mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-07-29 07:14:20 +00:00
update inference config to take model and not model_dir
This commit is contained in:
Hardik Shah
parent
08c3802f45
commit
039861f1c7
9 changed files with 400 additions and 101 deletions
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@ -75,11 +75,13 @@ safetensors files to avoid downloading duplicate weights.
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from huggingface_hub import snapshot_download
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from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
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from llama_toolchain.common.model_utils import model_local_dir
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repo_id = model.huggingface_repo
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if repo_id is None:
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raise ValueError(f"No repo id found for model {model.descriptor()}")
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output_dir = Path(DEFAULT_CHECKPOINT_DIR) / model.descriptor()
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output_dir = model_local_dir(model)
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os.makedirs(output_dir, exist_ok=True)
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try:
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true_output_dir = snapshot_download(
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@ -107,8 +109,9 @@ safetensors files to avoid downloading duplicate weights.
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def _meta_download(self, model: "Model", meta_url: str):
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from llama_models.sku_list import llama_meta_net_info
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from llama_toolchain.common.model_utils import model_local_dir
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output_dir = Path(DEFAULT_CHECKPOINT_DIR) / model.descriptor()
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output_dir = model_local_dir(model)
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os.makedirs(output_dir, exist_ok=True)
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info = llama_meta_net_info(model)
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8
llama_toolchain/common/model_utils.py
Normal file
8
llama_toolchain/common/model_utils.py
Normal file
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@ -0,0 +1,8 @@
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import os
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from llama_models.datatypes import Model
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from .config_dirs import DEFAULT_CHECKPOINT_DIR
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def model_local_dir(model: Model) -> str:
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return os.path.join(DEFAULT_CHECKPOINT_DIR, model.descriptor())
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@ -4,61 +4,17 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from enum import Enum
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from typing import Literal, Optional, Union
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from typing import Optional
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from llama_models.llama3_1.api.datatypes import CheckpointQuantizationFormat
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from pydantic import BaseModel, Field
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from pydantic import BaseModel
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from strong_typing.schema import json_schema_type
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from typing_extensions import Annotated
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from llama_toolchain.inference.api import QuantizationConfig
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@json_schema_type
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class CheckpointType(Enum):
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pytorch = "pytorch"
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huggingface = "huggingface"
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@json_schema_type
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class PytorchCheckpoint(BaseModel):
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checkpoint_type: Literal[CheckpointType.pytorch.value] = (
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CheckpointType.pytorch.value
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)
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checkpoint_dir: str
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tokenizer_path: str
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model_parallel_size: int
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quantization_format: CheckpointQuantizationFormat = (
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CheckpointQuantizationFormat.bf16
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)
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@json_schema_type
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class HuggingFaceCheckpoint(BaseModel):
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checkpoint_type: Literal[CheckpointType.huggingface.value] = (
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CheckpointType.huggingface.value
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)
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repo_id: str # or model_name ?
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model_parallel_size: int
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quantization_format: CheckpointQuantizationFormat = (
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CheckpointQuantizationFormat.bf16
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)
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@json_schema_type
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class ModelCheckpointConfig(BaseModel):
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checkpoint: Annotated[
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Union[PytorchCheckpoint, HuggingFaceCheckpoint],
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Field(discriminator="checkpoint_type"),
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]
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@json_schema_type
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class MetaReferenceImplConfig(BaseModel):
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model: str
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checkpoint_config: ModelCheckpointConfig
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quantization: Optional[QuantizationConfig] = None
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torch_seed: Optional[int] = None
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max_seq_len: int
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@ -27,11 +27,22 @@ from llama_models.llama3_1.api.chat_format import ChatFormat, ModelInput
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from llama_models.llama3_1.api.datatypes import Message
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from llama_models.llama3_1.api.model import Transformer
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from llama_models.llama3_1.api.tokenizer import Tokenizer
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from llama_models.sku_list import resolve_model
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from termcolor import cprint
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from llama_toolchain.common.model_utils import model_local_dir
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from llama_toolchain.inference.api import QuantizationType
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from .config import CheckpointType, MetaReferenceImplConfig
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from .config import MetaReferenceImplConfig
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def model_checkpoint_dir(model) -> str:
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checkpoint_dir = Path(model_local_dir(model))
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if not Path(checkpoint_dir / "consolidated.00.pth").exists():
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checkpoint_dir = checkpoint_dir / "original"
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assert checkpoint_dir.exists(), f"Could not find checkpoint dir: {checkpoint_dir}"
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return str(checkpoint_dir)
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@dataclass
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@ -51,9 +62,7 @@ class Llama:
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This method initializes the distributed process group, sets the device to CUDA,
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and loads the pre-trained model and tokenizer.
