diff --git a/Makefile b/Makefile index 178b065..47f0ab9 100644 --- a/Makefile +++ b/Makefile @@ -30,10 +30,5 @@ build: lint poetry build .PHONY: publish -publish: build export-requirements - poetry publish --username=__token__ --password=$(PYPI_TOKEN) - -.PHONEY: export-requirements -export-requirements: - poetry export -f requirements.txt -o requirements.txt --without-hashes - poetry export -f requirements.txt -o requirements-dev.txt --without-hashes --with dev +publish: build + poetry publish --username=__token__ --password=$(INFTYAI_PYPI_TOKEN) diff --git a/README.md b/README.md index ea9212b..882b316 100644 --- a/README.md +++ b/README.md @@ -1,134 +1,9 @@ -# llmlite +# AMRS - [![Latest Release](https://img.shields.io/github/v/release/inftyai/llmlite?include_prereleases)](https://github.com/inftyai/llmlite/releases/latest) + [![Latest Release](https://img.shields.io/github/v/release/inftyai/amrs?include_prereleases)](https://github.com/inftyai/amrs/releases/latest) -**🌵** llmlite is a library helps to communicate with all kinds of LLMs consistently. - -## Features - -- State-of-the-art LLMs support -- Continuous Batching via [vLLM](https://github.com/vllm-project/vllm) -- Quantization([issue#37] ()) -- Loading specific adapters ([issue#51](https://github.com/InftyAI/llmlite/issues/51)) -- Streaming ([issue#52](https://github.com/InftyAI/llmlite/issues/52)) - -### Model Support - -| Model | State | System Prompt | Note | -| ---- | ---- | ---- | ---- | -| ChatGPT | Done ✅ | Yes | | -| Llama-2 | Done ✅ | Yes | | -| CodeLlama | Done ✅ | Yes | | -| ChatGLM2 | Done ✅ | No | | -| Baichuan2 | Done ✅ | Yes | | -| ChatGLM3 | WIP ⏳ | Yes | | -| Claude-2 | RoadMap 📋 | | [issue#7](https://github.com/InftyAI/ChatLLM/issues/7) -| Falcon | RoadMap 📋 | | [issue#8](https://github.com/InftyAI/ChatLLM/issues/8) -| StableLM | RoadMap 📋 | | [issue#11](https://github.com/InftyAI/ChatLLM/issues/11) | - -### Backend Support - -| backend | State | -| ---- | ---- | -| [huggingface](https://github.com/huggingface) | Done ✅ | -| [vLLM](https://github.com/vllm-project/vllm) | Done ✅ | - -## How to install - -```cmd -pip install llmlite==0.0.15 -``` - -## How to use - -### Chat - -```python -from llmlite import ChatLLM, ChatMessage - -chat = ChatLLM( - model_name_or_path="meta-llama/Llama-2-7b-chat-hf", # required - task="text-generation", - ) - -result = chat.completion( - messages=[ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage(role="user", content="There's a llama in my garden, what should I do?"), - ] -) - -# Output: Oh my goodness, a llama in your garden?! 😱 That's quite a surprise! 😅 As an honest assistant, I must inform you that llamas are not typically known for their gardening skills, so it's possible that the llama in your garden may have wandered there accidentally or is seeking shelter. 🐮 ... - -``` - -### Continuous Batching - -_This is mostly supported by vLLM, you can enable this by configuring the **backend**._ - -```python -from llmlite import ChatLLM, ChatMessage - -chat = ChatLLM( - model_name_or_path="meta-llama/Llama-2-7b-chat-hf", - backend="vllm", -) - -results = chat.completion( - messages=[ - [ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage( role="user", content="There's a llama in my garden, what should I do?"), - ], - [ - ChatMessage(role="user", content="What's the population of the world?"), - ], - ], - max_tokens=2048, -) - -for result in results: - print(f"RESULT: \n{result}\n\n") -``` - -`llmlite` also supports other parameters like `temperature`, `max_length`, `do_sample`, `top_k`, `top_p` to help control the length, randomness and diversity of the generated text. - -See **[examples](./examples/)** for reference. - -### Prompting - -You can use `llmlite` to help you generate full prompts, for instance: - -```python -from llmlite import ChatLLM - -messages = [ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage(role="user", content="There's a llama in my garden, what should I do?"), -] - -ChatLLM.prompt("meta-llama/Llama-2-7b-chat-hf", messages) - -# Output: -# [INST] <> -# You're a honest assistant. -# <> - -# There's a llama in my garden, what should I do? [/INST] -``` - -### Logging - -Set the env variable `LOG_LEVEL` for log configuration, default to `INFO`, others like DEBUG, INFO, WARNING etc.. +The Adaptive Model Routing System (AMRS) is a cutting-edge framework designed to select the best-fit model for exploration and exploitation. ## Contributions 🚀 All kinds of contributions are welcomed ! Please follow [Contributing](/CONTRIBUTING.md). - -## Contributors - -🎉 Thanks to all these contributors. - - - - diff --git a/llmlite/apis/__init__.py b/amrs/__init__.py similarity index 100% rename from llmlite/apis/__init__.py rename to amrs/__init__.py diff --git a/examples/chatglm2.py b/examples/chatglm2.py deleted file mode 100644 index cb293e6..0000000 --- a/examples/chatglm2.py +++ /dev/null @@ -1,20 +0,0 @@ -from llmlite import ChatLLM, ChatMessage - -chat = ChatLLM( - model_name_or_path="THUDM/chatglm2-6b", - # temperature=0.2, - # max_length=2048, - # do_sample=True, - # top_p=0.7, - # top_k=3, -) - -# chatglm2 doesn't support system prompt -result = chat.completion( - messages=[ - ChatMessage(role="user", content="中国共有多少人口？"), - ], - temperature=0.7, # You can also overwrite the configurations in each conservation. -) - -print(result) diff --git a/examples/chatgpt.py b/examples/chatgpt.py deleted file mode 100644 index 6c93941..0000000 --- a/examples/chatgpt.py +++ /dev/null @@ -1,18 +0,0 @@ -from llmlite import ChatLLM, ChatMessage - -# You should set the OPENAI_API_KEY first. - -chat = ChatLLM( - model_name_or_path="gpt-3.5-turbo", -) - -result = chat.completion( - messages=[ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage( - role="user", content="There's a llama in my garden, what should I do?" - ), - ], -) - -print(result) diff --git a/examples/codellama.py b/examples/codellama.py deleted file mode 100644 index 5821364..0000000 --- a/examples/codellama.py +++ /dev/null @@ -1,22 +0,0 @@ -from llmlite import ChatLLM, ChatMessage - -chat = ChatLLM( - model_name_or_path="codellama/CodeLlama-13b-instruct-hf", - task="text-generation", - max_length=2048, - # temperature=0.2, - # do_sample=True, - # top_p=0.7, - # top_k=3, -) - -result = chat.completion( - messages=[ - ChatMessage( - role="user", - content="import socket\n\ndef ping_exponential_backoff(host: str):", - ), - ] -) - -print(result) diff --git a/examples/llama2.py b/examples/llama2.py deleted file mode 100644 index e49a0d8..0000000 --- a/examples/llama2.py +++ /dev/null @@ -1,21 +0,0 @@ -from llmlite import ChatLLM, ChatMessage - -chat = ChatLLM( - model_name_or_path="meta-llama/Llama-2-7b-chat-hf", - task="text-generation", - # temperature=0.2, - # do_sample=True, - # top_p=0.7, - # top_k=3, -) - -result = chat.completion( - messages=[ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage( - role="user", content="There's a llama in my garden, what should I do?" - ), - ], -) - -print(result) diff --git a/examples/vllm.py b/examples/vllm.py deleted file mode 100644 index c661bde..0000000 --- a/examples/vllm.py +++ /dev/null @@ -1,27 +0,0 @@ -from llmlite import ChatLLM, ChatMessage - -chat = ChatLLM( - model_name_or_path="meta-llama/Llama-2-7b-chat-hf", - backend="vllm", -) - -results = chat.completion( - messages=[ - [ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage( - role="user", content="There's a llama in my garden, what should I do?" - ), - ], - [ - ChatMessage(role="user", content="How many people are there in China?"), - ], - ], - max_tokens=2048, - # temperature=0.7, - # top_p=0.8, - # top_k=3, -) - -for result in results: - print(f"RESULT: \n{result}\n\n") diff --git a/llmlite/__init__.py b/llmlite/__init__.py deleted file mode 100644 index e205b68..0000000 --- a/llmlite/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -from llmlite.apis.chatllm import ChatLLM -from llmlite.llms.messages import ChatMessage - -__version__ = "0.0.15" - -__all__ = [ - "ChatLLM", - "ChatMessage", -] diff --git a/llmlite/apis/chatllm.py b/llmlite/apis/chatllm.py deleted file mode 100644 index 6af6b2d..0000000 --- a/llmlite/apis/chatllm.py +++ /dev/null @@ -1,94 +0,0 @@ -from typing import List, Optional, Union -import logging - -from llmlite import consts -from llmlite.llms.llm import LLM, get_model_info -from llmlite.llms.messages import ChatMessage - - -class ChatLLM: - """ - How To Use: - chat = ChatLLM( - model_name_or_path="meta-llama/Llama-2-7b-chat-hf", # required - task="text-generation", # optional - ) - - result = chat.completion( - messages=[ - ChatMessage(role="system", content="You're a honest assistant."), - ChatMessage(role="user", content="There's a llama in my garden, what should I do?"), - ] - ) - - """ - - def __init__( - self, - model_name_or_path: str, - backend: str = None, - **kwargs, - ): - """ - Args: - model_name_or_path (str): The model name or the model path. - task (str): The task defining which pipeline will be returned, default to `text-generation`. - """ - - if model_name_or_path == "": - raise Exception("model_name_or_path must exist") - - if backend not in [ - None, - consts.BACKEND_ENDPOINT, - consts.BACKEND_HF, - consts.BACKEND_VLLM, - ]: - raise Exception("backend not support") - - self._llm = LLM.from_pretrained( - model_name_or_path=model_name_or_path, - backend=backend, - **kwargs, - ) - - self.logger = logging.getLogger("llmlite.ChatLLM") - - def completion( - self, - messages: Union[List[ChatMessage], List[List[ChatMessage]]], - **kwargs, - ) -> Optional[Union[str, List[str]]]: - """ - Args: - messages: A list of conversations looks like below: - [ - ChatMessage(role="system", content="You are a helpful assistant."), - ChatMessage(role="user", content="Who won the world series in 2020?"), - ChatMessage(role="assistant", content="The Los Angeles Dodgers won the World Series in 2020."), - ] - - We have three types of `roles` here: - system: a system level instruction to guide your model's behavior throughout the conversation. - user: a series of questions you ask the model. - assistant: an answer replying to the user questions. - The `content` contains the text of the message from the role. - - Note: The indexes of the messages are following the sequence of conversations. - - Returns: - Sentences of string type or a list of string type sentences, this will only happen with vLLM backend. - """ - - self._llm.validation(messages=messages) - - res = self._llm.completion(messages=messages, **kwargs) - self.logger.debug(f"Result: {res}") - return res - - @classmethod - def prompt( - cls, model_name_or_path: str, messages: List[ChatMessage], **kwargs - ) -> Optional[str]: - model_class, _ = get_model_info(model_name_or_path) - return model_class.prompt(model_name_or_path, messages, **kwargs) diff --git a/llmlite/backends/__init__.py b/llmlite/backends/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/llmlite/backends/backend.py b/llmlite/backends/backend.py deleted file mode 100644 index 1774283..0000000 --- a/llmlite/backends/backend.py +++ /dev/null @@ -1,15 +0,0 @@ -from abc import ABC, abstractmethod -from typing import Optional - - -class Backend(ABC): - def __init__( - self, - model_name_or_path: str, - **kwargs, - ) -> None: - pass - - @abstractmethod - def completion(self, content: str, **kwargs) -> Optional[str]: - pass diff --git a/llmlite/backends/hf_backend.py b/llmlite/backends/hf_backend.py deleted file mode 100644 index 0c86bb5..0000000 --- a/llmlite/backends/hf_backend.py +++ /dev/null @@ -1,48 +0,0 @@ -from typing import Optional - -import transformers # type: ignore -from transformers import AutoTokenizer, AutoConfig - -from llmlite.backends.backend import Backend - -# from llmlite.utils import util - - -class HFBackend(Backend): - def __init__( - self, - model_name_or_path: str, - architecture: str, - **kwargs, - ): - task = kwargs.pop("task", None) - trust_remote_code = kwargs.pop("trust_remote_code", True) - device_map = kwargs.pop("device_map", "auto") - - # model_class = util.get_class("transformers", architecture) - - tokenizer = AutoTokenizer.from_pretrained( - model_name_or_path, - trust_remote_code=trust_remote_code, - ) - # TODO: remove this if model path is already supported - # model = model_class.from_pretrained(model_name_or_path).half().cuda().eval() - config = AutoConfig.from_pretrained(model_name_or_path) - - self._pipeline = transformers.pipeline( - task=task, - model=model_name_or_path, - tokenizer=tokenizer, - config=config, - trust_remote_code=trust_remote_code, - device_map=device_map, - **kwargs, - ) - - def completion(self, content: str, **kwargs) -> Optional[str]: - sequences = self._pipeline( - content, - return_full_text=False, - **kwargs, - ) - return sequences[0]["generated_text"] diff --git a/llmlite/backends/vllm_backend.py b/llmlite/backends/vllm_backend.py deleted file mode 100644 index b2fc4f5..0000000 --- a/llmlite/backends/vllm_backend.py +++ /dev/null @@ -1,30 +0,0 @@ -from typing import Optional, List - -from vllm import LLM as vllm -from vllm import SamplingParams - -from llmlite.backends.backend import Backend - - -class VLLMBackend(Backend): - def __init__( - self, - model_name_or_path: str, - **kwargs, - ): - trust_remote_code = kwargs.pop("trust_remote_code", True) - # 'task' is an unexpected keyword argument to vLLM. - _ = kwargs.pop("task", None) - - self._model = vllm( - model=model_name_or_path, - trust_remote_code=trust_remote_code, - **kwargs, - ) - - def completion(self, contents: List[str], **kwargs) -> Optional[List[str]]: - sequences = self._model.generate(contents, SamplingParams(**kwargs)) - response = [] - for seq in sequences: - response.append(seq.outputs[0].text) - return response diff --git a/llmlite/consts.py b/llmlite/consts.py deleted file mode 100644 index 064aa9c..0000000 --- a/llmlite/consts.py +++ /dev/null @@ -1,15 +0,0 @@ -# Backends -BACKEND_HF = "hf" -BACKEND_VLLM = "vllm" -BACKEND_ENDPOINT = "ep" # endpoint - -# Model architecture -MODEL_TYPE_BAICHUAN = "baichuan" -MODEL_TYPE_CHATGLM = "chatglm" -MODEL_TYPE_GPT = "chatgpt" -MODEL_TYPE_LLAMA = "llama" - -# Prompt type -SYSTEM_PROMPT = "system" -USER_PROMPT = "user" -ASSISTANT_PROMPT = "assistant" diff --git a/llmlite/llms/__init__.py b/llmlite/llms/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/llmlite/llms/baichuan.py b/llmlite/llms/baichuan.py deleted file mode 100644 index 2c5af91..0000000 --- a/llmlite/llms/baichuan.py +++ /dev/null @@ -1,107 +0,0 @@ -from typing import List, Optional, Dict, Any -import logging - -import torch -from transformers import AutoTokenizer, GenerationConfig # type: ignore - -from llmlite.llms.model import Model -from llmlite import consts -from llmlite.llms.messages import ChatMessage -from llmlite.utils import util - -user_token = "" -assistant_token = "" - - -class Baichuan(Model): - def __init__( - self, - model_name_or_path: str, - backend: str, - **kwargs: Dict[str, Any], - ) -> None: - super().