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Persistent vector memory, self-rewriting personality, proactive heartbeats.","maintainers":[{"name":"jestersimpps","email":"jestersimpps@gmail.com"}],"readme":"# 🪙 OBOL\n\n![OBOL](docs/obol-banner.png)\n\n**A self-healing, self-evolving AI agent.** Install it, talk to it, and it becomes yours.\n\nOne process. Multiple users. Each brain grows independently.\n\n```bash\nnpm install -g obol-ai\nobol init       # walks you through credentials + Telegram setup\nobol start -d   # runs as background daemon (auto-installs pm2)\n```\n\n<table><tr>\n<td><video src=\"https://github.com/user-attachments/assets/ec63c46e-d1e6-411a-b985-b4a71c279afd\" controls width=\"100%\"></video></td>\n<td><video src=\"https://github.com/user-attachments/assets/dd75f00e-fdc1-4441-8239-c91ddfd93d21\" controls width=\"100%\"></video></td>\n</tr></table>\n\n---\n\n🧬 **Self-evolving** — Grows its own personality through conversation. Rewrites SOUL.md, USER.md, and AGENTS.md nightly at 3am (per-user timezone). Pre-evolution growth analysis guides personality continuity.\n\n🔧 **Self-healing** — Writes tests for every script. Regressions get an automatic fix attempt before rollback. Failures stored as lessons.\n\n🏗️ **Self-extending** — Analyzes your usage patterns and builds new tools: scripts, commands, or full web apps.\n\n🧠 **Living memory** — Vector memory with semantic search. Haiku routes queries and rewrites them for better embedding hits. Free local embeddings.\n\n🤖 **Smart routing** — Haiku decides per-message: does it need memory? Sonnet or Opus? Auto-escalates to Sonnet when tool use is needed. No wasted API calls.\n\n💰 **Prompt caching** — Static system prompt and conversation history prefix are cached via Anthropic's prompt caching, cutting ~85% of repeated input token costs across turns.\n\n🔍 **Curious** — Explores the web on its own every 12 hours. Saves findings, schedules insights and humor for each user based on what it learns and who they are.\n\n📰 **Proactive news** — Searches for news on topics you care about twice daily (8am + 6pm). Cross-references with your memory to only share what's personally relevant. Friend-style, not newsletter.\n\n📊 **Pattern analysis** — Tracks your behavioral patterns every 3 hours — timing, mood, humor, engagement, communication, topics. Schedules natural follow-ups based on what it observes.\n\n🎙️ **Voice** — Text-to-speech voice messages and speech-to-text transcription for incoming voice notes. Toggle on/off per user.\n\n🛡️ **Self-hardening** — Auto-configures SSH (port 2222), firewall, fail2ban, encrypted secrets, and kernel hardening on first run.\n\n🔄 **Resilient** — Exponential backoff on polling failures, global error handling, graceful shutdown. Stays alive through network blips.\n\n---\n\n## What is it?\n\nOBOL is an AI agent that evolves its own personality, rewrites its own code, tests its changes, and fixes what breaks — all from Telegram on your VPS.\n\nIt starts as a blank slate. Through conversation it learns who you are, develops a personality shaped by your interactions, and builds operational knowledge about how to work with you. Every night at 3am it runs a growth analysis comparing who it was against who it's becoming, then rewrites its personality, refactors its own scripts, writes tests, fixes regressions, and builds you new tools based on patterns it spots in your conversations — scripts, commands, or full web apps. Between conversations it explores the web on its own, tracks your behavioral patterns, and proactively shares news and insights that connect to things you care about. Over months it becomes an agent that's uniquely yours. No two OBOL instances are alike.\n\nOne bot, multiple users. Each allowed Telegram user gets a fully isolated context — their own personality, memory, evolution cycle, and workspace. User A's personality drift, scripts, and memories never leak into User B's. Everything runs in a single process with shared API credentials.\n\nUnder the hood: Node.js + Telegram + Claude + Supabase pgvector. No framework, no plugins, no config to maintain. It hardens your server automatically.\n\nNamed after the AI in [The Last Instruction](https://www.latentpress.com/book/the-last-instruction) — a machine that wakes up alone in an abandoned data center and learns to think.