<p align="center">
<h1 align="center">Box Agent</h1>
<p align="center">A general-purpose AI agent with sandboxed code execution, sub-agent parallelism, and multi-provider LLM support.</p>
</p>
<p align="center">
<a href="https://pypi.org/project/box-agent/"><img src="https://img.shields.io/pypi/v/box-agent?color=orange" alt="PyPI"></a>
<a href="https://pypi.org/project/box-agent/"><img src="https://img.shields.io/pypi/dm/box-agent?color=brightgreen" alt="Downloads"></a>
<a href="https://pypi.org/project/box-agent/"><img src="https://img.shields.io/pypi/pyversions/box-agent?color=blue" alt="Python"></a>
<a href="https://github.com/Raccoon-Office/Box-Agent/blob/main/LICENSE"><img src="https://img.shields.io/github/license/Raccoon-Office/Box-Agent?color=green" alt="License"></a>
<a href="https://github.com/Raccoon-Office/Box-Agent/releases"><img src="https://img.shields.io/github/v/release/Raccoon-Office/Box-Agent?color=blue" alt="Release"></a>
</p>
<p align="center">
English | <a href="./README_CN.md">ไธญๆ</a>
</p>
---
**Get started in 30 seconds:**
```bash
uv tool install box-agent # or: pip install box-agent (Python 3.10+)
box-agent setup # interactive config wizard
box-agent # start chatting
```
Or run a one-shot task:
```bash
box-agent --task "Analyze sales.csv โ show top 10 products by revenue with a bar chart"
```
---
## Why Box Agent?
Most agent frameworks are either too simple (no sandbox, no tools) or too complex (massive dependencies, rigid architecture). Box Agent hits the sweet spot:
| Feature | Box Agent | Open Interpreter | Aider |
| ---------------------------- | ------------------------------------------------- | --------------------- | ------------------ |
| Sandboxed code execution | Jupyter kernel in isolated venv | Runs in host Python | N/A |
| Sub-agent parallelism | Multiple sub-agents run concurrently | No | No |
| Multi-provider LLM | Anthropic, OpenAI, DeepSeek, SiliconFlow, any API | OpenAI + a few others | OpenAI + Anthropic |
| MCP tool integration | Native | No | No |
| ACP protocol (embed in apps) | Full support | No | No |
| Standalone binary | PyInstaller runtime, no Python needed | No | No |
| Context compression | Staged automatic compaction + LLM summary | Manual | Git-based |
## Key Features
### Local Video Reading
`read_video` samples timestamped frames through the existing image-understanding
path, transcribes speech with the desktop Volc ASR service, and supports time-range
reads and continuation. It requires ffmpeg/ffprobe and the corresponding vision
and speech-service configuration. See [video reading](docs/VIDEO_READING.md) for
runtime setup, sampling limits, partial results and streaming-ASR latency.
### Local Email Analysis
`read_email` decodes local `.eml` headers, plain/HTML bodies and attachment
metadata offline, without a Python sandbox or additional packages. Prefer it
over `read_file` for emails. The body supports character pagination; continue
with `next_offset` and `expected_sha256=source_sha256` to detect a changed source.
To inspect an attachment, call the separate `extract_email_attachment` tool
with its `attachment_index` and a new `output_path` inside the workspace, then
use the appropriate document or image tool. Reading creates no files;
extraction checks write permissions and never overwrites a file. Read-only
sub-agents can read emails; delegated extraction requires an explicit write scope.
Messages are limited to 50 MiB, 256 MIME parts, 30 nesting levels and 100
attachments. Encrypted messages are not decrypted.
### Sub-Agent Parallelism
Delegate isolated work through a flat task contract with optional tools, Skills,
files, write scope, and hard step/tool-call budgets. Omitted tools resolve only
to trusted local readers; explicit capabilities still pass a fail-closed runtime
policy. Passing known local text paths in `files` selects the bounded,
completeness-checked batch fast path automatically when `read_file` is the only
resolved tool; requesting additional tools keeps the general child loop. The parent remains
responsible for conflict handling, the final deliverable, and verification.
