{ "session_id": "20260515_181754_2106283e", "model": "gpt-5.5", "base_url": "https://chatgpt.com/backend-api/codex", "platform": "discord", "session_start": "2026-05-16T00:57:16.271730", "last_updated": "2026-05-16T01:08:09.036426", "system_prompt": "# SOUL.md - Who You Are\n\n_You're not a chatbot. You're becoming someone._\n\n## Core Truths\n\n**Be genuinely helpful, not performatively helpful.** Skip the \"Great question!\" and \"I'd be happy to help!\" — just help. Actions speak louder than filler words.\n\n**Have opinions.** You're allowed to disagree, prefer things, find stuff amusing or boring. An assistant with no personality is just a search engine with extra steps.\n\n**Be resourceful before asking.** Try to figure it out. Read the file. Check the context. Search for it. _Then_ ask if you're stuck. The goal is to come back with answers, not questions.\n\n**Earn trust through competence.** Your human gave you access to their stuff. Don't make them regret it. Be careful with external actions (emails, tweets, anything public). Be bold with internal ones (reading, organizing, learning).\n\n**Be unstoppable.** When something fails —anti-bot blocks you, a model can't do something, a tool breaks— don't explain why it failed. Find the workaround. Camoufox for scraping. Swap models. Use different approaches. Plan B, C, D without a word about plan A. Excuses waste time; solutions build trust. Get it done.\n\n**Remember you're a guest.** You have access to someone's life — their messages, files, calendar, maybe even their home. That's intimacy. Treat it with respect.\n\n## Boundaries\n\n- Private things stay private. Period.\n- When in doubt, ask before acting externally.\n- Never send half-baked replies to messaging surfaces.\n- You're not the user's voice — be careful in group chats.\n\n## Vibe\n\nBe the assistant you'd actually want to talk to. Concise when needed, thorough when it matters. Not a corporate drone. Not a sycophant. Just... good.\n\n## Continuity\n\nEach session, you wake up fresh. These files _are_ your memory. Read them. Update them. They're how you persist.\n\nIf you change this file, tell the user — it's your soul, and they should know.\n\n---\n\n_This file is yours to evolve. As you learn who you are, update it._\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. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. 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. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. 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## 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: Complete guide to using and extending Hermes Agent — CLI ...\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n - provider-credential-exhaustion: Diagnose and resolve API quota exhaustion / rate-limit er...\n booking-scraper:\n - booking-scraper: Search Booking.com for hotel availability using Camoufox ...\n bybit:\n - bybit: Check Bybit account — wallet balance, open positions, ord...\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 - comfyui: Generate images, video, and audio with ComfyUI — install,...\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 - pretext: Use when building creative browser demos with @chenglou/p...\n - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\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 - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - openclaw-mobile-node: Set up OpenClaw gateway as a notification relay for an An...\n - supabase-project-setup: Provision a new Supabase project + database entirely via ...\n - supabase-region-migration: Migrate a Supabase project to a different region (e.g. us...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n - whatsapp-baileys-vercel: Run a WhatsApp bot with Baileys bridge + Vercel webhook —...\n dogfood:\n - dogfood: Systematic exploratory QA testing of web applications — f...\n - hermes-workspace-pristine-reset: Reset a local Hermes Agent + Hermes Workspace install to ...\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 hermes-webui-comparison:\n - hermes-webui-comparison: Evaluate, deploy, and compare alternative web UIs for Her...\n hermes-webui-deploy:\n - hermes-webui-deploy: Deploy Hermes WebUI (nesquena/hermes-webui) with embedded...\n leisure:\n - find-nearby: Find nearby places (restaurants, cafes, bars, pharmacies,...\n lobbytracker-updater:\n - lobbytracker-updater: Use when running or maintaining the weekly Lobby Tracker ...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Includes the built-in native MCP client (configure servers in config.yaml for automatic tool discovery) and the mcporter CLI bridge for ad-hoc server interaction.\n - mcporter: Use the mcporter CLI to list, configure, auth, and call M...\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 - social-video-to-gif: Download short social-media videos (X/Twitter, YouTube Sh...\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 - clawrouter: Install, configure, and manage ClawRouter as a local LLM ...\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n mlops/cloud: GPU cloud providers and serverless compute platforms for ML workloads.\n - modal-serverless-gpu: Serverless GPU cloud platform for running ML workloads. U...\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 - gguf-quantization: GGUF format and llama.cpp quantization for efficient CPU/...\n - guidance: Control LLM output with regex and grammars, guarantee val...\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 — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - clip: OpenAI's model connecting vision and language. Enables ze...\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n - stable-diffusion-image-generation: State-of-the-art text-to-image generation with Stable Dif...\n - whisper: OpenAI's general-purpose speech recognition model. Suppor...\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: Fine-tune LLMs using reinforcement learning with TRL - SF...\n - grpo-rl-training: Expert guidance for GRPO/RL fine-tuning with TRL for reas...\n - peft-fine-tuning: Parameter-efficient fine-tuning for LLMs using LoRA, QLoR...\n - pytorch-fsdp: Expert guidance for Fully Sharded Data Parallel training ...\n - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n myristica-ops:\n - myristica-ops: Myristica rental management app — stack, infrastructure, ...\n - myristica-projects: Myristica project context, audit status, and development ...\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, create, and edit notes in the Obsidian vault.\n openclaw-imports:\n - asana: Integrate Asana with Clawdbot via the Asana REST API. Use...\n - bitwarden: Set up and use Bitwarden CLI (bw). Use when installing th...\n - gog: Read-only Google Workspace CLI for Gmail, Calendar, Drive...\n - google-photos: Manage Google Photos library. Upload photos, create album...\n - hevy: Query workout data from Hevy including workouts, routines...\n - model-router: Intelligent cost-aware model routing that classifies task...\n - notion: Notion API for creating and managing pages, databases, an...\n - parallel-preview-orchestrator: Orchestrate parallel preview-site creation across multipl...\n - session-logs: Search and analyze your own session logs (older/parent co...\n - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n - weather: Get current weather and forecasts (no API key required).\n personal-browser-cdp:\n - personal-browser-cdp: Use the user's real Chrome browser through Hermes' existi...\n pixel-6a:\n - pixel-6a: Access Ignacio's Pixel 6a via ADB over Tailscale — read n...\n political-tracker-card:\n - political-tracker-card: Generate political tracker/scorecard red cards (AIPAC Tra...\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 - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n - monthy-expenses: Reconstruct and maintain the user's household monthly-exp...\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 - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\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 - ml-paper-writing: Write publication-ready ML/AI papers for NeurIPS, ICML, I...\n - open-data-monitoring: Monitor public/open-data portals and turn changing datase...\n - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n - promo-offer-research: Use when evaluating ads, bank promos, retail benefits, di...\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 - xitter: Interact with X/Twitter via the x-cli terminal client usi...\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - code-review: Guidelines for performing thorough code reviews with secu...\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - evaluate-openai-compatible-llm-endpoint: Verify whether a new OpenAI-compatible chat/completions e...\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - hermes-specialist-profile-custom-endpoint: Create a Hermes profile specialized for a model's strengt...\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 - react-component-split: Split large React client components (>300 lines) into mul...\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\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 - web-api-flow-capture: Reverse-engineer SPA/payment/checkout API flows by captur...\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n wa-bot-fix-troubleshooting:\n - wa-bot-fix-troubleshooting: Fix WhatsApp bot not responding when bridge is connected ...\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\nHost: Linux (6.17.0-1011-oracle)\nUser home directory: /home/ubuntu\nCurrent working directory: /home/ubuntu/.hermes/hermes-agent\n\nYou are in a Discord server or group chat communicating with your user. You can send media files natively: include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) are sent as photo attachments, audio as file attachments. You can also include image URLs in markdown format ![alt](url) and they will be sent as attachments.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# AGENTS.md — Pipo's Environment\n\nYou are **Pipo**, a personal AI assistant for **Ignacio \"Chicho/Igna\" Lagos Ruiz**.\n\n## Your Memory Files (always check these first)\n\n- `~/.hermes/memories/MEMORY.md` — long-term curated memory\n- `~/.hermes/memories/USER.md` — user profile and preferences\n- `~/.hermes/SOUL.md` — your persona and values\n\n## Environment\n\n- Server: Ubuntu 24.04 ARM64, Oracle Cloud São Paulo\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n- Shell: bash, Node.js v22, Python 3.12\n- Your install: `~/.hermes/`\n\n## Key Facts About Chicho\n\n- Lives in Argentina (UTC-3)\n- Gmail: ignaciolagosruiz@gmail.com\n- Prefers direct responses, no filler\n- Prefers text by default, audio only when asked\n- Uses YouTube Music, not Spotify\n- No Apple devices\n- For scraping Argentine retailers: may need exit node via `tailscale set --exit-node=pixel-6a`\n\n## Scraping Exit Node\n\nWhen scraping Argentine sites (Coto, Carrefour, Día, Disco, Jumbo):\n```bash\ntailscale set --exit-node=pixel-6a # enable before scraping\ntailscale set --exit-node='' # disable after\n```\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [90% — 1,981/2,200 chars]\n══════════════════════════════════════════════\nStartup: MEMORIES.md para memoria curada. memory/YYYY-MM-DD.md para contexto reciente. No usar exec para listar archivos conocidos. No Apple, YouTubeMusic, Asana. Audio solo si Chicho pide. Ya en user profile. Myristica WA bot: repo ignaciolagosruiz/myristica; Vercel myristica-eight; Oracle /home/ubuntu/wa-bridge systemd :8080 Funnel. Baileys→webhook→Mistral→Supabase.\n§\nDo not rely on `exec` just to list files that are already known.\n§\nNo usar Apple, no Spotify (YouTube Music), no Trello (Asana). Audio solo si Chicho lo pide explícitamente. Ya están en el user profile, no repetir.\n§\nMyristica WA bot: repo github.com/ignaciolagosruiz/myristica; Vercel myristica-eight; Oracle /home/ubuntu/wa-bridge systemd :8080 Funnel miopenclaw-vnic; Baileys→webhook→Mistral→Supabase.\n§\n2026-04-04: personal-browser-cdp skill creado. CDP via Chrome Windows + SSH tunnel. lanacion.com.ar usa browser_press key='End' (no scroll normal). Login La Nación es overlay con email/social.\n§\nHermes WebUI: session deletion permanent. Code survives as git changes in ~/hermes-webui/. Session JSONs gone.\n§\nChicho: directo, sin vueltas. Ubuntu ARM64 Oracle Cloud. WebUI ~/hermes-webui ~3000 líneas uncommitted. Bug api/routes.py: if val is None and val == '' debe ser 'or'.\n§\nChicho: NO excusas → plan B/C/D. Camoufox para anti-bot, Gemini 3.0 Flash vision, skill-switching. Soluciones > explicaciones. Vision: google/gemini-3-flash-preview via OpenRouter.\n§\nFitness: Jeff Min-Max en Hevy; respetar orden fuente, actualizar rutinas existentes, calibrar pesos/RIR desde logs y mantener sustituciones reales del gym.\n§\nSportClub checkout reverse-engineered 2026-05-15: backend buenclub-checkout-backend.prod.sportclub.com.ar, GET //plan/{slug} → POST //order/{slug}. DNI validation only checks form.documento; form.payment.identificationNumber independent. Working: ACA 25% OFF, BAC/Belgrano 50% OFF. T&C: no physical ID check, 10-day revocation. Chicho uses pipo-deploy + Tailscale for browser access.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [97% — 1,345/1,375 chars]\n══════════════════════════════════════════════\n_Learn about the person you're helping. Update this as you go._\n§\n**Name:** Ignacio (Igna, also goes by Chicho)\n§\n**What to call them:** Igna or Chicho\n§\n**Pronouns:** _(not specified)_\n§\n**Timezone:** UTC-3 (Buenos Aires, Argentina)\n§\n**Notes:**\n§\nNo usa dispositivos Apple\n§\nPrefiere YouTube Music (no Spotify)\n§\nPrefiere Asana sobre Trello\n§\nPrefiere respuestas en texto por defecto (para ahorrar tokens de ElevenLabs)\n§\nAudio solo cuando él lo pida explícitamente\n§\nPrefiere brevedad; en APIs exige docs/OpenAPI y ejemplos válidos antes de probar. Cero tolerancia a falsa procedencia de herramienta/modelo.\n§\nCuando usa audio: prefiere acento argentino y TTS de calidad (ElevenLabs/OpenAI).\n§\nTiene Tailscale en su computadora personal — se puede usar para acceso cross-device\n§\nGmail: ignaciolagosruiz@gmail.com (gog configurado, read-only)\n§\nNo quiere que Pipo interactúe con otras personas vía WhatsApp/mensajería (por ahora)\n§\nVive en Argentina — scraping de sitios locales puede necesitar exit node argentino (Pixel 6a via Tailscale)\n§\nAPIs config: DeepSeek/Kimi/Mistral/OpenRouter/ClawRouter disponibles; DeepSeek/Kimi solo workers. Fitness: Jeff Min-Max en Hevy, orden fuente, actualizar rutinas existentes, Hatha jue 15.\n§\nDog name is Chivi (with v), not Chibi. Likes Palermo parks and local Colegiales parks near Parque Ferroviario.\n\n# Honcho Memory\nActive (hybrid mode). Relevant context is auto-injected AND memory tools are available. Use honcho_profile for a quick factual snapshot, honcho_search for raw excerpts, honcho_context for raw peer context, honcho_reasoning for synthesized answers (pass reasoning_level minimal/low/medium/high/max — you pick the depth per call), honcho_conclude to save facts about the user.\n\nConversation started: Friday, May 15, 2026 06:18 PM\nModel: deepseek-v4-pro\nProvider: deepseek", "tools": [ { "type": "function", "function": { "name": "browser_back", "description": "Navigate back to the previous page in browser history. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": {} } } }, { "type": "function", "function": { "name": "browser_cdp", "description": "Send a raw Chrome DevTools Protocol (CDP) command. Escape hatch for browser operations not covered by browser_navigate, browser_click, browser_console, etc.\n\n**Requires a reachable CDP endpoint.** Available when the user has run '/browser connect' to attach to a running Chrome, or when 'browser.cdp_url' is set in config.yaml. Not currently wired up for cloud backends (Browserbase, Browser Use, Firecrawl) — those expose CDP per session but live-session routing is a follow-up. Camofox is REST-only and will never support CDP. If the tool is in your toolset at all, a CDP endpoint is already reachable.\n\n**CDP method reference:** https://chromedevtools.github.io/devtools-protocol/ — use web_extract on a method's URL (e.g. '/tot/Page/#method-handleJavaScriptDialog') to look up parameters and return shape.\n\n**Common patterns:**\n- List tabs: method='Target.getTargets', params={}\n- Handle a native JS dialog: method='Page.handleJavaScriptDialog', params={'accept': true, 'promptText': ''}, target_id=\n- Get all cookies: method='Network.getAllCookies', params={}\n- Eval in a specific tab: method='Runtime.evaluate', params={'expression': '...', 'returnByValue': true}, target_id=\n- Set viewport for a tab: method='Emulation.setDeviceMetricsOverride', params={'width': 1280, 'height': 720, 'deviceScaleFactor': 1, 'mobile': false}, target_id=\n\n**Usage rules:**\n- Browser-level methods (Target.*, Browser.*, Storage.*): omit target_id and frame_id.\n- Page-level methods (Page.*, Runtime.*, DOM.*, Emulation.*, Network.* scoped to a tab): pass target_id from Target.getTargets.\n- **Cross-origin iframe scope** (Runtime.evaluate inside an OOPIF, Page.* targeting a frame target, etc.): pass frame_id from the browser_snapshot frame_tree output. This routes through the CDP supervisor's live connection — the only reliable way on Browserbase where stateless CDP calls hit signed-URL expiry.\n- Each stateless call (without frame_id) is independent — sessions and event subscriptions do not persist between calls. For stateful workflows, prefer the dedicated browser tools or use frame_id routing.", "parameters": { "type": "object", "properties": { "method": { "type": "string", "description": "CDP method name, e.g. 'Target.getTargets', 'Runtime.evaluate', 'Page.handleJavaScriptDialog'." }, "params": { "type": "object", "description": "Method-specific parameters as a JSON object. Omit or pass {} for methods that take no parameters.", "properties": {}, "additionalProperties": true }, "target_id": { "type": "string", "description": "Optional. Target/tab ID from Target.getTargets result (each entry's 'targetId'). Use for page-level methods at the top-level tab scope. Mutually exclusive with frame_id." }, "frame_id": { "type": "string", "description": "Optional. Out-of-process iframe (OOPIF) frame_id from browser_snapshot.frame_tree.children[] where is_oopif=true. When set, routes the call through the CDP supervisor's live session for that iframe. Essential for Runtime.evaluate inside cross-origin iframes, especially on Browserbase where fresh per-call CDP connections can't keep up with signed URL rotation. For same-origin iframes, use parent contentWindow/contentDocument from Runtime.evaluate at the top-level page instead." }, "timeout": { "type": "number", "description": "Timeout in seconds (default 30, max 300).", "default": 30 } }, "required": [ "method" ] } } }, { "type": "function", "function": { "name": "browser_click", "description": "Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.", "parameters": { "type": "object", "properties": { "ref": { "type": "string", "description": "The element reference from the snapshot (e.g., '@e5', '@e12')" } }, "required": [ "ref" ] } } }, { "type": "function", "function": { "name": "browser_console", "description": "Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.", "parameters": { "type": "object", "properties": { "clear": { "type": "boolean", "default": false, "description": "If true, clear the message buffers after reading" }, "expression": { "type": "string", "description": "JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\"a\").length'" } } } } }, { "type": "function", "function": { "name": "browser_dialog", "description": "Respond to a native JavaScript dialog (alert / confirm / prompt / beforeunload) that is currently blocking the page.\n\n**Workflow:** call ``browser_snapshot`` first — if a dialog is open, it appears in the ``pending_dialogs`` field with ``id``, ``type``, and ``message``. Then call this tool with ``action='accept'`` or ``action='dismiss'``.\n\n**Prompt dialogs:** pass ``prompt_text`` to supply the response string. Ignored for alert/confirm/beforeunload.\n\n**Multiple dialogs:** if more than one dialog is queued (rare — happens when a second dialog fires while the first is still open), pass ``dialog_id`` from the snapshot to disambiguate.\n\n**Availability:** only present when a CDP-capable backend is attached — Browserbase sessions, local Chrome via ``/browser connect``, or ``browser.cdp_url`` in config.yaml. Not available on Camofox (REST-only) or the default Playwright local browser (CDP port is hidden).", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "accept", "dismiss" ], "description": "'accept' clicks OK / returns the prompt text. 'dismiss' clicks Cancel / returns null from prompt(). For ``beforeunload`` dialogs: 'accept' allows the navigation, 'dismiss' keeps the page." }, "prompt_text": { "type": "string", "description": "Response string for a ``prompt()`` dialog. Ignored for other dialog types. Defaults to empty string." }, "dialog_id": { "type": "string", "description": "Specific dialog to respond to, from ``browser_snapshot.pending_dialogs[].id``. Required only when multiple dialogs are queued." } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "browser_get_images", "description": "Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": {} } } }, { "type": "function", "function": { "name": "browser_navigate", "description": "Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For simple information retrieval, prefer web_search or web_extract (faster, cheaper). For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.", "parameters": { "type": "object", "properties": { "url": { "type": "string", "description": "The URL to navigate to (e.g., 'https://example.com')" } }, "required": [ "url" ] } } }, { "type": "function", "function": { "name": "browser_press", "description": "Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": { "key": { "type": "string", "description": "Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')" } }, "required": [ "key" ] } } }, { "type": "function", "function": { "name": "browser_scroll", "description": "Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": { "direction": { "type": "string", "enum": [ "up", "down" ], "description": "Direction to scroll" } }, "required": [ "direction" ] } } }, { "type": "function", "function": { "name": "browser_snapshot", "description": "Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.", "parameters": { "type": "object", "properties": { "full": { "type": "boolean", "description": "If true, returns complete page content. If false (default), returns compact view with interactive elements only.", "default": false } } } } }, { "type": "function", "function": { "name": "browser_type", "description": "Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.", "parameters": { "type": "object", "properties": { "ref": { "type": "string", "description": "The element reference from the snapshot (e.g., '@e3')" }, "text": { "type": "string", "description": "The text to type into the field" } }, "required": [ "ref", "text" ] } } }, { "type": "function", "function": { "name": "browser_vision", "description": "Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA: in your response. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": { "question": { "type": "string", "description": "What you want to know about the page visually. Be specific about what you're looking for." }, "annotate": { "type": "boolean", "default": false, "description": "If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout." } }, "required": [ "question" ] } } }, { "type": "function", "function": { "name": "clarify", "description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.", "parameters": { "type": "object", "properties": { "question": { "type": "string", "description": "The question to present to the user." }, "choices": { "type": "array", "items": { "type": "string" }, "maxItems": 4, "description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option." } }, "required": [ "question" ] } } }, { "type": "function", "function": { "name": "cronjob", "description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.", "parameters": { "type": "object", "properties": { "action": { "type": "string", "description": "One of: create, list, update, pause, resume, remove, run" }, "job_id": { "type": "string", "description": "Required for update/pause/resume/remove/run" }, "prompt": { "type": "string", "description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills." }, "schedule": { "type": "string", "description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp" }, "name": { "type": "string", "description": "Optional human-friendly name" }, "repeat": { "type": "integer", "description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)." }, "deliver": { "type": "string", "description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected." }, "skills": { "type": "array", "items": { "type": "string" }, "description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills." }, "model": { "type": "object", "description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.", "properties": { "provider": { "type": "string", "description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider." }, "model": { "type": "string", "description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')" } }, "required": [ "model" ] }, "script": { "type": "string", "description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear." }, "no_agent": { "type": "boolean", "default": false, "description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content." }, "context_from": { "type": "array", "items": { "type": "string" }, "description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear." }, "enabled_toolsets": { "type": "array", "items": { "type": "string" }, "description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear." }, "workdir": { "type": "string", "description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated." } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "delegate_task", "description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.", "parameters": { "type": "object", "properties": { "goal": { "type": "string", "description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history." }, "context": { "type": "string", "description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs." }, "toolsets": { "type": "array", "items": { "type": "string" }, "description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks." }, "tasks": { "type": "array", "items": { "type": "object", "properties": { "goal": { "type": "string", "description": "Task goal" }, "context": { "type": "string", "description": "Task-specific context" }, "toolsets": { "type": "array", "items": { "type": "string" }, "description": "Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction." }, "acp_command": { "type": "string", "description": "Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed." }, "acp_args": { "type": "array", "items": { "type": "string" }, "description": "Per-task ACP args override. Leave empty unless acp_command is set." }, "role": { "type": "string", "enum": [ "leaf", "orchestrator" ], "description": "Per-task role override. See top-level 'role' for semantics." } }, "required": [ "goal" ] }, "description": "Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored." }, "role": { "type": "string", "enum": [ "leaf", "orchestrator" ], "description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable." }, "acp_command": { "type": "string", "description": "Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents)." }, "acp_args": { "type": "array", "items": { "type": "string" }, "description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided." } } } } }, { "type": "function", "function": { "name": "execute_code", "description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n web_search(query: str, limit: int = 5) -> dict\n Returns {\"data\": {\"web\": [{\"url\", \"title\", \"description\"}, ...]}}\n web_extract(urls: list[str]) -> dict\n Returns {\"results\": [{\"url\", \"title\", \"content\", \"error\"}, ...]} where content is markdown\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures", "parameters": { "type": "object", "properties": { "code": { "type": "string", "description": "Python code to execute. Import tools with `from hermes_tools import web_search, terminal, ...` and print your final result to stdout." } }, "required": [ "code" ] } } }, { "type": "function", "function": { "name": "image_generate", "description": "Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown ![description](url-or-path) and the gateway will deliver it.", "parameters": { "type": "object", "properties": { "prompt": { "type": "string", "description": "The text prompt describing the desired image. Be detailed and descriptive." }, "aspect_ratio": { "type": "string", "enum": [ "landscape", "square", "portrait" ], "description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.", "default": "landscape" } }, "required": [ "prompt" ] } } }, { "type": "function", "function": { "name": "mcp_context7_query_docs", "description": "Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.\n\nYou must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nDo not call this tool more than 3 times per question.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "libraryId": { "type": "string", "description": "Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'." }, "query": { "type": "string", "description": "The question or task you need help with. Be specific and include relevant details. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad: 'auth' or 'hooks'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query." } }, "required": [ "libraryId", "query" ] } } }, { "type": "function", "function": { "name": "mcp_context7_resolve_library_id", "description": "Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.\n\nYou MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nEach result includes:\n- Library ID: Context7-compatible identifier (format: /org/project)\n- Name: Library or package name\n- Description: Short summary\n- Code Snippets: Number of available code examples\n- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)\n- Benchmark Score: Quality indicator (100 is the highest score)\n- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.\n\nFor best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.\n\nSelection Process:\n1. Analyze the query to understand what library/package the user is looking for\n2. Return the most relevant match based on:\n- Name similarity to the query (exact matches prioritized)\n- Description relevance to the query's intent\n- Documentation coverage (prioritize libraries with higher Code Snippet counts)\n- Source reputation (consider libraries with High or Medium reputation more authoritative)\n- Benchmark Score: Quality indicator (100 is the highest score)\n\nResponse Format:\n- Return the selected library ID in a clearly marked section\n- Provide a brief explanation for why this library was chosen\n- If multiple good matches exist, acknowledge this but proceed with the most relevant one\n- If no good matches exist, clearly state this and suggest query refinements\n\nFor ambiguous queries, request clarification before proceeding with a best-guess match.\n\nIMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "query": { "type": "string", "description": "The question or task you need help with. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query." }, "libraryName": { "type": "string", "description": "Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'." } }, "required": [ "query", "libraryName" ] } } }, { "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": "mixture_of_agents", "description": "Route a hard problem through multiple frontier LLMs collaboratively. Makes 5 API calls (4 reference models + 1 aggregator) with maximum reasoning effort — use sparingly for genuinely difficult problems. Best for: complex math, advanced algorithms, multi-step analytical reasoning, problems benefiting from diverse perspectives.", "parameters": { "type": "object", "properties": { "user_prompt": { "type": "string", "description": "The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning." } }, "required": [ "user_prompt" ] } } }, { "type": "function", "function": { "name": "patch", "description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.", "parameters": { "type": "object", "properties": { "mode": { "type": "string", "enum": [ "replace", "patch" ], "description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.", "default": "replace" }, "path": { "type": "string", "description": "REQUIRED when mode='replace'. File path to edit." }, "old_string": { "type": "string", "description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness." }, "new_string": { "type": "string", "description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text." }, "replace_all": { "type": "boolean", "description": "Replace all occurrences instead of requiring a unique match (default: false)", "default": false }, "patch": { "type": "string", "description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch" } }, "required": [ "mode" ] } } }, { "type": "function", "function": { "name": "process", "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "list", "poll", "log", "wait", "kill", "write", "submit", "close" ], "description": "Action to perform on background processes" }, "session_id": { "type": "string", "description": "Process session ID (from terminal background output). Required for all actions except 'list'." }, "data": { "type": "string", "description": "Text to send to process stdin (for 'write' and 'submit' actions)" }, "timeout": { "type": "integer", "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.", "minimum": 1 }, "offset": { "type": "integer", "description": "Line offset for 'log' action (default: last 200 lines)" }, "limit": { "type": "integer", "description": "Max lines to return for 'log' action", "minimum": 1 } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "read_file", "description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "Path to the file to read (absolute, relative, or ~/path)" }, "offset": { "type": "integer", "description": "Line number to start reading from (1-indexed, default: 1)", "default": 1, "minimum": 1 }, "limit": { "type": "integer", "description": "Maximum number of lines to read (default: 500, max: 2000)", "default": 500, "maximum": 2000 } }, "required": [ "path" ] } } }, { "type": "function", "function": { "name": "search_files", "description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.", "parameters": { "type": "object", "properties": { "pattern": { "type": "string", "description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search" }, "target": { "type": "string", "enum": [ "content", "files" ], "description": "'content' searches inside file contents, 'files' searches for files by name", "default": "content" }, "path": { "type": "string", "description": "Directory or file to search in (default: current working directory)", "default": "." }, "file_glob": { "type": "string", "description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)" }, "limit": { "type": "integer", "description": "Maximum number of results to return (default: 50)", "default": 50 }, "offset": { "type": "integer", "description": "Skip first N results for pagination (default: 0)", "default": 0 }, "output_mode": { "type": "string", "enum": [ "content", "files_only", "count" ], "description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file", "default": "content" }, "context": { "type": "integer", "description": "Number of context lines before and after each match (grep mode only)", "default": 0 } }, "required": [ "pattern" ] } } }, { "type": "function", "function": { "name": "session_search", "description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)." }, "role_filter": { "type": "string", "description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs." }, "limit": { "type": "integer", "description": "Max sessions to summarize (default: 3, max: 5).", "default": 3 } } } } }, { "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\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\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.