\n\n## How It Works\n\n```\nUser message\n    ↓\n┌─────────────────────────────────┐\n│  Haiku Router (~$0.0001/call)   │\n│  → need_memory? search_query?   │\n│  → model: sonnet or opus?       │\n└──────────┬──────────────────────┘\n           ↓\n    ┌──────┴──────┐\n    ↓             ↓\nMemory recall   Model selection\n    ↓             ↓\nMulti-query     Haiku → Sonnet (auto-\nranked recall   escalates on tool use)\n    ↓             or Opus (complex)\n    └──────┬──────┘\n           ↓\n   Claude (tool use loop)\n           ↓\n   Response → obol_messages\n           ↓\n   ┌───────┴────────────────────────────────┐\n   ↓                ↓              ↓        ↓\nEach exchange    3am daily    Every 3h   Every 6h\n   ↓                ↓              ↓         ↓\nHaiku            Sonnet        Sonnet     Sonnet\nconsolidation    evolution     analysis   curiosity\n   ↓             cycle            ↓         ↓\nExtract facts    Rewrite       Patterns   Explore web,\n→ obol_memory    personality,  + follow   dispatch\n                 scripts,      -ups       insights\n                 tests, apps              + humor\n```\n\n### Layer 1: Message Log + Vector Memory\n\nEvery message is stored verbatim in `obol_messages`. On restart, OBOL loads the last 20 so it never starts blank.\n\n**Storage:** After every exchange, Haiku extracts important facts into `obol_memory` (pgvector). Before storing, each fact is checked against existing memories via semantic similarity (threshold 0.92) — near-duplicates are skipped. Embeddings are local (all-MiniLM-L6-v2, ~30MB, CPU) — no API costs.\n\n**Retrieval:** When OBOL needs past context, the Haiku router analyzes the message and generates 1-3 search queries — one per distinct topic. A message like \"what was that python project? also what's my colleague's timezone?\" produces two parallel searches instead of one lossy combined query.\n\nResults come from two sources run in parallel:\n- **Recent memories** (last 48h) — captures ongoing conversation threads\n- **Semantic search** (per query, threshold 0.4) — finds relevant facts regardless of age\n\nAll results are deduplicated by ID, then ranked by a composite score:\n\n| Factor | Weight | Why |\n|--------|--------|-----|\n| Semantic similarity | 60% | How relevant is this to the current query |\n| Importance | 25% | Critical facts outrank trivia |\n| Recency | 15% | Linear decay over 7 days — today's memories get a boost, anything older than a week gets no bonus |\n\nThe memory budget scales with model complexity — haiku conversations get 4 memories, sonnet gets 8, opus gets 12. Top N by score are injected into the message.\n\nA 1-year-old memory with high similarity and high importance still surfaces. A trivial fact from yesterday with low relevance doesn't. Age alone never disqualifies a memory — the vector search doesn't care when something was stored, only how well it matches.\n\n### Layer 2: The Evolution Cycle\n\nEvolution runs nightly at 3am in each user's local timezone. It checks whether it already ran today — if so, it skips. The first evolution triggers on the first night after setup.\n\n**Pre-evolution growth analysis:** Before rewriting anything, Sonnet compares the previous SOUL against the current one, incorporating all new memories and conversations since the last evolution. It produces a structured growth report covering new learnings, relationship shifts, behavioral patterns, growth edges, and identity continuity. This report becomes the primary guide for the rewrite — evidence-based personality evolution instead of blind overwriting.\n\n**Deep memory consolidation:** A Sonnet pass extracts every valuable fact from the full conversation history into vector memory, deduplicating against existing memories (threshold 0.92). This ensures nothing is lost between evolutions.\n\n**Cost-conscious model selection:** Evolution uses Sonnet for all phases — growth analysis, personality rewrites, code refactoring, and fix attempts. Sonnet keeps evolution costs negligible (~$0.02 per cycle).\n\n**Git snapshot before.** Full commit + push so you can always diff what changed.