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"""
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checkpoint = config.checkpoint_config.checkpoint
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if checkpoint.checkpoint_type != CheckpointType.pytorch.value:
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raise NotImplementedError("HuggingFace checkpoints not supported yet")
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model = resolve_model(config.model)
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if (
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config.quantization
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@ -67,7 +76,7 @@ class Llama:
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if not torch.distributed.is_initialized():
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torch.distributed.init_process_group("nccl")
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model_parallel_size = checkpoint.model_parallel_size
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model_parallel_size = model.hardware_requirements.gpu_count
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if not model_parallel_is_initialized():
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initialize_model_parallel(model_parallel_size)
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@ -82,7 +91,8 @@ class Llama:
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sys.stdout = open(os.devnull, "w")
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start_time = time.time()
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ckpt_dir = checkpoint.checkpoint_dir
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ckpt_dir = model_checkpoint_dir(model)
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checkpoints = sorted(Path(ckpt_dir).glob("*.pth"))
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assert len(checkpoints) > 0, f"no checkpoint files found in {ckpt_dir}"
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assert model_parallel_size == len(
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@ -103,7 +113,9 @@ class Llama:
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max_batch_size=config.max_batch_size,
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**params,
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)
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tokenizer = Tokenizer(model_path=checkpoint.tokenizer_path)
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tokenizer_path = os.path.join(ckpt_dir, "tokenizer.model")
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tokenizer = Tokenizer(model_path=tokenizer_path)
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assert (
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model_args.vocab_size == tokenizer.n_words
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@ -4,6 +4,7 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import os
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from copy import deepcopy
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from dataclasses import dataclass
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from functools import partial
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@ -12,9 +13,10 @@ from typing import Generator, List, Optional
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from llama_models.llama3_1.api.chat_format import ChatFormat
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from llama_models.llama3_1.api.datatypes import Message
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from llama_models.llama3_1.api.tokenizer import Tokenizer
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from llama_models.sku_list import resolve_model
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from .config import MetaReferenceImplConfig
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from .generation import Llama
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from .generation import Llama, model_checkpoint_dir
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from .parallel_utils import ModelParallelProcessGroup
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@ -60,11 +62,12 @@ class LlamaModelParallelGenerator:
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def __init__(self, config: MetaReferenceImplConfig):
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self.config = config
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self.model = resolve_model(self.config.model)
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# this is a hack because Agent's loop uses this to tokenize and check if input is too long
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# while the tool-use loop is going
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checkpoint = self.config.checkpoint_config.checkpoint
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self.formatter = ChatFormat(Tokenizer(checkpoint.tokenizer_path))
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checkpoint_dir = model_checkpoint_dir(self.model)
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tokenizer_path = os.path.join(checkpoint_dir, "tokenizer.model")
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self.formatter = ChatFormat(Tokenizer(tokenizer_path))
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def start(self):
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self.__enter__()
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@ -73,9 +76,8 @@ class LlamaModelParallelGenerator:
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self.__exit__(None, None, None)
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def __enter__(self):
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checkpoint = self.config.checkpoint_config.checkpoint
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self.group = ModelParallelProcessGroup(
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checkpoint.model_parallel_size,
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self.model.hardware_requirements.gpu_count,
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init_model_cb=partial(init_model_cb, self.config),
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)
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self.group.start()
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@ -44,11 +44,13 @@ OLLAMA_SUPPORTED_SKUS = {
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}
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def get_provider_impl(config: OllamaImplConfig) -> Inference:
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async def get_provider_impl(config: OllamaImplConfig) -> Inference:
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assert isinstance(
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config, OllamaImplConfig
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), f"Unexpected config type: {type(config)}"
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return OllamaInference(config)
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impl = OllamaInference(config)
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await impl.initialize()
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return impl
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class OllamaInference(Inference):
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340
ollama_install.sh
Normal file
340
ollama_install.sh
Normal file
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@ -0,0 +1,340 @@
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#!/bin/sh
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# This script installs Ollama on Linux.
