Headless Bot Project

Use this reference when a human asks for a LingTai-backed bot that should run as its own project without stepping through the interactive TUI. The pattern is channel-agnostic:

1. Create a normal LingTai project with lingtai-tui spawn.
2. Write channel secrets into sidecar files under the agent directory.
3. Activate the required addon/MCP entries in init.json.
4. Copy or construct the agent's preset policy (manifest.preset) by

referencing the intended saved/template presets.

1. Refresh or relaunch the agent and verify the channel end-to-end.

Do not fabricate .lingtai/ by hand. The supported bootstrap entrypoint remains lingtai-tui spawn. The helper bundled here currently provisions Telegram bots; future helpers for other chat surfaces should live under this same generic reference rather than creating channel-specific top-level skill names.

Inputs

Common inputs:

• PROJECT_DIR: new project directory. It must not already contain .lingtai/.
• PRESET: saved or template preset name for the initial lingtai-tui spawn.
• AGENT_NAME: agent directory/name to create under .lingtai/.
• LANGUAGE: one of en, zh, or wen.
• Optional source agent init.json if the new bot should inherit the same

manifest.preset policy as an existing orchestrator.

Telegram-specific inputs:

• TELEGRAM_BOT_TOKEN: bot token from @BotFather. Keep it in the environment

or a local prompt, never in shell history, logs, git, issues, or docs.

• ALLOWED_USERS: comma-separated Telegram numeric user IDs allowed to talk to

the bot.

Preferred Telegram Helper

Run the bundled helper. Use the installed-bundle path ~/.lingtai-tui/utilities/swiss-knife/reference/headless-bot/scripts/create_telegram_bot_project.py, or the source-checkout path tui/internal/preset/skills/swiss-knife/reference/headless-bot/scripts/create_telegram_bot_project.py:

bash
read -rsp 'Telegram bot token: ' TELEGRAM_BOT_TOKEN; export TELEGRAM_BOT_TOKEN; echo
python3 <helper-path>/create_telegram_bot_project.py \
  --project-dir /path/to/new-project \
  --preset minimax \
  --agent-name my-bot-agent \
  --language en \
  --allowed-users 123456789 \
  --preset-policy-from /path/to/source-agent/init.json

The helper:

1. Runs lingtai-tui spawn <dir> --preset <name> --agent-name <name> --language <code>.
2. Writes <agent_dir>/.secrets/telegram.json with mode 0600.
3. Adds telegram to top-level addons.
4. Adds top-level mcp.telegram using the local LingTai runtime Python and

invokes lingtai.mcp_servers.telegram with args: ["-m", "lingtai.mcp_servers.telegram"]; it passes LINGTAI_TELEGRAM_CONFIG=.secrets/telegram.json.

1. Optionally copies manifest.preset from --preset-policy-from into the new

agent's init.json without copying any preset JSON files.

1. Touches <agent_dir>/.refresh so a running agent reloads the updated config.

If refresh is not enough for the installed runtime, relaunch or CPR the agent.

The helper intentionally reads TELEGRAM_BOT_TOKEN from the environment instead of a command-line flag, because argv can be captured by shell history and process monitors. Its output redacts token-like values. The --preset-policy-from flag is optional; use it when the bot should inherit an existing agent's preset access policy.

Preset Policy: Copy References, Not Preset Files

Headless bots often need access to the same model/preset choices as an existing orchestrator. Do not grant that access by manually copying saved preset JSON files into the new project's .lingtai/presets/saved/ directory. That creates stale, duplicated configuration and can diverge from the user's real saved presets.

Instead, patch the new agent's init.json so its manifest.preset block points to the intended saved or template presets. If the bot should mirror an existing agent, copy only that source agent's manifest.preset policy block:

bash
python3 - <<'PY'
import json
from pathlib import Path

source_init = Path('/path/to/source-agent/init.json')
target_init = Path('/path/to/new-project/.lingtai/<agent-name>/init.json')

source = json.loads(source_init.read_text())
target = json.loads(target_init.read_text())

preset_policy = source.get('manifest', {}).get('preset')
if not isinstance(preset_policy, dict):
    raise SystemExit(f'{source_init} has no manifest.preset policy object')

target.setdefault('manifest', {})['preset'] = preset_policy
target_init.write_text(json.dumps(target, indent=2, ensure_ascii=False) + '\n')
PY

Expected shape:

json
{
  "manifest": {
    "preset": {
      "active": "~/.lingtai-tui/presets/saved/codex.json",
      "default": "~/.lingtai-tui/presets/saved/codex.json",
      "allowed": [
        "~/.lingtai-tui/presets/saved/codex.json",
        "~/.lingtai-tui/presets/saved/minimax_cn.json"
      ]
    }
  }
}

Keep this separate from secrets and MCP credentials. After changing the preset policy, refresh or restart the agent and confirm the active preset in .agent.json or the runtime logs.