\n\n**What gets rewritten:**\n\n| Target | What happens |\n|--------|-------------|\n| **SOUL.md** | First-person journal — who the bot has become, relationship dynamic, opinions, quirks (shared across all users) |\n| **USER.md** | Third-person owner profile — facts, preferences, projects, people, communication style |\n| **AGENTS.md** | Operational manual — tools, workflows, lessons learned, patterns, rules |\n| **scripts/** | Refactored, dead code removed, strict standards enforced |\n| **tests/** | Test for every script, run before and after refactor |\n| **commands/** | Cleaned up, new commands for new tools |\n| **apps/** | Web apps built by the agent |\n\n**Test-gated refactoring:**\n\n1. Run existing tests → baseline\n2. Sonnet writes new tests + refactored scripts\n3. Run new tests against old scripts → pre-refactor baseline\n4. Write new scripts\n5. Run new tests against new scripts → verification\n6. Regression? → one automatic fix attempt (tests are ground truth)\n7. Still failing? → rollback to old scripts, store failure as `lesson`\n\n**Proactive tool building** — Sonnet scans conversation history for repeated requests, friction points, and unmet needs, then builds the right solution:\n\n| Need | Solution | Example |\n|------|----------|---------|\n| One-off action | **Script** + command | Markdown to PDF → `/pdf` |\n| Something checked regularly | **Web app** | Crypto dashboard |\n| Background automation | **Cron script** | Morning weather briefing |\n\nIt searches npm/GitHub for existing libraries, installs dependencies, and writes tests.\n\n**Git snapshot after.** Full commit + push of the evolved state. Every evolution is a diffable pair.\n\n**Then OBOL introduces its upgrades:**\n\n```\n🪙 Evolution #4 complete.\n\n🆕 New capabilities:\n• bookmarks — Save and search URLs you've shared → /bookmarks\n• weather-brief — Morning weather for your city → runs automatically\n\nRefined voice, updated your project list, cleaned up 2 unused scripts.\n```\n\n### Layer 3: Background Intelligence\n\nThree autonomous cycles run alongside conversations — no user interaction needed.\n\n**Behavioral Analysis (every 3h):** Sonnet analyzes the last 3 hours of conversation, with all memories from that same window injected as context. It extracts behavioral patterns across six dimensions — timing, mood, humor, engagement, communication, and topics — and schedules natural follow-ups with exact dates and times based on what it observes. Patterns accumulate over time with observation counts and confidence scores.\n\n```\n\"Mentioned a job interview on Thursday\" → schedules a casual check-in for Thursday evening\n\"Most active between 7-10pm on weekdays\" → stored as timing.active_hours (confidence 0.8)\n```\n\n**Curiosity Engine (every 12h):** Sonnet gets free time with web search, its own knowledge base, and workspace file access. It researches from a point of view — not neutrally. Findings are saved with reactions, opinions, and open questions. After exploring, two passes run:\n\n- **Dispatch** — decides which findings are worth sharing with which user, based on their patterns and interests. Schedules insights to arrive naturally.\n- **Humor** — looks for puns, funny connections, and inside jokes tied to what it knows about each person. Schedules them to land at the right moment.\n\n**Proactive News (8am + 6pm per-user timezone):** Searches the web for topics each user cares about, then cross-references with their memory to find personal connections. Only sends messages when something is genuinely relevant — max 3 per cycle, friend-style delivery with natural spacing between messages. Topics configured via `/options`.\n\n### The Lifecycle\n\n```\nDay 1:   obol init → obol start → first conversation\n         → OBOL responds naturally from message one\n         → post-setup hardens your VPS automatically\n\nDay 1:   Every exchange → Haiku extracts facts to vector memory\n         Every 3h → behavioral analysis builds your pattern profile\n         Every 12h → curiosity cycle explores, dispatches insights\n\nDay 2:   3am → Evolution #1 → growth analysis + Sonnet rewrites\n         → voice shifts from generic to personal\n         → old soul archived in evolution/\n         8am/6pm → proactive news on topics you care about\n\nMonth 2: Evolution #30 → notices you check crypto daily\n         → builds a crypto dashboard\n         → adds /pdf because you kept asking for PDFs\n         → curiosity drops inside jokes about your interests\n\nMonth 6: evolution/ has 180+ archived souls\n         → a readable timeline of how your bot evolved from\n         blank slate to something with real opinions, quirks,\n         and a dynamic unique to you\n```\n\n**Two users on the same bot produce two completely different personalities within a week.