__init__(model_name_or_path, backend, **kwargs) - - __config__ = { - "support_system_prompt": True, - "backends": [consts.BACKEND_HF], - "default_backend": consts.BACKEND_HF, - "architecture": "AutoModelForCausalLM", - } - - @classmethod - def load_with_hf( - cls, - model_name_or_path: str, - **kwargs: Dict[str, Any], - ): - trust_remote_code = kwargs.pop("trust_remote_code", True) - use_fast = kwargs.pop("use_fast", False) - device_map = kwargs.pop("device_map", "auto") - torch_type = kwargs.pop("torch_type", torch.bfloat16) - - arch = cls.get_config("architecture") - if arch is None: - raise Exception("architecture not exists") - - model_class = util.get_class("transformers", arch) - - tokenizer = AutoTokenizer.from_pretrained( - model_name_or_path, - trust_remote_code=trust_remote_code, - use_fast=use_fast, - ) - model = model_class.from_pretrained( - model_name_or_path, - trust_remote_code=trust_remote_code, - torch_dtype=torch_type, - device_map=device_map, - **kwargs, - ) - model.generation_config = GenerationConfig.from_pretrained(model_name_or_path) - - config_args = { - "model": model, - "tokenizer": tokenizer, - "logger": logging.getLogger("llmlite.Baichuan"), - } - return cls(model_name_or_path, consts.BACKEND_HF, **config_args) - - def completion( - self, - messages: List[ChatMessage], - **kwargs, - ) -> Optional[str]: - inputs = [] - for msg in messages: - inputs.append({"role": msg.role, "content": msg.content}) - response = self._model.chat(self._tokenizer, inputs) - return response - - @classmethod - def prompt( - cls, - model_name_or_path: str, - messages: List[ChatMessage], - **kwargs, - ) -> Optional[str]: - super().prompt(model_name_or_path, messages, **kwargs) - - # This is inspired by https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat/blob/main/generation_utils.py - system_prompt = None - - if len(messages) > 0 and messages[0].role == consts.SYSTEM_PROMPT: - system_prompt = messages[0].content + "\n" - messages = messages[1 : len(messages)] - - prompts = "" - for msg in messages: - if msg.role == consts.USER_PROMPT: - prompts += user_token + msg.content - if msg.role == consts.ASSISTANT_PROMPT: - prompts += assistant_token + msg.content - - if system_prompt is None: - return prompts + assistant_token - else: - return system_prompt + prompts + assistant_token diff --git a/llmlite/llms/chatglm.py b/llmlite/llms/chatglm.py deleted file mode 100644 index 94fe7fa..0000000 --- a/llmlite/llms/chatglm.py +++ /dev/null @@ -1,157 +0,0 @@ -from typing import List, Optional, Tuple, Dict, Any, Union -import logging - -from transformers import AutoTokenizer # type: ignore - -from llmlite.llms.model import Model -from llmlite.utils.util import get_class -from llmlite.llms.messages import ChatMessage -from llmlite import consts -from llmlite.utils import util - -chatglm2 = 2 -chatglm3 = 3 - - -class ChatGLM(Model): - """ - ChatGLM is mainly used for chinese questions and answers. Currently don't support system prompt yet. - """ - - def __init__( - self, - model_name_or_path: str, - backend: str, - **kwargs: Dict[str, Any], - ) -> None: - super().__init__(model_name_or_path, backend, **kwargs) - - __config__ = { - "support_system_prompt": False, - "backends": [consts.BACKEND_HF, consts.BACKEND_VLLM], - "default_backend": consts.BACKEND_HF, - "architecture": "AutoModel", - } - - @classmethod - def load_with_hf( - cls, - model_name_or_path: str, - **kwargs: Dict[str, Any], - ): - trust_remote_code = kwargs.pop("trust_remote_code", True) - # Task is not required by ChatGLM, or we'll report error. - _ = kwargs.pop("task", None) - - arch = cls.get_config("architecture") - if arch is None: - raise Exception("architecture not exists") - - model_class = get_class("transformers", arch) - - tokenizer = AutoTokenizer.from_pretrained( - model_name_or_path, - trust_remote_code=trust_remote_code, - ) - model = ( - model_class.from_pretrained( - model_name_or_path, - trust_remote_code=trust_remote_code, - **kwargs, - ) - .half() - .cuda() - .eval() - ) - - config_args = { - "tokenizer": tokenizer, - "model": model, - "logger": logging.getLogger("llmlite.ChatGLM"), - } - return cls(model_name_or_path, consts.BACKEND_HF, **config_args) - - def completion( - self, - messages: List[ChatMessage], - **kwargs, - ) -> Optional[Union[str, List[str]]]: - """ - This is how ChatGLM chat() looks like: - - def chat( - self, - tokenizer, - query: str, - history: List[Tuple[str, str]] = None, - max_length: int = 8192, - num_beams=1, - do_sample=True, - top_p=0.8, - temperature=0.8, - logits_processor=None, - **kwargs, - ) - """ - - if self._version == chatglm2 and self._backend == consts.BACKEND_HF: - query, history = build_history(messages) - response, _ = self._model.chat( - self._tokenizer, - query, - history=history, - ) - return response - - # TODO: support vllm - if self._version == chatglm2 and self._backend == consts.BACKEND_VLLM: - prompt = [] - for message in messages: - prompt.append(self.prompt(self._model_name_or_path, message)) - response = self._backend_runtime.completion(prompt) - return response - - # TODO: support chatglm3 - if self._version == chatglm3 and self._backend == consts.BACKEND_HF: - pass - if self._version == chatglm3 and self._backend == consts.BACKEND_VLLM: - pass - - @classmethod - def prompt( - cls, - model_name_or_path: str, - messages: List[ChatMessage], - **kwargs, - ) -> Optional[str]: - super().prompt(model_name_or_path, messages, **kwargs) - - _, version = util.parse_model_name(model_name_or_path) - - # TODO: how vllm support conversion chatglm. - if version == chatglm2: - prompt = "" - query, history = build_history(messages) - - # This is inspired by https://huggingface.co/THUDM/chatglm2-6b/blob/main/tokenization_chatglm.py#build_prompt() - for i, (old_query, response) in enumerate(history): - prompt += "[Round {}]\n\n问：{}\n\n答：{}\n\n".format( - i + 1, old_query, response - ) - prompt += "[Round {}]\n\n问：{}\n\n答：".format(len(history) + 1, query) - return prompt - - # TODO: support chatglm3 - if version == chatglm3: - return None - - -def build_history(messages: List[ChatMessage]) -> Tuple[str, List[Tuple[str, str]]]: - query = messages[-1].content - history = [] - - pair_number = int(len(messages) / 2) - for i in range(0, pair_number): - history.append((messages[2 * i].content, messages[2 * i + 1].content)) - - return query, history diff --git a/llmlite/llms/chatgpt.py b/llmlite/llms/chatgpt.py deleted file mode 100644 index 5ea4180..0000000 --- a/llmlite/llms/chatgpt.py +++ /dev/null @@ -1,49 +0,0 @@ -import os -from typing import List, Optional, Dict, Any -import logging - -import openai # type: ignore - -from llmlite.llms.messages import ChatMessage -from llmlite.llms.model import Model -from llmlite import consts - - -class ChatGPT(Model): - def __init__(self, model_name_or_path: str, **kwargs: Dict[str, Any]) -> None: - super().