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pawbot

A self-hosted AI agent for your browser, terminal, and chat apps.

Give pawbot a task and it can read and write files, run commands, search the web, call MCP tools, remember conversations, and run scheduled work. Use the WebUI when you want a visual workspace, the terminal when you want speed, or a chat app when you want your agent to be available wherever you are.

The feature that makes pawbot different to develop is Record & Replay: record one real agent turn, then replay it offline while you change the code — without another model request, another token bill, or real tool side effects.

Start here

You want to...	Start with...
Install the released package	Quick install
Open the browser workspace	WebUI
Run one request from a terminal	CLI
Connect a chat app	Channels
Understand the replay feature	Record & Replay
Change the agent or add a tool	Development

What can pawbot do?

• Work with files, shell commands, web search, web fetching, documents, images, and other tools.
• Connect to MCP servers and load extensions without changing the core agent.
• Keep session history and long-term memory across conversations.
• Run long tasks and scheduled automations.
• Use Anthropic, OpenAI-compatible endpoints, local models, fallbacks, and model presets.
• Reach the same agent from the WebUI, CLI/TUI, API, or supported chat channels.
• Expose a Python SDK and an OpenAI-compatible API for your own applications.

How a turn works

Every entry point reaches the same turn pipeline. The important boundary is between the orchestration loop and the provider/tool rails: the former can be budgeted, cancelled, checkpointed, and replayed without making the provider or real tools part of a regression test.

flowchart LR
    A[WebUI / CLI / API / chat channels] --> B[Gateway / Message Bus]
    B --> C[AgentLoop turn pipeline]
    C --> C1[Restore session]
    C1 --> C2[Compact context]
    C2 --> C3[Dispatch command]
    C3 --> C4[Build provider request]
    C4 --> D[AgentRunner ReAct loop]
    D --> E[Provider response]
    D --> F[Tool Registry]
    F --> G[Batch planner]
    G --> H[Call executor]
    H --> I[Tool observation]
    D --> J[Budget + checkpoint]
    J --> K[Session recovery]
    E --> L[LLM response rail]
    I --> M[Tool observation rail]
    L --> N[Record & Replay]
    M --> N
    N --> O[Offline replay + structural diff]
    D --> P[Turn delivery / UI events]

The result is one execution unit with explicit resource limits, recovery checkpoints, tool side-effect boundaries, and an offline evidence trail.

Why pawbot?

One agent, several ways to use it

The WebUI, terminal, API, and chat channels share the same conversations, tools, and configuration. Start in the browser and continue from the terminal; or keep the agent running behind a gateway and talk to it from a chat app.

Record an agent once, replay it as often as you need

LLM calls and external tools make agent bugs expensive and difficult to repeat. Pawbot records the model responses and tool observations of a turn. Replay then runs the current agent code against those recorded inputs:

• no new provider request;
• no new token cost;
• no network dependency;
• no real tool side effects;
• a structural diff when orchestration changes.

This is useful for debugging, regression tests, and safe refactoring of the agent loop.

Keep your data on your machine

Pawbot is designed for self-hosting. Sessions, configuration, workspaces, and recordings stay under your control. Shell commands, file access, network tools, and MCP servers are explicit capabilities with documented security boundaries.

Quick install

Published package

After the package is published, install and open the WebUI with one command:

macOS / Linux:

uv tool install --force --upgrade pawbot-ai && pawbot

Windows PowerShell:

uv tool install --force --upgrade pawbot-ai; pawbot

The repository also includes isolated fallback installers. On a fresh desktop install they start the WebUI automatically; use pawbot agent when you want the terminal/TUI client explicitly:

• scripts/install.sh
• scripts/install.ps1

For a fresh macOS or Linux desktop, the installer can be run directly from GitHub:

curl -fsSL https://raw.githubusercontent.com/m2dumpling/pawbot/v0.3.2/scripts/install.sh | sh

If curl is not available, use wget instead:

wget -qO- https://raw.githubusercontent.com/m2dumpling/pawbot/v0.3.2/scripts/install.sh | sh

For native Windows PowerShell:

iex (irm https://raw.githubusercontent.com/m2dumpling/pawbot/v0.3.2/scripts/install.ps1)

The installer selects an active virtual environment, uv, pipx, or a dedicated ~/.pawbot/venv fallback, then opens the WebUI on a fresh desktop. Before creating the fallback environment it verifies that Python's venv and ensurepip support is available. If a minimal Debian/Ubuntu image is missing python3.x-venv, installation stops with the exact package command to run and does not print a misleading startup command. On success it runs pawbot --version; if the launcher is not on the current shell's PATH, it prints the verified launcher path and the command to use now. Configure the first Provider and model in Settings → Models before sending your first task.

From a source checkout

Requirements: Python 3.11+ and uv. Bun is only needed when developing the WebUI or TUI.

uv sync --all-extras --dev
uv run pawbot --help

Install optional channel dependencies when needed:

uv run --no-sync python -m scripts.install_channel_dependencies --all-channels

Quick start

WebUI

The browser workspace is the easiest first run:

uv run pawbot webui

Configure your first provider and model in Settings → Models, start a new conversation, and send Hello!. The first-run WebUI binds to localhost by default.

CLI

Run pawbot without a subcommand to open the WebUI. Use pawbot agent when you explicitly want the terminal/TUI client.

Run one request and exit:

uv run pawbot agent --message "Explain the top-level modules in this repository"

Start the gateway directly when you want a long-running process:

uv run pawbot gateway

Keep the gateway in the background:

uv run pawbot gateway --background
uv run pawbot gateway status
uv run pawbot gateway logs

Record & Replay

Record a real turn:

uv run pawbot agent \
  --message "Inspect the repository and summarize the agent loop" \
  --record .pawbot/blackbox/demo

Replay it offline:

uv run pawbot agent --replay .pawbot/blackbox/demo

The concise equivalent is:

uv run pawbot replay .pawbot/blackbox/demo

Add --benchmark to print provider-free local replay timing and message/diff counts.

In the WebUI, Settings → Record & Replay provides the same workflow: click Start recording, run tasks across as many chat sessions as needed, then click Stop recording. The recording window belongs to the agent, so all turns before Stop are stored in one sample. Incomplete samples stay visible with a reason and can be deleted from the UI instead of failing later on replay.

Pause after an iteration and inspect the reconstructed messages:

uv run pawbot agent \
  --replay .pawbot/blackbox/demo \
  --break-at 2

The recording contains the provider-response rail, the tool-observation rail, and the turn envelope. Replay checks tool ordering, result insertion, context governance, continuation, and the final message structure. See docs/record-replay.md for the format and privacy boundary.

When choosing a model in Settings → Models, pawbot also reads capability metadata from the provider's /models response when available, then applies curated metadata for known model IDs. Context length and supported reasoning levels are shown before saving; if an API does not advertise them, the UI says so and keeps the value manually editable. See the curated model capability registry for the fallback table and context-window migration rules.

Channels and integrations

Pawbot can be used from its WebUI, terminal, OpenAI-compatible API, Python SDK, WebSocket channel, and supported chat channels. MCP servers and extension points let you add capabilities without hard-coding them into the agent loop.

Architecture

User message
    ↓
Channel / WebUI / CLI / API
    ↓
AgentLoop: prepare the conversation and run one turn
    ↓
AgentRunner: ask the model, call tools, add results, repeat when needed
    ↓
Provider + ToolRegistry + MCP
    ↓
Answer, saved session, and channel response

The core source is organized around:

• pawbot/agent/loop.py — turn orchestration;
• pawbot/agent/runner.py — the model/tool loop;
• pawbot/agent/turn/ — turn state and stages;
• pawbot/agent/blackbox/ — Record & Replay;
• pawbot/agent/tools/ — tool contracts and execution;
• pawbot/session/ — conversations, memory, and recovery;
• pawbot/providers/ — model adapters and retries.

Documentation

• Documentation index
• Record & Replay
• Release notes
• Publishing guide
• Changelog
• Contributing
• Security policy

Security and privacy

Pawbot can run shell commands, access local files, call network tools, and connect to MCP servers. Read SECURITY.md before enabling them.

Never commit:

• config.json, .env*, provider credentials, or certificates;
• .pawbot/ recordings and session data;
• work/, sessions/, run/, SQLite files, or private logs;
• prompts, tool results, or local paths containing personal information.

Replay artifacts can contain sensitive prompts and tool output. Sanitize them before sharing; use tests/fixtures/blackbox/ for repository-safe examples.

Development

uv sync --all-extras --dev
uv run --no-sync python -m scripts.install_channel_dependencies --all-channels
uv run ruff check pawbot
uv run basedpyright
uv run pytest -q

For WebUI changes:

cd webui
bun install --frozen-lockfile
bun run test
bun run build

Project status

Pawbot is an Alpha/Experimental Preview project. It is ready for personal self-hosting, development, testing, and small single-node deployments. It does not currently promise multi-instance session consistency, durable distributed execution, automatic failover, or enterprise high availability.

License

MIT — see LICENSE and THIRD_PARTY_NOTICES.md.