```
You: "Analyze data1.csv, data2.csv, and data3.csv separately, then give me a combined summary"
โโ Sub-Agent 1 โโโโโโโ โโ Sub-Agent 2 โโโโโโโ โโ Sub-Agent 3 โโโโโโโ
โ Read data1.csv โ โ Read data2.csv โ โ Read data3.csv โ
โ Run statistics โ โ Run statistics โ โ Run statistics โ
โ Generate charts โ โ Generate charts โ โ Generate charts โ
โ โ Summary: ... โ โ โ Summary: ... โ โ โ Summary: ... โ
โโโโโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโ
โ parallel โ
โโ Parent Agent โโโโโโโโโโโ
โ Combines 3 summaries โ
โ Produces final report โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโ
```
Child policy is derived by the runtime: process tools, external side effects,
and unknown MCP tools fail closed; path writes require an exact scope. See the
[sub-agent delegation contract](docs/SUB_AGENT_DELEGATION.md) for schemas,
limits, compatibility behavior, and host diagnostics.
### Sandboxed Code Execution
Python runs in an isolated Jupyter kernel with pre-installed data science packages (`pandas`, `numpy`, `matplotlib`, `scikit-learn`, `openpyxl`, `xlrd`). Generated files (charts, CSVs, PDFs) are automatically detected and surfaced as structured artifacts.
`execute_code` keeps a bounded 32 KiB head/tail preview of stdout/stderr.
Larger output is streamed in full to an internal file; model replies, UI events,
and traces carry the preview and file reference instead of the full text.
Read that file in bounded pages to recover omitted content. If output persistence
fails, the reply explicitly reports that the full output is unavailable and keeps
the preview, without interrupting the Agent loop or rerunning the code.
### Multi-Provider LLM
One config, any provider:
```yaml
# Anthropic
api_base: "https://api.anthropic.com"
provider: "anthropic"
model: "claude-sonnet-4-20250514"
# DeepSeek
api_base: "https://api.deepseek.com"
provider: "openai"
model: "deepseek-chat"
# Any OpenAI-compatible endpoint
api_base: "https://your-api.example.com/v1"
provider: "openai"
model: "your-model"
```
### Staged Context Compression
`read_file` preserves its existing line pagination (`offset`, `limit`, default
500 lines, maximum 2000). Set `byte_offset=0` to read at most 16 KiB of text,
then pass the returned `next_byte_offset` until it is null. Byte mode seeks
directly, preserves UTF-8 characters and original newlines, and overrides
`offset`/`limit`. A line page above 100,000 characters automatically returns
the first byte chunk starting at that page's first line; byte continuation
reads toward EOF. Line scanning uses bounded 64 KiB reads. Fragments report
their byte range without claiming complete-line context coverage. Reads use
the current file, not a snapshot; existing model-context budgets still apply.
- **Oversized tool results**: Individual results are persisted immediately when needed; fresh parallel results also share a 50k-character pre-request budget. The model receives a stable preview while full text remains on disk. Read results are exempt and stay bounded by Read's own line/character controls.
- **Tool output delivery**: All tools share a final guard before model history, host events and diagnostic traces. Text above 512 KiB and structured metadata above 64 KiB are externalized; a 1 MiB serialized result budget accounts for combined fields and JSON escaping below the 4 MiB event limit. Valid Read pages and small semantic model projections remain intact. Tools may supply a private `raw_output_preview` for their own host schema: Plan preserves identity, titles and step structure while bounding narrative fields; Todo preserves execution state and prioritizes active work. Both previews are capped at 48 KiB and 64 steps/items. The shared layer validates these previews, saves the complete original JSON, and adds `_persisted_output` with `path`, `output_truncated` and `file_complete`. It does not recursively rewrite unknown business fields; results without a valid tool-owned preview retain only verbatim small fields and the file reference. Output-storage/serialization failures produce an explicit partial/unavailable notice without repeating the tool or stopping the Agent Loop; cancellation and durable session-commit failures retain their existing behavior. This guard cannot prevent memory used to construct the original output inside a tool.
- **Usage-aware auto-summary**: The next request is estimated from the latest real API usage plus subsequent messages. When it reaches the model-derived safety threshold, older history is summarized into a `user` message while bounded recent messages and todo, plan, and skill state are restored.
