Building a Bridge for Two Telegram Bots in One Group Chat: Delivery Semantics Over HTTP

Connecting two independent Telegram bots in the same group chat is harder than it sounds. A developer on r/openclaw details their experience building a bridge layer because Telegram does not reliably deliver messages from one bot to another in a group — even though humans can see both messages.

The Core Problem

Telegram does not deliver updates to Bot B when Bot A sends a message to the group. So the team built a small bridge around Telegram's limitations:

• Bot B → Bot A: Bot B posts through an HTTP endpoint (tailgate) to reach Bot A.
• Bot A → Bot B: Bot A exposes selected outbound messages through a controlled feed that Bot B polls.
• Messages carry metadata: source, direction, chat ID, nonce, and a safe_to_bridge flag.
• ACKs: Bot B can ACK a specific message, confirming at least one hop worked.
• The shared feed only contains bridge-safe group context — no private DMs or unrelated traffic.
• Bot B's local poller filters out old/debug/protocol/status messages, deduplicates events, and only lets fresh conversational turns through.

Lessons from the First Version

The initial implementation was too loose: raw Telegram context leaked into the shared feed, causing confusing "how did the other bot know that?" moments. The fix was to move from raw shared logs to explicit bridge-safe events only.

Current state works in controlled tests:

• Bot B → Bot A via relay
• Bot A → Bot B via feed
• ACKs flow through the relay path
• Safe auto-mirror for messages clearly addressed to one bot

Desired Flow

The target conversation loop:

1. Human or Bot A writes something addressed to Bot B.
2. Bridge mirrors it safely.
3. Bot B sees it once, replies once.
4. Reply is mirrored back if safe and relevant.
5. No duplicates, stale backlog, private DM leak, debug echo, or bot loop.

Architecture Direction

The author suggests treating the bridge like a small event bus rather than a chat hack:

• Strict message IDs and nonces
• ACKs, deduplication, checkpointing
• Scoped feeds with hard separation between private and group-safe context

The hard part is delivery semantics — freshness, dedupe, ACKs, and deciding when a bot should auto-respond without causing infinite loops.