Initial upload: aesthetic-immich-starter
This commit is contained in:
Abderrahim-Mouhcine
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# Copyright 2024 The MediaPipe Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""MediaPipe Tasks GenAI Bundler API."""
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import mediapipe.tasks.python.genai.bundler.llm_bundler
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BundleConfig = llm_bundler.BundleConfig
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create_bundle = llm_bundler.create_bundle
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# Remove unnecessary modules to avoid duplication in API docs.
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del llm_bundler
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@@ -0,0 +1,236 @@
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# Copyright 2024 The MediaPipe Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
|
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# You may obtain a copy of the License at
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||||
#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
|
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Functions to perform llm packing."""
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import ctypes
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import dataclasses
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import enum
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from typing import List, Optional
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from mediapipe.tasks.python.core import mediapipe_c_bindings
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from mediapipe.tasks.python.core import mediapipe_c_utils
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from mediapipe.tasks.python.core import serial_dispatcher
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from mediapipe.tasks.python.genai.bundler import llm_bundler_metadata_options
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from mediapipe.tasks.python.genai.bundler import llm_bundler_metadata_options_c
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from mediapipe.tasks.python.genai.converter import external_dependencies
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from mediapipe.tasks.python.metadata.metadata_writers import model_asset_bundle_utils
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sentencepiece = external_dependencies.sentencepiece
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_CTYPES_SIGNATURES = (
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mediapipe_c_utils.CFunction(
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func_name="MpLlmBundlerGenerateMetadata",
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argtypes=[
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ctypes.POINTER(
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llm_bundler_metadata_options_c.LlmBundlerMetadataOptionsC
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),
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ctypes.POINTER(ctypes.c_int),
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],
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restype=ctypes.POINTER(ctypes.c_char),
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),
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mediapipe_c_utils.CFunction(
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func_name="MpLlmBundlerFreeMetadata",
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argtypes=[
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ctypes.POINTER(ctypes.c_char),
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],
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restype=None,
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),
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)
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@dataclasses.dataclass(frozen=True)
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class BundleConfig:
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"""Config for LLM Bundler.
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Attributes:
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tflite_model: Path to the multi-signature tflite model with "prefill" and
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"decode" signatures converted using ODML Transformers APIs.
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tokenizer_model: Path to the tokenizer model. Currently only SentencePience
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tokenizer is supported. As such, tokenizer.model proto is expected to be
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passed here.
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start_token: Token that will be used to signify the beginning of a sequence.
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stop_tokens: Tokens that will be used to signify the end of a sequence.
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output_filename: Name of the generated `.task` file containing the Bundle.
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enable_bytes_to_unicode_mapping: Enables GPT-2 style bytes to unicode
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mapping. For more details see:
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https://github.com/openai/gpt-2/blob/master/src/encoder.py#L9
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system_prompt: The starting text would be feed to the model on the start of
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each session, commonly called the System prompt. This is useful for
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instruction tuned models and pre-conditioning the model behavior. This
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field is mutually exclusive with prompt_prefix_system and
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prompt_suffix_system.
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prompt_prefix_user: The prefix that should be prepended to each user portion
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of prompts passed to the model.
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prompt_suffix_user: The suffix that should be appended to each user portion
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of prompts passed to the model.
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prompt_prefix_model: The prefix that should be prepended to each model
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portion of prompts passed to the model.
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prompt_suffix_model: The suffix that should be appended to each model
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portion of prompts passsed to the model.
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prompt_prefix_system: The prefix that should be prepended to each system
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portion of prompts passed to the model.
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prompt_suffix_system: The suffix that should be appended to each system
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portion of prompts passsed to the model.
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user_role_token: The token that indicates the user's turn.
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system_role_token: The token that indicates the system's turn.
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model_role_token: The token that indicates the model's turn.
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end_role_token: The token that indicates the end of the prompt.
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tflite_embedder: Path to the embedding model if the embedding lookup is done
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externally.
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tflite_per_layer_embedder: Path to the per layer embedding model if the per
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layer embedding lookup is done externally.