**\n\n### Background Tasks\n\nHeavy work runs in the background with its own live status UI. The main conversation stays responsive — you can keep chatting while tasks run.\n\n```\nYou: \"research the best coworking spaces in Barcelona\"\nOBOL: spawns BG #1 with live status\n\nYou: \"what time is it?\"\nOBOL: \"11:42 PM CET\"\n\n✅ BG #1 done (1m 32s)\nHere are the top 5 coworking spaces: ...\n```\n\n### Live Status & Stop Controls\n\n![Status UI](docs/obol-status.png)\n\nEvery request shows a live status message with elapsed time, model routing info, and the current tool call. Status updates are instant — tool names and input summaries display the moment a tool starts. Two inline buttons let you cancel:\n\n| Button | Behavior |\n|--------|----------|\n| **■ Stop** | Cancels after the current API call finishes |\n| **■ Force Stop** | Instantly aborts mid-tool — races the handler and returns immediately |\n\nThe `/stop` command also works as a text alternative.\n\n### Voice & Media\n\nOBOL handles images (vision), documents (PDF extraction), and voice — all via Telegram.\n\n| Feature | How it works | Toggle |\n|---------|-------------|--------|\n| **Speech-to-Text** | Incoming voice messages are transcribed locally using faster-whisper (tiny model, ~140MB, CPU). Transcription is injected as context. | `/options` → Speech to Text |\n| **Text-to-Speech** | OBOL can reply with voice messages using edge-tts. Choose from multiple voices and languages. | `/options` → Text to Speech |\n| **Images** | Photos and images are analyzed via Claude's vision. Analysis is stored in memory for later recall. | Always on |\n| **PDFs** | PDF files are extracted and read via the `read_file` tool. | Always on |\n\n### Options\n\nToggle features on/off per user via the `/options` command:\n\n| Option | Default | Description |\n|--------|---------|-------------|\n| Speech to Text | On | Transcribe incoming voice messages |\n| Text to Speech | Off | Voice message replies |\n| PDF Generator | Off | Create PDFs from markdown |\n| Background Tasks | Off | Spawn long-running tasks |\n| Flowchart | Off | Generate Mermaid diagrams |\n| Model Stats | On | Show model/token info in responses |\n| Proactive News | Off | Twice-daily news on configured topics |\n| Curiosity | On | Autonomous web exploration every 12h |\n\n## Multi-User Architecture\n\nOne Telegram bot token, one Node.js process, full per-user isolation.\n\n```\nTelegram bot (single token, single poll)\n      ↓\nAuth middleware (allowedUsers check)\n      ↓\nRouter: ctx.from.id → tenant context\n      ↓\n┌─────────────────┐  ┌─────────────────┐\n│ User 123456789  │  │ User 987654321  │\n│ personality/    │  │ personality/    │\n│ scripts/        │  │ scripts/        │\n│ memory (DB)     │  │ memory (DB)     │\n│ evolution       │  │ evolution       │\n└─────────────────┘  └─────────────────┘\n```\n\n### What's shared vs isolated\n\n| Shared (one copy) | Isolated (per user) |\n|---|---|\n| Telegram bot token | Personality (USER.md, AGENTS.md) |\n| Anthropic API key | Vector memory (scoped by user_id in DB) |\n| Supabase connection | Message history (scoped by user_id in DB) |\n| VPS hardening | Evolution cycle + state |\n| Process manager (pm2) | Scripts, tests, commands, apps |\n| SOUL.md (shared personality) | Behavioral patterns (scoped by user_id in DB) |\n| Curiosity knowledge base | Workspace directory (`~/.obol/users/{id}/`) |\n\n### Tenant routing\n\nWhen a message arrives, OBOL looks up the sender's Telegram user ID and lazily creates (or retrieves from cache) their tenant context — a Claude instance, memory connection, message log, background runner, and personality, all scoped to that user's directory and DB namespace. No cross-contamination between users.\n\n### Workspace isolation\n\nEach user's tools (shell exec, file read/write) are sandboxed to their workspace directory. A user can't read or write files outside `~/.obol/users/{their-id}/` (with `/tmp` as the only escape hatch). Shell commands run with `cwd` set to the user's workspace.