Open source do GitHub: #10 a #6 | Vol. 13 #shorts
Os projetos #10 a #6 do Top 15 open source do GitHub, Vol. 13, 10 segundos para cada um.
#10 House Control: 0xProbabillity/house-control
#9 Talorys: rociiu/talorys
#8 Indra OCR: datalab-to/indra
#7 net-merge: rohit267/net-merge
#6 opendesk: useopendesk/opendesk
Vídeo completo com os 15: youtu.be
Oferecimento: Hallen Tech, hallentech.com
#shorts #opensource #github
12 likes · 292 views
Mais 15 projetos open source do GitHub que valem o seu tempo | Vol. 13
Mais 15 projetos open source do GitHub que valem o seu tempo, em contagem regressiva e com 10 segundos para cada um: um conversor de 255 formatos que funciona arrastando, uma TV sem anúncios, o Figma offline, janelas do Mac no iPad e muito mais.
📺 Décimo terceiro volume da série Open source do GitHub. Escolhidos pela análise da lista inteira (estrelas, frequência de commits, último commit, README, documentação, capturas e site), conferida em 23/10/2026.
Qual desses você vai testar primeiro? Conta nos comentários!
⏱️ CAPÍTULOS E LINKS
0:00 Abertura
0:10 #15 HQTUI: painéis de terminal no estilo btop em 10 linguagens, sem dependências
profullstack/hqtui
0:20 #14 Amagine3D: descreva o aparelho e as medidas e ganhe a caixa em 3D editável, em STEP, STL ou 3MF (6,3 mil estrelas)
amagine-ai/Amagine3D
0:30 #13 slides-grab: o agente cria slides em HTML e você seleciona uma área para pedir o ajuste; exporta em PDF (1,2 mil estrelas)
NomaDamas/slides-grab
0:40 #12 Snitch: monitor de rede em tempo real com firewall de saída: veja e bloqueie cada conexão
aixisstudio/Snitch
0:50 #11 Glide: gravador de tela open source para macOS no estilo Screen Studio, com zoom automático nos cliques
michaelshimeles/glide
1:00 #10 House Control: a sua casa em 3D na barra do Mac e no iPhone, controlando luzes e ar-condicionado
0xProbabillity/house-control
1:10 #9 Talorys: agente pessoal de IA que roda na sua conta da Cloudflare, com memória, tarefas e lembretes (1,4 mil estrelas)
rociiu/talorys
1:20 #8 Indra OCR: modelo de OCR minúsculo que roda na CPU, em mais de 80 idiomas e até letra de mão
datalab-to/indra
1:30 #7 net-merge: usa Wi-Fi, cabo e celular ao mesmo tempo, somando a velocidade das conexões (1,8 mil estrelas)
rohit267/net-merge
1:40 #6 opendesk: central de atendimento open source com e-mail, chat do site e base de ajuda numa caixa só
useopendesk/opendesk
1:50 #5 editonny: skill para Claude Code e Codex que edita vídeo por conversa: corta pausas, legenda e arruma o áudio
soumatheusgomes/editonny
2:00 #4 Desigma: alternativa gratuita e offline ao Figma, feita em Rust, que importa arquivos do Figma
deepfounder-ai/desigma
2:10 #3 Sill: qualquer janela do Mac no iPhone ou iPad, com toque, teclado e Apple Pencil, sem conta nem servidor (3,9 mil estrelas)
Saffsanity/sill
2:20 #2 cleanyourtv: tira anúncios e apps de fábrica da TV pelo Wi-Fi, de forma reversível (24,8 mil estrelas)
Gathin23/cleanyourtv
2:30 Oferecimento Hallen Tech
2:44 #1 Filee: conversor de arquivos offline: segure uma tecla, arraste e converta entre 255 formatos (10,3 mil estrelas)
KnifeLemon/Filee
2:54 Encerramento
🧡 Oferecimento: Hallen Tech, liderança de tecnologia sob demanda, software, cloud e segurança para a sua empresa.
Site: hallentech.com
E-mail: contato@hallentech.com
Instagram: instagram.com
LinkedIn da Hallen Tech: linkedin.com
LinkedIn do Eddwan: linkedin.com
Se curtiu, deixa o like, segue o canal e ativa as notificações para a próxima lista.
#opensource #github #programacao #ferramentas
294 likes · 6 comments · 9,142 views
Talorys GitHub Overview: Private AI on Cloudflare with Memory and Task Automation
talorys by rociiu: rociiu/talorys
Talorys is an open-source personal AI agent designed to run inside your Cloudflare account, combining scheduled automations, durable memory, task management, and a streaming chat interface. This overview explains the Node.js 22+ and Cloudflare prerequisites, the npx create-talorys@latest deployment flow, optional semantic recall, OAuth, and local password hashing. It also covers the security tradeoffs—there is no forgot-password button—the 10,000 daily Workers AI neuron limit, token guardrails, WAF troubleshooting, local talorys.json state, and iPhone notification setup. The key takeaway: a single-user edge architecture can keep personal tasks and memories under one owner’s control, but it remains tied to Cloudflare quotas and services.
TimeStamps:
0:00 Why a private personal AI agent
0:16 Talorys on Cloudflare
0:32 Prerequisites and self-hosted tradeoffs
0:57 CLI deployment and optional semantic recall
1:19 OAuth, local password hashing, and access
1:50 End-to-end task flow in the interface
2:56 403 recovery and the serverless architecture
3:30 Workers AI neuron limits
3:46 Token guardrails in Settings
4:39 Local talorys files and the update anchor
5:02 iPhone notifications and single-user control
🔐 Local password hashing and single-user access
☁️ Cloudflare edge architecture, Durable Objects, and Workers AI
🧠 Semantic recall, memory, tasks, and scheduled automations
📱 Quotas, maintenance files, and iPhone notifications
For viewers comparing self-hosted AI options, Talorys is best understood as a focused single-user Cloudflare deployment: convenient managed edge primitives, privacy-oriented credential handling, and built-in tasks and memory, balanced against Workers AI quotas, Cloudflare dependence, and a no-recovery-password model. Check the repository’s current documentation before deploying or updating.
#Talorys #Cloudflare #PersonalAI
[de-DE] YNAS ynp_dd5ea2b365601887 Cinematic
Privater automatisierter Staging-Upload. Paketidentität: ynp_dd5ea2b365601887; Ausgabe: cinematic.
[es-US] YNAS ynp_dd5ea2b365601887 cinemático
Carga de entorno de prueba de automatización privada. Identidad del paquete: ynp_dd5ea2b365601887; salida: cinemática.
[fr-FR] YNAS ynp_dd5ea2b365601887 cinématique
Téléchargement de l'environnement de test d'automatisation privé. Identifiant du package : ynp_dd5ea2b365601887 ; sortie : cinématique.
