> ## Documentation Index > Fetch the complete documentation index at: https://docs.myspellchecker.com/llms.txt > Use this file to discover all available pages before exploring further. # Overview > Command reference for spell checking, dictionary building, model training, and text segmentation via the CLI. The `myspellchecker` CLI is installed with the package and provides commands for checking text, building dictionaries, training AI models, segmenting text, and managing configuration. ## Installation The CLI is installed automatically with the package: ```bash theme={null} pip install myspellchecker myspellchecker --help ``` ## Commands Overview | Command | Description | | ------------- | -------------------------------------------------------------- | | `check` | Check text for spelling errors (default when no command given) | | `build` | Build dictionary database from corpus | | `train-model` | Train a custom semantic model | | `segment` | Segment text into words | | `config` | Manage configuration | | `infer-pos` | Infer POS tags for database | | `completion` | Generate shell completion | ## check Check text for spelling errors. This is the default command: if no subcommand is recognized, `check` is assumed. ### Usage ```bash theme={null} myspellchecker check [OPTIONS] [INPUT] ``` ### Arguments | Argument | Description | | -------- | ------------------------------------- | | `INPUT` | Input file path (or stdin if omitted) | ### Options | Option | Short | Description | | --------------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------- | | `--output` | `-o` | Output file path (default: stdout) | | `--format` | `-f` | Output format: `json`, `text`, `csv`, `rich` (default: `rich` for TTY, `json` for pipes) | | `--color` | | Force color output even when not a TTY | | `--no-color` | | Disable color output | | `--level` | | Validation level: `syllable`, `word` (default: `syllable`) | | `--db` | | Custom database path | | `--no-phonetic` | | Disable phonetic matching | | `--no-context` | | Disable context checking | | `--no-ner` | | Disable Named Entity Recognition | | `--ner-model` | | HuggingFace model name for transformer NER (default: `chuuhtetnaing/myanmar-ner-model`). Requires `pip install myspellchecker[transformers]` | | `--ner-device` | | Device for NER inference: `-1`=CPU, `0`+=GPU index (default: `-1`) | | `--preset` | `-p` | Configuration preset: `default`, `fast`, `accurate`, `minimal`, `strict` | | `--verbose` | `-v` | Enable verbose logging | | `--config` | `-c` | Path to configuration file (YAML or JSON format) | Note: `--color` and `--no-color` are mutually exclusive. ### Examples ```bash theme={null} # Check a file myspellchecker check document.txt # Check with JSON output myspellchecker check document.txt -f json -o results.json # Check from stdin echo "မြန်မာနိုင်ငံ" | myspellchecker check # Use specific database myspellchecker check document.txt --db custom.db # Fast checking (syllable only) myspellchecker check document.txt --level syllable # Thorough checking myspellchecker check document.txt --level word -p accurate # With custom config file myspellchecker check document.txt -c config.yaml # Force color output in a pipe myspellchecker check document.txt --color | less -R # Rich formatted output (default in terminal) myspellchecker check document.txt -f rich ``` ### Output Formats **Rich (default in terminal)**: Colored, formatted output with panels and tables using the Rich library. Auto-selected when running in an interactive terminal. **Text (grep-like)**: ```python theme={null} # WARNING: Myanmar text may not render correctly in your terminal. # Use a text editor with proper font support to view this output. document.txt:1:5: invalid_syllable 'xyz' -> Try: [abc, def, ghi] # Summary: 1 errors found in 10 lines. ``` **JSON (default in pipes)**: ```json theme={null} { "summary": { "total_errors": 1, "total_lines": 10 }, "results": [ { "file": "document.txt", "line": 1, "text": "...", "has_errors": true, "errors": [ { "text": "xyz", "position": 5, "error_type": "invalid_syllable", "suggestions": ["abc", "def", "ghi"], "confidence": 1.0 } ] } ] } ``` Additional fields appear in each error object depending on the error type: `action` and `message` for syllable errors, `syllable_count` for word errors, and `probability` and `prev_word` for context errors. **CSV**: ```csv theme={null} file,line,position,error_type,text,suggestions document.txt,1,5,invalid_syllable,xyz,"abc,def,ghi" ``` ## build Build a dictionary database from corpus files. ### Usage ```bash theme={null} myspellchecker build [OPTIONS] ``` ### Options | Option | Short | Description | | ---------------------- | ----- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `--input` | `-i` | Input corpus file(s) (UTF-8 encoded text, CSV, TSV, JSON) | | `--output` | `-o` | Output database path (default: `mySpellChecker-default.db`) | | `--work-dir` | | Directory for intermediate files (default: `temp_build`) | | `--keep-intermediate` | | Keep intermediate files after build | | `--sample` | | Generate sample corpus for testing | | `--col` | | Column name/index for CSV/TSV files (default: `text`) | | `--json-key` | | Key name for JSON objects (default: `text`) | | `--pos-tagger` | | POS tagger type: `rule_based`, `viterbi`, `transformer` | | `--pos-model` | | HuggingFace model ID or local path for transformer tagger (default: `chuuhtetnaing/myanmar-pos-model`) | | `--pos-device` | | Device for transformer POS tagger: `-1`=CPU, `0`+=GPU (default: `-1`) | | `--incremental` | | Perform incremental update on existing database | | `--curated-input` | | Path to curated lexicon CSV file (words marked as `is_curated=1`) | | `--curated-lexicon-hf` | | Download and use the official curated lexicon from HuggingFace (`thettwe/myspellchecker-resources`). Cached after first download. Mutually exclusive with `--curated-input` | | `--word-engine` | | Word segmentation engine: `myword`, `crf`, `transformer` (default: `myword`) | | `--seg-model` | | HuggingFace model ID or local path for transformer word segmentation (only used when `--word-engine=transformer`) | | `--seg-device` | | Device for transformer word segmenter: `-1`=CPU, `0`+=GPU (default: `-1`, only used when `--word-engine=transformer`) | | `--validate` | | Validate inputs only without building (pre-flight check) | | `--min-frequency` | | Minimum word frequency threshold (default: from config) | | `--num-workers` | | Number of parallel workers (default: auto-detect based on CPU cores) | | `--batch-size` | | Batch size for processing (default: 10000) | | `--worker-timeout` | | Worker timeout in seconds for parallel processing (default: 1800) | | `--no-dedup` | | Disable line-level deduplication during ingestion | | `--no-desegment` | | Keep word segmentation markers (spaces/underscores between Myanmar chars) | | `--no-enrich` | | Skip enrichment step (confusable pairs, compounds, collocations, register tags) | | `--verbose` | `-v` | Enable verbose logging with detailed timing breakdowns | ### Examples ```bash theme={null} # Build sample database myspellchecker build --sample # Build from corpus file myspellchecker build -i corpus.txt -o dictionary.db # Build from multiple files myspellchecker build -i "data/*.txt" "extra/*.json" # Build from directory (auto-detects txt, json, jsonl) myspellchecker build -i ./corpus/ -o dictionary.db # Validate before building myspellchecker build -i corpus.txt --validate # With POS tagging myspellchecker build -i corpus.txt --pos-tagger viterbi # Incremental update myspellchecker build -i new_data.txt -o dictionary.db --incremental # Filter by frequency myspellchecker build -i corpus.txt -o dictionary.db --min-frequency 5 # Build with curated lexicon myspellchecker build -i corpus.txt --curated-input data/curated_lexicon.csv -o dictionary.db # Combine corpus with curated lexicon and transformer POS tagger myspellchecker build -i corpus.txt --curated-input data/curated_lexicon.csv \ --pos-tagger transformer --pos-device 0 -o dictionary.db ``` ### Build Process 1. **Ingestion**: Read and parse input files 2. **Segmentation**: Break text into syllables and words 3. **Frequency Calculation**: Count occurrences and N-grams 4. **POS Tagging**: Tag words with part-of-speech (if enabled) 5. **Enrichment**: Mine confusable pairs, compounds, collocations, register tags (unless `--no-enrich`) 6. **Packaging**: Create optimized SQLite database ## train-model Train semantic models for context checking. ### Usage ```bash theme={null} myspellchecker train-model [OPTIONS] ``` ### Options | Option | Short | Description | | ------------------------------- | ----- | -------------------------------------------------------------------------------- | | `--input` | `-i` | Input corpus file (required; raw text, one sentence per line) | | `--output` | `-o` | Output directory for the model (required) | | `--architecture` | `-a` | Model architecture: `roberta`, `bert` (default: `roberta`) | | `--epochs` | | Number of training epochs (default: 5) | | `--batch-size` | | Training batch size (default: 16) | | `--learning-rate` | | Peak learning rate (default: 5e-5) | | `--warmup-ratio` | | Ratio of steps for LR warmup (default: 0.1) | | `--weight-decay` | | Weight decay for optimizer (default: 0.01) | | `--hidden-size` | | Size of hidden layers (default: 256) | | `--layers` | | Number of transformer layers (default: 4) | | `--heads` | | Number of attention heads (default: 4) | | `--max-length` | | Maximum sequence length (default: 128) | | `--vocab-size` | | Tokenizer vocabulary size (default: 30000) | | `--min-frequency` | | Minimum token frequency (default: 2) | | `--resume` | | Resume training from checkpoint directory | | `--keep-checkpoints` | | Keep intermediate PyTorch checkpoints after export | | `--no-metrics` | | Disable saving training metrics to JSON | | `--streaming` | | Use streaming mode for large corpora (constant memory usage) | | `--checkpoint-dir` | | Persistent checkpoint directory for job resume (e.g. `/opt/ml/checkpoints`) | | `--max-steps` | | Cap total training steps (overrides epochs x steps\_per\_epoch) | | `--fp16` | | Enable mixed-precision (FP16) training for faster speed and lower memory | | `--gradient-accumulation-steps` | | Accumulate gradients over N steps (effective batch = batch-size x N, default: 1) | ### Architectures | Architecture | Description | | ------------ | ------------------------------------------- | | `roberta` | RoBERTa (default) - Dynamic masking, no NSP | | `bert` | BERT - Static masking, with NSP capability | ### Examples ```bash theme={null} # Train with default settings (RoBERTa architecture) myspellchecker train-model -i corpus.txt -o ./models/ # Train BERT model with more epochs myspellchecker train-model -i corpus.txt -o ./models/ --architecture bert --epochs 10 # Train with custom hyperparameters myspellchecker train-model -i corpus.txt -o ./models/ \ --learning-rate 3e-5 --warmup-ratio 0.1 --weight-decay 0.01 # Train larger model myspellchecker train-model -i corpus.txt -o ./models/ \ --hidden-size 512 --layers 6 --heads 8 # Resume training from checkpoint myspellchecker train-model -i corpus.txt -o ./models/ \ --resume ./models/checkpoints/checkpoint-500 # Keep checkpoints and disable metrics myspellchecker train-model -i corpus.txt -o ./models/ \ --keep-checkpoints --no-metrics ``` ## segment Segment text into words and optionally tag with POS. ### Usage ```bash theme={null} myspellchecker segment [OPTIONS] [INPUT] ``` ### Options | Option | Short | Description | | ----------- | ----- | ------------------------------------------------------ | | `--output` | `-o` | Output file path (default: stdout) | | `--format` | `-f` | Output format: `text`, `json`, `tsv` (default: `text`) | | `--tag` | | Include POS tags (uses joint segmentation-tagging) | | `--db` | | Custom database path | | `--verbose` | `-v` | Enable verbose logging | ### Examples ```bash theme={null} # Segment text (default text format) myspellchecker segment document.txt # Output as JSON myspellchecker segment document.txt -f json # Output as TSV myspellchecker segment document.txt -f tsv # With POS tags myspellchecker segment document.txt --tag # From stdin echo "မြန်မာနိုင်ငံ" | myspellchecker segment ``` ### Output **Word mode with tags**: ```python theme={null} မြန်မာ/N နိုင်ငံ/N ``` ## config Manage configuration files. ### Usage ```bash theme={null} myspellchecker config [SUBCOMMAND] ``` ### Subcommands | Subcommand | Description | | ---------- | ------------------------------------------------------- | | `init` | Create a new configuration file with defaults | | `show` | Show configuration file search paths and current config | ### config init Options | Option | Description | | --------- | ------------------------------------------------------------------------------------- | | `--path` | Path for configuration file (default: `~/.config/myspellchecker/myspellchecker.yaml`) | | `--force` | Overwrite existing configuration file | ### Examples ```bash theme={null} # Create config file (default location) myspellchecker config init # Create config file at custom path myspellchecker config init --path ./myspellchecker.yaml # Overwrite existing config file myspellchecker config init --force # Show current config and search paths myspellchecker config show ``` ### Configuration File Locations Configuration files are searched in this order: 1. Path specified with `--config` flag 2. Current directory: `myspellchecker.yaml`, `myspellchecker.yml`, or `myspellchecker.json` 3. User config directory: `~/.config/myspellchecker/myspellchecker.{yaml,yml,json}` ## infer-pos Infer POS tags for untagged words in the database using a rule-based engine. ### Usage ```bash theme={null} myspellchecker infer-pos [OPTIONS] ``` ### Options | Option | Short | Description | | ------------------ | ----- | ------------------------------------------------------------------------------ | | `--db` | | Database path to update with inferred POS tags (required) | | `--min-frequency` | | Minimum word frequency for inference (default: 0, infer all) | | `--min-confidence` | | Minimum confidence threshold, 0.0-1.0 (default: 0.0) | | `--include-tagged` | | Also infer for words that already have `pos_tag` (updates `inferred_pos` only) | | `--dry-run` | | Show statistics without modifying the database | | `--verbose` | `-v` | Enable verbose output with detailed statistics | ### Inference Sources | Source | Description | | -------------------- | --------------------------------------------------- | | `numeral_detection` | Myanmar numerals and numeral words | | `prefix_pattern` | Words with prefix patterns (e.g., အ prefix -> Noun) | | `proper_noun_suffix` | Proper noun suffixes (country, city names) | | `ambiguous_registry` | Known ambiguous words (multi-POS) | | `morphological` | Suffix-based morphological analysis | ### Examples ```bash theme={null} # Infer POS tags for all untagged words myspellchecker infer-pos --db dictionary.db # Infer only for high-frequency words myspellchecker infer-pos --db dictionary.db --min-frequency 10 # Set minimum confidence threshold myspellchecker infer-pos --db dictionary.db --min-confidence 0.7 # Preview changes without modifying database myspellchecker infer-pos --db dictionary.db --dry-run # Include already-tagged words for re-inference myspellchecker infer-pos --db dictionary.db --include-tagged ``` ## completion Generate shell completion scripts. ### Usage ```bash theme={null} myspellchecker completion --shell [bash|zsh|fish] ``` ### Options | Option | Description | | --------- | --------------------------------------------------- | | `--shell` | Shell type: `bash`, `zsh`, `fish` (default: `bash`) | ### Examples ```bash theme={null} # Generate bash completion myspellchecker completion --shell bash > ~/.bash_completion.d/myspellchecker source ~/.bash_completion.d/myspellchecker # Generate zsh completion myspellchecker completion --shell zsh > ~/.zsh/completions/_myspellchecker # Generate fish completion myspellchecker completion --shell fish > ~/.config/fish/completions/myspellchecker.fish ``` ## Global Options Available for all commands: | Option | Description | | -------- | ----------------- | | `--help` | Show help message | Note: `--verbose`/`-v` is available on most subcommands (`check`, `build`, `segment`, `infer-pos`) but is defined per-subcommand, not globally. ## Exit Codes | Code | Meaning | | ---- | --------------------------------------------------------- | | 0 | Success (no errors found, or validation passed) | | 1 | General runtime error (configuration, data loading, etc.) | | 2 | Invalid arguments, file not found, or permission error | | 130 | Process interrupted (Ctrl+C) | ## Configuration File Create `~/.config/myspellchecker/myspellchecker.yaml`: ```yaml theme={null} # Database path (required - no bundled database included) database: /path/to/your/custom.db # Use a preset (default, fast, accurate, minimal, strict) preset: default # Core settings max_edit_distance: 2 max_suggestions: 5 # Feature toggles use_phonetic: true use_context_checker: true # Provider configuration provider_config: pool_max_size: 5 pool_timeout: 5.0 ``` ## Environment Variables All environment variables use the `MYSPELL_` prefix. They override config file values but are overridden by CLI flags. ### Core Settings | Variable | Description | Values | | ------------------------------------ | --------------------------------------------- | --------------- | | `MYSPELL_DATABASE_PATH` | Default database path | File path | | `MYSPELL_MAX_EDIT_DISTANCE` | Max edit distance | 1-3 | | `MYSPELL_MAX_SUGGESTIONS` | Max suggestions returned | Integer >= 1 | | `MYSPELL_USE_CONTEXT_CHECKER` | Enable context validation | true/false | | `MYSPELL_USE_PHONETIC` | Enable phonetic matching | true/false | | `MYSPELL_USE_NER` | Enable Named Entity Recognition | true/false | | `MYSPELL_USE_RULE_BASED_VALIDATION` | Enable rule-based validation | true/false | | `MYSPELL_WORD_ENGINE` | Word segmentation engine | `myword`, `crf` | | `MYSPELL_FALLBACK_TO_EMPTY_PROVIDER` | Fall back to empty provider if DB missing | true/false | | `MYSPELL_ALLOW_EXTENDED_MYANMAR` | Allow Extended Myanmar characters (Shan, Mon) | true/false | ### POS Tagger Settings | Variable | Description | Values | | ------------------------------- | ----------------------------- | -------------------------------------- | | `MYSPELL_POS_TAGGER_TYPE` | POS tagger type | `rule_based`, `viterbi`, `transformer` | | `MYSPELL_POS_TAGGER_BEAM_WIDTH` | Beam width for Viterbi tagger | Integer >= 1 | | `MYSPELL_POS_TAGGER_MODEL_NAME` | Transformer model name/path | String | ### Provider Settings | Variable | Description | Values | | ----------------------- | ---------------------------- | ------------ | | `MYSPELL_POOL_MIN_SIZE` | Connection pool minimum size | Integer >= 0 | | `MYSPELL_POOL_MAX_SIZE` | Connection pool maximum size | Integer >= 1 | ### Semantic Checker Settings | Variable | Description | Values | | --------------------------------- | ---------------------------------- | -------------- | | `MYSPELL_SEMANTIC_MODEL_PATH` | Path to ONNX model file | File path | | `MYSPELL_SEMANTIC_TOKENIZER_PATH` | Path to tokenizer directory | Directory path | | `MYSPELL_SEMANTIC_NUM_THREADS` | Inference threads | Integer | | `MYSPELL_SEMANTIC_PREDICT_TOP_K` | Top-K predictions for mask filling | Integer | | `MYSPELL_SEMANTIC_CHECK_TOP_K` | Top-K candidates to check | Integer | ### SymSpell Settings | Variable | Description | Values | | ---------------------------------------- | ---------------------------------- | ------------ | | `MYSPELL_SYMSPELL_PREFIX_LENGTH` | Prefix length for SymSpell | 4-10 | | `MYSPELL_SYMSPELL_BEAM_WIDTH` | Beam width | Integer >= 1 | | `MYSPELL_SYMSPELL_USE_WEIGHTED_DISTANCE` | Use Myanmar-weighted edit distance | true/false | ### N-gram Context Settings | Variable | Description | Values | | ----------------------------------- | ----------------------------- | ------- | | `MYSPELL_NGRAM_BIGRAM_THRESHOLD` | Bigram probability threshold | 0.0-1.0 | | `MYSPELL_NGRAM_TRIGRAM_THRESHOLD` | Trigram probability threshold | 0.0-1.0 | | `MYSPELL_NGRAM_RERANK_LEFT_WEIGHT` | Left-context rerank weight | 0.0-1.0 | | `MYSPELL_NGRAM_RERANK_RIGHT_WEIGHT` | Right-context rerank weight | 0.0-1.0 | ### Phonetic Settings | Variable | Description | Values | | ----------------------------------- | --------------------------------------- | ------- | | `MYSPELL_PHONETIC_BYPASS_THRESHOLD` | Phonetic similarity threshold | 0.0-1.0 | | `MYSPELL_PHONETIC_EXTRA_DISTANCE` | Extra edit distance for phonetic bypass | 0-3 | ### Ranker Settings | Variable | Description | Values | | ------------------------------------------------------------- | ------------------------------------ | -------------------------------------------------------------------- | | `MYSPELL_RANKER_UNIFIED_BASE_TYPE` | Base ranker type | `default`, `frequency_first`, `phonetic_first`, `edit_distance_only` | | `MYSPELL_RANKER_ENABLE_TARGETED_RERANK_HINTS` | Enable targeted rerank hints | true/false | | `MYSPELL_RANKER_ENABLE_TARGETED_CANDIDATE_INJECTIONS` | Enable targeted candidate injections | true/false | | `MYSPELL_RANKER_ENABLE_TARGETED_GRAMMAR_COMPLETION_TEMPLATES` | Enable grammar completion templates | true/false | ## Next Steps * [Configuration](/guides/configuration) - Full configuration options * [Data Pipeline](/data-pipeline/index) - Building dictionaries * [API Reference](/api-reference/index) - Python API