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tflite_vision_encoder: Path to the vision encoder model.
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tflite_vision_adapter: Path to the vision adapter model.
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"""
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tflite_model: str
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tokenizer_model: str
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start_token: str
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stop_tokens: List[str]
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output_filename: str
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enable_bytes_to_unicode_mapping: bool = False
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system_prompt: Optional[str] = None
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prompt_prefix_user: Optional[str] = None
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prompt_suffix_user: Optional[str] = None
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prompt_prefix_model: Optional[str] = None
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prompt_suffix_model: Optional[str] = None
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prompt_prefix_system: Optional[str] = None
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prompt_suffix_system: Optional[str] = None
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user_role_token: Optional[str] = None
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system_role_token: Optional[str] = None
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model_role_token: Optional[str] = None
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end_role_token: Optional[str] = None
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tflite_embedder: Optional[str] = None
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tflite_per_layer_embedder: Optional[str] = None
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tflite_vision_encoder: Optional[str] = None
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tflite_vision_adapter: Optional[str] = None
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class _BundleTags(enum.Enum):
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"""Bundle tags."""
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TF_LITE_PREFILL_DECODE = 1
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TOKENIZER_MODEL = 2
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METADATA = 3
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TF_LITE_EMBEDDER = 4
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TF_LITE_PER_LAYER_EMBEDDER = 5
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TF_LITE_VISION_ENCODER = 6
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TF_LITE_VISION_ADAPTER = 7
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def _validate_config(config: BundleConfig):
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"""Validates the given config.
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Args:
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config: The config to validate.
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Raises:
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ValueError if the config is invalid. Invalid configs can be:
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- tokenizer_model is not a valid SentencePiece model.
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- start_token is not a valid token in the tokenizer_model.
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- stop_tokens is not a list of valid tokens in the tokenizer_model.
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- system_prompt and prompt_*_system are both set.
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"""
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if not isinstance(config.stop_tokens, list):
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raise ValueError("stop_tokens must be a list of strings.")
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if not config.stop_tokens:
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raise ValueError("stop_tokens must be non-empty.")
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try:
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sp = sentencepiece.SentencePieceProcessor()
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sp.Load(config.tokenizer_model)
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except Exception as e:
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raise ValueError(
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f"Failed to load tokenizer model from {config.tokenizer_model}. "
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"Please ensure you are passing a valid SentencePiece model."
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) from e
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if config.system_prompt and (
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config.prompt_prefix_system or config.prompt_suffix_system
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):
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raise ValueError(
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"system_prompt and prompt_*_system are mutually exclusive."
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)
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def create_bundle(config: BundleConfig):
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"""Creates a bundle from the given config."""
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_validate_config(config)
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artifacts = {}
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with open(config.tflite_model, "rb") as f:
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artifacts[_BundleTags.TF_LITE_PREFILL_DECODE.name] = f.read()
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with open(config.tokenizer_model, "rb") as f:
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artifacts[_BundleTags.TOKENIZER_MODEL.name] = f.read()
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lib = mediapipe_c_bindings.load_raw_library(_CTYPES_SIGNATURES)
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with serial_dispatcher.SerialDispatcher(
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lib, _CTYPES_SIGNATURES
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) as bundler_lib:
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metadata_options = llm_bundler_metadata_options.LlmBundlerMetadataOptions(
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start_token=config.start_token,
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stop_tokens=config.stop_tokens,
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enable_bytes_to_unicode_mapping=config.enable_bytes_to_unicode_mapping,
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system_prompt=config.system_prompt,