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# It detects the current operating system architecture and installs the appropriate version of Ollama.
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set -eu
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status() { echo ">>> $*" >&2; }
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error() { echo "ERROR $*"; exit 1; }
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warning() { echo "WARNING: $*"; }
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TEMP_DIR=$(mktemp -d)
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cleanup() { rm -rf $TEMP_DIR; }
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trap cleanup EXIT
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available() { command -v $1 >/dev/null; }
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require() {
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local MISSING=''
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for TOOL in $*; do
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if ! available $TOOL; then
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MISSING="$MISSING $TOOL"
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fi
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done
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echo $MISSING
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}
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[ "$(uname -s)" = "Linux" ] || error 'This script is intended to run on Linux only.'
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ARCH=$(uname -m)
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case "$ARCH" in
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x86_64) ARCH="amd64" ;;
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aarch64|arm64) ARCH="arm64" ;;
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*) error "Unsupported architecture: $ARCH" ;;
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esac
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IS_WSL2=false
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KERN=$(uname -r)
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case "$KERN" in
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*icrosoft*WSL2 | *icrosoft*wsl2) IS_WSL2=true;;
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*icrosoft) error "Microsoft WSL1 is not currently supported. Please upgrade to WSL2 with 'wsl --set-version <distro> 2'" ;;
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*) ;;
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esac
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VER_PARAM="${OLLAMA_VERSION:+?version=$OLLAMA_VERSION}"
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SUDO=
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if [ "$(id -u)" -ne 0 ]; then
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# Running as root, no need for sudo
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if ! available sudo; then
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error "This script requires superuser permissions. Please re-run as root."
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fi
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SUDO="sudo"
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fi
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NEEDS=$(require curl awk grep sed tee xargs)
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if [ -n "$NEEDS" ]; then
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status "ERROR: The following tools are required but missing:"
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for NEED in $NEEDS; do
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echo " - $NEED"
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done
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exit 1
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fi
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status "Downloading ollama..."
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curl --fail --show-error --location --progress-bar -o $TEMP_DIR/ollama "https://ollama.com/download/ollama-linux-${ARCH}${VER_PARAM}"
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for BINDIR in /usr/local/bin /usr/bin /bin; do
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echo $PATH | grep -q $BINDIR && break || continue
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done
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status "Installing ollama to $BINDIR..."
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$SUDO install -o0 -g0 -m755 -d $BINDIR
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$SUDO install -o0 -g0 -m755 $TEMP_DIR/ollama $BINDIR/ollama
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install_success() {
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status 'The Ollama API is now available at 127.0.0.1:11434.'
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status 'Install complete. Run "ollama" from the command line.'
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}
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trap install_success EXIT
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# Everything from this point onwards is optional.
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configure_systemd() {
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if ! id ollama >/dev/null 2>&1; then
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status "Creating ollama user..."
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$SUDO useradd -r -s /bin/false -U -m -d /usr/share/ollama ollama
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fi
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if getent group render >/dev/null 2>&1; then
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status "Adding ollama user to render group..."
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$SUDO usermod -a -G render ollama
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fi
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if getent group video >/dev/null 2>&1; then
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status "Adding ollama user to video group..."
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$SUDO usermod -a -G video ollama
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fi
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status "Adding current user to ollama group..."
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$SUDO usermod -a -G ollama $(whoami)
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status "Creating ollama systemd service..."