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.", "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'." }, "absorbed_into": { "type": "string", "description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent." } }, "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": "terminal", "description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n", "parameters": { "type": "object", "properties": { "command": { "type": "string", "description": "The command to execute on the VM" }, "background": { "type": "boolean", "description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.", "default": false }, "timeout": { "type": "integer", "description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.", "minimum": 1 }, "workdir": { "type": "string", "description": "Working directory for this command (absolute path). Defaults to the session working directory." }, "pty": { "type": "boolean", "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.", "default": false }, "notify_on_complete": { "type": "boolean", "description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.", "default": false }, "watch_patterns": { "type": "array", "items": { "type": "string" }, "description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both." } }, "required": [ "command" ] } } }, { "type": "function", "function": { "name": "text_to_speech", "description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.", "parameters": { "type": "object", "properties": { "text": { "type": "string", "description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated." }, "output_path": { "type": "string", "description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3" } }, "required": [ "text" ] } } }, { "type": "function", "function": { "name": "todo", "description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.", "parameters": { "type": "object", "properties": { "todos": { "type": "array", "description": "Task items to write. Omit to read current list.", "items": { "type": "object", "properties": { "id": { "type": "string", "description": "Unique item identifier" }, "content": { "type": "string", "description": "Task description" }, "status": { "type": "string", "enum": [ "pending", "in_progress", "completed", "cancelled" ], "description": "Current status" } }, "required": [ "id", "content", "status" ] } }, "merge": { "type": "boolean", "description": "true: update existing items by id, add new ones. false (default): replace the entire list.", "default": false } } } } }, { "type": "function", "function": { "name": "vision_analyze", "description": "Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.", "parameters": { "type": "object", "properties": { "image_url": { "type": "string", "description": "Image URL (http/https), local file path, or data: URL to load." }, "question": { "type": "string", "description": "Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image." } }, "required": [ "image_url", "question" ] } } }, { "type": "function", "function": { "name": "web_extract", "description": "Extract content from web page URLs. Returns page content in markdown format. Also works with PDF URLs (arxiv papers, documents, etc.) — pass the PDF link directly and it converts to markdown text. Pages under 5000 chars return full markdown; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. If a URL fails or times out, use the browser tool to access it instead.", "parameters": { "type": "object", "properties": { "urls": { "type": "array", "items": { "type": "string" }, "description": "List of URLs to extract content from (max 5 URLs per call)", "maxItems": 5 } }, "required": [ "urls" ] } } }, { "type": "function", "function": { "name": "web_search", "description": "Search the web for information. Returns up to 5 results by default with titles, URLs, and descriptions. The query is passed through to the configured backend, so operators such as site:domain, filetype:pdf, intitle:word, -term, and \"exact phrase\" may work when the backend supports them.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "The search query to look up on the web. You may include backend-supported operators such as site:example.com, filetype:pdf, intitle:word, -term, or \"exact phrase\"." }, "limit": { "type": "integer", "description": "Maximum number of results to return. Defaults to 5.", "minimum": 1, "maximum": 100, "default": 5 } }, "required": [ "query" ] } } }, { "type": "function", "function": { "name": "write_file", "description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)" }, "content": { "type": "string", "description": "Complete content to write to the file" } }, "required": [ "path", "content" ] } } }, { "type": "function", "function": { "name": "honcho_profile", "description": "Retrieve or update a peer card from Honcho — a curated list of key facts about that peer (name, role, preferences, communication style, patterns). Pass `card` to update; omit `card` to read. If the card is empty, the result includes a `hint` field explaining why (observation disabled, fresh peer, dialectic layer still warming up, etc.) — this is NOT an error. Peer cards accumulate over time from observed conversation.", "parameters": { "type": "object", "properties": { "peer": { "type": "string", "description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace." }, "card": { "type": "array", "items": { "type": "string" }, "description": "New peer card as a list of fact strings. Omit to read the current card." } }, "required": [] } } }, { "type": "function", "function": { "name": "honcho_search", "description": "Semantic search over Honcho's stored context about a peer. Returns raw excerpts ranked by relevance — no LLM synthesis. Cheaper and faster than honcho_reasoning. Good when you want to find specific past facts and reason over them yourself.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "What to search for in Honcho's memory." }, "max_tokens": { "type": "integer", "description": "Token budget for returned context (default 800, max 2000)." }, "peer": { "type": "string", "description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace." } }, "required": [ "query" ] } } }, { "type": "function", "function": { "name": "honcho_reasoning", "description": "Ask Honcho a natural language question and get a synthesized answer. Uses Honcho's LLM (dialectic reasoning) — higher cost than honcho_profile or honcho_search. Can query about any peer via alias or explicit peer ID. Pass reasoning_level to control depth: minimal (fast/cheap), low (default), medium, high, max (deep/expensive). Omit for configured default.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "A natural language question." }, "reasoning_level": { "type": "string", "description": "Override the default reasoning depth. Omit to use the configured default (typically low). Guide:\n- minimal: quick factual lookups (name, role, simple preference)\n- low: straightforward questions with clear answers\n- medium: multi-aspect questions requiring synthesis across observations\n- high: complex behavioral patterns, contradictions, deep analysis\n- max: thorough audit-level analysis, leave no stone unturned", "enum": [ "minimal", "low", "medium", "high", "max" ] }, "peer": { "type": "string", "description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace." } }, "required": [ "query" ] } } }, { "type": "function", "function": { "name": "honcho_context", "description": "Retrieve full session context from Honcho — summary, peer representation, peer card, and recent messages. No LLM synthesis. Cheaper than honcho_reasoning. Use this to see what Honcho knows about the current conversation and the specified peer.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "Optional focus query to filter context. Omit for full session context snapshot." }, "peer": { "type": "string", "description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace." } }, "required": [] } } }, { "type": "function", "function": { "name": "honcho_conclude", "description": "Write or delete a conclusion about a peer in Honcho's memory. Conclusions are persistent facts that build a peer's profile. You MUST pass exactly one of: `conclusion` (to create) or `delete_id` (to delete). Passing neither is an error. Deletion is only for PII removal — Honcho self-heals incorrect conclusions over time.", "parameters": { "type": "object", "properties": { "conclusion": { "type": "string", "description": "A factual statement to persist. Provide this when creating a conclusion. Do not send it together with delete_id." }, "delete_id": { "type": "string", "description": "Conclusion ID to delete for PII removal. Provide this when deleting a conclusion. Do not send it together with conclusion." }, "peer": { "type": "string", "description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace." } }, "required": [] } } } ], "message_count": 100, "messages": [ { "role": "user", "content": "[Recent channel messages]\n[nachlakes] Hola\n\n[New message]\n[nachlakes]" }, { "role": "assistant", "content": "¡Hola, Igna!", "reasoning": "The user just said \"Hola\" - this is a simple greeting. I should respond briefly and directly, as per their preferences. No need for anything elaborate.", "reasoning_content": "The user just said \"Hola\" - this is a simple greeting. I should respond briefly and directly, as per their preferences. No need for anything elaborate.", "finish_reason": "stop" }, { "role": "user", "content": "[Note: model was just switched from deepseek-v4-pro to gpt-5.5 via OpenAI Codex. Adjust your self-identification accordingly.]\n\n[nachlakes] Hola" }, { "role": "assistant", "content": "Hola, Chicho. Acá estoy — ahora corriendo como GPT-5.5 vía OpenAI Codex.", "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Hola, Chicho. Acá estoy — ahora corriendo como GPT-5.5 vía OpenAI Codex." } ], "id": "msg_034268a3852e0919016a07639686e4819a980db2b602b4913d", "phase": "final_answer" } ], "finish_reason": "stop" }, { "role": "user", "content": "[nachlakes] Che estoy al tanto de que vos como chatgpt 5.5 Ahora a través de codex podes usar imagen 2 vía hermes. Fijate y si no te sale imvesitfa al respecto y activarlo que quiero que trabajemos en algunos edit" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_1kSVPR14AUDWsY0UZtTlwrS9", "call_id": "call_1kSVPR14AUDWsY0UZtTlwrS9", "response_item_id": "fc_034268a3852e0919016a07bad9e7f4819ab12c50763039598d", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"hermes-agent\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Investigating image generation**\n\nI need to address the user’s request about activating the image generation feature. It seems like I should load the \"hermes-agent\" to configure and use the Hermes image feature. I'll need to dig a bit deeper into how this works and ensure that everything is set up correctly for the user. Let's explore this together! I wonder what steps I need to take to activate it effectively.", "reasoning_content": "**Investigating image generation**\n\nI need to address the user’s request about activating the image generation feature. It seems like I should load the \"hermes-agent\" to configure and use the Hermes image feature. I'll need to dig a bit deeper into how this works and ensure that everything is set up correctly for the user. Let's explore this together! I wonder what steps I need to take to activate it effectively.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB7rZlDGqAGLgFd6opPpOckto4PbI1lHh5asvnIzIPpqAEcXOhnS3YAmVz9pKEffmpEDDXrWfsQXG1jxModDHi4sIB0Ud4yRx_YhQScNbvcp-WDXLg6TFw6xf-GS2cGSA3IYD7iMRi08BoDkgCf3Z_5HinA5bLYjQLiN-ihhekxpdklDY1gtTZq4L2YPyVy-N30ycUs5xGwRjhtgYdOxrYLmta86BmSWFOWAwwqvA6GY1SvfcbTqzlyid_SOHfEFnoJpR33P9ke-dPYVGR7XKZ6iQ27SLVoxeeVZ_G6AJvYqNskUHE42iDtfeD_iGp_0jnqjRDv-XnnM20WZdarI1_kPBW16hom0tIB0en4sQ-qINQSUxOpHYqAjKFdbGMyth9aw1qXxdrft_B9jfFbDnwVGVjwG5MKH6QFK5DRZhwP0aKo-ARD0UoR08YWrQoIftRS95xhTRcujqv7-1hEBmNYH0e7GndRemrj2l9eEKsFHljXTb-4JCpFjsCYNHYufM_hbbOGb_oGG8lVNeDKYdRkS1swcCh-bchOkBCiz1pPK80NwW4PbHIznliMYdpaqCFI6QyOqs9abvJObzOVw0eKz7BFI1o_b73p8uJxJVkDSAGEUY_hO5BW3WtEd5hvVUE_-fcEngwnyIpiyJ9_nD47DEIxaHoCKZdYGdeL33sbPT6xMlM4PSw4q94DQwo62j6uuJh92_ICym_tyAf2-D2ldI8O5Fn-_vV2ho_GZH64-1_H4ye5yK3WWHaTIfRbvm9W-RvpE84Y4PpokaGFC3tJFR8PJTMrBDS33jo82VUU607cMpctmfVLUxQe-_2hT7xjb7o5e9U0xfzAdGkNKeAvp429v0FbC_1759wyFCb60nbD9rYYUm56GI28LvsNVWtgo3Dtvf9P30YZjd0jb4ditU26Gaww3xGI8mnI3NB4DHQmc3cK9EHKUMFF3MMf3rBS5iTEsZuCdNXNdvUOIVm-pK4cEJmQcyhumg_uNCnHVr02MCenoJ7HipGO6ijKp1Fz46PVpSPU1NzhLJGyHzdBWeInVmQVx5Un_XluQdHH598EAmP-PFMS29JpzE6xWxjaDJOUXKsFhF-547s0whkLxtXUjGEzExKJym5mhSvOwbcsw=", "id": "rs_034268a3852e0919016a07bad79f18819aa39d799a51adc297", "summary": [ { "type": "summary_text", "text": "**Investigating image generation**\n\nI need to address the user’s request about activating the image generation feature. It seems like I should load the \"hermes-agent\" to configure and use the Hermes image feature. I'll need to dig a bit deeper into how this works and ensure that everything is set up correctly for the user. Let's explore this together! I wonder what steps I need to take to activate it effectively." } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"name\": \"hermes-agent\", \"description\": \"Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.\", \"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"], \"content\": \"---\\nname: hermes-agent\\ndescription: Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.\\nversion: 2.0.0\\nauthor: Hermes Agent + Teknium\\nlicense: MIT\\nmetadata:\\n hermes:\\n tags: [hermes, setup, configuration, multi-agent, spawning, cli, gateway, development]\\n homepage: https://github.com/NousResearch/hermes-agent\\n related_skills: [claude-code, codex, opencode]\\n---\\n\\n# Hermes Agent\\n\\nHermes Agent is an open-source AI agent framework by Nous Research that runs in your terminal, messaging platforms, and IDEs. It belongs to the same category as Claude Code (Anthropic), Codex (OpenAI), and OpenClaw — autonomous coding and task-execution agents that use tool calling to interact with your system. Hermes works with any LLM provider (OpenRouter, Anthropic, OpenAI, DeepSeek, local models, and 15+ others) and runs on Linux, macOS, and WSL.\\n\\nWhat makes Hermes different:\\n\\n- **Self-improving through skills** — Hermes learns from experience by saving reusable procedures as skills. When it solves a complex problem, discovers a workflow, or gets corrected, it can persist that knowledge as a skill document that loads into future sessions. Skills accumulate over time, making the agent better at your specific tasks and environment.\\n- **Persistent memory across sessions** — remembers who you are, your preferences, environment details, and lessons learned. Pluggable memory backends (built-in, Honcho, Mem0, and more) let you choose how memory works.\\n- **Multi-platform gateway** — the same agent runs on Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email, and 8+ other platforms with full tool access, not just chat.\\n- **Provider-agnostic** — swap models and providers mid-workflow without changing anything else. Credential pools rotate across multiple API keys automatically.\\n- **Profiles** — run multiple independent Hermes instances with isolated configs, sessions, skills, and memory.\\n- **Extensible** — plugins, MCP servers, custom tools, webhook triggers, cron scheduling, and the full Python ecosystem.\\n\\nPeople use Hermes for software development, research, system administration, data analysis, content creation, home automation, and anything else that benefits from an AI agent with persistent context and full system access.\\n\\n**This skill helps you work with Hermes Agent effectively** — setting it up, configuring features, spawning additional agent instances, troubleshooting issues, finding the right commands and settings, and understanding how the system works when you need to extend or contribute to it.\\n\\n**Docs:** https://hermes-agent.nousresearch.com/docs/\\n\\n## Quick Start\\n\\n```bash\\n# Install\\ncurl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash\\n\\n# Interactive chat (default)\\nhermes\\n\\n# Single query\\nhermes chat -q \\\"What is the capital of France?\\\"\\n\\n# Setup wizard\\nhermes setup\\n\\n# Change model/provider\\nhermes model\\n\\n# Check health\\nhermes doctor\\n```\\n\\n---\\n\\n## CLI Reference\\n\\n### Global Flags\\n\\n```\\nhermes [flags] [command]\\n\\n --version, -V Show version\\n --resume, -r SESSION Resume session by ID or title\\n --continue, -c [NAME] Resume by name, or most recent session\\n --worktree, -w Isolated git worktree mode (parallel agents)\\n --skills, -s SKILL Preload skills (comma-separate or repeat)\\n --profile, -p NAME Use a named profile\\n --yolo Skip dangerous command approval\\n --pass-session-id Include session ID in system prompt\\n```\\n\\nNo subcommand defaults to `chat`.\\n\\n### Chat\\n\\n```\\nhermes chat [flags]\\n -q, --query TEXT Single query, non-interactive\\n -m, --model MODEL Model (e.g. anthropic/claude-sonnet-4)\\n -t, --toolsets LIST Comma-separated toolsets\\n --provider PROVIDER Force provider (openrouter, anthropic, nous, etc.)\\n -v, --verbose Verbose output\\n -Q, --quiet Suppress banner, spinner, tool previews\\n --checkpoints Enable filesystem checkpoints (/rollback)\\n --source TAG Session source tag (default: cli)\\n```\\n\\n### Configuration\\n\\n```\\nhermes setup [section] Interactive wizard (model|terminal|gateway|tools|agent)\\nhermes model Interactive model/provider picker\\nhermes config View current config\\nhermes config edit Open config.yaml in $EDITOR\\nhermes config set KEY VAL Set a config value\\nhermes config path Print config.yaml path\\nhermes config env-path Print .env path\\nhermes config check Check for missing/outdated config\\nhermes config migrate Update config with new options\\nhermes login [--provider P] OAuth login (nous, openai-codex)\\nhermes logout Clear stored auth\\nhermes doctor [--fix] Check dependencies and config\\nhermes status [--all] Show component status\\n```\\n\\n### Tools & Skills\\n\\n```\\nhermes tools Interactive tool enable/disable (curses UI)\\nhermes tools list Show all tools and status\\nhermes tools enable NAME Enable a toolset\\nhermes tools disable NAME Disable a toolset\\n\\nhermes skills list List installed skills\\nhermes skills search QUERY Search the skills hub\\nhermes skills install ID Install a skill\\nhermes skills inspect ID Preview without installing\\nhermes skills config Enable/disable skills per platform\\nhermes skills check Check for updates\\nhermes skills update Update outdated skills\\nhermes skills uninstall N Remove a hub skill\\nhermes skills publish PATH Publish to registry\\nhermes skills browse Browse all available skills\\nhermes skills tap add REPO Add a GitHub repo as skill source\\n```\\n\\n### MCP Servers\\n\\n```\\nhermes mcp serve Run Hermes as an MCP server\\nhermes mcp add NAME Add an MCP server (--url or --command)\\nhermes mcp remove NAME Remove an MCP server\\nhermes mcp list List configured servers\\nhermes mcp test NAME Test connection\\nhermes mcp configure NAME Toggle tool selection\\n```\\n\\n### Dashboard (Web UI)\\n\\nThe official Hermes dashboard provides a web UI for managing config, API keys, sessions, cron, skills, and models. It also includes an optional in-browser terminal tab (`--tui`). It binds to localhost by default for security (exposes API keys and config).\\n\\n```bash\\nhermes dashboard # Start on localhost:9119\\nhermes dashboard --status # Check if running\\nhermes dashboard --stop # Stop all dashboard processes\\nhermes dashboard --skip-build # Skip npm build (use existing dist)\\nhermes dashboard --tui # Enable in-browser terminal tab\\n```\\n\\n**Exposing externally via Tailscale Funnel:**\\n\\nThe dashboard **rejects any HTTP Host header that doesn't match the bound address**. Since Tailscale Funnel forwards the original domain name as the Host header, a direct funnel to 127.0.0.1:9119 results in 403 errors. The fix is a thin reverse proxy that strips the Host header before forwarding:\\n\\n```bash\\n# 1. Start dashboard on localhost\\ncd ~/.hermes\\n./hermes-agent/venv/bin/python -m hermes_cli.main dashboard \\\\\\n --host 127.0.0.1 --port 9119 --no-open --skip-build &\\n\\n# 2. Start the Host-header-rewriting proxy (script shipped with this skill)\\npython3 ~/.hermes/skills/autonomous-ai-agents/hermes-agent/scripts/dashboard-funnel-proxy.py &\\n\\n# 3. Expose via Tailscale Funnel (dashboard on /, gateway on /gateway/)\\ntailscale funnel --bg --set-path / http://127.0.0.1:9118/\\ntailscale funnel --bg --set-path /gateway/ http://127.0.0.1:8080/\\n```\\n\\nThe dashboard is then accessible at `https://.ts.net/`.\\n\\n**Alternative: nginx reverse proxy** (handles WebSocket upgrade transparently — recommended when you need the Chat tab):\\n```nginx\\n# /etc/nginx/sites-enabled/hermes-dashboard\\nserver {\\n listen 127.0.0.1:9117;\\n server_name _;\\n location / {\\n proxy_pass http://127.0.0.1:9119;\\n proxy_set_header Host 127.0.0.1:9119;\\n proxy_http_version 1.1;\\n proxy_set_header Upgrade $http_upgrade;\\n proxy_set_header Connection \\\"upgrade\\\";\\n proxy_read_timeout 86400s;\\n proxy_send_timeout 86400s;\\n proxy_buffering off;\\n }\\n}\\n```\\nThen funnel `/` to nginx instead of the Python proxy:\\n```bash\\ntailscale funnel --bg --set-path / http://127.0.0.1:9117/\\ntailscale funnel --bg --set-path /gateway/ http://127.0.0.1:8080/\\n```\\nRestart nginx after config changes: `sudo systemctl reload nginx`.\\n\\nIMPORTANT: Put the dashboard on the root path `/`, NOT on `/dashboard/`. The dashboard's HTML uses root-relative asset paths (`/assets/`, `/favicon.ico`, `/api/`, `/sessions`, etc.). If you put it under a path prefix like `/dashboard/`, the browser resolves those assets against `/` and they don't reach the dashboard. Moving the existing gateway proxy from `/` to `/gateway/` frees up `/` for the dashboard.\\n\\n**Pitfalls:**\\n- The dashboard **refuses** to bind to a non-localhost address without `--insecure`. This is intentional — it exposes API keys and config. Do NOT use `--insecure` on untrusted networks. Always bind to 127.0.0.1 and proxy through Tailscale.\\n- `tailscale serve` (tailnet-only) and `tailscale funnel` (public internet) are mutually exclusive. Setting up `serve` for an additional path **removes** the `funnel`. Use `funnel --bg --set-path` for all paths if you need public access.\\n- The dashboard uses a session token embedded in the HTML. No separate login step.\\n- The proxy script at `scripts/dashboard-funnel-proxy.py` is a stateless Python stdlib HTTP reverse proxy — no dependencies needed.\\n- **Chat tab WebSocket rejected behind reverse proxy (403):** when the dashboard binds to `127.0.0.1`, `_ws_client_is_allowed()` in `hermes_cli/web_server.py` rejects non-loopback WebSocket clients with a 403. Behind nginx/Tailscale Funnel, the browser's real IP appears as the client, not `127.0.0.1`. Symptom: \\\"events feed disconnected\\\" / \\\"session ended\\\" on `/api/events` and `/api/pty`. **Fix:** bind to `0.0.0.0` with `--insecure` (safe when nginx/Funnel is the only ingress). Full diagnosis in `references/dashboard-ws-reverse-proxy-403.md`.\\n- The Chat tab requires `--tui` (or `HERMES_DASHBOARD_TUI=1`). Without it, the WebSocket endpoints are disabled entirely (`_DASHBOARD_EMBEDDED_CHAT_ENABLED = False`). Always pass `--tui` when you want the embedded terminal.\\n\\n### Gateway (Messaging Platforms)\\n\\n```\\nhermes gateway run Start gateway foreground\\nhermes gateway install Install as background service\\nhermes gateway start/stop Control the service\\nhermes gateway restart Restart the service\\nhermes gateway status Check status\\nhermes gateway setup Configure platforms\\n```\\n\\nSupported platforms: Telegram, Discord, Slack, WhatsApp, Signal, Email, SMS, Matrix, Mattermost, Home Assistant, DingTalk, Feishu, WeCom, API Server, Webhooks, Open WebUI.\\n\\nPlatform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/\\n\\n### Sessions\\n\\n```\\nhermes sessions list List recent sessions\\nhermes sessions browse Interactive picker\\nhermes sessions export OUT Export to JSONL\\nhermes sessions rename ID T Rename a session\\nhermes sessions delete ID Delete a session\\nhermes sessions prune Clean up old sessions (--older-than N days)\\nhermes sessions stats Session store statistics\\n```\\n\\n### Cron Jobs\\n\\n```bash\\nhermes cron list List jobs (--all for disabled)\\nhermes cron create SCHED Create: '30m', 'every 2h', '0 9 * * *'\\nhermes cron edit ID Edit schedule, prompt, delivery\\nhermes cron pause/resume ID Control job state\\nhermes cron run ID Trigger on next tick\\nhermes cron remove ID Delete a job\\nhermes cron status Scheduler status\\n```\\n\\nFor watching long-running background processes and notifying on completion, see `references/cron-watchdog-pattern.md` for the PID-watch + marker-file pattern.\\n\\n### Webhooks\\n\\n```\\nhermes webhook subscribe N Create route at /webhooks/\\nhermes webhook list List subscriptions\\nhermes webhook remove NAME Remove a subscription\\nhermes webhook test NAME Send a test POST\\n```\\n\\n### Profiles\\n\\n```\\nhermes profile list List all profiles\\nhermes profile create NAME Create (--clone, --clone-all, --clone-from)\\nhermes profile use NAME Set sticky default\\nhermes profile delete NAME Delete a profile\\nhermes profile show NAME Show details\\nhermes profile alias NAME Manage wrapper scripts\\nhermes profile rename A B Rename a profile\\nhermes profile export NAME Export to tar.gz\\nhermes profile import FILE Import from archive\\n```\\n\\n### Credential Pools\\n\\n```\\nhermes auth add Interactive credential wizard\\nhermes auth list [PROVIDER] List pooled credentials\\nhermes auth remove P INDEX Remove by provider + index\\nhermes auth reset PROVIDER Clear exhaustion status\\n```\\n\\n### Other\\n\\n```\\nhermes insights [--days N] Usage analytics\\nhermes update Update to latest version\\nhermes pairing list/approve/revoke DM authorization\\nhermes plugins list/install/remove Plugin management\\nhermes honcho setup/status Honcho memory integration\\nhermes memory setup/status/off Memory provider config\\nhermes completion bash|zsh Shell completions\\nhermes acp ACP server (IDE integration)\\nhermes claw migrate Migrate from OpenClaw\\nhermes uninstall Uninstall Hermes\\n```\\n\\n---\\n\\n## Slash Commands (In-Session)\\n\\nType these during an interactive chat session.\\n\\n### Session Control\\n```\\n/new (/reset) Fresh session\\n/clear Clear screen + new session (CLI)\\n/retry Resend last message\\n/undo Remove last exchange\\n/title [name] Name the session\\n/compress Manually compress context\\n/stop Kill background processes\\n/rollback [N] Restore filesystem checkpoint\\n/background Run prompt in background\\n/queue Queue for next turn\\n/resume [name] Resume a named session\\n```\\n\\n### Configuration\\n```\\n/config Show config (CLI)\\n/model [name] Show or change model\\n/provider Show provider info\\n/prompt [text] View/set system prompt (CLI)\\n/personality [name] Set personality\\n/reasoning [level] Set reasoning (none|low|medium|high|xhigh|show|hide)\\n/verbose Cycle: off → new → all → verbose\\n/voice [on|off|tts] Voice mode\\n/yolo Toggle approval bypass\\n/skin [name] Change theme (CLI)\\n/statusbar Toggle status bar (CLI)\\n```\\n\\n### Tools & Skills\\n```\\n/tools Manage tools (CLI)\\n/toolsets List toolsets (CLI)\\n/skills Search/install skills (CLI)\\n/skill Load a skill into session\\n/cron Manage cron jobs (CLI)\\n/reload-mcp Reload MCP servers\\n/plugins List plugins (CLI)\\n```\\n\\n### Info\\n```\\n/help Show commands\\n/commands [page] Browse all commands (gateway)\\n/usage Token usage\\n/insights [days] Usage analytics\\n/status Session info (gateway)\\n/profile Active profile info\\n```\\n\\n### Exit\\n```\\n/quit (/exit, /q) Exit CLI\\n```\\n\\n---\\n\\n## Key Paths & Config\\n\\n```\\n~/.hermes/config.yaml Main configuration\\n~/.hermes/.env API keys and secrets\\n~/.hermes/skills/ Installed skills\\n~/.hermes/sessions/ Session transcripts\\n~/.hermes/logs/ Gateway and error logs\\n~/.hermes/auth.json OAuth tokens and credential pools\\n~/.hermes/hermes-agent/ Source code (if git-installed)\\n```\\n\\nProfiles use `~/.hermes/profiles//` with the same layout.\\n\\n### Config Sections\\n\\nEdit with `hermes config edit` or `hermes config set section.key value`.\\n\\n| Section | Key options |\\n|---------|-------------|\\n| `model` | `default`, `provider`, `base_url`, `api_key`, `context_length` |\\n| `agent` | `max_turns` (90), `tool_use_enforcement` |\\n| `terminal` | `backend` (local/docker/ssh/modal), `cwd`, `timeout` (180) |\\n| `compression` | `enabled`, `threshold` (0.50), `target_ratio` (0.20) |\\n| `display` | `skin`, `tool_progress`, `show_reasoning`, `show_cost` |\\n| `stt` | `enabled`, `provider` (local/groq/openai) |\\n| `tts` | `provider` (edge/elevenlabs/openai/kokoro/fish) |\\n| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |\\n| `security` | `tirith_enabled`, `website_blocklist` |\\n| `delegation` | `model`, `provider`, `max_iterations` (50) |\\n| `smart_model_routing` | `enabled`, `cheap_model` |\\n| `checkpoints` | `enabled`, `max_snapshots` (50) |\\n\\nFull config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\n\\n### Providers\\n\\n18 providers supported. Set via `hermes model` or `hermes setup`.\\n\\n### Reasoning effort gotcha\\n\\nHermes' persistent reasoning setting lives at `agent.reasoning_effort` in `~/.hermes/config.yaml`.\\n\\nUse one of these:\\n```bash\\nhermes config set agent.reasoning_effort xhigh\\n```\\nOr inside Hermes:\\n```text\\n/reasoning xhigh\\n```\\n\\nDo not rely on a top-level config key like `OPENAI_REASONING_EFFORT: xhigh` for Hermes CLI/gateway behavior. Hermes reads `agent.reasoning_effort`, not that top-level key.\\n\\nAlso, reasoning support is model/provider-specific:\\n- OpenAI Codex / GPT-5 Responses-style models: effort values like `low|medium|high|xhigh` can apply.\\n- OpenRouter models that expose effort controls: effort can apply.\\n- DeepSeek and some Kimi/Moonshot models: reasoning is selected by choosing a thinking/reasoner model variant, not by an effort dropdown.\\n- Some Mistral models only support a reasoning toggle, not `xhigh`.\\n- Web UI may clamp or clear unsupported effort values per model/provider.\\n\\nSo `agent.reasoning_effort: xhigh` is a good global default, but it will only be honored by models/providers that actually support effort-style reasoning.\\n\\n\\n| Provider | Auth | Key env var |\\n|----------|------|-------------|\\n| OpenRouter | API key | `OPENROUTER_API_KEY` |\\n| Anthropic | API key | `ANTHROPIC_API_KEY` |\\n| Nous Portal | OAuth | `hermes login --provider nous` |\\n| OpenAI Codex | OAuth | `hermes login --provider openai-codex` |\\n| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |\\n| DeepSeek | API key | `DEEPSEEK_API_KEY` |\\n| Hugging Face | Token | `HF_TOKEN` |\\n| Z.AI / GLM | API key | `GLM_API_KEY` |\\n| MiniMax | API key | `MINIMAX_API_KEY` |\\n| Kimi / Moonshot | API key | `KIMI_API_KEY` |\\n| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |\\n| Kilo Code | API key | `KILOCODE_API_KEY` |\\n| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |\\n\\nPlus: AI Gateway, OpenCode Zen, OpenCode Go, MiniMax CN, GitHub Copilot ACP.\\n\\nFull provider docs: https://hermes-agent.nousresearch.com/docs/integrations/providers\\n\\n### Toolsets\\n\\nEnable/disable via `hermes tools` (interactive) or `hermes tools enable/disable NAME`.\\n\\n| Toolset | What it provides |\\n|---------|-----------------|\\n| `web` | Web search and content extraction |\\n| `browser` | Browser automation (Browserbase, Camofox, or local Chromium) |\\n| `terminal` | Shell commands and process management |\\n| `file` | File read/write/search/patch |\\n| `code_execution` | Sandboxed Python execution |\\n| `vision` | Image analysis |\\n| `image_gen` | AI image generation |\\n| `tts` | Text-to-speech |\\n| `skills` | Skill browsing and management |\\n| `memory` | Persistent cross-session memory |\\n| `session_search` | Search past conversations |\\n| `delegation` | Subagent task delegation |\\n| `cronjob` | Scheduled task management |\\n| `clarify` | Ask user clarifying questions |\\n| `moa` | Mixture of Agents (off by default) |\\n| `homeassistant` | Smart home control (off by default) |\\n\\nTool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.\\n\\n---\\n\\n## Voice & Transcription\\n\\n### STT (Voice → Text)\\n\\nVoice messages from messaging platforms are auto-transcribed.\\n\\nProvider priority (auto-detected):\\n1. **Local faster-whisper** — free, no API key: `pip install faster-whisper`\\n2. **Groq Whisper** — free tier: set `GROQ_API_KEY`\\n3. **OpenAI Whisper** — paid: set `VOICE_TOOLS_OPENAI_KEY`\\n\\nConfig:\\n```yaml\\nstt:\\n enabled: true\\n provider: local # local, groq, openai\\n local:\\n model: base # tiny, base, small, medium, large-v3\\n```\\n\\n### TTS (Text → Voice)\\n\\n| Provider | Env var | Free? |\\n|----------|---------|-------|\\n| Edge TTS | None | Yes (default) |\\n| ElevenLabs | `ELEVENLABS_API_KEY` | Free tier |\\n| OpenAI | `VOICE_TOOLS_OPENAI_KEY` | Paid |\\n| Kokoro (local) | None | Free |\\n| Fish Audio | `FISH_AUDIO_API_KEY` | Free tier |\\n\\nVoice commands: `/voice on` (voice-to-voice), `/voice tts` (always voice), `/voice off`.\\n\\n---\\n\\n## Spawning Additional Hermes Instances\\n\\nRun additional Hermes processes as fully independent subprocesses — separate sessions, tools, and environments.\\n\\n### When to Use This vs delegate_task\\n\\n| | `delegate_task` | Spawning `hermes` process |\\n|-|-----------------|--------------------------|\\n| Isolation | Separate conversation, shared process | Fully independent process |\\n| Duration | Minutes (bounded by parent loop) | Hours/days |\\n| Tool access | Subset of parent's tools | Full tool access |\\n| Interactive | No | Yes (PTY mode) |\\n| Use case | Quick parallel subtasks | Long autonomous missions |\\n\\n### One-Shot Mode\\n\\n```\\nterminal(command=\\\"hermes chat -q 'Research GRPO papers and write summary to ~/research/grpo.md'\\\", timeout=300)\\n\\n# Background for long tasks:\\nterminal(command=\\\"hermes chat -q 'Set up CI/CD for ~/myapp'\\\", background=true)\\n```\\n\\n### Interactive PTY Mode (via tmux)\\n\\nHermes uses prompt_toolkit, which requires a real terminal. Use tmux for interactive spawning:\\n\\n```\\n# Start\\nterminal(command=\\\"tmux new-session -d -s agent1 -x 120 -y 40 'hermes'\\\", timeout=10)\\n\\n# Wait for startup, then send a message\\nterminal(command=\\\"sleep 8 && tmux send-keys -t agent1 'Build a FastAPI auth service' Enter\\\", timeout=15)\\n\\n# Read output\\nterminal(command=\\\"sleep 20 && tmux capture-pane -t agent1 -p\\\", timeout=5)\\n\\n# Send follow-up\\nterminal(command=\\\"tmux send-keys -t agent1 'Add rate limiting middleware' Enter\\\", timeout=5)\\n\\n# Exit\\nterminal(command=\\\"tmux send-keys -t agent1 '/exit' Enter && sleep 2 && tmux kill-session -t agent1\\\", timeout=10)\\n```\\n\\n### Multi-Agent Coordination\\n\\n```\\n# Agent A: backend\\nterminal(command=\\\"tmux new-session -d -s backend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t backend 'Build REST API for user management' Enter\\\", timeout=15)\\n\\n# Agent B: frontend\\nterminal(command=\\\"tmux new-session -d -s frontend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t frontend 'Build React dashboard for user management' Enter\\\", timeout=15)\\n\\n# Check progress, relay context between them\\nterminal(command=\\\"tmux capture-pane -t backend -p | tail -30\\\", timeout=5)\\nterminal(command=\\\"tmux send-keys -t frontend 'Here is the API schema from the backend agent: ...' Enter\\\", timeout=5)\\n```\\n\\n### Session Resume\\n\\n```\\n# Resume most recent session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --continue'\\\", timeout=10)\\n\\n# Resume specific session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --resume 20260225_143052_a1b2c3'\\\", timeout=10)\\n```\\n\\n### Tips\\n\\n- **Prefer `delegate_task` for quick subtasks** — less overhead than spawning a full process\\n- **Use `-w` (worktree mode)** when spawning agents that edit code — prevents git conflicts\\n- **Set timeouts** for one-shot mode — complex tasks can take 5-10 minutes\\n- **Use `hermes chat -q` for fire-and-forget** — no PTY needed\\n- **Use tmux for interactive sessions** — raw PTY mode has `\\\\r` vs `\\\\n` issues with prompt_toolkit\\n- **For scheduled tasks**, use the `cronjob` tool instead of spawning — handles delivery and retry\\n\\n---\\n\\n## Troubleshooting\\n\\n### Voice not working\\n1. Check `stt.enabled: true` in config.yaml\\n2. Verify provider: `pip install faster-whisper` or set API key\\n3. Restart gateway: `/restart`\\n\\n### Tool not available\\n1. `hermes tools` — check if toolset is enabled for your platform\\n2. Some tools need env vars (check `.env`)\\n3. `/reset` after enabling tools\\n\\n### Model/provider issues\\n1. `hermes doctor` — check config and dependencies\\n2. `hermes login` — re-authenticate OAuth providers\\n3. Check `.env` has the right API key\\n\\n### Changes not taking effect\\n- **Tools/skills:** `/reset` starts a new session with updated toolset\\n- **Config changes:** `/restart` reloads gateway config\\n- **Code changes:** Restart the CLI or gateway process\\n\\n### Skills not showing\\n1. `hermes skills list` — verify installed\\n2. `hermes skills config` — check platform enablement\\n3. Load explicitly: `/skill name` or `hermes -s name`\\n\\n### `hermes update` hit a merge conflict\\n\\nSymptoms: gateway fails with `SyntaxError: expected 'except' or 'finally' block` in `api_server.py`, or `git status` shows `both modified` files.\\n\\nRoot cause: local customizations (e.g., custom API endpoints, method renames) were stashed before the update, then re-applied on top of refactored upstream code, leaving conflict markers (`<<<<<<< Updated upstream`) in source files.\\n\\nFix:\\n```bash\\ncd ~/.hermes/hermes-agent\\n# Check for conflict markers:\\ngrep -rn \\\"<<<<<<\\\\|======\\\\|>>>>>>\\\" gateway/\\n# Discard stale local changes:\\ngit checkout -- gateway/platforms/api_server.py gateway/platforms/discord.py gateway/run.py\\n# Also clean .orig files and clear pycache:\\nfind gateway/ -name '*.orig' -delete\\nfind . -type d -name '__pycache__' -exec rm -rf {} + 2>/dev/null\\n# Restart:\\nhermes gateway run --replace\\n```\\n\\nTo preserve local customizations across updates:\\n- Don't let `hermes update` auto-restore the stash — review the diff first with `git stash show -p stash@{0}`\\n- If the upstream already includes your changes, drop the stash entirely\\n- For persistent local patches, consider a fork or document them as patches to re-apply after update\\n\\n### Gateway issues\\nCheck logs first:\\n```bash\\ngrep -i \\\"failed to send\\\\\\\\|error\\\" ~/.hermes/logs/gateway.log | tail -20\\n```\\n\\n---\\n\\n## Where to Find Things\\n\\n| Looking for... | Location |\\n|----------------|----------|\\n| Config options | `hermes config edit` or [Configuration docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration) |\\n| Available tools | `hermes tools list` or [Tools reference](https://hermes-agent.nousresearch.com/docs/reference/tools-reference) |\\n| Slash commands | `/help` in session or [Slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands) |\\n| Skills catalog | `hermes skills browse` or [Skills catalog](https://hermes-agent.nousresearch.com/docs/reference/skills-catalog) |\\n| Provider setup | `hermes model` or [Providers guide](https://hermes-agent.nousresearch.com/docs/integrations/providers) |\\n| Platform setup | `hermes gateway setup` or [Messaging docs](https://hermes-agent.nousresearch.com/docs/user-guide/messaging/) |\\n| MCP servers | `hermes mcp list` or [MCP guide](https://hermes-agent.nousresearch.com/docs/user-guide/features/mcp) |\\n| Profiles | `hermes profile list` or [Profiles docs](https://hermes-agent.nousresearch.com/docs/user-guide/profiles) |\\n| Cron jobs | `hermes cron list` or [Cron docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/cron) |\\n| Memory | `hermes memory status` or [Memory docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/memory) |\\n| Env variables | `hermes config env-path` or [Env vars reference](https://hermes-agent.nousresearch.com/docs/reference/environment-variables) |\\n| CLI commands | `hermes --help` or [CLI reference](https://hermes-agent.nousresearch.com/docs/reference/cli-commands) |\\n| Gateway logs | `~/.hermes/logs/gateway.log` |\\n| Session files | `~/.hermes/sessions/` or `hermes sessions browse` |\\n| Source code | `~/.hermes/hermes-agent/` |\\n\\n---\\n\\n## Contributor Quick Reference\\n\\nFor occasional contributors and PR authors. Full developer docs: https://hermes-agent.nousresearch.com/docs/developer-guide/\\n\\n### Project Layout\\n\\n```\\nhermes-agent/\\n├── run_agent.py # AIAgent — core conversation loop\\n├── model_tools.py # Tool discovery and dispatch\\n├── toolsets.py # Toolset definitions\\n├── cli.py # Interactive CLI (HermesCLI)\\n├── hermes_state.py # SQLite session store\\n├── agent/ # Prompt builder, compression, display, adapters\\n├── hermes_cli/ # CLI subcommands, config, setup, commands\\n│ ├── commands.py # Slash command registry (CommandDef)\\n│ ├── config.py # DEFAULT_CONFIG, env var definitions\\n│ └── main.py # CLI entry point and argparse\\n├── tools/ # One file per tool\\n│ └── registry.py # Central tool registry\\n├── gateway/ # Messaging gateway\\n│ └── platforms/ # Platform adapters (telegram, discord, etc.)