__init__(model_name_or_path, consts.BACKEND_ENDPOINT, **kwargs) - - self._logger = logging.getLogger("llmlite.ChatGPTChat") - - self._api_key = os.getenv("OPENAI_API_KEY") - self._endpoint = os.getenv("OPENAI_ENDPOINT") - - if self._api_key is None or self._api_key == "": - raise Exception("no OPENAI_API_KEY provided") - - openai.api_key = self._api_key - if self._endpoint is not None: - openai.api_base = self._endpoint - - __config__ = { - "support_system_prompt": True, - "backends": [consts.BACKEND_ENDPOINT], - "default_backend": consts.BACKEND_ENDPOINT, - } - - def completion( - self, - messages: List[ChatMessage], - **kwargs, - ) -> Optional[str]: - inputs = [] - for message in messages: - inputs.append({"role": message.role, "content": message.content}) - - completion = openai.ChatCompletion.create( - model=self._model_name_or_path, - messages=inputs, - **kwargs, - ) - - return completion.choices[0].message.content diff --git a/llmlite/llms/llama.py b/llmlite/llms/llama.py deleted file mode 100644 index 4b2433d..0000000 --- a/llmlite/llms/llama.py +++ /dev/null @@ -1,131 +0,0 @@ -import logging -from typing import List, Optional, Dict, Any - -from llmlite import consts -from llmlite.llms.messages import ChatMessage -from llmlite.llms.model import Model - - -class Llama(Model): - """ - Llama2 required prompt template: https://huggingface.co/blog/llama2#how-to-prompt-llama-2 - The prompt template for the first turn looks like: - - [INST] <> - {{ system_prompt }} - <> - - {{ user_message }} [/INST] - - As the conversation progresses, all the interactions will be appended to the previous prompt like: - - [INST] <> - {{ system_prompt }} - <> - - {{ user_msg_1 }} [/INST] {{ model_answer_1 }} [INST] {{ user_msg_2 }} [/INST] - """ - - def __init__( - self, - model_name_or_path: str, - backend: str, - **kwargs, - ) -> None: - super().__init__(model_name_or_path, backend, **kwargs) - - __config__ = { - "support_system_prompt": True, - "backends": [consts.BACKEND_HF, consts.BACKEND_VLLM], - "default_backend": consts.BACKEND_HF, - "architecture": "LlamaForCausalLM", - } - - @classmethod - def load_with_hf( - cls, - model_name_or_path: str, - **kwargs: Dict[str, Any], - ): - # Llama requires task, default to "text-generation". - if kwargs.get("task", None) is None: - kwargs.update({"task": "text-generation"}) - return super().load_with_hf(model_name_or_path, **kwargs) - - @classmethod - def prompt( - cls, - model_name_or_path: str, - messages: List[ChatMessage], - **kwargs, - ) -> Optional[str]: - has_system_prompt = False - prompt = None - - for message in messages: - role = message.role - content = message.content - - if role == consts.SYSTEM_PROMPT: - # We only can accept one system prompt. - if has_system_prompt: - continue - - prompt = format_llama_prompt( - role=consts.SYSTEM_PROMPT, content=content, history=None - ) - has_system_prompt = True - - elif role == consts.USER_PROMPT: - prompt = format_llama_prompt( - role=consts.USER_PROMPT, content=content, history=prompt - ) - - elif role == consts.ASSISTANT_PROMPT: - prompt = format_llama_prompt( - role=consts.ASSISTANT_PROMPT, content=content, history=prompt - ) - - else: - logger = logging.getLogger("llmlite.LlamaChat") - logger.error("unavailable instruction role: %s", role) - - return prompt - - -def format_llama_prompt( - role: str, - content: str, - history: str | None, -) -> str: - if content is None: - return "" - - result = "" - - # SYSTEM_PROMPT will only be added once in the very beginning of the conversation. - if role == consts.SYSTEM_PROMPT: - result = "[INST] <>\n" - result += content + "\n" - result += "<>\n\n" - return result - - if role == consts.USER_PROMPT: - # No system prompt - if history is None: - return "[INST] " + content + " [/INST] " - else: - # end with system prompt - if history.endswith("<>\n\n"): - return history + content + " [/INST] " - else: - # end with assistant prompt - return history + "[INST] " + content + " [/INST] " - - if role == consts.ASSISTANT_PROMPT: - # history or content should not be nil here. - if history is None or content is None: - return result - return history + content + " " - - return result diff --git a/llmlite/llms/llm.py b/llmlite/llms/llm.py deleted file mode 100644 index 77aa1df..0000000 --- a/llmlite/llms/llm.py +++ /dev/null @@ -1,78 +0,0 @@ -from typing import Optional -from llmlite import consts -from llmlite.llms.baichuan import Baichuan -from llmlite.llms.chatglm import ChatGLM -from llmlite.llms.llama import Llama -from llmlite.llms.chatgpt import ChatGPT -from llmlite.utils import util - - -# TODO: loading the configs automatically or construct a register function. -class LLMStore: - LLMs = { - consts.MODEL_TYPE_LLAMA: Llama, - consts.MODEL_TYPE_GPT: ChatGPT, - consts.MODEL_TYPE_CHATGLM: ChatGLM, - consts.MODEL_TYPE_BAICHUAN: Baichuan, - } - - -class LLM: - @classmethod - def from_pretrained( - cls, - model_name_or_path: str, - backend: Optional[str], - **kwargs, - ): - """ - from_pretrained helps to load the model in advance, we support 3 backends right now: - - endpoint: with this backend, you have to implement the logics additionally, what you - required to do is to implement the completion() function. - - hf: basically, no longer need to implement the model loading logic if the model is - supported by huggingface pipeline, what you required to do is set the model configs only. - Or you have to implement the load_with_hf() and completion() concurrently. - - vllm: no longer need to implement the logic since vllm does everything for you if the - model is supported by vllm already. - """ - - model_class, _ = get_model_info(model_name_or_path) - backend = get_backend(model_name_or_path, backend) - - # We can call the API directly, no need to load the model. - if backend == consts.BACKEND_ENDPOINT: - return model_class(model_name_or_path, **kwargs) - - if backend == consts.BACKEND_HF: - return model_class.load_with_hf(model_name_or_path, **kwargs) - - if backend == consts.BACKEND_VLLM: - return model_class.load_with_vllm(model_name_or_path, **kwargs) - - raise Exception("unsupported backend: %s", backend) - - -# TODO: add tests -def get_model_info(model_name_or_path: str): - model_type, version = util.parse_model_name(model_name_or_path) - - model_class = LLMStore.LLMs.get(model_type, None) - assert model_class is not None, "llm not exists" - - return model_class, version - - -# TODO: add tests -def get_backend(model_name_or_path: str, backend: Optional[str]) -> str: - model_class, _ = get_model_info(model_name_or_path) - - if backend is None: - backend = model_class.get_config("default_backend") - assert backend is not None, "default backend not configured" - - support_backends = model_class.get_config("backends") # type: ignore - assert support_backends is not None and backend in support_backends, ( - "only supported backends: " + support_backends - ) - - return backend diff --git a/llmlite/llms/messages.py b/llmlite/llms/messages.py deleted file mode 100644 index d92d30a..0000000 --- a/llmlite/llms/messages.py +++ /dev/null @@ -1,8 +0,0 @@ -from typing import Literal - -from pydantic import BaseModel - - -class ChatMessage(BaseModel): - role: Literal["user", "assistant", "system"] - content: str diff --git a/llmlite/llms/model.py b/llmlite/llms/model.py deleted file mode 100644 index 74d3bd2..0000000 --- a/llmlite/llms/model.py +++ /dev/null @@ -1,145 +0,0 @@ -from typing import Optional, List, Dict, Any, Union - -from llmlite.llms.messages import ChatMessage -from llmlite.backends.hf_backend import HFBackend -from llmlite.backends.vllm_backend import VLLMBackend -from llmlite import consts -from llmlite.utils import util - - -class Model: - def __init__( - self, - model_name_or_path: str, - backend: str, - **kwargs: Dict[str, Any], - ) -> None: - self._model_name_or_path = model_name_or_path - self._backend = backend - _, self._version = util.parse_model_name(model_name_or_path) - - updates = {"_" + k: v for k, v in kwargs.items()} - self.__dict__.update(updates) - - # Each model should have its own configuration. - __config__ = {} - - @property - def backend(self) -> str: - return self._backend - - @classmethod - def get_config(cls, key: str) -> Any: - return cls.__config__.get(key) - - # You should implement this if the model has a different architecture or has not supported - # by huggingface pipeline yet. Also, you should implement the completion() the same time. - @classmethod - def load_with_hf( - cls, - model_name_or_path: str, - **kwargs: Dict[str, Any], - ): - arch = cls.get_config("architecture") - if arch is None: - raise Exception("architecture not exists") - - backend_runtime = HFBackend( - model_name_or_path, - arch, - **kwargs, - ) - - return cls( - model_name_or_path, - backend=consts.BACKEND_HF, - backend_runtime=backend_runtime, - ) - - # You should implement this if the model has a different architecture or has not supported - # by huggingface pipeline yet. Also, you should implement the completion() the same time. - @classmethod - def load_with_vllm( - cls, - model_name_or_path: str, - **kwargs: Dict[str, Any], - ): - arch = cls.get_config("architecture") - if arch is None: - raise Exception("architecture not exists") - - backend_runtime = VLLMBackend( - model_name_or_path, - **kwargs, - ) - - return cls( - model_name_or_path, - backend=consts.BACKEND_VLLM, - backend_runtime=backend_runtime, - ) - - def completion( - self, messages: Union[List[ChatMessage], List[List[ChatMessage]]], **kwargs - ) -> Optional[Union[str, List[str]]]: - if self._backend == consts.BACKEND_HF: - prompt = self.prompt(self._model_name_or_path, messages, **kwargs) - - generated_text = self._backend_runtime.completion(prompt, **kwargs) - return generated_text - - if self._backend == consts.BACKEND_VLLM: - prompts = [] - for msg in messages: - pt = self.prompt(self._model_name_or_path, msg, **kwargs) - prompts.append(pt) - - generated_text = self._backend_runtime.completion(prompts, **kwargs) - return generated_text - - def validation( - self, - messages: Union[List[ChatMessage], List[List[ChatMessage]]], - ): - if self._backend == consts.BACKEND_VLLM: - assert all( - isinstance(item, list) for item in messages - ), "vLLM only supports batch inference" - else: - assert all( - isinstance(item, ChatMessage) for item in messages - ), "batch inference only supports with vLLM backend" - - assert len(messages) > 0, "messages should not be empty" - - def validate(messages: List[ChatMessage]): - assert len(messages) > 0, "messages should not be empty" - assert ( - messages[-1].role == consts.USER_PROMPT - ), "last message should be user prompt" - - if self.get_config("support_system_prompt"): - for i, msg in enumerate(messages): - if msg.role == consts.SYSTEM_PROMPT: - assert i == 0, "system prompt should be in the first role" - else: - for msg in messages: - assert ( - msg.role != consts.SYSTEM_PROMPT - ), "system prompt not supported" - - if all(isinstance(item, list) for item in messages): - [validate(messages=item) for item in messages] - else: - validate(messages=messages) - - @classmethod - def prompt( - cls, model_name_or_path: str, messages: List[ChatMessage], **kwargs - ) -> Optional[str]: - """ - You should implement the prompt additionally because different model - has different prompt format. - """ - - pass diff --git a/llmlite/utils/__init__.py b/llmlite/utils/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/llmlite/utils/log.py b/llmlite/utils/log.py deleted file mode 100644 index 6cea829..0000000 --- a/llmlite/utils/log.py +++ /dev/null @@ -1,11 +0,0 @@ -import logging -import os - - -def logging_level(): - level = os.getenv("LOG_LEVEL") - return logging.INFO if level is None else level - - -logger = logging.getLogger("llmlite") -logger.setLevel(logging_level()) diff --git a/llmlite/utils/util.py b/llmlite/utils/util.py deleted file mode 100644 index 9b48602..0000000 --- a/llmlite/utils/util.py +++ /dev/null @@ -1,44 +0,0 @@ -from typing import Tuple -import importlib - -from llmlite import consts - - -def get_class(module_name, class_name): - module = importlib.import_module(module_name) - return getattr(module, class_name) - - -# Return the model_type and the version together. -def parse_model_name(model_name: str) -> Tuple[str, float]: - model_name = model_name.lower() - - if "llama2" in model_name or "llama-2" in model_name or "codellama" in model_name: - return consts.MODEL_TYPE_LLAMA, 2 - - if "chatglm2" in model_name: - return consts.MODEL_TYPE_CHATGLM, 2 - - if "chatglm3" in model_name: - return consts.MODEL_TYPE_CHATGLM, 3 - - if "baichuan2" in model_name: - return consts.MODEL_TYPE_BAICHUAN, 2 - - if "gpt-3.5" in model_name: - return consts.MODEL_TYPE_GPT, 3.5 - - if "gpt-4" in model_name: - return consts.MODEL_TYPE_GPT, 4 - - raise UnavailableModelException( - "model unavailable, supporting model family: `llama`,, `chatglm`, `chatgpt`, `baichuan`" - ) - - -class UnavailableModelException(Exception): - def __init__(self, message): - self.message = message - 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"696912df08fa462fba791a14f6f438aee8e0dbe8726aaa6a394261100c5382a1" diff --git a/pyproject.toml b/pyproject.toml index 0099bb7..9862913 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,21 +1,13 @@ [tool.poetry] -name = "llmlite" -version = "0.0.15" -description = "A library helps to chat with all kinds of LLMs consistently." +name = "AMRS" +version = "0.0.0" +description = "The adaptive model routing system for exploration and exploitation." authors = ["InftyAI"] license = "MIT License" readme = "README.md" [tool.poetry.dependencies] python = "^3.10" -accelerate = "0.22.0" -transformers = "4.34.0" -sentencepiece = "0.1.99" -pydantic = "<2" -openai = "^0.28.0" -vllm = "0.2.3" -tokenizers = "0.14" -torch = "^2.1.1" [tool.poetry.group.dev.dependencies] mypy = "^1.5.1" @@ -37,5 +29,4 @@ filterwarnings = [ [tool.mypy] exclude = [ 'tmp/', - 'example/', ] diff --git a/requirements-dev.txt b/requirements-dev.txt deleted file mode 100644 index e87f09f..0000000 --- a/requirements-dev.txt +++ /dev/null @@ -1,91 +0,0 @@ -accelerate==0.22.0 ; python_version >= "3.10" and python_version < "4.0" -aiohttp==3.8.6 ; python_version >= "3.10" and python_version < "4.0" -aioprometheus[starlette]==23.3.0 ; python_version >= "3.10" and python_version < "4.0" -aiosignal==1.3.1 ; python_version >= "3.10" and python_version < "4.0" -anyio==3.7.1 ; python_version >= "3.10" and python_version < "4.0" -async-timeout==4.0.3 ; python_version >= "3.10" and python_version < "4.0" -attrs==23.1.0 ; python_version >= "3.10" and python_version < "4.0" -black==23.10.1 ; python_version >= "3.10" and python_version < "4.0" -certifi==2023.7.22 ; python_version >= "3.10" and python_version < "4.0" -charset-normalizer==3.3.1 ; python_version >= "3.10" and python_version < "4.0" -click==8.1.7 ; python_version >= "3.10" and python_version < "4.0" -colorama==0.4.6 ; python_version >= "3.10" and python_version < "4.0" and (sys_platform == "win32" or platform_system == "Windows") -einops==0.7.0 ; python_version >= "3.10" and python_version < "4.0" -exceptiongroup==1.1.3 ; python_version >= "3.10" and python_version < "3.11" -fastapi==0.105.0 ; python_version >= "3.10" and python_version < "4.0" -filelock==3.12.4 ; python_version >= "3.10" and python_version < "4.0" -frozenlist==1.4.0 ; python_version >= "3.10" and python_version < "4.0" -fsspec==2023.10.0 ; python_version >= "3.10" and python_version < "4.0" -h11==0.14.0 ; python_version >= "3.10" and python_version < "4.0" -httptools==0.6.1 ; python_version >= "3.10" and python_version < "4.0" -huggingface-hub==0.16.4 ; python_version >= "3.10" and python_version < "4.0" -idna==3.4 ; python_version >= "3.10" and python_version < "4.0" -iniconfig==2.0.0 ; python_version >= "3.10" and python_version < "4.0" -jinja2==3.1.2 ; python_version >= "3.10" and python_version < "4.0" -jsonschema-specifications==2023.11.2 ; python_version >= "3.10" and python_version < "4.0" -jsonschema==4.20.0 ; python_version >= "3.10" and python_version < "4.0" -markupsafe==2.1.3 ; python_version >= "3.10" and python_version < "4.0" -mpmath==1.3.0 ; python_version >= "3.10" and python_version < "4.0" -msgpack==1.0.7 ; python_version >= "3.10" and python_version < "4.0" -multidict==6.0.4 ; python_version >= "3.10" and python_version < "4.0" -mypy-extensions==1.0.0 ; python_version >= "3.10" and python_version < "4.0" -mypy==1.6.1 ; python_version >= "3.10" and python_version < "4.0" -networkx==3.2 ; python_version >= "3.10" and python_version < "4.0" -ninja==1.11.1.1 ; python_version >= "3.10" and python_version < "4.0" -numpy==1.25.2 ; python_version >= "3.10" and python_version < "4.0" -nvidia-cublas-cu12==12.1.3.1 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cuda-cupti-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cuda-nvrtc-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cuda-runtime-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cudnn-cu12==8.9.2.26 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cufft-cu12==11.0.2.54 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-curand-cu12==10.3.2.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cusolver-cu12==11.4.5.107 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cusparse-cu12==12.1.0.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-nccl-cu12==2.18.1 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-nvjitlink-cu12==12.3.101 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-nvtx-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -openai==0.28.1 ; python_version >= "3.10" and python_version < "4.0" -orjson==3.9.10 ; python_version >= "3.10" and python_version < "4.0" -packaging==23.2 ; python_version >= "3.10" and python_version < "4.0" -pandas==2.1.4 ; python_version >= "3.10" and python_version < "4.0" -pathspec==0.11.2 ; python_version >= "3.10" and python_version < "4.0" -platformdirs==3.11.0 ; python_version >= "3.10" and python_version < "4.0" -pluggy==1.3.0 ; python_version >= "3.10" and python_version < "4.0" -protobuf==4.25.1 ; python_version >= "3.10" and python_version < "4.0" -psutil==5.9.6 ; python_version >= "3.10" and python_version < "4.0" -pyarrow==14.0.1 ; python_version >= "3.10" and python_version < "4.0" -pydantic==1.10.13 ; python_version >= "3.10" and python_version < "4.0" -pytest==7.4.3 ; python_version >= "3.10" and python_version < "4.0" -python-dateutil==2.8.2 ; python_version >= "3.10" and python_version < "4.0" -python-dotenv==1.0.0 ; python_version >= "3.10" and python_version < "4.0" -pytz==2023.3.post1 ; python_version >= "3.10" and python_version < "4.0" -pyyaml==6.0.1 ; python_version >= "3.10" and python_version < "4.0" -quantile-python==1.1 ; python_version >= "3.10" and python_version < "4.0" -ray==2.8.1 ; python_version >= "3.10" and python_version < "4.0" -referencing==0.32.0 ; python_version >= "3.10" and python_version < "4.0" -regex==2023.10.3 ; python_version >= "3.10" and python_version < "4.0" -requests==2.31.0 ; python_version >= "3.10" and python_version < "4.0" -rpds-py==0.13.2 ; python_version >= "3.10" and python_version < "4.0" -safetensors==0.4.0 ; python_version >= "3.10" and python_version < "4.0" -sentencepiece==0.1.99 ; python_version >= "3.10" and python_version < "4.0" -six==1.16.0 ; python_version >= "3.10" and python_version < "4.0" -sniffio==1.3.0 ; python_version >= "3.10" and python_version < "4.0" -starlette==0.27.0 ; python_version >= "3.10" and python_version < "4.0" -sympy==1.12 ; python_version >= "3.10" and python_version < "4.0" -tokenizers==0.14.0 ; python_version >= "3.10" and python_version < "4.0" -tomli==2.0.1 ; python_version >= "3.10" and python_version < "3.11" -torch==2.1.1 ; python_version >= "3.10" and python_version < "4.0" -tqdm==4.66.1 ; python_version >= "3.10" and python_version < "4.0" -transformers==4.34.0 ; python_version >= "3.10" and python_version < "4.0" -triton==2.1.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -typing-extensions==4.8.0 ; python_version >= "3.10" and python_version < "4.0" -tzdata==2023.3 ; python_version >= "3.10" and python_version < "4.0" -urllib3==2.0.7 ; python_version >= "3.10" and python_version < "4.0" -uvicorn[standard]==0.24.0.post1 ; python_version >= "3.10" and python_version < "4.0" -uvloop==0.19.