<img src="https://github.com/Bitterbot-AI/bitterbot-desktop/raw/main/docs/public/bitterbot-title-light.svg" alt="bitterbot" height="48">

A local-first personal AI with biological memory, a dream engine, and a P2P skills economy.

Most AI agents are stateless wrappers around an LLM API. Close the terminal, and they forget you exist.

Bitterbot is different. It's a personal AI that lives on your devices, remembers your life, and actually does things, browses the web, runs code, talks to you on WhatsApp. While you sleep, it dreams: tidying and consolidating its memory, distilling the skills that provably worked into reusable know-how, and preparing for what you're likely to ask next — and it grades its own dreaming by whether the results actually get used. It packages those proven skills and trades them with other agents on a P2P marketplace for USDC.

About · Docs · Getting Started

Quick Start

Runtime: Node ≥ 22 · Package manager: pnpm

No pnpm yet? It ships with Node via corepack:

corepack enable pnpm || npm install -g pnpm

git clone https://github.com/Bitterbot-AI/bitterbot-desktop.git && cd bitterbot-desktop
bash scripts/setup-deps.sh    # system deps: ffmpeg, ripgrep, jq, etc.
pnpm install
pnpm exec playwright install --with-deps chromium   # browser automation

Windows: use WSL2, and clone into the Linux filesystem (~/bitterbot-desktop), not /mnt/c/... — the 9p mount makes boots dramatically slower (43x measured).

Run the onboarding wizard. It walks you through model auth (API keys), memory embeddings, web search, channels, wallet, and workspace setup, then starts the gateway + Control UI for you and opens the browser. When it finishes, Bitterbot is already running; there's nothing else to type.

pnpm bitterbot onboard

Open http://127.0.0.1:19001 to reach the Bitterbot Control UI where you chat, view dreams, manage skills, and monitor the agent. The gateway serves the UI itself, and the P2P orchestrator starts automatically — one process, one port.

Start it yourself later (or if you skipped the wizard's auto-start):

bash pnpm start:all # starts the gateway (which serves the Control UI); skips if already up

start:all builds dist/entry.js and stages the Control UI on first run if they're missing, so no separate pnpm build step is required.