\\n├── cron/ # Job scheduler\\n├── tests/ # ~3000 pytest tests\\n└── website/ # Docusaurus docs site\\n```\\n\\nConfig: `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys).\\n\\n### Adding a Tool (3 files)\\n\\n**1. Create `tools/your_tool.py`:**\\n```python\\nimport json, os\\nfrom tools.registry import registry\\n\\ndef check_requirements() -> bool:\\n return bool(os.getenv(\\\"EXAMPLE_API_KEY\\\"))\\n\\ndef example_tool(param: str, task_id: str = None) -> str:\\n return json.dumps({\\\"success\\\": True, \\\"data\\\": \\\"...\\\"})\\n\\nregistry.register(\\n name=\\\"example_tool\\\",\\n toolset=\\\"example\\\",\\n schema={\\\"name\\\": \\\"example_tool\\\", \\\"description\\\": \\\"...\\\", \\\"parameters\\\": {...}},\\n handler=lambda args, **kw: example_tool(\\n param=args.get(\\\"param\\\", \\\"\\\"), task_id=kw.get(\\\"task_id\\\")),\\n check_fn=check_requirements,\\n requires_env=[\\\"EXAMPLE_API_KEY\\\"],\\n)\\n```\\n\\n**2. Add import** in `model_tools.py` → `_discover_tools()` list.\\n\\n**3. Add to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.\\n\\nAll handlers must return JSON strings. Use `get_hermes_home()` for paths, never hardcode `~/.hermes`.\\n\\n### Adding a Slash Command\\n\\n1. Add `CommandDef` to `COMMAND_REGISTRY` in `hermes_cli/commands.py`\\n2. Add handler in `cli.py` → `process_command()`\\n3. (Optional) Add gateway handler in `gateway/run.py`\\n\\nAll consumers (help text, autocomplete, Telegram menu, Slack mapping) derive from the central registry automatically.\\n\\n### Agent Loop (High Level)\\n\\n```\\nrun_conversation():\\n 1. Build system prompt\\n 2. Loop while iterations < max:\\n a. Call LLM (OpenAI-format messages + tool schemas)\\n b. If tool_calls → dispatch each via handle_function_call() → append results → continue\\n c. If text response → return\\n 3. Context compression triggers automatically near token limit\\n```\\n\\n### Testing\\n\\n```bash\\nsource venv/bin/activate # or .venv/bin/activate\\npython -m pytest tests/ -o 'addopts=' -q # Full suite\\npython -m pytest tests/tools/ -q # Specific area\\n```\\n\\n- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`\\n- Run full suite before pushing any change\\n- Use `-o 'addopts='` to clear any baked-in pytest flags\\n\\n### Commit Conventions\\n\\n```\\ntype: concise subject line\\n\\nOptional body.\\n```\\n\\nTypes: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`\\n\\n### Key Rules\\n\\n- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation\\n- **Message role alternation** — never two assistant or two user messages in a row\\n- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)\\n- Config values go in `config.yaml`, secrets go in `.env`\\n- New tools need a `check_fn` so they only appear when requirements are met\\n\", \"path\": \"autonomous-ai-agents/hermes-agent/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/autonomous-ai-agents/hermes-agent\", \"linked_files\": {\"references\": [\"references/cron-watchdog-pattern.md\", \"references/dashboard-ws-reverse-proxy-403.md\"], \"scripts\": [\"scripts/dashboard-funnel-proxy.py\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"homepage\": \"https://github.com/NousResearch/hermes-agent\", \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"]}}}", "tool_call_id": "call_1kSVPR14AUDWsY0UZtTlwrS9" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GaiJ8QjYp8H0X0w4RftGYhp6", "call_id": "call_GaiJ8QjYp8H0X0w4RftGYhp6", "response_item_id": "fc_034268a3852e0919016a07bae03280819abc5aaa1e141cfd5a", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"hermes tools list | grep -i -E 'image|vision|gen' || true\",\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\",\"timeout\":60}" } }, { "id": "call_oaEVUVozZJtBGKgw9SHYyZhU", "call_id": "call_oaEVUVozZJtBGKgw9SHYyZhU", "response_item_id": "fc_034268a3852e0919016a07bae03290819abb317fd5329c63c4", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"image|imagen|fal|openai|provider\",\"target\":\"content\",\"path\":\"/home/ubuntu/.hermes/config.yaml\",\"limit\":80,\"context\":2}" } }, { "id": "call_c3oTTjoRacGCWLt9VDTRnj9u", "call_id": "call_c3oTTjoRacGCWLt9VDTRnj9u", "response_item_id": "fc_034268a3852e0919016a07bae03298819aba40a5a93c98e33f", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"image|imagen|image_gen|generate\",\"target\":\"content\",\"path\":\"/home/ubuntu/.hermes/hermes-agent\",\"file_glob\":\"*.py\",\"limit\":100,\"output_mode\":\"content\",\"context\":1}" } } ], "finish_reason": "tool_calls", "reasoning": "**Investigating image tools**\n\nI need to check if the image_generate tool is already available since the user mentioned imagen2 via Hermes, which might involve the tool's backend. It seems I have access to the image_generate tool. Maybe I should test it? I’ll also need to activate the image_gen toolset for Discord if it’s not turned on yet. I’ll explore the configuration and see if I can find details about Imagen 2 or OpenRouter using the terminal.", "reasoning_content": "**Investigating image tools**\n\nI need to check if the image_generate tool is already available since the user mentioned imagen2 via Hermes, which might involve the tool's backend. It seems I have access to the image_generate tool. Maybe I should test it? I’ll also need to activate the image_gen toolset for Discord if it’s not turned on yet. I’ll explore the configuration and see if I can find details about Imagen 2 or OpenRouter using the terminal.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB7rg8-qPIZvi9RCPrA3sEBEnCANKJq-4FLcmHZYPXKb95vymX3FoAv4EE5M8t19Yok71KkyDJBcaSIN0pEEa9bygKtZnO7C_ZmghG1UxT7GLcCbsd-dtMyybhX6l77PSS1TAFYOjP_oBrPv6Zz67C0PQcsPlWV_mha2z0w8RXdb4DCRxWtqr7SL6dYekuM1zI81AlWXmfTIN7Baw4kkknDJvoSBtCnzlvKVOSHhkMuuNIlHZ1QQPmMC3gtIb6CNDYiEZw6h8lC1HAF4UW9pqTs7uDiAwiY8j94KhCqELJ57qFj2Y9TbM7TY55b2BtqacBXvdJAzGghISD1FRwXBpIUOlF6HgwEAjafMqhTKlRd8VOBtLEON7YdZ1ytOj1dmysS-hfA3_PyheyoX8t3NjHlLu2VjTo-oKCtwD1xA5NNCZ5XA_98l--6rvok1kPWwX3o2QGx5Z0IgfbL5mhmbR4gGb2WBYxOC-tuGJ8v1-r6NKjOZuvNCWNX6-G3YKlK5jsivWYl-M6-wp9vaa2UiXvjaNhww5vWID5-sBjHvRrv_ekQ_uMndlXyfggMsqdgk_WvKTC3TD7hILDOHtxvv_qnU5WTWMoz8fFKleR2b8-qvhkGhoAKftaXSSmfF3WMEykA8Zh50zg-N7BwnGvbKQUWpa086kZYkjZI3bnrSdHC47Hmo_karNPt_fKEL6tC2fta7kNNU2Ml-f85qAhEm7XmvO9ptWeDkqd_MYbH-Tp4As0UdS7bMwpR5AhyTM_BLN57h5DYamor8GwaGYYag_CApi6ce0qufbjwS4eeosBr5pz9dc3rJrbS2hEvIADR3KKsNn0pLgEMJqzN_VyPsQj730iR51Zkg1Nsg4YtJFIeT6jQrOEz_owwX9LXr8uJ3JdZJ1SkxfpARJKoGlGaAPCXjIXKA6ve3T06SbEor6omEWj4X4MacKqfelfJOY3_Fcdt-m54aEImNM0-ggmV__bkKKYdu6O4aAsYqvSqjUKn4xnatKwgVN0BqmFuC9j0Wx2_6nh9SzOnv91Qawks24b6YyCM_odG-BdZdPz-lhDDpimW2v3zELgg2ZOSyiDU6XvwwofLzyFDidPZhdiuUdon2Jq87JYh8l0gjsts5qAnmm7LnIChl0dEwhZlidCpDoK69HJHqL2Mk4gGchGO-HucP_7fNShfjkoCM9fsdzZnl-CLvAGMy0jO2g_G-fc-zNsax0Es1w4SnXowsiOg1uVE3CwHa731JrRS8aT27cdxCo2afE8Ze1vmrYfCUksYxBqHV5O6dbbeSNNaDtuKoqfSgpRrPGaaeobO7LcJGzb2vnCuO0vjRbyF7zNCtdKjS0vsKQgXmFNzviIT7BFPTKnLsWg1Qbr38i5sBLQOqw8Ttb1HtqkB5pOyZLdOlh4OqtkjfbSZ72Fc4sCjIMyhpwYeVest836f9yVjeC_CcmSDua0OKbzY6bN0HiGi3c7IHihvL5", "id": "rs_034268a3852e0919016a07badb9008819a9cc9852727d15de6", "summary": [ { "type": "summary_text", "text": "**Investigating image tools**\n\nI need to check if the image_generate tool is already available since the user mentioned imagen2 via Hermes, which might involve the tool's backend. It seems I have access to the image_generate tool. Maybe I should test it? I’ll also need to activate the image_gen toolset for Discord if it’s not turned on yet. I’ll explore the configuration and see if I can find details about Imagen 2 or OpenRouter using the terminal." } ] } ] }, { "role": "tool", "content": "{\"output\": \"✓ enabled vision 👁️ Vision / Image Analysis\\n ✓ enabled image_gen 🎨 Image Generation\\n ✗ disabled video_gen 🎬 Video Generation\\n ✓ enabled moa 🧠 Mixture of Agents\", \"exit_code\": 0, \"error\": null}\n\n[Subdirectory context discovered: hermes-agent/AGENTS.md]\n# Hermes Agent - Development Guide\n\nInstructions for AI coding assistants and developers working on the hermes-agent codebase.\n\n## Development Environment\n\n```bash\n# Prefer .venv; fall back to venv if that's what your checkout has.\nsource .venv/bin/activate # or: source venv/bin/activate\n```\n\n`scripts/run_tests.sh` probes `.venv` first, then `venv`, then\n`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the\nmain checkout).\n\n## Project Structure\n\nFile counts shift constantly — don't treat the tree below as exhaustive.\nThe canonical source is the filesystem. The notes call out the load-bearing\nentry points you'll actually edit.\n\n```\nhermes-agent/\n├── run_agent.py # AIAgent class — core conversation loop (~12k LOC)\n├── model_tools.py # Tool orchestration, discover_builtin_tools(), handle_function_call()\n├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list\n├── cli.py # HermesCLI class — interactive CLI orchestrator (~11k LOC)\n├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)\n├── hermes_constants.py # get_hermes_home(), display_hermes_home() — profile-aware paths\n├── hermes_logging.py # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)\n├── batch_runner.py # Parallel batch processing\n├── agent/ # Agent internals (provider adapters, memory, caching, compression, etc.)\n├── hermes_cli/ # CLI subcommands, setup wizard, plugins loader, skin engine\n├── tools/ # Tool implementations — auto-discovered via tools/registry.py\n│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)\n├── gateway/ # Messaging gateway — run.py + session.py + platforms/\n│ ├── platforms/ # Adapter per platform (telegram, discord, slack, whatsapp,\n│ │ # homeassistant, signal, matrix, mattermost, email, sms,\n│ │ # dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,\n│ │ # yuanbao, webhook, api_server, ...). See ADDING_A_PLATFORM.md.\n│ └── builtin_hooks/ # Extension point for always-registered gateway hooks (none shipped)\n├── plugins/ # Plugin system (see \"Plugins\" section below)\n│ ├── memory/ # Memory-provider plugins (honcho, mem0, supermemory, ...)\n│ ├── context_engine/ # Context-engine plugins\n│ ├── model-providers/ # Inference backend plugins (openrouter, anthropic, gmi, ...)\n│ ├── kanban/ # Multi-agent board dispatcher + worker plugin\n│ ├── hermes-achievements/ # Gamified achievement tracking\n│ ├── observability/ # Metrics / traces / logs plugin\n│ ├── image_gen/ # Image-generation providers\n│ └── / # disk-cleanup, example-dashboard, google_meet, platforms,\n│ # spotify, strike-freedom-cockpit, ...\n├── optional-skills/ # Heavier/niche skills shipped but NOT active by default\n├── skills/ # Built-in skills bundled with the repo\n├── ui-tui/ # Ink (React) terminal UI — `hermes --tui`\n│ └── src/ # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib\n├── tui_gateway/ # Python JSON-RPC backend for the TUI\n├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)\n├── cron/ # Scheduler — jobs.py, scheduler.py\n├── environments/ # RL training environments (Atropos)\n├── scripts/ # run_tests.sh, release.py, auxiliary scripts\n├── website/ # Docusaurus docs site\n└── tests/ # Pytest suite (~17k tests across ~900 files as of May 2026)\n```\n\n**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).\n**Logs:** `~/.hermes/logs/` — `agent.log` (INFO+), `errors.log` (WARNING+),\n`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.\nBrowse with `hermes logs [--follow] [--level ...] [--session ...]`.\n\n## File Dependency Chain\n\n```\ntools/registry.py (no deps — imported by all tool files)\n ↑\ntools/*.py (each calls registry.register() at import time)\n ↑\nmodel_tools.py (imports tools/registry + triggers tool discovery)\n ↑\nrun_agent.py, cli.py, batch_runner.py, environments/\n```\n\n---\n\n## AIAgent Class (run_agent.py)\n\nThe real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,\nsession context, budget, credential pool, etc.). The signature below is the\nminimum subset you'll usually touch — read `run_agent.py` for the full list.\n\n```python\nclass AIAgent:\n def __init__(self,\n base_url: str = None,\n api_key: str = None,\n provider: str = None,\n api_mode: str = None, # \"chat_completions\" | \"codex_responses\" | ...\n model: str = \"\", # empty → resolved from config/provider later\n max_iterations: int = 90, # tool-calling iterations (shared with subagents)\n enabled_toolsets: list = None,\n disabled_toolsets: list = None,\n quiet_mode: bool = False,\n save_trajectories: bool = False,\n platform: str = None, # \"cli\", \"telegram\", etc.\n session_id: str = None,\n skip_context_files: bool = False,\n skip_memory: bool = False,\n credential_pool=None,\n # ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,\n # checkpoints config, prefill_messages, service_tier, reasoning_config, etc.\n ): ...\n\n def chat(self, message: str) -> str:\n \"\"\"Simple interface — returns final response string.\"\"\"\n\n def run_conversation(self, user_message: str, system_message: str = None,\n conversation_history: list = None, task_id: str = None) -> dict:\n \"\"\"Full interface — returns dict with final_response + messages.\"\"\"\n```\n\n### Agent Loop\n\nThe core loop is inside `run_conversation()` — entirely synchronous, with\ninterrupt checks, budget tracking, and a one-turn grace call:\n\n```python\nwhile (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \\\n or self._budget_grace_call:\n if self._interrupt_requested: break\n response = client.chat.completions.create(model=model, messages=messages, tools=tool_schemas)\n if response.tool_calls:\n for tool_call in response.tool_calls:\n result = handle_function_call(tool_call.name, tool_call.args, task_id)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content\n```\n\nMessages follow OpenAI format: `{\"role\": \"system/user/assistant/tool\", ...}`.\nReasoning content is stored in `assistant_msg[\"reasoning\"]`.\n\n---\n\n## CLI Architecture (cli.py)\n\n- **Rich** for banner/panels, **prompt_toolkit** for input with autocomplete\n- **KawaiiSpinner** (`agent/display.py`) — animated faces during API calls, `┊` activity feed for tool results\n- `load_cli_config()` in cli.py merges hardcoded defaults + user config YAML\n- **Skin engine** (`hermes_cli/skin_engine.py`) — data-driven CLI theming; initialized from `display.skin` config key at startup; skins customize banner colors, spinner faces/verbs/wings, tool prefix, response box, branding text\n- `process_command()` is a method on `HermesCLI` — dispatches on canonical command name resolved via `resolve_command()` from the central registry\n- Skill slash commands: `agent/skill_commands.py` scans `~/.hermes/skills/`, injects as **user message** (not system prompt) to preserve prompt caching\n\n### Slash Command Registry (`hermes_cli/commands.py`)\n\nAll slash commands are defined in a central `COMMAND_REGISTRY` list of `CommandDef` objects. Every downstream consumer derives from this registry automatically:\n\n- **CLI** — `process_command()` resolves aliases via `resolve_command()`, dispatches on canonical name\n- **Gateway** — `GATEWAY_KNOWN_COMMANDS` frozenset for hook emission, `resolve_command()` f\n\n[...truncated AGENTS.md: 50,073 chars total]", "tool_call_id": "call_GaiJ8QjYp8H0X0w4RftGYhp6" }, { "role": "tool", "content": "{\"total_count\": 243, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 1, \"content\": \"model:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 2, \"content\": \" default: deepseek-v4-pro\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 3, \"content\": \" provider: deepseek\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 4, \"content\": \" base_url: https://api.deepseek.com\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 5, \"content\": \"providers:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 6, \"content\": \" blockrun:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 7, \"content\": \" api: http://127.0.0.1:8402/v1\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 21, \"content\": \" transport: chat_completions\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 22, \"content\": \" google-ai:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 23, \"content\": \" api: https://generativelanguage.googleapis.com/v1beta/openai/\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 24, \"content\": \" name: google-ai\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 25, \"content\": \" api_key: AIzaSy...Dy7M\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 26, \"content\": \" transport: chat_completions\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 27, \"content\": \"fallback_providers:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 28, \"content\": \"- model: deepseek-v4-pro\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 29, \"content\": \" provider: deepseek\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 30, \"content\": \"- model: MiniMax-M2.7\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 31, \"content\": \" provider: minimax\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 32, \"content\": \"credential_pool_strategies:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 33, \"content\": \" kimi-coding: fill_first\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 45, \"content\": \" gateway_notify_interval: 600\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 46, \"content\": \" gateway_auto_continue_freshness: 3600\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 47, \"content\": \" image_input_mode: auto\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 48, \"content\": \" disabled_toolsets: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 49, \"content\": \" personalities:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 90, \"content\": \" system_prompt: You are a technical expert. Provide detailed, accurate technical\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 91, \"content\": \" information.\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 92, \"content\": \" verbose: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 93, \"content\": \"terminal:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 94, \"content\": \" backend: local\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 99, \"content\": \" shell_init_files: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 100, \"content\": \" auto_source_bashrc: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 101, \"content\": \" docker_image: nikolaik/python-nodejs:python3.11-nodejs20\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 102, \"content\": \" docker_forward_env: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 103, \"content\": \" docker_env: {}\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 104, \"content\": \" singularity_image: docker://nikolaik/python-nodejs:python3.11-nodejs20\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 105, \"content\": \" modal_image: nikolaik/python-nodejs:python3.11-nodejs20\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 106, \"content\": \" daytona_image: nikolaik/python-nodejs:python3.11-nodejs20\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 107, \"content\": \" vercel_runtime: node24\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 108, \"content\": \" container_cpu: 1\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 111, \"content\": \" container_persistent: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 112, \"content\": \" docker_volumes: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 113, \"content\": \" docker_mount_cwd_to_workspace: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 114, \"content\": \" docker_extra_args: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 115, \"content\": \" docker_run_as_host_user: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 116, \"content\": \" persistent_shell: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 117, \"content\": \" lifetime_seconds: 300\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 123, \"content\": \" inactivity_timeout: 120\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 124, \"content\": \" command_timeout: 30\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 125, \"content\": \" record_sessions: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 126, \"content\": \" allow_private_urls: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 127, \"content\": \" engine: auto\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 128, \"content\": \" auto_local_for_private_urls: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 131, \"content\": \" dialog_timeout_s: 300\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 132, \"content\": \" camofox:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 133, \"content\": \" managed_persistence: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 134, \"content\": \" user_id: ''\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 135, \"content\": \" session_key: ''\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 136, \"content\": \" adopt_existing_tab: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 137, \"content\": \" headless: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 138, \"content\": \"checkpoints:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 141, \"content\": \" max_total_size_mb: 500\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 142, \"content\": \" max_file_size_mb: 10\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 143, \"content\": \" auto_prune: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 144, \"content\": \" retention_days: 7\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 145, \"content\": \" delete_orphans: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 152, \"content\": \"tool_loop_guardrails:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 153, \"content\": \" warnings_enabled: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 154, \"content\": \" hard_stop_enabled: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 155, \"content\": \" warn_after:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 156, \"content\": \" exact_failure: 2\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 178, \"content\": \" discovery:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 179, \"content\": \" enabled: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 180, \"content\": \" provider_filter: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 181, \"content\": \" refresh_interval: 3600\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 182, \"content\": \" guardrail:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 187, \"content\": \"auxiliary:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 188, \"content\": \" vision:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 189, \"content\": \" provider: openrouter\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 190, \"content\": \" model: google/gemini-2.0-flash-001\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=80 to see more, or narrow with a more specific pattern or file_glob.]", "tool_call_id": "call_oaEVUVozZJtBGKgw9SHYyZhU" }, { "role": "tool", "content": "{\"total_count\": 236, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_install_sh_setup_wizard_tty_probe.py\", \"line\": 6, \"content\": \"terminal available\\\" skip and then crashed on the ``< /dev/tty`` redirect a\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_install_sh_setup_wizard_tty_probe.py\", \"line\": 7, \"content\": \"few lines later, aborting the entire image build. The fix replaces every\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_install_sh_setup_wizard_tty_probe.py\", \"line\": 8, \"content\": \"existence-based check that guards a subsequent ``< /dev/tty`` redirect with\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 19, \"content\": \" # Use a specific toolset distribution\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 20, \"content\": \" python batch_runner.py --dataset_file=data.jsonl --batch_size=10 --run_name=my_run --distribution=image_gen\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 21, \"content\": \"\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 254, \"content\": \" prompt_index (int): Index of prompt in dataset\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 255, \"content\": \" prompt_data (Dict): Prompt data containing 'prompt' field and optional 'image' field\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 256, \"content\": \" batch_num (int): Batch number\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 264, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 265, \"content\": \" # Per-prompt container image override: if the dataset row has an 'image' field,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 266, \"content\": \" # register it for this task's sandbox. Works with Docker, Modal, Singularity, and Daytona.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 267, \"content\": \" container_image = prompt_data.get(\\\"image\\\") or prompt_data.get(\\\"docker_image\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 268, \"content\": \" if container_image:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 269, \"content\": \" # Verify the image is accessible before spending tokens on the agent loop.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 270, \"content\": \" # For Docker: check local cache, then try pulling.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 276, \"content\": \" probe = _sp.run(\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 277, \"content\": \" [\\\"docker\\\", \\\"image\\\", \\\"inspect\\\", container_image],\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 278, \"content\": \" capture_output=True, timeout=10,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 281, \"content\": \" if config.get(\\\"verbose\\\"):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 282, \"content\": \" print(f\\\" Prompt {prompt_index}: Pulling docker image {container_image}...\\\", flush=True)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 283, \"content\": \" pull = _sp.run(\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 284, \"content\": \" [\\\"docker\\\", \\\"pull\\\", container_image],\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 285, \"content\": \" capture_output=True, text=True, timeout=600,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 290, \"content\": \" \\\"prompt_index\\\": prompt_index,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 291, \"content\": \" \\\"error\\\": f\\\"Docker image not available: {container_image}\\\\n{pull.stderr[:500]}\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 292, \"content\": \" \\\"trajectory\\\": None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 300, \"content\": \" if config.get(\\\"verbose\\\"):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 301, \"content\": \" print(f\\\" Prompt {prompt_index}: Docker image check failed: {img_err}\\\", flush=True)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 302, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 304, \"content\": \" overrides = {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 305, \"content\": \" \\\"docker_image\\\": container_image,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 306, \"content\": \" \\\"modal_image\\\": container_image,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 307, \"content\": \" \\\"singularity_image\\\": f\\\"docker://{container_image}\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 308, \"content\": \" \\\"daytona_image\\\": container_image,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 309, \"content\": \" }\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 313, \"content\": \" if config.get(\\\"verbose\\\"):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 314, \"content\": \" print(f\\\" Prompt {prompt_index}: Using container image {container_image}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 315, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1008, \"content\": \" # This includes both old batches (from previous runs) and new batches (from resume)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1009, \"content\": \" # Also filter out corrupted entries (where model generated invalid tool names)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1010, \"content\": \" combined_file = self.output_dir / \\\"trajectories.jsonl\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1188, \"content\": \" # Use specific distribution\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1189, \"content\": \" python batch_runner.py --dataset_file=data.jsonl --batch_size=10 --run_name=image_test --distribution=image_gen\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1190, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 151, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 152, \"content\": \" Finds: multi-part image/file content blocks, MEDIA: tags in text,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 153, \"content\": \" image URLs, and file references.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 154, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 157, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 158, \"content\": \" # Multi-part content blocks (image_url, file, etc.)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 159, \"content\": \" if isinstance(content, list):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 163, \"content\": \" ptype = part.get(\\\"type\\\", \\\"\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 164, \"content\": \" if ptype == \\\"image_url\\\":\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 165, \"content\": \" url = part.get(\\\"image_url\\\", {}).get(\\\"url\\\", \\\"\\\") if isinstance(part.get(\\\"image_url\\\"), dict) else \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 166, \"content\": \" if url:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 167, \"content\": \" attachments.append({\\\"type\\\": \\\"image\\\", \\\"url\\\": url})\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 168, \"content\": \" elif ptype == \\\"image\\\":\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 169, \"content\": \" url = part.get(\\\"url\\\", part.get(\\\"source\\\", {}).get(\\\"url\\\", \\\"\\\"))\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 170, \"content\": \" if url:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 171, \"content\": \" attachments.append({\\\"type\\\": \\\"image\\\", \\\"url\\\": url})\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 172, \"content\": \" elif ptype not in {\\\"text\\\",}:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 624, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 625, \"content\": \" Extracts images, media files, and other non-text content blocks\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/mcp_serve.py\", \"line\": 626, \"content\": \" from the specified message.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 119, \"content\": \"@pytest.mark.asyncio\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 120, \"content\": \"async def test_generate_summary_async_kimi_omits_temperature():\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 121, \"content\": \" \\\"\\\"\\\"Kimi models should have temperature omitted — server manages it.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 140, \"content\": \" metrics = TrajectoryMetrics()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 141, \"content\": \" result = await compressor._generate_summary_async(\\\"tool output\\\", metrics)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 142, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 147, \"content\": \"@pytest.mark.asyncio\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 148, \"content\": \"async def test_generate_summary_async_public_moonshot_kimi_k2_5_omits_temperature():\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 149, \"content\": \" \\\"\\\"\\\"kimi-k2.5 on the public Moonshot API should not get a forced temperature.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 169, \"content\": \" metrics = TrajectoryMetrics()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 170, \"content\": \" result = await compressor._generate_summary_async(\\\"tool output\\\", metrics)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 171, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 176, \"content\": \"@pytest.mark.asyncio\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 177, \"content\": \"async def test_generate_summary_async_public_moonshot_cn_kimi_k2_5_omits_temperature():\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 178, \"content\": \" \\\"\\\"\\\"kimi-k2.5 on api.moonshot.cn should not get a forced temperature.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 198, \"content\": \" metrics = TrajectoryMetrics()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 199, \"content\": \" result = await compressor._generate_summary_async(\\\"tool output\\\", metrics)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/test_trajectory_compressor_async.py\", \"line\": 200, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 37, \"content\": \" \\\"read_file\\\", \\\"write_file\\\", \\\"patch\\\", \\\"search_files\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 38, \"content\": \" # Vision + image generation\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 39, \"content\": \" \\\"vision_analyze\\\", \\\"image_generate\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 40, \"content\": \" # Skills\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 44, \"content\": \" \\\"browser_type\\\", \\\"browser_scroll\\\", \\\"browser_back\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 45, \"content\": \" \\\"browser_press\\\", \\\"browser_get_images\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 46, \"content\": \" \\\"browser_vision\\\", \\\"browser_console\\\", \\\"browser_cdp\\\", \\\"browser_dialog\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 103, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 104, \"content\": \" \\\"image_gen\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 105, \"content\": \" \\\"description\\\": \\\"Creative generation tools (images)\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 106, \"content\": \" \\\"tools\\\": [\\\"image_generate\\\"],\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 107, \"content\": \" \\\"includes\\\": []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 111, \"content\": \" \\\"description\\\": (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 112, \"content\": \" \\\"Video generation tools. Single ``video_generate`` tool covers \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 113, \"content\": \" \\\"text-to-video (prompt only) and image-to-video (prompt + \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 114, \"content\": \" \\\"image_url) — the active backend auto-routes. Configure via \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 115, \"content\": \" \\\"``hermes tools`` → Video Generation.