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prompt_prefix_user=config.prompt_prefix_user,
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prompt_suffix_user=config.prompt_suffix_user,
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prompt_prefix_model=config.prompt_prefix_model,
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prompt_suffix_model=config.prompt_suffix_model,
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prompt_prefix_system=config.prompt_prefix_system,
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prompt_suffix_system=config.prompt_suffix_system,
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user_role_token=config.user_role_token,
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system_role_token=config.system_role_token,
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model_role_token=config.model_role_token,
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end_role_token=config.end_role_token,
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)
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metadata_options_c = metadata_options.to_ctypes()
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buffer_size = ctypes.c_int()
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metadata_buffer = None
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try:
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metadata_buffer = bundler_lib.MpLlmBundlerGenerateMetadata(
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ctypes.byref(metadata_options_c), ctypes.byref(buffer_size)
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)
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artifacts[_BundleTags.METADATA.name] = ctypes.string_at(
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metadata_buffer, buffer_size.value
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)
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finally:
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if metadata_buffer:
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bundler_lib.MpLlmBundlerFreeMetadata(metadata_buffer)
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if config.tflite_embedder:
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with open(config.tflite_embedder, "rb") as f:
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artifacts[_BundleTags.TF_LITE_EMBEDDER.name] = f.read()
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if config.tflite_per_layer_embedder:
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with open(config.tflite_per_layer_embedder, "rb") as f:
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artifacts[_BundleTags.TF_LITE_PER_LAYER_EMBEDDER.name] = f.read()
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if config.tflite_vision_encoder:
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with open(config.tflite_vision_encoder, "rb") as f:
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artifacts[_BundleTags.TF_LITE_VISION_ENCODER.name] = f.read()
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if config.tflite_vision_adapter:
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with open(config.tflite_vision_adapter, "rb") as f:
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artifacts[_BundleTags.TF_LITE_VISION_ADAPTER.name] = f.read()
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output_filename = config.output_filename
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if not output_filename.endswith(".task"):
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output_filename = config.output_filename + ".task"
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model_asset_bundle_utils.create_model_asset_bundle(
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artifacts,
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output_filename,
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)
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+142
@@ -0,0 +1,142 @@
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# Copyright 2026 The MediaPipe Authors.
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||||
#
|
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# Licensed under the Apache License, Version 2.0 (the "License");
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||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""LlmBundlerMetadataOptions Python dataclass."""
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import ctypes
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import dataclasses
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from typing import Optional
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from mediapipe.tasks.python.genai.bundler import llm_bundler_metadata_options_c
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@dataclasses.dataclass
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class LlmBundlerMetadataOptions:
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"""Options for bundling LLM metadata.
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||||
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Attributes:
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start_token: Token that will be used to signify the beginning of a sequence.
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stop_tokens: Tokens that will be used to signify the end of a sequence.
|
||||
enable_bytes_to_unicode_mapping: Enables GPT-2 style bytes to unicode
|
||||
mapping. For more details see:
|
||||
https://github.com/openai/gpt-2/blob/master/src/encoder.py#L9
|
||||
system_prompt: The starting text would be feed to the model on the start of
|
||||
each session, commonly called the System prompt. This is useful for
|
||||
instruction tuned models and pre-conditioning the model behavior. This
|
||||
field is mutually exclusive with prompt_prefix_system and
|
||||
prompt_suffix_system.
|
||||
prompt_prefix_user: The prefix that should be prepended to each user portion
|
||||
of prompts passed to the model.
|
||||
prompt_suffix_user: The suffix that should be appended to each user portion
|
||||
of prompts passed to the model.
|
||||
prompt_prefix_model: The prefix that should be prepended to each model
|
||||
portion of prompts passed to the model.
|
||||
prompt_suffix_model: The suffix that should be appended to each model
|
||||
portion of prompts passsed to the model.
|
||||
prompt_prefix_system: The prefix that should be prepended to each system
|
||||
portion of prompts passed to the model.
|
||||
prompt_suffix_system: The suffix that should be appended to each system
|
||||
portion of prompts passsed to the model.
|
||||
user_role_token: The token that indicates the user's turn.
|
||||
system_role_token: The token that indicates the system's turn.
|
||||
model_role_token: The token that indicates the model's turn.
|
||||
end_role_token: The token that indicates the end of the prompt.
