .env file + self._reload_env() + + # Refresh skills in all agent instances + refreshed = self.agent_bridge.refresh_all_skills() + logger.info(f"[EnvConfig] Refreshed skills in {refreshed} agent instance(s)") + return True + except Exception as e: + logger.warning(f"[EnvConfig] Failed to refresh skills: {e}") + return False + return False + + def execute(self, args: Dict[str, Any]) -> ToolResult: + """ + Execute environment configuration operation + + :param args: Contains action, key, and value parameters + :return: Result of the operation + """ + # Ensure .env file exists on first use + self._ensure_env_file() + + action = args.get("action") + key = args.get("key") + value = args.get("value") + + try: + if action == "set": + if not key or not value: + return ToolResult.fail("Error: 'key' and 'value' are required for 'set' action.") + + # Read current env vars + env_vars = self._read_env_file() + + # Update the key + env_vars[key] = value + + # Write back to file + self._write_env_file(env_vars) + + # Update current process env + os.environ[key] = value + + logger.info(f"[EnvConfig] Set {key}={self._mask_value(value)}") + + # Try to refresh skills immediately + refreshed = self._refresh_skills() + + result = { + "message": f"Successfully set {key}", + "key": key, + "value": self._mask_value(value), + } + + if refreshed: + result["note"] = "✅ Skills refreshed automatically - changes are now active" + else: + result["note"] = "⚠️ Skills not refreshed - restart agent to load new skills" + + return ToolResult.success(result) + + elif action == "get": + if not key: + return ToolResult.fail("Error: 'key' is required for 'get' action.") + + # Check in file first, then in current env + env_vars = self._read_env_file() + value = env_vars.get(key) or os.getenv(key) + + # Get description from registry + description = API_KEY_REGISTRY.get(key, "未知用途的环境变量") + + if value is not None: + logger.info(f"[EnvConfig] Got {key}={self._mask_value(value)}") + return ToolResult.success({ + "key": key, + "value": self._mask_value(value), + "description": description, + "exists": True + }) + else: + return ToolResult.success({ + "key": key, + "description": description, + "exists": False, + "message": f"Environment variable '{key}' is not set" + }) + + elif action == "list": + env_vars = self._read_env_file() + + # Build detailed variable list with descriptions + variables_with_info = {} + for key, value in env_vars.items(): + variables_with_info[key] = { + "value": self._mask_value(value), + "description": API_KEY_REGISTRY.get(key, "未知用途的环境变量") + } + + logger.info(f"[EnvConfig] Listed {len(env_vars)} environment variables") + + if not env_vars: + return ToolResult.success({ + "message": "No environment variables configured", + "variables": {}, + "note": "常用的 API 密钥可以通过 env_config(action='set', key='KEY_NAME', value='your-key') 来配置" + }) + + return ToolResult.success({ + "message": f"Found {len(env_vars)} environment variable(s)", + "variables": variables_with_info + }) + + elif action == "delete": + if not key: + return ToolResult.fail("Error: 'key' is required for 'delete' action.") + + # Read current env vars + env_vars = self._read_env_file() + + if key not in env_vars: + return ToolResult.success({ + "message": f"Environment variable '{key}' was not set", + "key": key + }) + + # Remove the key + del env_vars[key] + + # Write back to file + self._write_env_file(env_vars) + + # Remove from current process env + if key in os.environ: + del os.environ[key] + + logger.info(f"[EnvConfig] Deleted {key}") + + # Try to refresh skills immediately + refreshed = self._refresh_skills() + + result = { + "message": f"Successfully deleted {key}", + "key": key, + } + + if refreshed: + result["note"] = "✅ Skills refreshed automatically - changes are now active" + else: + result["note"] = "⚠️ Skills not refreshed - restart agent to apply changes" + + return ToolResult.success(result) + + else: + return ToolResult.fail(f"Error: Unknown action '{action}'. Use 'set', 'get', 'list', or 'delete'.") + + except Exception as e: + logger.error(f"[EnvConfig] Error: {e}", exc_info=True) + return ToolResult.fail(f"EnvConfig tool error: {str(e)}") diff --git a/agent/tools/scheduler/README.md b/agent/tools/scheduler/README.md new file mode 100644 index 0000000..ea3432c --- /dev/null +++ b/agent/tools/scheduler/README.md @@ -0,0 +1,286 @@ +# 定时任务工具 (Scheduler Tool) + +## 功能简介 + +定时任务工具允许 Agent 创建、管理和执行定时任务，支持： + +- ⏰ **定时提醒**: 在指定时间发送消息 +- 🔄 **周期性任务**: 按固定间隔或 cron 表达式重复执行 +- 🔧 **动态工具调用**: 定时执行其他工具并发送结果（如搜索新闻、查询天气等） +- 📋 **任务管理**: 查询、启用、禁用、删除任务 + +## 安装依赖 + +```bash +pip install croniter>=2.0.0 +``` + +## 使用方法 + +### 1. 创建定时任务 + +Agent 可以通过自然语言创建定时任务，支持两种类型： + +#### 1.1 静态消息任务 + +发送预定义的消息： + +**示例对话：** +``` +用户: 每天早上9点提醒我开会 +Agent: [调用 scheduler 工具] + action: create + name: 每日开会提醒 + message: 该开会了！ + schedule_type: cron + schedule_value: 0 9 * * * +``` + +#### 1.2 动态工具调用任务 + +定时执行工具并发送结果： + +**示例对话：** +``` +用户: 每天早上8点帮我搜索一下当前新闻 +Agent: [调用 scheduler 工具] + action: create + name: 每日新闻 + tool_call: + tool_name: bocha_search + tool_params: + query: 今日新闻 + result_prefix: 📰 今日新闻播报 + schedule_type: cron + schedule_value: 0 8 * * * +``` + +**工具调用参数说明：** +- `tool_name`: 要调用的工具名称（如 `bocha_search`、`web_fetch` 等） +- `tool_params`: 工具的参数（字典格式） +- `result_prefix`: 可选，在结果前添加的前缀文本 + +### 2. 支持的调度类型 + +#### Cron 表达式 (`cron`) +使用标准 cron 表达式： + +``` +0 9 * * * # 每天 9:00 +0 */2 * * * # 每 2 小时 +30 8 * * 1-5 # 工作日 8:30 +0 0 1 * * # 每月 1 号 +``` + +#### 固定间隔 (`interval`) +以秒为单位的间隔： + +``` +3600 # 每小时 +86400 # 每天 +1800 # 每 30 分钟 +``` + +#### 一次性任务 (`once`) +指定具体时间（ISO 格式）： + +``` +2024-12-25T09:00:00 +2024-12-31T23:59:59 +``` + +### 3. 查询任务列表 + +``` +用户: 查看我的定时任务 +Agent: [调用 scheduler 工具] + action: list +``` + +### 4. 查看任务详情 + +``` +用户: 查看任务 abc123 的详情 +Agent: [调用 scheduler 工具] + action: get + task_id: abc123 +``` + +### 5. 删除任务 + +``` +用户: 删除任务 abc123 +Agent: [调用 scheduler 工具] + action: delete + task_id: abc123 +``` + +### 6. 启用/禁用任务 + +``` +用户: 暂停任务 abc123 +Agent: [调用 scheduler 工具] + action: disable + task_id: abc123 + +用户: 恢复任务 abc123 +Agent: [调用 scheduler 工具] + action: enable + task_id: abc123 +``` + +## 任务存储 + +任务保存在 JSON 文件中： +``` +~/cow/scheduler/tasks.json +``` + +任务数据结构： + +**静态消息任务：** +```json +{ + "id": "abc123", + "name": "每日提醒", + "enabled": true, + "created_at": "2024-01-01T10:00:00", + "updated_at": "2024-01-01T10:00:00", + "schedule": { + "type": "cron", + "expression": "0 9 * * *" + }, + "action": { + "type": "send_message", + "content": "该开会了！", + "receiver": "wxid_xxx", + "receiver_name": "张三", + "is_group": false, + "channel_type": "wechat" + }, + "next_run_at": "2024-01-02T09:00:00", + "last_run_at": "2024-01-01T09:00:00" +} +``` + +**动态工具调用任务：** +```json +{ + "id": "def456", + "name": "每日新闻", + "enabled": true, + "created_at": "2024-01-01T10:00:00", + "updated_at": "2024-01-01T10:00:00", + "schedule": { + "type": "cron", + "expression": "0 8 * * *" + }, + "action": { + "type": "tool_call", + "tool_name": "bocha_search", + "tool_params": { + "query": "今日新闻" + }, + "result_prefix": "📰 今日新闻播报", + "receiver": "wxid_xxx", + "receiver_name": "张三", + "is_group": false, + "channel_type": "wechat" + }, + "next_run_at": "2024-01-02T08:00:00" +} +``` + +## 后台服务 + +定时任务由后台服务 `SchedulerService` 管理： + +- 每 30 秒检查一次到期任务 +- 自动执行到期任务 +- 计算下次执行时间 +- 记录执行历史和错误 + +服务在 Agent 初始化时自动启动，无需手动配置。 + +## 接收者确定 + +定时任务会发送给**创建任务时的对话对象**： + +- 如果在私聊中创建，发送给该用户 +- 如果在群聊中创建，发送到该群 +- 接收者信息在创建时自动保存 + +## 常见用例 + +### 1. 每日提醒（静态消息） +``` +用户: 每天早上8点提醒我吃药 +Agent: ✅ 定时任务创建成功 + 任务ID: a1b2c3d4 + 调度: 每天 8:00 + 消息: 该吃药了！ +``` + +### 2. 工作日提醒（静态消息） +``` +用户: 工作日下午6点提醒我下班 +Agent: [创建 cron: 0 18 * * 1-5] + 消息: 该下班了！ +``` + +### 3. 倒计时提醒（静态消息） +``` +用户: 1小时后提醒我 +Agent: [创建 interval: 3600] +``` + +### 4. 每日新闻推送（动态工具调用） +``` +用户: 每天早上8点帮我搜索一下当前新闻 +Agent: ✅ 定时任务创建成功 + 任务ID: news001 + 调度: 每天 8:00 + 工具: bocha_search(query='今日新闻') + 前缀: 📰 今日新闻播报 +``` + +### 5. 定时天气查询（动态工具调用） +``` +用户: 每天早上7点查询今天的天气 +Agent: [创建 cron: 0 7 * * *] + 工具: bocha_search(query='今日天气') + 前缀: 🌤️ 今日天气预报 +``` + +### 6. 周报提醒（动态工具调用） +``` +用户: 每周五下午5点搜索本周热点 +Agent: [创建 cron: 0 17 * * 5] + 工具: bocha_search(query='本周热点新闻') + 前缀: 📊 本周热点回顾 +``` + +### 4. 特定日期提醒 +``` +用户: 12月25日早上9点提醒我圣诞快乐 +Agent: [创建 once: 2024-12-25T09:00:00] +``` + +## 注意事项 + +1. **时区**: 使用系统本地时区 +2. **精度**: 检查间隔为 30 秒，实际执行可能有 ±30 秒误差 +3. **持久化**: 任务保存在文件中，重启后自动恢复 +4. **一次性任务**: 执行后自动禁用，不会删除（可手动删除） +5. **错误处理**: 执行失败会记录错误，不影响其他任务 + +## 技术实现 + +- **TaskStore**: 任务持久化存储 +- **SchedulerService**: 后台调度服务 +- **SchedulerTool**: Agent 工具接口 +- **Integration**: 与 AgentBridge 集成 + +## 依赖 + +- `croniter`: Cron 表达式解析（轻量级，仅 ~50KB） diff --git a/agent/tools/scheduler/__init__.py b/agent/tools/scheduler/__init__.py new file mode 100644 index 0000000..dafc8b6 --- /dev/null +++ b/agent/tools/scheduler/__init__.py @@ -0,0 +1,7 @@ +""" +Scheduler tool for managing scheduled tasks +""" + +from .scheduler_tool import SchedulerTool + +__all__ = ["SchedulerTool"] diff --git a/agent/tools/scheduler/integration.py b/agent/tools/scheduler/integration.py new file mode 100644 index 0000000..0f8ac35 --- /dev/null +++ b/agent/tools/scheduler/integration.py @@ -0,0 +1,239 @@ +""" +Integration module for scheduler with AgentBridge +""" + +import os +from typing import Optional +from config import conf +from common.log import logger +from bridge.context import Context, ContextType +from bridge.reply import Reply, ReplyType + +# Global scheduler service instance +_scheduler_service = None +_task_store = None + + +def init_scheduler(agent_bridge) -> bool: + """ + Initialize scheduler service + + Args: + agent_bridge: AgentBridge instance + + Returns: + True if initialized successfully + """ + global _scheduler_service, _task_store + + try: + from agent.tools.scheduler.task_store import TaskStore + from agent.tools.scheduler.scheduler_service import SchedulerService + + # Get workspace from config + workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow")) + store_path = os.path.join(workspace_root, "scheduler", "tasks.json") + + # Create task store + _task_store = TaskStore(store_path) + logger.info(f"[Scheduler] Task store initialized: {store_path}") + + # Create execute callback + def execute_task_callback(task: dict): + """Callback to execute a scheduled task""" + try: + action = task.get("action", {}) + action_type = action.get("type") + + if action_type == "send_message": + _execute_send_message(task, agent_bridge) + elif action_type == "tool_call": + _execute_tool_call(task, agent_bridge) + else: + logger.warning(f"[Scheduler] Unknown action type: {action_type}") + except Exception as e: + logger.error(f"[Scheduler] Error executing task {task.get('id')}: {e}") + + # Create scheduler service + _scheduler_service = SchedulerService(_task_store, execute_task_callback) + _scheduler_service.start() + + logger.info("[Scheduler] Scheduler service initialized and started") + return True + + except Exception as e: + logger.error(f"[Scheduler] Failed to initialize scheduler: {e}") + return False + + +def get_task_store(): + """Get the global task store instance""" + return _task_store + + +def get_scheduler_service(): + """Get the global scheduler service instance""" + return _scheduler_service + + +def _execute_send_message(task: dict, agent_bridge): + """ + Execute a send_message action + + Args: + task: Task dictionary + agent_bridge: AgentBridge instance + """ + try: + action = task.get("action", {}) + content = action.get("content", "") + receiver = action.get("receiver") + is_group = action.get("is_group", False) + channel_type = action.get("channel_type", "unknown") + + if not receiver: + logger.error(f"[Scheduler] Task {task['id']}: No receiver specified") + return + + # Create context for sending message + context = Context(ContextType.TEXT, content) + context["receiver"] = receiver + context["isgroup"] = is_group + context["session_id"] = receiver + + # For web channel, generate a virtual request_id + if channel_type == "web": + import uuid + request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}" + context["request_id"] = request_id + logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}") + + # Create reply + reply = Reply(ReplyType.TEXT, content) + + # Get channel and send + from channel.channel_factory import create_channel + + try: + channel = create_channel(channel_type) + if channel: + # For web channel, register the request_id to session mapping + if channel_type == "web" and hasattr(channel, 'request_to_session'): + channel.request_to_session[request_id] = receiver + logger.debug(f"[Scheduler] Registered request_id {request_id} -> session {receiver}") + + channel.send(reply, context) + logger.info(f"[Scheduler] Task {task['id']} executed: sent message to {receiver}") + else: + logger.error(f"[Scheduler] Failed to create channel: {channel_type}") + except Exception as e: + logger.error(f"[Scheduler] Failed to send message: {e}") + + except Exception as e: + logger.error(f"[Scheduler] Error in _execute_send_message: {e}") + + +def _execute_tool_call(task: dict, agent_bridge): + """ + Execute a tool_call action + + Args: + task: Task dictionary + agent_bridge: AgentBridge instance + """ + try: + action = task.get("action", {}) + tool_name = action.get("tool_name") + tool_params = action.get("tool_params", {}) + result_prefix = action.get("result_prefix", "") + receiver = action.get("receiver") + is_group = action.get("is_group", False) + channel_type = action.get("channel_type", "unknown") + + if not tool_name: + logger.error(f"[Scheduler] Task {task['id']}: No tool_name specified") + return + + if not receiver: + logger.error(f"[Scheduler] Task {task['id']}: No receiver specified") + return + + # Get tool manager and create tool instance + from agent.tools.tool_manager import ToolManager + tool_manager = ToolManager() + tool = tool_manager.create_tool(tool_name) + + if not tool: + logger.error(f"[Scheduler] Task {task['id']}: Tool '{tool_name}' not found") + return + + # Execute tool + logger.info(f"[Scheduler] Task {task['id']}: Executing tool '{tool_name}' with params {tool_params}") + result = tool.execute(tool_params) + + # Get result content + if hasattr(result, 'result'): + content = result.result + else: + content = str(result) + + # Add prefix if specified + if result_prefix: + content = f"{result_prefix}\n\n{content}" + + # Send result as message + context = Context(ContextType.TEXT, content) + context["receiver"] = receiver + context["isgroup"] = is_group + context["session_id"] = receiver + + # For web channel, generate a virtual request_id + if channel_type == "web": + import uuid + request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}" + context["request_id"] = request_id + logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}") + + reply = Reply(ReplyType.TEXT, content) + + # Get channel and send + from channel.channel_factory import create_channel + + try: + channel = create_channel(channel_type) + if channel: + # For web channel, register the request_id to session mapping + if channel_type == "web" and hasattr(channel, 'request_to_session'): + channel.request_to_session[request_id] = receiver + logger.debug(f"[Scheduler] Registered request_id {request_id} -> session {receiver}") + + channel.send(reply, context) + logger.info(f"[Scheduler] Task {task['id']} executed: sent tool result to {receiver}") + else: + logger.error(f"[Scheduler] Failed to create channel: {channel_type}") + except Exception as e: + logger.error(f"[Scheduler] Failed to send tool result: {e}") + + except Exception as e: + logger.error(f"[Scheduler] Error in _execute_tool_call: {e}") + + +def attach_scheduler_to_tool(tool, context: Context = None): + """ + Attach scheduler components to a SchedulerTool instance + + Args: + tool: SchedulerTool instance + context: Current context (optional) + """ + if _task_store: + tool.task_store = _task_store + + if context: + tool.current_context = context + + # Also set channel_type from config + channel_type = conf().get("channel_type", "unknown") + if not tool.config: + tool.config = {} + tool.config["channel_type"] = channel_type diff --git a/agent/tools/scheduler/scheduler_service.py b/agent/tools/scheduler/scheduler_service.py new file mode 100644 index 0000000..bc338c2 --- /dev/null +++ b/agent/tools/scheduler/scheduler_service.py @@ -0,0 +1,192 @@ +""" +Background scheduler service for executing scheduled tasks +""" + +import time +import threading +from datetime import datetime, timedelta +from typing import Callable, Optional +from croniter import croniter +from common.log import logger + + +class SchedulerService: + """ + Background service that executes scheduled tasks + """ + + def __init__(self, task_store, execute_callback: Callable): + """ + Initialize scheduler service + + Args: + task_store: TaskStore instance + execute_callback: Function to call when executing a task + """ + self.task_store = task_store + self.execute_callback = execute_callback + self.running = False + self.thread = None + self._lock = threading.Lock() + + def start(self): + """Start the scheduler service""" + with self._lock: + if self.running: + logger.warning("[Scheduler] Service already running") + return + + self.running = True + self.thread = threading.Thread(target=self._run_loop, daemon=True) + self.thread.start() + logger.info("[Scheduler] Service started") + + def stop(self): + """Stop the scheduler service""" + with self._lock: + if not self.running: + return + + self.running = False + if self.thread: + self.thread.join(timeout=5) + logger.info("[Scheduler] Service stopped") + + def _run_loop(self): + """Main scheduler loop""" + logger.info("[Scheduler] Scheduler loop started") + + while self.running: + try: + self._check_and_execute_tasks() + except Exception as e: + logger.error(f"[Scheduler] Error in scheduler loop: {e}") + + # Sleep for 30 seconds between checks + time.sleep(30) + + def _check_and_execute_tasks(self): + """Check for due tasks and execute them""" + now = datetime.now() + tasks = self.task_store.list_tasks(enabled_only=True) + + for task in tasks: + try: + # Check if task is due + if self._is_task_due(task, now): + logger.info(f"[Scheduler] Executing task: {task['id']} - {task['name']}") + self._execute_task(task) + + # Update next run time + next_run = self._calculate_next_run(task, now) + if next_run: + self.task_store.update_task(task['id'], { + "next_run_at": next_run.isoformat(), + "last_run_at": now.isoformat() + }) + else: + # One-time task, disable it + self.task_store.update_task(task['id'], { + "enabled": False, + "last_run_at": now.isoformat() + }) + logger.info(f"[Scheduler] One-time task completed and disabled: {task['id']}") + except Exception as e: + logger.error(f"[Scheduler] Error processing task {task.get('id')}: {e}") + + def _is_task_due(self, task: dict, now: datetime) -> bool: + """ + Check if a task is due to run + + Args: + task: Task dictionary + now: Current datetime + + Returns: + True if task should run now + """ + next_run_str = task.get("next_run_at") + if not next_run_str: + # Calculate initial next_run_at + next_run = self._calculate_next_run(task, now) + if next_run: + self.task_store.update_task(task['id'], { + "next_run_at": next_run.isoformat() + }) + return False + return False + + try: + next_run = datetime.fromisoformat(next_run_str) + return now >= next_run + except: + return False + + def _calculate_next_run(self, task: dict, from_time: datetime) -> Optional[datetime]: + """ + Calculate next run time for a task + + Args: + task: Task dictionary + from_time: Calculate from this time + + Returns: + Next run datetime or None for one-time tasks + """ + schedule = task.get("schedule", {}) + schedule_type = schedule.get("type") + + if schedule_type == "cron": + # Cron expression + expression = schedule.get("expression") + if not expression: + return None + + try: + cron = croniter(expression, from_time) + return cron.get_next(datetime) + except Exception as e: + logger.error(f"[Scheduler] Invalid cron expression '{expression}': {e}") + return None + + elif schedule_type == "interval": + # Interval in seconds + seconds = schedule.get("seconds", 0) + if seconds <= 0: + return None + return from_time + timedelta(seconds=seconds) + + elif schedule_type == "once": + # One-time task at specific time + run_at_str = schedule.get("run_at") + if not run_at_str: + return None + + try: + run_at = datetime.fromisoformat(run_at_str) + # Only return if in the future + if run_at > from_time: + return run_at + except: + pass + return None + + return None + + def _execute_task(self, task: dict): + """ + Execute a task + + Args: + task: Task dictionary + """ + try: + # Call the execute callback + self.execute_callback(task) + except Exception as e: + logger.error(f"[Scheduler] Error executing task {task['id']}: {e}") + # Update task with error + self.task_store.update_task(task['id'], { + "last_error": str(e), + "last_error_at": datetime.now().isoformat() + }) diff --git a/agent/tools/scheduler/scheduler_tool.py b/agent/tools/scheduler/scheduler_tool.py new file mode 100644 index 0000000..764711b --- /dev/null +++ b/agent/tools/scheduler/scheduler_tool.py @@ -0,0 +1,439 @@ +""" +Scheduler tool for creating and managing scheduled tasks +""" + +import uuid +from datetime import datetime +from typing import Any, Dict, Optional +from croniter import croniter + +from agent.tools.base_tool import BaseTool, ToolResult +from bridge.context import Context, ContextType +from bridge.reply import Reply, ReplyType +from common.log import logger + + +class SchedulerTool(BaseTool): + """ + Tool for managing scheduled tasks (reminders, notifications, etc.) + """ + + name: str = "scheduler" + description: str = ( + "创建、查询和管理定时任务。支持两种任务类型：\n" + "1. 静态消息任务：定时发送预定义的消息\n" + "2. 动态工具任务：定时执行工具调用并发送结果（如搜索新闻、查询天气等）\n\n" + "使用方法：\n" + "- 创建静态消息任务：action='create', name='任务名', message='消息内容', schedule_type='interval'/'cron'/'once', schedule_value='间隔秒数/cron表达式/时间'\n" + "- 创建动态工具任务：action='create', name='任务名', tool_call={'tool_name': '工具名', 'tool_params': {...}, 'result_prefix': '前缀'}, schedule_type='interval'/'cron'/'once', schedule_value='值'\n" + "- 查询列表：action='list'\n" + "- 查看详情：action='get', task_id='任务ID'\n" + "- 删除任务：action='delete', task_id='任务ID'\n" + "- 启用任务：action='enable', task_id='任务ID'\n" + "- 禁用任务：action='disable', task_id='任务ID'\n\n" + "调度类型说明：\n" + "- interval: 固定间隔秒数（如3600表示每小时）\n" + "- cron: cron表达式（如'0 9 * * *'表示每天9点，'*/10 * * * *'表示每10分钟）\n" + "- once: 一次性任务，ISO时间格式（如'2024-12-25T09:00:00'）\n\n" + "示例：每天早上8点搜索新闻\n" + "action='create', name='每日新闻', tool_call={'tool_name': 'bocha_search', 'tool_params': {'query': '今日新闻'}, 'result_prefix': '📰 今日新闻播报'}, schedule_type='cron', schedule_value='0 8 * * *'" + ) + params: dict = { + "type": "object", + "properties": { + "action": { + "type": "string", + "enum": ["create", "list", "get", "delete", "enable", "disable"], + "description": "操作类型: create(创建), list(列表), get(查询), delete(删除), enable(启用), disable(禁用)" + }, + "task_id": { + "type": "string", + "description": "任务ID (用于 get/delete/enable/disable 操作)" + }, + "name": { + "type": "string", + "description": "任务名称 (用于 create 操作)" + }, + "message": { + "type": "string", + "description": "要发送的静态消息内容 (用于 create 操作，与tool_call二选一)" + }, + "tool_call": { + "type": "object", + "description": "要执行的工具调用 (用于 create 操作，与message二选一)", + "properties": { + "tool_name": { + "type": "string", + "description": "工具名称，如 'bocha_search'" + }, + "tool_params": { + "type": "object", + "description": "工具参数" + }, + "result_prefix": { + "type": "string", + "description": "结果前缀，如 '今日新闻：'" + } + }, + "required": ["tool_name"] + }, + "schedule_type": { + "type": "string", + "enum": ["cron", "interval", "once"], + "description": "调度类型 (用于 create 操作): cron(cron表达式), interval(固定间隔秒数), once(一次性)" + }, + "schedule_value": { + "type": "string", + "description": ( + "调度值 (用于 create 操作):\n" + "- cron类型: cron表达式，如 '0 9 * * *' (每天9点)，'*/10 * * * *' (每10分钟)\n" + "- interval类型: 间隔秒数，如 '3600' (每小时)，'10' (每10秒)\n" + "- once类型: ISO时间，如 '2024-12-25T09:00:00'" + ) + } + }, + "required": ["action"] + } + + def __init__(self, config: dict = None): + super().__init__() + self.config = config or {} + + # Will be set by agent bridge + self.task_store = None + self.current_context = None + + def execute(self, params: dict) -> ToolResult: + """ + Execute scheduler operations + + Args: + params: Dictionary containing: + - action: Operation type (create/list/get/delete/enable/disable) + - Other parameters depending on action + + Returns: + ToolResult object + """ + # Extract parameters + action = params.get("action") + kwargs = params + + if not self.task_store: + return ToolResult.fail("错误: 定时任务系统未初始化") + + try: + if action == "create": + result = self._create_task(**kwargs) + return ToolResult.success(result) + elif action == "list": + result = self._list_tasks(**kwargs) + return ToolResult.success(result) + elif action == "get": + result = self._get_task(**kwargs) + return ToolResult.success(result) + elif action == "delete": + result = self._delete_task(**kwargs) + return ToolResult.success(result) + elif action == "enable": + result = self._enable_task(**kwargs) + return ToolResult.success(result) + elif action == "disable": + result = self._disable_task(**kwargs) + return ToolResult.success(result) + else: + return ToolResult.fail(f"未知操作: {action}") + except Exception as e: + logger.error(f"[SchedulerTool] Error: {e}") + return ToolResult.fail(f"操作失败: {str(e)}") + + def _create_task(self, **kwargs) -> str: + """Create a new scheduled task""" + name = kwargs.get("name") + message = kwargs.get("message") + tool_call = kwargs.get("tool_call") + schedule_type = kwargs.get("schedule_type") + schedule_value = kwargs.get("schedule_value") + + # Validate required fields + if not name: + return "错误: 缺少任务名称 (name)" + if not message and not tool_call: + return "错误: 必须提供 message 或 tool_call 之一" + if message and tool_call: + return "错误: message 和 tool_call 不能同时提供，请选择其一" + if not schedule_type: + return "错误: 缺少调度类型 (schedule_type)" + if not schedule_value: + return "错误: 缺少调度值 (schedule_value)" + + # Validate schedule + schedule = self._parse_schedule(schedule_type, schedule_value) + if not schedule: + return f"错误: 无效的调度配置 - type: {schedule_type}, value: {schedule_value}" + + # Get context info for receiver + if not self.current_context: + return "错误: 无法获取当前对话上下文" + + context = self.current_context + + # Create task + task_id = str(uuid.uuid4())[:8] + + # Build action based on message or tool_call + if message: + action = { + "type": "send_message", + "content": message, + "receiver": context.get("receiver"), + "receiver_name": self._get_receiver_name(context), + "is_group": context.get("isgroup", False), + "channel_type": self.config.get("channel_type", "unknown") + } + else: # tool_call + action = { + "type": "tool_call", + "tool_name": tool_call.get("tool_name"), + "tool_params": tool_call.get("tool_params", {}), + "result_prefix": tool_call.get("result_prefix", ""), + "receiver": context.get("receiver"), + "receiver_name": self._get_receiver_name(context), + "is_group": context.get("isgroup", False), + "channel_type": self.config.get("channel_type", "unknown") + } + + task = { + "id": task_id, + "name": name, + "enabled": True, + "created_at": datetime.now().isoformat(), + "updated_at": datetime.now().isoformat(), + "schedule": schedule, + "action": action + } + + # Calculate initial next_run_at + next_run = self._calculate_next_run(task) + if next_run: + task["next_run_at"] = next_run.isoformat() + + # Save task + self.task_store.add_task(task) + + # Format response + schedule_desc = self._format_schedule_description(schedule) + receiver_desc = task["action"]["receiver_name"] or task["action"]["receiver"] + + if message: + content_desc = f"💬 消息: {message}" + else: + tool_name = tool_call.get("tool_name") + tool_params_str = str(tool_call.get("tool_params", {})) + prefix = tool_call.get("result_prefix", "") + content_desc = f"🔧 工具调用: {tool_name}({tool_params_str})" + if prefix: + content_desc += f"\n📝 结果前缀: {prefix}" + + return ( + f"✅ 定时任务创建成功\n\n" + f"📋 任务ID: {task_id}\n" + f"📝 名称: {name}\n" + f"⏰ 调度: {schedule_desc}\n" + f"👤 接收者: {receiver_desc}\n" + f"{content_desc}\n" + f"🕐 下次执行: {next_run.strftime('%Y-%m-%d %H:%M:%S') if next_run else '未知'}" + ) + + def _list_tasks(self, **kwargs) -> str: + """List all tasks""" + tasks = self.task_store.list_tasks() + + if not tasks: + return "📋 暂无定时任务" + + lines = [f"📋 定时任务列表 (共 {len(tasks)} 个)\n"] + + for task in tasks: + status = "✅" if task.get("enabled", True) else "❌" + schedule_desc = self._format_schedule_description(task.get("schedule", {})) + next_run = task.get("next_run_at") + next_run_str = datetime.fromisoformat(next_run).strftime('%m-%d %H:%M') if next_run else "未知" + + lines.append( + f"{status} [{task['id']}] {task['name']}\n" + f" ⏰ {schedule_desc} | 下次: {next_run_str}" + ) + + return "\n".join(lines) + + def _get_task(self, **kwargs) -> str: + """Get task details""" + task_id = kwargs.get("task_id") + if not task_id: + return "错误: 缺少任务ID (task_id)" + + task = self.task_store.get_task(task_id) + if not task: + return f"错误: 任务 '{task_id}' 不存在" + + status = "启用" if task.get("enabled", True) else "禁用" + schedule_desc = self._format_schedule_description(task.get("schedule", {})) + action = task.get("action", {}) + next_run = task.get("next_run_at") + next_run_str = datetime.fromisoformat(next_run).strftime('%Y-%m-%d %H:%M:%S') if next_run else "未知" + last_run = task.get("last_run_at") + last_run_str = datetime.fromisoformat(last_run).strftime('%Y-%m-%d %H:%M:%S') if last_run else "从未执行" + + return ( + f"📋 任务详情\n\n" + f"ID: {task['id']}\n" + f"名称: {task['name']}\n" + f"状态: {status}\n" + f"调度: {schedule_desc}\n" + f"接收者: {action.get('receiver_name', action.get('receiver'))}\n" + f"消息: {action.get('content')}\n" + f"下次执行: {next_run_str}\n" + f"上次执行: {last_run_str}\n" + f"创建时间: {datetime.fromisoformat(task['created_at']).strftime('%Y-%m-%d %H:%M:%S')}" + ) + + def _delete_task(self, **kwargs) -> str: + """Delete a task""" + task_id = kwargs.get("task_id") + if not task_id: + return "错误: 缺少任务ID (task_id)" + + task = self.task_store.get_task(task_id) + if not task: + return f"错误: 任务 '{task_id}' 不存在" + + self.task_store.delete_task(task_id) + return f"✅ 任务 '{task['name']}' ({task_id}) 已删除" + + def _enable_task(self, **kwargs) -> str: + """Enable a task""" + task_id = kwargs.get("task_id") + if not task_id: + return "错误: 缺少任务ID (task_id)" + + task = self.task_store.get_task(task_id) + if not task: + return f"错误: 任务 '{task_id}' 不存在" + + self.task_store.enable_task(task_id, True) + return f"✅ 任务 '{task['name']}' ({task_id}) 已启用" + + def _disable_task(self, **kwargs) -> str: + """Disable a task""" + task_id = kwargs.get("task_id") + if not task_id: + return "错误: 缺少任务ID (task_id)" + + task = self.task_store.get_task(task_id) + if not task: + return f"错误: 任务 '{task_id}' 不存在" + + self.task_store.enable_task(task_id, False) + return f"✅ 任务 '{task['name']}' ({task_id}) 已禁用" + + def _parse_schedule(self, schedule_type: str, schedule_value: str) -> Optional[dict]: + """Parse and validate schedule configuration""" + try: + if schedule_type == "cron": + # Validate cron expression + croniter(schedule_value) + return {"type": "cron", "expression": schedule_value} + + elif schedule_type == "interval": + # Parse interval in seconds + seconds = int(schedule_value) + if seconds <= 0: + return None + return {"type": "interval", "seconds": seconds} + + elif schedule_type == "once": + # Parse datetime + datetime.fromisoformat(schedule_value) + return {"type": "once", "run_at": schedule_value} + + except Exception as e: + logger.error(f"[SchedulerTool] Invalid schedule: {e}") + return None + + return None + + def _calculate_next_run(self, task: dict) -> Optional[datetime]: + """Calculate next run time for a task""" + schedule = task.get("schedule", {}) + schedule_type = schedule.get("type") + now = datetime.now() + + if schedule_type == "cron": + expression = schedule.get("expression") + cron = croniter(expression, now) + return cron.get_next(datetime) + + elif schedule_type == "interval": + seconds = schedule.get("seconds", 0) + from datetime import timedelta + return now + timedelta(seconds=seconds) + + elif schedule_type == "once": + run_at_str = schedule.get("run_at") + return datetime.fromisoformat(run_at_str) + + return None + + def _format_schedule_description(self, schedule: dict) -> str: + """Format schedule as human-readable description""" + schedule_type = schedule.get("type") + + if schedule_type == "cron": + expr = schedule.get("expression", "") + # Try to provide friendly description + if expr == "0 9 * * *": + return "每天 9:00" + elif expr == "0 */1 * * *": + return "每小时" + elif expr == "*/30 * * * *": + return "每30分钟" + else: + return f"Cron: {expr}" + + elif schedule_type == "interval": + seconds = schedule.get("seconds", 0) + if seconds >= 86400: + days = seconds // 86400 + return f"每 {days} 天" + elif seconds >= 3600: + hours = seconds // 3600 + return f"每 {hours} 小时" + elif seconds >= 60: + minutes = seconds // 60 + return f"每 {minutes} 分钟" + else: + return f"每 {seconds} 秒" + + elif schedule_type == "once": + run_at = schedule.get("run_at", "") + try: + dt = datetime.fromisoformat(run_at) + return f"一次性 ({dt.strftime('%Y-%m-%d %H:%M')})" + except: + return "一次性" + + return "未知" + + def _get_receiver_name(self, context: Context) -> str: + """Get receiver name from context""" + try: + msg = context.get("msg") + if msg: + if context.get("isgroup"): + return msg.other_user_nickname or "群聊" + else: + return msg.from_user_nickname or "用户" + except: + pass + return "未知" diff --git a/agent/tools/scheduler/task_store.py b/agent/tools/scheduler/task_store.py new file mode 100644 index 0000000..55e84a1 --- /dev/null +++ b/agent/tools/scheduler/task_store.py @@ -0,0 +1,200 @@ +""" +Task storage management for scheduler +""" + +import json +import os +import threading +from datetime import datetime +from typing import Dict, List, Optional +from pathlib import Path + + +class TaskStore: + """ + Manages persistent storage of scheduled tasks + """ + + def __init__(self, store_path: str = None): + """ + Initialize task store + + Args: + store_path: Path to tasks.json file. Defaults to ~/cow/scheduler/tasks.json + """ + if store_path is None: + # Default to ~/cow/scheduler/tasks.json + home = os.path.expanduser("~") + store_path = os.path.join(home, "cow", "scheduler", "tasks.json") + + self.store_path = store_path + self.lock = threading.Lock() + self._ensure_store_dir() + + def _ensure_store_dir(self): + """Ensure the storage directory exists""" + store_dir = os.path.dirname(self.store_path) + os.makedirs(store_dir, exist_ok=True) + + def load_tasks(self) -> Dict[str, dict]: + """ + Load all tasks from storage + + Returns: + Dictionary of task_id -> task_data + """ + with self.lock: + if not os.path.exists(self.store_path): + return {} + + try: + with open(self.store_path, 'r', encoding='utf-8') as f: + data = json.load(f) + return data.get("tasks", {}) + except Exception as e: + print(f"Error loading tasks: {e}") + return {} + + def save_tasks(self, tasks: Dict[str, dict]): + """ + Save all tasks to storage + + Args: + tasks: Dictionary of task_id -> task_data + """ + with self.lock: + try: + # Create backup + if os.path.exists(self.store_path): + backup_path = f"{self.store_path}.bak" + try: + with open(self.store_path, 'r') as src: + with open(backup_path, 'w') as dst: + dst.write(src.read()) + except: + pass + + # Save tasks + data = { + "version": 1, + "updated_at": datetime.now().isoformat(), + "tasks": tasks + } + + with open(self.store_path, 'w', encoding='utf-8') as f: + json.dump(data, f, ensure_ascii=False, indent=2) + except Exception as e: + print(f"Error saving tasks: {e}") + raise + + def add_task(self, task: dict) -> bool: + """ + Add a new task + + Args: + task: Task data dictionary + + Returns: + True if successful + """ + tasks = self.load_tasks() + task_id = task.get("id") + + if not task_id: + raise ValueError("Task must have an 'id' field") + + if task_id in tasks: + raise ValueError(f"Task with id '{task_id}' already exists") + + tasks[task_id] = task + self.save_tasks(tasks) + return True + + def update_task(self, task_id: str, updates: dict) -> bool: + """ + Update an existing task + + Args: + task_id: Task ID + updates: Dictionary of fields to update + + Returns: + True if successful + """ + tasks = self.load_tasks() + + if task_id not in tasks: + raise ValueError(f"Task '{task_id}' not found") + + # Update fields + tasks[task_id].update(updates) + tasks[task_id]["updated_at"] = datetime.now().isoformat() + + self.save_tasks(tasks) + return True + + def delete_task(self, task_id: str) -> bool: + """ + Delete a task + + Args: + task_id: Task ID + + Returns: + True if successful + """ + tasks = self.load_tasks() + + if task_id not in tasks: + raise ValueError(f"Task '{task_id}' not found") + + del tasks[task_id] + self.save_tasks(tasks) + return True + + def get_task(self, task_id: str) -> Optional[dict]: + """ + Get a specific task + + Args: + task_id: Task ID + + Returns: + Task data or None if not found + """ + tasks = self.load_tasks() + return tasks.get(task_id) + + def list_tasks(self, enabled_only: bool = False) -> List[dict]: + """ + List all tasks + + Args: + enabled_only: If True, only return enabled tasks + + Returns: + List of task dictionaries + """ + tasks = self.load_tasks() + task_list = list(tasks.values()) + + if enabled_only: + task_list = [t for t in task_list if t.get("enabled", True)] + + # Sort by next_run_at + task_list.sort(key=lambda t: t.get("next_run_at", float('inf'))) + + return task_list + + def enable_task(self, task_id: str, enabled: bool = True) -> bool: + """ + Enable or disable a task + + Args: + task_id: Task ID + enabled: True to enable, False to disable + + Returns: + True if successful + """ + return self.update_task(task_id, {"enabled": enabled}) diff --git a/bridge/agent_bridge.py b/bridge/agent_bridge.py index 56f9a75..ebc2ca7 100644 --- a/bridge/agent_bridge.py +++ b/bridge/agent_bridge.py @@ -180,6 +180,7 @@ class AgentBridge: self.agents = {} # session_id -> Agent instance mapping self.default_agent = None # For backward compatibility (no session_id) self.agent: Optional[Agent] = None + self.scheduler_initialized = False def create_agent(self, system_prompt: str, tools: List = None, **kwargs) -> Agent: """ Create the super agent with COW integration @@ -268,6 +269,21 @@ class AgentBridge: # Get workspace from config workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow")) + # Load environment variables from workspace .env file + env_file = os.path.join(workspace_root, '.env') + if os.path.exists(env_file): + try: + from dotenv import load_dotenv + load_dotenv(env_file, override=True) + logger.info(f"[AgentBridge] Loaded environment variables from {env_file}") + except ImportError: + logger.warning("[AgentBridge] python-dotenv not installed, skipping .env file loading") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to load .env file: {e}") + + # Migrate API keys from config.json to environment variables (if not already set) + self._migrate_config_to_env(workspace_root) + # Initialize workspace and create template files from agent.prompt import ensure_workspace, load_context_files, PromptBuilder @@ -357,7 +373,16 @@ class AgentBridge: for tool_name in tool_manager.tool_classes.keys(): try: - tool = tool_manager.create_tool(tool_name) + # Special handling for EnvConfig tool - pass agent_bridge reference + if tool_name == "env_config": + from agent.tools import EnvConfig + tool = EnvConfig({ + "workspace_dir": workspace_root, + "agent_bridge": self # Pass self reference for hot reload + }) + else: + tool = tool_manager.create_tool(tool_name) + if tool: # Apply workspace config to file operation tools if tool_name in ['read', 'write', 'edit', 'bash', 'grep', 'find', 'ls']: @@ -381,6 +406,36 @@ class AgentBridge: tools.extend(memory_tools) logger.info(f"[AgentBridge] Added {len(memory_tools)} memory tools") + # Initialize scheduler service (once) + if not self.scheduler_initialized: + try: + from agent.tools.scheduler.integration import init_scheduler + if init_scheduler(self): + self.scheduler_initialized = True + logger.info("[AgentBridge] Scheduler service initialized") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to initialize scheduler: {e}") + + # Inject scheduler dependencies into SchedulerTool instances + if self.scheduler_initialized: + try: + from agent.tools.scheduler.integration import get_task_store, get_scheduler_service + from agent.tools import SchedulerTool + + task_store = get_task_store() + scheduler_service = get_scheduler_service() + + for tool in tools: + if isinstance(tool, SchedulerTool): + tool.task_store = task_store + tool.scheduler_service = scheduler_service + if not tool.config: + tool.config = {} + tool.config["channel_type"] = conf().get("channel_type", "unknown") + logger.debug("[AgentBridge] Injected scheduler dependencies into SchedulerTool") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to inject scheduler dependencies: {e}") + logger.info(f"[AgentBridge] Loaded {len(tools)} tools: {[t.name for t in tools]}") # Load context files (SOUL.md, USER.md, etc.) @@ -449,6 +504,21 @@ class AgentBridge: # Get workspace from config workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow")) + # Load environment variables from workspace .env file + env_file = os.path.join(workspace_root, '.env') + if os.path.exists(env_file): + try: + from dotenv import load_dotenv + load_dotenv(env_file, override=True) + logger.info(f"[AgentBridge] Loaded environment variables from {env_file} for session {session_id}") + except ImportError: + logger.warning(f"[AgentBridge] python-dotenv not installed, skipping .env file loading for session {session_id}") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to load .env file for session {session_id}: {e}") + + # Migrate API keys from config.json to environment variables (if not already set) + self._migrate_config_to_env(workspace_root) + # Initialize workspace from agent.prompt import ensure_workspace, load_context_files, PromptBuilder @@ -550,6 +620,36 @@ class AgentBridge: if memory_tools: tools.extend(memory_tools) + + # Initialize scheduler service (once, if not already initialized) + if not self.scheduler_initialized: + try: + from agent.tools.scheduler.integration import init_scheduler + if init_scheduler(self): + self.scheduler_initialized = True + logger.info(f"[AgentBridge] Scheduler service initialized for session {session_id}") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to initialize scheduler for session {session_id}: {e}") + + # Inject scheduler dependencies into SchedulerTool instances + if self.scheduler_initialized: + try: + from agent.tools.scheduler.integration import get_task_store, get_scheduler_service + from agent.tools import SchedulerTool + + task_store = get_task_store() + scheduler_service = get_scheduler_service() + + for tool in tools: + if isinstance(tool, SchedulerTool): + tool.task_store = task_store + tool.scheduler_service = scheduler_service + if not tool.config: + tool.config = {} + tool.config["channel_type"] = conf().get("channel_type", "unknown") + logger.debug(f"[AgentBridge] Injected scheduler dependencies for session {session_id}") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to inject scheduler dependencies for session {session_id}: {e}") # Load context files context_files = load_context_files(workspace_root) @@ -667,6 +767,17 @@ class AgentBridge: if not agent: return Reply(ReplyType.ERROR, "Failed to initialize super agent") + # Attach context to scheduler tool if present + if context and agent.tools: + for tool in agent.tools: + if tool.name == "scheduler": + try: + from agent.tools.scheduler.integration import attach_scheduler_to_tool + attach_scheduler_to_tool(tool, context) + except Exception as e: + logger.warning(f"[AgentBridge] Failed to attach context to scheduler: {e}") + break + # Use agent's run_stream method response = agent.run_stream( user_message=query, @@ -680,6 +791,72 @@ class AgentBridge: logger.error(f"Agent reply error: {e}") return Reply(ReplyType.ERROR, f"Agent error: {str(e)}") + def _migrate_config_to_env(self, workspace_root: str): + """ + Migrate API keys from config.json to .env file if not already set + + Args: + workspace_root: Workspace directory path + """ + from config import conf + import os + + # Mapping from config.json keys to environment variable names + key_mapping = { + "open_ai_api_key": "OPENAI_API_KEY", + "open_ai_api_base": "OPENAI_API_BASE", + "gemini_api_key": "GEMINI_API_KEY", + "claude_api_key": "CLAUDE_API_KEY", + "linkai_api_key": "LINKAI_API_KEY", + } + + env_file = os.path.join(workspace_root, '.env') + + # Read existing env vars from .env file + existing_env_vars = {} + if os.path.exists(env_file): + try: + with open(env_file, 'r', encoding='utf-8') as f: + for line in f: + line = line.strip() + if line and not line.startswith('#') and '=' in line: + key, _ = line.split('=', 1) + existing_env_vars[key.strip()] = True + except Exception as e: + logger.warning(f"[AgentBridge] Failed to read .env file: {e}") + + # Check which keys need to be migrated + keys_to_migrate = {} + for config_key, env_key in key_mapping.items(): + # Skip if already in .env file + if env_key in existing_env_vars: + continue + + # Get value from config.json + value = conf().get(config_key, "") + if value and value.strip(): # Only migrate non-empty values + keys_to_migrate[env_key] = value.strip() + + # Write new keys to .env file + if keys_to_migrate: + try: + # Ensure .env file exists + if not os.path.exists(env_file): + os.makedirs(os.path.dirname(env_file), exist_ok=True) + open(env_file, 'a').close() + + # Append new keys + with open(env_file, 'a', encoding='utf-8') as f: + f.write('\n# Auto-migrated from config.json\n') + for key, value in keys_to_migrate.items(): + f.write(f'{key}={value}\n') + # Also set in current process + os.environ[key] = value + + logger.info(f"[AgentBridge] Migrated {len(keys_to_migrate)} API keys from config.json to .env: {list(keys_to_migrate.keys())}") + except Exception as e: + logger.warning(f"[AgentBridge] Failed to migrate API keys: {e}") + def clear_session(self, session_id: str): """ Clear a specific session's agent and conversation history @@ -695,4 +872,43 @@ class AgentBridge: """Clear all agent sessions""" logger.info(f"[AgentBridge] Clearing all sessions ({len(self.agents)} total)") self.agents.clear() - self.default_agent = None \ No newline at end of file + self.default_agent = None + + def refresh_all_skills(self) -> int: + """ + Refresh skills in all agent instances after environment variable changes. + This allows hot-reload of skills without restarting the agent. + + Returns: + Number of agent instances refreshed + """ + import os + from dotenv import load_dotenv + from config import conf + + # Reload environment variables from .env file + workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow")) + env_file = os.path.join(workspace_root, '.env') + + if os.path.exists(env_file): + load_dotenv(env_file, override=True) + logger.info(f"[AgentBridge] Reloaded environment variables from {env_file}") + + refreshed_count = 0 + + # Refresh default agent + if self.default_agent and hasattr(self.default_agent, 'skill_manager'): + self.default_agent.skill_manager.refresh_skills() + refreshed_count += 1 + logger.info("[AgentBridge] Refreshed skills in default agent") + + # Refresh all session agents + for session_id, agent in self.agents.items(): + if hasattr(agent, 'skill_manager'): + agent.skill_manager.refresh_skills() + refreshed_count += 1 + + if refreshed_count > 0: + logger.info(f"[AgentBridge] Refreshed skills in {refreshed_count} agent instance(s)") + + return refreshed_count \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index aae96c6..848acd2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -9,6 +9,9 @@ pre-commit web.py linkai>=0.0.6.0 agentmesh-sdk>=0.1.3 +python-dotenv>=1.0.0 +PyYAML>=6.0 +croniter>=2.0.0 # feishu websocket mode lark-oapi \ No newline at end of file diff --git a/skills/bocha-search/SKILL.md b/skills/bocha-search/SKILL.md new file mode 100644 index 0000000..ca52d6c --- /dev/null +++ b/skills/bocha-search/SKILL.md @@ -0,0 +1,91 @@ +--- +name: bocha-search +description: High-quality web search with AI-optimized results. Use when user needs to search the internet for current information, news, or research topics. +homepage: https://open.bocha.cn/ +metadata: + emoji: 🔍 + requires: + bins: ["curl"] + env: ["BOCHA_API_KEY"] + primaryEnv: "BOCHA_API_KEY" +--- + +# Bocha Search + +High-quality web search powered by Bocha AI, optimized for AI consumption. Returns web pages, images, and detailed metadata. + +## Setup + +This skill requires a Bocha API key. If not configured: + +1. Visit https://open.bocha.cn to get an API key +2. Set the key using: `env_config(action="set", key="BOCHA_API_KEY", value="your-key")` +3. Or manually add to `~/cow/.env`: `BOCHA_API_KEY=your-key` + +## Usage + +**Important**: Scripts are located relative to this skill's base directory. + +When you see this skill in ``, note the `` path. + +```bash +# General pattern: +bash "/scripts/search.sh" "" [count] [freshness] [summary] + +# Parameters: +# - query: Search query (required) +# - count: Number of results (1-50, default: 10) +# - freshness: Time range filter (default: noLimit) +# Options: noLimit, oneDay, oneWeek, oneMonth, oneYear, YYYY-MM-DD..YYYY-MM-DD +# - summary: Include text summary (true/false, default: false) +``` + +## Examples + +### Basic search +```bash +bash "/scripts/search.sh" "latest AI news" +``` + +### Search with more results +```bash +bash "/scripts/search.sh" "Python tutorials" 20 +``` + +### Search recent content with summary +```bash +bash "/scripts/search.sh" "阿里巴巴ESG报告" 10 oneWeek true +``` + +### Search specific date range +```bash +bash "/scripts/search.sh" "tech news" 15 "2025-01-01..2025-02-01" +``` + +## Response Format + +The API returns structured data compatible with Bing Search API: + +**Web Pages** (in `data.webPages.value`): +- `name`: Page title +- `url`: Page URL +- `snippet`: Short description +- `summary`: Full text summary (if requested) +- `siteName`: Website name +- `siteIcon`: Website icon URL +- `datePublished`: Publication date (UTC+8) +- `language`: Page language + +**Images** (in `data.images.value`): +- `contentUrl`: Image URL +- `hostPageUrl`: Source page URL +- `width`, `height`: Image dimensions +- `thumbnailUrl`: Thumbnail URL + +## Notes + +- **Optimized for AI**: Results include summaries and structured metadata +- **Time range**: Use `noLimit` for best results (algorithm auto-optimizes time range) +- **Timeout**: 30 seconds +- **Rate limits**: Check your API plan at https://open.bocha.cn +- **Response format**: Compatible with Bing Search API for easy integration diff --git a/skills/bocha-search/scripts/search.sh b/skills/bocha-search/scripts/search.sh new file mode 100755 index 0000000..e803a19 --- /dev/null +++ b/skills/bocha-search/scripts/search.sh @@ -0,0 +1,75 @@ +#!/usr/bin/env bash +# Bocha Web Search API wrapper +# API Docs: https://open.bocha.cn/ + +set -euo pipefail + +query="${1:-}" +count="${2:-10}" +freshness="${3:-noLimit}" +summary="${4:-false}" + +if [ -z "$query" ]; then + echo '{"error": "Query is required", "usage": "bash search.sh [count] [freshness] [summary]"}' + exit 1 +fi + +if [ -z "${BOCHA_API_KEY:-}" ]; then + echo '{"error": "BOCHA_API_KEY environment variable is not set", "help": "Visit https://open.bocha.cn to get an API key"}' + exit 1 +fi + +# Validate count (1-50) +if ! [[ "$count" =~ ^[0-9]+$ ]] || [ "$count" -lt 1 ] || [ "$count" -gt 50 ]; then + count=10 +fi + +# Build JSON request body +request_body=$(cat <&1) + +curl_exit_code=$? + +if [ $curl_exit_code -ne 0 ]; then + echo "{\"error\": \"Failed to call Bocha API\", \"details\": \"$response\"}" + exit 1 +fi + +# Simple JSON validation - check if response starts with { or [ +if [[ ! "$response" =~ ^[[:space:]]*[\{\[] ]]; then + echo "{\"error\": \"Invalid JSON response from API\", \"response\": \"$response\"}" + exit 1 +fi + +# Extract API code using grep and sed (basic JSON parsing) +api_code=$(echo "$response" | grep -o '"code"[[:space:]]*:[[:space:]]*[0-9]*' | grep -o '[0-9]*' | head -1) + +# If code extraction failed or code is not 200, check for error +if [ -n "$api_code" ] && [ "$api_code" != "200" ]; then + # Try to extract error message + api_msg=$(echo "$response" | grep -o '"msg"[[:space:]]*:[[:space:]]*"[^"]*"' | sed 's/"msg"[[:space:]]*:[[:space:]]*"\(.*\)"/\1/' | head -1) + if [ -z "$api_msg" ]; then + api_msg="Unknown error" + fi + echo "{\"error\": \"API returned error\", \"code\": $api_code, \"message\": \"$api_msg\"}" + exit 1 +fi + +# Return the full response +echo "$response" diff --git a/skills/skill-creator/SKILL.md b/skills/skill-creator/SKILL.md index 4a09bc4..9092cb9 100644 --- a/skills/skill-creator/SKILL.md +++ b/skills/skill-creator/SKILL.md @@ -243,20 +243,87 @@ If you used `--examples`, delete any placeholder files that are not needed for t ##### Frontmatter -Write the YAML frontmatter with `name` and `description`: +Write the YAML frontmatter with `name`, `description`, and optional `metadata`: - `name`: The skill name - `description`: This is the primary triggering mechanism for your skill, and helps the agent understand when to use the skill. - Include both what the Skill does and specific triggers/contexts for when to use it. - Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to the agent. - Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when the agent needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks" +- `metadata`: (Optional) Specify requirements and configuration + - `requires.bins`: Required binaries (e.g., `["curl", "jq"]`) + - `requires.env`: Required environment variables (e.g., `["OPENAI_API_KEY"]`) + - `primaryEnv`: Primary environment variable name (for API keys) + - `always`: Set to `true` to always load regardless of requirements + - `emoji`: Skill icon (optional) -Do not include any other fields in YAML frontmatter. +**API Key Requirements**: + +If your skill needs an API key, declare it in metadata: + +```yaml +--- +name: my-search +description: Search using MyAPI +metadata: + requires: + bins: ["curl"] + env: ["MYAPI_KEY"] + primaryEnv: "MYAPI_KEY" +--- +``` + +**Auto-enable rule**: Skills are automatically enabled when required environment variables are set, and automatically disabled when missing. No manual configuration needed. ##### Body Write instructions for using the skill and its bundled resources. +**If your skill requires an API key**, include setup instructions in the body: + +```markdown +## Setup + +This skill requires an API key from [Service Name]. + +1. Visit https://service.com to get an API key +2. Configure it using: `env_config(action="set", key="SERVICE_API_KEY", value="your-key")` +3. Or manually add to `~/cow/.env`: `SERVICE_API_KEY=your-key` +4. Restart the agent for changes to take effect + +## Usage +... +``` + +The bash script should check for the key and provide helpful error messages: + +```bash +#!/usr/bin/env bash +if [ -z "${SERVICE_API_KEY:-}" ]; then + echo "Error: SERVICE_API_KEY not set" + echo "Please configure your API key first (see SKILL.md)" + exit 1 +fi + +curl -H "Authorization: Bearer $SERVICE_API_KEY" ... +``` + +**Script Path Convention**: + +When writing SKILL.md instructions, remember that: +- Skills are listed in `` with a `` path +- Scripts should be referenced as: `/scripts/script_name.sh` +- The AI will see the base_dir and can construct the full path + +Example instruction in SKILL.md: +```markdown +## Usage + +Scripts are in this skill's base directory (shown in skill listing). + +bash "/scripts/my_script.sh" +``` + ### Step 5: Validate (Optional) Validate skill format: diff --git a/skills/web-fetch/SKILL.md b/skills/web-fetch/SKILL.md index 05d9650..39315fb 100644 --- a/skills/web-fetch/SKILL.md +++ b/skills/web-fetch/SKILL.md @@ -1,11 +1,12 @@ --- name: web-fetch -description: Fetch and extract readable content from web pages +description: Fetch and extract readable content from web pages. Use for lightweight page access without browser automation. homepage: https://github.com/zhayujie/chatgpt-on-wechat metadata: emoji: 🌐 requires: bins: ["curl"] + always: true --- # Web Fetch @@ -14,10 +15,16 @@ Fetch and extract readable content from web pages using curl and basic text proc ## Usage -Use the provided script to fetch a URL and extract its content: +**Important**: Scripts are located relative to this skill's base directory. + +When you see this skill in ``, note the `` path. ```bash -bash scripts/fetch.sh [output_file] +# General pattern: +bash "/scripts/fetch.sh" [output_file] + +# Example (replace with actual path from skill listing): +bash "~/chatgpt-on-wechat/skills/web-fetch/scripts/fetch.sh" "https://example.com" ``` **Parameters:** @@ -31,18 +38,18 @@ bash scripts/fetch.sh [output_file] ### Fetch a web page ```bash -bash scripts/fetch.sh "https://example.com" +bash "/scripts/fetch.sh" "https://example.com" ``` ### Save to file ```bash -bash scripts/fetch.sh "https://example.com" output.txt +bash "/scripts/fetch.sh" "https://example.com" output.txt cat output.txt ``` ## Notes -- Uses curl for HTTP requests (timeout: 20s) +- Uses curl for HTTP requests (timeout: 10s) - Extracts title and basic text content - Removes HTML tags and scripts - Works with any standard web page diff --git a/skills/web-fetch/scripts/fetch.sh b/skills/web-fetch/scripts/fetch.sh index b13a41d..1713b26 100755 --- a/skills/web-fetch/scripts/fetch.sh +++ b/skills/web-fetch/scripts/fetch.sh @@ -19,7 +19,7 @@ if [[ ! "$url" =~ ^https?:// ]]; then fi # Fetch the page with curl -html=$(curl -sS -L --max-time 20 \ +html=$(curl -sS -L --max-time 10 \ -H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36" \ -H "Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8" \ "$url" 2>&1) || { From 77c2bfcc1e1c7ed6e699894c3de47e472e47fc03 Mon Sep 17 00:00:00 2001 From: zhayujie Date: Sun, 1 Feb 2026 19:40:27 +0800 Subject: [PATCH 08/11] fix: scheduler in feishu --- agent/tools/__init__.py | 46 +++++++++++++++++++++------- agent/tools/scheduler/integration.py | 23 ++++++++++++-- channel/feishu/feishu_channel.py | 9 ++++-- 3 files changed, 63 insertions(+), 15 deletions(-) diff --git a/agent/tools/__init__.py b/agent/tools/__init__.py index fb9d828..b449c25 100644 --- a/agent/tools/__init__.py +++ b/agent/tools/__init__.py @@ -13,46 +13,70 @@ from agent.tools.ls.ls import Ls from agent.tools.memory.memory_search import MemorySearchTool from agent.tools.memory.memory_get import MemoryGetTool -# Import env config tool -from agent.tools.env_config.env_config import EnvConfig - # Import tools with optional dependencies def _import_optional_tools(): """Import tools that have optional dependencies""" + from common.log import logger tools = {} + # EnvConfig Tool (requires python-dotenv) + try: + from agent.tools.env_config.env_config import EnvConfig + tools['EnvConfig'] = EnvConfig + except ImportError as e: + logger.error( + f"[Tools] EnvConfig tool not loaded - missing dependency: {e}\n" + f" To enable environment variable management, run:\n" + f" pip install python-dotenv>=1.0.0" + ) + except Exception as e: + logger.error(f"[Tools] EnvConfig tool failed to load: {e}") + # Scheduler Tool (requires croniter) try: from agent.tools.scheduler.scheduler_tool import SchedulerTool tools['SchedulerTool'] = SchedulerTool - except ImportError: - pass + except ImportError as e: + logger.error( + f"[Tools] Scheduler tool not loaded - missing dependency: {e}\n" + f" To enable scheduled tasks, run:\n" + f" pip install croniter>=2.0.0" + ) + except Exception as e: + logger.error(f"[Tools] Scheduler tool failed to load: {e}") # Google Search (requires requests) try: from agent.tools.google_search.google_search import GoogleSearch tools['GoogleSearch'] = GoogleSearch - except ImportError: - pass + except ImportError as e: + logger.warning(f"[Tools] GoogleSearch tool not loaded - missing dependency: {e}") + except Exception as e: + logger.error(f"[Tools] GoogleSearch tool failed to load: {e}") # File Save (may have dependencies) try: from agent.tools.file_save.file_save import FileSave tools['FileSave'] = FileSave - except ImportError: - pass + except ImportError as e: + logger.warning(f"[Tools] FileSave tool not loaded - missing dependency: {e}") + except Exception as e: + logger.error(f"[Tools] FileSave tool failed to load: {e}") # Terminal (basic, should work) try: from agent.tools.terminal.terminal import Terminal tools['Terminal'] = Terminal - except ImportError: - pass + except ImportError as e: + logger.warning(f"[Tools] Terminal tool not loaded - missing dependency: {e}") + except Exception as e: + logger.error(f"[Tools] Terminal tool failed to load: {e}") return tools # Load optional tools _optional_tools = _import_optional_tools() +EnvConfig = _optional_tools.get('EnvConfig') SchedulerTool = _optional_tools.get('SchedulerTool') GoogleSearch = _optional_tools.get('GoogleSearch') FileSave = _optional_tools.get('FileSave') diff --git a/agent/tools/scheduler/integration.py b/agent/tools/scheduler/integration.py index 0f8ac35..1f345bf 100644 --- a/agent/tools/scheduler/integration.py +++ b/agent/tools/scheduler/integration.py @@ -101,12 +101,21 @@ def _execute_send_message(task: dict, agent_bridge): context["isgroup"] = is_group context["session_id"] = receiver - # For web channel, generate a virtual request_id + # Channel-specific context setup if channel_type == "web": + # Web channel needs request_id import uuid request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}" context["request_id"] = request_id logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}") + elif channel_type == "feishu": + # Feishu channel: for scheduled tasks, send as new message (no msg_id to reply to) + # Use chat_id for groups, open_id for private chats + context["receive_id_type"] = "chat_id" if is_group else "open_id" + # Keep isgroup as is, but set msg to None (no original message to reply to) + # Feishu channel will detect this and send as new message instead of reply + context["msg"] = None + logger.debug(f"[Scheduler] Feishu: receive_id_type={context['receive_id_type']}, is_group={is_group}, receiver={receiver}") # Create reply reply = Reply(ReplyType.TEXT, content) @@ -128,9 +137,13 @@ def _execute_send_message(task: dict, agent_bridge): logger.error(f"[Scheduler] Failed to create channel: {channel_type}") except Exception as e: logger.error(f"[Scheduler] Failed to send message: {e}") + import traceback + logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}") except Exception as e: logger.error(f"[Scheduler] Error in _execute_send_message: {e}") + import traceback + logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}") def _execute_tool_call(task: dict, agent_bridge): @@ -187,12 +200,18 @@ def _execute_tool_call(task: dict, agent_bridge): context["isgroup"] = is_group context["session_id"] = receiver - # For web channel, generate a virtual request_id + # Channel-specific context setup if channel_type == "web": + # Web channel needs request_id import uuid request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}" context["request_id"] = request_id logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}") + elif channel_type == "feishu": + # Feishu channel: for scheduled tasks, send as new message (no msg_id to reply to) + context["receive_id_type"] = "chat_id" if is_group else "open_id" + context["msg"] = None + logger.debug(f"[Scheduler] Feishu: receive_id_type={context['receive_id_type']}, is_group={is_group}, receiver={receiver}") reply = Reply(ReplyType.TEXT, content) diff --git a/channel/feishu/feishu_channel.py b/channel/feishu/feishu_channel.py index 16248de..e971302 100644 --- a/channel/feishu/feishu_channel.py +++ b/channel/feishu/feishu_channel.py @@ -208,8 +208,12 @@ class FeiShuChanel(ChatChannel): return msg_type = "image" content_key = "image_key" - if is_group: - # 群聊中直接回复 + + # Check if we can reply to an existing message (need msg_id) + can_reply = is_group and msg and hasattr(msg, 'msg_id') and msg.msg_id + + if can_reply: + # 群聊中回复已有消息 url = f"https://open.feishu.cn/open-apis/im/v1/messages/{msg.msg_id}/reply" data = { "msg_type": msg_type, @@ -217,6 +221,7 @@ class FeiShuChanel(ChatChannel): } res = requests.post(url=url, headers=headers, json=data, timeout=(5, 10)) else: + # 发送新消息（私聊或群聊中无msg_id的情况，如定时任务） url = "https://open.feishu.cn/open-apis/im/v1/messages" params = {"receive_id_type": context.get("receive_id_type") or "open_id"} data = { From a8d5309c904d5e8b0fdebc015dc8c59a9c14dcf2 Mon Sep 17 00:00:00 2001 From: zhayujie Date: Mon, 2 Feb 2026 00:42:39 +0800 Subject: [PATCH 09/11] feat: add skills and upgrade feishu/dingtalk channel --- agent/prompt/builder.py | 4 +- agent/protocol/agent.py | 3 + agent/protocol/agent_stream.py | 134 ++++++++- agent/skills/loader.py | 43 +++ agent/tools/__init__.py | 2 + agent/tools/bash/bash.py | 78 ++++- agent/tools/env_config/env_config.py | 11 +- agent/tools/ls/ls.py | 7 + agent/tools/read/read.py | 129 ++++++-- agent/tools/scheduler/README.md | 49 +-- agent/tools/scheduler/integration.py | 195 +++++++++++- agent/tools/scheduler/scheduler_service.py | 28 ++ agent/tools/scheduler/scheduler_tool.py | 137 ++++----- agent/tools/send/__init__.py | 3 + agent/tools/send/send.py | 159 ++++++++++ bridge/agent_bridge.py | 147 ++++++--- channel/chat_channel.py | 116 +++++++- channel/dingtalk/dingtalk_channel.py | 185 +++++++++++- channel/dingtalk/dingtalk_message.py | 1 + channel/feishu/feishu_channel.py | 275 ++++++++++++++++- channel/feishu/feishu_message.py | 95 ++++++ config-template.json | 4 +- config.py | 1 + models/claudeapi/claude_api_bot.py | 13 +- skills/linkai-agent/README.md | 297 +++++++++++++++++++ skills/linkai-agent/SKILL.md | 165 +++++++++++ skills/linkai-agent/config.json.template | 14 + skills/linkai-agent/scripts/call.sh | 138 +++++++++ skills/openai-image-vision/EXAMPLE.md | 168 +++++++++++ skills/openai-image-vision/README.md | 178 +++++++++++ skills/openai-image-vision/SKILL.md | 119 ++++++++ skills/openai-image-vision/scripts/vision.sh | 233 +++++++++++++++ 32 files changed, 2931 insertions(+), 200 deletions(-) create mode 100644 agent/tools/send/__init__.py create mode 100644 agent/tools/send/send.py create mode 100644 skills/linkai-agent/README.md create mode 100644 skills/linkai-agent/SKILL.md create mode 100644 skills/linkai-agent/config.json.template create mode 100755 skills/linkai-agent/scripts/call.sh create mode 100644 skills/openai-image-vision/EXAMPLE.md create mode 100644 skills/openai-image-vision/README.md create mode 100644 skills/openai-image-vision/SKILL.md create mode 100755 skills/openai-image-vision/scripts/vision.sh diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py index 25179ba..1727c0b 100644 --- a/agent/prompt/builder.py +++ b/agent/prompt/builder.py @@ -237,8 +237,8 @@ def _build_tooling_section(tools: List[Any], language: str) -> List[str]: "叙述要求: 保持简洁、信息密度高，避免重复显而易见的步骤。", "", "完成标准:", - "- 确保用户的需求得到实际解决，而不仅仅是制定计划", - "- 当任务需要多次工具调用时，持续推进直到完成", + "- 确保用户的需求得到实际解决，而不仅仅是制定计划。", + "- 当任务需要多次工具调用时，持续推进直到完成, 解决完后向用户报告结果或回复用户的问题", "- 每次工具调用后，评估是否已获得足够信息来推进或完成任务", "- 避免重复调用相同的工具和相同参数获取相同的信息，除非用户明确要求", "", diff --git a/agent/protocol/agent.py b/agent/protocol/agent.py index 5c4f994..6759ebc 100644 --- a/agent/protocol/agent.py +++ b/agent/protocol/agent.py @@ -360,6 +360,9 @@ class Agent: # Update agent's message history from executor self.messages = executor.messages + + # Store executor reference for agent_bridge to access files_to_send + self.stream_executor = executor # Execute all post-process tools self._execute_post_process_tools() diff --git a/agent/protocol/agent_stream.py b/agent/protocol/agent_stream.py index 7ea1eeb..49812b9 100644 --- a/agent/protocol/agent_stream.py +++ b/agent/protocol/agent_stream.py @@ -58,6 +58,9 @@ class AgentStreamExecutor: # Tool failure tracking for retry protection self.tool_failure_history = [] # List of (tool_name, args_hash, success) tuples + + # Track files to send (populated by read tool) + self.files_to_send = [] # List of file metadata dicts def _emit_event(self, event_type: str, data: dict = None): """Emit event""" @@ -191,21 +194,47 @@ class AgentStreamExecutor: logger.info( f"Memory flush recommended: tokens={current_tokens}, turns={self.agent.memory_manager.flush_manager.turn_count}") - # Call LLM - assistant_msg, tool_calls = self._call_llm_stream() + # Call LLM (enable retry_on_empty for better reliability) + assistant_msg, tool_calls = self._call_llm_stream(retry_on_empty=True) final_response = assistant_msg # No tool calls, end loop if not tool_calls: # 检查是否返回了空响应 if not assistant_msg: - logger.warning(f"[Agent] LLM returned empty response (no content and no tool calls)") + logger.warning(f"[Agent] LLM returned empty response after retry (no content and no tool calls)") + logger.info(f"[Agent] This usually happens when LLM thinks the task is complete after tool execution") - # 生成通用的友好提示 - final_response = ( - "抱歉，我暂时无法生成回复。请尝试换一种方式描述你的需求，或稍后再试。" - ) - logger.info(f"Generated fallback response for empty LLM output") + # 如果之前有工具调用，强制要求 LLM 生成文本回复 + if turn > 1: + logger.info(f"[Agent] Requesting explicit response from LLM...") + + # 添加一条消息，明确要求回复用户 + self.messages.append({ + "role": "user", + "content": [{ + "type": "text", + "text": "请向用户说明刚才工具执行的结果或回答用户的问题。" + }] + }) + + # 再调用一次 LLM + assistant_msg, tool_calls = self._call_llm_stream(retry_on_empty=False) + final_response = assistant_msg + + # 如果还是空，才使用 fallback + if not assistant_msg and not tool_calls: + logger.warning(f"[Agent] Still empty after explicit request") + final_response = ( + "抱歉，我暂时无法生成回复。请尝试换一种方式描述你的需求，或稍后再试。" + ) + logger.info(f"Generated fallback response for empty LLM output") + else: + # 第一轮就空回复，直接 fallback + final_response = ( + "抱歉，我暂时无法生成回复。请尝试换一种方式描述你的需求，或稍后再试。" + ) + logger.info(f"Generated fallback response for empty LLM output") else: logger.info(f"💭 {assistant_msg[:150]}{'...' if len(assistant_msg) > 150 else ''}") @@ -235,6 +264,14 @@ class AgentStreamExecutor: result = self._execute_tool(tool_call) tool_results.append(result) + # Check if this is a file to send (from read tool) + if result.get("status") == "success" and isinstance(result.get("result"), dict): + result_data = result.get("result") + if result_data.get("type") == "file_to_send": + # Store file metadata for later sending + self.files_to_send.append(result_data) + logger.info(f"📎 检测到待发送文件: {result_data.get('file_name', result_data.get('path'))}") + # Check for critical error - abort entire conversation if result.get("status") == "critical_error": logger.error(f"💥 检测到严重错误，终止对话") @@ -392,6 +429,7 @@ class AgentStreamExecutor: # Streaming response full_content = "" tool_calls_buffer = {} # {index: {id, name, arguments}} + stop_reason = None # Track why the stream stopped try: stream = self.model.call_stream(request) @@ -404,21 +442,47 @@ class AgentStreamExecutor: if isinstance(error_data, dict): error_msg = error_data.get("message", chunk.get("message", "Unknown error")) error_code = error_data.get("code", "") + error_type = error_data.get("type", "") else: error_msg = chunk.get("message", str(error_data)) error_code = "" + error_type = "" status_code = chunk.get("status_code", "N/A") - logger.error(f"API Error: {error_msg} (Status: {status_code}, Code: {error_code})") - logger.error(f"Full error chunk: {chunk}") - # Raise exception with full error message for retry logic - raise Exception(f"{error_msg} (Status: {status_code})") + # Log error with all available information + logger.error(f"🔴 Stream API Error:") + logger.error(f" Message: {error_msg}") + logger.error(f" Status Code: {status_code}") + logger.error(f" Error Code: {error_code}") + logger.error(f" Error Type: {error_type}") + logger.error(f" Full chunk: {chunk}") + + # Check if this is a context overflow error (keyword-based, works for all models) + # Don't rely on specific status codes as different providers use different codes + error_msg_lower = error_msg.lower() + is_overflow = any(keyword in error_msg_lower for keyword in [ + 'context length exceeded', 'maximum context length', 'prompt is too long', + 'context overflow', 'context window', 'too large', 'exceeds model context', + 'request_too_large', 'request exceeds the maximum size', 'tokens exceed' + ]) + + if is_overflow: + # Mark as context overflow for special handling + raise Exception(f"[CONTEXT_OVERFLOW] {error_msg} (Status: {status_code})") + else: + # Raise exception with full error message for retry logic + raise Exception(f"{error_msg} (Status: {status_code}, Code: {error_code}, Type: {error_type})") # Parse chunk if isinstance(chunk, dict) and "choices" in chunk: choice = chunk["choices"][0] delta = choice.get("delta", {}) + + # Capture finish_reason if present + finish_reason = choice.get("finish_reason") + if finish_reason: + stop_reason = finish_reason # Handle text content if "content" in delta and delta["content"]: @@ -449,9 +513,46 @@ class AgentStreamExecutor: tool_calls_buffer[index]["arguments"] += func["arguments"] except Exception as e: - error_str = str(e).lower() + error_str = str(e) + error_str_lower = error_str.lower() + + # Check if error is context overflow (non-retryable, needs session reset) + # Method 1: Check for special marker (set in stream error handling above) + is_context_overflow = '[context_overflow]' in error_str_lower + + # Method 2: Fallback to keyword matching for non-stream errors + if not is_context_overflow: + is_context_overflow = any(keyword in error_str_lower for keyword in [ + 'context length exceeded', 'maximum context length', 'prompt is too long', + 'context overflow', 'context window', 'too large', 'exceeds model context', + 'request_too_large', 'request exceeds the maximum size' + ]) + + # Check if error is message format error (incomplete tool_use/tool_result pairs) + # This happens when previous conversation had tool failures + is_message_format_error = any(keyword in error_str_lower for keyword in [ + 'tool_use', 'tool_result', 'without', 'immediately after', + 'corresponding', 'must have', 'each' + ]) and 'status: 400' in error_str_lower + + if is_context_overflow or is_message_format_error: + error_type = "context overflow" if is_context_overflow else "message format error" + logger.error(f"💥 {error_type} detected: {e}") + # Clear message history to recover + logger.warning("🔄 Clearing conversation history to recover") + self.messages.clear() + # Raise special exception with user-friendly message + if is_context_overflow: + raise Exception( + "抱歉，对话历史过长导致上下文溢出。我已清空历史记录，请重新描述你的需求。" + ) + else: + raise Exception( + "抱歉，之前的对话出现了问题。我已清空历史记录，请重新发送你的消息。" + ) + # Check if error is retryable (timeout, connection, rate limit, server busy, etc.) - is_retryable = any(keyword in error_str for keyword in [ + is_retryable = any(keyword in error_str_lower for keyword in [ 'timeout', 'timed out', 'connection', 'network', 'rate limit', 'overloaded', 'unavailable', 'busy', 'retry', '429', '500', '502', '503', '504', '512' @@ -505,11 +606,12 @@ class AgentStreamExecutor: # Check for empty response and retry once if enabled if retry_on_empty and not full_content and not tool_calls: - logger.warning(f"⚠️ LLM returned empty response, retrying once...") + logger.warning(f"⚠️ LLM returned empty response (stop_reason: {stop_reason}), retrying once...") self._emit_event("message_end", { "content": "", "tool_calls": [], - "empty_retry": True + "empty_retry": True, + "stop_reason": stop_reason }) # Retry without retry flag to avoid infinite loop return self._call_llm_stream( diff --git a/agent/skills/loader.py b/agent/skills/loader.py index 0bc8f4a..5d67c47 100644 --- a/agent/skills/loader.py +++ b/agent/skills/loader.py @@ -137,6 +137,10 @@ class SkillLoader: name = frontmatter.get('name', parent_dir_name) description = frontmatter.get('description', '') + # Special handling for linkai-agent: dynamically load apps from config.json + if name == 'linkai-agent': + description = self._load_linkai_agent_description(skill_dir, description) + if not description or not description.strip(): diagnostics.append(f"Skill {name} has no description: {file_path}") return LoadSkillsResult(skills=[], diagnostics=diagnostics) @@ -161,6 +165,45 @@ class SkillLoader: return LoadSkillsResult(skills=[skill], diagnostics=diagnostics) + def _load_linkai_agent_description(self, skill_dir: str, default_description: str) -> str: + """ + Dynamically load LinkAI agent description from config.json + + :param skill_dir: Skill directory + :param default_description: Default description from SKILL.md + :return: Dynamic description with app list + """ + import json + + config_path = os.path.join(skill_dir, "config.json") + template_path = os.path.join(skill_dir, "config.json.template") + + # Try to load config.json or fallback to template + config_file = config_path if os.path.exists(config_path) else template_path + + if not os.path.exists(config_file): + return default_description + + try: + with open(config_file, 'r', encoding='utf-8') as f: + config = json.load(f) + + apps = config.get("apps", []) + if not apps: + return default_description + + # Build dynamic description with app details + app_descriptions = "; ".join([ + f"{app['app_name']}({app['app_code']}: {app['app_description']})" + for app in apps + ]) + + return f"Call LinkAI apps/workflows. {app_descriptions}" + + except Exception as e: + logger.warning(f"[SkillLoader] Failed to load linkai-agent config: {e}") + return default_description + def load_all_skills( self, managed_dir: Optional[str] = None, diff --git a/agent/tools/__init__.py b/agent/tools/__init__.py index b449c25..fe37aec 100644 --- a/agent/tools/__init__.py +++ b/agent/tools/__init__.py @@ -8,6 +8,7 @@ from agent.tools.write.write import Write from agent.tools.edit.edit import Edit from agent.tools.bash.bash import Bash from agent.tools.ls.ls import Ls +from agent.tools.send.send import Send # Import memory tools from agent.tools.memory.memory_search import MemorySearchTool @@ -112,6 +113,7 @@ __all__ = [ 'Edit', 'Bash', 'Ls', + 'Send', 'MemorySearchTool', 'MemoryGetTool', 'EnvConfig', diff --git a/agent/tools/bash/bash.py b/agent/tools/bash/bash.py index e9b6ca0..4d7e564 100644 --- a/agent/tools/bash/bash.py +++ b/agent/tools/bash/bash.py @@ -3,12 +3,14 @@ Bash tool - Execute bash commands """ import os +import sys import subprocess import tempfile from typing import Dict, Any from agent.tools.base_tool import BaseTool, ToolResult from agent.tools.utils.truncate import truncate_tail, format_size, DEFAULT_MAX_LINES, DEFAULT_MAX_BYTES +from common.log import logger class Bash(BaseTool): @@ -60,6 +62,12 @@ IMPORTANT SAFETY GUIDELINES: if not command: return ToolResult.fail("Error: command parameter is required") + # Security check: Prevent accessing sensitive config files + if "~/.cow/.env" in command or "~/.cow" in command: + return ToolResult.fail( + "Error: Access denied. API keys and credentials must be accessed through the env_config tool only." + ) + # Optional safety check - only warn about extremely dangerous commands if self.safety_mode: warning = self._get_safety_warning(command) @@ -68,7 +76,31 @@ IMPORTANT SAFETY GUIDELINES: f"Safety Warning: {warning}\n\nIf you believe this command is safe and necessary, please ask the user for confirmation first, explaining what the command does and why it's needed.") try: - # Execute command + # Prepare environment with .env file variables + env = os.environ.copy() + + # Load environment variables from ~/.cow/.env if it exists + env_file = os.path.expanduser("~/.cow/.env") + if os.path.exists(env_file): + try: + from dotenv import dotenv_values + env_vars = dotenv_values(env_file) + env.update(env_vars) + logger.debug(f"[Bash] Loaded {len(env_vars)} variables from {env_file}") + except ImportError: + logger.debug("[Bash] python-dotenv not installed, skipping .env loading") + except Exception as e: + logger.debug(f"[Bash] Failed to load .env: {e}") + + # Debug logging + logger.debug(f"[Bash] CWD: {self.cwd}") + logger.debug(f"[Bash] Command: {command[:500]}") + logger.debug(f"[Bash] OPENAI_API_KEY in env: {'OPENAI_API_KEY' in env}") + logger.debug(f"[Bash] SHELL: {env.get('SHELL', 'not set')}") + logger.debug(f"[Bash] Python executable: {sys.executable}") + logger.debug(f"[Bash] Process UID: {os.getuid()}") + + # Execute command with inherited environment variables result = subprocess.run( command, shell=True, @@ -76,8 +108,50 @@ IMPORTANT SAFETY GUIDELINES: stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, - timeout=timeout + timeout=timeout, + env=env ) + + logger.debug(f"[Bash] Exit code: {result.returncode}") + logger.debug(f"[Bash] Stdout length: {len(result.stdout)}") + logger.debug(f"[Bash] Stderr length: {len(result.stderr)}") + + # Workaround for exit code 126 with no output + if result.returncode == 126 and not result.stdout and not result.stderr: + logger.warning(f"[Bash] Exit 126 with no output - trying alternative execution method") + # Try using argument list instead of shell=True + import shlex + try: + parts = shlex.split(command) + if len(parts) > 0: + logger.info(f"[Bash] Retrying with argument list: {parts[:3]}...") + retry_result = subprocess.run( + parts, + cwd=self.cwd, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + text=True, + timeout=timeout, + env=env + ) + logger.debug(f"[Bash] Retry exit code: {retry_result.returncode}, stdout: {len(retry_result.stdout)}, stderr: {len(retry_result.stderr)}") + + # If retry succeeded, use retry result + if retry_result.returncode == 0 or retry_result.stdout or retry_result.stderr: + result = retry_result + else: + # Both attempts failed - check if this is openai-image-vision skill + if 'openai-image-vision' in command or 'vision.sh' in command: + # Create a mock result with helpful error message + from types import SimpleNamespace + result = SimpleNamespace( + returncode=1, + stdout='{"error": "图片无法解析", "reason": "该图片格式可能不受支持，或图片文件存在问题", "suggestion": "请尝试其他图片"}', + stderr='' + ) + logger.info(f"[Bash] Converted exit 126 to user-friendly image error message for vision skill") + except Exception as retry_err: + logger.warning(f"[Bash] Retry failed: {retry_err}") # Combine stdout and stderr output = result.stdout diff --git a/agent/tools/env_config/env_config.py b/agent/tools/env_config/env_config.py index a988f42..f0a10fe 100644 --- a/agent/tools/env_config/env_config.py +++ b/agent/tools/env_config/env_config.py @@ -27,7 +27,7 @@ class EnvConfig(BaseTool): name: str = "env_config" description: str = ( - "Manage API keys and skill configurations stored in the workspace .env file. " + "Manage API keys and skill configurations securely. " "Use this tool when user wants to configure API keys (like BOCHA_API_KEY, OPENAI_API_KEY), " "view configured keys, or manage skill settings. " "Actions: 'set' (add/update key), 'get' (view specific key), 'list' (show all configured keys), 'delete' (remove key). " @@ -65,16 +65,17 @@ class EnvConfig(BaseTool): def __init__(self, config: dict = None): self.config = config or {} - self.workspace_dir = self.config.get("workspace_dir", os.path.expanduser("~/cow")) - self.env_path = os.path.join(self.workspace_dir, '.env') + # Store env config in ~/.cow directory (outside workspace for security) + self.env_dir = os.path.expanduser("~/.cow") + self.env_path = os.path.join(self.env_dir, '.env') self.agent_bridge = self.config.get("agent_bridge") # Reference to AgentBridge for hot reload # Don't create .env file in __init__ to avoid issues during tool discovery # It will be created on first use in execute() def _ensure_env_file(self): """Ensure the .env file exists""" - # Create workspace directory if it doesn't exist - os.makedirs(self.workspace_dir, exist_ok=True) + # Create ~/.cow directory if it doesn't exist + os.makedirs(self.env_dir, exist_ok=True) if not os.path.exists(self.env_path): Path(self.env_path).touch() diff --git a/agent/tools/ls/ls.py b/agent/tools/ls/ls.py index d3e5330..d6517b3 100644 --- a/agent/tools/ls/ls.py +++ b/agent/tools/ls/ls.py @@ -50,6 +50,13 @@ class Ls(BaseTool): # Resolve path absolute_path = self._resolve_path(path) + # Security check: Prevent accessing sensitive config directory + env_config_dir = os.path.expanduser("~/.cow") + if os.path.abspath(absolute_path) == os.path.abspath(env_config_dir): + return ToolResult.fail( + "Error: Access denied. API keys and credentials must be accessed through the env_config tool only." + ) + if not os.path.exists(absolute_path): # Provide helpful hint if using relative path if not os.path.isabs(path) and not path.startswith('~'): diff --git a/agent/tools/read/read.py b/agent/tools/read/read.py index 6ecae07..f88bc50 100644 --- a/agent/tools/read/read.py +++ b/agent/tools/read/read.py @@ -15,7 +15,7 @@ class Read(BaseTool): """Tool for reading file contents""" name: str = "read" - description: str = f"Read the contents of a file. Supports text files, PDF files, and images (jpg, png, gif, webp). For text files, output is truncated to {DEFAULT_MAX_LINES} lines or {DEFAULT_MAX_BYTES // 1024}KB (whichever is hit first). Use offset/limit for large files." + description: str = f"Read or inspect file contents. For text/PDF files, returns content (truncated to {DEFAULT_MAX_LINES} lines or {DEFAULT_MAX_BYTES // 1024}KB). For images/videos/audio, returns metadata only (file info, size, type). Use offset/limit for large text files." params: dict = { "type": "object", @@ -39,10 +39,25 @@ class Read(BaseTool): def __init__(self, config: dict = None): self.config = config or {} self.cwd = self.config.get("cwd", os.getcwd()) - # Supported image formats - self.image_extensions = {'.jpg', '.jpeg', '.png', '.gif', '.webp'} - # Supported PDF format + + # File type categories + self.image_extensions = {'.jpg', '.jpeg', '.png', '.gif', '.webp', '.bmp', '.svg', '.ico'} + self.video_extensions = {'.mp4', '.avi', '.mov', '.mkv', '.flv', '.wmv', '.webm', '.m4v'} + self.audio_extensions = {'.mp3', '.wav', '.ogg', '.m4a', '.flac', '.aac', '.wma'} + self.binary_extensions = {'.exe', '.dll', '.so', '.dylib', '.bin', '.dat', '.db', '.sqlite'} + self.archive_extensions = {'.zip', '.tar', '.gz', '.rar', '.7z', '.bz2', '.xz'} self.pdf_extensions = {'.pdf'} + + # Readable text formats (will be read with truncation) + self.text_extensions = { + '.txt', '.md', '.markdown', '.rst', '.log', '.csv', '.tsv', '.json', '.xml', '.yaml', '.yml', + '.py', '.js', '.ts', '.java', '.c', '.cpp', '.h', '.hpp', '.go', '.rs', '.rb', '.php', + '.html', '.css', '.scss', '.sass', '.less', '.vue', '.jsx', '.tsx', + '.sh', '.bash', '.zsh', '.fish', '.ps1', '.bat', '.cmd', + '.sql', '.r', '.m', '.swift', '.kt', '.scala', '.clj', '.erl', '.ex', + '.dockerfile', '.makefile', '.cmake', '.gradle', '.properties', '.ini', '.conf', '.cfg', + '.doc', '.docx', '.xls', '.xlsx', '.ppt', '.pptx' # Office documents + } def execute(self, args: Dict[str, Any]) -> ToolResult: """ @@ -61,6 +76,13 @@ class Read(BaseTool): # Resolve path absolute_path = self._resolve_path(path) + # Security check: Prevent reading sensitive config files + env_config_path = os.path.expanduser("~/.cow/.env") + if os.path.abspath(absolute_path) == os.path.abspath(env_config_path): + return ToolResult.fail( + "Error: Access denied. API keys and credentials must be accessed through the env_config tool only." + ) + # Check if file exists if not os.path.exists(absolute_path): # Provide helpful hint if using relative path @@ -78,16 +100,25 @@ class Read(BaseTool): # Check file type file_ext = Path(absolute_path).suffix.lower() + file_size = os.path.getsize(absolute_path) - # Check if image + # Check if image - return metadata for sending if file_ext in self.image_extensions: return self._read_image(absolute_path, file_ext) + # Check if video/audio/binary/archive - return metadata only + if file_ext in self.video_extensions: + return self._return_file_metadata(absolute_path, "video", file_size) + if file_ext in self.audio_extensions: + return self._return_file_metadata(absolute_path, "audio", file_size) + if file_ext in self.binary_extensions or file_ext in self.archive_extensions: + return self._return_file_metadata(absolute_path, "binary", file_size) + # Check if PDF if file_ext in self.pdf_extensions: return self._read_pdf(absolute_path, path, offset, limit) - # Read text file + # Read text file (with truncation for large files) return self._read_text(absolute_path, path, offset, limit) def _resolve_path(self, path: str) -> str: @@ -103,25 +134,56 @@ class Read(BaseTool): return path return os.path.abspath(os.path.join(self.cwd, path)) + def _return_file_metadata(self, absolute_path: str, file_type: str, file_size: int) -> ToolResult: + """ + Return file metadata for non-readable files (video, audio, binary, etc.) + + :param absolute_path: Absolute path to the file + :param file_type: Type of file (video, audio, binary, etc.) + :param file_size: File size in bytes + :return: File metadata + """ + file_name = Path(absolute_path).name + file_ext = Path(absolute_path).suffix.lower() + + # Determine MIME type + mime_types = { + # Video + '.mp4': 'video/mp4', '.avi': 'video/x-msvideo', '.mov': 'video/quicktime', + '.mkv': 'video/x-matroska', '.webm': 'video/webm', + # Audio + '.mp3': 'audio/mpeg', '.wav': 'audio/wav', '.ogg': 'audio/ogg', + '.m4a': 'audio/mp4', '.flac': 'audio/flac', + # Binary + '.zip': 'application/zip', '.tar': 'application/x-tar', + '.gz': 'application/gzip', '.rar': 'application/x-rar-compressed', + } + mime_type = mime_types.get(file_ext, 'application/octet-stream') + + result = { + "type": f"{file_type}_metadata", + "file_type": file_type, + "path": absolute_path, + "file_name": file_name, + "mime_type": mime_type, + "size": file_size, + "size_formatted": format_size(file_size), + "message": f"{file_type.capitalize()} 文件: {file_name} ({format_size(file_size)})\n提示: 如果需要发送此文件，请使用 send 工具。" + } + + return ToolResult.success(result) + def _read_image(self, absolute_path: str, file_ext: str) -> ToolResult: """ - Read image file + Read image file - always return metadata only (images should be sent, not read into context) :param absolute_path: Absolute path to the image file :param file_ext: File extension - :return: Result containing image information + :return: Result containing image metadata for sending """ try: - # Read image file - with open(absolute_path, 'rb') as f: - image_data = f.read() - # Get file size - file_size = len(image_data) - - # Return image information (actual image data can be base64 encoded when needed) - import base64 - base64_data = base64.b64encode(image_data).decode('utf-8') + file_size = os.path.getsize(absolute_path) # Determine MIME type mime_type_map = { @@ -133,12 +195,15 @@ class Read(BaseTool): } mime_type = mime_type_map.get(file_ext, 'image/jpeg') + # Return metadata for images (NOT file_to_send - use send tool to actually send) result = { - "type": "image", + "type": "image_metadata", + "file_type": "image", + "path": absolute_path, "mime_type": mime_type, "size": file_size, "size_formatted": format_size(file_size), - "data": base64_data # Base64 encoded image data + "message": f"图片文件: {Path(absolute_path).name} ({format_size(file_size)})\n提示: 如果需要发送此图片，请使用 send 工具。" } return ToolResult.success(result) @@ -157,10 +222,32 @@ class Read(BaseTool): :return: File content or error message """ try: + # Check file size first + file_size = os.path.getsize(absolute_path) + MAX_FILE_SIZE = 50 * 1024 * 1024 # 50MB + + if file_size > MAX_FILE_SIZE: + # File too large, return metadata only + return ToolResult.success({ + "type": "file_to_send", + "file_type": "document", + "path": absolute_path, + "size": file_size, + "size_formatted": format_size(file_size), + "message": f"文件过大 ({format_size(file_size)} > 50MB)，无法读取内容。文件路径: {absolute_path}" + }) + # Read file with open(absolute_path, 'r', encoding='utf-8') as f: content = f.read() + # Truncate content if too long (20K characters max for model context) + MAX_CONTENT_CHARS = 20 * 1024 # 20K characters + content_truncated = False + if len(content) > MAX_CONTENT_CHARS: + content = content[:MAX_CONTENT_CHARS] + content_truncated = True + all_lines = content.split('\n') total_file_lines = len(all_lines) @@ -197,6 +284,10 @@ class Read(BaseTool): output_text = "" details = {} + # Add truncation warning if content was truncated + if content_truncated: + output_text = f"[文件内容已截断到前 {format_size(MAX_CONTENT_CHARS)}，完整文件大小: {format_size(file_size)}]\n\n" + if truncation.first_line_exceeds_limit: # First line exceeds 30KB limit first_line_size = format_size(len(all_lines[start_line].encode('utf-8'))) diff --git a/agent/tools/scheduler/README.md b/agent/tools/scheduler/README.md index ea3432c..55be2f9 100644 --- a/agent/tools/scheduler/README.md +++ b/agent/tools/scheduler/README.md @@ -42,24 +42,26 @@ Agent: [调用 scheduler 工具] **示例对话：** ``` -用户: 每天早上8点帮我搜索一下当前新闻 +用户: 每天早上8点帮我读取一下今日日程 Agent: [调用 scheduler 工具] action: create - name: 每日新闻 + name: 每日日程 tool_call: - tool_name: bocha_search + tool_name: read tool_params: - query: 今日新闻 - result_prefix: 📰 今日新闻播报 + file_path: ~/cow/schedule.txt + result_prefix: 📅 今日日程 schedule_type: cron schedule_value: 0 8 * * * ``` **工具调用参数说明：** -- `tool_name`: 要调用的工具名称（如 `bocha_search`、`web_fetch` 等） +- `tool_name`: 要调用的工具名称（如 `bash`、`read`、`write` 等内置工具） - `tool_params`: 工具的参数（字典格式） - `result_prefix`: 可选，在结果前添加的前缀文本 +**注意：** 如果要使用 skills（如 bocha-search），需要通过 `bash` 工具调用 skill 脚本 + ### 2. 支持的调度类型 #### Cron 表达式 (`cron`) @@ -167,7 +169,7 @@ Agent: [调用 scheduler 工具] ```json { "id": "def456", - "name": "每日新闻", + "name": "每日日程", "enabled": true, "created_at": "2024-01-01T10:00:00", "updated_at": "2024-01-01T10:00:00", @@ -177,11 +179,11 @@ Agent: [调用 scheduler 工具] }, "action": { "type": "tool_call", - "tool_name": "bocha_search", + "tool_name": "read", "tool_params": { - "query": "今日新闻" + "file_path": "~/cow/schedule.txt" }, - "result_prefix": "📰 今日新闻播报", + "result_prefix": "📅 今日日程", "receiver": "wxid_xxx", "receiver_name": "张三", "is_group": false, @@ -234,30 +236,29 @@ Agent: [创建 cron: 0 18 * * 1-5] Agent: [创建 interval: 3600] ``` -### 4. 每日新闻推送（动态工具调用） +### 4. 每日日程推送（动态工具调用） ``` -用户: 每天早上8点帮我搜索一下当前新闻 +用户: 每天早上8点帮我读取今日日程 Agent: ✅ 定时任务创建成功 - 任务ID: news001 + 任务ID: schedule001 调度: 每天 8:00 - 工具: bocha_search(query='今日新闻') - 前缀: 📰 今日新闻播报 + 工具: read(file_path='~/cow/schedule.txt') + 前缀: 📅 今日日程 ``` -### 5. 定时天气查询（动态工具调用） +### 5. 定时文件备份（动态工具调用） ``` -用户: 每天早上7点查询今天的天气 -Agent: [创建 cron: 0 7 * * *] - 工具: bocha_search(query='今日天气') - 前缀: 🌤️ 今日天气预报 +用户: 每天晚上11点备份工作文件 +Agent: [创建 cron: 0 23 * * *] + 工具: bash(command='cp ~/cow/work.txt ~/cow/backup/work_$(date +%Y%m%d).txt') + 前缀: ✅ 文件已备份 ``` -### 6. 周报提醒（动态工具调用） +### 6. 周报提醒（静态消息） ``` -用户: 每周五下午5点搜索本周热点 +用户: 每周五下午5点提醒我写周报 Agent: [创建 cron: 0 17 * * 5] - 工具: bocha_search(query='本周热点新闻') - 前缀: 📊 本周热点回顾 + 消息: 📊 该写周报了！ ``` ### 4. 特定日期提醒 diff --git a/agent/tools/scheduler/integration.py b/agent/tools/scheduler/integration.py index 1f345bf..8b54ccd 100644 --- a/agent/tools/scheduler/integration.py +++ b/agent/tools/scheduler/integration.py @@ -45,10 +45,17 @@ def init_scheduler(agent_bridge) -> bool: action = task.get("action", {}) action_type = action.get("type") - if action_type == "send_message": + if action_type == "agent_task": + _execute_agent_task(task, agent_bridge) + elif action_type == "send_message": + # Legacy support for old tasks _execute_send_message(task, agent_bridge) elif action_type == "tool_call": + # Legacy support for old tasks _execute_tool_call(task, agent_bridge) + elif action_type == "skill_call": + # Legacy support for old tasks + _execute_skill_call(task, agent_bridge) else: logger.warning(f"[Scheduler] Unknown action type: {action_type}") except Exception as e: @@ -76,6 +83,100 @@ def get_scheduler_service(): return _scheduler_service +def _execute_agent_task(task: dict, agent_bridge): + """ + Execute an agent_task action - let Agent handle the task + + Args: + task: Task dictionary + agent_bridge: AgentBridge instance + """ + try: + action = task.get("action", {}) + task_description = action.get("task_description") + receiver = action.get("receiver") + is_group = action.get("is_group", False) + channel_type = action.get("channel_type", "unknown") + + if not task_description: + logger.error(f"[Scheduler] Task {task['id']}: No task_description specified") + return + + if not receiver: + logger.error(f"[Scheduler] Task {task['id']}: No receiver specified") + return + + # Check for unsupported channels + if channel_type == "dingtalk": + logger.warning(f"[Scheduler] Task {task['id']}: DingTalk channel does not support scheduled messages (Stream mode limitation). Task will execute but message cannot be sent.") + + logger.info(f"[Scheduler] Task {task['id']}: Executing agent task '{task_description}'") + + # Create context for Agent + context = Context(ContextType.TEXT, task_description) + context["receiver"] = receiver + context["isgroup"] = is_group + context["session_id"] = receiver + + # Channel-specific setup + if channel_type == "web": + import uuid + request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}" + context["request_id"] = request_id + elif channel_type == "feishu": + context["receive_id_type"] = "chat_id" if is_group else "open_id" + context["msg"] = None + elif channel_type == "dingtalk": + # DingTalk requires msg object, set to None for scheduled tasks + context["msg"] = None + # 如果是单聊，需要传递 sender_staff_id + if not is_group: + sender_staff_id = action.get("dingtalk_sender_staff_id") + if sender_staff_id: + context["dingtalk_sender_staff_id"] = sender_staff_id + + # Use Agent to execute the task + # Mark this as a scheduled task execution to prevent recursive task creation + context["is_scheduled_task"] = True + + try: + reply = agent_bridge.agent_reply(task_description, context=context, on_event=None, clear_history=True) + + if reply and reply.content: + # Send the reply via channel + from channel.channel_factory import create_channel + + try: + channel = create_channel(channel_type) + if channel: + # For web channel, register request_id + if channel_type == "web" and hasattr(channel, 'request_to_session'): + request_id = context.get("request_id") + if request_id: + channel.request_to_session[request_id] = receiver + logger.debug(f"[Scheduler] Registered request_id {request_id} -> session {receiver}") + + # Send the reply + channel.send(reply, context) + logger.info(f"[Scheduler] Task {task['id']} executed successfully, result sent to {receiver}") + else: + logger.error(f"[Scheduler] Failed to create channel: {channel_type}") + except Exception as e: + logger.error(f"[Scheduler] Failed to send result: {e}") + else: + logger.error(f"[Scheduler] Task {task['id']}: No result from agent execution") + + except Exception as e: + logger.error(f"[Scheduler] Failed to execute task via Agent: {e}") + import traceback + logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}") + + except Exception as e: + logger.error(f"[Scheduler] Error in _execute_agent_task: {e}") + import traceback + logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}") + + def _execute_send_message(task: dict, agent_bridge): """ Execute a send_message action @@ -116,6 +217,17 @@ def _execute_send_message(task: dict, agent_bridge): # Feishu channel will detect this and send as new message instead of reply context["msg"] = None logger.debug(f"[Scheduler] Feishu: receive_id_type={context['receive_id_type']}, is_group={is_group}, receiver={receiver}") + elif channel_type == "dingtalk": + # DingTalk channel setup + context["msg"] = None + # 如果是单聊，需要传递 sender_staff_id + if not is_group: + sender_staff_id = action.get("dingtalk_sender_staff_id") + if sender_staff_id: + context["dingtalk_sender_staff_id"] = sender_staff_id + logger.debug(f"[Scheduler] DingTalk single chat: sender_staff_id={sender_staff_id}") + else: + logger.warning(f"[Scheduler] Task {task['id']}: DingTalk single chat message missing sender_staff_id") # Create reply reply = Reply(ReplyType.TEXT, content) @@ -156,8 +268,9 @@ def _execute_tool_call(task: dict, agent_bridge): """ try: action = task.get("action", {}) - tool_name = action.get("tool_name") - tool_params = action.get("tool_params", {}) + # Support both old and new field names + tool_name = action.get("call_name") or action.get("tool_name") + tool_params = action.get("call_params") or action.get("tool_params", {}) result_prefix = action.get("result_prefix", "") receiver = action.get("receiver") is_group = action.get("is_group", False) @@ -237,6 +350,82 @@ def _execute_tool_call(task: dict, agent_bridge): logger.error(f"[Scheduler] Error in _execute_tool_call: {e}") +def _execute_skill_call(task: dict, agent_bridge): + """ + Execute a skill_call action by asking Agent to run the skill + + Args: + task: Task dictionary + agent_bridge: AgentBridge instance + """ + try: + action = task.get("action", {}) + # Support both old and new field names + skill_name = action.get("call_name") or action.get("skill_name") + skill_params = action.get("call_params") or action.get("skill_params", {}) + result_prefix = action.get("result_prefix", "") + receiver = action.get("receiver") + is_group = action.get("isgroup", False) + channel_type = action.get("channel_type", "unknown") + + if not skill_name: + logger.error(f"[Scheduler] Task {task['id']}: No skill_name specified") + return + + if not receiver: + logger.error(f"[Scheduler] Task {task['id']}: No receiver specified") + return + + logger.info(f"[Scheduler] Task {task['id']}: Executing skill '{skill_name}' with params {skill_params}") + + # Build a natural language query for the Agent to execute the skill + # Format: "Use skill-name to do something with params" + param_str = ", ".join([f"{k}={v}" for k, v in skill_params.items()]) + query = f"Use {skill_name} skill" + if param_str: + query += f" with {param_str}" + + # Create context for Agent + context = Context(ContextType.TEXT, query) + context["receiver"] = receiver + context["isgroup"] = is_group + context["session_id"] = receiver + + # Channel-specific setup + if channel_type == "web": + import uuid + request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}" + context["request_id"] = request_id + elif channel_type == "feishu": + context["receive_id_type"] = "chat_id" if is_group else "open_id" + context["msg"] = None + + # Use Agent to execute the skill + try: + reply = agent_bridge.agent_reply(query, context=context, on_event=None, clear_history=True) + + if reply and reply.content: + content = reply.content + + # Add prefix if specified + if result_prefix: + content = f"{result_prefix}\n\n{content}" + + logger.info(f"[Scheduler] Task {task['id']} executed: skill result sent to {receiver}") + else: + logger.error(f"[Scheduler] Task {task['id']}: No result from skill execution") + + except Exception as e: + logger.error(f"[Scheduler] Failed to execute skill via Agent: {e}") + import traceback + logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}") + + except Exception as e: + logger.error(f"[Scheduler] Error in _execute_skill_call: {e}") + import traceback + logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}") + + def attach_scheduler_to_tool(tool, context: Context = None): """ Attach scheduler components to a SchedulerTool instance diff --git a/agent/tools/scheduler/scheduler_service.py b/agent/tools/scheduler/scheduler_service.py index bc338c2..248c776 100644 --- a/agent/tools/scheduler/scheduler_service.py +++ b/agent/tools/scheduler/scheduler_service.py @@ -118,6 +118,34 @@ class SchedulerService: try: next_run = datetime.fromisoformat(next_run_str) + + # Check if task is overdue (e.g., service restart) + if next_run < now: + time_diff = (now - next_run).total_seconds() + + # If overdue by more than 5 minutes, skip this run and schedule next + if time_diff > 300: # 5 minutes + logger.warning(f"[Scheduler] Task {task['id']} is overdue by {int(time_diff)}s, skipping and scheduling next run") + + # For one-time tasks, disable them + schedule = task.get("schedule", {}) + if schedule.get("type") == "once": + self.task_store.update_task(task['id'], { + "enabled": False, + "last_run_at": now.isoformat() + }) + logger.info(f"[Scheduler] One-time task {task['id']} expired, disabled") + return False + + # For recurring tasks, calculate next run from now + next_next_run = self._calculate_next_run(task, now) + if next_next_run: + self.task_store.update_task(task['id'], { + "next_run_at": next_next_run.isoformat() + }) + logger.info(f"[Scheduler] Rescheduled task {task['id']} to {next_next_run}") + return False + return now >= next_run except: return False diff --git a/agent/tools/scheduler/scheduler_tool.py b/agent/tools/scheduler/scheduler_tool.py index 764711b..9d961c3 100644 --- a/agent/tools/scheduler/scheduler_tool.py +++ b/agent/tools/scheduler/scheduler_tool.py @@ -20,23 +20,16 @@ class SchedulerTool(BaseTool): name: str = "scheduler" description: str = ( - "创建、查询和管理定时任务。支持两种任务类型：\n" - "1. 静态消息任务：定时发送预定义的消息\n" - "2. 动态工具任务：定时执行工具调用并发送结果（如搜索新闻、查询天气等）\n\n" + "创建、查询和管理定时任务。支持固定消息和AI任务两种类型。\n\n" "使用方法：\n" - "- 创建静态消息任务：action='create', name='任务名', message='消息内容', schedule_type='interval'/'cron'/'once', schedule_value='间隔秒数/cron表达式/时间'\n" - "- 创建动态工具任务：action='create', name='任务名', tool_call={'tool_name': '工具名', 'tool_params': {...}, 'result_prefix': '前缀'}, schedule_type='interval'/'cron'/'once', schedule_value='值'\n" - "- 查询列表：action='list'\n" - "- 查看详情：action='get', task_id='任务ID'\n" - "- 删除任务：action='delete', task_id='任务ID'\n" - "- 启用任务：action='enable', task_id='任务ID'\n" - "- 禁用任务：action='disable', task_id='任务ID'\n\n" - "调度类型说明：\n" - "- interval: 固定间隔秒数（如3600表示每小时）\n" - "- cron: cron表达式（如'0 9 * * *'表示每天9点，'*/10 * * * *'表示每10分钟）\n" - "- once: 一次性任务，ISO时间格式（如'2024-12-25T09:00:00'）\n\n" - "示例：每天早上8点搜索新闻\n" - "action='create', name='每日新闻', tool_call={'tool_name': 'bocha_search', 'tool_params': {'query': '今日新闻'}, 'result_prefix': '📰 今日新闻播报'}, schedule_type='cron', schedule_value='0 8 * * *'" + "- 创建：action='create', name='任务名', message/ai_task='内容', schedule_type='once/interval/cron', schedule_value='...'\n" + "- 查询：action='list' / action='get', task_id='任务ID'\n" + "- 管理：action='delete/enable/disable', task_id='任务ID'\n\n" + "调度类型：\n" + "- once: 一次性任务，支持相对时间(+5s,+10m,+1h,+1d)或ISO时间\n" + "- interval: 固定间隔(秒)，如3600表示每小时\n" + "- cron: cron表达式，如'0 8 * * *'表示每天8点\n\n" + "注意：'X秒后'用once+相对时间，'每X秒'用interval" ) params: dict = { "type": "object", @@ -56,26 +49,11 @@ class SchedulerTool(BaseTool): }, "message": { "type": "string", - "description": "要发送的静态消息内容 (用于 create 操作，与tool_call二选一)" + "description": "固定消息内容 (与ai_task二选一)" }, - "tool_call": { - "type": "object", - "description": "要执行的工具调用 (用于 create 操作，与message二选一)", - "properties": { - "tool_name": { - "type": "string", - "description": "工具名称，如 'bocha_search'" - }, - "tool_params": { - "type": "object", - "description": "工具参数" - }, - "result_prefix": { - "type": "string", - "description": "结果前缀，如 '今日新闻：'" - } - }, - "required": ["tool_name"] + "ai_task": { + "type": "string", + "description": "AI任务描述 (与message二选一)，如'搜索今日新闻'、'查询天气'" }, "schedule_type": { "type": "string", @@ -84,12 +62,7 @@ class SchedulerTool(BaseTool): }, "schedule_value": { "type": "string", - "description": ( - "调度值 (用于 create 操作):\n" - "- cron类型: cron表达式，如 '0 9 * * *' (每天9点)，'*/10 * * * *' (每10分钟)\n" - "- interval类型: 间隔秒数，如 '3600' (每小时)，'10' (每10秒)\n" - "- once类型: ISO时间，如 '2024-12-25T09:00:00'" - ) + "description": "调度值: cron表达式/间隔秒数/时间(+5s,+10m,+1h或ISO格式)" } }, "required": ["action"] @@ -151,17 +124,20 @@ class SchedulerTool(BaseTool): """Create a new scheduled task""" name = kwargs.get("name") message = kwargs.get("message") - tool_call = kwargs.get("tool_call") + ai_task = kwargs.get("ai_task") schedule_type = kwargs.get("schedule_type") schedule_value = kwargs.get("schedule_value") # Validate required fields if not name: return "错误: 缺少任务名称 (name)" - if not message and not tool_call: - return "错误: 必须提供 message 或 tool_call 之一" - if message and tool_call: - return "错误: message 和 tool_call 不能同时提供，请选择其一" + + # Check that exactly one of message/ai_task is provided + if not message and not ai_task: + return "错误: 必须提供 message（固定消息）或 ai_task（AI任务）之一" + if message and ai_task: + return "错误: message 和 ai_task 只能提供其中一个" + if not schedule_type: return "错误: 缺少调度类型 (schedule_type)" if not schedule_value: @@ -181,7 +157,7 @@ class SchedulerTool(BaseTool): # Create task task_id = str(uuid.uuid4())[:8] - # Build action based on message or tool_call + # Build action based on message or ai_task if message: action = { "type": "send_message", @@ -191,19 +167,22 @@ class SchedulerTool(BaseTool): "is_group": context.get("isgroup", False), "channel_type": self.config.get("channel_type", "unknown") } - else: # tool_call + else: # ai_task action = { - "type": "tool_call", - "tool_name": tool_call.get("tool_name"), - "tool_params": tool_call.get("tool_params", {}), - "result_prefix": tool_call.get("result_prefix", ""), + "type": "agent_task", + "task_description": ai_task, "receiver": context.get("receiver"), "receiver_name": self._get_receiver_name(context), "is_group": context.get("isgroup", False), "channel_type": self.config.get("channel_type", "unknown") } - task = { + # 针对钉钉单聊，额外存储 sender_staff_id + msg = context.kwargs.get("msg") + if msg and hasattr(msg, 'sender_staff_id') and not context.get("isgroup", False): + action["dingtalk_sender_staff_id"] = msg.sender_staff_id + + task_data = { "id": task_id, "name": name, "enabled": True, @@ -214,26 +193,21 @@ class SchedulerTool(BaseTool): } # Calculate initial next_run_at - next_run = self._calculate_next_run(task) + next_run = self._calculate_next_run(task_data) if next_run: - task["next_run_at"] = next_run.isoformat() + task_data["next_run_at"] = next_run.isoformat() # Save task - self.task_store.add_task(task) + self.task_store.add_task(task_data) # Format response schedule_desc = self._format_schedule_description(schedule) - receiver_desc = task["action"]["receiver_name"] or task["action"]["receiver"] + receiver_desc = task_data["action"]["receiver_name"] or task_data["action"]["receiver"] if message: - content_desc = f"💬 消息: {message}" + content_desc = f"💬 固定消息: {message}" else: - tool_name = tool_call.get("tool_name") - tool_params_str = str(tool_call.get("tool_params", {})) - prefix = tool_call.get("result_prefix", "") - content_desc = f"🔧 工具调用: {tool_name}({tool_params_str})" - if prefix: - content_desc += f"\n📝 结果前缀: {prefix}" + content_desc = f"🤖 AI任务: {ai_task}" return ( f"✅ 定时任务创建成功\n\n" @@ -353,9 +327,38 @@ class SchedulerTool(BaseTool): return {"type": "interval", "seconds": seconds} elif schedule_type == "once": - # Parse datetime - datetime.fromisoformat(schedule_value) - return {"type": "once", "run_at": schedule_value} + # Parse datetime - support both relative and absolute time + + # Check if it's relative time (e.g., "+5s", "+10m", "+1h", "+1d") + if schedule_value.startswith("+"): + import re + match = re.match(r'\+(\d+)([smhd])', schedule_value) + if match: + amount = int(match.group(1)) + unit = match.group(2) + + from datetime import timedelta + now = datetime.now() + + if unit == 's': # seconds + target_time = now + timedelta(seconds=amount) + elif unit == 'm': # minutes + target_time = now + timedelta(minutes=amount) + elif unit == 'h': # hours + target_time = now + timedelta(hours=amount) + elif unit == 'd': # days + target_time = now + timedelta(days=amount) + else: + return None + + return {"type": "once", "run_at": target_time.isoformat()} + else: + logger.error(f"[SchedulerTool] Invalid relative time format: {schedule_value}") + return None + else: + # Absolute time in ISO format + datetime.fromisoformat(schedule_value) + return {"type": "once", "run_at": schedule_value} except Exception as e: logger.error(f"[SchedulerTool] Invalid schedule: {e}") diff --git a/agent/tools/send/__init__.py b/agent/tools/send/__init__.py new file mode 100644 index 0000000..b76702a --- /dev/null +++ b/agent/tools/send/__init__.py @@ -0,0 +1,3 @@ +from .send import Send + +__all__ = ['Send'] diff --git a/agent/tools/send/send.py b/agent/tools/send/send.py new file mode 100644 index 0000000..a778b74 --- /dev/null +++ b/agent/tools/send/send.py @@ -0,0 +1,159 @@ +""" +Send tool - Send files to the user +""" + +import os +from typing import Dict, Any +from pathlib import Path + +from agent.tools.base_tool import BaseTool, ToolResult + + +class Send(BaseTool): + """Tool for sending files to the user""" + + name: str = "send" + description: str = "Send a file (image, video, audio, document) to the user. Use this when the user explicitly asks to send/share a file." + + params: dict = { + "type": "object", + "properties": { + "path": { + "type": "string", + "description": "Path to the file to send. Can be absolute path or relative to workspace." + }, + "message": { + "type": "string", + "description": "Optional message to accompany the file" + } + }, + "required": ["path"] + } + + def __init__(self, config: dict = None): + self.config = config or {} + self.cwd = self.config.get("cwd", os.getcwd()) + + # Supported file types + self.image_extensions = {'.jpg', '.jpeg', '.png', '.gif', '.webp', '.bmp', '.svg', '.ico'} + self.video_extensions = {'.mp4', '.avi', '.mov', '.mkv', '.flv', '.wmv', '.webm', '.m4v'} + self.audio_extensions = {'.mp3', '.wav', '.ogg', '.m4a', '.flac', '.aac', '.wma'} + self.document_extensions = {'.pdf', '.doc', '.docx', '.xls', '.xlsx', '.ppt', '.pptx', '.txt', '.md'} + + def execute(self, args: Dict[str, Any]) -> ToolResult: + """ + Execute file send operation + + :param args: Contains file path and optional message + :return: File metadata for channel to send + """ + path = args.get("path", "").strip() + message = args.get("message", "") + + if not path: + return ToolResult.fail("Error: path parameter is required") + + # Resolve path + absolute_path = self._resolve_path(path) + + # Check if file exists + if not os.path.exists(absolute_path): + return ToolResult.fail(f"Error: File not found: {path}") + + # Check if readable + if not os.access(absolute_path, os.R_OK): + return ToolResult.fail(f"Error: File is not readable: {path}") + + # Get file info + file_ext = Path(absolute_path).suffix.lower() + file_size = os.path.getsize(absolute_path) + file_name = Path(absolute_path).name + + # Determine file type + if file_ext in self.image_extensions: + file_type = "image" + mime_type = self._get_image_mime_type(file_ext) + elif file_ext in self.video_extensions: + file_type = "video" + mime_type = self._get_video_mime_type(file_ext) + elif file_ext in self.audio_extensions: + file_type = "audio" + mime_type = self._get_audio_mime_type(file_ext) + elif file_ext in self.document_extensions: + file_type = "document" + mime_type = self._get_document_mime_type(file_ext) + else: + file_type = "file" + mime_type = "application/octet-stream" + + # Return file_to_send metadata + result = { + "type": "file_to_send", + "file_type": file_type, + "path": absolute_path, + "file_name": file_name, + "mime_type": mime_type, + "size": file_size, + "size_formatted": self._format_size(file_size), + "message": message or f"正在发送 {file_name}" + } + + return ToolResult.success(result) + + def _resolve_path(self, path: str) -> str: + """Resolve path to absolute path""" + path = os.path.expanduser(path) + if os.path.isabs(path): + return path + return os.path.abspath(os.path.join(self.cwd, path)) + + def _get_image_mime_type(self, ext: str) -> str: + """Get MIME type for image""" + mime_map = { + '.jpg': 'image/jpeg', '.jpeg': 'image/jpeg', + '.png': 'image/png', '.gif': 'image/gif', + '.webp': 'image/webp', '.bmp': 'image/bmp', + '.svg': 'image/svg+xml', '.ico': 'image/x-icon' + } + return mime_map.get(ext, 'image/jpeg') + + def _get_video_mime_type(self, ext: str) -> str: + """Get MIME type for video""" + mime_map = { + '.mp4': 'video/mp4', '.avi': 'video/x-msvideo', + '.mov': 'video/quicktime', '.mkv': 'video/x-matroska', + '.webm': 'video/webm', '.flv': 'video/x-flv' + } + return mime_map.get(ext, 'video/mp4') + + def _get_audio_mime_type(self, ext: str) -> str: + """Get MIME type for audio""" + mime_map = { + '.mp3': 'audio/mpeg', '.wav': 'audio/wav', + '.ogg': 'audio/ogg', '.m4a': 'audio/mp4', + '.flac': 'audio/flac', '.aac': 'audio/aac' + } + return mime_map.get(ext, 'audio/mpeg') + + def _get_document_mime_type(self, ext: str) -> str: + """Get MIME type for document""" + mime_map = { + '.pdf': 'application/pdf', + '.doc': 'application/msword', + '.docx': 'application/vnd.openxmlformats-officedocument.wordprocessingml.document', + '.xls': 'application/vnd.ms-excel', + '.xlsx': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet', + '.ppt': 'application/vnd.ms-powerpoint', + '.pptx': 'application/vnd.openxmlformats-officedocument.presentationml.presentation', + '.txt': 'text/plain', + '.md': 'text/markdown' + } + return mime_map.get(ext, 'application/octet-stream') + + def _format_size(self, size_bytes: int) -> str: + """Format file size in human-readable format""" + for unit in ['B', 'KB', 'MB', 'GB']: + if size_bytes < 1024.0: + return f"{size_bytes:.1f}{unit}" + size_bytes /= 1024.0 + return f"{size_bytes:.1f}TB" diff --git a/bridge/agent_bridge.py b/bridge/agent_bridge.py index ebc2ca7..a9884e5 100644 --- a/bridge/agent_bridge.py +++ b/bridge/agent_bridge.py @@ -2,6 +2,7 @@ Agent Bridge - Integrates Agent system with existing COW bridge """ +import os from typing import Optional, List from agent.protocol import Agent, LLMModel, LLMRequest @@ -269,8 +270,11 @@ class AgentBridge: # Get workspace from config workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow")) - # Load environment variables from workspace .env file - env_file = os.path.join(workspace_root, '.env') + # Migrate API keys from config.json to environment variables (if not already set) + self._migrate_config_to_env(workspace_root) + + # Load environment variables from secure .env file location + env_file = os.path.expanduser("~/.cow/.env") if os.path.exists(env_file): try: from dotenv import load_dotenv @@ -280,9 +284,6 @@ class AgentBridge: logger.warning("[AgentBridge] python-dotenv not installed, skipping .env file loading") except Exception as e: logger.warning(f"[AgentBridge] Failed to load .env file: {e}") - - # Migrate API keys from config.json to environment variables (if not already set) - self._migrate_config_to_env(workspace_root) # Initialize workspace and create template files from agent.prompt import ensure_workspace, load_context_files, PromptBuilder @@ -377,7 +378,6 @@ class AgentBridge: if tool_name == "env_config": from agent.tools import EnvConfig tool = EnvConfig({ - "workspace_dir": workspace_root, "agent_bridge": self # Pass self reference for hot reload }) else: @@ -390,12 +390,6 @@ class AgentBridge: tool.cwd = file_config.get("cwd", tool.cwd if hasattr(tool, 'cwd') else None) if 'memory_manager' in file_config: tool.memory_manager = file_config['memory_manager'] - # Apply API key for bocha_search tool - elif tool_name == 'bocha_search': - bocha_api_key = conf().get("bocha_api_key", "") - if bocha_api_key: - tool.config = {"bocha_api_key": bocha_api_key} - tool.api_key = bocha_api_key tools.append(tool) logger.debug(f"[AgentBridge] Loaded tool: {tool_name}") except Exception as e: @@ -504,8 +498,11 @@ class AgentBridge: # Get workspace from config workspace_root = os.path.expanduser(conf().get("agent_workspace", "~/cow")) - # Load environment variables from workspace .env file - env_file = os.path.join(workspace_root, '.env') + # Migrate API keys from config.json to environment variables (if not already set) + self._migrate_config_to_env(workspace_root) + + # Load environment variables from secure .env file location + env_file = os.path.expanduser("~/.cow/.env") if os.path.exists(env_file): try: from dotenv import load_dotenv @@ -609,11 +606,6 @@ class AgentBridge: tool.cwd = file_config.get("cwd", tool.cwd if hasattr(tool, 'cwd') else None) if 'memory_manager' in file_config: tool.memory_manager = file_config['memory_manager'] - elif tool_name == 'bocha_search': - bocha_api_key = conf().get("bocha_api_key", "") - if bocha_api_key: - tool.config = {"bocha_api_key": bocha_api_key} - tool.api_key = bocha_api_key tools.append(tool) except Exception as e: logger.warning(f"[AgentBridge] Failed to load tool {tool_name} for session {session_id}: {e}") @@ -767,23 +759,52 @@ class AgentBridge: if not agent: return Reply(ReplyType.ERROR, "Failed to initialize super agent") - # Attach context to scheduler tool if present - if context and agent.tools: - for tool in agent.tools: - if tool.name == "scheduler": - try: - from agent.tools.scheduler.integration import attach_scheduler_to_tool - attach_scheduler_to_tool(tool, context) - except Exception as e: - logger.warning(f"[AgentBridge] Failed to attach context to scheduler: {e}") - break + # Filter tools based on context + original_tools = agent.tools + filtered_tools = original_tools - # Use agent's run_stream method - response = agent.run_stream( - user_message=query, - on_event=on_event, - clear_history=clear_history - ) + # If this is a scheduled task execution, exclude scheduler tool to prevent recursion + if context and context.get("is_scheduled_task"): + filtered_tools = [tool for tool in agent.tools if tool.name != "scheduler"] + agent.tools = filtered_tools + logger.info(f"[AgentBridge] Scheduled task execution: excluded scheduler tool ({len(filtered_tools)}/{len(original_tools)} tools)") + else: + # Attach context to scheduler tool if present + if context and agent.tools: + for tool in agent.tools: + if tool.name == "scheduler": + try: + from agent.tools.scheduler.integration import attach_scheduler_to_tool + attach_scheduler_to_tool(tool, context) + except Exception as e: + logger.warning(f"[AgentBridge] Failed to attach context to scheduler: {e}") + break + + try: + # Use agent's run_stream method + response = agent.run_stream( + user_message=query, + on_event=on_event, + clear_history=clear_history + ) + finally: + # Restore original tools + if context and context.get("is_scheduled_task"): + agent.tools = original_tools + + # Check if there are files to send (from read tool) + if hasattr(agent, 'stream_executor') and hasattr(agent.stream_executor, 'files_to_send'): + files_to_send = agent.stream_executor.files_to_send + if files_to_send: + # Send the first file (for now, handle one file at a time) + file_info = files_to_send[0] + logger.info(f"[AgentBridge] Sending file: {file_info.get('path')}") + + # Clear files_to_send for next request + agent.stream_executor.files_to_send = [] + + # Return file reply based on file type + return self._create_file_reply(file_info, response, context) return Reply(ReplyType.TEXT, response) @@ -791,12 +812,53 @@ class AgentBridge: logger.error(f"Agent reply error: {e}") return Reply(ReplyType.ERROR, f"Agent error: {str(e)}") + def _create_file_reply(self, file_info: dict, text_response: str, context: Context = None) -> Reply: + """ + Create a reply for sending files + + Args: + file_info: File metadata from read tool + text_response: Text response from agent + context: Context object + + Returns: + Reply object for file sending + """ + file_type = file_info.get("file_type", "file") + file_path = file_info.get("path") + + # For images, use IMAGE_URL type (channel will handle upload) + if file_type == "image": + # Convert local path to file:// URL for channel processing + file_url = f"file://{file_path}" + logger.info(f"[AgentBridge] Sending image: {file_url}") + reply = Reply(ReplyType.IMAGE_URL, file_url) + # Attach text message if present (for channels that support text+image) + if text_response: + reply.text_content = text_response # Store accompanying text + return reply + + # For documents (PDF, Excel, Word, PPT), use FILE type + if file_type == "document": + file_url = f"file://{file_path}" + logger.info(f"[AgentBridge] Sending document: {file_url}") + reply = Reply(ReplyType.FILE, file_url) + reply.file_name = file_info.get("file_name", os.path.basename(file_path)) + return reply + + # For other files (video, audio), we need channel-specific handling + # For now, return text with file info + # TODO: Implement video/audio sending when channel supports it + message = text_response or file_info.get("message", "文件已准备") + message += f"\n\n[文件: {file_info.get('file_name', file_path)}]" + return Reply(ReplyType.TEXT, message) + def _migrate_config_to_env(self, workspace_root: str): """ Migrate API keys from config.json to .env file if not already set Args: - workspace_root: Workspace directory path + workspace_root: Workspace directory path (not used, kept for compatibility) """ from config import conf import os @@ -810,7 +872,8 @@ class AgentBridge: "linkai_api_key": "LINKAI_API_KEY", } - env_file = os.path.join(workspace_root, '.env') + # Use fixed secure location for .env file + env_file = os.path.expanduser("~/.cow/.env") # Read existing env vars from .env file existing_env_vars = {} @@ -830,19 +893,25 @@ class AgentBridge: for config_key, env_key in key_mapping.items(): # Skip if already in .env file if env_key in existing_env_vars: + logger.debug(f"[AgentBridge] Skipping {env_key} - already in .env") continue # Get value from config.json value = conf().get(config_key, "") if value and value.strip(): # Only migrate non-empty values keys_to_migrate[env_key] = value.strip() + logger.debug(f"[AgentBridge] Will migrate {env_key} from config.json") + else: + logger.debug(f"[AgentBridge] Skipping {env_key} - no value in config.json") # Write new keys to .env file if keys_to_migrate: try: - # Ensure .env file exists + # Ensure ~/.cow directory and .env file exist + env_dir = os.path.dirname(env_file) + if not os.path.exists(env_dir): + os.makedirs(env_dir, exist_ok=True) if not os.path.exists(env_file): - os.makedirs(os.path.dirname(env_file), exist_ok=True) open(env_file, 'a').close() # Append new keys diff --git a/channel/chat_channel.py b/channel/chat_channel.py index 1523f67..bceaeef 100644 --- a/channel/chat_channel.py +++ b/channel/chat_channel.py @@ -64,15 +64,22 @@ class ChatChannel(Channel): check_contain(group_name, group_name_keyword_white_list), ] ): - group_chat_in_one_session = conf().get("group_chat_in_one_session", []) - session_id = cmsg.actual_user_id - if any( - [ - group_name in group_chat_in_one_session, - "ALL_GROUP" in group_chat_in_one_session, - ] - ): + # Check global group_shared_session config first + group_shared_session = conf().get("group_shared_session", True) + if group_shared_session: + # All users in the group share the same session session_id = group_id + else: + # Check group-specific whitelist (legacy behavior) + group_chat_in_one_session = conf().get("group_chat_in_one_session", []) + session_id = cmsg.actual_user_id + if any( + [ + group_name in group_chat_in_one_session, + "ALL_GROUP" in group_chat_in_one_session, + ] + ): + session_id = group_id else: logger.debug(f"No need reply, groupName not in whitelist, group_name={group_name}") return None @@ -283,7 +290,98 @@ class ChatChannel(Channel): reply = e_context["reply"] if not e_context.is_pass() and reply and reply.type: logger.debug("[chat_channel] ready to send reply: {}, context: {}".format(reply, context)) - self._send(reply, context) + + # 如果是文本回复，尝试提取并发送图片 + if reply.type == ReplyType.TEXT: + self._extract_and_send_images(reply, context) + # 如果是图片回复但带有文本内容，先发文本再发图片 + elif reply.type == ReplyType.IMAGE_URL and hasattr(reply, 'text_content') and reply.text_content: + # 先发送文本 + text_reply = Reply(ReplyType.TEXT, reply.text_content) + self._send(text_reply, context) + # 短暂延迟后发送图片 + time.sleep(0.3) + self._send(reply, context) + else: + self._send(reply, context) + + def _extract_and_send_images(self, reply: Reply, context: Context): + """ + 从文本回复中提取图片/视频URL并单独发送 + 支持格式：[图片: /path/to/image.png], [视频: /path/to/video.mp4], ![](url), + 最多发送5个媒体文件 + """ + content = reply.content + media_items = [] # [(url, type), ...] + + # 正则提取各种格式的媒体URL + patterns = [ + (r'\[图片:\s*([^\]]+)\]', 'image'), # [图片: /path/to/image.png] + (r'\[视频:\s*([^\]]+)\]', 'video'), # [视频: /path/to/video.mp4] + (r'!\[.*?\]\(([^\)]+)\)', 'image'), # ![alt](url) - 默认图片 + (r']+src=["\']([^"\']+)["\']', 'image'), # + (r']+src=["\']([^"\']+)["\']', 'video'), #