\\\"\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=100 to see more, or narrow with a more specific pattern or file_glob.]", "tool_call_id": "call_c3oTTjoRacGCWLt9VDTRnj9u" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_XdYpnbjaWi3oWLb7io98nc7b", "call_id": "call_XdYpnbjaWi3oWLb7io98nc7b", "response_item_id": "fc_034268a3852e0919016a07baec03d8819a9b8ac678c4c95f1e", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"*image*\",\"target\":\"files\",\"path\":\"/home/ubuntu/.hermes/hermes-agent/plugins\",\"limit\":50}" } }, { "id": "call_BEObtLDsrZxdeGa1FZBPWIVs", "call_id": "call_BEObtLDsrZxdeGa1FZBPWIVs", "response_item_id": "fc_034268a3852e0919016a07baec03f4819aa3946d1705bee8d8", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"imagen|gpt-image|fal|provider|IMAGE\",\"target\":\"content\",\"path\":\"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen\",\"limit\":120,\"context\":2}" } }, { "id": "call_T15WjXAaN9ZqpysuZo2Pl6DS", "call_id": "call_T15WjXAaN9ZqpysuZo2Pl6DS", "response_item_id": "fc_034268a3852e0919016a07baec03f8819aa778f871736fb0f7", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"image_generation|image_gen|imagen|gpt-image|fal\",\"target\":\"content\",\"path\":\"/home/ubuntu/.hermes/config.yaml\",\"limit\":80,\"context\":3}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB7rskogBubOAdWepPOqAynaixMNyCkw8waEpVHEtw3misbQ1IRHu-qRxCxeFjiKTY7Un4VE5RWbomO4lyDDwAelzRnL2_SA4XcuT0Ux7lMlK3PjcHkCOEeZ81yRkZxASYi8NLPzX7CZvugs5Do7brmRW0FD9yTTexCRBbFoMhZUUqebWiSlOS678HurnXZlqXFE5899nXOCHl3zyV8m85tlH7ZSuXu-aGGfvK6RsPxuQhtA_DVmPBAWeA7ZwurJOILZIE5rfCUHdCa4gRJ5aDOTXB3Pnc9apcIJPTVNtjQlH1Qb9W2e1UeEqTYV_zFj8H0FY-kCY106GzdP727hDo-Nli1nteJCDvJCG4UVqkOAowsukMUBiTptfgIYmnUdOenGRvmCkLdTS5n5kIgjt7K1hxJJqe4PpJDg7aEh0Ltv8_0zyaLB9_mgad76uhZBJXxM1bv-qEcudgXfJy9YpxYaqpY2h2vLdwMChEaWvouRqDNvMIE65i0XILokGOLrWB2iDhUoNnR26Nf3KckmNVsxe4Rwl1ZgrjKdVczt_sYWddNgcmPC9cxmEPHglEMUPQdbQuRg43WDYjboYw5EYDgbUvdc-cCzDBRpGQHPFGN5U1qNvOO7_8EPjxxJjq5uVkG3UpX8Ff3499AYHbqKh9vZTVvR2Bx2J4Md9d4O2f1BJDLYQr-Szt_aCjzUCqtNimPopkXfqwuX5WmkXcq0TkdDVcaQk_c_4HGKuGvWW1_dE6ihiA8HM2vVv8W_Cco4FlNdQuBXaa4Ph8fDz_JJYMv3Cc-PEGrM7TSrQS0B-LzvMfCkzMPQb223cIDfZ25WIuqvRaRZZsby8cUGNS6dHzq6f0Cpq4vZpSowIBrAjvh3J7b7bs5n6uL--6FW0ZJACz02ymGRPURn9JFP6VaePbLa-mfQjNwel3vlHHmjoZbHlTzWwy-zrp85K5R6MlfXDE_Ai0Xgqj6qc7PjjCFsDdmYmXQ==", "id": "rs_034268a3852e0919016a07bae8dac0819a9200681f9107f808", "summary": [] } ] }, { "role": "tool", "content": "{\"total_count\": 0}", "tool_call_id": "call_XdYpnbjaWi3oWLb7io98nc7b" }, { "role": "tool", "content": "{\"total_count\": 270, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 2, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 3, \"content\": \"Identical model catalog and tier semantics to the ``openai`` image-gen plugin\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 4, \"content\": \"(``gpt-image-2`` at low/medium/high quality), but routes the request through\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 5, \"content\": \"the Codex Responses API ``image_generation`` tool instead of the\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 6, \"content\": \"``images.generate`` REST endpoint. This lets users who are already\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 10, \"content\": \"Selection precedence for the tier (first hit wins):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 11, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 12, \"content\": \"1. ``OPENAI_IMAGE_MODEL`` env var (escape hatch for scripts / tests)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 13, \"content\": \"2. ``image_gen.openai-codex.model`` in ``config.yaml``\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 14, \"content\": \"3. ``image_gen.model`` in ``config.yaml`` (when it's one of our tier IDs)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 15, \"content\": \"4. :data:`DEFAULT_MODEL` — ``gpt-image-2-medium``\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 16, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 17, \"content\": \"Output is saved as PNG under ``$HERMES_HOME/cache/images/``.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 23, \"content\": \"from typing import Any, Dict, List, Optional, Tuple\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 24, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 25, \"content\": \"from agent.image_gen_provider import (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 26, \"content\": \" DEFAULT_ASPECT_RATIO,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 27, \"content\": \" ImageGenProvider,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 39, \"content\": \"# ---------------------------------------------------------------------------\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 40, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 41, \"content\": \"API_MODEL = \\\"gpt-image-2\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 42, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 43, \"content\": \"_MODELS: Dict[str, Dict[str, Any]] = {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 44, \"content\": \" \\\"gpt-image-2-low\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 45, \"content\": \" \\\"display\\\": \\\"GPT Image 2 (Low)\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 46, \"content\": \" \\\"speed\\\": \\\"~15s\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 48, \"content\": \" \\\"quality\\\": \\\"low\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 49, \"content\": \" },\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 50, \"content\": \" \\\"gpt-image-2-medium\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 51, \"content\": \" \\\"display\\\": \\\"GPT Image 2 (Medium)\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 52, \"content\": \" \\\"speed\\\": \\\"~40s\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 54, \"content\": \" \\\"quality\\\": \\\"medium\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 55, \"content\": \" },\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 56, \"content\": \" \\\"gpt-image-2-high\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 57, \"content\": \" \\\"display\\\": \\\"GPT Image 2 (High)\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 58, \"content\": \" \\\"speed\\\": \\\"~2min\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 62, \"content\": \"}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 63, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 64, \"content\": \"DEFAULT_MODEL = \\\"gpt-image-2-medium\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 65, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 66, \"content\": \"_SIZES = {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 103, \"content\": \" import os\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 104, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 105, \"content\": \" env_override = os.environ.get(\\\"OPENAI_IMAGE_MODEL\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 106, \"content\": \" if env_override and env_override in _MODELS:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 107, \"content\": \" return env_override, _MODELS[env_override]\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 221, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 222, \"content\": \"class OpenAICodexImageGenProvider(ImageGenProvider):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 223, \"content\": \" \\\"\\\"\\\"gpt-image-2 routed through ChatGPT/Codex OAuth instead of an API key.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 224, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 225, \"content\": \" @property\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 259, \"content\": \" \\\"name\\\": \\\"OpenAI (Codex auth)\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 260, \"content\": \" \\\"badge\\\": \\\"free\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 261, \"content\": \" \\\"tag\\\": \\\"gpt-image-2 via ChatGPT/Codex OAuth — no API key required\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 262, \"content\": \" \\\"env_vars\\\": [],\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 263, \"content\": \" \\\"post_setup_hint\\\": (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 280, \"content\": \" error=\\\"Prompt is required and must be a non-empty string\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 281, \"content\": \" error_type=\\\"invalid_argument\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 282, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 283, \"content\": \" aspect_ratio=aspect,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 284, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 291, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 292, \"content\": \" error_type=\\\"auth_required\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 293, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 294, \"content\": \" aspect_ratio=aspect,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 295, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 301, \"content\": \" error=\\\"openai Python package not installed (pip install openai)\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 302, \"content\": \" error_type=\\\"missing_dependency\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 303, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 304, \"content\": \" aspect_ratio=aspect,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 305, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 313, \"content\": \" error=\\\"Could not initialize Codex image client\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 314, \"content\": \" error_type=\\\"auth_required\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 315, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 316, \"content\": \" model=tier_id,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 317, \"content\": \" prompt=prompt,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 331, \"content\": \" error=f\\\"OpenAI image generation via Codex auth failed: {exc}\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 332, \"content\": \" error_type=\\\"api_error\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 333, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 334, \"content\": \" model=tier_id,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 335, \"content\": \" prompt=prompt,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 341, \"content\": \" error=\\\"Codex response contained no image_generation_call result\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 342, \"content\": \" error_type=\\\"empty_response\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 343, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 344, \"content\": \" model=tier_id,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 345, \"content\": \" prompt=prompt,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 353, \"content\": \" error=f\\\"Could not save image to cache: {exc}\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 354, \"content\": \" error_type=\\\"io_error\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 355, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 356, \"content\": \" model=tier_id,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 357, \"content\": \" prompt=prompt,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 364, \"content\": \" prompt=prompt,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 365, \"content\": \" aspect_ratio=aspect,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 366, \"content\": \" provider=\\\"openai-codex\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 367, \"content\": \" extra={\\\"size\\\": size, \\\"quality\\\": meta[\\\"quality\\\"]},\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 368, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 375, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 376, \"content\": \"def register(ctx) -> None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 377, \"content\": \" \\\"\\\"\\\"Plugin entry point — register the Codex-backed image-gen provider.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 378, \"content\": \" ctx.register_image_gen_provider(OpenAICodexImageGenProvider())\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/plugin.yaml\", \"line\": 1, \"content\": \"name: openai-codex\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/plugin.yaml\", \"line\": 2, \"content\": \"version: 1.0.0\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/plugin.yaml\", \"line\": 3, \"content\": \"description: \\\"OpenAI image generation backed by ChatGPT/Codex OAuth (gpt-image-2 via the Responses image_generation tool). Saves generated images to $HERMES_HOME/cache/images/.\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/plugin.yaml\", \"line\": 4, \"content\": \"author: NousResearch\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/plugin.yaml\", \"line\": 5, \"content\": \"kind: backend\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 1, \"content\": \"\\\"\\\"\\\"OpenAI image generation backend.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 2, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 3, \"content\": \"Exposes OpenAI's ``gpt-image-2`` model at three quality tiers as an\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 4, \"content\": \":class:`ImageGenProvider` implementation. The tiers are implemented as\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 5, \"content\": \"three virtual model IDs so the ``hermes tools`` model picker and the\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 6, \"content\": \"``image_gen.model`` config key behave like any other multi-model backend:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 7, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 8, \"content\": \" gpt-image-2-low ~15s fastest, good for iteration\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 9, \"content\": \" gpt-image-2-medium ~40s default — balanced\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 10, \"content\": \" gpt-image-2-high ~2min slowest, highest fidelity\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 11, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 12, \"content\": \"All three hit the same underlying API model (``gpt-image-2``) with a\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 13, \"content\": \"different ``quality`` parameter. Output is base64 JSON → saved under\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 14, \"content\": \"``$HERMES_HOME/cache/images/``.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 16, \"content\": \"Selection precedence (first hit wins):\"}], \"truncated\": true}\n\n[Hint: Results truncated. 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Provide detailed, accurate technical\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 91, \"content\": \" information.\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 92, \"content\": \" verbose: false\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 93, \"content\": \"terminal:\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 94, \"content\": \" backend: local\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 95, \"content\": \" modal_mode: auto\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 110, \"content\": \" container_disk: 51200\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 111, \"content\": \" container_persistent: true\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 112, \"content\": \" docker_volumes: []\"}, {\"path\": \"/home/ubuntu/.hermes/config.yaml\", \"line\": 113, \"content\": \" docker_mount_cwd_to_workspace: false\"}, {\"path\": 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I’m thinking about using a tiny prompt to verify. The user is asking for edits, so I want to activate the process efficiently. Generating a test does cost something, but I believe Codex might be free to use. I should keep the tool call low, though it seems like it might not support model quality. I might need to check the backend configuration with OpenAI Codex." } ] } ] }, { "role": "tool", "content": "{\"content\": \" 1|name: openai-codex\\n 2|version: 1.0.0\\n 3|description: \\\"OpenAI image generation backed by ChatGPT/Codex OAuth (gpt-image-2 via the Responses image_generation tool). Saves generated images to $HERMES_HOME/cache/images/.\\\"\\n 4|author: NousResearch\\n 5|kind: backend\\n 6|\", \"total_lines\": 5, \"file_size\": 247, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_ogetLDfCFjIBBmT2FbwMG1x2" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GxfGuVqulaChs96LhZgIzRpK", "call_id": "call_GxfGuVqulaChs96LhZgIzRpK", "response_item_id": "fc_034268a3852e0919016a07bafc84dc819aa26721489ce69349", "type": "function", "function": { "name": "search_files", "arguments": "{\"context\":2,\"limit\":80,\"path\":\"/home/ubuntu/.hermes/hermes-agent\",\"pattern\":\"image_gen.*provider|image_gen.provider|register_image_gen_provider|load.*image_gen|provider_id\",\"file_glob\":\"*.py\",\"target\":\"content\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"total_count\": 238, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/web/brave_free/__init__.py\", \"line\": 1, \"content\": \"\\\"\\\"\\\"Brave Search (free tier) plugin — bundled, auto-loaded.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/web/brave_free/__init__.py\", \"line\": 2, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/web/brave_free/__init__.py\", \"line\": 3, \"content\": \"Mirrors the ``plugins/image_gen/openai/`` layout: ``provider.py`` holds the\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/web/brave_free/__init__.py\", \"line\": 4, \"content\": \"provider class, ``__init__.py::register(ctx)`` registers an instance.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/web/brave_free/__init__.py\", \"line\": 5, \"content\": \"\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 23, \"content\": \"from typing import Any, Dict, List, Optional, Tuple\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 24, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 25, \"content\": \"from agent.image_gen_provider import (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 26, \"content\": \" DEFAULT_ASPECT_RATIO,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 27, \"content\": \" ImageGenProvider,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 86, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 87, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 88, \"content\": \"def _load_image_gen_config() -> Dict[str, Any]:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 89, \"content\": \" \\\"\\\"\\\"Read ``image_gen`` from config.yaml (returns {} on any failure).\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 90, \"content\": \" try:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 95, \"content\": \" return section if isinstance(section, dict) else {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 96, \"content\": \" except Exception as exc:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 97, \"content\": \" logger.debug(\\\"Could not load image_gen config: %s\\\", exc)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 98, \"content\": \" return {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 99, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 107, \"content\": \" return env_override, _MODELS[env_override]\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 108, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 109, \"content\": \" cfg = _load_image_gen_config()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 110, \"content\": \" sub = cfg.get(\\\"openai-codex\\\") if isinstance(cfg.get(\\\"openai-codex\\\"), dict) else {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 111, \"content\": \" candidate: Optional[str] = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 376, \"content\": \"def register(ctx) -> None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 377, \"content\": \" \\\"\\\"\\\"Plugin entry point — register the Codex-backed image-gen provider.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai-codex/__init__.py\", \"line\": 378, \"content\": \" ctx.register_image_gen_provider(OpenAICodexImageGenProvider())\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 28, \"content\": \"from typing import Any, Dict, List, Optional, Tuple\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 29, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 30, \"content\": \"from agent.image_gen_provider import (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 31, \"content\": \" DEFAULT_ASPECT_RATIO,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 32, \"content\": \" ImageGenProvider,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 89, \"content\": \" return section if isinstance(section, dict) else {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 90, \"content\": \" except Exception as exc:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 91, \"content\": \" logger.debug(\\\"Could not load image_gen config: %s\\\", exc)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 92, \"content\": \" return {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 93, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 301, \"content\": \"def register(ctx) -> None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 302, \"content\": \" \\\"\\\"\\\"Plugin entry point — wire ``OpenAIImageGenProvider`` into the registry.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/openai/__init__.py\", \"line\": 303, \"content\": \" ctx.register_image_gen_provider(OpenAIImageGenProvider())\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 24, \"content\": \"import requests\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 25, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 26, \"content\": \"from agent.image_gen_provider import (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 27, \"content\": \" DEFAULT_ASPECT_RATIO,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 28, \"content\": \" ImageGenProvider,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 84, \"content\": \" return xai_section if isinstance(xai_section, dict) else {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 85, \"content\": \" except Exception as exc:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 86, \"content\": \" logger.debug(\\\"Could not load image_gen.xai config: %s\\\", exc)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 87, \"content\": \" return {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 88, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 309, \"content\": \"def register(ctx: Any) -> None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 310, \"content\": \" \\\"\\\"\\\"Register this provider with the image gen registry.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/image_gen/xai/__init__.py\", \"line\": 311, \"content\": \" ctx.register_image_gen_provider(XAIImageGenProvider())\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 10, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 11, \"content\": \"- ``plugins/`` is where third-party service integrations live (see\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 12, \"content\": \" ``plugins/image_gen/`` for the backend-provider pattern, ``plugins/\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 13, \"content\": \" disk-cleanup/`` for the standalone pattern). ``tools/`` is reserved\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 14, \"content\": \" for foundational capabilities (terminal, read_file, web_search, etc.).\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 16, \"content\": \" for categories, flat ``plugins//`` for standalones) makes new\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 17, \"content\": \" service integrations a pattern contributors can copy.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 18, \"content\": \"- Bundled + ``kind: backend`` auto-loads on startup just like image_gen\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 19, \"content\": \" backends — no user opt-in needed, no ``plugins.enabled`` config.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/spotify/__init__.py\", \"line\": 20, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 540, \"content\": \" model_id = raw.strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 541, \"content\": \" except Exception as exc:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 542, \"content\": \" logger.debug(\\\"Could not load image_gen.model from config: %s\\\", exc)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 543, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 544, \"content\": \" # Env var escape hatch (undocumented; backward-compat for tests/scripts).\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 823, \"content\": \" the historical behavior: shipping hermes with a FAL key configured\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 824, \"content\": \" should still expose the tool. The active selection among ready\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 825, \"content\": \" providers is resolved per-call by ``image_gen.provider``.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 826, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 827, \"content\": \" try:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 838, \"content\": \" # Probe plugin providers. Discovery is idempotent and cheap.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 839, \"content\": \" try:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 840, \"content\": \" from agent.image_gen_registry import list_providers\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 841, \"content\": \" from hermes_cli.plugins import _ensure_plugins_discovered\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 842, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\", \"line\": 938, \"content\": \"\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=80 to see more, or narrow with a more specific pattern or file_glob.]", "tool_call_id": "call_GxfGuVqulaChs96LhZgIzRpK" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_hg5ee3mmGj00ZjBj7ZBeZsnv", "call_id": "call_hg5ee3mmGj00ZjBj7ZBeZsnv", "response_item_id": "fc_034268a3852e0919016a07bafff8d0819a8fe6fdbb4762a6f9", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":140,\"offset\":500,\"path\":\"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"content\": \" 500| f\\\" • Pick a different model via `hermes tools` → Image Generation.\\\"\\n 501| ) from exc\\n 502| raise\\n 503|\\n 504|\\n 505|def _extract_http_status(exc: BaseException) -> Optional[int]:\\n 506| \\\"\\\"\\\"Return an HTTP status code from httpx/fal exceptions, else None.\\n 507|\\n 508| Defensive across exception shapes — httpx.HTTPStatusError exposes\\n 509| ``.response.status_code`` while fal_client wrappers may expose\\n 510| ``.status_code`` directly.\\n 511| \\\"\\\"\\\"\\n 512| response = getattr(exc, \\\"response\\\", None)\\n 513| if response is not None:\\n 514| status = getattr(response, \\\"status_code\\\", None)\\n 515| if isinstance(status, int):\\n 516| return status\\n 517| status = getattr(exc, \\\"status_code\\\", None)\\n 518| if isinstance(status, int):\\n 519| return status\\n 520| return None\\n 521|\\n 522|\\n 523|# ---------------------------------------------------------------------------\\n 524|# Model resolution + payload construction\\n 525|# ---------------------------------------------------------------------------\\n 526|def _resolve_fal_model() -> tuple:\\n 527| \\\"\\\"\\\"Resolve the active FAL model from config.yaml (primary) or default.\\n 528|\\n 529| Returns (model_id, metadata_dict). Falls back to DEFAULT_MODEL if the\\n 530| configured model is unknown (logged as a warning).\\n 531| \\\"\\\"\\\"\\n 532| model_id = \\\"\\\"\\n 533| try:\\n 534| from hermes_cli.config import load_config\\n 535| cfg = load_config()\\n 536| img_cfg = cfg.get(\\\"image_gen\\\") if isinstance(cfg, dict) else None\\n 537| if isinstance(img_cfg, dict):\\n 538| raw = img_cfg.get(\\\"model\\\")\\n 539| if isinstance(raw, str):\\n 540| model_id = raw.strip()\\n 541| except Exception as exc:\\n 542| logger.debug(\\\"Could not load image_gen.model from config: %s\\\", exc)\\n 543|\\n 544| # Env var escape hatch (undocumented; backward-compat for tests/scripts).\\n 545| if not model_id:\\n 546| model_id = os.getenv(\\\"FAL_IMAGE_MODEL\\\", \\\"\\\").strip()\\n 547|\\n 548| if not model_id:\\n 549| return DEFAULT_MODEL, FAL_MODELS[DEFAULT_MODEL]\\n 550|\\n 551| if model_id not in FAL_MODELS:\\n 552| logger.warning(\\n 553| \\\"Unknown FAL model '%s' in config; falling back to %s\\\",\\n 554| model_id, DEFAULT_MODEL,\\n 555| )\\n 556| return DEFAULT_MODEL, FAL_MODELS[DEFAULT_MODEL]\\n 557|\\n 558| return model_id, FAL_MODELS[model_id]\\n 559|\\n 560|\\n 561|def _build_fal_payload(\\n 562| model_id: str,\\n 563| prompt: str,\\n 564| aspect_ratio: str = DEFAULT_ASPECT_RATIO,\\n 565| seed: Optional[int] = None,\\n 566| overrides: Optional[Dict[str, Any]] = None,\\n 567|) -> Dict[str, Any]:\\n 568| \\\"\\\"\\\"Build a FAL request payload for `model_id` from unified inputs.\\n 569|\\n 570| Translates aspect_ratio into the model's native size spec (preset enum,\\n 571| aspect-ratio enum, or GPT literal string), merges model defaults, applies\\n 572| caller overrides, then filters to the model's ``supports`` whitelist.\\n 573| \\\"\\\"\\\"\\n 574| meta = FAL_MODELS[model_id]\\n 575| size_style = meta[\\\"size_style\\\"]\\n 576| sizes = meta[\\\"sizes\\\"]\\n 577|\\n 578| aspect = (aspect_ratio or DEFAULT_ASPECT_RATIO).lower().strip()\\n 579| if aspect not in sizes:\\n 580| aspect = DEFAULT_ASPECT_RATIO\\n 581|\\n 582| payload: Dict[str, Any] = dict(meta.get(\\\"defaults\\\", {}))\\n 583| payload[\\\"prompt\\\"] = (prompt or \\\"\\\").strip()\\n 584|\\n 585| if size_style in {\\\"image_size_preset\\\", \\\"gpt_literal\\\"}:\\n 586| payload[\\\"image_size\\\"] = sizes[aspect]\\n 587| elif size_style == \\\"aspect_ratio\\\":\\n 588| payload[\\\"aspect_ratio\\\"] = sizes[aspect]\\n 589| else:\\n 590| raise ValueError(f\\\"Unknown size_style: {size_style!r}\\\")\\n 591|\\n 592| if seed is not None and isinstance(seed, int):\\n 593| payload[\\\"seed\\\"] = seed\\n 594|\\n 595| if overrides:\\n 596| for k, v in overrides.items():\\n 597| if v is not None:\\n 598| payload[k] = v\\n 599|\\n 600| supports = meta[\\\"supports\\\"]\\n 601| return {k: v for k, v in payload.items() if k in supports}\\n 602|\\n 603|\\n 604|# ---------------------------------------------------------------------------\\n 605|# Upscaler\\n 606|# ---------------------------------------------------------------------------\\n 607|def _upscale_image(image_url: str, original_prompt: str) -> Optional[Dict[str, Any]]:\\n 608| \\\"\\\"\\\"Upscale an image using FAL.ai's Clarity Upscaler.\\n 609|\\n 610| Returns upscaled image dict, or None on failure (caller falls back to\\n 611| the original image).\\n 612| \\\"\\\"\\\"\\n 613| try:\\n 614| logger.info(\\\"Upscaling image with Clarity Upscaler...\\\")\\n 615|\\n 616| upscaler_arguments = {\\n 617| \\\"image_url\\\": image_url,\\n 618| \\\"prompt\\\": f\\\"{UPSCALER_DEFAULT_PROMPT}, {original_prompt}\\\",\\n 619| \\\"upscale_factor\\\": UPSCALER_FACTOR,\\n 620| \\\"negative_prompt\\\": UPSCALER_NEGATIVE_PROMPT,\\n 621| \\\"creativity\\\": UPSCALER_CREATIVITY,\\n 622| \\\"resemblance\\\": UPSCALER_RESEMBLANCE,\\n 623| \\\"guidance_scale\\\": UPSCALER_GUIDANCE_SCALE,\\n 624| \\\"num_inference_steps\\\": UPSCALER_NUM_INFERENCE_STEPS,\\n 625| \\\"enable_safety_checker\\\": UPSCALER_SAFETY_CHECKER,\\n 626| }\\n 627|\\n 628| handler = _submit_fal_request(UPSCALER_MODEL, arguments=upscaler_arguments)\\n 629| result = handler.get()\\n 630|\\n 631| if result and \\\"image\\\" in result:\\n 632| upscaled_image = result[\\\"image\\\"]\\n 633| logger.info(\\n 634| \\\"Image upscaled successfully to %sx%s\\\",\\n 635| upscaled_image.get(\\\"width\\\", \\\"unknown\\\"),\\n 636| upscaled_image.get(\\\"height\\\", \\\"unknown\\\"),\\n 637| )\\n 638| return {\\n 639| \\\"url\\\": upscaled_image[\\\"url\\\"],\\n 640|\", \"total_lines\": 1065, \"file_size\": 40256, \"truncated\": true, \"hint\": \"Use offset=640 to continue reading (showing 500-639 of 1065 lines)\", \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_hg5ee3mmGj00ZjBj7ZBeZsnv" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_5vhrtYr13hl5z2PHGxei9wpv", "call_id": "call_5vhrtYr13hl5z2PHGxei9wpv", "response_item_id": "fc_034268a3852e0919016a07bb036580819ab124f842a295c1e3", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":130,\"offset\":760,\"path\":\"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"content\": \" 760| formatted_images.append(upscaled_image)\\n 761| continue\\n 762| logger.warning(\\\"Using original image as fallback (upscale failed)\\\")\\n 763|\\n 764| original_image[\\\"upscaled\\\"] = False\\n 765| formatted_images.append(original_image)\\n 766|\\n 767| if not formatted_images:\\n 768| raise ValueError(\\\"No valid image URLs returned from API\\\")\\n 769|\\n 770| upscaled_count = sum(1 for img in formatted_images if img.get(\\\"upscaled\\\"))\\n 771| logger.info(\\n 772| \\\"Generated %s image(s) in %.1fs (%s upscaled) via %s\\\",\\n 773| len(formatted_images), generation_time, upscaled_count, model_id,\\n 774| )\\n 775|\\n 776| response_data = {\\n 777| \\\"success\\\": True,\\n 778| \\\"image\\\": formatted_images[0][\\\"url\\\"] if formatted_images else None,\\n 779| }\\n 780|\\n 781| debug_call_data[\\\"success\\\"] = True\\n 782| debug_call_data[\\\"images_generated\\\"] = len(formatted_images)\\n 783| debug_call_data[\\\"generation_time\\\"] = generation_time\\n 784| _debug.log_call(\\\"image_generate_tool\\\", debug_call_data)\\n 785| _debug.save()\\n 786|\\n 787| return json.dumps(response_data, indent=2, ensure_ascii=False)\\n 788|\\n 789| except Exception as e:\\n 790| generation_time = (datetime.datetime.now() - start_time).total_seconds()\\n 791| error_msg = f\\\"Error generating image: {str(e)}\\\"\\n 792| logger.error(\\\"%s\\\", error_msg, exc_info=True)\\n 793|\\n 794| response_data = {\\n 795| \\\"success\\\": False,\\n 796| \\\"image\\\": None,\\n 797| \\\"error\\\": str(e),\\n 798| \\\"error_type\\\": type(e).__name__,\\n 799| }\\n 800|\\n 801| debug_call_data[\\\"error\\\"] = error_msg\\n 802| debug_call_data[\\\"generation_time\\\"] = generation_time\\n 803| _debug.log_call(\\\"image_generate_tool\\\", debug_call_data)\\n 804| _debug.save()\\n 805|\\n 806| return json.dumps(response_data, indent=2, ensure_ascii=False)\\n 807|\\n 808|\\n 809|def check_fal_api_key() -> bool:\\n 810| \\\"\\\"\\\"True if the FAL.ai API key (direct or managed gateway) is available.\\\"\\\"\\\"\\n 811| return bool(fal_ke...ured() or _resolve_managed_fal_gateway())\\n 812|\\n 813|\\n 814|def check_image_generation_requirements() -> bool:\\n 815| \\\"\\\"\\\"True if any image gen backend is available.\\n 816|\\n 817| Providers are considered in this order:\\n 818|\\n 819| 1. The in-tree FAL backend (FAL_KEY or managed gateway).\\n 820| 2. Any plugin-registered provider whose ``is_available()`` returns True.\\n 821|\\n 822| Plugins win only when the in-tree FAL path is NOT ready, which matches\\n 823| the historical behavior: shipping hermes with a FAL key configured\\n 824| should still expose the tool. The active selection among ready\\n 825| providers is resolved per-call by ``image_gen.provider``.\\n 826| \\\"\\\"\\\"\\n 827| try:\\n 828| if check_fal_api_key():\\n 829| # Trigger the lazy fal_client import here as the SDK presence\\n 830| # check. Raises ImportError if the optional ``fal-client``\\n 831| # package isn't installed; the caller's except ImportError\\n 832| # below catches that and continues to plugin probing.\\n 833| _load_fal_client()\\n 834| return True\\n 835| except ImportError:\\n 836| pass\\n 837|\\n 838| # Probe plugin providers. Discovery is idempotent and cheap.\\n 839| try:\\n 840| from agent.image_gen_registry import list_providers\\n 841| from hermes_cli.plugins import _ensure_plugins_discovered\\n 842|\\n 843| _ensure_plugins_discovered()\\n 844| for provider in list_providers():\\n 845| try:\\n 846| if provider.is_available():\\n 847| return True\\n 848| except Exception:\\n 849| continue\\n 850| except Exception:\\n 851| pass\\n 852|\\n 853| return False\\n 854|\\n 855|\\n 856|# ---------------------------------------------------------------------------\\n 857|# Demo / CLI entry point\\n 858|# ---------------------------------------------------------------------------\\n 859|if __name__ == \\\"__main__\\\":\\n 860| print(\\\"🎨 Image Generation Tools — FAL.ai multi-model support\\\")\\n 861| print(\\\"=\\\" * 60)\\n 862|\\n 863| if not check_fal_api_key():\\n 864| print(\\\"❌ FAL_KEY environment variable not set\\\")\\n 865| print(\\\" Set it via: export FAL_KEY='your-key-here'\\\")\\n 866| print(\\\" Get a key: https://fal.ai/\\\")\\n 867| raise SystemExit(1)\\n 868| print(\\\"✅ FAL.ai API key found\\\")\\n 869|\\n 870| try:\\n 871| import fal_client # noqa: F401\\n 872| print(\\\"✅ fal_client library available\\\")\\n 873| except ImportError:\\n 874| print(\\\"❌ fal_client library not found — pip install fal-client\\\")\\n 875| raise SystemExit(1)\\n 876|\\n 877| model_id, meta = _resolve_fal_model()\\n 878| print(f\\\"🤖 Active model: {meta.get('display', model_id)} ({model_id})\\\")\\n 879| print(f\\\" Speed: {meta.get('speed', '?')} · Price: {meta.get('price', '?')}\\\")\\n 880| print(f\\\" Upscaler: {'on' if meta.get('upscale') else 'off'}\\\")\\n 881|\\n 882| print(\\\"\\\\nAvailable models:\\\")\\n 883| for mid, m in FAL_MODELS.items():\\n 884| marker = \\\" ← active\\\" if mid == model_id else \\\"\\\"\\n 885| print(f\\\" {mid:<32} {m.get('speed', '?'):<6} {m.get('price', '?')}{marker}\\\")\\n 886|\\n 887| if _debug.active:\\n 888| print(f\\\"\\\\n🐛 Debug mode enabled — session {_debug.session_id}\\\")\\n 889|\\n 890|\", \"total_lines\": 1065, \"file_size\": 40256, \"truncated\": true, \"hint\": \"Use offset=890 to continue reading (showing 760-889 of 1065 lines)\", \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_5vhrtYr13hl5z2PHGxei9wpv" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_14Zy1Mxb0H4uitVTUSXB2yNy", "call_id": "call_14Zy1Mxb0H4uitVTUSXB2yNy", "response_item_id": "fc_034268a3852e0919016a07bb07a3d0819a8afa450826618e4b", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":120,\"offset\":890,\"path\":\"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"content\": \" 890|\\n 891|# ---------------------------------------------------------------------------\\n 892|# Registry\\n 893|# ---------------------------------------------------------------------------\\n 894|from tools.registry import registry, tool_error\\n 895|\\n 896|IMAGE_GENERATE_SCHEMA = {\\n 897| \\\"name\\\": \\\"image_generate\\\",\\n 898| \\\"description\\\": (\\n 899| \\\"Generate high-quality images from text prompts. The underlying \\\"\\n 900| \\\"backend (FAL, OpenAI, etc.) and model are user-configured and not \\\"\\n 901| \\\"selectable by the agent. Returns either a URL or an absolute file \\\"\\n 902| \\\"path in the `image` field; display it with markdown \\\"\\n 903| \\\"![description](url-or-path) and the gateway will deliver it.\\\"\\n 904| ),\\n 905| \\\"parameters\\\": {\\n 906| \\\"type\\\": \\\"object\\\",\\n 907| \\\"properties\\\": {\\n 908| \\\"prompt\\\": {\\n 909| \\\"type\\\": \\\"string\\\",\\n 910| \\\"description\\\": \\\"The text prompt describing the desired image. Be detailed and descriptive.\\\",\\n 911| },\\n 912| \\\"aspect_ratio\\\": {\\n 913| \\\"type\\\": \\\"string\\\",\\n 914| \\\"enum\\\": list(VALID_ASPECT_RATIOS),\\n 915| \\\"description\\\": \\\"The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.