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Prompts & LLMs280k · #18

bengali-nlp

Has your agent process Bengali text. It helps understand and work with the language, normalizing text and handling its unique characteristics.

What it does

This tool helps process Bengali (Bangla) text. It ensures text is displayed and stored correctly, separates words, and handles language-specific numbers and characters.

When to use it

  • ✓When you have Bengali text to analyze.
  • ✓When building apps for Bengali speakers.
  • ✓When working with Bengali educational content.

Example of what to ask your AI

“Please process this Bengali text for me: 'আমি বাংলায় গান গাই।'”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/affaan-m/ECC/blob/main/pi/core/skills/bengali-nlp/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/affaan-m/ECC/blob/main/pi/core/skills/bengali-nlp/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool uses specific rules to organize Bengali characters, correctly separating words and handling Bengali-formatted numbers. It also ensures the text is in a standard format to avoid issues.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add affaan-m/ECC --skill bengali-nlp

Or download just the file:

curl -L https://raw.githubusercontent.com/affaan-m/ECC/main/pi/core/skills/bengali-nlp/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Bengali (Bangla) NLP Patterns

Best practices for processing, storing, and displaying Bengali text in software applications and AI systems.

When to Activate

  • Working with Bengali/Bangla text data
  • Building apps targeting Bengali-speaking users
  • Processing NCTB (National Curriculum and Textbook Board) educational content
  • Implementing Bengali search, autocomplete, or text input
  • Training or fine-tuning LLMs on Bengali data
  • Building Bengali chatbots or conversational AI
  • Handling mixed Bengali-English (Banglish) text

Bengali Unicode and Script Handling

Unicode Range

Bengali script occupies U+0980–U+09FF. Key character classes:

U+0981–U+0983  Chandrabindu, Anusvara, Visarga
U+0985–U+0994  Independent vowels (অ আ ই ঈ উ ঊ ঋ ঌ এ ঐ ও ঔ)
U+0995–U+09B0  Consonants (ক–র)
U+09B2         ল
U+09B6–U+09B9  শ ষ স হ
U+09DC, U+09DD, U+09DF  Additional consonants (ড়, ঢ়, য়)
U+09BC         Nukta
U+09BE–U+09C8  Dependent vowel signs (কার): া ি ী ু ূ ৃ ে ৈ
U+09CB–U+09CC  Dependent vowel signs: ো ৌ
U+09CD         Hasanta (virama) — forms conjuncts
U+09CE         Khanda Ta (ৎ)
U+09D7         AU length mark
U+09E0–U+09E3  Extended vowels
U+09E6–U+09EF  Bengali digits: ০১২৩৪৫৬৭৮৯
U+09F0–U+09F1  Assamese letters: ৰ (ra with middle diagonal), ৱ (ra with lower diagonal)
U+09F2–U+09F3  Rupee mark ৲ and rupee sign ৳
U+09F4–U+09F9  Historic currency numerators ৴ ৵ ৶ ৷ ৸ and denominator ৹
U+09FA         Isshar ৺

Normalization

Always normalize Bengali text to NFC before comparison, storage, or search:

import unicodedata

def normalize_bangla(text: str) -> str:
    """Normalize Bengali text to NFC form."""
    return unicodedata.normalize("NFC", text)

# NFC composes characters: base + combining marks -> precomposed
text_nfd = "ক\u09C7\u09BE"  # decomposed form of "কো"
text_nfc = normalize_bangla(text_nfd)
assert text_nfc == "কো"
assert text_nfc == normalize_bangla(text_nfc)  # idempotent
// JavaScript
function normalizeBangla(text) {
  return text.normalize('NFC');
}

Conjunct Consonants (যুক্তবর্ণ)

Bengali conjuncts are formed with Hasanta (্) between consonants:

ক + ্ + ষ = ক্ষ (ksha)
স + ্ + ত = স্ত (sta)
ন + ্ + ত + ্ + র = ন্ত্র (ntra)

Never split strings in the middle of a conjunct. Use grapheme cluster boundaries:

import regex  # pip install regex

def grapheme_length(text: str) -> int:
    """Count user-perceived characters (grapheme clusters)."""
    return len(regex.findall(r"\X", text))

# "ক্ষ" is 1 grapheme but 3 code points (ক + ্ + ষ)
assert grapheme_length("ক্ষ") == 1
assert len("ক্ষ") == 3  # code point count — wrong for display
// JavaScript — use Intl.Segmenter for grapheme-safe operations
function graphemeLength(text) {
  const segmenter = new Intl.Segmenter('bn', { granularity: 'grapheme' });
  return [...segmenter.segment(text)].length;
}

Bengali Digits

Handle both Bengali (০-৯) and ASCII (0-9) digits:

BANGLA_DIGITS = "০১২৩৪৫৬৭৮৯"
ASCII_DIGITS = "0123456789"

def bangla_to_ascii_digits(text: str) -> str:
    table = str.maketrans(BANGLA_DIGITS, ASCII_DIGITS)
    return text.translate(table)

def ascii_to_bangla_digits(text: str) -> str:
    table = str.maketrans(ASCII_DIGITS, BANGLA_DIGITS)
    return text.translate(table)

Tokenization

Word Boundary Detection

Bengali uses spaces between words, but compound words and postpositions can complicate tokenization:

import re

def tokenize_bangla(text: str) -> list[str]:
    """Basic Bengali tokenizer — split on whitespace and punctuation."""
    # Remove Bengali and ASCII punctuation, but preserve decimal points
    text = re.sub(r'(?<!\d)\.|\.(?!\d)|[।,;:!?\-\'"()\[\]{}]', ' ', text)
    return [token for token in text.split() if token]

# For production, use a trained tokenizer:
# - bnlp (pip install bnlp_toolkit)
# - stanza with Bengali model
# - spaCy with Bengali pipeline

Using bnlp Toolkit

from bnlp import NLTKTokenizer

tokenizer = NLTKTokenizer()
tokens = tokenizer.word_tokenize("আমি বাংলায় গান গাই।")
# ['আমি', 'বাংলায়', 'গান', 'গাই', '।']

Handling Postpositions and Case Markers

Bengali postpositions attach to nouns. Tokenizers should be aware of common suffixes:

-এর (possessive), -তে (locative), -কে (accusative)
-র (possessive after vowel), -য় (locative variant)

Text Processing Patterns

Script Detection

import re

def is_bangla(text: str) -> bool:

…
FAQ

What is text normalization?

Normalization is the process of ensuring Bengali text is in a consistent format, combining characters that might be written differently but mean the same thing.

What are 'conjuncts'?

Conjuncts are Bengali letters that join together to form a single sound or character, like 'ক্ষ'. The tool makes sure these letters are treated as one unit.

Why do I need to worry about Bengali numbers?

Bengali has its own digits (০১২৩৪৫৬৭৮৯). This tool can convert these numbers to the ones we normally use (0-9) and back if needed.

Details

Original description by the author

Bengali (Bangla) text processing patterns including Unicode normalization, script detection, tokenization, conjunct handling, and Bangla-specific NLP best practices for AI applications.

repo: affaan-m/ECC

Popularity

GitHub stars
280k
Ranking position
#18
License
MIT
Updated
10/15/2026

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