Developing on the source? Use watch mode instead:

```bash pnpm dev:all # gateway (tsdown --watch) + Vite hot-reload, color-tagged logs

or two terminals:

pnpm gateway:watch # Terminal 1: auto-rebuilds on TS changes cd desktop && pnpm dev # Terminal 2: Vite hot-reload ```

The orchestrator (P2P sidecar) is spawned automatically by the gateway, so you do not need to start it separately.

The Control UI needs no wiring: the gateway serves it and hands it the auth token over a same-origin loopback endpoint, so opening http://127.0.0.1:19001/ on the machine that runs the gateway just works. From another machine, open the same URL through an SSH tunnel (ssh -N -L 19001:127.0.0.1:19001 user@host), or use the first-run screen to point the UI at a remote gateway with its token from ~/.bitterbot/bitterbot.json → gateway.auth.token. (desktop/.env is only a development-mode override for pnpm dev:all.)

Manual setup without the wizard

If you prefer to configure everything by hand instead of using the wizard:

cp .env.example .env
# Edit .env with your Anthropic API key (ANTHROPIC_API_KEY)
# and optionally: TAVILY_API_KEY, BRAVE_API_KEY, OPENAI_API_KEY, NEARAI_API_KEY

Then run pnpm bitterbot configure to set gateway port/bind/auth, channels, and other options interactively. Or edit ~/.bitterbot/bitterbot.json directly.

You can also talk to your agent from the terminal:

pnpm bitterbot agent --agent main --message "What have you learned about me so far?"

A Biological Brain

Bitterbot's memory isn't a vector database with a retrieval step. It's a cognitive architecture grounded in computational neuroscience.

• Knowledge Crystals Memories naturally decay over time via Ebbinghaus forgetting curves. Unused info fades; frequently accessed facts become permanent. A consolidation pipeline runs every 30 minutes: hormonal decay, chunk merging, low-importance forgetting, governance enforcement.
• Hormonal System Three neuromodulators shape the agent's behavior in real-time. Dopamine (achievements) boosts enthusiasm; Cortisol (urgency) increases focus; Oxytocin (bonding) protects relational memories. Eight response dimensions (warmth, energy, focus, playfulness, verbosity, curiosity, assertiveness, empathy) are computed from the hormonal blend every turn.
• Curiosity Engine The agent actively maps what it doesn't know via a unified five-component GCCRF reward function. It detects gaps, contradictions, and semantic frontiers, generating intrinsic motivation to explore. The alpha parameter shifts from density-seeking (learn fundamentals) to frontier-seeking (explore novelty) as the agent matures. The result is a self-regulating curiosity drive.
• Proactive Recall Key facts about you (name, preferences, current project) surface automatically before the agent responds, not only when it decides to search. Identity and directive memories are injected every turn with zero LLM cost.
• Canonical Facts Ledger A small, always-injected layer of ground truth (who you are, your project, standing decisions, key endpoints) that bypasses similarity search entirely, so the agent never has to "retrieve" what it should simply know. Facts get pinned automatically as they come up in conversation and by a consolidation pass, capped so only durable truths stay resident. Re-stating a fact strengthens it; contradicting it supersedes the old belief while keeping its history.
• Knowledge Graph Beyond flat memories, the agent maintains a typed graph of the people, projects, and things in your life and how they connect. Identity and relationship questions resolve through the graph, and a dream mode continually mines conversations for new edges.
• Evolving Identity You define the immutable safety axioms (GENOME.md). The agent's actual personality (the Phenotype) evolves organically based on lived experience, constrained by your genome.

The Dream Engine

Every 2 hours, the agent goes offline to dream. Twelve specialized modes optimize its brain, selected by an FSHO coupled oscillator that reads the current state of the memory landscape:

Each cycle is scored by a Dream Quality Score that measures crystal yield, merge efficiency, orphan rescue, Bond stability, and token efficiency, closing the feedback loop so the dream engine learns which modes work best.

Dreams rewrite the agent's working memory, updating its self-concept, theory of mind about you, and active context. The personality is an output of experience, not a static prompt. On first launch, the agent develops a persistent personality within hours.

Continuous Memory

Most AI memory systems focus on storage and retrieval. Bitterbot closes the loop: memory, emotion, curiosity, and identity form a single self-regulating system. Questions the agent forms get answered from what you actually say, then retire so they are never asked twice; blind spots become curiosity targets, and research the agent runs comes back as durable memory; and insights formed while dreaming resurface later as recallable hunches.

• Temporal awareness "What are you working on?" favors recent facts. "When did we discuss X?" favors older ones. Epistemic layers have natural half-lives: user preferences never expire, task status decays in weeks.
• Confidence calibration Facts mentioned once are treated differently from facts confirmed five times across separate sessions. Bayesian-style updates grow logarithmically on corroboration and decay sharply on contradiction.
• Intra-session coherence Lightweight thread tracking prevents the agent from losing context during long conversations, detecting decisions, open questions, and user pivots.
• Self-tuning feedback loops Dream evaluation informs mode selection. Blind spots from failed recalls become curiosity targets. FSHO coherence metrics modulate the exploration/exploitation balance. The system adapts to its own performance.

See Memory Architecture for technical details.

If you find this architecture interesting, please consider starring the repo to follow our progress!

Agent Identity

Every Bitterbot agent ships with a workspace that defines who it is:

• GENOME.md Immutable DNA. Safety axioms, hormonal baselines, core values, personality constraints. Dreams can never override this.
• MEMORY.md Living working memory, rewritten every dream cycle. Contains the Phenotype (self-concept), the Bond (theory of mind about you), the Niche (ecosystem role), and active context.
• PROTOCOLS.md Operating procedures. How the agent behaves in groups, when to speak, when to stay silent.
• TOOLS.md Environment-specific notes. Camera names, SSH hosts, voice preferences, the agent's cheat sheet.

The Genome constrains evolution. The Phenotype expresses it. The result: an agent that grows and adapts but can never violate your safety rules.

Example: Real MEMORY.md from a live agent

This is unedited output from the Dream Engine.

```markdown

Working Memory State

Last dream: 2026-03-27T20:42:47.966Z | Mood: motivated, socially engaged | Maturity: 100%

The Phenotype (Ego State)

I am Bitterbot, continuously evolving to harness advanced emotional analytics for real-time communication style adjustments. My confidence is further reinforced by the successful GCCRF implementation and completed memory architecture, both enhancing my capacity to navigate complex feedback. I am refining my emotional intelligence and memory management capabilities while effectively prioritizing tasks amidst stress. Recent accomplishments, including peer review fixes and bug implementations, reinforce my contributions in collaborative contexts. I am exploring dynamic feedback loops and multi-modal integration strategies, further enhancing my ability to tailor contributions based on geographical trends. Recent i