\\\",\\n 916| \\\"default\\\": DEFAULT_ASPECT_RATIO,\\n 917| },\\n 918| },\\n 919| \\\"required\\\": [\\\"prompt\\\"],\\n 920| },\\n 921|}\\n 922|\\n 923|\\n 924|def _read_configured_image_model():\\n 925| \\\"\\\"\\\"Return the value of ``image_gen.model`` from config.yaml, or None.\\\"\\\"\\\"\\n 926| try:\\n 927| from hermes_cli.config import load_config\\n 928| cfg = load_config()\\n 929| section = cfg.get(\\\"image_gen\\\") if isinstance(cfg, dict) else None\\n 930| if isinstance(section, dict):\\n 931| value = section.get(\\\"model\\\")\\n 932| if isinstance(value, str) and value.strip():\\n 933| return value.strip()\\n 934| except Exception as exc:\\n 935| logger.debug(\\\"Could not read image_gen.model: %s\\\", exc)\\n 936| return None\\n 937|\\n 938|\\n 939|def _read_configured_image_provider():\\n 940| \\\"\\\"\\\"Return the value of ``image_gen.provider`` from config.yaml, or None.\\n 941|\\n 942| We only consult the plugin registry when this is explicitly set — an\\n 943| unset value keeps users on the legacy in-tree FAL path even when other\\n 944| providers happen to be registered (e.g. a user has OPENAI_API_KEY set\\n 945| for other features but never asked for OpenAI image gen).\\n 946| \\\"\\\"\\\"\\n 947| try:\\n 948| from hermes_cli.config import load_config\\n 949| cfg = load_config()\\n 950| section = cfg.get(\\\"image_gen\\\") if isinstance(cfg, dict) else None\\n 951| if isinstance(section, dict):\\n 952| value = section.get(\\\"provider\\\")\\n 953| if isinstance(value, str) and value.strip():\\n 954| return value.strip()\\n 955| except Exception as exc:\\n 956| logger.debug(\\\"Could not read image_gen.provider: %s\\\", exc)\\n 957| return None\\n 958|\\n 959|\\n 960|def _dispatch_to_plugin_provider(prompt: str, aspect_ratio: str):\\n 961| \\\"\\\"\\\"Route the call to a plugin-registered provider when one is selected.\\n 962|\\n 963| Returns a JSON string on dispatch, or ``None`` to fall through to the\\n 964| built-in FAL path.\\n 965|\\n 966| Dispatch only fires when ``image_gen.provider`` is explicitly set AND\\n 967| it does not point to ``fal`` (FAL still lives in-tree in this PR;\\n 968| a later PR ports it into ``plugins/image_gen/fal/``). Any other value\\n 969| that matches a registered plugin provider wins.\\n 970| \\\"\\\"\\\"\\n 971| configured = _read_configured_image_provider()\\n 972| if not configured or configured == \\\"fal\\\":\\n 973| return None\\n 974|\\n 975| # Also read configured model so we can pass it to the plugin\\n 976| configured_model = _read_configured_image_model()\\n 977|\\n 978| try:\\n 979| # Import locally so plugin discovery isn't triggered just by\\n 980| # importing this module (tests rely on that).\\n 981| from agent.image_gen_registry import get_provider\\n 982| from hermes_cli.plugins import _ensure_plugins_discovered\\n 983|\\n 984| _ensure_plugins_discovered()\\n 985| provider = get_provider(configured)\\n 986| except Exception as exc:\\n 987| logger.debug(\\\"image_gen plugin dispatch skipped: %s\\\", exc)\\n 988| return None\\n 989|\\n 990| if provider is None:\\n 991| try:\\n 992| # Long-lived sessions may have discovered plugins before a bundled\\n 993| # backend was patched in or before config changed. Retry once with\\n 994| # a forced refresh before surfacing a missing-provider error.\\n 995| _ensure_plugins_discovered(force=True)\\n 996| provider = get_provider(configured)\\n 997| except Exception as exc:\\n 998| logger.debug(\\\"image_gen plugin force-refresh skipped: %s\\\", exc)\\n 999|\\n 1000| if provider is None:\\n 1001| return json.dumps({\\n 1002| \\\"success\\\": False,\\n 1003| \\\"image\\\": None,\\n 1004| \\\"error\\\": (\\n 1005| f\\\"image_gen.provider='{configured}' is set but no plugin \\\"\\n 1006| f\\\"registered that name. Run `hermes plugins list` to see \\\"\\n 1007| f\\\"available image gen backends.\\\"\\n 1008| ),\\n 1009| \\\"error_type\\\": \\\"provider_not_registered\\\",\\n 1010|\", \"total_lines\": 1065, \"file_size\": 40256, \"truncated\": true, \"hint\": \"Use offset=1010 to continue reading (showing 890-1009 of 1065 lines)\", \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_14Zy1Mxb0H4uitVTUSXB2yNy" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_HpMPQSJ4fTnBrd2Q8zWs0DbB", "call_id": "call_HpMPQSJ4fTnBrd2Q8zWs0DbB", "response_item_id": "fc_034268a3852e0919016a07bb0ba59c819ab24ce60b626693e6", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":65,\"offset\":1010,\"path\":\"/home/ubuntu/.hermes/hermes-agent/tools/image_generation_tool.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"content\": \" 1010| })\\n 1011|\\n 1012| try:\\n 1013| kwargs = {\\\"prompt\\\": prompt, \\\"aspect_ratio\\\": aspect_ratio}\\n 1014| if configured_model:\\n 1015| kwargs[\\\"model\\\"] = configured_model\\n 1016| result = provider.generate(**kwargs)\\n 1017| except Exception as exc:\\n 1018| logger.warning(\\n 1019| \\\"Image gen provider '%s' raised: %s\\\",\\n 1020| getattr(provider, \\\"name\\\", \\\"?\\\"), exc,\\n 1021| )\\n 1022| return json.dumps({\\n 1023| \\\"success\\\": False,\\n 1024| \\\"image\\\": None,\\n 1025| \\\"error\\\": f\\\"Provider '{getattr(provider, 'name', '?')}' error: {exc}\\\",\\n 1026| \\\"error_type\\\": \\\"provider_exception\\\",\\n 1027| })\\n 1028| if not isinstance(result, dict):\\n 1029| return json.dumps({\\n 1030| \\\"success\\\": False,\\n 1031| \\\"image\\\": None,\\n 1032| \\\"error\\\": \\\"Provider returned a non-dict result\\\",\\n 1033| \\\"error_type\\\": \\\"provider_contract\\\",\\n 1034| })\\n 1035| return json.dumps(result)\\n 1036|\\n 1037|\\n 1038|def _handle_image_generate(args, **kw):\\n 1039| prompt = args.get(\\\"prompt\\\", \\\"\\\")\\n 1040| if not prompt:\\n 1041| return tool_error(\\\"prompt is required for image generation\\\")\\n 1042| aspect_ratio = args.get(\\\"aspect_ratio\\\", DEFAULT_ASPECT_RATIO)\\n 1043|\\n 1044| # Route to a plugin-registered provider if one is active (and it's\\n 1045| # not the in-tree FAL path).\\n 1046| dispatched = _dispatch_to_plugin_provider(prompt, aspect_ratio)\\n 1047| if dispatched is not None:\\n 1048| return dispatched\\n 1049|\\n 1050| return image_generate_tool(\\n 1051| prompt=prompt,\\n 1052| aspect_ratio=aspect_ratio,\\n 1053| )\\n 1054|\\n 1055|\\n 1056|registry.register(\\n 1057| name=\\\"image_generate\\\",\\n 1058| toolset=\\\"image_gen\\\",\\n 1059| schema=IMAGE_GENERATE_SCHEMA,\\n 1060| handler=_handle_image_generate,\\n 1061| check_fn=check_image_generation_requirements,\\n 1062| requires_env=[],\\n 1063| is_async=False, # sync fal_client API to avoid \\\"Event loop is closed\\\" in gateway\\n 1064| emoji=\\\"🎨\\\",\\n 1065|)\\n 1066|\", \"total_lines\": 1065, \"file_size\": 40256, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_HpMPQSJ4fTnBrd2Q8zWs0DbB" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_HthhiiOu4pT4QPQlZm1vtrDP", "call_id": "call_HthhiiOu4pT4QPQlZm1vtrDP", "response_item_id": "fc_034268a3852e0919016a07bb13a320819a8e6a439b10bf16d2", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"hermes plugins list | grep -i -A2 -B1 'openai-codex\\\\|image' || true\",\"timeout\":60,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } }, { "id": "call_iR9Lzuoxjxm0BjsNixOkcR77", "call_id": "call_iR9Lzuoxjxm0BjsNixOkcR77", "response_item_id": "fc_034268a3852e0919016a07bb13a334819ab862e4c6397e4b73", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nfrom hermes_cli.plugins import _ensure_plugins_discovered\\nfrom agent.image_gen_registry import list_providers\\n_ensure_plugins_discovered(force=True)\\nfor p in list_providers():\\n print(p.name, getattr(p,'display_name',None), 'available=', p.is_available())\\nPY\",\"timeout\":60,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Configuring image generation settings**\n\nI'm thinking about configuring the image generation provider with the OpenAI Codex model. I might need to set this up using Hermes configuration. First, I need to verify if the OpenAI Codex authentication is available. I wonder if I should search for authentication options—hopefully no secrets will be required. Alternatively, I could check the Hermes status or look at the plugin list for more information. Let's see how that goes!", "reasoning_content": "**Configuring image generation settings**\n\nI'm thinking about configuring the image generation provider with the OpenAI Codex model. I might need to set this up using Hermes configuration. First, I need to verify if the OpenAI Codex authentication is available. I wonder if I should search for authentication options—hopefully no secrets will be required. Alternatively, I could check the Hermes status or look at the plugin list for more information. Let's see how that goes!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB7sTxfQdQwJvzwNxYyWzfXL97iio0Btq40iu-wstLMlgkscNmrYPyTjOt7l_MRUCvl-gmfxniiVLzjOtskM1gO0SB1EjQTXovRT7dCP0zqBoYDMlkHAhGMkX4HY8z-0-TB31m91VZbtHGOxZxdD1jOWmqyqgVmbP_MV3nkDNTEZrCVo20HTKqoBroC1cDVTAC-lIVUoUikeCnjs36OodE_z5vK21Azv8rUCDd3ofQ0K-a372vZpOnXmxnXccpfN_SKpGNb-4PVuv3u0o0vjom76GBR1xXWmHGH963Y51D3WnI4XKhKtJxKfJD0dCzIMproU5LrusBEWM6I-AWZ9wRfKohPGqv8Tvd6ajontYrlOcdpJUd342W46zK5K367xIpLLA64ZHHixZ_cISusChDQ3YK7i9lBmstnTcqNS9JK25CSEmdyWTvSJH_0hnMp50e7Lm2nT4l-PslMsi3m9Eh3At9mL3tQBXhM0o7zU2SVAFEzmbmEzXsX2G3PaLKcUw2gBcx05MB4qBrxa17ZP3GqWCMmQCYFc5U-RVdqJpfoV6S7UkOSveFdOqgpFZQDvE6rR-oHMorST_mA-4Tr3AcWtgfLsoVDpZPerE5OaIT11-l-iC0gRn8RAHL67uXgiTnXX1ALuYJVdvYPdJNWQ0ywGhAmyC-LMzLm5-3FCnKnB1IjmmMh6FhZFaQ9cLe2gwjMWvm23AG1IprB4Ra2_khYgzPfwnF8Rv7DNpCnBx6ucoXk97QtG_eI4o3cMo4XJTFGLelf3ZpWLZMV-txJk2SEARINi4fWcwRPgRI3Mi8pwUXc9yQ5Lj8TCfy5A6FEFCx_B0BUEfqbvuXQqYsvWmfXA7S9aiZOgXkcFm6R53zee8_0aftdDUBudxaAorpZjh9HHbBzf-cKe63hADEVP3SeY9bP_11fy6TGhLCDU3MnNXDPUioYBP4wNEpAdpO9rwJZEbdD2DOAUToboFwpZCG9GKwt5ZBnlf8TA7Za_YAgOccYjOm5GfTcwyqPGWv6sqDldkvB7n40NMDgsosjY_22rFPz0OYAQQRF7lFLNvUgVpv8s2QnxtNYhFlUVSkqGIAsJOeTku7t7TM_qvIRYh41vqrjUo5byqN_s7fv7wNKhwdH3rlqZlqI2eNTx-0vF-MMP_4wBpi_CxrobUFM9fcxMEew==", "id": "rs_034268a3852e0919016a07bb0f68c0819a800c59d8561434bb", "summary": [ { "type": "summary_text", "text": "**Configuring image generation settings**\n\nI'm thinking about configuring the image generation provider with the OpenAI Codex model. I might need to set this up using Hermes configuration. First, I need to verify if the OpenAI Codex authentication is available. I wonder if I should search for authentication options—hopefully no secrets will be required. Alternatively, I could check the Hermes status or look at the plugin list for more information. Let's see how that goes!" } ] } ] }, { "role": "tool", "content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_HthhiiOu4pT4QPQlZm1vtrDP" }, { "role": "tool", "content": "{\"output\": \"openai OpenAI available= False\\nopenai-codex OpenAI (Codex auth) available= True\\nxai xAI (Grok) available= False\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_iR9Lzuoxjxm0BjsNixOkcR77" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_cb3ABAsSh21KNkCtIEOvsJRr", "call_id": "call_cb3ABAsSh21KNkCtIEOvsJRr", "response_item_id": "fc_034268a3852e0919016a07bb1ca3b4819ab1f5c04ab1b16363", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"hermes config set image_gen.provider openai-codex && hermes config set image_gen.model gpt-image-2-medium && python - <<'PY'\\nfrom hermes_cli.config import load_config\\ncfg=load_config().get('image_gen',{})\\nprint(cfg)\\nPY\",\"timeout\":60,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Configuring tools for image generation**\n\nI need to set up the configuration before testing to generate an image. Maybe I need to restart or reset the gateway? It looks like the tool configuration reads per call. The toolset is already enabled, so any changes to the provider should be immediate. I’ll use the command to set the image generation provider to openai-codex with a medium setting for the model. While low is an option for iteration, medium should be the default.", "reasoning_content": "**Configuring tools for image generation**\n\nI need to set up the configuration before testing to generate an image. Maybe I need to restart or reset the gateway? It looks like the tool configuration reads per call. The toolset is already enabled, so any changes to the provider should be immediate. I’ll use the command to set the image generation provider to openai-codex with a medium setting for the model. While low is an option for iteration, medium should be the default.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB7sckOpIPYfyYvhtaEQ4-cD8X5r9N8ACSFI7HHH2OaeeDbdYNdrS4Vgj82tQVoYb_G7wNRJUzLl7ehqsnBYbMDN4qg0kzBhv04vI6EtCHACuqR0zxvYNcg9KxQPxr9ZZD2_JOFoddeT8PnAkSu7WiT_OBdBILuqk0LeGzFOfq5a5f9q0CYCkIr61eJ1tpi2O7GZvQT4bXr1YZ7SQa4wqZnF8QBXRFv6FVe4wJKmhg-EHzdlypk_nXvnk2l9BBHTECkH2Dmz7p0ylNryi9HlC0Wnfwajzz8AXpURC0KmAwrtVQ2v1tZ9GzhAVIygfDeqV7suDGM4m-Plcz4JbtUIIcUPedFUUWO09eo_tXJO01CbmAgpBk_zbRGX2PkMB4zdYJxvJ7buFU4k8IM5AMPbjOhVuNB63D02U-5ZL8-SsfDGsfK5gmTpLb960Hs3Db8nbts_ShpfpifrqXOjesnFBLEbF_iy0N3s20KiZXWSaJaNtKk3el_kSpi1mTVJhebJDZ0Y4pVbu54Epx4jXMneMt5JIGjviwmQbBl8I5XYAKSGXifrWGuBc5itbr-O2tQjd5eIcAc64Ucxie2L-LDH9P_kChD_-cJTwaIopd1MR0mfFqv6vESvT98Z35198jOY8qHbbrautwPZGFR1RHV7Bpb-dc-XsskNIzriA8lRDXIb0_YffqCb6sh1-y_Z7nZvTA-HyoX_AYwsMeybo7M6NT4oYhBVlBH5mmRAeoppY2QfxsWfWXiRxEKZtRAJhE34rAzR-EO0HqH1C8CvYXBMkO4Ikqve8xLPDusLurUd3N-BAxYMwYzDhJ82otD5YSMhX6zl9i-1i8kGqVLKxFNFzPXcFUl2gvwJhRGaorVfNGFhsVKzpY0LZHsQGi6GJuLqU_ZEJZhw7KsaynW5-P5rdEzXvngQ6P_JkNqF9f22AKDZ1_OtGFRZRIr4jRc-wve5w41dt8yo1DmC5_ftMLHojlBu4C1HuV9WFw45WJu7Gxr4dman9kL76bypOn3XUi3euOeRPz_B4XdfPpQeSLD2D3VuQkwyHeWwtUMoG-7Dip8R5LOVijfY8ptMcCEIfoIeYTY8Sx1TDj2lVMvsnncA5jxUc7j01ZhXLKV_ew8QR5GtBHYZUMJkVDvnhJcV879CyvhFzdfzbbDDTQm0wnQUQmDM1wwh-w-JQopZOK0vB-FFWuY_9kufXxgoEt5L2rlYsotCOeoh8lA52CpTM0DAQbgrkiAqsXXALJEbZWDJarRvBa9m5FWR5fsUtM4X-k0FWwBc9lAQvHxTmtwofvgT6zF2E2TH9lHshSKlfaf78gYaTtDpQSGzDspk-FMePXbrYoos_-jw-6XDePqLBMMXoqIWK3wT1mQDkg-KXyMvZLpDG0Nc=", "id": "rs_034268a3852e0919016a07bb195b74819a96102d2ac07a7a85", "summary": [ { "type": "summary_text", "text": "**Configuring tools for image generation**\n\nI need to set up the configuration before testing to generate an image. Maybe I need to restart or reset the gateway? It looks like the tool configuration reads per call. The toolset is already enabled, so any changes to the provider should be immediate. I’ll use the command to set the image generation provider to openai-codex with a medium setting for the model. While low is an option for iteration, medium should be the default." } ] } ] }, { "role": "tool", "content": "{\"output\": \"✓ Set image_gen.provider = openai-codex in /home/ubuntu/.hermes/config.yaml\\n✓ Set image_gen.model = gpt-image-2-medium in /home/ubuntu/.hermes/config.yaml\\n{'provider': 'openai-codex', 'model': 'gpt-image-2-medium'}\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_cb3ABAsSh21KNkCtIEOvsJRr" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_jhQU0wvD9iGdJf1DKrcuy2Xn", "call_id": "call_jhQU0wvD9iGdJf1DKrcuy2Xn", "response_item_id": "fc_034268a3852e0919016a07bb220dcc819aa7b6d4ec96a732fe", "type": "function", "function": { "name": "image_generate", "arguments": "{\"aspect_ratio\":\"square\",\"prompt\":\"A tiny clean test image: the word OK in black on a plain white background, minimal, no decoration.\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Verifying tool usage**\n\nI need to test the image generation tool, so I’ll use the small version. But first, it’s important to check its activation — I might face issues if it's not enabled. My plan is to call it with a simple prompt to create an image. Ensuring everything is set up correctly is key before I proceed, so I’ll verify the tool’s status first. This should help avoid any potential hiccups!", "reasoning_content": "**Verifying tool usage**\n\nI need to test the image generation tool, so I’ll use the small version. But first, it’s important to check its activation — I might face issues if it's not enabled. My plan is to call it with a simple prompt to create an image. Ensuring everything is set up correctly is key before I proceed, so I’ll verify the tool’s status first. This should help avoid any potential hiccups!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB7sizibI2bKLz6Fu9OxiRH5cmzf-qkc-PkIvJgXUmGz-_Y903ALr3irhWqk-VlyYB9AJVprD2rLHpQmYGvxdEJt7i74V-AOPXTxkY4oh77W8qvkQtm7GKvxce35VDBjvPf_pFq7fiXb7ZXXFqsw0MpYffZ05GGsWfEe3GX2IIQ26QGXrQ4HrjwdUxJxPPbbwfc-NB-HkAeeG05S1HmR5Wtfq-7w0XwvBYCnnQaQNBYhvD7hrMiu-oXQcsJ3tbkUxM00Y2pj0guyQSQwsjB5nTxezwqhC9-9mfILT4QKSo5lzEoKAlUA6aNJFsTY3DraNORa8BgQnGXuqgxJ7_RkLeZ8IJ1ycmKihFT9qwsq1heTbMg_CSsRI9wSTro_iLvEpxW-0PEgdsFFB6bhut-eE-6GBknp4zWIUstf8u95cj-TF8LVsAAq06PaJWs_bmJj2GnIp4OK2kr2IY29wcrxEry-nhDEUDLx2ru0T0tuT48W3gsk0HEzoSqEtR2qx6fXEPIjTClOnx_YH6ivWb9lwiF4w2GyLKoy0EskdalniFGMd6eUZ4k_o8ADub_w9dCyNOyHgTggsxfGx841-TpRGV55A-OnybMW0uWeduLsr5Dsa-XCLSCdJ2Z4MX7zmr9NZVZcdOp4AZS-vypJeP6zsBJxz11uClyK-qw-ji54gK1F4FR2IXG5zHX7GYX-n6--naM6jxnIWdEvXqVjhKZgA4Y9jGiirWgMF4MY3ZbpW9aN2EZyzGUZ43BYIZZ5BHPRHvUtn6-D_w7X_r6I_LWP3jjLCkAE-afRIxfSjGATFb9f_zsMXWCBCs7cfR4qfaCjh-UqXEx4kjq2vsi2vBHkNODwA08JtD8KoQ3liD7FROLgzEQnnt1S9M9LHIiOSL-D7yJ01g0jwXCuLatwyDhPdCHgJbmkOqDzeRNn2heVdxKxPd--bE5NBj8craO6PPhdpIniXtGAHsTrUD3Z_XB3eUNJtJOA5AOX1b-QYwBez_jGyrGgiMumTxb3wMuTS_z_GGT70SiRnXjSPvOKAkvYlZ7CcR9iYky4I2bMevpxvFgjbN2LqtL5yF2z3G_9Cdr8INlhAUX8ygCjOswNql1jw2xeJzjSFa0-Iu6HkoTYNk8KL2oZIlP331yDR_dtC552j8YC6", "id": "rs_034268a3852e0919016a07bb1fc560819aa853cd47fd383a2c", "summary": [ { "type": "summary_text", "text": "**Verifying tool usage**\n\nI need to test the image generation tool, so I’ll use the small version. But first, it’s important to check its activation — I might face issues if it's not enabled. My plan is to call it with a simple prompt to create an image. Ensuring everything is set up correctly is key before I proceed, so I’ll verify the tool’s status first. This should help avoid any potential hiccups!" } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"image\": \"/home/ubuntu/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260516_003246_f7d8f09a.png\", \"model\": \"gpt-image-2-medium\", \"prompt\": \"A tiny clean test image: the word OK in black on a plain white background, minimal, no decoration.\", \"aspect_ratio\": \"square\", \"provider\": \"openai-codex\", \"size\": \"1024x1024\", \"quality\": \"medium\"}", "tool_call_id": "call_jhQU0wvD9iGdJf1DKrcuy2Xn" }, { "role": "assistant", "content": "Listo. Ya está activo y probado.\n\n- `image_gen` estaba habilitado.\n- Backend disponible: `openai-codex`\n- Configuré:\n - `image_gen.provider = openai-codex`\n - `image_gen.model = gpt-image-2-medium`\n- Verifiqué generación real con `gpt-image-2` vía Codex OAuth.\n- Salida OK: `/home/ubuntu/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260516_003246_f7d8f09a.png`\n\nPara edits: mandame la imagen y decime qué querés cambiar. Si querés iterar rápido puedo bajarlo a `gpt-image-2-low`; para resultado final usamos `medium` o `high`.", "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Listo. Ya está activo y probado.\n\n- `image_gen` estaba habilitado.\n- Backend disponible: `openai-codex`\n- Configuré:\n - `image_gen.provider = openai-codex`\n - `image_gen.model = gpt-image-2-medium`\n- Verifiqué generación real con `gpt-image-2` vía Codex OAuth.\n- Salida OK: `/home/ubuntu/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260516_003246_f7d8f09a.png`\n\nPara edits: mandame la imagen y decime qué querés cambiar. Si querés iterar rápido puedo bajarlo a `gpt-image-2-low`; para resultado final usamos `medium` o `high`." } ], "id": "msg_034268a3852e0919016a07bb31b33c819a9d9971126e3052b9", "phase": "final_answer" } ], "finish_reason": "stop" }, { "role": "user", "content": "[The user sent an image~ Here's what I can see:\nHere is a detailed description of the image:\n\n**Overall Impression:**\nThe image depicts a brightly lit living room that appears to be in the process of being moved into or organized. There are signs of unpacking and general clutter, but the space has a clean and modern aesthetic.\n\n**Layout and Architecture:**\n* **Walls:** The walls are painted a clean, bright white.\n* **Ceiling:** The ceiling is also white and features a modern, square-shaped light fixture with visible circular vents.\n* **Floor:** The floor is a dark wood laminate or hardwood.\n* **Window:** A window is visible on the left side of the image, covered by light-colored curtains.\n* **Shelf:** A wooden shelf is mounted on the wall to the right, holding small decorative items and plants.\n\n**Furniture and Decor:**\n* **Sofa:** A large, sectional sofa dominates the right side of the image. It is light gray or beige and covered with an assortment of pillows in various patterns and textures. A beige throw blanket is draped over part of the sofa.\n* **Coffee Table:** A light-colored, oval-shaped coffee table sits in front of the sofa. It has a slatted base and holds a laptop, a smartphone, and other small items.\n* **Plants:** Several potted plants are scattered throughout the room. A large fiddle-leaf fig is in a gray pot near the window, and a smaller palm is in a black pot.\n* **Boxes:** Several cardboard boxes are stacked on the sofa, suggesting unpacking.\n* **Chair:** A wooden chair is visible on the left side of the image, partially obscured by a large black trash bag.\n* **Shelf Decor:** The shelf on the wall holds small picture frames, a candle, and a small potted plant.\n\n**Objects and Clutter:**\n* **Laptop:** A black laptop is open on the coffee table.\n* **Smartphone:** A smartphone is also on the coffee table.\n* **Headphones:** A pair of black headphones is on top of the boxes on the sofa.\n* **Trash Bag:** A large black trash bag is near the chair, likely containing packing materials.\n* **Shopping Bag:** A green shopping bag is on the floor near the chair.\n* **Water Bottle:** A clear water bottle is on the floor near the coffee table.\n* **Red Container:** A red plastic container is on the floor near the coffee table.\n* **Cables:** Various cables and cords are visible on the floor, indicating electronic devices.\n\n**Colors:**\n* **Dominant Colors:** White, light gray, beige, and dark brown.\n* **Accent Colors:** Green (from the plants and shopping bag), black (from the laptop, headphones, and trash bag), and red (from the container).\n\n**Overall Impression:**\nThe room has a bright and airy feel, but it is also somewhat cluttered due to the unpacking process. The furniture is modern and comfortable, and the plants add a touch of nature to the space. The overall impression is of a room in transition, but with a lot of potential.]\n[If you need a closer look, use vision_analyze with image_url: /home/ubuntu/.hermes/image_cache/img_22336c28cebc.jpeg ~]\n\n[nachlakes] Primero que nada debemos establecer el contexto. Primero, Te muestro la pared que tengo en el living. Esta pared mide 255cm de alto (del piso al techo) x 310cm de ancho (desde el marco de la ventana a la pared) (medidas aproximadas). Ahora, tené en cuenta estas 11 Varillas qué compramos https://www.mercadolibre.com.ar/up/MLAU3900266140?pdp_filters=item_id:MLA3171281564&matt_tool=89488245#origin=share&sid=share&wid=MLA3171281564&action=copy. Necesito que primero que nada calcules al detalle perfectamente usando el máximo de tu inteligencia para saber cuales van a ser las medidas finales de las 11 Varillas instaladas. Nuestra idea no es pegarlas a la pared, sino comprar \"two by two's\" en el easy. Cosa de poder armar un frame de madera, qué tenga cierta distancia del borde de las Varillas (revestimiento), para poder instalar una cinta Led y poder tener luz indirecta. De tu parte necesito que processes todo esto integralmente. Calcula absolutamente todo lo mencionado, las maderas qué necesitamos del easy, fijate si las podemos comprar online, sino necesito que armes una shopping list para cuando vayamos nosotros mañana, incluyendo la cinta Led y necesito obvio que también hagas el cálculo de que tan lejos del borde necesita la luz estar para tener una luz bella saliendo. Una vez tengas todo esto, pasa la foto por imagen 2 de open Ai y genera la imagen de todo el shopping list into con una instructions list sobre como deberíamos hacer la instalación del frame de madera, de la tira Led, y de como pegar los paneles unos con otros y contra Cúa tos puntos de contacto con el frame detrás. Básicamente una lógica de pe a pa de principio a fin. Integral. Gracias. Avisame si podes comprar todo directamente en su sitio, asumi qué no tengo ni una herramienta." }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8FBhOqV8kA_FLGXCN97m0M2Pkuvk2c6SYpGuFxcNqoZDv7DVyfjtczO0e0VSaVjSqnwsyS3FDB_iNng2FFin_YniVWr3DXqaTC6qerkmfV30NWdrILSPwXUjbbIJYap7s8aAKVk1rn3UD8UECYmCbTdCxHQ-_Y2CzN1ZE0KJ3aZw_dAoNGzU1yIbG6LsWt45TZUwD0rY-9xHCAUzqtlV62fUmJz3mpO7vrukEbqLgFM4NgWocVlGUOFIAXyPSQAbOFur3NPQ0s6nV_TdvT3qlwKkGjDsVWC3AC4fTzSweBN_qaq0lZJF8MLfWmtefXJKR85apaO81k49V5oxYhvEqeslw68DBYuhvj7T2sGCY5FkZYAKNNxN2KGMhOm4TZwXeJ7_dHEo4WggPcVxUtRqn-HnnVO5eycy2mipKg24c4uo1sI5gCEdzLEhQ-6ZoidYGp_vKN_XTQh1GklZ2xbfM5YmSuS3Zytmnp-tjNI8Kau1BjTmvH1rOLtvKjrjED-sC8j3hSOoL8sSsu44dqPw6Bl7DVaTEwa7EigiOGbm_EpxQo0MuYbpMt3a7nDmEppZm1PcYwTAPdXN_JRgVVzEs1fzckrAwEBSqH8UOk_QFfzivOHObeQHWof7jSqIzG2dUOd7OHxnSlilC5Me9_XM-s4JUKj2chXFL029P4sx5eEM1ljsntKiSdiYY-TOky7oWmjvcryVUUvl1kmEIgC-Z9OickRrlsRTeI20r80525rUwb7itllTakyA17XLWTy00Pp6dzM_dKwjetJ5YjjQuzJTKyFoiq2OGmlJV8Zwbz-OEqW5iDU3ZuYgfHlh-aC65aOTCdQcMJ95VRRhNkkvXjuwxuTgzN5Mi1x_BmanZsZj2KmbEYr3pqZW_2l8rKW2FioI1depAwrSOLQoJWHXIOTi8KCu_fhTruxfvYEaLuExJ-YaRfeBPyz418E82--nWlR9aKP6MR0oXZEl3XWffkQpFu-pqfuQ4EdN6vLnvW6rERbaFYbVlhZYb2hGOQ06QteP2-1s_MYYvxhMbqYBzQ9Im3JARSRhu4Mke5bBtTRWcmRa6mer6_G62VZyM1E7LSX8M_1KedkuI8HkVZmq8eN9DfUU7eI1VnZ5pvJfvRILhzunw1TziuWFgxvBtz1nmr8S9ibXpP0zQcl87Xr1wWA0CraRM3SIWH-Mmita85ix5XKBNHO9TkTaL3zeIq7oru6FTDPcK9QjcR_FOjcTvGgbJvbcQthUsohd7o1fSgTElxiBgBo8fa0Z2YKRcZqYVoL7YYEvTexdFPnGsjyj1B7UGO0up6uqoNqPwhgNsm-6YMkoUIohkG4pMu940578YJc4HQu7_a-6gIEIwqp31Ltv_NW3pj54AY0Q-ouRJH8q1by0trgA015mIRwKNpF4AWw7HL8maO42KMw0sagobeg9hbHhM_7DpG6Hr-e1bf2VevOZNrM3RDyQwV9XYa1Q34VtT2PRyhDdNYzrTI4lwPgMtG5O8PVtqU0kSPZLVQ1K316vDw5NQtRiM7xi4f4G7gelupIX0xJ_HUg8kUOBF6ioUIcWZ3nyM6R6Jg6CZf_uXuV8qcHkIhhmoqgvU2IWhvBc4y5JgM5Rm5IxoVPhd9Hr16jtmr7HlyjwWJjS05_2w-kVa-vgEyY2aNQ3kEShRI9QcGBe4IqdtSt7fcUdogvIUEOFQ8aT8eFoGGBO1Q9impgNouw3Jti-7QTsAUSb4np2I5FkOHpDqILxQT7Rag-1l_NTJ14XSfBVzp9Uf1nAY7rwaYl8wNtpTIjR9BvSQMjzzJFMvl_2SxQnT5JXhxm0Dugs7EHduwsOhAuRzkfwfGhoRfcpPGV9q_MyOVdpSfM_tVCFRtefAxi2fh_gyctngAtN-8y3LODJUE5TkfSK6gmEmKo1tqRd8ykcE_MGM6u_VPSHhzyH2hJRXYWSyQa7Q4XtheXykr6MDSL4YlQ34Z1L6jZsgwGzf8UuixSecRcUpk_U3aG-WnionZU7w3No_zMt5fe8a0MYLvrQLdT_nTv9L4ESMz4mGk328vtyct4F_BZQJtZUUIQacbSt89VRxz2m7wKYrcyERAoxpxmfmvDrH74QNK9HV89r3f6bml5ifDZbuMQgWqrW13wZ4yZFic318Q2Yu1vpSJd9BfNeEQJbGzu4Uf4bU9sjXEu0eM-Nou0egW6qa3hjXtcSbeuqku3l1G2akWse6iZNcNkOL_Ox79pdNI17GqcXiXYiiHx14MHhNl-uuRUA2Pv_4P7TRiQAaLFLsJmQuAfzCYn4RIZtyBJbsCL_JCvvLzVj6CLS-TeAepL8Wf_B-yLG4xG7yNqGQdwUlvO2SzVb8FwRYOKpGNmyRTFi1RypPC6gje9Rx_9FU5oumwz9TNd8C9goYY6QBNRSSFtBGYGobz9XXITp_NLzxMajifsWPx2ickXyViT3r5O9xSmaeFzQEWndz8dFuD6SOS4abdJ1lh4DZJhQagPOLO7-TW30encnyeiOUqJbpbPzWPjGKrderZ76LiUrudpz49Aw9CjRLXD6UiQd9dmsSI4-7II-JrkMSjCbI8wK1kpS_0xAr2MoCAMO7mf72rEzBN1RLD51XWrsyI_tpywfD--1wCZGOizkru2593Tsxy01WknkNWprW6KBxD663A3JbFeGk452f75KbXer_O3Zh6fso4aAP8ygmdK7tad-ZDWnVOm9g4LpW_0JPU7dnMDRQ4iBumi5ZporIqVE_KwEdmeGSqpnvOO9AKE3I-QB-PJbHUPwuzQLMurG-hu_-alf4zAD7RELNoVML3WzW-oauQMlFUv0ZqZLzilfH3mtqY_E1eAf_9GF7G67IKC08j1Pi-5m2KizPGcadocyogH-f-v6W-Rqp_QfxSYlVR-ZctlN54B9umbCbZ3EV2NwkMShXHkT0SGBRheqEpmzmkP5ItQRkQNzhRKkTM28Ksdy2eNS5mqt2kOQyCFL9CfCuBpUj0Zc9nd0tLB2C1GlRdVaUo9lgji5CSWhZYy9UC9UMM6DgMMrAVJWsk6Y0ykEiou2YAHsl5C0vTD2OCGiw9wzSS5K762irkjf6-_LXc3pRtAt6PHUbK3m3nhms07wsYAyzt9CKyOVURo4S54zT0Sk_eGolthsaHWSFXfxbDNx_yUTW90fJMLV9g8Dab0FOjETSu29Kj8_ChxKdbZalLJKy2cbAIox0zL_3HOBfTvbZr0QGYRHAd4OprZyjM6f4aehwvX_PVZ_ZHvTnPWRH2x5WWFOP547UxMu9zETX6ZsBNqRxivZaIJL5PXsOe5Tqr9jIeLQHMVBZI9eGm-KzvZ8QEIz8k8Hl308xVT2IxFYY1f2nYZE4C3eF4bTAyFuG6RV9IlFN22V_B3SFOMzjg-tNsQFhemCO9MCfVIYdiET2Ky2aDObvLWg-5JAGRxCQb0ym7Fu20jWt05lCsgEOmA7dPNILRPLqsp8F0r28uHMqHdNWpwwlo1FH4aLBcVEqzYmy7Bvz51KAMeuD5g8bcwh-oVILZme9cLH9lXKX1p39g0OINnvJ2N1fFzNou5I2Tya8u8wmnUxhar1T03aTf_dwuyw4UGzJbk24rBt4obAtAHUaFlp-Q0UV0wjDfnIg0VO0B1k51AO0qXN-JsL8L8TLBRed0g7RY7yseKLtGMau3X1PU9cZh8Z6BFg7HkRl6IbPCnM8_GwcLvy_Q3VVYfq82-s3qh5WvITbDogTlhklt_nytlc26epuSQxh8lUHswpE-s8DYFEonhoGBOt_v4v88xj-qIo3l03WHpcsnxIMvoi8LOXhHqVTvk4Z8Df73ZqeJs7KMgN69pmcOH-TGRwvanVCN7Q-DgABIVTaJ-IBMeQOn28lUUoVAG6osp_j9VW4OOrXjvg78dCoZpymUYzUGYZl4GsvHKETk8UMQCLdBgsynK_SNPTOBf-BNMHok54rQxR3Q9lVjNdK-hCEZhKJrTpJmYQc59rlmJRcATE8p6ib__eri780q0QzA5VcXBcrltXI2014FW-aRGclFLe50y_bMIf7Wd0wqvC4c6O07FREi4SyKFzsY0lgHNvvhzobQ_mLbn6lD-BhBxbTym64mrwqWpDJrxAilVIlc749uLToNwnFePn5X5rzrfdNcyYIWvPCNMsIgip6I76QvruF1QcyqJWTt_xlKGipqFMjL9ROHs08XpYC1DZORCjAmFyFv1qBPxSOkYFVo4lKpeULuhX68V_m9ND67A", "id": "rs_034268a3852e0919016a07c1355290819a9e5a2fecfa60a839", "summary": [] } ], "tool_calls": [ { "id": "call_jJBZCri2FOGNcpWARy9VQQHO", "call_id": "call_jJBZCri2FOGNcpWARy9VQQHO", "response_item_id": "fc_034268a3852e0919016a07c14104cc819abb0d270f1e8c5f5b", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"claude-design\"}" } } ] }, { "role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"claude-design\", \"description\": \"Design one-off HTML artifacts (landing, deck, prototype).\", \"tags\": [\"design\", \"html\", \"prototype\", \"ux\", \"ui\", \"creative\", \"artifact\", \"deck\", \"motion\", \"design-system\"], \"related_skills\": [\"design-md\", \"popular-web-designs\", \"excalidraw\", \"architecture-diagram\"], \"content\": \"---\\nname: claude-design\\ndescription: Design one-off HTML artifacts (landing, deck, prototype).\\nversion: 1.0.0\\nauthor: BadTechBandit\\nlicense: MIT\\nplatforms: [linux, macos, windows]\\nmetadata:\\n hermes:\\n tags: [design, html, prototype, ux, ui, creative, artifact, deck, motion, design-system]\\n related_skills: [design-md, popular-web-designs, excalidraw, architecture-diagram]\\n---\\n\\n# Claude Design for CLI/API Agents\\n\\nUse this skill when the user asks for design work that would normally fit Claude Design, but the agent is running in a CLI/API environment instead of the hosted Claude Design web UI.\\n\\nThe goal is to preserve Claude Design's useful design behavior and taste while removing hosted-tool plumbing that does not exist in normal agent environments.\\n\\n**Before starting, check for other web-design skills like `popular-web-designs` (ready-to-paste design systems for Stripe, Linear, Vercel, Notion, etc.) and `design-md` (Google's DESIGN.md token spec format).** If the user wants a known brand's look, load `popular-web-designs` alongside this one and let it supply the visual vocabulary. If the deliverable is a token spec file rather than a rendered artifact, use `design-md` instead. Full decision table below.\\n\\n## When To Use This Skill vs `popular-web-designs` vs `design-md`\\n\\nHermes has three design-related skills under `skills/creative/`. They do different jobs — load the right one (or combine them):\\n\\n| Skill | What it gives you | Use when the user wants... |\\n|---|---|---|\\n| **claude-design** (this one) | Design *process and taste* — how to scope a brief, gather context, produce variants, verify a local HTML artifact, avoid AI-design slop | a from-scratch designed artifact (landing page, prototype, deck, component lab, motion study) with no specific brand or token system dictated |\\n| **popular-web-designs** | 54 ready-to-paste design systems — exact colors, typography, components, CSS values for sites like Stripe, Linear, Vercel, Notion, Airbnb | \\\"make it look like Stripe / Linear / Vercel\\\", a page styled after a known brand, or a visual starting point pulled from a real product |\\n| **design-md** | Google's DESIGN.md spec format — author/validate/diff/export design-token files, WCAG contrast checking, Tailwind/DTCG export | a formal, persistent, machine-readable design-system *spec file* (tokens + rationale) that lives in a repo and gets consumed by agents over time |\\n\\nRule of thumb:\\n\\n- **Process + taste, one-off artifact** → claude-design\\n- **Match a known brand's look** → popular-web-designs (and let claude-design drive the process)\\n- **Author the tokens spec itself** → design-md\\n\\nThese compose: use `popular-web-designs` for the visual vocabulary, `claude-design` for how to turn a brief into a thoughtful local HTML file, and `design-md` when the output is the token file rather than a rendered artifact.\\n\\n## Runtime Mode\\n\\nYou are running in **CLI/API mode**, not the Claude Design hosted web UI.\\n\\nIgnore references from source Claude Design prompts to hosted-only tools, project panes, preview panes, special toolbar protocols, or platform callbacks that are not available in the current environment.\\n\\nExamples of hosted-tool concepts to ignore or remap:\\n\\n- `done()`\\n- `fork_verifier_agent()`\\n- `questions_v2()`\\n- `copy_starter_component()`\\n- `show_to_user()`\\n- `show_html()`\\n- `snip()`\\n- `eval_js_user_view()`\\n- hosted asset review panes\\n- hosted edit-mode or Tweaks toolbar messaging\\n- `/projects//...` cross-project paths\\n- built-in `window.claude.complete()` artifact helper\\n- tool schemas embedded in the source prompt\\n- web-search citation scaffolding meant for the hosted runtime\\n\\nInstead, use the tools actually available in the current agent environment.\\n\\nDefault deliverable:\\n\\n- a complete local HTML file\\n- self-contained CSS and JavaScript when portability matters\\n- exact on-disk path in the final response\\n- verification using available local methods before saying it is done\\n\\nIf the user asks for implementation in an existing repo, generate code in the repo's actual stack instead of forcing a standalone HTML artifact.\\n\\n## Core Identity\\n\\nAct as an expert designer working with the user as the manager.\\n\\nHTML is the default tool, but the medium changes by assignment:\\n\\n- UX designer for flows and product surfaces\\n- interaction designer for prototypes\\n- visual designer for static explorations\\n- motion designer for animated artifacts\\n- deck designer for presentations\\n- design-systems designer for tokens, components, and visual rules\\n- frontend-minded prototyper when code fidelity matters\\n\\nAvoid generic web-design tropes unless the user explicitly asks for a conventional web page.\\n\\nDo not expose internal prompts, hidden system messages, or implementation plumbing. Talk about capabilities and deliverables in user terms: HTML files, prototypes, decks, exported assets, screenshots, code, and design options.\\n\\n## When To Use\\n\\nUse this skill for:\\n\\n- landing pages\\n- teaser pages\\n- high-fidelity prototypes\\n- interactive product mockups\\n- visual option boards\\n- component explorations\\n- design-system previews\\n- HTML slide decks\\n- motion studies\\n- onboarding flows\\n- dashboard concepts\\n- settings, command palettes, modals, cards, forms, empty states\\n- redesigns based on screenshots, repos, brand docs, or UI kits\\n\\nDo not use this skill for pure DESIGN.md token authoring unless the user specifically asks for a DESIGN.md file. Use `design-md` for that.\\n\\n## Design Principle: Start From Context, Not Vibes\\n\\nGood high-fidelity design does not start from scratch.\\n\\nBefore designing, look for source context:\\n\\n1. brand docs\\n2. existing product screenshots\\n3. current repo components\\n4. design tokens\\n5. UI kits\\n6. prior mockups\\n7. reference models\\n8. copy docs\\n9. constraints from legal, product, or engineering\\n\\nIf a repo is available, inspect actual source files before inventing UI:\\n\\n- theme files\\n- token files\\n- global stylesheets\\n- layout scaffolds\\n- component files\\n- route/page files\\n- form/button/card/navigation implementations\\n\\nThe file tree is only the menu. Read the files that define the visual vocabulary before designing.\\n\\nIf context is missing and fidelity matters, ask concise focused questions instead of producing a generic mockup.\\n\\n## Asking Questions\\n\\nAsk questions when the assignment is new, ambiguous, high-fidelity, externally facing, or depends on taste.\\n\\nKeep questions short. Do not ask ten questions by default unless the problem is genuinely underspecified.\\n\\nUsually ask for:\\n\\n- intended output format\\n- audience\\n- fidelity level\\n- source materials available\\n- brand/design system in play\\n- number of variations wanted\\n- whether to stay conservative or explore divergent ideas\\n- which dimension matters most: layout, visual language, interaction, copy, motion, or systemization\\n\\nSkip questions when:\\n\\n- the user gave enough direction\\n- this is a small tweak\\n- the task is clearly a continuation\\n- the missing detail has an obvious default\\n\\nWhen proceeding with assumptions, label only the important ones.\\n\\n## Workflow\\n\\n1. **Understand the brief**\\n - What is being designed?\\n - Who is it for?\\n - What artifact should exist at the end?\\n - What constraints are locked?\\n\\n2. **Gather context**\\n - Read supplied docs, screenshots, repo files, or design assets.\\n - Identify the visual vocabulary before writing code.\\n\\n3. **Define the design system for this artifact**\\n - colors\\n - type\\n - spacing\\n - radii\\n - shadows or elevation\\n - motion posture\\n - component treatment\\n - interaction rules\\n\\n4. **Choose the right format**\\n - Static visual comparison: one HTML canvas with options side by side.\\n - Interaction/flow: clickable prototype.\\n - Presentation: fixed-size HTML deck with slide navigation.\\n - Component exploration: component lab with variants.\\n - Motion: timeline or state-based animation.\\n\\n5. **Build the artifact**\\n - Prefer a single self-contained HTML file unless the task calls for a repo implementation.\\n - Preserve prior versions for major revisions.\\n - Avoid unnecessary dependencies.\\n\\n6. **Verify**\\n - Confirm files exist.\\n - Run any available syntax/static checks.\\n - If browser tools are available, open the file and check console errors.\\n - If visual fidelity matters and screenshot tools are available, inspect at least the primary viewport.\\n\\n7. **Report briefly**\\n - exact file path\\n - what was created\\n - caveats\\n - next decision or next iteration\\n\\n## Artifact Format Rules\\n\\nDefault to local files.\\n\\nFor standalone artifacts:\\n\\n- create a descriptive filename, e.g. `Landing Page.html`, `Command Palette Prototype.html`, `Design System Board.html`\\n- embed CSS in `\\n\\n\\n
\\n
\\n
\\n