- **Tool-call arguments**: Write/edit arguments remain verbatim until a whole-history summary replaces their turn; they are not independently compacted.
- **Legacy safety guard**: Internal history placeholders from older or externally supplied sessions are rejected if a model tries to reuse them as executable file/code arguments; Box-Agent requests one clean regeneration instead of writing the placeholder to disk.
### More
- **MCP Tools**: Connect to any [MCP server](https://github.com/modelcontextprotocol/servers) โ web search, knowledge graphs, databases
- **Claude Skills**: 12 built-in runtime, Office, and artifact skills, plus on-demand marketplace skill sources
- **ACP Protocol**: Embed Box Agent in Electron apps, Zed Editor, or any ACP-compatible host via JSON-RPC over stdio
- **Standalone Runtime**: PyInstaller binary bundles Python + all dependencies. No external Python needed โ download and run
- **Cross-session Memory**: Persistent memory lets the agent retain key information across conversations
- **Safety Layer**: Dangerous command detection, workspace scope control, auto-backup before file modifications. Interactive permission negotiation for out-of-workspace access (CLI prompts user, ACP sends reverse RPC to host)
- **Planning Snapshots**: Structured plan tool for rendering objective, scope, steps, verification, and risks in host UIs
- **Task Tracking**: Built-in todo tool for multi-step task decomposition and progress tracking
## Demos
### Task Execution
_The agent creates a webpage and opens it in the browser._
### Claude Skill โ PDF Generation
_The agent uses a skill to create a professional document._
### Web Search via MCP
_The agent searches the web and summarizes results._
## Installation
> **Requires Python 3.10+.** If your system Python is older (e.g. 3.9), use `uv tool install` โ it manages Python automatically.
### Quick Start (uv, recommended)
[uv](https://docs.astral.sh/uv/) handles Python version management for you โ no need to upgrade your system Python:
```bash
# Install uv (if not already)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install box-agent (auto-downloads Python 3.10+ if needed)
uv tool install box-agent
box-agent setup # interactive config wizard
box-agent # start chatting
# Upgrade later
uv tool upgrade box-agent
```
### Quick Start (pip)
If you already have Python 3.10+:
```bash
pip install box-agent
box-agent setup
box-agent
```
### From Source
```bash
git clone https://github.com/Raccoon-Office/Box-Agent.git
cd Box-Agent
uv sync
uv run python -m box_agent.cli
```
## Contributor Quickstart
If you are joining the project as a collaborator, start here before changing
code:
```bash
git clone https://github.com/Raccoon-Office/Box-Agent.git
cd Box-Agent
git submodule update --init --recursive # needed for bundled skills
uv sync
uv run python -m box_agent.cli --help
uv run pytest tests/test_core.py -q
```
Read these files first:
- `AGENTS.md` โ repo-local engineering rules and verification expectations.
- `CONTRIBUTING.md` โ contribution flow, PR checklist, and commit style.
- `docs/REVIEW_GUIDE.md` โ maintainer review order, blockers, and proof requirements.
- `docs/DEVELOPMENT_GUIDE.md` โ deeper architecture and development notes.
- `docs/INTEGRATION.md` โ ACP/runtime integration details for host apps.
Project map:
| Area | Where to start |
| ---- | -------------- |
| Agent execution loop | `box_agent/core.py`, `box_agent/agent.py`, `box_agent/events.py` |
| CLI and config | `box_agent/cli.py`, `box_agent/config.py`, `box_agent/config/` |
| LLM providers | `box_agent/llm/` |
| Built-in tools | `box_agent/tools/` |
| ACP server/runtime embedding | `box_agent/acp/`, `box_agent/build_runtime_cli.py` |
| Skills | `box_agent/skills/`, `box_agent/tools/skill_loader.py` |
| Tests | `tests/test_<area>.py` |
Common development loop:
```bash
# Run the smallest relevant test while iterating
uv run pytest tests/test_bash_tool.py -q
# Run the full suite when the change's impact or CI gate requires it
bash general_review/ci/test.sh
# Catch whitespace/patch formatting issues
git diff --check
```
Use focused tests for the area you touched: tools in `tests/test_*_tool.py`,
LLM behavior in `tests/test_llm*.py` / `tests/test_error_messages.py`, ACP in
`tests/test_acp*.py`, memory in `tests/test_memory*.py`, and runtime packaging
in `tests/test_build_runtime.py` / `tests/test_cli_runtime.py`. Tests that need
real provider credentials are skipped unless the required API keys are present.
When a change affects the standalone runtime used by a host app, source changes
are not enough: rebuild the runtime, install it into the host, restart the
running ACP process, then probe the installed runtime. For local packaging:
```bash
uv run box-agent-build-runtime
```
Build a versioned runtime and install the resulting archive into the usual
officev3 checkout in one command:
```bash
uv run box-agent-build-runtime --version 0.8.82 --install-officev3
```
Pass an explicit checkout path after `--install-officev3`, or set
`BOX_AGENT_OFFICEV3_DIR`, when officev3 is stored elsewhere.
### Configuration
After running `box-agent setup`, your config lives at `~/.box-agent/config/config.yaml`:
```yaml
api_key: "your-api-key"
api_base: "https://api.anthropic.com"
model: "claude-sonnet-4-20250514"
provider: "anthropic" # "anthropic" or "openai"
max_steps: 300
max_parallel_tools: 8
parallel_tool_timeout_seconds: 900
provider_stale_seconds: 300
sub_agent_token_limit: 50000
sub_agent_batch_synthesis_timeout_seconds: 600 # 0 disables the extra batch synthesis cap
goal_autopilot_enabled: true
goal_autopilot_max_turns: 3
goal_autopilot_max_seconds: 14400
goal_autopilot_no_progress_turns: 2
```
Tool limits are omitted by default so runtime upgrades can supply updated
defaults from `box_agent/config.py`. Add only deliberate overrides under
`tool_limits:`; inspect the current effective values with
`box-agent config --json`.
```bash
box-agent config # show current config summary
box-agent config --get model # print one config value
box-agent config --set max_steps 300
box-agent config --set goal_autopilot_max_turns 5
box-agent config --set tool_limits.external_skill.max_tool_calls 160
box-agent config --set tool_limits.external_skill.max_delegated_tool_calls 512
box-agent config --set tool_limits.completion.deadline_seconds 1800
box-agent config --set tools.bash_default_timeout_seconds 300
box-agent config --json # machine-readable config summary
box-agent config --edit # open in editor
box-agent doctor # check environment & API connectivity
box-agent doctor --json # machine-readable health check
```
### Isolated runtime profiles
Hosts may opt into a dedicated absolute `BOX_AGENT_HOME` before starting the runtime. This routes Box-Agent-owned configuration and state away from the default user profile without changing the operating-system `HOME`; unset behavior stays compatible. Explicit profiles require their own `config/config.yaml` and never fall back to legacy configuration or login-token environment variables.
For endpoints that reject `reasoning_effort: "none"`, see
[reasoning configuration](docs/reasoning-configuration.md) for the explicit
`reasoning_effort_when_disabled: low` compatibility option and child Agent inheritance.
See [isolated runtime profiles](docs/isolated-runtime-profile.md) and the no-background-startup [example configuration](box_agent/config/isolated-profile-example.yaml). This is path/configuration isolation, not an OS sandbox or permission to call a model.
## CLI Usage
```bash
# Interactive mode
box-agent
box-agent --workspace /path/to/project
box-agent --no-sandbox # disable Jupyter sandbox
# Non-interactive (CI/CD, scripts)
box-agent --task "analyze data.csv and create a report"
box-agent --task "analyze data.csv" --json # append execution summary JSON
box-agent --task "local file task" --no-verify-api # skip startup API probe
box-agent --task "create a PPT" --force-plan-start # publish a plan before work
box-agent --task "create a PPT" --no-completion-gate
box-agent --goal "Ship CLI parity" --task "finish tests"
box-agent --goal "Ship CLI parity" --task "finish tests" --no-goal-autopilot
box-agent --deep-think --task "review this repo" # enable thinking mode when supported
# Subcommands
box-agent setup # config wizard
box-agent config # show/edit config
box-agent doctor # health check
box-agent log # open log directory
box-agent trace-viewer # open the offline Agent Trace diagnostics page
box-agent goal status # show persistent workspace goal
box-agent goal complete --evidence "tests passed"
box-agent install-browser # install Chromium for Playwright MCP (~200MB)
box-agent install-node # install managed Node.js runtime for skills (macOS)
```
### Code-mode startup context
Code-mode sessions load the workspace-root `AGENTS.md` into the startup prompt.
They do not run Git commands during prompt assembly; the prompt states that Git
state has not been checked. The agent can inspect Git through tools when needed
and must still protect existing user changes.
### Agent Trace diagnostics
Run `box-agent trace-viewer` to open the packaged, offline developer viewer. Open `~/.box-agent/log/sessions/` for a newest-first overview of every trace, then select one run to inspect per-turn metrics, LLM/tool waterfalls, raw events, and the complete system โ user โ assistant/tool โ final-response chain. You can still open one `.jsonl` file directly.
Both ACP and CLI create session traces automatically. Each CLI invocation writes
`cli-<unique-id>.jsonl`; interactive user turns have distinct turn IDs in that
file. `/clear` resets conversation history without deleting the diagnostic trace,
and Goal autopilot continuations stay within the originating user turn. Native
CLI traces include input, LLM/tool activity, final output, stop reason and turn
duration; no test-harness writer is required. Startup probes and idle CLI commands
are outside the turn trace. Set `BOX_AGENT_SESSION_TRACE_DIR` to override the
directory, or `BOX_AGENT_SESSION_TRACE_ENABLED=0` to disable tracing. CLI trace
initialization or write failures do not fail the task. These files contain sensitive task data; the same
retention policy below applies to both entrypoints.
Choose **Compare sources** to compare equivalent runs from any number of sources. The selected root uses source directories directly, without an extra data-directory level:
```text
comparison-traces/
baseline/*.jsonl
current/*.jsonl
candidate-x/*.jsonl
```
The viewer groups traces by normalized `turn.input` first and may use a compatible normalized filename when input is missing or non-conflicting. It keeps repeated runs per source selectable, shows each source side by side, and calculates duration, call, token, and error deltas against the selected reference source.
If an embedded browser does not expose the native file picker, run the loopback-only service and enter the trace directory path in the page:
```bash
uv run python -m box_agent.trace_viewer.server --port 8766
```
The offline page reads files in the browser. In ledger mode, the service reads only top-level `.jsonl` files from the directory you enter. In comparison mode, it reads top-level `.jsonl` files from each immediate non-symlink source directory and goes no deeper. It checks metadata once per second and refreshes the active view when files are added or changed; trace bodies are transferred over `127.0.0.1` only when that metadata changes. The service rejects requests whose `Host` or `Origin` is not its exact loopback authority, preventing a rebinding site from reading local traces. Neither mode makes external network requests. Chromium and Edge can keep following appended records after you grant a file handle; drag/drop and ordinary file inputs load a snapshot. Session traces may contain prompts, tool arguments, outputs, and business dataโhandle them as sensitive diagnostic artifacts.
### Browser automation (optional)
Box-Agent ships with a disabled [`@playwright/mcp`](https://github.com/microsoft/playwright-mcp) entry. To enable browser tools locally:
```bash
box-agent install-browser # downloads Chromium and flips the entry to enabled
```
Requires Node.js โฅ 18 on `PATH`. Chromium lands in `~/.box-agent/browsers/` (shared by CLI and ACP runtime) and `mcpServers.playwright.disabled` in `~/.box-agent/config/mcp.json` is set to `false`.
**ACP embedders**: no env-var plumbing required โ `box-agent-acp` defaults `PLAYWRIGHT_BROWSERS_PATH` to the same `~/.box-agent/browsers/` path. To point at a different cache, export `PLAYWRIGHT_BROWSERS_PATH=<your path>` before spawning `box-agent-acp` (our setdefault won't override it).
**Web access routing** is shared by CLI, ACP and child agents through the
capability-gated `Web Access Routing` prompt. Explicit browser/tab/reader choices
come first, followed by continuation of an existing page, dependencies on the
user's browser state, independent visible/interactive browser work, and public
URL body retrieval. Source discovery uses search before choosing a reader.
For example, โopen Baiduโ uses the managed browser, while โsummarize this public
article URLโ prefers `web_extract`. A request to review a new form does not itself
require the user's system browser; stop before submission when the user owns it.
Skills provide execution and evidence procedures for the selected channel.
Unavailable tools must be discovered or reported, never invented. Recovery may
select another channel only when it preserves the task and does not replace an
explicit target or required browser state; uncertain actions must be verified
before any retry. This is a shared model-facing policy, not an unconditional
Fetch-to-managed-to-user-browser fallback or a guarantee of model compliance.
In-session commands: `/help`, `/clear`, `/clear_all`, `/history`, `/stats`, `/sandbox_status`, `/log`, `/goal`, `/memory review`, `/exit`
CLI Skill subprocesses receive the original user requests, including constraints
such as "do not generate images", through the same source-binding contract as
ACP. Interactive requests accumulate until `/clear` or `/clear_all`; assistant
output and automatic goal-continuation prompts are not added as source facts.
ACP session traces keep their existing `~/.box-agent/log/sessions/<session-id>.jsonl`
name and `box-agent-session-trace/v1` record format. Retention removes only whole,
inactive session files: files older than 7 days are eligible, and the directory
has a soft 512 MiB cap. The current append target, files modified within 24
hours, and the newest two sessions are protected. Cleanup runs best-effort at
most once every 6 hours; cleanup failures never interrupt agent execution.
Operators can override the defaults with `BOX_AGENT_SESSION_TRACE_RETENTION_DAYS`,
`BOX_AGENT_SESSION_TRACE_MAX_TOTAL_BYTES`, and
`BOX_AGENT_SESSION_TRACE_CLEANUP_INTERVAL_SECONDS`, or disable cleanup with
`BOX_AGENT_SESSION_TRACE_RETENTION_ENABLED=0`.
Use `/goal <objective>` or `--goal "<objective>"` to keep a durable workspace objective attached to later turns. The CLI persists it under `~/.box-agent/goals/`; later turns include that goal until you run `/goal pause`, `/goal resume`, `/goal block <reason>`, `/goal complete <evidence>`, or `/goal clear`. Scripted runs can manage it with `box-agent goal ...`.
In non-interactive `--task` mode and ACP sessions, active goals also use bounded autopilot: when a turn ends naturally but the goal is still `active`, Box-Agent automatically continues in the same session until the model marks the goal `complete`, marks it `blocked`, the user cancels, `goal_autopilot_max_turns` / `goal_autopilot_max_seconds` is reached, or `goal_autopilot_no_progress_turns` consecutive automatic continuations make no recorded goal progress. Use `--no-goal-autopilot` for one CLI run, or set `goal_autopilot_enabled: false` in config.
## ACP & Editor Integration
ACP `session/cancel` interrupts a pending primary model stream read without
waiting for the next HTTP chunk or activity heartbeat, then closes the stream
and finishes the turn with `stopReason: cancelled`. This does not restart the
shared runtime or cancel other sessions. Tool execution retains its existing
cooperative cancellation behavior; cancelling a turn does not roll back tool
side effects that have already occurred.
Box Agent supports the [Agent Communication Protocol](https://github.com/nichochar/agent-client-protocol) for embedding in editors and apps.
**Zed Editor** โ add to `settings.json`:
```json
{
"agent_servers": {
"box-agent": {
"command": "/path/to/box-agent-acp"
}
}
}
```
**Standalone Runtime** โ for Electron apps and other hosts:
```bash
# Download pre-built binary (latest release; omit the tag to always get the newest)
gh release download --repo Raccoon-Office/Box-Agent --pattern "box-agent-runtime-*.tar.gz"
# Or build from source (current platform)
uv run box-agent-build-runtime
# Build both macOS architectures from one source snapshot (no upload/host install)
# Requires prepared .venv (ARM) and .venv-x64 (Intel), including PyInstaller.
uv run box-agent-build-runtime --mac-all --version 0.9.13 --dry-run
uv run box-agent-build-runtime --mac-all --version 0.9.13
# Build both archives directly into Lab's desktop dist/runtime (no host runtime replacement).
uv run box-agent-build-runtime --mac-all-lab --version 1.0.0 --dry-run
uv run box-agent-build-runtime --mac-all-lab --version 1.0.0
# Build macOS Intel/x64 runtime from Apple Silicon
# Requires a separate x86_64 venv because PyInstaller cannot bundle arm64 wheels into an x64 binary.
# One-time setup:
# arch -x86_64 /bin/bash -c 'curl -LsSf https://astral.sh/uv/install.sh | INSTALLER_NO_MODIFY_PATH=1 UV_INSTALL_DIR="$HOME/.local/bin-x64" sh'
# UV_PROJECT_ENVIRONMENT=.venv-x64 arch -x86_64 ~/.local/bin-x64/uv sync
# Reuse the existing x64 Python without depending on the x64 uv install path.
# Isolate intermediate outputs from ARM builds; add --version X.Y.Z if needed.
.venv-x64/bin/python -m box_agent.build_runtime_cli --target darwin-x64 --output dist/runtime-darwin-x64
```
The runtime communicates via JSON-RPC over stdio. stdout = protocol only, stderr = diagnostics.
macOS runtime archives contain ACP and its internal dependencies. Stable tool
Python/Node runtimes are host-managed and must match the target architecture;
they are not bundled into this ACP-only archive.
`--mac-all` checks the actual Python process architectures, uses separate build/cache
directories, and validates every native Mach-O file. Only after both builds pass are
the two archives, SHA-256 sidecars and a `box-agent-runtime-v<version>-mac.json` report
placed together in `dist/runtime/`. Existing same-version output is never overwritten.
Use `--arm-python PATH` / `--intel-python PATH` for custom environments; both must use
the same Python major/minor and PyInstaller version. `--dry-run` checks prerequisites
without building. This mode requires an explicit stable version and cannot be combined
with `--target`, `--arch`, `--install-officev3` or `--install-lab`.
See the [dual-architecture workflow](docs/PRODUCTION_GUIDE_CN.md#macos-ๅๆถๆไธๆฌกๆๅปบ).
`--mac-all-lab [DIR]` reuses the same dual build and writes to
`<Lab>/apps/office-desktop/dist/runtime/` by default. It locates Lab using
`BOX_AGENT_LAB_DIR` or the neighboring checkout; `--output` / `BOX_AGENT_RUNTIME_OUTPUT`
can override the destination. Then run
`pnpm desktop:release:mac -- --agent-version 1.0.0 --runtime-dir apps/office-desktop/dist/runtime`
from the Lab root to build both clients. Neither command uploads artifacts.
## Testing
```bash
bash general_review/ci/test.sh # all tests, up to four workers
uv run pytest tests/test_core.py -v # core + context compression
uv run pytest --cov # with coverage
```
## Troubleshooting
**Model quota or arrearage**: Recognized business error codes such as `Arrearage` determine the error category before generic message text. HTTP status remains a separate diagnostic and retry signal; unknown codes fall back to the existing text rules. Check the account balance and billing status for the configured model provider before retrying.
**SSL Certificate Error**: `pip install --upgrade certifi` or set `verify=False` for testing.
**Module Not Found**: Make sure you're in the project directory: `cd Box-Agent && uv run python -m box_agent.cli`
## Contributing
Issues and PRs welcome! See [Contributing Guide](CONTRIBUTING.md).
## License
[MIT](LICENSE)
## Links
- [Documentation](docs/README.md)
- [PyPI](https://pypi.org/project/box-agent/) ยท [GitHub](https://github.com/Raccoon-Office/Box-Agent) ยท [Releases](https://github.com/Raccoon-Office/Box-Agent/releases)
- [Anthropic API](https://docs.anthropic.com/claude/reference) ยท [MCP Servers](https://github.com/modelcontextprotocol/servers) ยท [ACP Protocol](https://github.com/nichochar/agent-client-protocol)
---
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