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cat <<EOF | $SUDO tee /etc/systemd/system/ollama.service >/dev/null
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[Unit]
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Description=Ollama Service
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After=network-online.target
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[Service]
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ExecStart=$BINDIR/ollama serve
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User=ollama
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Group=ollama
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Restart=always
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RestartSec=3
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Environment="PATH=$PATH"
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[Install]
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WantedBy=default.target
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EOF
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SYSTEMCTL_RUNNING="$(systemctl is-system-running || true)"
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case $SYSTEMCTL_RUNNING in
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running|degraded)
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status "Enabling and starting ollama service..."
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$SUDO systemctl daemon-reload
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$SUDO systemctl enable ollama
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start_service() { $SUDO systemctl restart ollama; }
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trap start_service EXIT
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;;
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esac
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}
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if available systemctl; then
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configure_systemd
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fi
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# WSL2 only supports GPUs via nvidia passthrough
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# so check for nvidia-smi to determine if GPU is available
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if [ "$IS_WSL2" = true ]; then
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if available nvidia-smi && [ -n "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; then
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status "Nvidia GPU detected."
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fi
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install_success
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exit 0
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fi
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# Install GPU dependencies on Linux
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if ! available lspci && ! available lshw; then
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warning "Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies."
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exit 0
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fi
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check_gpu() {
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# Look for devices based on vendor ID for NVIDIA and AMD
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case $1 in
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lspci)
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case $2 in
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nvidia) available lspci && lspci -d '10de:' | grep -q 'NVIDIA' || return 1 ;;
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amdgpu) available lspci && lspci -d '1002:' | grep -q 'AMD' || return 1 ;;
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esac ;;
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lshw)
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case $2 in
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nvidia) available lshw && $SUDO lshw -c display -numeric -disable network | grep -q 'vendor: .* \[10DE\]' || return 1 ;;
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amdgpu) available lshw && $SUDO lshw -c display -numeric -disable network | grep -q 'vendor: .* \[1002\]' || return 1 ;;
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esac ;;
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nvidia-smi) available nvidia-smi || return 1 ;;
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esac
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}
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if check_gpu nvidia-smi; then
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status "NVIDIA GPU installed."
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exit 0
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fi
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if ! check_gpu lspci nvidia && ! check_gpu lshw nvidia && ! check_gpu lspci amdgpu && ! check_gpu lshw amdgpu; then
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install_success
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warning "No NVIDIA/AMD GPU detected. Ollama will run in CPU-only mode."
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exit 0
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fi
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if check_gpu lspci amdgpu || check_gpu lshw amdgpu; then
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# Look for pre-existing ROCm v6 before downloading the dependencies
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for search in "${HIP_PATH:-''}" "${ROCM_PATH:-''}" "/opt/rocm" "/usr/lib64"; do
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if [ -n "${search}" ] && [ -e "${search}/libhipblas.so.2" -o -e "${search}/lib/libhipblas.so.2" ]; then
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status "Compatible AMD GPU ROCm library detected at ${search}"
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install_success
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exit 0
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fi
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done
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status "Downloading AMD GPU dependencies..."
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$SUDO rm -rf /usr/share/ollama/lib
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$SUDO chmod o+x /usr/share/ollama
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$SUDO install -o ollama -g ollama -m 755 -d /usr/share/ollama/lib/rocm
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curl --fail --show-error --location --progress-bar "https://ollama.com/download/ollama-linux-amd64-rocm.tgz${VER_PARAM}" \
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| $SUDO tar zx --owner ollama --group ollama -C /usr/share/ollama/lib/rocm .
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install_success
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status "AMD GPU ready."
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exit 0
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fi
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CUDA_REPO_ERR_MSG="NVIDIA GPU detected, but your OS and Architecture are not supported by NVIDIA. Please install the CUDA driver manually https://docs.nvidia.com/cuda/cuda-installation-guide-linux/"
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# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-7-centos-7
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# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-8-rocky-8
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# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-9-rocky-9
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# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#fedora
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install_cuda_driver_yum() {
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status 'Installing NVIDIA repository...'