|
||||
"""
|
||||
|
||||
start_token: str
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||||
stop_tokens: list[str]
|
||||
enable_bytes_to_unicode_mapping: bool = False
|
||||
system_prompt: Optional[str] = None
|
||||
prompt_prefix_user: Optional[str] = None
|
||||
prompt_suffix_user: Optional[str] = None
|
||||
prompt_prefix_model: Optional[str] = None
|
||||
prompt_suffix_model: Optional[str] = None
|
||||
prompt_prefix_system: Optional[str] = None
|
||||
prompt_suffix_system: Optional[str] = None
|
||||
user_role_token: Optional[str] = None
|
||||
system_role_token: Optional[str] = None
|
||||
model_role_token: Optional[str] = None
|
||||
end_role_token: Optional[str] = None
|
||||
|
||||
def to_ctypes(
|
||||
self,
|
||||
) -> llm_bundler_metadata_options_c.LlmBundlerMetadataOptionsC:
|
||||
"""Converts the object to a ctypes structure."""
|
||||
stop_tokens_c = (ctypes.c_char_p * len(self.stop_tokens))()
|
||||
for i, token in enumerate(self.stop_tokens):
|
||||
stop_tokens_c[i] = token.encode("utf-8")
|
||||
start_token_c = self.start_token.encode("utf-8")
|
||||
system_prompt_c = (
|
||||
self.system_prompt.encode("utf-8") if self.system_prompt else None
|
||||
)
|
||||
prompt_prefix_user_c = (
|
||||
self.prompt_prefix_user.encode("utf-8")
|
||||
if self.prompt_prefix_user
|
||||
else None
|
||||
)
|
||||
prompt_suffix_user_c = (
|
||||
self.prompt_suffix_user.encode("utf-8")
|
||||
if self.prompt_suffix_user
|
||||
else None
|
||||
)
|
||||
prompt_prefix_model_c = (
|
||||
self.prompt_prefix_model.encode("utf-8")
|
||||
if self.prompt_prefix_model
|
||||
else None
|
||||
)
|
||||
prompt_suffix_model_c = (
|
||||
self.prompt_suffix_model.encode("utf-8")
|
||||
if self.prompt_suffix_model
|
||||
else None
|
||||
)
|
||||
prompt_prefix_system_c = (
|
||||
self.prompt_prefix_system.encode("utf-8")
|
||||
if self.prompt_prefix_system
|
||||
else None
|
||||
)
|
||||
prompt_suffix_system_c = (
|
||||
self.prompt_suffix_system.encode("utf-8")
|
||||
if self.prompt_suffix_system
|
||||
else None
|
||||
)
|
||||
user_role_token_c = (
|
||||
self.user_role_token.encode("utf-8") if self.user_role_token else None
|
||||
)
|
||||
system_role_token_c = (
|
||||
self.system_role_token.encode("utf-8")
|
||||
if self.system_role_token
|
||||
else None
|
||||
)
|
||||
model_role_token_c = (
|
||||
self.model_role_token.encode("utf-8") if self.model_role_token else None
|
||||
)
|
||||
end_role_token_c = (
|
||||
self.end_role_token.encode("utf-8") if self.end_role_token else None
|
||||
)
|
||||
return llm_bundler_metadata_options_c.LlmBundlerMetadataOptionsC(
|
||||
start_token=start_token_c,
|
||||
stop_tokens=stop_tokens_c,
|
||||
num_stop_tokens=len(self.stop_tokens),
|
||||
enable_bytes_to_unicode_mapping=self.enable_bytes_to_unicode_mapping,
|
||||
system_prompt=system_prompt_c,
|
||||
prompt_prefix_user=prompt_prefix_user_c,
|
||||
prompt_suffix_user=prompt_suffix_user_c,
|
||||
prompt_prefix_model=prompt_prefix_model_c,
|
||||
prompt_suffix_model=prompt_suffix_model_c,
|
||||
prompt_prefix_system=prompt_prefix_system_c,
|
||||
prompt_suffix_system=prompt_suffix_system_c,
|
||||
user_role_token=user_role_token_c,
|
||||
system_role_token=system_role_token_c,
|
||||
model_role_token=model_role_token_c,
|
||||
end_role_token=end_role_token_c,
|
||||
)
|
||||
+38
@@ -0,0 +1,38 @@
|
||||
# Copyright 2026 The MediaPipe Authors.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""Ctypes wrapper for LlmBundlerMetadataOptions."""
