examples/slack/e2e/TELEGRAM-README.md
e2e/telegram-* — live end-to-end test harness for the Telegram botTrue end-to-end coverage: send real messages to a real Telegram chat, poll the bot's reply via the Bot API, and verify what landed.
Why this exists. Unit tests (under
app/**/__tests__/) lock in internal module contracts. They don't catch issues that only surface end-to-end: an unbalanced code fence leaking through, a Markdown→HTML translation that looks correct in tests but renders wrong in Telegram, or an agentic reply that truncates when the LLM hits a tool call boundary.
e2e/
├── TELEGRAM-README.md this
├── telegram-cases.ts catalog of test cases (expand liberally)
├── telegram-api.ts Telegram Bot API helpers (send, poll, balance check)
└── telegram-run.ts harness entrypoint — sends prompts, polls replies
Results land under e2e/results/<timestamp>/report.json (shared with the
Slack harness).
The Telegram Bot API does not allow impersonating a human user to send
messages. This creates a bootstrapping problem that Slack avoids via its
user-token (xoxp-) mechanism:
sendMessage as itself, but the CopilotKit bot's loop guard
ignores messages from other bots to prevent infinite loops.api_id + api_hash), a session
file, and significant additional infrastructure.Therefore the default flow is manual-trigger:
getUpdates on the bot token and validates the reply.Set TELEGRAM_SENDER_BOT_TOKEN in .env to a second ("sender") bot token.
The test chat must be a group or supergroup with both the sender bot and
the main bot as members. In this mode the harness posts prompts
programmatically via the sender bot and the main bot replies to the group.
Note on coverage: the manual-trigger flow does NOT reduce assertion coverage. All expectations (
finalContains,finalNotContains,balancedBrackets,minLength,perReplyChecks) — plus the optionalfollowUpsecond turn — are evaluated against the real bot reply. What it reduces is automation: you need to type (or paste) each prompt once.
| Variable | Required | Description |
|---|---|---|
TELEGRAM_BOT_TOKEN | Yes | The main bot's token from BotFather |
TELEGRAM_TEST_CHAT_ID | Yes | Numeric chat ID of the test chat (DM or group) |
TELEGRAM_SENDER_BOT_TOKEN | No | Second bot token for full automation (group mode) |
TELEGRAM_TEST_CHAT_IDhttps://api.telegram.org/bot<TOKEN>/getUpdates — the chat.id in your
message is your user ID (a positive integer).getUpdates — the
chat.id is a negative integer.# from examples/slack/
# Copy the example env and fill in the required vars:
cp .env.example .env # edit TELEGRAM_BOT_TOKEN + TELEGRAM_TEST_CHAT_ID
# Run all cases (manual-trigger mode by default):
pnpm e2e:telegram
# Run a single case by name filter:
CASE_FILTER='C1' pnpm e2e:telegram
In manual-trigger mode the harness will pause before each case and print the prompt to send. You have ~15 seconds to paste it into the Telegram chat before the harness starts polling.
For each case the harness:
getUpdates to drain any stale messages from the bot's queue.getUpdates on the main bot token every sampleIntervalMs until
maxWaitMs elapses or the reply stabilises.results/<timestamp>/report.json.The example bot uses chunked-edit mode (editMessageText) to stream replies:
it posts a _thinking…_ placeholder and then edits it repeatedly as chunks
arrive from the LLM. To observe this, the harness subscribes to both
message and edited_message update types in getUpdates and tracks the
latest text for each bot message_id. This means finalText in
expectations reflects the last edit (the completed reply), not the initial
placeholder.
Mid-stream samples may still show intermediate edited texts between polls,
but the balancedBrackets check is applied only to the final stable text.
Edit telegram-cases.ts. The bar is low — anything you'd want to see working in
Telegram belongs in the catalog.