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case $PACKAGE_MANAGER in
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yum)
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$SUDO $PACKAGE_MANAGER -y install yum-utils
|
||||
if curl -I --silent --fail --location "https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo" >/dev/null ; then
|
||||
$SUDO $PACKAGE_MANAGER-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo
|
||||
else
|
||||
error $CUDA_REPO_ERR_MSG
|
||||
fi
|
||||
;;
|
||||
dnf)
|
||||
if curl -I --silent --fail --location "https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo" >/dev/null ; then
|
||||
$SUDO $PACKAGE_MANAGER config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo
|
||||
else
|
||||
error $CUDA_REPO_ERR_MSG
|
||||
fi
|
||||
;;
|
||||
esac
|
||||
|
||||
case $1 in
|
||||
rhel)
|
||||
status 'Installing EPEL repository...'
|
||||
# EPEL is required for third-party dependencies such as dkms and libvdpau
|
||||
$SUDO $PACKAGE_MANAGER -y install https://dl.fedoraproject.org/pub/epel/epel-release-latest-$2.noarch.rpm || true
|
||||
;;
|
||||
esac
|
||||
|
||||
status 'Installing CUDA driver...'
|
||||
|
||||
if [ "$1" = 'centos' ] || [ "$1$2" = 'rhel7' ]; then
|
||||
$SUDO $PACKAGE_MANAGER -y install nvidia-driver-latest-dkms
|
||||
fi
|
||||
|
||||
$SUDO $PACKAGE_MANAGER -y install cuda-drivers
|
||||
}
|
||||
|
||||
# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu
|
||||
# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#debian
|
||||
install_cuda_driver_apt() {
|
||||
status 'Installing NVIDIA repository...'
|
||||
if curl -I --silent --fail --location "https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-keyring_1.1-1_all.deb" >/dev/null ; then
|
||||
curl -fsSL -o $TEMP_DIR/cuda-keyring.deb https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-keyring_1.1-1_all.deb
|
||||
else
|
||||
error $CUDA_REPO_ERR_MSG
|
||||
fi
|
||||
|
||||
case $1 in
|
||||
debian)
|
||||
status 'Enabling contrib sources...'
|
||||
$SUDO sed 's/main/contrib/' < /etc/apt/sources.list | $SUDO tee /etc/apt/sources.list.d/contrib.list > /dev/null
|
||||
if [ -f "/etc/apt/sources.list.d/debian.sources" ]; then
|
||||
$SUDO sed 's/main/contrib/' < /etc/apt/sources.list.d/debian.sources | $SUDO tee /etc/apt/sources.list.d/contrib.sources > /dev/null
|
||||
fi
|
||||
;;
|
||||
esac
|
||||
|
||||
status 'Installing CUDA driver...'
|
||||
$SUDO dpkg -i $TEMP_DIR/cuda-keyring.deb
|
||||
$SUDO apt-get update
|
||||
|
||||
[ -n "$SUDO" ] && SUDO_E="$SUDO -E" || SUDO_E=
|
||||
DEBIAN_FRONTEND=noninteractive $SUDO_E apt-get -y install cuda-drivers -q
|
||||
}
|
||||
|
||||
if [ ! -f "/etc/os-release" ]; then
|
||||
error "Unknown distribution. Skipping CUDA installation."
|
||||
fi
|
||||
|
||||
. /etc/os-release
|
||||
|
||||
OS_NAME=$ID
|
||||
OS_VERSION=$VERSION_ID
|
||||
|
||||
PACKAGE_MANAGER=
|
||||
for PACKAGE_MANAGER in dnf yum apt-get; do
|
||||
if available $PACKAGE_MANAGER; then
|
||||
break
|
||||
fi
|
||||
done
|
||||
|
||||
if [ -z "$PACKAGE_MANAGER" ]; then
|
||||
error "Unknown package manager. Skipping CUDA installation."