|
||||
|
||||
import ctypes
|
||||
|
||||
|
||||
class LlmBundlerMetadataOptionsC(ctypes.Structure):
|
||||
"""Wrapper for LlmBundlerMetadataOptions in C."""
|
||||
|
||||
_fields_ = [
|
||||
("start_token", ctypes.c_char_p),
|
||||
("stop_tokens", ctypes.POINTER(ctypes.c_char_p)),
|
||||
("num_stop_tokens", ctypes.c_int),
|
||||
("enable_bytes_to_unicode_mapping", ctypes.c_bool),
|
||||
("system_prompt", ctypes.c_char_p),
|
||||
("prompt_prefix_user", ctypes.c_char_p),
|
||||
("prompt_suffix_user", ctypes.c_char_p),
|
||||
("prompt_prefix_model", ctypes.c_char_p),
|
||||
("prompt_suffix_model", ctypes.c_char_p),
|
||||
("prompt_prefix_system", ctypes.c_char_p),
|
||||
("prompt_suffix_system", ctypes.c_char_p),
|
||||
("user_role_token", ctypes.c_char_p),
|
||||
("system_role_token", ctypes.c_char_p),
|
||||
("model_role_token", ctypes.c_char_p),
|
||||
("end_role_token", ctypes.c_char_p),
|
||||
]
|
||||
+60
@@ -0,0 +1,60 @@
|
||||
# Copyright 2026 The MediaPipe Authors.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from absl.testing import absltest
|
||||
from mediapipe.tasks.python.genai.bundler import llm_bundler_metadata_options
|
||||
|
||||
|
||||
class LlmBundlerMetadataOptionsTest(absltest.TestCase):
|
||||
|
||||
def test_to_ctypes(self):
|
||||
options = llm_bundler_metadata_options.LlmBundlerMetadataOptions(
|
||||
start_token="start",
|
||||
stop_tokens=["stop1", "stop2"],
|
||||
enable_bytes_to_unicode_mapping=True,
|
||||
system_prompt="system",
|
||||
prompt_prefix_user="user_prefix",
|
||||
prompt_suffix_user="user_suffix",
|
||||
prompt_prefix_model="model_prefix",
|
||||
prompt_suffix_model="model_suffix",
|
||||
prompt_prefix_system=None,
|
||||
prompt_suffix_system=None,
|
||||
user_role_token="user_role",
|
||||
system_role_token=None,
|
||||
model_role_token="model_role",
|
||||
end_role_token="end_role",
|
||||
)
|
||||
|
||||
options_c = options.to_ctypes()
|
||||
|
||||
self.assertEqual(options_c.start_token, b"start")
|
||||
self.assertEqual(options_c.stop_tokens[0], b"stop1")
|
||||
self.assertEqual(options_c.stop_tokens[1], b"stop2")
|
||||
self.assertEqual(options_c.num_stop_tokens, 2)
|
||||
self.assertTrue(options_c.enable_bytes_to_unicode_mapping)
|
||||
self.assertEqual(options_c.system_prompt, b"system")
|
||||
self.assertEqual(options_c.prompt_prefix_user, b"user_prefix")
|
||||
self.assertEqual(options_c.prompt_suffix_user, b"user_suffix")
|
||||
self.assertEqual(options_c.prompt_prefix_model, b"model_prefix")
|
||||
self.assertEqual(options_c.prompt_suffix_model, b"model_suffix")
|
||||
self.assertIsNone(options_c.prompt_prefix_system)
|
||||
self.assertIsNone(options_c.prompt_suffix_system)
|
||||
self.assertEqual(options_c.user_role_token, b"user_role")
|
||||
self.assertIsNone(options_c.system_role_token)
|
||||
self.assertEqual(options_c.model_role_token, b"model_role")
|
||||
self.assertEqual(options_c.end_role_token, b"end_role")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
absltest.main()
|
||||
Reference in New Issue
Block a user