Manual Telegram Workflow

Use this when you need to inspect or adapt each step. Replace placeholders, but never paste a real token into committed files or chat transcripts.

bash
lingtai-tui spawn "$PROJECT_DIR" \
  --preset "$PRESET" \
  --agent-name "$AGENT_NAME" \
  --language "$LANGUAGE"

The command prints JSON containing agent_dir. Treat that as the only supported source for the agent path.

Create the sidecar secret:

json
{
  "accounts": [
    {
      "alias": "main",
      "bot_token": "<redacted-telegram-bot-token>",
      "allowed_users": [123456789]
    }
  ],
  "poll_interval": 1.0
}

Save it as:

text
<agent_dir>/.secrets/telegram.json

Then set restrictive permissions:

bash
chmod 700 "<agent_dir>/.secrets"
chmod 600 "<agent_dir>/.secrets/telegram.json"

Patch <agent_dir>/init.json so these top-level keys exist:

json
{
  "addons": ["telegram"],
  "mcp": {
    "telegram": {
      "type": "stdio",
      "command": "~/.lingtai-tui/runtime/venv/bin/python",
      "args": ["-m", "lingtai.mcp_servers.telegram"],
      "env": {
        "LINGTAI_TELEGRAM_CONFIG": ".secrets/telegram.json"
      }
    }
  }
}

If addons or mcp already exists, merge instead of replacing unrelated entries. The command should point to the local LingTai runtime Python. On unusual installs, resolve it with:

bash
python3 - <<'PY'
from pathlib import Path
print(Path.home() / ".lingtai-tui" / "runtime" / "venv" / "bin" / "python")
PY

Refresh Or Relaunch

After writing init.json and channel secret files, refresh the running agent:

bash
touch "<agent_dir>/.refresh"

If the listener does not appear in logs within a minute, inspect process state before starting anything else:

bash
lingtai-tui list "$PROJECT_DIR"

If the agent is stuck in a relaunch/dead loop, use the runtime lifecycle controls available in your environment (for example suspend/CPR from an orchestrator) or relaunch from the project. Do not start a second copy of the same agent without checking lingtai-tui list first.

Verification Checklist

Run these checks before handing the bot to a user:

• lingtai-tui list "$PROJECT_DIR" shows the new agent and no duplicate copy.
• Bot API getMe succeeds. Redact the token in commands and logs:

bash
python3 - <<'PY'
import json, os, urllib.request
token = os.environ["TELEGRAM_BOT_TOKEN"]
with urllib.request.urlopen(f"https://api.telegram.org/bot{token}/getMe", timeout=15) as r:
    data = json.load(r)
print(json.dumps({"ok": data.get("ok"), "result": data.get("result", {})}, indent=2))
print("token: <redacted>")
PY

• The agent log shows the Telegram MCP/listener starting, without printing the

bot token.

• The runtime sees the intended preset policy; check init.json, .agent.json,

or the logs after refresh/relaunch.

• Slash commands still work in the TUI, especially /refresh, /doctor, and a

simple chat prompt.

• From an allowed Telegram account, send /start to the bot and confirm the

agent responds.

• From a non-allowed account, confirm access is denied or ignored.

Security Rules

• Never commit .secrets/telegram.json, .env, screenshots, terminal captures,

issue comments, or summaries containing a real bot token.

• Prefer allowed_users; an omitted allowlist makes the bot reachable by anyone

who discovers it.

• Rotate the token in @BotFather immediately if it appears in logs, git

history, chat, crash reports, or process arguments.

• Use placeholders such as <redacted-telegram-bot-token> in examples. Do not use

realistic token-shaped dummy strings.

• Keep generated secret files mode 0600 and directories mode 0700 on shared

machines.