|
||||
fi
|
||||
|
||||
if ! check_gpu nvidia-smi || [ -z "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; then
|
||||
case $OS_NAME in
|
||||
centos|rhel) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -d '.' -f 1) ;;
|
||||
rocky) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -c1) ;;
|
||||
fedora) [ $OS_VERSION -lt '39' ] && install_cuda_driver_yum $OS_NAME $OS_VERSION || install_cuda_driver_yum $OS_NAME '39';;
|
||||
amzn) install_cuda_driver_yum 'fedora' '37' ;;
|
||||
debian) install_cuda_driver_apt $OS_NAME $OS_VERSION ;;
|
||||
ubuntu) install_cuda_driver_apt $OS_NAME $(echo $OS_VERSION | sed 's/\.//') ;;
|
||||
*) exit ;;
|
||||
esac
|
||||
fi
|
||||
|
||||
if ! lsmod | grep -q nvidia || ! lsmod | grep -q nvidia_uvm; then
|
||||
KERNEL_RELEASE="$(uname -r)"
|
||||
case $OS_NAME in
|
||||
rocky) $SUDO $PACKAGE_MANAGER -y install kernel-devel kernel-headers ;;
|
||||
centos|rhel|amzn) $SUDO $PACKAGE_MANAGER -y install kernel-devel-$KERNEL_RELEASE kernel-headers-$KERNEL_RELEASE ;;
|
||||
fedora) $SUDO $PACKAGE_MANAGER -y install kernel-devel-$KERNEL_RELEASE ;;
|
||||
debian|ubuntu) $SUDO apt-get -y install linux-headers-$KERNEL_RELEASE ;;
|
||||
*) exit ;;
|
||||
esac
|
||||
|
||||
NVIDIA_CUDA_VERSION=$($SUDO dkms status | awk -F: '/added/ { print $1 }')
|
||||
if [ -n "$NVIDIA_CUDA_VERSION" ]; then
|
||||
$SUDO dkms install $NVIDIA_CUDA_VERSION
|
||||
fi
|
||||
|
||||
if lsmod | grep -q nouveau; then
|
||||
status 'Reboot to complete NVIDIA CUDA driver install.'
|
||||
exit 0
|
||||
fi
|
||||
|
||||
$SUDO modprobe nvidia
|
||||
$SUDO modprobe nvidia_uvm
|
||||
fi
|
||||
|
||||
# make sure the NVIDIA modules are loaded on boot with nvidia-persistenced
|
||||
if command -v nvidia-persistenced > /dev/null 2>&1; then
|
||||
$SUDO touch /etc/modules-load.d/nvidia.conf
|
||||
MODULES="nvidia nvidia-uvm"
|
||||
for MODULE in $MODULES; do
|
||||
if ! grep -qxF "$MODULE" /etc/modules-load.d/nvidia.conf; then
|
||||
echo "$MODULE" | sudo tee -a /etc/modules-load.d/nvidia.conf > /dev/null
|
||||
fi
|
||||
done
|
||||
fi
|
||||
|
||||
status "NVIDIA GPU ready."
|
||||
install_success
|
||||
|
|
@ -14,24 +14,18 @@ from llama_models.llama3_1.api.datatypes import (
|
|||
StopReason,
|
||||
SystemMessage,
|
||||
)
|
||||
|
||||
from llama_toolchain.inference.api.config import (
|
||||
InferenceConfig,
|
||||
InlineImplConfig,
|
||||
RemoteImplConfig,
|
||||
ModelCheckpointConfig,
|
||||
PytorchCheckpoint,
|
||||
CheckpointQuantizationFormat,
|
||||
)
|
||||
from llama_toolchain.inference.api_instance import (
|
||||
get_inference_api_instance,
|
||||
)
|
||||
from llama_toolchain.inference.api.datatypes import (
|
||||
ChatCompletionResponseEventType,
|
||||
)
|
||||
from llama_toolchain.inference.meta_reference.inference import get_provider_impl
|
||||
from llama_toolchain.inference.meta_reference.config import (
|
||||
MetaReferenceImplConfig,
|
||||
)
|
||||
|
||||
from llama_toolchain.inference.api.endpoints import ChatCompletionRequest
|
||||
|
||||
|
||||
MODEL = "Meta-Llama3.1-8B-Instruct"
|
||||
HELPER_MSG = """
|
||||
This test needs llama-3.1-8b-instruct models.
