Bot Reply Delivery Reliability

Every agent reply on Telegram, Slack, and Discord is split at paragraph boundaries, keeps its code fences intact, and is measured in the length unit each platform actually enforces.

from praisonaiagents import Agent
from praisonai.bots import Bot

agent = Agent(name="assistant", instructions="Answer with long, code-heavy replies.")
bot = Bot("telegram", agent=agent)
bot.run()

The user asks a question; the delivery layer chunks the reply so a long, code-heavy, or emoji-heavy answer reaches them whole rather than being rejected by the platform’s length limit.

Quick Start

Nothing to configure

Chunking runs automatically on every adapter. A reply that fits the platform cap is sent as-is; a longer one is split at paragraph boundaries before sending.

Code fences stay intact

A fenced code block is kept whole rather than split mid-block, so users always see complete, copyable code.

Telegram measures in UTF-16

Telegram counts its 4096-character cap in UTF-16 code units. PraisonAI counts in the same unit, so emoji- and CJK-heavy replies are chunked at the point Telegram actually enforces.

How It Works

chunk_message splits the reply, using the platform’s length_unit to measure each piece. chunk_message(text, max_length, preserve_fences, length_unit) returns a list of chunks, each within the platform cap:

from praisonai.bots._chunk import chunk_message

# Telegram: 4096 cap, measured in UTF-16 code units
chunks = chunk_message(
    long_text,
    max_length=4096,
    preserve_fences=True,
    length_unit="utf16",
)
for chunk in chunks:
    await adapter.send_message(channel_id, chunk)

The adapter reads length_unit from its own platform_capabilities(), so you rarely call chunk_message yourself — it runs inside _send_long_message on every reply.

Platform Caps

Platform	Max length	Length unit
Telegram	4096	`utf16`
Slack	4096	`codepoints`
Discord	2000	`codepoints`

Only Telegram declares length_unit="utf16" in the current SDK (TelegramBot.default_capabilities()). Every other adapter uses the "codepoints" default, where one character counts as one unit.

Common Patterns

Long transcripts
Code-heavy replies
Emoji / CJK on Telegram

A reply longer than the platform cap is split at paragraph boundaries and sent as several messages — no manual chunking needed in the agent.

preserve_fences=True (the default) keeps a fenced block whole so syntax highlighting and copy-paste stay intact.

A single emoji is two UTF-16 code units. Measuring in utf16 means an emoji-heavy reply is chunked at the point Telegram’s 4096-unit cap actually bites, not later.

Best Practices

Let the adapter chunk — don't pre-split in the agent

The delivery layer already splits at paragraph boundaries and measures in the correct unit. Manual chunking inside the agent duplicates work and usually produces worse breaks.

Use utf16 for any Telegram-style platform

If you build a custom adapter for a platform that counts UTF-16 (like Telegram), set length_unit="utf16" on its PlatformCapabilities so emoji/CJK replies are measured correctly.

Keep preserve_fences on

Leaving preserve_fences=True keeps code blocks whole. Turn it off only when you specifically want a fenced block hard-split by character count.

Messaging Bots

Deploy bots on Telegram, Slack, and Discord

Bot Platform Capabilities

Per-platform length units and limits

Durable Outbound Delivery

Persist, retry, and drain outbound replies across restarts

Getting Started

Install

Core Concepts

Guides

Features

Models

Databases

Observability

Memory

Telemetry & Analytics

Knowledge

RAG

Persistence

Tools

Other Features

Developers

Configuration

Best Practices

Getting Started (No Code)

Bot Reply Delivery Reliability

Quick Start

How It Works

Platform Caps

Common Patterns

Best Practices

Messaging Bots

Bot Platform Capabilities

Durable Outbound Delivery

​Quick Start

​How It Works

​Platform Caps

​Common Patterns

​Best Practices

​Related

Messaging Bots

Bot Platform Capabilities

Durable Outbound Delivery

Quick Start

How It Works

Platform Caps

Common Patterns

Best Practices

Related