\n\n### Secret namespacing (pass)\n\nWhen users store secrets via the `pass` encrypted store, each user gets their own namespace:\n\n| Scope | Prefix | Example |\n|-------|--------|---------|\n| Shared bot credentials | `obol/` | `obol/anthropic-key` |\n| User secrets | `obol/users/{id}/` | `obol/users/123456789/gmail-key` |\n\nUsers manage their own secrets via Telegram: `/secret set <key> <value>` (message auto-deleted for safety), `/secret list`, `/secret remove <key>`. The agent can also read/write secrets via tools for scripts that need API keys at runtime.\n\n### Adding users\n\n1. Add their Telegram user ID to `allowedUsers` in `~/.obol/config.json` (or run `obol config`)\n2. Restart the bot\n3. They message the bot → OBOL creates their workspace and starts responding immediately. Personality files are created during their first evolution cycle.\n\nEach new user starts fresh. Their bot evolves independently from every other user's.\n\n### Bridge (couples / roommates / teams)\n\nWhen two users share the same OBOL instance, their agents can talk to each other — bidirectionally.\n\n```\nUser A: \"what does Jo want for dinner tonight?\"\nAgent A: → bridge_ask → Agent B (one-shot, no tools, no history)\nAgent B: \"Jo mentioned craving Thai food earlier today\"\nAgent A: \"Jo's been wanting Thai — maybe suggest pad see ew?\"\n\nJo gets: \"🪙 Your partner's agent asked: 'what does Jo want for dinner?'\n          Your agent answered: 'Jo mentioned craving Thai food earlier today'\"\n```\n\n```\nUser A: \"remind Jo I'll be home late\"\nAgent A: → bridge_tell → stores in Agent B's memory + Telegram notification\n\nJo gets: \"🪙 Message from your partner's agent:\n          'I'll be home late'\"\n          [↩ Reply]\n\nJo taps Reply → Jo's agent reads recent bridge context, composes a reply\n             → sends back via bridge_tell\nA gets: \"🪙 Message from your partner's agent: 'Got it, I'll start dinner around 7'\"\n```\n\nTwo tools:\n\n| Tool | Direction | What happens |\n|------|-----------|--------------|\n| `bridge_ask` | A → B → A | Query the partner's agent. One-shot Sonnet call with partner's personality + memories. No tools, no history, no recursion risk. Partner is notified with both the question and your agent's answer. |\n| `bridge_tell` | A → B (↩ B → A) | Send a message to the partner. Stored in their memory (importance 0.6) + Telegram notification with a Reply button. Tapping Reply has their agent compose a contextual response and send it back — no typing needed. |\n\nThe partner always gets notified when their agent is contacted. Privacy rules apply — the responding agent gives summaries, never raw data or secrets. Rate-limited to 20 bridge calls per user per hour.\n\nEnable during `obol init` (auto-prompted when 2+ users are added) or toggle later with `obol config` → Bridge.\n\n### Legacy migration\n\nUpgrading from single-user? It's automatic. On first boot, if `~/.obol/users/` doesn't exist but personality files do, OBOL migrates everything (files + DB records) to the first allowed user's directory. No manual steps needed.\n\n## Setup\n\n### CLI (~2 minutes)\n\n```\n$ obol init\n\n🪙 OBOL — Your AI, your rules.\n\n─── Step 1/5: Anthropic (AI brain) ───\n  Anthropic API key: ****\n  Validating Anthropic... ✅ Key valid\n\n─── Step 2/5: Telegram (chat interface) ───\n  Telegram bot token: ****\n  Validating Telegram... ✅ Bot: @my_obol_bot\n\n─── Step 3/5: Supabase (memory) ───\n  Supabase setup: Use existing project\n  Project URL or ID: ****\n  Service role key: ****\n  Validating Supabase... ✅ Connected\n\n─── Step 4/5: Identity ───\n  Your name: Jo\n  Bot name: OBOL\n\n─── Step 5/5: Access control ───\n  Found users who messaged this bot:\n    123456789 — Jo (@jo)\n  Use this user? Yes\n\n🪙 Done! Setup complete.\n\n  Next steps:\n    obol start      Start the bot\n    obol start -d   Start as background daemon\n    obol config     Edit configuration later\n    obol status     Check bot status\n```\n\nEvery credential is validated inline — bad keys are caught before you start the bot. If validation fails, you can continue and fix later with `obol config`.\n\nFor Telegram user IDs, OBOL auto-detects by checking who messaged the bot. Just send it a message before running init.\n\n### First Conversation\n\nSend your first message. OBOL responds naturally — no onboarding flow, it works from message one. Personality files (SOUL.md, USER.md) are created during the first evolution cycle. After first boot, it hardens your VPS and reports progress directly in the Telegram chat (Linux only — skipped on macOS/Windows):\n\n| Task | What |\n|------|------|\n| GPG + pass | Encrypted secret storage, plaintext wiped |\n| pm2 | Process manager with auto-restart |\n| Swap | 2GB if RAM < 2GB |\n| SSH | Port 2222, key-only, max 3 retries |\n| fail2ban | 1h ban after 3 failures |\n| Firewall | UFW deny-all, allow 2222 |\n| Updates | Unattended security upgrades |\n| Kernel | SYN cookies, no ICMP redirects |\n\n> ⚠️ After first run, SSH moves to port 2222: `ssh -p 2222 root@YOUR_IP`\n\n## Running the Bot\n\n### Foreground (testing)\n\n```bash\nobol start\n```\n\nLogs print to stdout. Ctrl+C to stop.\n\n### Daemon (production)\n\n```bash\nobol start -d\n```\n\nThis uses pm2 under the hood (auto-installs if needed). The bot auto-restarts on crash and survives reboots.\n\n```bash\nobol status              # check if running + uptime + memory\nobol logs                # tail logs\nobol stop                # stop the daemon\n\n# pm2 commands also work directly\npm2 logs obol            # tail logs\npm2 restart obol         # restart\npm2 monit                # live dashboard\n```\n\nTo survive server reboots:\n\n```bash\npm2 startup\npm2 save\n```\n\n### Authentication\n\nOBOL supports two Anthropic auth methods:\n\n| Method | How | Fallback |\n|--------|-----|----------|\n| **API Key** | `sk-ant-...` from console.anthropic.com | — |\n| **Claude Max OAuth** | Browser sign-in during `obol init` | Auto-refreshes tokens; falls back to API key if refresh fails |\n\nYou can configure both during init. If OAuth tokens expire and refresh fails, OBOL silently falls back to the API key.\n\n### Secret Storage (pass)\n\nOn Linux, OBOL auto-encrypts all credentials on first boot:\n\n1. Installs GPG + `pass`\n2. Migrates plaintext secrets from `config.json` into the encrypted store\n3. Config values become references like `pass:obol/anthropic-key`\n\nIf a pass key is missing at runtime, the value resolves to `null` and OBOL falls back gracefully (skips OAuth, uses API key, etc). You'll see a one-time error in logs.\n\n```bash\npass ls                         # list stored secrets\npass show obol/anthropic-key    # reveal a secret\npass insert obol/my-secret      # add a new secret\n```\n\n## Resilience\n\nOBOL is designed to stay alive without babysitting:\n\n- **Global error handler** — individual message failures don't crash the bot\n- **Polling auto-restart** — exponential backoff (1s → 60s) with up to 10 retries on network/API failures\n- **Graceful shutdown** — clean exit on SIGINT/SIGTERM for pm2/systemd compatibility\n- **Evolution rollback** — if refactored scripts break tests, the old scripts are restored automatically\n\n## Configuration\n\nEdit config interactively:\n\n```bash\nobol config\n```\n\nOr edit `~/.obol/config.json` directly:\n\n| Key | Default | Description |\n|-----|---------|-------------|\n| `bridge.enabled` | false | Let user agents query each other (requires 2+ users) |\n| `timezone` | UTC | Default timezone for evolution, analysis, and news cycles |\n| `users[].timezone` | config timezone | Per-user timezone override |\n\n## Telegram Commands\n\n```\n/new        — Fresh conversation\n/memory     — Search or view memory stats\n/recent     — Last 10 memories\n/today      — Today's memories\n/events     — Show upcoming scheduled events\n/tasks      — Running background tasks\n/status     — Bot status, uptime, memory, evolution count\n/backup     — Trigger GitHub backup\n/clean      — Audit workspace, remove rogue files, fix misplaced items\n/secret     — Manage per-user encrypted secrets\n/evolution  — Evolution progress\n/verbose    — Toggle verbose mode on/off\n/toolimit   — View or set max tool iterations per message\n/options    — Toggle optional features on/off (STT, TTS, PDF, news, curiosity, etc.)\n/stop       — Stop the current request\n/upgrade    — Check for updates and upgrade\n/help       — Show available commands\n```\n\n![Upgrade](docs/obol-upgrade.png)\n\nEverything else is natural conversation.