|
||||
Please donwload using the llama cli
|
||||
|
|
@ -50,32 +44,18 @@ class InferenceTests(unittest.IsolatedAsyncioTestCase):
|
|||
@classmethod
|
||||
async def asyncSetUpClass(cls):
|
||||
# assert model exists on local
|
||||
model_dir = os.path.expanduser(
|
||||
"~/.llama/checkpoints/Meta-Llama-3.1-8B-Instruct/original/"
|
||||
)
|
||||
model_dir = os.path.expanduser(f"~/.llama/checkpoints/{MODEL}/original/")
|
||||
assert os.path.isdir(model_dir), HELPER_MSG
|
||||
|
||||
tokenizer_path = os.path.join(model_dir, "tokenizer.model")
|
||||
assert os.path.exists(tokenizer_path), HELPER_MSG
|
||||
|
||||
inline_config = InlineImplConfig(
|
||||
checkpoint_config=ModelCheckpointConfig(
|
||||
checkpoint=PytorchCheckpoint(
|
||||
checkpoint_dir=model_dir,
|
||||
tokenizer_path=tokenizer_path,
|
||||
model_parallel_size=1,
|
||||
quantization_format=CheckpointQuantizationFormat.bf16,
|
||||
)
|
||||
),
|
||||
config = MetaReferenceImplConfig(
|
||||
model=MODEL,
|
||||
max_seq_len=2048,
|
||||
)
|
||||
inference_config = InferenceConfig(impl_config=inline_config)
|
||||
|
||||
# -- For faster testing iteration --
|
||||
# remote_config = RemoteImplConfig(url="http://localhost:5000")
|
||||
# inference_config = InferenceConfig(impl_config=remote_config)
|
||||
|
||||
cls.api = await get_inference_api_instance(inference_config)
|
||||
cls.api = await get_provider_impl(config, {})
|
||||
await cls.api.initialize()
|
||||
|
||||
current_date = datetime.now()
|
||||
|
|
@ -134,7 +114,7 @@ class InferenceTests(unittest.IsolatedAsyncioTestCase):
|
|||
await cls.api.shutdown()
|
||||
|
||||
async def asyncSetUp(self):
|
||||
self.valid_supported_model = "Meta-Llama3.1-8B-Instruct"
|
||||
self.valid_supported_model = MODEL
|
||||
|
||||
async def test_text(self):
|
||||
request = ChatCompletionRequest(
|
||||
|
|
|
|||
|
|
@ -10,14 +10,12 @@ from llama_models.llama3_1.api.datatypes import (
|
|||
SamplingStrategy,
|
||||
SystemMessage,
|
||||
)
|
||||
from llama_toolchain.inference.api_instance import (
|
||||
get_inference_api_instance,
|
||||
)
|
||||
from llama_toolchain.inference.api.datatypes import (
|
||||
ChatCompletionResponseEventType,
|
||||
)
|
||||
from llama_toolchain.inference.api.endpoints import ChatCompletionRequest
|
||||
from llama_toolchain.inference.api.config import InferenceConfig, OllamaImplConfig
|
||||
from llama_toolchain.inference.ollama.config import OllamaImplConfig
|
||||
from llama_toolchain.inference.ollama.ollama import get_provider_impl
|
||||
|
||||
|
||||
class OllamaInferenceTests(unittest.IsolatedAsyncioTestCase):
|
||||
|
|
@ -30,9 +28,7 @@ class OllamaInferenceTests(unittest.IsolatedAsyncioTestCase):
|
|||
)
|
||||
|
||||
# setup ollama
|
||||
self.api = await get_inference_api_instance(
|
||||
InferenceConfig(impl_config=ollama_config)
|
||||
)
|
||||
self.api = await get_provider_impl(ollama_config)
|
||||
await self.api.initialize()
|
||||
|
||||
current_date = datetime.now()
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue