{
"session_id": "20260430_050434_9fb352",
"model": "glm-4.7",
"base_url": "https://api.z.ai/api/coding/paas/v4",
"platform": "weixin",
"session_start": "2026-04-30T05:04:34.808208",
"last_updated": "2026-04-30T05:06:52.243341",
"system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [14% — 328/2,200 chars]\n══════════════════════════════════════════════\n用户 GitHub: openjerry1995，拥有开源项目 ai_chat_history_exporter（Chrome 扩展），路径: /root/ai_chat_history_exporter，版本 v2.1.1，功能：导出 ChatGPT/Claude/Grok/Gemini 对话为 Markdown，100% 本地运行隐私保护，SSH 已配置可正常 Git 操作\n§\n用户服务器已安装自托管 SearxNG 搜索服务，位置：/root/searxng，虚拟环境：/root/searxng-venv，运行端口：8080，Hermes 配置文件已添加 web_search 后端指向 http://127.0.0.1:8080/search\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [4% — 61/1,375 chars]\n══════════════════════════════════════════════\n当用户询问实时性问题时（如新闻、最新动态、Reddit讨论等），默认使用 reddit-search skill 进行搜索\n\n# Holographic Memory\nActive. 25 facts stored with entity resolution and trust scoring.\nUse fact_store to search, probe entities, reason across entities, or add facts.\nUse fact_feedback to rate facts after using them (trains trust scores).\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n\n autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n - design-md: Author/validate/export Google's DESIGN.md token spec files.\n - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n - humanizer: Humanize text: strip AI-isms and add real voice.\n - ideation: Generate project ideas via creative constraints.\n - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n devops:\n - vpn-troubleshooting: Diagnose and fix VPN performance issues, especially MTU-r...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n dogfood:\n - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n email: Skills for sending, receiving, searching, and managing email from the terminal.\n - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n - obsidian: Read, search, and create notes in the Obsidian vault.\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n - notion: Notion API via curl: pages, databases, blocks, search.\n - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n red-teaming:\n - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n - arxiv: Search arXiv papers by keyword, author, category, or ID.\n - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n - reddit-search: Reddit search using self-hosted SearXNG metasearch\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - chrome-extension-development: Chrome Extension development — Manifest V3, service worke...\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n yuanbao:\n - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nConversation started: Thursday, April 30, 2026 05:04 AM\nModel: glm-4.7\nProvider: zai\n\nYou are on Weixin/WeChat. Markdown formatting is supported, so you may use it when it improves readability, but keep the message compact and chat-friendly. You can send media files natively: include MEDIA:/absolute/path/to/file in your response. Images are sent as native photos, videos play inline when supported, and other files arrive as downloadable documents. You can also include image URLs in markdown format  and they will be downloaded and sent as native media when possible.",
"tools": [
{
"type": "function",
"function": {
"name": "memory",
"description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"replace",
"remove"
],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": [
"memory",
"user"
],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
}
},
"required": [
"action",
"target"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_manage",
"description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"create",
"patch",
"edit",
"delete",
"write_file",
"remove_file"
],
"description": "The action to perform."
},
"name": {
"type": "string",
"description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
},
"content": {
"type": "string",
"description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
},
"category": {
"type": "string",
"description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
},
"file_path": {
"type": "string",
"description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
},
"file_content": {
"type": "string",
"description": "Content for the file. Required for 'write_file'."
}
},
"required": [
"action",
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_view",
"description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."
},
"file_path": {
"type": "string",
"description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."
}
},
"required": [
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skills_list",
"description": "List available skills (name + description). Use skill_view(name) to load full content.",
"parameters": {
"type": "object",
"properties": {
"category": {
"type": "string",
"description": "Optional category filter to narrow results"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "fact_store",
"description": "Deep structured memory with algebraic reasoning. Use alongside the memory tool — memory for always-on context, fact_store for deep recall and compositional queries.\n\nACTIONS (simple → powerful):\n• add — Store a fact the user would expect you to remember.\n• search — Keyword lookup ('editor config', 'deploy process').\n• probe — Entity recall: ALL facts about a person/thing.\n• related — What connects to an entity? Structural adjacency.\n• reason — Compositional: facts connected to MULTIPLE entities simultaneously.\n• contradict — Memory hygiene: find facts making conflicting claims.\n• update/remove/list — CRUD operations.\n\nIMPORTANT: Before answering questions about the user, ALWAYS probe or reason first.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"search",
"probe",
"related",
"reason",
"contradict",
"update",
"remove",
"list"
]
},
"content": {
"type": "string",
"description": "Fact content (required for 'add')."
},
"query": {
"type": "string",
"description": "Search query (required for 'search')."
},
"entity": {
"type": "string",
"description": "Entity name for 'probe'/'related'."
},
"entities": {
"type": "array",
"items": {
"type": "string"
},
"description": "Entity names for 'reason'."
},
"fact_id": {
"type": "integer",
"description": "Fact ID for 'update'/'remove'."
},
"category": {
"type": "string",
"enum": [
"user_pref",
"project",
"tool",
"general"
]
},
"tags": {
"type": "string",
"description": "Comma-separated tags."
},
"trust_delta": {
"type": "number",
"description": "Trust adjustment for 'update'."
},
"min_trust": {
"type": "number",
"description": "Minimum trust filter (default: 0.3)."
},
"limit": {
"type": "integer",
"description": "Max results (default: 10)."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "fact_feedback",
"description": "Rate a fact after using it. Mark 'helpful' if accurate, 'unhelpful' if outdated. This trains the memory — good facts rise, bad facts sink.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"helpful",
"unhelpful"
]
},
"fact_id": {
"type": "integer",
"description": "The fact ID to rate."
}
},
"required": [
"action",
"fact_id"
]
}
}
}
],
"message_count": 142,
"messages": [
{
"role": "user",
"content": "是不是搞不定？ 不行我自己上去设置微信吧"
},
{
"role": "assistant",
"content": "不是的！完全可以搞定。😄\n\n请问您想要做什么？是需要：\n- 配置微信机器人？\n- 设置消息推送？\n- 集成某个功能？\n- 还是其他什么？\n\n告诉我就好，我来帮您处理！",
"reasoning": "用户用中文问我\"是不是搞不定？不行我自己上去设置微信吧\"，意思是\"是不是搞不定？不行我自己上去设置微信吧\"。\n\n看起来用户可能是在等我的回应，或者是在询问某个任务是否完成。但是从当前会话上下文来看，这是会话的开始，我们还没有进行任何对话或任务。\n\n我需要礼貌地回应，询问用户想要做什么，或者是否之前有其他任务在进行中。\n\n让我用中文回复用户。"
},
{
"role": "user",
"content": "你是ubuntu还是mac上"
},
{
"role": "assistant",
"content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\n## Active Task\n用户询问：“帮我查一下知道最近的白宫记者协会枪击时间吗”\n\n## Goal\n用户想要查询关于“白宫记者协会枪击事件”的最新新闻报道。同时，用户之前要求优化 Reddit 搜索 Skill，移除 PullPush API 并修复 Google 搜索（当前使用 DuckDuckGo 替代）的 bug。\n\n## Constraints & Preferences\n* **VPN 设置**：需要支持 3 个设备同时连接，每个设备独立配置（IP 不冲突）。\n* **Reddit 搜索**：优先显示最近 12 个月内的帖子，优先高赞内容。\n* **技术栈**：搜索脚本使用 Python，注重性能（使用 regex 而非重型解析库），不需要完美的 HTML 格式。\n* **源限制**：用户明确要求移除 PullPush API；仅使用搜索引擎（DuckDuckGo/Google）进行 site:reddit.com 搜索。\n* **记忆偏好**：已记录当用户询问实时性问题时（新闻、动态、Reddit 讨论），默认使用 `reddit-search` skill。\n* **安全要求**：不得在总结中包含 API Keys、密码或 WireGuard 私钥。\n\n## Completed Actions\n1. **WireGuard VPN 服务端修复**：\n * 修改 `/etc/wireguard/wg0.conf`，将 MTU 从 1300 提升至 1420。\n * 为 3 个设备（Device 1/2/3）分别分配 IP：10.0.0.2, 10.0.0.3, 10.0.0.4。\n * 生成并配置了 3 对独立的 WireGuard 密钥。\n * 重启服务：`sudo wg-quick down wg0 && sudo wg-quick up wg0` [tool: terminal]\n2. **WireGuard 客户端配置生成**：\n * 生成了 3 个客户端配置文件：`/tmp/device1.conf`, `/tmp/device2.conf`, `/tmp/device3.conf`。\n * 为 Device 3 生成了 QR 码图片：`/tmp/device3_qr.png` [tool: write_file, qrencode, terminal]\n3. **Reddit Search Skill 创建与优化**：\n * 创建 Skill：`~/.hermes/skills/research/reddit-search/` [tool: write_file, terminal]\n * 实现 `search_reddit.py`，使用 Python regex 解析 HTML。\n * 实现评分算法：优先最近发布（7天+50分，30天+40分等）和高互动量。\n * **移除 PullPush API**：响应请求，将搜索源简化为仅 DuckDuckGo HTML 搜索（作为 Google 替代）。\n * **添加时间过滤**：默认限制为 12 个月内的结果，支持 `--days` 参数。\n * 修复 `relevance_score` 计算逻辑。\n * 更新 `SKILL.md` 文档至 v2.0.0。\n4. **搜索测试与调试**：\n * 多次测试 Skill 运行（如搜索 \"docker compose\", \"wireguard vpn\"）。\n * 发现 DuckDuckGo HTML 搜索端点返回 302/Challenge (Bot 检测)，导致脚本无法获取结果。\n\n## Active State\n* **环境**：Ubuntu 22.04 (racknerd-770948b)。\n* **VPN 状态**：\n * 服务端已重启，监听端口 51820。\n * Device 1 (10.0.0.2) 已连接。\n * MTU 已设为 1420。\n* **Reddit Search Skill 状态**：\n * 脚本位于 `~/.hermes/skills/research/reddit-search/scripts/search_reddit.py`。\n * **当前问题**：DuckDuckGo 对自动化请求启用了 Bot 保护（返回 202 状态码或 Challenge 表单），导致搜索功能失效。\n * 之前尝试使用 Bing 搜索 (`curl` to bing.com) 返回 200 状态，但尚未集成到 Python 脚本中进行解析。\n* **用户记忆**：已添加 \"当用户询问实时性问题时默认使用 reddit-search skill\"。\n\n## In Progress\n正在尝试通过 `curl` 和 Python `requests` 验证“白宫记者协会枪击”相关新闻。由于 DuckDuckGo 被 Bot 屏蔽，目前尝试直接访问 Bing 搜索获取 HTML 内容，但尚未成功提取出具体的新闻事件详情。\n\n## Blocked\n* **搜索功能受阻**：DuckDuckGo HTML 搜索端点检测到自动化脚本，返回 Challenge 页面而非搜索结果。\n* **PullPush API 移除**：已按用户要求移除，无法回退使用。\n* **无有效搜索源**：目前没有可用的免费、无需认证且能绕过 Bot 检测的 `site:reddit.com` 搜索方案。\n\n## Key Decisions\n* **WireGuard 多设备配置**：决定在服务端 `wg0.conf` 中添加多个 `[Peer]` 段，每个 Peer 对应一个固定的 IP 地址（.2, .3, .4），解决了之前 3 个设备共用配置导致的 IP 冲突和速度慢的问题。\n* **Skill 搜索策略**：用户要求删除 PullPush 且用 Python 解析库（性能优先），因此选择了基于 Regex 的 DuckDuckGo HTML 抓取方案，但这导致了当前的 Bot 屏蔽问题。\n* **MTU 调整**：将 MTU 从 1300 提升至 1420 以解决 VPN 性能瓶颈。\n\n## Resolved Questions\n1. **如何停止 Mac 上的 Hermes？** -> 提供了 `pkill` 命令和检查 `launchd`/`config.yaml` 的步骤。\n2. **VPN 变慢的原因？** -> 确诊为 MTU 过低（1300）和三设备共用一个配置导致 IP 冲突。\n3. **如何支持多设备 VPN？** -> 已在服务端配置并生成了 3 个独立的客户端配置文件（含 QR 码）。\n4. **Reddit 搜索最佳免费方案？** -> 调研了 Google Site Search, PullPush, 旧版 Reddit 等方案，并创建了整合 Skill。\n5. **能否用 curl 直接调 Google？** -> 解释了当前实现使用的是 DuckDuckGo HTML 搜索，直接调用 Google 搜索需要处理复杂的 Bot 防护和 Cookie，且通常需要 API Key。\n\n## Pending User Asks\n* **回答关于“白宫记者协会枪击事件”的新闻查询**（目前因搜索工具失效未完成）。\n* **修复 Google 搜索的 bug**（需要找到能绕过 Bot 检测的新搜索源或解析方案）。\n\n## Relevant Files\n* `/etc/wireguard/wg0.conf`：VPN 服务端配置，包含 3 个 Peer 配置，MTU 1420。私钥已 Redact。\n* `/tmp/device1.conf`, `/tmp/device2.conf`, `/tmp/device3.conf`：3 个设备的客户端配置文件，包含各自的 [REDACTED] PrivateKey 和独立 IP。\n* `/tmp/device3_qr.png`：Device 3 的配置二维码图片。\n* `~/.hermes/skills/research/reddit-search/SKILL.md`：Skill 说明文档 (v2.0.0)。\n* `~/.hermes/skills/research/reddit-search/scripts/search_reddit.py`：Python 搜索脚本，当前使用 DuckDuckGo（已失效）。\n* `~/.hermes/skills/research/reddit-search/references/sources.md`：API 来源参考文档。\n\n## Remaining Work\n1. **修复搜索功能**：\n * 寻找替代 DuckDuckGo 的搜索源（如 Bing HTML 解析、旧版 Reddit 直接搜索）。\n * 或者实现 Reddit 官方 API（如果用户可提供 Token）。\n * 目前尝试 Bing 搜索返回了 HTML，需要解析提取 `reddit.com` 链接。\n2. **响应用户的新闻查询**：在搜索功能恢复后，查询“白宫记者协会枪击”的相关信息。\n\n## Critical Context\n* WireGuard 服务端公钥 Endpoint：`23.94.194.34:51820`。\n* 客户端配置中的 `[Peer] PublicKey`（服务端公钥）：`FjHHksJSi3wbBW8UoevUTPgk2XeL5dTLmXByEka/yBU=`。\n* 用户的 VPN 环境已修复，但 AI 助手的搜索能力（Reddit/新闻）当前因反爬虫机制暂时不可用。\n* 时间戳校准问题：之前的测试中 PullPush API 返回的日期（如 2025-05-19）与系统当前时间（2026-04-30，基于工具输出）存在偏差，这也是移除 PullPush 的原因之一。\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---",
"tool_calls": [
{
"id": "call_1fc0020ac0644c4a93f6f3ed",
"call_id": "call_1fc0020ac0644c4a93f6f3ed",
"response_item_id": "fc_1fc0020ac0644c4a93f6f3ed",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 -c \\\"\\nimport requests\\nimport re\\n\\nurl = 'https://www.bing.com/search?q=white+house+shooting+2025&setlang=en'\\nheaders = {\\n 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'\\n}\\n\\nr = requests.get(url, headers=headers, timeout=10)\\n\\n# 寻找新闻标题和链接\\n# Bing 的结果通常在特定的 class 中\\nlines = r.text.split('\\\\\\\\n')\\nfor i, line in enumerate(lines):\\n if 'shooting' in line.lower() and ('href' in line.lower() or 'white' in line.lower()):\\n # 打印上下文\\n start = max(0, i-2)\\n end = min(len(lines), i+3)\\n print('\\\\\\\\n'.join(lines[start:end]))\\n print('---')\\n if i > 200:\\n break\\n\\\"\"}"
}
}
],
"reasoning": "好，Bing 返回了页面。让我解析页面内容来找到实际的新闻链接。",
"reasoning_content": "好，Bing 返回了页面。让我解析页面内容来找到实际的新闻链接。"
},
{
"role": "tool",
"content": "{\"output\": \"white house shooting 2025 - Searchwhite house shooting 2025 - Searchwhite house shooting 2025 - Search