litert-lm-builder-nightly 0.12.0.dev20260518

Python tools for building and inspecting LiteRT-LM file formats.

LiteRT-LM Builder

Python tools for building, inspecting, and unpacking LiteRT-LM (.litertlm) container files.

Usage

The package provides two main Command Line Interfaces (CLIs): litert-lm-builder and litert-lm-peek.

---

🛠️ Build a LiteRT-LM File (litert-lm-builder)

Use litert-lm-builder to package various components into a single .litertlm file. There are two ways to use this tool:

Method 1: Build using a TOML Configuration

Specify all the components and metadata in a TOML file, then run:

litert-lm-builder toml --path config.toml output --path model.litertlm

Example TOML File (config.toml):

[system_metadata]
entries = [
  { key = "author", value_type = "String", value = "Authors" }
]

[[section]]
section_type = "LlmMetadata"
data_path = "path/to/llm_metadata.pb"

[[section]]
section_type = "SP_Tokenizer"
data_path = "path/to/sp.model"

[[section]]
section_type = "TFLiteModel"
model_type = "PREFILL_DECODE"
data_path = "path/to/model.tflite"
additional_metadata = [
  { key = "model_version", value_type = "String", value = "1.0.1" }
]

Method 2: Build via Command Line Arguments

You can construct the file by chaining subcommands in the terminal. The order of the subcommands determines the order of the sections in the generated file.

litert-lm-builder \
  system_metadata --str author "Authors" \
  llm_metadata --path path/to/llm_metadata.pb \
  sp_tokenizer --path path/to/sp.model \
  tflite_model --path path/to/model.tflite --model_type prefill_decode --str_metadata model_version "1.0.1" \
  output --path model.litertlm

Subcommands and Options Reference:

• output (Required): Specifies the output file path.
  • --path PATH: Path to save the built .litertlm file.
• toml: Load configuration from a TOML file.
  • --path PATH: Path to the .toml file.
• system_metadata: Add global system metadata.
  • --str KEY VALUE: Add a string key-value pair (can be specified multiple times).
  • --int KEY VALUE: Add an integer key-value pair (can be specified multiple times).
• llm_metadata: Add LLM-specific configuration.
  • --path PATH: Path to the LLM metadata (text or binary proto).
• tflite_model: Add a TFLite model.
  • --path PATH: Path to the .tflite file.
  • --model_type TYPE: e.g., embedder, prefill_decode.
  • --backend_constraint BACKEND: (Optional) Backend constraint (e.g., gpu, cpu, npu).
  • --prefer_activation_type TYPE: (Optional) Preferred activation type (fp16, fp32, fp32_fp16).
  • --str_metadata KEY VALUE: (Optional) String metadata for this model section.
• sp_tokenizer: Add a SentencePiece tokenizer.
  • --path PATH: Path to the .model file.
  • --str_metadata KEY VALUE: (Optional) String metadata.
• hf_tokenizer: Add a Hugging Face tokenizer.
  • --path PATH: Path to the tokenizer.json file.
  • --str_metadata KEY VALUE: (Optional) String metadata.

---

🔍 Inspect and Unpack a LiteRT-LM File (litert-lm-peek)

Use litert-lm-peek to inspect the contents of a .litertlm file or extract all its packaged files.

litert-lm-peek --litertlm_file model.litertlm [options]

Options Reference:

• --litertlm_file PATH (Required): The path to the .litertlm file to inspect.
• --dump_files_dir PATH (Optional): The directory where all packaged files (models, tokenizers, weights) should be extracted/unpacked. If not provided, the tool will only print the metadata and section structures to the console without extracting files.