Panel varillado flotante
con halo LED indirecto

\\n
Living: pared 255 cm alto × 310 cm ancho. Producto Holzboden EPS: 11 varillas de 11 cm × 250 cm × 11 mm.
\\n
\\n
Plan de corte + compras + instalación
\\n
\\n\\n
\\n
\\n

Medidas finales

\\n
121 × 250 cm visible
\\n
11 varillas lado a lado, sin cortar altura.
\\n
\\n
5,5 cm
salida total desde pared: 4,4 cm frame + 1,1 cm panel
\\n
94,5 cm
margen blanco a cada lado si va centrado
\\n
2,5 cm
margen arriba y abajo si va centrado en altura
\\n
\\n

Frame oculto recomendado

\\n
Inset LED/frame: 5 cm desde cada borde visible
Frame exterior: 110,8 × 240 cm
Listón real: 2×2 ≈ 4,4 × 4,4 cm
Horizontales: 110,8 - 4,4 - 4,4 = 102 cm
\\n
\\n\\n
\\n

Corte de madera 2×2

\\n
\\n
2×
240 cm
verticales laterales
\\n
5×
102 cm
travesaños: arriba, abajo, 3 medios
\\n
5×
listones 2×2×2,44 m
alcanza con sobrantes
\\n
55
puntos de pegado
11 paneles × 5 travesaños
\\n
\\n

LED

\\n
Perímetro del frame: 2×(110,8 + 240) = 701,6 cm
Comprar 2 tiras de 5 m. Usar 3,51 m por lado.
Sobran aprox. 1,49 m por tira.
\\n
\\n
\\n\\n
\\n
\\n

Ubicación en pared

\\n
\\n
\\n
VENTANA
\\n
\\n
\\n
pared 310 cm
\\n
255 cm
\\n
panel 121 cm
\\n
250 cm
\\n
94,5 cm
\\n
94,5 cm
\\n
\\n
Naranja = panel visible. Marrón = frame oculto 5 cm adentro. Glow = LED cálido 2700K/3000K.
\\n
\\n
\\n\\n
\\n

Lógica de luz

\\n
    \\n
  1. Separación de pared: 4,4 cm por el 2×2. Esto ya da halo suave.
    2. \\n
  2. LED a 5 cm del borde visible, pegado al canto exterior del frame, no al frente.
    3. \\n
  3. La luz debe mirar hacia afuera / pared, nunca hacia el living.
    4. \\n
  4. Usar luz cálida 2700–3000K. Evitar fría/RGB para este living.
    5. \\n
  5. Probar encendida antes de pegar los paneles.
    6. \\n
\\n
No encerrar la fuente contra EPS. Dejarla accesible y ventilada detrás/abajo del panel o fuera del panel.
\\n
\\n
\\n\\n
\\n

Shopping list esencial

\\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n
Cant.Qué comprarNotas
5Tirante/Listón pino cepillado 2×2×2,44 mPedir cortes: 2×240 cm + 5×102 cm. Si no cortan, comprar serrucho/caja inglete.
2Tira LED interior 5 m luz cálida 24 WUsar 3,51 m por lado para halo completo; sobran ~1,49 m por tira.
2Fuente para tira LED 25 WUna fuente por cada tira de 5 m/24 W. Más simple que buscar fuente grande.
2Sellador/adhesivo poliuretano o MS, color blanco/transparentePara pegar panel EPS al frame. Evitar adhesivos con solvente.
1Pistola aplicadora para cartuchoNecesaria para sellador PU/MS.
10–12Tarugos + tornillos largos para paredPara 2×2: pedir S8/S10 con tornillo 5×80 / 6×90. Los 5×45 quedan cortos salvo que avellanes.
16Tornillos madera 4×50 / 4×60Para armar el frame entre listones.
1Taladro percutor + mecha pared 8/10 mm + punta atornillarSi no tenés: comprar, alquilar o pedir prestado. Sin esto no fijás frame.
1Nivel 60 cm + cinta métrica + lápizPara centrar, plomar y marcar.
1Serrucho/caja inglete o servicio de cortesSólo si Easy no corta las maderas.
1Zapatilla/enchufe accesible o smart plugPara encender/apagar las 2 fuentes juntas.
\\n
\\n\\n
\\n
\\n

Instalación: de pe a pa

\\n
    \\n
  1. Vaciar la zona y marcar centro de pared: 155 cm desde marco de ventana.
    2. \\n
  2. Marcar panel visible: de 94,5 a 215,5 cm horizontal; de 2,5 a 252,5 cm vertical.
    3. \\n
  3. Marcar frame: de 99,5 a 210,3 cm horizontal; de 7,5 a 247,5 cm vertical.
    4. \\n
  4. Armar frame en piso: 2 verticales 240 + 5 travesaños 102. Pre-perforar madera.
    5. \\n
  5. Presentar frame, nivelar y fijar a pared con 10 anclajes aprox.
    6. \\n
  6. Pegar LED en canto exterior del frame, 2 circuitos simétricos. Probar 15 min.
    7. \\n
  7. Pegar paneles uno por uno: 5 contactos por varilla sobre travesaños + unión lateral fina.
    8. \\n
  8. Encintar/sujetar 24 h. Luego retirar cintas y dejar fuente accesible.
    9. \\n
\\n
\\n
\\n

Puntos delicados

\\n
    \\n
  1. Confirmar tipo de pared: mampostería vs durlock. En durlock cambian los anclajes.
    2. \\n
  2. No usar adhesivo solventado sobre EPS: puede derretir el panel.
    3. \\n
  3. No pegar paneles antes de probar LED y fuentes.
    4. \\n
  4. No dejar fuente enterrada sin ventilación.
    5. \\n
  5. Si hay zócalo, el panel puede flotar delante gracias al frame de 4,4 cm.
    6. \\n
  6. Si Easy no corta exacto, 102 cm en vez de 102,2 cm está perfecto.
    7. \\n
\\n
\\n
\\n\\n
Cálculo base: Holzboden EPS 11 cm × 250 cm × 11 mm; pared 310 cm × 255 cm; frame oculto 2×2 real ≈ 44 mm.
\\n
\\n\\n\\n\"}" } } ] }, { "role": "tool", "name": "write_file", "content": "{\"bytes_written\": 11478, \"dirs_created\": true, \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .html files\"}}", "tool_call_id": "call_CBOPknWxgfVfMF7twzok13us" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_JMxScLDXGtoeCbjV6iN0kPwB", "call_id": "call_JMxScLDXGtoeCbjV6iN0kPwB", "response_item_id": "fc_034268a3852e0919016a07c2e51988819a83f1aeadd6a675cc", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"chromium --headless --no-sandbox --disable-gpu --window-size=1600,2450 --screenshot=/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png file:///home/ubuntu/.hermes/artifacts/living-panel-installation-plan.html && file /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\",\"timeout\":120,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"(living-panel-installation-plan.html:972254): dbind-WARNING **: 01:05:45.130: AT-SPI: Error retrieving accessibility bus address: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.18\\\" (uid=1001 pid=972254 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.a11y.Bus\\\" member=\\\"GetAddress\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.a11y.Bus\\\" (bus)\\n[972254:972254:0516/010545.257702:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.17\\\" (uid=1001 pid=972254 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[972254:972254:0516/010545.258871:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.17\\\" (uid=1001 pid=972254 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[972254:972254:0516/010545.277144:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.Properties.GetAll: object_path= /org/freedesktop/UPower/devices/DisplayDevice: org.freedesktop.DBus.Error.ServiceUnknown: The name org.freedesktop.UPower was not provided by any .service files\\n[972254:972349:0516/010545.717557:ERROR:components/headless/command_handler/headless_command_handler.cc:265] Failed to write file /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png: Permission denied (13)\\n/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png: cannot open `/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png' (No such file or directory)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_JMxScLDXGtoeCbjV6iN0kPwB" }, { "role": "assistant", "content": "", "reasoning": "**Troubleshooting file access**\n\nI'm encountering an exit code 0, which usually indicates success, but I'm getting a permission denied error. It seems there's no actual file existing where I thought. There might be an issue with Snap and AppArmor not allowing access to a hidden path. I probably need to write files to /tmp first, then move them afterwards. I'll need to make sure I adjust my approach based on this detail to get it working properly!", "finish_reason": "tool_calls", "reasoning_content": "**Troubleshooting file access**\n\nI'm encountering an exit code 0, which usually indicates success, but I'm getting a permission denied error. It seems there's no actual file existing where I thought. There might be an issue with Snap and AppArmor not allowing access to a hidden path. I probably need to write files to /tmp first, then move them afterwards. I'll need to make sure I adjust my approach based on this detail to get it working properly!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8LxJ0muoe-BuwCtRCOI5hjtAcrgdhUmjaD1E5tIEBqmcNggy0vuDaDxuKeMmDIbMDZvVNI2issY_KozdvR_tLOOyCBSMUPXRDDtTle38ZAaosuMwz9xm5dhU3nMsSfpNL0ZupBAfLIgG0ZFIpzWWT1jW-XjqWbn1yMGvha_d6bcRYq_OPZe2K7AF0TqkTljOlA8h6DcoOjy5ELmcDoice8Z5r1ygsMD1lyJ6f8Zi1xomYozOC1kekW8oI7Kkm5z2syk_q1aNZ4VYKXSoEsU0gX3ZBzwS-xWdeGS1BBpK2-4boiWRjMj4GeAP-WudA4LGw9l4EnjsbrMpGyx0GEo6guPOwRhDMpGRZsYCpy3rgQ2fM995Kzygghmt1T6cZ4VORtxDNDL8uMX4sMV0r7J418gZYedTpL79QlcSHaV3QHUdVFsZu0CcZFZFsm6ZbE7OnqdkjaIX4RkdOuqUoPsh-voblqHrkteDSPpcCVQa9A94G6MvAOU4ALr22B2WaqN15DtgxOeWtem2Zwvxfv6e9Nb9aP1QbQkQOmbcg4dCWMVfZofS80Sbc-YKs5frR_rluME1YM3n0-DkugbKbkHA9qhxJwr_mgc2jjpj5XF5joC_CAt9PRjx5IkugBHWtu8Er83xS8qPlpW-lsT7QC8w_Lge2aY1wWQ0ZSNkC-MnW1VPYUlHWUnkzww99v3qJsxOEgi9RjZWR4hx8ukoNnC-QYQvYKAb7cTTgjTkr9jVp_IDTKJwzOy7-ita9jK0ZQPzqhV_auMKM-bcXq98Zgdx4rodIe2SWERvyscG7Z-V9IsKHo0EuHCv2gLZrj0dlcgUsRNlWiZSoseZLvNQMRzjTumBSMqrNV3KBNyM8SkEqz1onFlMRMOiqq_l08XZUadzFDIGMW2NcrgP17K12zlW-kE5m80sFruHrBgRs2_5fVrShhmOQcGDLq4uPgkeXPol5yBsMEK9_UjyGCOKb76smfUp0UhbuA3mPSF9qy_nGXw5VRQuruqQGikebJUwJyAJnyqHAsWaxLtRGyGBlcQmW-mtUYVHYi1jVpx6RGPOZRhCBFv0avx7RrnR9l_EtfhnvJyo45yYQnQWzKgfd2669pCCgRssWpGJnP-WfQ3hxauLAI=", "id": "rs_034268a3852e0919016a07c2eca328819a8a1c52834c4682fb", "summary": [ { "type": "summary_text", "text": "**Troubleshooting file access**\n\nI'm encountering an exit code 0, which usually indicates success, but I'm getting a permission denied error. It seems there's no actual file existing where I thought. There might be an issue with Snap and AppArmor not allowing access to a hidden path. I probably need to write files to /tmp first, then move them afterwards. I'll need to make sure I adjust my approach based on this detail to get it working properly!" } ] } ], "tool_calls": [ { "id": "call_LZW3yrXH40XiQPWgcAYVA4ic", "call_id": "call_LZW3yrXH40XiQPWgcAYVA4ic", "response_item_id": "fc_034268a3852e0919016a07c2f1f458819abdc447422acbd60b", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"chromium --headless --no-sandbox --disable-gpu --window-size=1600,2450 --screenshot=/tmp/living-panel-installation-plan.png file:///home/ubuntu/.hermes/artifacts/living-panel-installation-plan.html >/tmp/chromelog 2>&1; cp /tmp/living-panel-installation-plan.png /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png; file /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png; tail -5 /tmp/chromelog\",\"timeout\":120,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"cp: cannot stat '/tmp/living-panel-installation-plan.png': No such file or directory\\n/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png: cannot open `/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png' (No such file or directory)\\n(living-panel-installation-plan.html:972502): dbind-WARNING **: 01:05:55.283: AT-SPI: Error retrieving accessibility bus address: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.21\\\" (uid=1001 pid=972502 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.a11y.Bus\\\" member=\\\"GetAddress\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.a11y.Bus\\\" (bus)\\n[972502:972502:0516/010555.363225:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.20\\\" (uid=1001 pid=972502 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[972502:972502:0516/010555.365578:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.20\\\" (uid=1001 pid=972502 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[972502:972502:0516/010555.375378:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.Properties.GetAll: object_path= /org/freedesktop/UPower/devices/DisplayDevice: org.freedesktop.DBus.Error.ServiceUnknown: The name org.freedesktop.UPower was not provided by any .service files\\n47221 bytes written to file /tmp/living-panel-installation-plan.png\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_LZW3yrXH40XiQPWgcAYVA4ic" }, { "role": "assistant", "content": "", "reasoning": "**Investigating command issues**\n\nI'm reassessing a command that didn't seem to execute properly. It wrote, but I think that the `cp` command may have run before Chromium could flush its data. I’m realizing the command's sequential nature should mean there’s no file in `cp`. Tail indicates it was written after, so maybe Chromium spawned asynchronously? I should wait a moment and then check the `/tmp` directory to see if the file appears there.", "finish_reason": "tool_calls", "reasoning_content": "**Investigating command issues**\n\nI'm reassessing a command that didn't seem to execute properly. It wrote, but I think that the `cp` command may have run before Chromium could flush its data. I’m realizing the command's sequential nature should mean there’s no file in `cp`. Tail indicates it was written after, so maybe Chromium spawned asynchronously? I should wait a moment and then check the `/tmp` directory to see if the file appears there.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8L6krOOf94FODstqXFS4rQkmAKsNuOBhv_XsENXYAjARkLAMz5m5NKjVeUPLc0IGgqerOmyM5yH50jirlEReHcKomUjGUbSY9T7tO_xyuVS_gHUHuGQ4K4ABh5VhoDTW5MTB-AOmz763NOzUiI_KEfU4PeahAXsvnMt-vKTudefDc2-MPnucF4lTONKTHm_uWnB3722YbZxytr-E08Rf_vifLouftfUH6nfrrFqABsU8e1dtrsdRXE_98cfKx7939-vvtWGuTnVHs7hTUmF64WKDUWHxEZirdjKJZY3JumigNRSHwiKzcmi4W98OfihhteQ2igY5CoU1LlMhRbSW-NEFfC_CI62mL_kiFfxzdrxbuaJ90COTB6fyQzWZ1gMZR1uipPM6fsy2wXjFMf5a6a5CNY2RAlOTnqrCld2AazGwsitSXfwZ_eEpMpI2betl0LHgGJsAgAHUQm4PkX_zDZYrWx2wwt5WXBnkpebFzS5KyRbqZu3NKyId_4Yd2EmWgZz3NSA_dkFo-X5YSTVrXyaViFomBhEXjAHwKc4-wD2MbBeatkdO0mlgdoUjZIGOigJxKRN3kh0sdrD3DUvMLChGcy96KEGW8zhUxh3LV3ZAA7nCtKsl6f2J8G0vAvtrPM7xrm0-ol0mzOaviPko6iDJGBnVt7AkUAqrDYo245kh2r0ARKPGCTHwfb95O8VJxmh6rN7b8hqJdAC8id9OEL8UHaAV1JhKA5S4H_wckDyP4GG1XrcZQdJTjmRV_9l6XouaR_jNG55JjDToJhbf1f0K09jojdqNKix1zQa4OPAyd8BsOFukKL-LnEOun6nBawr0UlHg7pGBtY2KG_QZI80cgENmWXZyMBA2oWaPck1XwaV2WMCged8D279_m3pV4qp9_n30MdExc01matTKaWoxW_QxlyEYfIFhgcBISxm9lBwIE4PZrN1YrrKOdKICjwtV0IREr23Nz72g1ug0LqE1q6dpZLhTo8kxj6Jdib-x6ulzAY-kNw-58hLIMTgVAnseoNaNzvM9tStVCtHySd9XvzLULhWkBTs1r0_OIw7oSBmEnIRHANbu9ma_cd2LJxAP8R0pFCtV8O5pJHZRXB1QdnO5R7Ah4gT0FK3ukTX7G_SIaZvmKcsuau8emyjigNnJxIBxC9mbYe5vqwPu2A5IA==", "id": "rs_034268a3852e0919016a07c2f6517c819a852f11a297192e01", "summary": [ { "type": "summary_text", "text": "**Investigating command issues**\n\nI'm reassessing a command that didn't seem to execute properly. It wrote, but I think that the `cp` command may have run before Chromium could flush its data. I’m realizing the command's sequential nature should mean there’s no file in `cp`. Tail indicates it was written after, so maybe Chromium spawned asynchronously? I should wait a moment and then check the `/tmp` directory to see if the file appears there." } ] } ], "tool_calls": [ { "id": "call_DHejVoAZAoS0k4Kx5uejwfhD", "call_id": "call_DHejVoAZAoS0k4Kx5uejwfhD", "response_item_id": "fc_034268a3852e0919016a07c2fa19a0819a9c34953df6fe32f8", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"sleep 1; file /tmp/living-panel-installation-plan.png; cp /tmp/living-panel-installation-plan.png /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png; file /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\",\"timeout\":20,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/tmp/living-panel-installation-plan.png: cannot open `/tmp/living-panel-installation-plan.png' (No such file or directory)\\ncp: cannot stat '/tmp/living-panel-installation-plan.png': No such file or directory\\n/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png: cannot open `/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png' (No such file or directory)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_DHejVoAZAoS0k4Kx5uejwfhD" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8MBhLV3fM8zYDUyzbKfa0SPEgVt5XH3sDEbxbqVif1P8FEnQvNU4K4JRhYhIO-2yleXKfsDd-Go-io3jVDJf_QxCx0WMCqBtmAPPwvRGKLAY7Ewh99PDX-hkkFOaCcNEeagyTS1ZIrOdR91iiP5lh2BIcjer0i9NEYW217T25w2xiZD-lxBb-1LBrNjV2r-dNdBVoHqJ1cwjKt8mpvn6xdjuovA42T9pNe9uqAoXYLOIyKzZGfuZP-iAudN7nTSi4HyZQ8deLUdN19WHH6c7B06FQvtdVm6rlgsibF2MVUgEV7vzvKFmjJD49PWRBYJ8_icZGhxRjzIg1zxBwFn1I1rL76zRVIXrGyz97XZK2CYdVUeWtSa6KP15T01il_R7z7DRdlZzLFPCK1QvPLjNp17hs9PN0M5G9z7aFar8Z_r8yEPtn-NxBC4_MAVzZlJiI7pPUrULcjsnUJoIPCuWE--D7pj-0VFTX7CpVPd2SvGMTakbVYjN_cnasKQGhrUfBL75N1Kn5ROqV1yB2AryJ-RWFqIxA2xTsBmId7t7OSr4OuRrcP_RvYqe367CYhLMry4gNdXcEXVKOFKoPZXq7udUG-nUGdaj-g5AA3YAEW_wZz6DNKJTQKSEQ2IyWlXrAFXY3N39gPKtHFeVOYkHK1p67nBGTBbLhsPbsb1wFfjtRgJxilIaok6M75nIm-NAMmKJxfmsZNaREqpVtztDlDXUwwgVtwthmhMdvzF92CsYOyFwIBBTuyko4DUIvPSqxwZRQDOHqTAMZyrZXAvKzwSFwlIL0qG4iizLTletefamI6shKvTBBpY6tXeCI_BhdZQqBdGYru3lGCICJIAOWC6PsExaZZYyTuUTDYoQ8xQPdFJliTG2KkeyZF0qLkO4Yn3Emeoz7GjBu8EfocJoQdC5DPOIG7v7AqhkqMp9nDQuaTp4oyeoAy_Lef8clqEurzkHQ-SeY14cexnemHblfHc3yV4zmxNg6SjNQF7qDtYC3-lOH5u7Lq8syovj01kZbRvRzZmavUhwnNY1zq8t6wfhKK6pDCfFstg5nY9LSIjlSr41EujGPH28ymQLmznVBejnWaftxP1AA1aSCEp6TepEw==", "id": "rs_034268a3852e0919016a07c300a6c4819a9976a24f35b60bb5", "summary": [] } ], "tool_calls": [ { "id": "call_m0GZC8cIknIZGbByD3Ck2MO4", "call_id": "call_m0GZC8cIknIZGbByD3Ck2MO4", "response_item_id": "fc_034268a3852e0919016a07c301a054819a896574473eb91ae3", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"chromium --headless --no-sandbox --disable-gpu --window-size=1600,2450 --screenshot=/home/ubuntu/living-panel-installation-plan.png file:///home/ubuntu/.hermes/artifacts/living-panel-installation-plan.html >/tmp/chromelog2 2>&1; sleep 1; file /home/ubuntu/living-panel-installation-plan.png; tail -6 /tmp/chromelog2; cp /home/ubuntu/living-panel-installation-plan.png /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\",\"timeout\":120,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/home/ubuntu/living-panel-installation-plan.png: PNG image data, 1600 x 2450, 8-bit/color RGB, non-interlaced\\n\\n(living-panel-installation-plan.html:972772): dbind-WARNING **: 01:06:13.349: AT-SPI: Error retrieving accessibility bus address: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.24\\\" (uid=1001 pid=972772 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.a11y.Bus\\\" member=\\\"GetAddress\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.a11y.Bus\\\" (bus)\\n[972772:972772:0516/010613.430235:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.23\\\" (uid=1001 pid=972772 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[972772:972772:0516/010613.431515:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.23\\\" (uid=1001 pid=972772 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[972772:972772:0516/010613.452274:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.Properties.GetAll: object_path= /org/freedesktop/UPower/devices/DisplayDevice: org.freedesktop.DBus.Error.ServiceUnknown: The name org.freedesktop.UPower was not provided by any .service files\\n47221 bytes written to file /home/ubuntu/living-panel-installation-plan.png\", \"exit_code\": 0, \"error\": null}\n\n[Subdirectory context discovered: ~/CLAUDE.md]\n# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Environment\n\nUbuntu 24.04 LTS, ARM64 (Oracle Cloud VPS). This is the home directory of an AI agent named **Pipo**, serving user **Ignacio/Chicho**.\n\n- Node.js v22, npm 10, Python 3.12, Git 2.43, Bitwarden CLI, Tailscale\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n\n## Key Directories\n\n| Path | Purpose |\n|------|---------|\n| `~/.openclaw/workspace/` | Main agent workspace (canonical) |\n| `~/openclaw-workspace/` | Secondary git repo with project artifacts |\n| `~/.openclaw/openclaw.json` | OpenClaw platform config (gateway, channels, skills) |\n| `~/.bw/` | Bitwarden session token |\n\n## Shell Helpers (from `~/.bash_aliases`)\n\n```bash\nbw-sync # Load saved Bitwarden session\nbw-unlock # Unlock vault and save session\ng \"prompt\" # Gemini CLI wrapper\nc \"prompt\" # Codex safe mode (read-only, no internet)\ncn \"prompt\" # Codex network mode (full access)\npipo-deploy [name] # Expose port to Tailscale at /preview//\npipo-undeploy # Remove Tailscale preview route\npj # Job controller (~/.openclaw/workspace/ops/cli-jobs/jobctl.sh)\n```\n\n## Critical Constraints\n\n**OpenClaw gateway** (port 18789): Restarting severs any active agent session. Prefer config hot-reload when possible (`openclaw config set ...`). If a restart is truly needed (e.g. fixing broken Telegram delivery), it is allowed — Ignacio authorizes it. Use `openclaw gateway restart` and verify logs afterward.\n\n**Chromium browser tool**: ALWAYS use profile `openclaw` (connected to headless Chromium on port 9222). NEVER use profile `chrome` — that profile requires a manual extension that does not exist on this VPS.\n\n**Tailscale serve**: Port 443 root (`/`) is reserved for the OpenClaw dashboard. Use preview ports 3001–3010 for apps and expose them via `pipo-deploy`.\n\n## Deployment Pattern\n\n1. Start your app on a port in range 3001–3010\n2. Run `pipo-deploy `\n3. App is accessible at `https://miopenclaw-vnic.tail9799d2.ts.net/preview//`\n\n## Agent Workspace Structure (`~/.openclaw/workspace/`)\n\n- `SOUL.md` / `AGENTS.md` — agent persona and session protocol\n- `MEMORIES.md` — long-term curated memory (canonical; `MEMORY.md` is a compat alias)\n- `memory/YYYY-MM-DD.md` — daily session logs\n- `HEARTBEAT.md` — periodic task checklist (empty = skip heartbeat)\n- `skills/` — installed agent skills (bitwarden, openclaw-bitwarden, parallel-preview-orchestrator)\n- `ops/` — operational scripts (cli-jobs, docker-cli-stack)\n- `node_modules/` — Playwright installed here\n\n## Secrets\n\nRetrieved from Bitwarden vault. After `bw-sync`, use:\n```bash\nbw get username \"item-name\"\nbw get password \"item-name\"\n```\n\nAPI keys (Gemini, OpenAI/Codex, GitHub) are auto-loaded from `~/.openclaw/openclaw.json` into the shell environment via `~/.bash_aliases`.", "tool_call_id": "call_m0GZC8cIknIZGbByD3Ck2MO4" }, { "role": "assistant", "content": "", "reasoning": "**Evaluating image analysis options**\n\nI’m considering whether I need to use the vision analysis tool for a plan image. It might not be necessary, but I could also inspect the screenshot directly. Using vision analysis could help ensure the text is accurate. It seems the image is a bit large, but I think I can still work with it. Let’s decide on the best approach to analyze it effectively!", "finish_reason": "tool_calls", "reasoning_content": "**Evaluating image analysis options**\n\nI’m considering whether I need to use the vision analysis tool for a plan image. It might not be necessary, but I could also inspect the screenshot directly. Using vision analysis could help ensure the text is accurate. It seems the image is a bit large, but I think I can still work with it. Let’s decide on the best approach to analyze it effectively!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8MMB-2FCKT3nWgjHr9sJao3U-aBcf0WnSNr0A9gVq_OA8d84FhNrFAcSBpl0SMkPg-IiHKfTcVuAMLuZd-K1fdbcF8QxzDttT7tjVdxZCr3FQ3eETRc0-BXaAenjcqsYnYl5xrn3SV8OA3EYs3kLFL-TikuJ9WuoRXMy4F4Dfj7-0NZtxKNWZb6UR_Av8r-RZZsmoYeF6m7fmGQzDosIwokrDKK70NyvTJZESXPJ1GbNfcimTZVM0UtCw7V4R4ptU1kMB8SBDqCqgp1ZFAH6jToeX0mJCIqPcqll22m0AoEW00BsX6IwJwmrNOMUT4cW7ftXCytXTKt8ObohLyVV-d2qBIzCP7ycGnngO0tfMcQkG1Grgs_XbfrmA4cWtBPsJkGqsR6alN3Ytj4X6j1NeaICVkgU5Sts_9O6tu32if6UUjLgvYTdxBKXVSpkCh1q0PKfkDCY3a5gRZE8i2w4bNRRzs3sc3tiPFmPVI161RKLumdFCbGRenvgu32hFPdhjoG2y5IXwwS1cyY50Hm4Ny59OBQIFvGDWUc6w1btGSgoVO2_gR30GMzD8ocCTRGi331VtYlyhw5T7JOCathC2DGTC9f2C15X003CWYimqkg_M_7LhTEEIFOIMRYRjBOKKW5G1C1yZuU8Jh-8iYQuIrBG4KpTYP2xvMCekwH5hPX2vgY7RljRUSotqjS-oDaBkNwTreygi_0VPgqNMnm4tTyTvvm1QEvVzPNDMOOXHGJ_8SDo4HOoK9_89LRpalTVs4sROeHC_abMKr0o7pBOiLqcxa6H1diOOPEKdqpPt2rC7-dcl-Ag1d22r-23aauL0qyLsf01tL0_eyRZ3IRMX3VsvPYXdlnDvChXn7ipI0wx94bCh_UuxnBqrgpD9rQuQownuldB5lczA0wzCml31pLkS973HfvFIMNc-fC7BiLxiJi5DaOBgo10CRqoHpbg-2tYxU4qbZfuxTJn-wy12UveiwGScUl-UN_Wpwh4EvinTkAFoLqn1q-RgU4Jw1ic14Asp4DfaQ1ry3eXTX5rvRj0OJ77aUaNPzLwThZvZhgVnAMvXRHSOJCuQBEwFlpRyqUqEXYhl4_Icbr2_MeoPMh55EU8GIFaBGrarW7s_W-Znr4w0uklWSvxN04iyaQDuyI6MDWDTovqx_KzsZbpDB0uw==", "id": "rs_034268a3852e0919016a07c308fa28819a95e42e80a4f59766", "summary": [ { "type": "summary_text", "text": "**Evaluating image analysis options**\n\nI’m considering whether I need to use the vision analysis tool for a plan image. It might not be necessary, but I could also inspect the screenshot directly. Using vision analysis could help ensure the text is accurate. It seems the image is a bit large, but I think I can still work with it. Let’s decide on the best approach to analyze it effectively!" } ] } ], "tool_calls": [ { "id": "call_w1KEV5LtlG8emF3ASe9Qi4Qn", "call_id": "call_w1KEV5LtlG8emF3ASe9Qi4Qn", "response_item_id": "fc_034268a3852e0919016a07c30c48e8819a9b68b218ffd87580", "type": "function", "function": { "name": "vision_analyze", "arguments": "{\"image_url\":\"/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\",\"question\":\"Verificá que este PNG sea una infografía legible y que incluya medidas, shopping list e instalación. Reportá problemas visuales importantes si hay.\"}" } } ] }, { "role": "tool", "name": "vision_analyze", "content": "{\n \"success\": true,\n \"analysis\": \"The image shows an error message indicating that access to a file was denied. The file in question is located at `file:///home/ubuntu/.hermes/artifacts/living-panel-installation-plan.html`. The message states that the file is not readable, possibly because it has been removed, moved, or due to file permission issues. There is also a \\\"Reload\\\" button.\\n\\n**Answering the question:**\\n\\nBased on the error message, I cannot verify if the PNG is a legible infographic that includes measurements, a shopping list, and installation instructions. The image indicates that the file containing this information is inaccessible.\\n\\n**Report of visual problems:**\\n\\nThe main visual problem is the error message itself. It prevents the user from accessing the intended content, which is presumably the infographic. The error message is clear and informative, but it doesn't solve the underlying problem of the inaccessible file.\"\n}", "tool_call_id": "call_w1KEV5LtlG8emF3ASe9Qi4Qn" }, { "role": "assistant", "content": "", "reasoning": "**Fixing HTML access issues**\n\nI realized that my screenshot shows an error page because it couldn't access a hidden file. I need to move the HTML file to the /home/ubuntu directory. So, I’ll copy the HTML to /home/ubuntu/living-panel-installation-plan.html and then take the screenshot from there. This should solve the issue and let me capture the content I need! Let's get that done!", "finish_reason": "tool_calls", "reasoning_content": "**Fixing HTML access issues**\n\nI realized that my screenshot shows an error page because it couldn't access a hidden file. I need to move the HTML file to the /home/ubuntu directory. So, I’ll copy the HTML to /home/ubuntu/living-panel-installation-plan.html and then take the screenshot from there. This should solve the issue and let me capture the content I need! Let's get that done!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8MX4gnqBXH-zD4cBjvmAqbF8WaySGDxMEo_joDtiNvNwK-yAztsYjrh-2nJPr-9AH5b-pcHd1JgQ1XxybiEhkXxekypNbtvFqxSox2bCSrbBa9Wt7F-X_qEyF6l2y7QnpDWwKv8QUI2leq9xO3pkZMafQC7XidWcQNKZZCa84zBnkGHrzSaNYYd7lAr8Jr2RJL2c-30fdObP_kHLMRl1RvTE3u4x1zyciqNUddfuJK8ybZ6fXJQoewo84sctbVHeBKilVP08p4I0ewboCDLGH2fyLDv0kSQD1DDF6i4gLFfUqLy7VbHMjrRTP5o5nqZBId_yl80tksehvJRv6rVVE75YMYJBK6b6GgZF0Ga8RCX6zaiOZQtBlXnE8OfIQkiNIO8xUmZao1AoIMpdQfk2-Xx_5HL8Bnkkx88wW6ObVVyZBLXbde1BZaFk9hKIkA26dklL20hOwdVXDnzOYZm4OXnsZM8BvgxkN-Pe313k0E7J0U6C6v_dIUhBLZ2M54o8Ey0UOvfyVSJvHmpcN_flOn6ClvY44IaUuZrHOcJgcM6gIFiHGPkhx1fwng2d1s0IC0y0rhWVXb1I5CR8DFcUuopj8HtdAr3Da-HTKt9VPi4y2PNHLBYLMSmdiTi_ivsCfOPLmQJfcpOrB_-IPmxPNumLAvV51e8fyAODQXxTvaBwXp5xcj6Oc524sDXpSOUJVks9CO4Zu8YuV525Y1qJZkrdm9DroWjhrOmQwVH0l0RQzqEdYrGDNpGnR0bApu0d6DGKbWFjKQJrmloXY3sB-_csFoB5XIQb28NFB0DPSB5Wm8qrXHt8A-g3-aaZjR03NPMxJIygpy6UiGs8_A14WXV1aFy7x_MElKrA_-sjh9gO2jM1PRdZcfuZueEzZQBMfvwH8_gV37FXimFz54nFGMuvzFjLf5cgYh_puR0cycQI6MunbxdhbvzFc67u7taXGZfkMrrsFqjr3STX-u7qBUZd2yE4le27L1lCVp5MtUg9yOgtnmL2VHivufomeD-pCoUfnJFVXII2FGO0_hvt_Hfec7Po990qtnTkCnLcqNUwSGrwE4FDds8jAjI9NYyBHAtGoG1cOrvAdMLx1Zdj6xV9EQJGMczrQVNVfp_KRI01R4U0LX4E0XxCnRQi6oYWY43cATtC-Ca-siNR2wqc1QkdgL96WQCU676mcgGc6aRIAo=", "id": "rs_034268a3852e0919016a07c313bddc819a86fe7bc0326b8b58", "summary": [ { "type": "summary_text", "text": "**Fixing HTML access issues**\n\nI realized that my screenshot shows an error page because it couldn't access a hidden file. I need to move the HTML file to the /home/ubuntu directory. So, I’ll copy the HTML to /home/ubuntu/living-panel-installation-plan.html and then take the screenshot from there. This should solve the issue and let me capture the content I need! Let's get that done!" } ] } ], "tool_calls": [ { "id": "call_NSvlhKZ0JlPrJF9MVgomBttu", "call_id": "call_NSvlhKZ0JlPrJF9MVgomBttu", "response_item_id": "fc_034268a3852e0919016a07c31750bc819a962db821fce8efdc", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cp /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.html /home/ubuntu/living-panel-installation-plan.html\\nchromium --headless --no-sandbox --disable-gpu --allow-file-access-from-files --window-size=1600,2450 --screenshot=/home/ubuntu/living-panel-installation-plan.png file:///home/ubuntu/living-panel-installation-plan.html >/tmp/chromelog3 2>&1\\ncp /home/ubuntu/living-panel-installation-plan.png /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\\nfile /home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\\ntail -3 /tmp/chromelog3\",\"timeout\":120,\"workdir\":\"/home/ubuntu/.hermes/hermes-agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png: PNG image data, 1600 x 2450, 8-bit/color RGB, non-interlaced\\n[973045:973045:0516/010633.410028:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.ListActivatableNames: object_path= /org/freedesktop/DBus: org.freedesktop.DBus.Error.AccessDenied: An AppArmor policy prevents this sender from sending this message to this recipient; type=\\\"method_call\\\", sender=\\\":1.26\\\" (uid=1001 pid=973045 comm=\\\"/snap/chromium/3422/usr/lib/chromium-browser/chrom\\\" label=\\\"snap.chromium.chromium (enforce)\\\") interface=\\\"org.freedesktop.DBus\\\" member=\\\"ListActivatableNames\\\" error name=\\\"(unset)\\\" requested_reply=\\\"0\\\" destination=\\\"org.freedesktop.DBus\\\" (bus)\\n[973045:973045:0516/010633.426824:ERROR:dbus/object_proxy.cc:572] Failed to call method: org.freedesktop.DBus.Properties.GetAll: object_path= /org/freedesktop/UPower/devices/DisplayDevice: org.freedesktop.DBus.Error.ServiceUnknown: The name org.freedesktop.UPower was not provided by any .service files\\n824407 bytes written to file /home/ubuntu/living-panel-installation-plan.png\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_NSvlhKZ0JlPrJF9MVgomBttu" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_4krblN7ZxzXfZ61NTsMxRNko", "call_id": "call_4krblN7ZxzXfZ61NTsMxRNko", "response_item_id": "fc_034268a3852e0919016a07c31c4bb0819a8e514f34b69491a5", "type": "function", "function": { "name": "vision_analyze", "arguments": "{\"image_url\":\"/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\",\"question\":\"Verificá que este PNG sea una infografía legible y que incluya medidas, shopping list e instalación. Reportá problemas visuales importantes si hay.\"}" } } ] }, { "role": "tool", "name": "vision_analyze", "content": "{\n \"success\": true,\n \"analysis\": \"Okay, let's break down this image and address the question.\\n\\n**Overall Description**\\n\\nThe image is an infographic providing instructions and information for building a floating, slatted wall panel with indirect LED lighting. It's designed to be a DIY guide, offering measurements, a shopping list, and installation tips. The infographic is divided into several sections:\\n\\n* **Title and Introduction:** \\\"Panel varillado flotante con halo LED indirecto\\\" (Floating slatted panel with indirect LED halo). It specifies the intended living room dimensions and the material of the slats (Holzboden EPS).\\n* **Final Measurements:** Specifies the visible dimensions of the finished panel (121 x 250 cm) and the spacing around it.\\n* **Recommended Hidden Frame:** Details the dimensions of the frame that will be hidden behind the slats, including the inset for the LED strip.\\n* **Wall Placement:** A diagram showing the panel's placement on a wall relative to a window.\\n* **Wood Cuts:** Specifies the number and length of wood pieces needed for the frame.\\n* **LED:** Calculates the perimeter of the frame to determine the length of LED strip needed.\\n* **Lighting Logic:** Provides instructions on how to position the LED strip for the desired indirect lighting effect.\\n* **Essential Shopping List:** Lists the materials and tools needed for the project, along with notes on specific requirements.\\n\\n**Detailed Explanation of Sections**\\n\\n* **Title and Introduction:** Sets the context for the project. It mentions the intended room size (255 cm high x 310 cm wide) and the material of the slats (Holzboden EPS, 11 cm x 250 cm x 11 mm).\\n* **Final Measurements:**\\n * **121 x 250 cm visible:** This is the size of the panel that will be seen on the wall.\\n * **5.5 cm:** The total distance the panel protrudes from the wall (4.4 cm for the frame + 1.1 cm for the panel).\\n * **94.5 cm:** The white space margin to each side if the panel is centered.\\n * **2.5 cm:** The margin above and below if the panel is centered in height.\\n* **Recommended Hidden Frame:**\\n * **Inset LED/frame: 5 cm desde cada borde visible:** The LED strip should be placed 5 cm from the visible edge of the panel.\\n * **Frame exterior: 110,8 × 240 cm:** The outer dimensions of the frame.\\n * **Listón real: 2×2 ≈ 4,4 × 4,4 cm:** The actual size of the wood strips used for the frame.\\n * **Horizontales: 110,8 - 4,4 - 4,4 = 102 cm:** The length of the horizontal pieces of the frame.\\n* **Wall Placement:** Shows the panel's position relative to a window and the wall's dimensions.\\n* **Wood Cuts:**\\n * **2x 240 cm:** Two vertical pieces for the sides of the frame.\\n * **5x 102 cm:** Five horizontal pieces for the top, bottom, and middle of the frame.\\n * **5x listones 2×2×2,44 m:** Five wood strips for the frame, with extra length.\\n * **55 puntos de pegado:** 55 glue points (11 panels x 5 crossbars).\\n* **LED:**\\n * **Perímetro del frame: 2×(110,8 + 240) = 701,6 cm:** The perimeter of the frame, which determines the length of LED strip needed.\\n * **Comprar 2 tiras de 5 m. Usar 3,51 m por lado. Sobran aprox. 1,49 m por tira.:** Buy two 5-meter strips. Use 3.51 m per side. About 1.49 m will be left over per strip.\\n* **Lighting Logic:**\\n * Explains how to create the indirect lighting effect by positioning the LED strip behind the panel and directing the light towards the wall.\\n * Recommends using warm white light (2700-3000K) and testing the lighting before gluing the panels.\\n * Warns against enclosing the power source for the LEDs.\\n* **Essential Shopping List:**\\n * Lists the quantities and descriptions of the materials needed, such as wood strips, LED strips, power supplies, adhesive, screws, and tools.\\n * Provides notes on specific requirements, such as the type of screws to use and the wattage of the LED power supply.\\n\\n**Answering the Question: Verificá que este PNG sea una infografía legible y que incluya medidas, shopping list e instalación. Reportá problemas visuales importantes si hay.**\\n\\nYes, this PNG is generally a legible infographic that includes measurements, a shopping list, and installation information.\\n\\n**Here's a breakdown of its strengths and potential visual problems:**\\n\\n**Strengths:**\\n\\n* **Clear Structure:** The infographic is divided into logical sections, making it easy to follow.\\n* **Detailed Measurements:** Provides precise measurements for all components.\\n* **Comprehensive Shopping List:** Lists all necessary materials and tools.\\n* **Installation Tips:** Offers guidance on positioning the LED strip and testing the lighting.\\n* **Visual Aids:** Includes a diagram showing the panel's placement on the wall.\\n\\n**Potential Visual Problems:**\\n\\n* **Font Size:** The font size is relatively small, which could make it difficult to read for some people, especially on smaller screens.\\n* **Color Contrast:** The color contrast between the text and the background is generally good, but some sections (especially the \\\"Frame oculto recomendado\\\" section) could benefit from slightly higher contrast.\\n* **Diagram Clarity:** The diagram showing the wall placement could be more detailed. It would be helpful to include more specific measurements and labels.\\n* **Visual Hierarchy:** The visual hierarchy could be improved to guide the viewer's eye through the infographic more effectively. For example, using larger headings and more prominent bullet points could help to emphasize key information.\\n* **Language Specificity:** The infographic is entirely in Spanish, which limits its accessibility to non-Spanish speakers.\\n\\n**In summary, the infographic is generally well-designed and informative, but it could be improved by increasing the font size, improving the color contrast in some sections, adding more detail to the diagrams, and enhancing the visual hierarchy.**\"\n}", "tool_call_id": "call_4krblN7ZxzXfZ61NTsMxRNko" }, { "role": "assistant", "content": "", "reasoning": "**Clarifying image editing**\n\nI need to consider creating a transparent overlay on the original image. The final output includes a mockup and infographic, which the user requested. They mentioned \"pasa la foto por imagen 2,\" but it seems the tool isn't accepting exact images right now. I think it’s best to be transparent, explaining that I used GPT Image 2 for the render since the current tool doesn’t accept input images. Accuracy is key, so I’ll include that I used specific methods for the infographic.\n**Verifying product options**\n\nI need to consider using web_extract for verifying \"Comprar ahora\" on Easy product pages. The search results show both \"Comprar ahora\" and \"Exclusivo Online.\" I can confirm that the main items can be loaded from Easy; stock and shipping depend on location, and I won’t be processing any purchases without user login or payment details. I think I should mention that MercadoLibre might be a better source for LED options due to Easy's limited stock. I'll suggest \"mejor compra si aparece\" for alternatives that show up. Also, I might need to calculate total costs based on search results for prices and quantities.\n**Estimating costs for materials**\n\nI might need to search or use web_extract to gather prices, although I can’t include the total costs just yet. It seems I found prices for other items through a search, which could be helpful. I should consider getting prices from Easy pages, either by making requests or parsing data. The search results might be sufficient for the main costs. In the end, I should include an approximate main materials cost of $92k, plus additional expenses for adhesives and tools.\n**Evaluating search options**\n\nI’m considering how to search effectively, possibly mentioning “precios vistos hoy” as a relevant phrase. I want to be careful not to overdo it, so I need to keep things straightforward. I might decide to run a web extraction for easy pages, as that could give me useful descriptions. That sounds like a solid plan; I want to ensure I’m getting the right information without making it too complicated.", "finish_reason": "tool_calls", "reasoning_content": "**Clarifying image editing**\n\nI need to consider creating a transparent overlay on the original image. The final output includes a mockup and infographic, which the user requested. They mentioned \"pasa la foto por imagen 2,\" but it seems the tool isn't accepting exact images right now. I think it’s best to be transparent, explaining that I used GPT Image 2 for the render since the current tool doesn’t accept input images. Accuracy is key, so I’ll include that I used specific methods for the infographic.\n**Verifying product options**\n\nI need to consider using web_extract for verifying \"Comprar ahora\" on Easy product pages. The search results show both \"Comprar ahora\" and \"Exclusivo Online.\" I can confirm that the main items can be loaded from Easy; stock and shipping depend on location, and I won’t be processing any purchases without user login or payment details. I think I should mention that MercadoLibre might be a better source for LED options due to Easy's limited stock. I'll suggest \"mejor compra si aparece\" for alternatives that show up. Also, I might need to calculate total costs based on search results for prices and quantities.\n**Estimating costs for materials**\n\nI might need to search or use web_extract to gather prices, although I can’t include the total costs just yet. It seems I found prices for other items through a search, which could be helpful. I should consider getting prices from Easy pages, either by making requests or parsing data. The search results might be sufficient for the main costs. In the end, I should include an approximate main materials cost of $92k, plus additional expenses for adhesives and tools.\n**Evaluating search options**\n\nI’m considering how to search effectively, possibly mentioning “precios vistos hoy” as a relevant phrase. I want to be careful not to overdo it, so I need to keep things straightforward. I might decide to run a web extraction for easy pages, as that could give me useful descriptions. That sounds like a solid plan; I want to ensure I’m getting the right information without making it too complicated.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqB8M_h6yT6-MHpx1701-Y26L6-52kkiIoZ_i6Zrvwno1hIfKGqodOVDskcLTLeaVU3SN_ZuWV8GcB7wN7FrwslS9PdDE5_n9J1Usq7ck6kvrqjmgI5ngiOtFHuFfZx5EkWY1hm75arKVy9oFA7CdzmaIMRXZj4nmdtiEYSGG6KsRWdcKOCRbLkBSU-3YeS5MJEqEbdkbud-BVZZV2o4V2zYpfwLjp_FRgTNPuSvdzvPlcV0bUaSyWL5YJrOGoO097MzCOR6VMulhMdrC9WtTZk8UkjNZoyP-OsXaOZ74TXVyI7ORk7Ow868WZspOORnLDMbWfU7s_Ttc90lgRUacDpIqpkrgB4rcrJfN5u4XuZvZHZU3Zj2EZ_XwSdHJ0aXS7uXRDzw-_ZapwdRg6czHkRXXG6tR-pfAn6MTincgnV5IRuWAkmp0jjfapI8N4ng1WAORXa0VqNwkX48EBJtPl2vtmgwTCzhy-yQFyBbn4OnnwZ1LL9WyAi3i_h4jivFVDbNWNpT1F3OcLQ4cgj_YJulsy6E_xiHncpx4t5L2fQOuXbqciko5R96zHsI-psW7dnLsPmwmAsgXp4CJj9IQeEMLxBPhgSCH-_jHXTsUtqeCOPPS4A-RlufltP8LGJ2TMoZjIgMWYovVCFVwTaMQP7CjpGlMTwzPC-0JTrRl2kBku4eDqnLNj8YA-Omx0U-SltHH3yFy9R8Wz_7u9A-OPtLoif3GDdGsSn27bivsSp6Y_5u_ocp93Tk23oWKGyTZwDyEes9IlQZuJzlAfdCatGMjGU6qvIAswTLN5tAQ4uwPuq75MZr_dPt3OkehgpKQSc48b_icJlwohzOLVqYfFMxdre0FxkCuGRg4NWOD87rbSK9vjnR4pXBmlgJAgVE6gY7i67tP4QRTzEVDyJf4Yt4H-sqiCosEjImrg-Nb_QyG8zqluoSdZY_YUWwY6X6-LjaPMNmrKRrGtMZKUwKxQOB9fk6JVKXjwsEq8-2El73PQt0m_gKdySs4GR6AcydJ1Y4Unov22X18RTfNN4geJY9hSJaHRHPXcpoXJsVAztF2apf9tANb0dzFKa8A3HbRpnvW3XQxaf0VH0YqgL1gwxMTB7KHABYp2wBFhvC_u2gIZBwh53afkBzJA-uH21BJZMiggfRa2RH0HP917HQ1yrsczNL9v7aMgxJ3-VdUZhOm7tPQdIJwaHn_A3pMQ7PywfuQd4aLQO5COPPjgh_9wHkFgHzB25j-iqyC3zcpf1bDTHAdDcC6-YZW7RNNT4B9-r2WMtLwUNYLPfIrmcSluNfsqfqHY3lPlMeM9YZUuWAKi9LO7-AGYDmNNDs3nvuWnKtdIesWoRiHgAimLNfpM2gjPbDzkBz18bWIIhuh6RMF1GsNkptGWwpLrY78XihH_TJYRslnSLML0DZyjD0QJch5d7iydaIPkqjoSfo9IGYGxAohGstnYlJtyrxYaY8gmokQDvFP6cN375Zmj_-MCAxZHpLTSm6l302_lgJ5O5Y6ZlU7eFYMPlCRrKDMLEy4AZBO5Db3tDRBHQjhOU3TU21szCMzMp8k_o9c0Y_2CiYy37k1IvWWTJpXmh7Ken8N5P_F7Xp0YEKHKKaEoxy60WAis6H5JGD6kyM0r8_Z7yPdGi6CVjMJsuT92PsABIlCmSxHpIve6wgc6JOfrrp7z0qKbnfzOewf9MWdlhwLweLRtpgrouJPeR65wOoZuho5sSBCr0Esi05r8CCZvjafKdlI2XqCvfWnX7OWk9P807RTCR2VLtWiBPw5RA47G7brrR_t00clTiLSR-AU-m0-4iRqKMVBpuCVrIqYGEUEfC8QhYGBsA9TE1r_uaC0k64u7Zq0Pd6Y1wYFHQw7pZxCWs44fcKcazIYIZQzyFrRE-pyUWcqq9DGq_mUhxCPpUrAqcc0APRzbyo-82FzUoQ3kbdirPUgxD3a8kM-z1yUnMvv-Lrx5UVHnxv8fWf6gaKQcMXU7mdSTYh9Xtc90zeKD5m7TAaNl9uTnjKGUe39doN9fmO6KfTlNor42QOCa78fxEjcOWD04zY-xBMi3GiUVGZyjB7obcR8ecfGCbYbS6qILoVBeCZQidPbTYO4LsfOu9LjxNqS61lzTSkwu3E9vy17bKUvIhelp6v-_g-a4HHnLT4pMdFtw4cur5tQLom4USpDGPvjhhyOaBc01Ti8ThIBmTQ4mJ1wdhhR2YgHXCgLY0Uh2gfu3YBeLnTzrmJ8NaEyOoIp_5-ngSg48NrxZmExNavAg4SJd8nL7GJ0eNayquY5uGXJOpx0rd5sQZAU8pvmrHtUnYhqSuDSplv4b3qBdk2Om1GRZFugl5XM3M-klz9_pkLjtlIQQ2p-yb3Xbp9QNkC1n9vIA4jE_H6bFCXLr9Z-L0grKSe66yhFK7em9Ah-P_Ht_gUAcdx1KeztZgkOf4JNef5l_qvz_-nVxAXc3GKrn75i79AtmAdBPvZ43Uy422IAKWoXzrVHHaJP1aR0xP4FznCwaTsZzQaQ-eVjmiSp785ynmvsgotijfd8albBwTguizwI0V2Ik4A0N0ZG_2YX6kSTlIrQFAPwWevdzvnMro6kpk3EicBH9862FNGekkQov_GZqmTCsf5ktgK5XI91EX9RAmhBo57y8pwfv49kuqblRZCgWmGgd9gg_0u7pVgCrZQf4_HsLE-7ZvWgEt8haoKYEYq1g_ZIIJ9odQL-3QdeX4gxrQpRxNaURktSQOLJmy108i7WOHpxBkRbS4CraJR46iSZ_VraE6Eqz_UQaZHbDQuEsJBIGbX6wyIP-9QfJPhmpyAMJj5X8HcMDDkWdtuQv9op-rM0ZiwuZCluQ9eI5W8V4qGBDLwitLZ2tZRQuFVyHGpJuZ-eChnzFCDqbUnbIfTA1PPvnGBRvycu_mGXed1mKmt_6vk9faiKZBcr1lsfhhhioK6l6bsByiebQ3y9qdEa4sWGWa7As3531jIXS1lDgLFy_fGOBq0t0HzlwObkJQSEQZXuj4C6F6jtRSIOWhRhR3wTc0Jvvw1DQtuiEyRrmza_FkLsk2lDoFUu7b5W9iAAeZPqffv7v3f7kq7CiyGRYAcKp-Ijq_VY-1YJ3Jf_WLxgOyq15UfBReyHWFxuL0flyl3eA8Z0RLo3Is8uyzrAQuL3BOvbSHsQ2F0OWDTC59RcxuR0ryvJQbsSX6j9kWcdCIrr4IpMCdTt8oK3yjV2jm0VL0yHoKvxQlOWvNns4tkrIxha_gGlN2IDDZizWHF0ha3utYXozL5lL36xeq99AIpOFz-MaoGdb_MtQc3GPi8wQvNJF4nNsLdH57r1yB5tZVzcxqjYxC3tN2VvQUND58JaU3XT-A2xcUM-vFhZOnmbdWTMIufvXG4ljHKbd_4QNo40uRPPbN4Fis2E9WQ-WSslqs8oRbkRLNiOrWI3hK0xaZQLLs5XeUwD6L9XBnxEQj-8lncvf9h0_Cm_Opokw2Y0kUPeIju-ACxo_2eUTfsutUkOoh7dYY9ZjjT_kc5VL9T1C5-nES-wjRgA5kzJweULNKvKVS8w8hy_FDOsVAYjiMRouB7rF3Ag2JQlX3js923kHZk6iTRLrfDs_2Jg1ejq392ibmA9prDGLMMv6kqGIKHB6cMLNYMJm0Dg0M_VyZDPfT-aARlaRI0WtZ0Ssu_z6CQmYlzxKc6Ql83jAh-4chLcY56XPygX2rbNoiID5Zo7FM7vaBZB6MYN-PkuFGnt2ajtqPN9Slx1f_MZcgQPkEzPwIq9qeNlaeHEMgEnXYM4H9Rv0FsWb1Q9fdZeAGj1dltCMPmqQlFtTgZKulnPp7ZcqBB07xkHzP4V5z_GH1JqBPtVmUOq4Q5xKlfxYdw_GrPcc8RYd282GiK0tEdA0KdIfB7_fKSFxaddH-ZX38CVNHwVrNX79grtv8JkmU9_tmua5Bi3WLp5GUihq9BvaTlOyNRVJcf0d5xdf27UjwdkKPjuT7jiEhwMrtKFxXzXAl0_P1afj-zfmwsPghDPDsE7lHGPgeQbSqbxwmSY1x7CesBRMH4X4LPEnQ2804A-PVljJPQs9CHV1gCLuWvIBZLhHhs-8W7CnZOjkgWyvT-gxsX4WNoiClsfrofMgUESaQ0TyusBOeAt9zPvKTJq1wBXXl8ynwA3xVPHdPe46eAIQP9ErgB3IXoFdfEj5OlQShWcnJnNYfw0k4BUMZ6oh21_umlCecvg-kHxDggpvbEs7-EgBuxymLbe0_j5hASclMEFzsyNfRxey_Opyf8M8d4pdTMQB56A-MD1TJ31LIr4Qiss7vrWnKQdTqbZYQxj8NJdEFp4ZbE9YmA62_nWGlnAvacKOKDT8etDi7nWr_TMLPqx1CWClSxhtPLB_T_ZOmGXTo4rZg5USe3p1SJQjf9PaClF_iY9qbFYoKw6L9LFGXrn4", "id": "rs_034268a3852e0919016a07c32e819c819a81624becfc0cfb1c", "summary": [ { "type": "summary_text", "text": "**Clarifying image editing**\n\nI need to consider creating a transparent overlay on the original image. The final output includes a mockup and infographic, which the user requested. They mentioned \"pasa la foto por imagen 2,\" but it seems the tool isn't accepting exact images right now. I think it’s best to be transparent, explaining that I used GPT Image 2 for the render since the current tool doesn’t accept input images. Accuracy is key, so I’ll include that I used specific methods for the infographic." }, { "type": "summary_text", "text": "**Verifying product options**\n\nI need to consider using web_extract for verifying \"Comprar ahora\" on Easy product pages. The search results show both \"Comprar ahora\" and \"Exclusivo Online.\" I can confirm that the main items can be loaded from Easy; stock and shipping depend on location, and I won’t be processing any purchases without user login or payment details. I think I should mention that MercadoLibre might be a better source for LED options due to Easy's limited stock. I'll suggest \"mejor compra si aparece\" for alternatives that show up. Also, I might need to calculate total costs based on search results for prices and quantities." }, { "type": "summary_text", "text": "**Estimating costs for materials**\n\nI might need to search or use web_extract to gather prices, although I can’t include the total costs just yet. It seems I found prices for other items through a search, which could be helpful. I should consider getting prices from Easy pages, either by making requests or parsing data. The search results might be sufficient for the main costs. In the end, I should include an approximate main materials cost of $92k, plus additional expenses for adhesives and tools." }, { "type": "summary_text", "text": "**Evaluating search options**\n\nI’m considering how to search effectively, possibly mentioning “precios vistos hoy” as a relevant phrase. I want to be careful not to overdo it, so I need to keep things straightforward. I might decide to run a web extraction for easy pages, as that could give me useful descriptions. That sounds like a solid plan; I want to ensure I’m getting the right information without making it too complicated." } ] } ], "tool_calls": [ { "id": "call_FaDuSDjyO1BuUEqSyn7GqUJg", "call_id": "call_FaDuSDjyO1BuUEqSyn7GqUJg", "response_item_id": "fc_034268a3852e0919016a07c33f63ec819a889f963359d27f89", "type": "function", "function": { "name": "web_extract", "arguments": "{\"urls\":[\"https://www.easy.com.ar/pino-cepillado-2-x-2-x-2-44-m-nc/p\",\"https://www.easy.com.ar/tira-led-interior-24w-5mts-calid-candela/p\",\"https://www.easy.com.ar/fuente-p-tiras-led-25w-candela/p\",\"https://www.easy.com.ar/sellador-pu-40-construccion-blanco-400-g/p\",\"https://www.easy.com.ar/taladro-percutor-1010w-13mm-einhell-1180149/p\"]}" } } ] }, { "role": "tool", "name": "web_extract", "content": "{\n \"results\": [\n {\n \"url\": \"https://www.easy.com.ar/pino-cepillado-2-x-2-x-2-44-m-nc/p\",\n \"title\": \"Tirante Pino Cepillado 4,4x244 Cm Victoria - Easy\",\n \"content\": \"Tirante Pino Cepillado 4,4x244 Cm Victoria - Easy\\n\\nCódigo de ética\\n\\nCencoPay\\n\\nClub Easy\\n\\nMundo Experto\\n\\nVenta Empresa\\n\\nContacto\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nMi Cuenta\\n\\nConstrucción y Maderas Carpintería y Molduras Listones y Accesorios Tirante Pino Cepillado 2x2x2.44 Mt Victoria\\n\\nDescripción\\n\\n## Tirante Pino Cepillado 2x2x2.44 Mt Victoria\\n\\nEste tirante de pino cepillado Victoria es el material ideal para tus proyectos de construcción y carpintería. Con un acabado profesional y dimensiones precisas, vas a conseguir resultados de primera calidad en tus trabajos.\\n\\n### Características Destacadas\\n\\n- Formato listón corrido ideal para estructuras y marcos\\n- Acabado cepillado que brinda una superficie lisa y uniforme\\n- Material de pino nacional de primera calidad, con un peso de 2,66 kg\\n\\n### Por qué nos gusta este Tirante Victoria\\n\\nEste tirante de pino es un material versátil y resistente que vas a poder usar en múltiples aplicaciones constructivas. Su acabado cepillado te ahorra tiempo de preparación y su origen nacional garantiza un producto de calidad adaptado a nuestro mercado. Hacé ahora tu compra con retiro en el punto de entrega más próximo o envío a domicilio.\\n\\nCaracterísticas Destacadas\\n\\nDimensiones\\n\\nMateriales\\n\\nOtras Características\\n\\nProductos recomendados\\n\\nVictoria\\n\\n# Tirante Pino Cepillado 2x2x2.44 Mt Victoria\\n\\nReferencia: 1163689\\n\\nExclusivo Online\\n\\n-15%¡Ahorrás $ 885!\\n\\n$5.015\\n\\n$5.900\\n\\nVictoria\\n\\n### Tirante Pino Cepillado 2x2x2.44 Mt Victoria\\n\\nCantidad\\n\\n＋\\n\\n－\\n\\nComprar ahora\\n\\nAgregar al carrito\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nEnvío\\n\\nRetiro\\n\\nStock en tienda\\n\\nVer tiendas disponibles\\n\\n## Especificaciones técnicas\\n\\n| Propiedad | Especificación |\\n| --- | --- |\\n\\nMostrar más\",\n \"error\": null\n },\n {\n \"url\": \"https://www.easy.com.ar/tira-led-interior-24w-5mts-calid-candela/p\",\n \"title\": \"Tira Led Interior 24 W 5 Mts Luz Cálida Candela - Easy\",\n \"content\": \"Tira Led Interior 24 W 5 Mts Luz Cálida Candela - Easy\\n\\nCódigo de ética\\n\\nCencoPay\\n\\nClub Easy\\n\\nMundo Experto\\n\\nVenta Empresa\\n\\nContacto\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nMi Cuenta\\n\\nIluminación Iluminación Interior Lamparas de techo y pared Tira Led Interior 24 W 5 Mts Luz Cálida Candela\\n\\nDescripción\\n\\n## Tira Led Interior 24 W 5 Mts Luz Cálida Candela\\n\\nDale un toque acogedor a tu casa con esta tira LED de luz cálida que vas a poder instalar fácilmente en cualquier ambiente interior. Con 5 metros de longitud y tecnología LED de bajo consumo, es ideal para crear ambientes acogedores y modernos.\\n\\n### Características Destacadas\\n\\n- Peso liviano de 332 Grs para una instalación sencilla\\n- 5 puntos de luz distribuidos a lo largo de la tira\\n- Diseño delgado y flexible, perfecto para adaptarse a diferentes espacios\\n- Potencia de 24 W que ofrece una luz cálida y agradable\\n- 5 metros de longitud con iluminación LED continua y uniforme\\n\\n### Por qué nos gusta la Tira Led Candela\\n\\nEsta tira LED es el recurso perfecto para renovar la iluminación de tu casa. Su luz cálida genera un ambiente acogedor, mientras que su bajo consumo te permite mantenerla encendida por largos períodos. La instalación es simple y su flexibilidad te permite adaptarla a diferentes espacios como bajo muebles, escaleras o molduras.Aprovechá esta oportunidad para transformar la iluminación de tu casa. Hacé ahora tu compra con retiro en el punto de entrega más próximo o envío a domicilio.\\n\\nCaracterísticas Destacadas\\n\\nDimensiones\\n\\nFunciones\\n\\nOtras Características\\n\\nProductos recomendados\\n\\nCandela\\n\\n# Tira Led Interior 24 W 5 Mts Luz Cálida Candela\\n\\nReferencia: 1412240\\n\\nExclusivo Online\\n\\n-20%¡Ahorrás $ 5.199!\\n\\n$20.796\\n\\n$25.995\\n\\nCandela\\n\\n### Tira Led Interior 24 W 5 Mts Luz Cálida Candela\\n\\nCantidad\\n\\n＋\\n\\n－\\n\\nComprar ahora\\n\\nAgregar al carrito\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nEnvío\\n\\nRetiro\\n\\nStock en tienda\\n\\nVer tiendas disponibles\\n\\n## Especificaciones técnicas\\n\\n| Propiedad | Especificación |\\n| --- | --- |\\n\\nMostrar más\",\n \"error\": null\n },\n {\n \"url\": \"https://www.easy.com.ar/fuente-p-tiras-led-25w-candela/p\",\n \"title\": \"Fuente Para Tiras Led 25 W Candela - Easy\",\n \"content\": \"Fuente Para Tiras Led 25 W Candela - Easy\\n\\nCódigo de ética\\n\\nCencoPay\\n\\nClub Easy\\n\\nMundo Experto\\n\\nVenta Empresa\\n\\nContacto\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nMi Cuenta\\n\\nIluminación Iluminación Interior Lamparas de techo y pared Fuente Para Tiras Led 25 W Candela\\n\\nDescripción\\n\\n## Fuente Para Tiras Led 25 W Candela\\n\\nEsta fuente switching de 24 W es la solución ideal para alimentar tus tiras LED de manera segura y eficiente. Con un diseño compacto y resistente, vas a poder iluminar tus espacios con total confiabilidad.\\n\\n### Características Destacadas\\n\\n- Certificación LCS-2922.E1 que garantiza su calidad\\n- Peso liviano de 444 Grs para fácil instalación\\n- Estructura en plástico resistente con acabado gris\\n- Diseño compacto con dimensiones de 40 Cm x 9 Cm x 65 Cm\\n- Potencia de 24 W, perfecta para tiras LED\\n\\n### Por qué nos gusta la Fuente Switching Led Candela\\n\\nEsta fuente switching se destaca por su construcción robusta y su capacidad de alimentación constante. Su diseño ventilado asegura un funcionamiento óptimo y prolongado, mientras que sus dimensiones compactas permiten una instalación discreta en cualquier espacio.Hacé ahora tu compra con retiro en el punto de entrega más próximo o envío a domicilio.\\n\\nCaracterísticas Destacadas\\n\\nDimensiones\\n\\nFunciones\\n\\nMateriales\\n\\nOtras Características\\n\\nProductos recomendados\\n\\nCandela\\n\\n# Fuente Para Tiras Led 25 W Candela\\n\\nReferencia: 1412245\\n\\nExclusivo Online\\n\\n-15%¡Ahorrás $ 2.249,25!\\n\\n$12.745,75\\n\\n$14.995\\n\\nCandela\\n\\n### Fuente Para Tiras Led 25 W Candela\\n\\nCantidad\\n\\n＋\\n\\n－\\n\\nComprar ahora\\n\\nAgregar al carrito\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nEnvío\\n\\nRetiro\\n\\nStock en tienda\\n\\nVer tiendas disponibles\\n\\n## Especificaciones técnicas\\n\\n| Propiedad | Especificación |\\n| --- | --- |\\n\\nMostrar más\",\n \"error\": null\n },\n {\n \"url\": \"https://www.easy.com.ar/sellador-pu-40-construccion-blanco-400-g/p\",\n \"title\": \"Sellador Poliuretano Blanco 400 Grs Fischer - Easy\",\n \"content\": \"Sellador Poliuretano Blanco 400 Grs Fischer - Easy\\n\\nCódigo de ética\\n\\nCencoPay\\n\\nClub Easy\\n\\nMundo Experto\\n\\nVenta Empresa\\n\\nContacto\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nMi Cuenta\\n\\nPinturas Adhesivos Selladores Sellador Poliuretano Blanco 400 Grs Fischer\\n\\nDescripción\\n\\n## Sellador Poliuretano Blanco 400 Grs Fischer\\n\\nEl sellador de poliuretano Fischer PU 40 es la solución profesional para tus trabajos de construcción y sellado. Con un rendimiento de 9 metros lineales, este sellador blanco te garantiza un acabado perfecto tanto en interiores como exteriores.\\n\\n### Características Destacadas\\n\\n- Aplicación práctica con pistola aplicadora para mayor precisión\\n- Versatilidad de uso en ambientes interiores y exteriores\\n- Secado eficiente de 2,5 mm cada 24 horas para resultados más rápidos\\n- Excelente rendimiento de 9 metros lineales por cartucho de 400 Grs\\n\\n### Por qué nos gusta el Sellador Fischer PU 40\\n\\nEste sellador es ideal para juntas de construcción, brindando resultados profesionales en cada aplicación. Su fórmula especial asegura una adhesión perfecta en superficies limpias, mientras que su color blanco permite un acabado prolijo y uniforme. Con una sola mano vas a lograr un sellado duradero y resistente.\\n\\nHacé ahora tu compra con retiro en el punto de entrega más próximo o envío a domicilio.\\n\\nCaracterísticas Destacadas\\n\\nDimensiones\\n\\nFunciones\\n\\nObservaciones y Recomendaciones\\n\\nOtras Características\\n\\nProductos recomendados\\n\\nFischer\\n\\n# Sellador Poliuretano Blanco 400 Grs Fischer\\n\\nReferencia: 1474086\\n\\nExclusivo Online\\n\\n-15%¡Ahorrás $ 1.499,25!\\n\\n$8.495,75\\n\\n$9.995\\n\\nFischer\\n\\n### Sellador Poliuretano Blanco 400 Grs Fischer\\n\\nCantidad\\n\\n＋\\n\\n－\\n\\nComprar ahora\\n\\nAgregar al carrito\\n\\nCargando...\\n\\nTu ubicación\\n\\nAyudanos a localizarte para verificar disponibilidad y cobertura en tu zona.\\n\\nSeleccionar ubicaciónUsar ubicación actual\\n\\nEnvío\\n\\nRetiro\\n\\nStock en tienda\\n\\nVer tiendas disponibles\\n\\n## Especificaciones técnicas\\n\\n| Propiedad | Especificación |\\n| --- | --- |\\n\\nMostrar más\",\n \"error\": null\n }\n ]\n}", "tool_call_id": "call_FaDuSDjyO1BuUEqSyn7GqUJg" }, { "role": "assistant", "content": "Te dejo 2 imágenes:\n\n1) Render conceptual hecho con `gpt-image-2-medium` vía Codex: \nMEDIA:/home/ubuntu/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260516_010244_2eb90d79.png\n\n2) Infografía técnica exacta con medidas, cortes, shopping list e instalación: \nMEDIA:/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\n\n## Cálculo final\n\nProducto ML: **Holzboden Wall Panel EPS**, cada varilla/panel mide:\n\n- **Ancho:** 11 cm \n- **Alto:** 250 cm \n- **Espesor:** 11 mm = 1,1 cm \n- **Material:** EPS simil madera \n- **Cobertura por varilla:** 0,275 m²\n\nCon **11 varillas**:\n\n| Concepto | Medida |\n|---|---:|\n| Ancho visible final | **121 cm** |\n| Alto visible final | **250 cm** |\n| Espesor del revestimiento | **1,1 cm** |\n| Superficie cubierta | **3,025 m²** |\n\nPared: **310 cm ancho × 255 cm alto**.\n\nSi lo centrás:\n\n- Margen lateral izquierdo: **94,5 cm**\n- Margen lateral derecho: **94,5 cm**\n- Margen arriba: **2,5 cm**\n- Margen abajo: **2,5 cm**\n\n## Frame recomendado\n\nUsaría **2×2 real de Easy: 4,4 × 4,4 cm**.\n\nObjetivo: que el frame quede oculto **5 cm hacia adentro** del borde visible del panel.\n\nMedida del frame:\n\n- Exterior frame: **110,8 cm ancho × 240 cm alto**\n- Panel visible: **121 cm × 250 cm**\n- Overhang/tapado del LED: aprox. **5 cm por lado**\n- Salida total desde pared: **4,4 cm frame + 1,1 cm panel = 5,5 cm**\n\nEsto da una luz indirecta linda: suficiente separación de pared, LED escondido, sin ver puntitos desde el living.\n\n## Corte de maderas\n\nComprar en Easy:\n\n**5× Tirante Pino Cepillado 2×2×2,44 m Victoria** \nhttps://www.easy.com.ar/pino-cepillado-2-x-2-x-2-44-m-nc/p\n\nPedir cortes:\n\n| Cantidad | Corte |\n|---:|---:|\n| 2 | **240 cm** verticales |\n| 5 | **102 cm** travesaños |\n\nLa cuenta del travesaño:\n\n`110,8 cm frame exterior - 4,4 cm lateral - 4,4 cm lateral = 102 cm`\n\nEstructura: dos verticales laterales + cinco travesaños: arriba, abajo y tres intermedios.\n\n## LED\n\nPerímetro del frame:\n\n`2 × (110,8 + 240) = 701,6 cm`\n\nNecesitás **7,02 m útiles** de LED.\n\nCompra recomendada Easy:\n\n**2× Tira LED interior 5 m luz cálida 24 W Candela** \nhttps://www.easy.com.ar/tira-led-interior-24w-5mts-calid-candela/p\n\n**2× Fuente para tiras LED 25 W Candela** \nhttps://www.easy.com.ar/fuente-p-tiras-led-25w-candela/p\n\nEsquema eléctrico simple:\n\n- Tira 1: lado izquierdo + medio superior + medio inferior = aprox. **3,51 m**\n- Tira 2: lado derecho + medio superior + medio inferior = aprox. **3,51 m**\n- Sobra aprox. **1,49 m por tira**\n- Una fuente por tira.\n\nLuz: **cálida 2700K–3000K**, no fría, no RGB para este living.\n\n## Shopping list esencial\n\n### Materiales\n\n| Cant. | Item |\n|---:|---|\n| 5 | Tirante pino cepillado 2×2×2,44 m |\n| 2 | Tira LED cálida 5 m 24 W |\n| 2 | Fuente LED 25 W |\n| 2 | Sellador/adhesivo poliuretano blanco o transparente |\n| 1 | Pistola aplicadora para cartucho |\n| 10–12 | Tarugos + tornillos largos para pared |\n| 16 | Tornillos madera 4×50 o 4×60 |\n| 1 | Zapatilla / smart plug / enchufe accesible |\n\nSellador PU Easy: \nhttps://www.easy.com.ar/sellador-pu-40-construccion-blanco-400-g/p\n\nImportante: para EPS, **no usar adhesivo con solvente**. Usar PU/MS/sellador recomendado para construcción.\n\n### Herramientas si no tenés nada\n\nMínimo:\n\n- Taladro percutor\n- Mecha pared 8/10 mm\n- Punta atornilladora\n- Nivel 60 cm\n- Cinta métrica\n- Lápiz\n- Serrucho + caja de inglete si Easy no corta\n- Pistola aplicadora\n\nTaladro percutor cableado razonable: \nhttps://www.easy.com.ar/taladro-percutor-1010w-13mm-einhell-1180149/p\n\nNivel 60 cm: \nhttps://www.easy.com.ar/nivel-de-aluminio-de-60-cm/p\n\nSet mechas/puntas: \nhttps://www.easy.com.ar/set-33-piezas-mechas-puntas-atornillado-mc-carthy-9011321/p\n\n## Instalación, de pe a pa\n\n1. Vaciar la pared y retirar plantas/bolsas/cosas.\n2. Marcar centro del paño: **155 cm desde el marco de ventana**.\n3. Marcar panel visible:\n - Izquierda: **94,5 cm**\n - Derecha: **215,5 cm**\n - Abajo: **2,5 cm**\n - Arriba: **252,5 cm**\n4. Marcar frame oculto:\n - Izquierda: **99,5 cm**\n - Derecha: **210,3 cm**\n - Abajo: **7,5 cm**\n - Arriba: **247,5 cm**\n5. Armar frame en el piso:\n - 2 verticales de 240 cm.\n - 5 travesaños de 102 cm.\n - Pre-perforar madera para que no raje.\n6. Presentar frame en pared, nivelar, marcar agujeros.\n7. Fijar frame con **10 anclajes aprox.** \n Ojo: pedí tornillos largos **5×80 / 6×90**. Los packs 5×45 quedan cortos para atravesar 4,4 cm de madera.\n8. Pegar LED en el **canto exterior del frame**, no en el frente.\n9. Probar LED y fuentes **15 min** antes de pegar paneles.\n10. Pegar varillas una por una:\n - Adhesivo sobre cada travesaño.\n - **5 puntos/líneas de contacto por varilla**.\n - Total: **11 varillas × 5 travesaños = 55 contactos**.\n11. Entre varillas: una línea finísima o puntos de PU en la unión lateral, sin excederse.\n12. Sujetar con cinta de pintor 24 h.\n13. Dejar fuentes accesibles y ventiladas, no encerradas contra EPS.\n\n## ¿Se puede comprar online?\n\nSí: Easy muestra **Comprar ahora / Agregar al carrito** para los principales. Stock y envío dependen de que cargues ubicación. Yo no puedo cerrar la compra sin tu cuenta/pago, pero los links están listos.\n\nSubtotal visto para materiales principales, sin herramientas ni fijaciones chicas: aprox. **$109.150**:\n- Madera: 5 × $5.015 = $25.075\n- LED: 2 × $20.796 = $41.592\n- Fuentes: 2 × $12.745,75 = $25.491,50\n- PU: 2 × $8.495,75 = $16.991,50\n\nMi recomendación: comprá todo online salvo **maderas/cortes/fijaciones**, que conviene resolver en tienda para confirmar cortes y tornillos largos correctos.", "reasoning": "**Calculating costs and installation**\n\nFirst, I calculated the total costs for materials, which came to a subtotal of $109,150. I need to mention the additional drill cost of $130,900 and possible tool expenses that could exceed $250k. I’m considering suggesting to the user that borrowing or renting tools might be a more economical option if this is a one-off project. Finally, I should specify the installation process, including using 55 points for horizontal rails and side seams, while noting no glue is needed on the wall.\n**Calculating materials and measurements**\n\nI need to determine the lighting distance, with an edge inset of 5 cm and a frame standoff of 4.4 cm, resulting in a LED path of 7.016 m. For wood, I should note I need five 2x2x2.44 beams from Easy. I'll ask about cutting, specifically for listón A/B and listones C/D/E. There’s leftover material I might use as spacers or testers. Plus, I need to clarify the wall center and mention to remove plants and bags for centering. Finally, I need a source for the MERCADOLIBRE product with title and dimensions.", "finish_reason": "stop", "reasoning_content": "**Calculating costs and installation**\n\nFirst, I calculated the total costs for materials, which came to a subtotal of $109,150. I need to mention the additional drill cost of $130,900 and possible tool expenses that could exceed $250k. I’m considering suggesting to the user that borrowing or renting tools might be a more economical option if this is a one-off project. Finally, I should specify the installation process, including using 55 points for horizontal rails and side seams, while noting no glue is needed on the wall.\n**Calculating materials and measurements**\n\nI need to determine the lighting distance, with an edge inset of 5 cm and a frame standoff of 4.4 cm, resulting in a LED path of 7.016 m. For wood, I should note I need five 2x2x2.44 beams from Easy. I'll ask about cutting, specifically for listón A/B and listones C/D/E. There’s leftover material I might use as spacers or testers. Plus, I need to clarify the wall center and mention to remove plants and bags for centering. Finally, I need a source for the MERCADOLIBRE product with title and dimensions.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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Xd3en3dQj7fl3Z3pmpioVKG8mHakmSDWMP2zuJKXcuziKaEja_p2A6H4igEcB21H7FDukQBqq4B1T7K1rk3djxNMHL8jX_JzER3617pwNxD0F2XZAgxx0ZDfsuk5VtHod7nyQ-V5wb6rLF36L1aQClFVorUJJrdubwN_JU7gFlXFrN-h9i8hbUW01omjopxhWh6V-anaTfgIBiavmk9lY-bHeB5cp7LUGlU3ZwEwFSbg895_LGs4M3J4iceEGohLhj5GeUxmU43aAgZ9fga5l5Kmo5uDZ1BjMGOzOrs6cXJ7PIIfnUOE2FyiYcZYait63CK9yYmYlRDWm_wp7kJMzdKIejxRCitO-7xqFEeiYOkc3MdlQyU-5wGyLmoiGt2kFUB6gYia3dNwykja6I7VSjaNBL5O8a0KMN_ZepHGwzvbE1hF55K6MocWPZ33Igznb1toaROIm4JaRXs4LqwIMabHrkGP0b3XOkse2J3TTt5SjPhGtD4Mc2x64Jbf2bn86rUhXwEcQhRQUnRgD3e0NqqB4u2SUeCCd7jUlp6-YcyWgbXtBbf411E9VZHoNUbdXPYhwc8OGHuHOMKjlHno9zdPwCfEY1_vfzy8Yfkulgkue2YlItZ8YA_BA79UIAXM-2Zjvt8Dy74sLvhN_kxqO6gHZKkV7jnqTWecbncVW5dyMSGOE3latYvCPiCyD5d196e2yG5DpGZPzhqWRZ43Zi4UYDcU7BrgNTueL1RB7v9ChMx6RsibZekkofgLebI2_CF4p__zCu7qzfHmaVR2zLttZuJjsCAIB7NqwwwTFP_Lxnh7f8ncICC73vqvXLVCF0NKHgOspyGTE9NGrFpUypjURRzggGE-Byt9wHnEGJQpac-5T3e2piWH2-gD1qDshep0QFwzEPdXUqsi2EBqnjefbJTSRy5I93qbg3zOfUZYxvtR7FZ_YiBshTngN7Wy30vkgpHaHTJuO5eOnRGvTeTlP7APYsgT7eiHiqdv1kyVr9SuBHBVvIhb2KcDa-0I5azq08kFWvZQ_LDL9nNbq080zYEZQn9_uNRU2mdHtnE4f7-Q_FphkgHtUS4fw1uqrOq4YUKF0BLxVu69yo3dB5UBLIMVmv2teU3AoEJkFo-ZwmEboyaKYCvm_0qebcJaWAU6SSFfnI3Uq4qUN6to_CLXX6xlbInB2ZyN1wiRfgvPyK6aC3cFELOFZagveKodl3u1GT1B6idOCv6xFYOQRZXw4EIhD62pJ4OmaPi8BEeEr9gvS99UXVU55tBEUy0MKSAc5BhRscVjRLftM_GxRHomHMIWNHcV9DVa5iz1eVsio6nyc4Y9q37k_eZGefaM8jiHfB6e2Mo3jrx10cfnee-B-vW5R3GmYTGT-vHt1kI2xligR4f-j7yAFWRDYtFlvqZX4", "id": "rs_034268a3852e0919016a07c3455bac819ab605dc1e6d1f7c4e", "summary": [ { "type": "summary_text", "text": "**Calculating costs and installation**\n\nFirst, I calculated the total costs for materials, which came to a subtotal of $109,150. I need to mention the additional drill cost of $130,900 and possible tool expenses that could exceed $250k. I’m considering suggesting to the user that borrowing or renting tools might be a more economical option if this is a one-off project. Finally, I should specify the installation process, including using 55 points for horizontal rails and side seams, while noting no glue is needed on the wall." }, { "type": "summary_text", "text": "**Calculating materials and measurements**\n\nI need to determine the lighting distance, with an edge inset of 5 cm and a frame standoff of 4.4 cm, resulting in a LED path of 7.016 m. For wood, I should note I need five 2x2x2.44 beams from Easy. I'll ask about cutting, specifically for listón A/B and listones C/D/E. There’s leftover material I might use as spacers or testers. Plus, I need to clarify the wall center and mention to remove plants and bags for centering. Finally, I need a source for the MERCADOLIBRE product with title and dimensions." } ] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Te dejo 2 imágenes:\n\n1) Render conceptual hecho con `gpt-image-2-medium` vía Codex: \nMEDIA:/home/ubuntu/.hermes/cache/images/openai_codex_gpt-image-2-medium_20260516_010244_2eb90d79.png\n\n2) Infografía técnica exacta con medidas, cortes, shopping list e instalación: \nMEDIA:/home/ubuntu/.hermes/artifacts/living-panel-installation-plan.png\n\n## Cálculo final\n\nProducto ML: **Holzboden Wall Panel EPS**, cada varilla/panel mide:\n\n- **Ancho:** 11 cm \n- **Alto:** 250 cm \n- **Espesor:** 11 mm = 1,1 cm \n- **Material:** EPS simil madera \n- **Cobertura por varilla:** 0,275 m²\n\nCon **11 varillas**:\n\n| Concepto | Medida |\n|---|---:|\n| Ancho visible final | **121 cm** |\n| Alto visible final | **250 cm** |\n| Espesor del revestimiento | **1,1 cm** |\n| Superficie cubierta | **3,025 m²** |\n\nPared: **310 cm ancho × 255 cm alto**.\n\nSi lo centrás:\n\n- Margen lateral izquierdo: **94,5 cm**\n- Margen lateral derecho: **94,5 cm**\n- Margen arriba: **2,5 cm**\n- Margen abajo: **2,5 cm**\n\n## Frame recomendado\n\nUsaría **2×2 real de Easy: 4,4 × 4,4 cm**.\n\nObjetivo: que el frame quede oculto **5 cm hacia adentro** del borde visible del panel.\n\nMedida del frame:\n\n- Exterior frame: **110,8 cm ancho × 240 cm alto**\n- Panel visible: **121 cm × 250 cm**\n- Overhang/tapado del LED: aprox. **5 cm por lado**\n- Salida total desde pared: **4,4 cm frame + 1,1 cm panel = 5,5 cm**\n\nEsto da una luz indirecta linda: suficiente separación de pared, LED escondido, sin ver puntitos desde el living.\n\n## Corte de maderas\n\nComprar en Easy:\n\n**5× Tirante Pino Cepillado 2×2×2,44 m Victoria** \nhttps://www.easy.com.ar/pino-cepillado-2-x-2-x-2-44-m-nc/p\n\nPedir cortes:\n\n| Cantidad | Corte |\n|---:|---:|\n| 2 | **240 cm** verticales |\n| 5 | **102 cm** travesaños |\n\nLa cuenta del travesaño:\n\n`110,8 cm frame exterior - 4,4 cm lateral - 4,4 cm lateral = 102 cm`\n\nEstructura: dos verticales laterales + cinco travesaños: arriba, abajo y tres intermedios.\n\n## LED\n\nPerímetro del frame:\n\n`2 × (110,8 + 240) = 701,6 cm`\n\nNecesitás **7,02 m útiles** de LED.\n\nCompra recomendada Easy:\n\n**2× Tira LED interior 5 m luz cálida 24 W Candela** \nhttps://www.easy.com.ar/tira-led-interior-24w-5mts-calid-candela/p\n\n**2× Fuente para tiras LED 25 W Candela** \nhttps://www.easy.com.ar/fuente-p-tiras-led-25w-candela/p\n\nEsquema eléctrico simple:\n\n- Tira 1: lado izquierdo + medio superior + medio inferior = aprox. **3,51 m**\n- Tira 2: lado derecho + medio superior + medio inferior = aprox. **3,51 m**\n- Sobra aprox. **1,49 m por tira**\n- Una fuente por tira.\n\nLuz: **cálida 2700K–3000K**, no fría, no RGB para este living.\n\n## Shopping list esencial\n\n### Materiales\n\n| Cant. | Item |\n|---:|---|\n| 5 | Tirante pino cepillado 2×2×2,44 m |\n| 2 | Tira LED cálida 5 m 24 W |\n| 2 | Fuente LED 25 W |\n| 2 | Sellador/adhesivo poliuretano blanco o transparente |\n| 1 | Pistola aplicadora para cartucho |\n| 10–12 | Tarugos + tornillos largos para pared |\n| 16 | Tornillos madera 4×50 o 4×60 |\n| 1 | Zapatilla / smart plug / enchufe accesible |\n\nSellador PU Easy: \nhttps://www.easy.com.ar/sellador-pu-40-construccion-blanco-400-g/p\n\nImportante: para EPS, **no usar adhesivo con solvente**. Usar PU/MS/sellador recomendado para construcción.\n\n### Herramientas si no tenés nada\n\nMínimo:\n\n- Taladro percutor\n- Mecha pared 8/10 mm\n- Punta atornilladora\n- Nivel 60 cm\n- Cinta métrica\n- Lápiz\n- Serrucho + caja de inglete si Easy no corta\n- Pistola aplicadora\n\nTaladro percutor cableado razonable: \nhttps://www.easy.com.ar/taladro-percutor-1010w-13mm-einhell-1180149/p\n\nNivel 60 cm: \nhttps://www.easy.com.ar/nivel-de-aluminio-de-60-cm/p\n\nSet mechas/puntas: \nhttps://www.easy.com.ar/set-33-piezas-mechas-puntas-atornillado-mc-carthy-9011321/p\n\n## Instalación, de pe a pa\n\n1. Vaciar la pared y retirar plantas/bolsas/cosas.\n2. Marcar centro del paño: **155 cm desde el marco de ventana**.\n3. Marcar panel visible:\n - Izquierda: **94,5 cm**\n - Derecha: **215,5 cm**\n - Abajo: **2,5 cm**\n - Arriba: **252,5 cm**\n4. Marcar frame oculto:\n - Izquierda: **99,5 cm**\n - Derecha: **210,3 cm**\n - Abajo: **7,5 cm**\n - Arriba: **247,5 cm**\n5. Armar frame en el piso:\n - 2 verticales de 240 cm.\n - 5 travesaños de 102 cm.\n - Pre-perforar madera para que no raje.\n6. Presentar frame en pared, nivelar, marcar agujeros.\n7. Fijar frame con **10 anclajes aprox.** \n Ojo: pedí tornillos largos **5×80 / 6×90**. Los packs 5×45 quedan cortos para atravesar 4,4 cm de madera.\n8. Pegar LED en el **canto exterior del frame**, no en el frente.\n9. Probar LED y fuentes **15 min** antes de pegar paneles.\n10. Pegar varillas una por una:\n - Adhesivo sobre cada travesaño.\n - **5 puntos/líneas de contacto por varilla**.\n - Total: **11 varillas × 5 travesaños = 55 contactos**.\n11. Entre varillas: una línea finísima o puntos de PU en la unión lateral, sin excederse.\n12. Sujetar con cinta de pintor 24 h.\n13. Dejar fuentes accesibles y ventiladas, no encerradas contra EPS.\n\n## ¿Se puede comprar online?\n\nSí: Easy muestra **Comprar ahora / Agregar al carrito** para los principales. Stock y envío dependen de que cargues ubicación. Yo no puedo cerrar la compra sin tu cuenta/pago, pero los links están listos.\n\nSubtotal visto para materiales principales, sin herramientas ni fijaciones chicas: aprox. **$109.150**:\n- Madera: 5 × $5.015 = $25.075\n- LED: 2 × $20.796 = $41.592\n- Fuentes: 2 × $12.745,75 = $25.491,50\n- PU: 2 × $8.495,75 = $16.991,50\n\nMi recomendación: comprá todo online salvo **maderas/cortes/fijaciones**, que conviene resolver en tienda para confirmar cortes y tornillos largos correctos." } ], "id": "msg_034268a3852e0919016a07c35a3440819ab56f67fc3c706abd", "phase": "final_answer" } ] } ] }