[hi] YNAS ynp_dd5ea2b365601887 सिनेमाई
निजी स्वचालन स्टेजिंग अपलोड। पैकेज पहचान: ynp_dd5ea2b365601887; आउटपुट: सिनेमाई।
[id] YNAS ynp_dd5ea2b365601887 sinematik
Unggahan staging otomatisasi pribadi. Identitas paket: ynp_dd5ea2b365601887; output: sinematik.
[it] YNAS ynp_dd5ea2b365601887 cinematic
Caricamento di automazione privata. Identità del pacchetto: ynp_dd5ea2b365601887; output: cinematico.
[pt-BR] YNAS ynp_dd5ea2b365601887 cinemático
Upload de teste de automação privada. Identificação do pacote: ynp_dd5ea2b365601887; saída: cinemática.
2 likes · 156 views
Top 10 Trending AI GitHub Tools (#1 Runs Agent Teams Like You Own Them)
Ten open-source AI tools trending this week: agents moved their infrastructure in-house. This countdown spans from local inference engines to the framework where agents run as persistent, networked teams that organize themselves.
ds4 (ten) runs DeepSeek V4 Flash on a MacBook at 39 tokens per second by streaming transformer layers from disk instead of forcing them all into memory at once. Ollama (nine) packages any GGUF model with a single command. Text-to-CAD (eight) generates real mechanical CAD files, exportable to STEP, STL, and 3MF formats. Ponytail cuts code by 54 percent (seven). God is Eye View brings satellite, flight, ship, and earthquake data into a 3D globe with 28 voice commands (six). HyperFrames renders MP4 from HTML deterministically (five). OpenMontage is a complete agentic video studio with 12 pipelines and 700-plus skills (four). Multica treats agents as teammates (three). Talorys runs on the free Cloudflare tier (two). At number one, OpenRig boots persistent agent teams from YAML with stable seats and recoverable state across reboots.
Projects in this video:
ds4: antirez/ds4
Ollama: ollama/ollama
Text-to-CAD: earthtojake/text-to-cad
ponytail: DietrichGebert/ponytail
God's Eye View: JasimAli75/gods-eye-view
HyperFrames: heygen-com/hyperframes
OpenMontage: brandeins11/OpenMontage
multica: multica-ai/multica
Talorys: rociiu/talorys
OpenRig: smota/openrig
0:00 Intro
1:00 #10 ds4
2:17 #9 Ollama
3:29 #8 Text-to-CAD
4:42 #7 ponytail
5:48 #6 God's Eye View
7:04 #5 HyperFrames
8:31 #4 OpenMontage
9:50 #3 multica
11:06 #2 Talorys
12:32 #1 OpenRig
14:07 Outro
Contact: digestibleinfohub@gmail.com
#OpenRig #AI #GitHub #OpenSource #DevTools
162 views
Топ-10 GitHub за 3 дня: схемы для Claude и поиск по Mac
Обзор: топ-10 новых репозиториев GitHub за 8–11 октября 2026 — open-source проекты, которые быстрее всех набрали звёзды.
В выпуске: скилл Claude Code для изометрических схем, быстрый поиск файлов на macOS и сервис Anthropic для проверки open-source на уязвимости.
1. wheresryan22/anatomy — Скилл Claude Code: превращает идею в интерактивную изометрическую схему устройства. (JavaScript, +2788 ★)
2. noahdunnagan/fsearch — Поиск файлов по всему диску macOS: по имени, с опечатками и по тексту внутри. (Rust, +1842 ★)
3. storytold/craft-launcher — Лаунчер ArtCraft: ставит и обновляет приложения пакета Craft, от PhotoCraft до CADCraft. (Rust, +1066 ★)
4. ARahim3/DigUp — Поиск по файлам Mac по смыслу: фото, PDF, записи и видео находятся по описанию. (Swift, +806 ★)
5. anthropics/oss-scanner — Сервис Anthropic: проверяет критичные open-source проекты на уязвимости. (Dockerfile, +781 ★)
6. marclou/mailcheap — Рассылки на своём сервере через Amazon SES: редактор, список, формы, архив выпусков. (JavaScript, +742 ★)
7. ThariqS/ai-newtab — Расширение Chrome: агент Claude собирает новую вкладку по вашей истории и страницам. (TypeScript, +730 ★)
8. rociiu/talorys — Личный ИИ-ассистент в вашем аккаунте Cloudflare: чат, память, задачи, напоминания. (TypeScript, +728 ★)
9. ToiCF/CF-Workers-TGProxy — Прокси для Telegram на Cloudflare Workers: ретранслирует WebSocket-трафик клиента. (+711 ★)
10. wesbos/photo-frame-dashboard — Заметки и скрипты: ADB, root и свои приложения на запертых Android-фоторамках. (Python, +704 ★)
Источник: GitHub Search API, репозитории созданы с 2026-10-08, отсортированы по звёздам.
Лидер: wheresryan22/anatomy
Остальные: noahdunnagan/fsearch, storytold/craft-launcher, ARahim3/DigUp, anthropics/oss-scanner, marclou/mailcheap, ThariqS/ai-newtab, rociiu/talorys, ToiCF/CF-Workers-TGProxy, wesbos/photo-frame-dashboard
#GitHub #opensource #программирование
Каждые 3 дня — 10 новых open-source проектов GitHub, быстрее всех набравших звёзды. Подписывайся, чтобы не пропустить следующий выпуск.
1 like · 92 views
Talorys: A Personal AI Agent in Your Own Cloudflare Account
_A closer look at the open-source project_ _rociiu/talorys_
Many AI assistants follow the same pattern. You sign up, hand your conversations to someone else's servers, and trust that your notes, tasks and personal details are handled well. Talorys takes the opposite approach. It is a personal AI agent that runs entirely inside your own Cloudflare account, with no server, database or account operated by its developers.
The pitch is short: one person, one Cloudflare account, one command.
npx create-talorys@latest
What you get
Talorys is a small, focused assistant rather than a sprawling platform. Out of the box it includes:
- Chat with streaming responses, Markdown rendering and indicators that show when the agent is using a tool.
- Memory for durable facts and preferences. You can view, edit and delete everything it remembers, and only the most relevant memories are sent to the model on each turn.
- Tasks, notes and projects with full create, read, update and delete in the UI. You can also manage them from chat, for example by saying "Add a task to review my project tomorrow."
- Automations such as one-time and recurring reminders, daily task digests and optional AI routines, all delivered to an in-app notification center.
It is single-user by design. There is no signup, no teams and no accounts. The installer asks you to set an owner password, and you sign in from any device with it.
One detail I like: it works without AI. If Workers AI is unavailable or you have used up your free daily quota, tasks, notes, memories and reminders keep working. Only chat pauses until the quota resets.
Deploying in one command
The installer does the tedious parts for you. It checks your Node.js version (20.18 or newer), verifies your Cloudflare login (or opens Cloudflare's authorization page in your browser), and lets you pick an account and an agent name. It then asks for an owner password, which is hashed locally with PBKDF2-SHA256 and stored only as a Cloudflare secret.
From there it generates a session secret, deploys a private Worker along with its SQLite-backed Durable Object, creates the Pages project, and verifies the live deployment before printing your pages.dev URL. The verification step checks the frontend, the auth endpoint and storage health without running any AI inference.
Here is the whole run at a glance, split by where each step happens:
!Mermaid Diagram
The installer is also forgiving. If it gets interrupted, you run the same command again and it reconciles what already exists, with no duplicate resources and no data deleted. When you want the latest version later, npx create-talorys@latest update redeploys to the same resources and keeps your password and sessions. There are also status and doctor commands, plus a reset-password command if you get locked out.
How it works under the hood
The architecture is lean, and it shows how far Cloudflare's platform can go on its own:
!Mermaid Diagram
A few design choices stand out:
- The agent has no public URL. The Worker is deployed with workers_dev and preview URLs turned off. Your browser only talks to the Pages site, whose /api function forwards requests over a service binding.
- Auth happens in the Worker, not the frontend. Sessions ride in an HttpOnly, SameSite=Strict cookie, the database stores only a keyed hash of each session token, and five failed logins from one IP within 15 minutes lock that client out.
- All state lives in one SQLite-backed Durable Object. Conversations, memories, tasks, notes, projects, automations, sessions and usage data share a single store.
- Scheduling uses Durable Object alarms. Reminders and routines fire without anything having to stay online. Per the architecture doc, each enabled automation holds one pending schedule, and a run missed by less than 24 hours still executes once.
One automation cycles like this, with nothing staying online in between:
!Mermaid Diagram
On the AI side, chat runs on Workers AI using the @cf/zai-org/glm-4.7-flash model, with streaming and tool calling. Responses stream as Server-Sent Events from end to end, and reasoning is switched off to conserve Workers AI Neurons. Models sit behind a small provider interface, so adding another provider means implementing it in code rather than flipping a setting.
The agent's tools are tightly scoped, too. According to the security doc, destructive actions such as deleting a task or note need explicit confirmation in your latest message, enforced in code rather than only in the prompt. Scheduled AI runs get read-only tools plus a notify tool, and there are no shell, code-execution or outbound-HTTP tools at all.
Free-tier friendly, with honest caveats
Talorys is built to fit within the Cloudflare Workers Free plan. It uses only Pages, Workers, SQLite Durable Objects and Workers AI, and it does not provision R2, D1, KV, Vectorize or any paid service.
The README is refreshingly candid that this is not "unlimited free." Cloudflare sets account-level quotas, including a daily Workers AI allocation, and those can change. When the AI allocation runs out, chat tells you clearly and resumes after the daily reset. If your account is on a paid plan, usage beyond the included amounts is billed by Cloudflare.
To keep usage predictable, there are adjustable guardrails in Settings → AI: maximum output tokens, maximum context tokens (older history gets summarized), limits on tool calls and reasoning steps per request, and daily caps on AI requests and scheduled AI runs. Simple reminders and task digests never touch the model at all.
Privacy and data ownership
Talorys includes no telemetry, analytics, tracking or advertising code, and it sends nothing to its developers. Your data sits in your own Cloudflare account.
One thing to keep in mind is that Cloudflare itself processes your data to provide its services. That includes running Workers AI inference on your chat messages and the relevant memories included in each prompt. "Self-hosted on Cloudflare" is not the same as "never leaves your machine," so it is worth reading Cloudflare's privacy policy and Workers AI terms.
You also keep an exit. Settings → Privacy → Download backup exports conversations, memories, tasks, notes, projects, settings and automations as a single JSON file, never sessions or credentials. Importing validates the file and merges it in one transaction, so restoring the same backup twice is harmless.
Trying it locally
If you would rather poke around before deploying, local development needs only Node.js 20.18 or newer:
git clone https://github.com/rociiu/talorys.git
cd talorys
npm install
npm run dev
This starts the agent Worker, the Pages Function proxy and the Vite UI together, using a deterministic mock AI provider, so no Cloudflare login is required. The repo is a TypeScript monorepo with a Hono-based agent app, a React and Vite frontend, shared Zod schemas, the installer package, and Playwright end-to-end tests.
Who is it for?
Talorys fits people who want a private, low-maintenance assistant without running servers or paying for yet another subscription, and who already have, or are happy to create, a Cloudflare account. It is also a useful reference for anyone curious about building agents on Durable Objects, alarms and Workers AI.
A few things to weigh before adopting it. It is a small project so far, with 10 commits and 10 stars at the time of writing. It is deliberately single-user, so it will not suit teams. And chat quality depends on the Workers AI model it uses by default (GLM-4.7-flash) rather than a frontier model you pick yourself.
Still, the core idea is compelling: a personal agent you deploy in minutes, own completely, and can export or tear down whenever you like. If that appeals to you, the repository is at rociiu/talorys and it is MIT licensed.
---
Published via ZyVOP — Write once in Markdown, auto-backup to GitHub, and syndicate to Dev.to, Medium & Hashnode in 1 click.
**A Free Cloud AI**
If you would like an AI “personal agent” but don’t want your data on some opaque cloud computer, there’s a new option that appears to be somewhat nicer: [rociiu] has talorys, an AI agent that runs in your Cloudflare account. True, it is […]
[Original post on poliverso.org]
1 like
Talorys: a self-hosted personal AI agent running on Cloudflare's free tier. No excuses left for not shipping your own agent.
rociiu/talorys
1 like
Talorys – A self-hosted personal AI agent on Cloudflare's free tier rociiu/talorys (news.ycombinator.com)
7 likes · 473 views
Cloudflare Workers AI Free Tier Can Run Out in 35 Messages. I Did the Math.
With Talorys's default settings, a long conversation can use up Cloudflare's free AI allowance in about 35 messages. On short chats you get closer to 550 model calls a day. Both numbers come from the same 10,000 free Workers AI "neurons".
Talorys is an MIT-licensed personal agent that showed up on HN this week, and it's built to live inside that allowance: chat, memory, tasks, notes and reminders, with no VPS, subscription or paid database behind it. I cloned it, built it, ran it locally and checked the neuron math against Cloudflare's own price sheet. The free tier is real, but it's smaller than "$0/month" makes it sound, and CPU, requests and storage aren't what runs out first.
What you actually get
Talorys is one Cloudflare account, one owner, one agent. The architecture from the README:
Browser ──HTTPS──▶ Cloudflare Pages (React app + /api Pages Function)
│ service binding (no public URL)
▼
Private Worker (Hono router)
▼
TalorysAgent (Agents SDK Durable Object)
├─ SQLite: conversations, memories, tasks, notes, ...
├─ Workers AI: @cf/zai-org/glm-4.7-flash
└─ Alarms: reminders and recurring schedules
All your data sits in a single SQLite-backed Durable Object called personal-agent. The Worker is deployed with workers_dev: false and preview_urls: false, so the only public surface is your *.pages.dev site. Auth happens in the Worker; the password is hashed with PBKDF2-SHA256 and stored as a Cloudflare secret. No R2, D1, KV or Vectorize gets provisioned.
The agent has 22 tools in v0.1.2: create_task, update_task, remember, search_memories, create_reminder, create_automation, notify_owner, create_note, update_note, create_project and so on. It has no web access. The search tool searches your own tasks, notes, memories and past conversations, not the internet. What you get is a very well-built personal organizer with an LLM front end, so if you were picturing an agent that browses and books things for you, keep looking.
Deploying it
The whole install is one command:
npx create-talorys@latest
It checks your Node version (v0.1.2 accepted 20.18+, but the README now requires Node 22+ because the bundled Wrangler needs it), opens Cloudflare's OAuth page, asks you for an owner password, deploys the private Worker plus its Durable Object, creates the Pages project with the service binding, runs health checks that deliberately skip AI inference, and prints your URL. If it dies halfway through, run the same command again and it picks up where it stopped. It doesn't delete anything.
Later you'll use:
npx create-talorys@latest update
npx create-talorys@latest doctor
npx create-talorys@latest reset-password
For CI or a headless box: TALORYS_OWNER_PASSWORD=... npx create-talorys@latest --yes --account-id <id> with CLOUDFLARE_API_TOKEN set.
What I ran
I didn't push it to a Cloudflare account for this post, so I can't show you a dashboard screenshot. What I did:
git clone https://github.com/rociiu/talorys.git
cd talorys
npm ci
npm run build
npm test
npm run dev
The test suites passed (14 + 58 + 3 + 32 tests). One create-talorys test file fails if you run tests before npm run build, because it looks for the built Worker template. Build first.
npm run dev starts wrangler dev on 8787, wrangler pages dev on 8788 and Vite on 5173, using a deterministic mock model, so you don't need a Cloudflare login. I logged in with the dev password and sent "Add a task to review my Cloudflare bill tomorrow" through /api/chat. The SSE stream showed a create_task tool call, then the reply, in 0.249s. /api/tasks had the new row. /api/usage reported 1 AI request, 370 input tokens and 13 output tokens.
Remember the mock: that 370 is Talorys's own ~4-chars-per-token estimate of system prompt plus message. It leaves out the JSON schemas for all 22 tools, which a real model call has to send, so real calls are heavier.
The math nobody in the HN thread finished
Most of the HN discussion was an argument over whether "self-hosted" is the right word, and only a few people posted numbers. One commenter said they spent 500 neurons in a few minutes of chatting and guessed the free 10,000 would cover "maybe 20-30 minutes of back and forth." Another linked the price sheet to put the whole 10k at about $0.11, but nobody worked out what that buys in messages, so here's the Workers AI pricing page applied to Talorys's defaults:
- glm-4.7-flash input: 5,500 neurons per million tokens
- output: 36,400 neurons per million tokens
- free: 10,000 neurons/day, reset at 00:00 UTC
- above that, on Workers Paid: $0.011 per 1,000 neurons
The defaults in packages/shared/src/constants.ts are maxContextTokens: 6000, maxOutputTokens: 1024, maxAgentIterations: 4, maxAiRequestsPerDay: 200.
| Scenario per model call | Neurons | Calls per free day |
| --- | --- | --- |
| Short chat: 2,000 in / 200 out | ~18 | ~550 |
| Full context: 6,000 in / 1,024 out | ~70 | ~140 |
| Full context, 4 agent iterations | ~280 per message | ~35 messages |
Output costs about 6.6x what input costs per token, so long replies drain the budget much faster than long history. The default cap of 200 AI requests/day multiplied by ~70 neurons is 14,000, which is more than the free allocation. On a long-running conversation, the app's own guardrail won't stop you before Cloudflare does.
On the Free plan you can't be billed, so going over just means chat returns an "allocation used for today" error until 00:00 UTC, and tasks, notes and plain reminders keep working because they never touch the model. If you're on Workers Paid, the overage is real money, but tiny: the entire 10k free allocation would cost $0.11 at list price.
The other limits are nowhere close for one person. Workers Free gives you 100,000 requests/day and 10 ms of CPU per request, and time spent waiting on inference doesn't count as CPU. Durable Objects on Free get 100,000 requests, 13,000 GB-s, 5M rows read and 100,000 rows written per day, with 5 GB of storage. You won't run out of any of those by managing your own to-do list. The neuron budget is the binding constraint: around 35 to 550 model calls a day, depending on how you use it.
Settings I'd change on day one
Go to Settings → AI and:
1. Lower maxOutputTokens from 1024 to around 400. Output is the expensive side, and a personal assistant rarely needs a 1,000-token answer.
2. Lower maxContextTokens from 6000 to 3000 or 4000. Older history gets summarized, so you lose less than you'd expect.
3. Set maxAiRequestsPerDay to something your neuron math supports, like 100, so the app hits its own limit before Cloudflare's.
4. Leave maxScheduledAiRunsPerDay at 6 unless you really want AI routines. Plain reminder and task_digest automations run on Durable Object alarms and cost zero neurons. Only agent_prompt calls the model.
Also, the in-app Usage panel is an estimate, and it says so. The actual neuron count lives in the Cloudflare dashboard under Workers AI. Look there once a week for the first month.
Is it "self-hosted"? No. Does that matter?
The most common HN complaint was the label. "Selfhosted on cloudflare is a great oxymoron," one commenter wrote, and others offered "self-managed" and "self-hosted but not self-owned" instead. They're right. Your data sits in a Durable Object on Cloudflare's hardware, Cloudflare runs inference on your messages, and the storage layer won't move to a VPS without a rewrite.
I still think it's the more interesting design. The usual self-hosted AI setup is a $5-10 VPS you patch yourself plus an API key for someone's model. Talorys trades the VPS for a free account, a scale-to-zero object and alarms that fire whether or not anything is "running." The model layer is the easy part to swap: one commenter said they'd replaced Workers AI in Cloudflare's own agents example apps with a local whisperfile binary in about 5 minutes, another estimated pointing it at a local model server is under 20 minutes of work, and the provider interface in apps/agent/src/ai/provider.ts is small. The Durable Object is where the real lock-in is, and I can't wave that away.
The backup export (talorys-backup.json, Settings → Privacy) is what keeps that lock-in tolerable. Download it on a schedule.
Who should bother
If you want a private tasks/notes/memory app you can talk to, with a hard spending cap of zero, this is the cleanest version of that idea I've seen. If you want an agent that does things in the outside world, you'll be writing tools, and each tool call is another round trip through your neuron budget.
So, for anyone already running a personal agent: what does it do for you every day, and how many model calls does that actually take? I'd like to know if 35 full-context messages is plenty or a joke.
Sources
- Talorys repo, v0.1.2: rociiu/talorys
- HN discussion: news.ycombinator.com
- Workers AI pricing: developers.cloudflare.com
- Workers limits: developers.cloudflare.com
- Durable Objects pricing: developers.cloudflare.com
1 comment
Mentions
Open source do GitHub: #10 a #6 | Vol. 13 #shorts Os projetos #10 a #6 do Top 15 open source do GitHub, Vol. 13, 10 segundos para cada um. #10 House Control: 0xProbabillity/house-control #9 Talorys: rociiu/talorys #8 Indra OCR: datalab-to/indra #7 net-merge: rohit267/net-merge #6 opendesk: useopendesk/opendesk Vídeo completo com os 15: youtu.be Oferecimento: Hallen Tech, hallentech.com #shorts #opensource #github
Mais 15 projetos open source do GitHub que valem o seu tempo | Vol. 13 Mais 15 projetos open source do GitHub que valem o seu tempo, em contagem regressiva e com 10 segundos para cada um: um conversor de 255 formatos que funciona arrastando, uma TV sem anúncios, o Figma offline, janelas do Mac no iPad e muito mais. 📺 Décimo terceiro volume da série Open source do GitHub. Escolhidos pela análise da lista inteira (estrelas, frequência de commits, último commit, README, documentação, capturas e site), conferida em 23/10/2026. Qual desses você vai testar primeiro? Conta nos comentários! ⏱️ CAPÍTULOS E LINKS 0:00 Abertura 0:10 #15 HQTUI: painéis de terminal no estilo btop em 10 linguagens, sem dependências profullstack/hqtui 0:20 #14 Amagine3D: descreva o aparelho e as medidas e ganhe a caixa em 3D editável, em STEP, STL ou 3MF (6,3 mil estrelas) amagine-ai/Amagine3D 0:30 #13 slides-grab: o agente cria slides em HTML e você seleciona uma área para pedir o ajuste; exporta em PDF (1,2 mil estrelas) NomaDamas/slides-grab 0:40 #12 Snitch: monitor de rede em tempo real com firewall de saída: veja e bloqueie cada conexão aixisstudio/Snitch 0:50 #11 Glide: gravador de tela open source para macOS no estilo Screen Studio, com zoom automático nos cliques michaelshimeles/glide 1:00 #10 House Control: a sua casa em 3D na barra do Mac e no iPhone, controlando luzes e ar-condicionado 0xProbabillity/house-control 1:10 #9 Talorys: agente pessoal de IA que roda na sua conta da Cloudflare, com memória, tarefas e lembretes (1,4 mil estrelas) rociiu/talorys 1:20 #8 Indra OCR: modelo de OCR minúsculo que roda na CPU, em mais de 80 idiomas e até letra de mão datalab-to/indra 1:30 #7 net-merge: usa Wi-Fi, cabo e celular ao mesmo tempo, somando a velocidade das conexões (1,8 mil estrelas) rohit267/net-merge 1:40 #6 opendesk: central de atendimento open source com e-mail, chat do site e base de ajuda numa caixa só useopendesk/opendesk 1:50 #5 editonny: skill para Claude Code e Codex que edita vídeo por conversa: corta pausas, legenda e arruma o áudio soumatheusgomes/editonny 2:00 #4 Desigma: alternativa gratuita e offline ao Figma, feita em Rust, que importa arquivos do Figma deepfounder-ai/desigma 2:10 #3 Sill: qualquer janela do Mac no iPhone ou iPad, com toque, teclado e Apple Pencil, sem conta nem servidor (3,9 mil estrelas) Saffsanity/sill 2:20 #2 cleanyourtv: tira anúncios e apps de fábrica da TV pelo Wi-Fi, de forma reversível (24,8 mil estrelas) Gathin23/cleanyourtv 2:30 Oferecimento Hallen Tech 2:44 #1 Filee: conversor de arquivos offline: segure uma tecla, arraste e converta entre 255 formatos (10,3 mil estrelas) KnifeLemon/Filee 2:54 Encerramento 🧡 Oferecimento: Hallen Tech, liderança de tecnologia sob demanda, software, cloud e segurança para a sua empresa. Site: hallentech.com E-mail: contato@hallentech.com Instagram: instagram.com LinkedIn da Hallen Tech: linkedin.com LinkedIn do Eddwan: linkedin.com Se curtiu, deixa o like, segue o canal e ativa as notificações para a próxima lista. #opensource #github #programacao #ferramentas
Talorys GitHub Overview: Private AI on Cloudflare with Memory and Task Automation talorys by rociiu: rociiu/talorys Talorys is an open-source personal AI agent designed to run inside your Cloudflare account, combining scheduled automations, durable memory, task management, and a streaming chat interface. This overview explains the Node.js 22+ and Cloudflare prerequisites, the npx create-talorys@latest deployment flow, optional semantic recall, OAuth, and local password hashing. It also covers the security tradeoffs—there is no forgot-password button—the 10,000 daily Workers AI neuron limit, token guardrails, WAF troubleshooting, local talorys.json state, and iPhone notification setup. The key takeaway: a single-user edge architecture can keep personal tasks and memories under one owner’s control, but it remains tied to Cloudflare quotas and services. TimeStamps: 0:00 Why a private personal AI agent 0:16 Talorys on Cloudflare 0:32 Prerequisites and self-hosted tradeoffs 0:57 CLI deployment and optional semantic recall 1:19 OAuth, local password hashing, and access 1:50 End-to-end task flow in the interface 2:56 403 recovery and the serverless architecture 3:30 Workers AI neuron limits 3:46 Token guardrails in Settings 4:39 Local talorys files and the update anchor 5:02 iPhone notifications and single-user control 🔐 Local password hashing and single-user access ☁️ Cloudflare edge architecture, Durable Objects, and Workers AI 🧠 Semantic recall, memory, tasks, and scheduled automations 📱 Quotas, maintenance files, and iPhone notifications For viewers comparing self-hosted AI options, Talorys is best understood as a focused single-user Cloudflare deployment: convenient managed edge primitives, privacy-oriented credential handling, and built-in tasks and memory, balanced against Workers AI quotas, Cloudflare dependence, and a no-recovery-password model. Check the repository’s current documentation before deploying or updating. #Talorys #Cloudflare #PersonalAI [de-DE] YNAS ynp_dd5ea2b365601887 Cinematic Privater automatisierter Staging-Upload. Paketidentität: ynp_dd5ea2b365601887; Ausgabe: cinematic. [es-US] YNAS ynp_dd5ea2b365601887 cinemático Carga de entorno de prueba de automatización privada. Identidad del paquete: ynp_dd5ea2b365601887; salida: cinemática. [fr-FR] YNAS ynp_dd5ea2b365601887 cinématique Téléchargement de l'environnement de test d'automatisation privé. Identifiant du package : ynp_dd5ea2b365601887 ; sortie : cinématique. [hi] YNAS ynp_dd5ea2b365601887 सिनेमाई निजी स्वचालन स्टेजिंग अपलोड। पैकेज पहचान: ynp_dd5ea2b365601887; आउटपुट: सिनेमाई। [id] YNAS ynp_dd5ea2b365601887 sinematik Unggahan staging otomatisasi pribadi. Identitas paket: ynp_dd5ea2b365601887; output: sinematik. [it] YNAS ynp_dd5ea2b365601887 cinematic Caricamento di automazione privata. Identità del pacchetto: ynp_dd5ea2b365601887; output: cinematico. [pt-BR] YNAS ynp_dd5ea2b365601887 cinemático Upload de teste de automação privada. Identificação do pacote: ynp_dd5ea2b365601887; saída: cinemática.
Top 10 Trending AI GitHub Tools (#1 Runs Agent Teams Like You Own Them) Ten open-source AI tools trending this week: agents moved their infrastructure in-house. This countdown spans from local inference engines to the framework where agents run as persistent, networked teams that organize themselves. ds4 (ten) runs DeepSeek V4 Flash on a MacBook at 39 tokens per second by streaming transformer layers from disk instead of forcing them all into memory at once. Ollama (nine) packages any GGUF model with a single command. Text-to-CAD (eight) generates real mechanical CAD files, exportable to STEP, STL, and 3MF formats. Ponytail cuts code by 54 percent (seven). God is Eye View brings satellite, flight, ship, and earthquake data into a 3D globe with 28 voice commands (six). HyperFrames renders MP4 from HTML deterministically (five). OpenMontage is a complete agentic video studio with 12 pipelines and 700-plus skills (four). Multica treats agents as teammates (three). Talorys runs on the free Cloudflare tier (two). At number one, OpenRig boots persistent agent teams from YAML with stable seats and recoverable state across reboots. Projects in this video: ds4: antirez/ds4 Ollama: ollama/ollama Text-to-CAD: earthtojake/text-to-cad ponytail: DietrichGebert/ponytail God's Eye View: JasimAli75/gods-eye-view HyperFrames: heygen-com/hyperframes OpenMontage: brandeins11/OpenMontage multica: multica-ai/multica Talorys: rociiu/talorys OpenRig: smota/openrig 0:00 Intro 1:00 #10 ds4 2:17 #9 Ollama 3:29 #8 Text-to-CAD 4:42 #7 ponytail 5:48 #6 God's Eye View 7:04 #5 HyperFrames 8:31 #4 OpenMontage 9:50 #3 multica 11:06 #2 Talorys 12:32 #1 OpenRig 14:07 Outro Contact: digestibleinfohub@gmail.com #OpenRig #AI #GitHub #OpenSource #DevTools
Топ-10 GitHub за 3 дня: схемы для Claude и поиск по Mac Обзор: топ-10 новых репозиториев GitHub за 8–11 октября 2026 — open-source проекты, которые быстрее всех набрали звёзды. В выпуске: скилл Claude Code для изометрических схем, быстрый поиск файлов на macOS и сервис Anthropic для проверки open-source на уязвимости. 1. wheresryan22/anatomy — Скилл Claude Code: превращает идею в интерактивную изометрическую схему устройства. (JavaScript, +2788 ★) 2. noahdunnagan/fsearch — Поиск файлов по всему диску macOS: по имени, с опечатками и по тексту внутри. (Rust, +1842 ★) 3. storytold/craft-launcher — Лаунчер ArtCraft: ставит и обновляет приложения пакета Craft, от PhotoCraft до CADCraft. (Rust, +1066 ★) 4. ARahim3/DigUp — Поиск по файлам Mac по смыслу: фото, PDF, записи и видео находятся по описанию. (Swift, +806 ★) 5. anthropics/oss-scanner — Сервис Anthropic: проверяет критичные open-source проекты на уязвимости. (Dockerfile, +781 ★) 6. marclou/mailcheap — Рассылки на своём сервере через Amazon SES: редактор, список, формы, архив выпусков. (JavaScript, +742 ★) 7. ThariqS/ai-newtab — Расширение Chrome: агент Claude собирает новую вкладку по вашей истории и страницам. (TypeScript, +730 ★) 8. rociiu/talorys — Личный ИИ-ассистент в вашем аккаунте Cloudflare: чат, память, задачи, напоминания. (TypeScript, +728 ★) 9. ToiCF/CF-Workers-TGProxy — Прокси для Telegram на Cloudflare Workers: ретранслирует WebSocket-трафик клиента. (+711 ★) 10. wesbos/photo-frame-dashboard — Заметки и скрипты: ADB, root и свои приложения на запертых Android-фоторамках. (Python, +704 ★) Источник: GitHub Search API, репозитории созданы с 2026-10-08, отсортированы по звёздам. Лидер: wheresryan22/anatomy Остальные: noahdunnagan/fsearch, storytold/craft-launcher, ARahim3/DigUp, anthropics/oss-scanner, marclou/mailcheap, ThariqS/ai-newtab, rociiu/talorys, ToiCF/CF-Workers-TGProxy, wesbos/photo-frame-dashboard #GitHub #opensource #программирование Каждые 3 дня — 10 новых open-source проектов GitHub, быстрее всех набравших звёзды. Подписывайся, чтобы не пропустить следующий выпуск.
Talorys: A Personal AI Agent in Your Own Cloudflare Account _A closer look at the open-source project_ _rociiu/talorys_ Many AI assistants follow the same pattern. You sign up, hand your conversations to someone else's servers, and trust that your notes, tasks and personal details are handled well. Talorys takes the opposite approach. It is a personal AI agent that runs entirely inside your own Cloudflare account, with no server, database or account operated by its developers. The pitch is short: one person, one Cloudflare account, one command. npx create-talorys@latest What you get Talorys is a small, focused assistant rather than a sprawling platform. Out of the box it includes: - Chat with streaming responses, Markdown rendering and indicators that show when the agent is using a tool. - Memory for durable facts and preferences. You can view, edit and delete everything it remembers, and only the most relevant memories are sent to the model on each turn. - Tasks, notes and projects with full create, read, update and delete in the UI. You can also manage them from chat, for example by saying "Add a task to review my project tomorrow." - Automations such as one-time and recurring reminders, daily task digests and optional AI routines, all delivered to an in-app notification center. It is single-user by design. There is no signup, no teams and no accounts. The installer asks you to set an owner password, and you sign in from any device with it. One detail I like: it works without AI. If Workers AI is unavailable or you have used up your free daily quota, tasks, notes, memories and reminders keep working. Only chat pauses until the quota resets. Deploying in one command The installer does the tedious parts for you. It checks your Node.js version (20.18 or newer), verifies your Cloudflare login (or opens Cloudflare's authorization page in your browser), and lets you pick an account and an agent name. It then asks for an owner password, which is hashed locally with PBKDF2-SHA256 and stored only as a Cloudflare secret. From there it generates a session secret, deploys a private Worker along with its SQLite-backed Durable Object, creates the Pages project, and verifies the live deployment before printing your pages.dev URL. The verification step checks the frontend, the auth endpoint and storage health without running any AI inference. Here is the whole run at a glance, split by where each step happens: !Mermaid Diagram The installer is also forgiving. If it gets interrupted, you run the same command again and it reconciles what already exists, with no duplicate resources and no data deleted. When you want the latest version later, npx create-talorys@latest update redeploys to the same resources and keeps your password and sessions. There are also status and doctor commands, plus a reset-password command if you get locked out. How it works under the hood The architecture is lean, and it shows how far Cloudflare's platform can go on its own: !Mermaid Diagram A few design choices stand out: - The agent has no public URL. The Worker is deployed with workers_dev and preview URLs turned off. Your browser only talks to the Pages site, whose /api function forwards requests over a service binding. - Auth happens in the Worker, not the frontend. Sessions ride in an HttpOnly, SameSite=Strict cookie, the database stores only a keyed hash of each session token, and five failed logins from one IP within 15 minutes lock that client out. - All state lives in one SQLite-backed Durable Object. Conversations, memories, tasks, notes, projects, automations, sessions and usage data share a single store. - Scheduling uses Durable Object alarms. Reminders and routines fire without anything having to stay online. Per the architecture doc, each enabled automation holds one pending schedule, and a run missed by less than 24 hours still executes once. One automation cycles like this, with nothing staying online in between: !Mermaid Diagram On the AI side, chat runs on Workers AI using the @cf/zai-org/glm-4.7-flash model, with streaming and tool calling. Responses stream as Server-Sent Events from end to end, and reasoning is switched off to conserve Workers AI Neurons. Models sit behind a small provider interface, so adding another provider means implementing it in code rather than flipping a setting. The agent's tools are tightly scoped, too. According to the security doc, destructive actions such as deleting a task or note need explicit confirmation in your latest message, enforced in code rather than only in the prompt. Scheduled AI runs get read-only tools plus a notify tool, and there are no shell, code-execution or outbound-HTTP tools at all. Free-tier friendly, with honest caveats Talorys is built to fit within the Cloudflare Workers Free plan. It uses only Pages, Workers, SQLite Durable Objects and Workers AI, and it does not provision R2, D1, KV, Vectorize or any paid service. The README is refreshingly candid that this is not "unlimited free." Cloudflare sets account-level quotas, including a daily Workers AI allocation, and those can change. When the AI allocation runs out, chat tells you clearly and resumes after the daily reset. If your account is on a paid plan, usage beyond the included amounts is billed by Cloudflare. To keep usage predictable, there are adjustable guardrails in Settings → AI: maximum output tokens, maximum context tokens (older history gets summarized), limits on tool calls and reasoning steps per request, and daily caps on AI requests and scheduled AI runs. Simple reminders and task digests never touch the model at all. Privacy and data ownership Talorys includes no telemetry, analytics, tracking or advertising code, and it sends nothing to its developers. Your data sits in your own Cloudflare account. One thing to keep in mind is that Cloudflare itself processes your data to provide its services. That includes running Workers AI inference on your chat messages and the relevant memories included in each prompt. "Self-hosted on Cloudflare" is not the same as "never leaves your machine," so it is worth reading Cloudflare's privacy policy and Workers AI terms. You also keep an exit. Settings → Privacy → Download backup exports conversations, memories, tasks, notes, projects, settings and automations as a single JSON file, never sessions or credentials. Importing validates the file and merges it in one transaction, so restoring the same backup twice is harmless. Trying it locally If you would rather poke around before deploying, local development needs only Node.js 20.18 or newer: git clone https://github.com/rociiu/talorys.git cd talorys npm install npm run dev This starts the agent Worker, the Pages Function proxy and the Vite UI together, using a deterministic mock AI provider, so no Cloudflare login is required. The repo is a TypeScript monorepo with a Hono-based agent app, a React and Vite frontend, shared Zod schemas, the installer package, and Playwright end-to-end tests. Who is it for? Talorys fits people who want a private, low-maintenance assistant without running servers or paying for yet another subscription, and who already have, or are happy to create, a Cloudflare account. It is also a useful reference for anyone curious about building agents on Durable Objects, alarms and Workers AI. A few things to weigh before adopting it. It is a small project so far, with 10 commits and 10 stars at the time of writing. It is deliberately single-user, so it will not suit teams. And chat quality depends on the Workers AI model it uses by default (GLM-4.7-flash) rather than a frontier model you pick yourself. Still, the core idea is compelling: a personal agent you deploy in minutes, own completely, and can export or tear down whenever you like. If that appeals to you, the repository is at rociiu/talorys and it is MIT licensed. --- Published via ZyVOP — Write once in Markdown, auto-backup to GitHub, and syndicate to Dev.to, Medium & Hashnode in 1 click.
**A Free Cloud AI** If you would like an AI “personal agent” but don’t want your data on some opaque cloud computer, there’s a new option that appears to be somewhat nicer: [rociiu] has talorys, an AI agent that runs in your Cloudflare account. True, it is […] [Original post on poliverso.org]
Talorys: a self-hosted personal AI agent running on Cloudflare's free tier. No excuses left for not shipping your own agent. rociiu/talorys
Talorys – A self-hosted personal AI agent on Cloudflare's free tier rociiu/talorys (news.ycombinator.com)
Cloudflare Workers AI Free Tier Can Run Out in 35 Messages. I Did the Math. With Talorys's default settings, a long conversation can use up Cloudflare's free AI allowance in about 35 messages. On short chats you get closer to 550 model calls a day. Both numbers come from the same 10,000 free Workers AI "neurons". Talorys is an MIT-licensed personal agent that showed up on HN this week, and it's built to live inside that allowance: chat, memory, tasks, notes and reminders, with no VPS, subscription or paid database behind it. I cloned it, built it, ran it locally and checked the neuron math against Cloudflare's own price sheet. The free tier is real, but it's smaller than "$0/month" makes it sound, and CPU, requests and storage aren't what runs out first. What you actually get Talorys is one Cloudflare account, one owner, one agent. The architecture from the README: Browser ──HTTPS──▶ Cloudflare Pages (React app + /api Pages Function) │ service binding (no public URL) ▼ Private Worker (Hono router) ▼ TalorysAgent (Agents SDK Durable Object) ├─ SQLite: conversations, memories, tasks, notes, ... ├─ Workers AI: @cf/zai-org/glm-4.7-flash └─ Alarms: reminders and recurring schedules All your data sits in a single SQLite-backed Durable Object called personal-agent. The Worker is deployed with workers_dev: false and preview_urls: false, so the only public surface is your *.pages.dev site. Auth happens in the Worker; the password is hashed with PBKDF2-SHA256 and stored as a Cloudflare secret. No R2, D1, KV or Vectorize gets provisioned. The agent has 22 tools in v0.1.2: create_task, update_task, remember, search_memories, create_reminder, create_automation, notify_owner, create_note, update_note, create_project and so on. It has no web access. The search tool searches your own tasks, notes, memories and past conversations, not the internet. What you get is a very well-built personal organizer with an LLM front end, so if you were picturing an agent that browses and books things for you, keep looking. Deploying it The whole install is one command: npx create-talorys@latest It checks your Node version (v0.1.2 accepted 20.18+, but the README now requires Node 22+ because the bundled Wrangler needs it), opens Cloudflare's OAuth page, asks you for an owner password, deploys the private Worker plus its Durable Object, creates the Pages project with the service binding, runs health checks that deliberately skip AI inference, and prints your URL. If it dies halfway through, run the same command again and it picks up where it stopped. It doesn't delete anything. Later you'll use: npx create-talorys@latest update npx create-talorys@latest doctor npx create-talorys@latest reset-password For CI or a headless box: TALORYS_OWNER_PASSWORD=... npx create-talorys@latest --yes --account-id <id> with CLOUDFLARE_API_TOKEN set. What I ran I didn't push it to a Cloudflare account for this post, so I can't show you a dashboard screenshot. What I did: git clone https://github.com/rociiu/talorys.git cd talorys npm ci npm run build npm test npm run dev The test suites passed (14 + 58 + 3 + 32 tests). One create-talorys test file fails if you run tests before npm run build, because it looks for the built Worker template. Build first. npm run dev starts wrangler dev on 8787, wrangler pages dev on 8788 and Vite on 5173, using a deterministic mock model, so you don't need a Cloudflare login. I logged in with the dev password and sent "Add a task to review my Cloudflare bill tomorrow" through /api/chat. The SSE stream showed a create_task tool call, then the reply, in 0.249s. /api/tasks had the new row. /api/usage reported 1 AI request, 370 input tokens and 13 output tokens. Remember the mock: that 370 is Talorys's own ~4-chars-per-token estimate of system prompt plus message. It leaves out the JSON schemas for all 22 tools, which a real model call has to send, so real calls are heavier. The math nobody in the HN thread finished Most of the HN discussion was an argument over whether "self-hosted" is the right word, and only a few people posted numbers. One commenter said they spent 500 neurons in a few minutes of chatting and guessed the free 10,000 would cover "maybe 20-30 minutes of back and forth." Another linked the price sheet to put the whole 10k at about $0.11, but nobody worked out what that buys in messages, so here's the Workers AI pricing page applied to Talorys's defaults: - glm-4.7-flash input: 5,500 neurons per million tokens - output: 36,400 neurons per million tokens - free: 10,000 neurons/day, reset at 00:00 UTC - above that, on Workers Paid: $0.011 per 1,000 neurons The defaults in packages/shared/src/constants.ts are maxContextTokens: 6000, maxOutputTokens: 1024, maxAgentIterations: 4, maxAiRequestsPerDay: 200. | Scenario per model call | Neurons | Calls per free day | | --- | --- | --- | | Short chat: 2,000 in / 200 out | ~18 | ~550 | | Full context: 6,000 in / 1,024 out | ~70 | ~140 | | Full context, 4 agent iterations | ~280 per message | ~35 messages | Output costs about 6.6x what input costs per token, so long replies drain the budget much faster than long history. The default cap of 200 AI requests/day multiplied by ~70 neurons is 14,000, which is more than the free allocation. On a long-running conversation, the app's own guardrail won't stop you before Cloudflare does. On the Free plan you can't be billed, so going over just means chat returns an "allocation used for today" error until 00:00 UTC, and tasks, notes and plain reminders keep working because they never touch the model. If you're on Workers Paid, the overage is real money, but tiny: the entire 10k free allocation would cost $0.11 at list price. The other limits are nowhere close for one person. Workers Free gives you 100,000 requests/day and 10 ms of CPU per request, and time spent waiting on inference doesn't count as CPU. Durable Objects on Free get 100,000 requests, 13,000 GB-s, 5M rows read and 100,000 rows written per day, with 5 GB of storage. You won't run out of any of those by managing your own to-do list. The neuron budget is the binding constraint: around 35 to 550 model calls a day, depending on how you use it. Settings I'd change on day one Go to Settings → AI and: 1. Lower maxOutputTokens from 1024 to around 400. Output is the expensive side, and a personal assistant rarely needs a 1,000-token answer. 2. Lower maxContextTokens from 6000 to 3000 or 4000. Older history gets summarized, so you lose less than you'd expect. 3. Set maxAiRequestsPerDay to something your neuron math supports, like 100, so the app hits its own limit before Cloudflare's. 4. Leave maxScheduledAiRunsPerDay at 6 unless you really want AI routines. Plain reminder and task_digest automations run on Durable Object alarms and cost zero neurons. Only agent_prompt calls the model. Also, the in-app Usage panel is an estimate, and it says so. The actual neuron count lives in the Cloudflare dashboard under Workers AI. Look there once a week for the first month. Is it "self-hosted"? No. Does that matter? The most common HN complaint was the label. "Selfhosted on cloudflare is a great oxymoron," one commenter wrote, and others offered "self-managed" and "self-hosted but not self-owned" instead. They're right. Your data sits in a Durable Object on Cloudflare's hardware, Cloudflare runs inference on your messages, and the storage layer won't move to a VPS without a rewrite. I still think it's the more interesting design. The usual self-hosted AI setup is a $5-10 VPS you patch yourself plus an API key for someone's model. Talorys trades the VPS for a free account, a scale-to-zero object and alarms that fire whether or not anything is "running." The model layer is the easy part to swap: one commenter said they'd replaced Workers AI in Cloudflare's own agents example apps with a local whisperfile binary in about 5 minutes, another estimated pointing it at a local model server is under 20 minutes of work, and the provider interface in apps/agent/src/ai/provider.ts is small. The Durable Object is where the real lock-in is, and I can't wave that away. The backup export (talorys-backup.json, Settings → Privacy) is what keeps that lock-in tolerable. Download it on a schedule. Who should bother If you want a private tasks/notes/memory app you can talk to, with a hard spending cap of zero, this is the cleanest version of that idea I've seen. If you want an agent that does things in the outside world, you'll be writing tools, and each tool call is another round trip through your neuron budget. So, for anyone already running a personal agent: what does it do for you every day, and how many model calls does that actually take? I'd like to know if 35 full-context messages is plenty or a joke. Sources - Talorys repo, v0.1.2: rociiu/talorys - HN discussion: news.ycombinator.com - Workers AI pricing: developers.cloudflare.com - Workers limits: developers.cloudflare.com - Durable Objects pricing: developers.cloudflare.com