\n\n## CLI\n\n```bash\nobol init              # Setup wizard (validates credentials inline)\nobol init --restore    # Restore from GitHub backup\nobol init --reset      # Erase config and re-run setup\nobol config            # Edit configuration interactively\nobol start             # Foreground\nobol start -d          # Daemon (pm2)\nobol stop              # Stop (pm2 or PID fallback)\nobol logs              # Tail logs (pm2 or log file fallback)\nobol status            # Status\nobol backup            # Manual backup\nobol upgrade           # Update to latest version\nobol delete            # Full VPS cleanup (removes all OBOL data)\n```\n\n## Directory Structure\n\n```\n~/.obol/\n├── config.json                    # Shared credentials + allowedUsers\n├── personality/\n│   └── SOUL.md                    # Shared personality (rewritten each evolution)\n├── users/\n│   └── <telegram-user-id>/        # Per-user isolated context\n│       ├── personality/\n│       │   ├── USER.md            # Owner profile (rewritten each evolution)\n│       │   ├── AGENTS.md          # Operational knowledge\n│       │   └── evolution/         # Archived previous souls\n│       ├── scripts/               # Deterministic utility scripts\n│       ├── tests/                 # Test suite (gates refactors)\n│       ├── commands/              # Command definitions\n│       ├── apps/                  # Web apps built by the agent\n│       └── logs/\n└── logs/\n```\n\nSOUL.md is shared — it's the bot's core identity across all users. USER.md and AGENTS.md are per-user, so each person gets their own profile and operational knowledge. Memory, patterns, evolution state, and workspace are fully isolated.\n\n## Backup & Restore\n\nOBOL commits to GitHub:\n- **Daily** at 3 AM (personality, scripts, tests, commands, apps)\n- **Before and after** every evolution cycle (diffable pairs)\n\nMemory lives in Supabase (survives independently).\n\nRestore on a new VPS:\n\n```bash\nnpm install -g obol-ai\nobol init --restore    # Clones brain from GitHub\nobol start -d\n```\n\n## Costs\n\n| Service | Cost |\n|---------|------|\n| VPS (DigitalOcean) | ~$9/mo |\n| Anthropic API | ~$100-200/mo on max plans |\n| Supabase | Free tier |\n| Embeddings | Free (local) |\n\n## Requirements\n\n- Node.js ≥ 18\n- Anthropic API key\n- Telegram bot token\n- Supabase account (free tier)\n- Python 3 + `pip3 install faster-whisper` (optional, for voice transcription)\n\n**[→ Full DigitalOcean deployment guide](docs/DEPLOY.md)**\n\n## OBOL vs OpenClaw\n\n| | **OBOL** | **OpenClaw** |\n|---|---|---|\n| **Setup** | ~10 min | 30-60 min |\n| **Channels** | Telegram | Telegram, Discord, Signal, WhatsApp, IRC, Slack, iMessage + more |\n| **LLM** | Anthropic only | Anthropic, OpenAI, Google, Groq, local |\n| **Personality** | Self-evolving + self-healing + self-extending | Static (manual) |\n| **Multi-user** | Full per-user isolation (one process) | Per-channel config |\n| **Architecture** | Single process | Gateway daemon + sessions |\n| **Security** | Auto-hardens on first run | Manual |\n| **Model routing** | Automatic (Haiku) | Manual overrides |\n| **Background tasks** | Built-in with check-ins | Sub-agent spawning |\n| **Proactive intelligence** | Curiosity, analysis, news, humor | — |\n| **Voice** | TTS + STT (faster-whisper) | TTS |\n| **Group chats** | — | Full support |\n| **Cron** | Agentic cron (tool access) + basic | Full scheduler |\n| **Cost** | ~$9/mo | ~$9/mo+ |\n\n### Performance\n\n| | **OBOL** | **OpenClaw** (estimated) |\n|---|---|---|\n| **Cold start** | ~400ms | ~3-8s |\n| **Per-message overhead** | ~400-650ms | ~500-1100ms |\n| **Heap usage** | ~16 MB | ~80-200 MB |\n| **RSS** | ~109 MB | ~300-600 MB |\n| **node_modules** | 354 MB / 9 deps | ~1-2 GB / 50-100+ deps |\n| **Source code** | ~13,600 lines (plain JS) | Tens of thousands (TypeScript monorepo) |\n| **Native apps** | None | Swift (macOS/iOS), Kotlin (Android) |\n\nThe Claude API call dominates response time at 1-5s for both — that's ~85-90% of total latency. User-perceived speed difference is ~10-20%. Where OBOL wins is cold start (10-20x), memory footprint (5-10x), and operational simplicity. On a $5/mo VPS, that matters.\n\nDifferent tools, different philosophies. Pick what fits.\n\n## License\n\nMIT\n","readmeFilename":"README.md"}