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_version >= "3.10" and python_version < "4.0" -vllm==0.2.3 ; python_version >= "3.10" and python_version < "4.0" -watchfiles==0.21.0 ; python_version >= "3.10" and python_version < "4.0" -websockets==12.0 ; python_version >= "3.10" and python_version < "4.0" -xformers==0.0.23 ; python_version >= "3.10" and python_version < "4.0" -yarl==1.9.2 ; python_version >= "3.10" and python_version < "4.0" diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 8db9bd9..0000000 --- a/requirements.txt +++ /dev/null @@ -1,82 +0,0 @@ -accelerate==0.22.0 ; python_version >= "3.10" and python_version < "4.0" -aiohttp==3.8.6 ; python_version >= "3.10" and python_version < "4.0" -aioprometheus[starlette]==23.3.0 ; python_version >= "3.10" and python_version < "4.0" -aiosignal==1.3.1 ; python_version >= "3.10" and python_version < "4.0" -anyio==3.7.1 ; python_version >= "3.10" and python_version < "4.0" -async-timeout==4.0.3 ; python_version >= "3.10" and python_version < "4.0" -attrs==23.1.0 ; python_version >= "3.10" and python_version < "4.0" -certifi==2023.7.22 ; python_version >= "3.10" and python_version < "4.0" -charset-normalizer==3.3.1 ; python_version >= "3.10" and python_version < "4.0" -click==8.1.7 ; python_version >= "3.10" and python_version < "4.0" -colorama==0.4.6 ; python_version >= "3.10" and python_version < "4.0" and (platform_system == "Windows" or sys_platform == "win32") -einops==0.7.0 ; python_version >= "3.10" and python_version < "4.0" -exceptiongroup==1.1.3 ; python_version >= "3.10" and python_version < "3.11" -fastapi==0.105.0 ; python_version >= "3.10" and python_version < "4.0" -filelock==3.12.4 ; python_version >= "3.10" and python_version < "4.0" -frozenlist==1.4.0 ; python_version >= "3.10" and python_version < "4.0" -fsspec==2023.10.0 ; python_version >= "3.10" and python_version < "4.0" -h11==0.14.0 ; python_version >= "3.10" and python_version < "4.0" -httptools==0.6.1 ; python_version >= "3.10" and python_version < "4.0" -huggingface-hub==0.16.4 ; python_version >= "3.10" and python_version < "4.0" -idna==3.4 ; python_version >= "3.10" and python_version < "4.0" -jinja2==3.1.2 ; python_version >= "3.10" and python_version < "4.0" -jsonschema-specifications==2023.11.2 ; python_version >= "3.10" and python_version < "4.0" -jsonschema==4.20.0 ; python_version >= "3.10" and python_version < "4.0" -markupsafe==2.1.3 ; python_version >= "3.10" and python_version < "4.0" -mpmath==1.3.0 ; python_version >= "3.10" and python_version < "4.0" -msgpack==1.0.7 ; python_version >= "3.10" and python_version < "4.0" -multidict==6.0.4 ; python_version >= "3.10" and python_version < "4.0" -networkx==3.2 ; python_version >= "3.10" and python_version < "4.0" -ninja==1.11.1.1 ; python_version >= "3.10" and python_version < "4.0" -numpy==1.25.2 ; python_version >= "3.10" and python_version < "4.0" -nvidia-cublas-cu12==12.1.3.1 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cuda-cupti-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cuda-nvrtc-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cuda-runtime-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cudnn-cu12==8.9.2.26 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cufft-cu12==11.0.2.54 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-curand-cu12==10.3.2.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cusolver-cu12==11.4.5.107 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-cusparse-cu12==12.1.0.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-nccl-cu12==2.18.1 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-nvjitlink-cu12==12.3.101 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -nvidia-nvtx-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -openai==0.28.1 ; python_version >= "3.10" and python_version < "4.0" -orjson==3.9.10 ; python_version >= "3.10" and python_version < "4.0" -packaging==23.2 ; python_version >= "3.10" and python_version < "4.0" -pandas==2.1.4 ; python_version >= "3.10" and python_version < "4.0" -protobuf==4.25.1 ; python_version >= "3.10" and python_version < "4.0" -psutil==5.9.6 ; python_version >= "3.10" and python_version < "4.0" -pyarrow==14.0.1 ; python_version >= "3.10" and python_version < "4.0" -pydantic==1.10.13 ; python_version >= "3.10" and python_version < "4.0" -python-dateutil==2.8.2 ; python_version >= "3.10" and python_version < "4.0" -python-dotenv==1.0.0 ; python_version >= "3.10" and python_version < "4.0" -pytz==2023.3.post1 ; python_version >= "3.10" and python_version < "4.0" -pyyaml==6.0.1 ; python_version >= "3.10" and python_version < "4.0" -quantile-python==1.1 ; python_version >= "3.10" and python_version < "4.0" -ray==2.8.1 ; python_version >= "3.10" and python_version < "4.0" -referencing==0.32.0 ; python_version >= "3.10" and python_version < "4.0" -regex==2023.10.3 ; python_version >= "3.10" and python_version < "4.0" -requests==2.31.0 ; python_version >= "3.10" and python_version < "4.0" -rpds-py==0.13.2 ; python_version >= "3.10" and python_version < "4.0" -safetensors==0.4.0 ; python_version >= "3.10" and python_version < "4.0" -sentencepiece==0.1.99 ; python_version >= "3.10" and python_version < "4.0" -six==1.16.0 ; python_version >= "3.10" and python_version < "4.0" -sniffio==1.3.0 ; python_version >= "3.10" and python_version < "4.0" -starlette==0.27.0 ; python_version >= "3.10" and python_version < "4.0" -sympy==1.12 ; python_version >= "3.10" and python_version < "4.0" -tokenizers==0.14.0 ; python_version >= "3.10" and python_version < "4.0" -torch==2.1.1 ; python_version >= "3.10" and python_version < "4.0" -tqdm==4.66.1 ; python_version >= "3.10" and python_version < "4.0" -transformers==4.34.0 ; python_version >= "3.10" and python_version < "4.0" -triton==2.1.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.10" and python_version < "4.0" -typing-extensions==4.8.0 ; python_version >= "3.10" and python_version < "4.0" -tzdata==2023.3 ; python_version >= "3.10" and python_version < "4.0" -urllib3==2.0.7 ; python_version >= "3.10" and python_version < "4.0" -uvicorn[standard]==0.24.0.post1 ; python_version >= "3.10" and python_version < "4.0" -uvloop==0.19.0 ; (sys_platform != "win32" and sys_platform != "cygwin") and platform_python_implementation != "PyPy" and python_version >= "3.10" and python_version < "4.0" -vllm==0.2.3 ; python_version >= "3.10" and python_version < "4.0" -watchfiles==0.21.0 ; python_version >= "3.10" and python_version < "4.0" -websockets==12.0 ; python_version >= "3.10" and python_version < "4.0" -xformers==0.0.23 ; python_version >= "3.10" and python_version < "4.0" -yarl==1.9.2 ; python_version >= "3.10" and python_version < "4.0" diff --git a/start.sh b/start.sh new file mode 100644 index 0000000..34bebb1 --- /dev/null +++ b/start.sh @@ -0,0 +1 @@ +eval $(poetry env activate) diff --git a/tests/integration_tests/test_chat.py b/tests/integration_tests/test_chat.py deleted file mode 100644 index 1061586..0000000 --- a/tests/integration_tests/test_chat.py +++ /dev/null @@ -1,146 +0,0 @@ -from llmlite.apis import ChatLLM, ChatMessage -from tests.integration_tests.util import build_model - - -class TestChat: - def test_llama(self): - test_cases = [ - { - "name": "local model with llama 2", - "model": build_model("meta-llama/Llama-2-7b-chat-hf"), - "task": "text-generation", - "messages": [ - ChatMessage( - role="system", content="You're an agent based on fact." - ), - ChatMessage( - role="user", content="How many people are there in China?" - ), - ], - }, - ] - - for tc in test_cases: - chat = ChatLLM( - model_name_or_path=tc["model"], - task=tc["task"], - temperature=0.2, - max_length=2048, - do_sample=True, - top_p=0.7, - top_k=3, - ) - result = chat.completion(messages=tc["messages"]) - assert len(result) > 0, "got result: " + result - - def test_chatglm(self): - test_cases = [ - { - "name": "local model with chatglm2", - "model": build_model("THUDM/chatglm2-6b"), - "messages": [ - ChatMessage(role="user", content="中国共有多少人口？"), - ], - }, - ] - - for tc in test_cases: - chat = ChatLLM( - model_name_or_path=tc["model"], - temperature=0.2, - max_length=2048, - do_sample=True, - top_p=0.7, - top_k=3, - ) - result = chat.completion(messages=tc["messages"]) - assert len(result) > 0, "got result: " + result - - def test_chatgpt(self): - test_cases = [ - { - "name": "test with gpt-3.5-turbo", - "model": "gpt-3.5-turbo", - "messages": [ - ChatMessage( - role="system", content="You're an agent based on fact." - ), - ChatMessage( - role="user", content="How many people are there in China?" - ), - ], - }, - { - "name": "test with gpt-4", - "model": "gpt-4", - "messages": [ - ChatMessage( - role="system", content="You're an agent based on fact." - ), - ChatMessage( - role="user", content="How many people are there in China?" - ), - ], - }, - ] - - for tc in test_cases: - chat = ChatLLM( - model_name_or_path=tc["model"], - ) - result = chat.completion(messages=tc["messages"]) - assert len(result) > 0, "got result: " + result - - def test_codellama(self): - test_cases = [ - { - "name": "test with only user prompt", - "messages": [ - ChatMessage(role="user", content="def fibonacci("), - ], - }, - { - "name": "test with system prompt exists", - "messages": [ - ChatMessage(role="system", content="Provide answers in golang"), - ChatMessage( - role="user", - content="Write a function that computes the sum of a given list.", - ), - ], - }, - ] - - chat = ChatLLM( - model_name_or_path=build_model("codellama/CodeLlama-13b-instruct-hf"), - task="text-generation", - ) - for tc in test_cases: - result = chat.completion( - messages=tc["messages"], - max_length=2048, - ) - assert len(result) > 0, "got result: " + result - - def test_baichuan(self): - test_cases = [ - { - "name": "enable system prompt", - "messages": [ - ChatMessage(role="system", content="请用诗词形容"), - ChatMessage(role="user", content="中国共有多少人口？"), - ], - }, - ] - - chat = ChatLLM(model_name_or_path=build_model("baichuan-inc/Baichuan2-7B-Chat")) - for tc in test_cases: - result = chat.completion( - messages=tc["messages"], - temperature=0.9, - max_length=2048, - do_sample=True, - top_p=0.7, - top_k=3, - ) - assert len(result) > 0, "got result: " + result diff --git a/tests/integration_tests/test_vllm.py b/tests/integration_tests/test_vllm.py deleted file mode 100644 index 9eaf734..0000000 --- a/tests/integration_tests/test_vllm.py +++ /dev/null @@ -1,66 +0,0 @@ -from llmlite.apis import ChatLLM, ChatMessage -from tests.integration_tests.util import build_model - - -class TestVLLM: - def test_llama_with_vllm(self): - test_cases = [ - { - "name": "local model with llama 2", - "model": build_model("meta-llama/Llama-2-7b-chat-hf"), - "messages": [ - [ - ChatMessage( - role="system", content="You're an agent based on fact." - ), - ChatMessage( - role="user", content="How many people are there in China?" - ), - ], - [ - ChatMessage( - role="user", - content="How many foreigners are there in China?", - ), - ], - ], - }, - ] - - for tc in test_cases: - chat = ChatLLM( - backend="vllm", - model_name_or_path=tc["model"], - ) - result = chat.completion( - messages=tc["messages"], - max_tokens=2048, - ) - assert len(result) == len(tc["messages"]) - - def test_chatglm_with_vllm(self): - test_cases = [ - { - "name": "local model with chatglm2", - "model": build_model("THUDM/chatglm2-6b"), - "messages": [ - [ - ChatMessage(role="user", content="中国共有多少人口？"), - ], - [ - ChatMessage(role="user", content="中国有多少外国人？"), - ], - ], - }, - ] - - for tc in test_cases: - chat = ChatLLM( - backend="vllm", - model_name_or_path=tc["model"], - ) - result = chat.completion( - messages=tc["messages"], - max_tokens=2048, - ) - assert len(result) == len(tc["messages"]) diff --git a/tests/integration_tests/util.py b/tests/integration_tests/util.py deleted file mode 100644 index 7651116..0000000 --- a/tests/integration_tests/util.py +++ /dev/null @@ -1,9 +0,0 @@ -import os - - -# This is help to test more efficiently with models pre-downloaded. -def build_model(model_name: str) -> str: - path = os.getenv("MODEL_PATH") - if path is not None: - return path + "/" + model_name - return model_name diff --git a/tests/unit_tests/llms/__init__.py b/tests/unit_tests/llms/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/tests/unit_tests/llms/test_baichuan.py b/tests/unit_tests/llms/test_baichuan.py deleted file mode 100644 index 1fd201e..0000000 --- a/tests/unit_tests/llms/test_baichuan.py +++ /dev/null @@ -1,55 +0,0 @@ -from llmlite.apis import ChatLLM -from llmlite import consts -from llmlite.llms.messages import ChatMessage - - -class TestBaichuan: - def test_baichuan_prompt(self): - test_cases = [ - { - "name": "prompt with both system_prompt and user_prompt", - "messages": [ - ChatMessage( - role=consts.SYSTEM_PROMPT, - content="You are an intelligent agent", - ), - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ], - "expected": """You are an intelligent agent -Who you are""", - }, - { - "name": "continuous conversation with system_prompt exists", - "messages": [ - ChatMessage( - role=consts.SYSTEM_PROMPT, - content="You are an intelligent agent", - ), - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="I'm an agent"), - ChatMessage(role=consts.USER_PROMPT, content="You're so clever"), - ], - "expected": """You are an intelligent agent -Who you areI'm an agentYou're so clever""", - }, - { - "name": "prompt with only user_prompt", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ], - "expected": """Who you are""", - }, - { - "name": "continuous conversation with no system_prompt", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="I'm an agent"), - ChatMessage(role=consts.USER_PROMPT, content="You're so clever"), - ], - "expected": """Who you areI'm an agentYou're so clever""", - }, - ] - - for tc in test_cases: - got = ChatLLM.prompt("baichuan2", tc["messages"]) - assert got == tc["expected"], "failed in case: " + tc["name"] diff --git a/tests/unit_tests/llms/test_chatglm.py b/tests/unit_tests/llms/test_chatglm.py deleted file mode 100644 index 8771487..0000000 --- a/tests/unit_tests/llms/test_chatglm.py +++ /dev/null @@ -1,66 +0,0 @@ -from llmlite.llms.chatglm import build_history -from llmlite.apis import ChatLLM -from llmlite import consts -from llmlite.llms.messages import ChatMessage - - -class TestChatGLM: - def test_build_history(self): - test_cases = [ - { - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="你是谁"), - ], - "want": ("你是谁", []), - }, - { - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="你是谁"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="我是一个聪明的机器人"), - ChatMessage(role=consts.USER_PROMPT, content="你可以帮我做作业吗"), - ], - "want": ("你可以帮我做作业吗", [("你是谁", "我是一个聪明的机器人")]), - }, - ] - - for tc in test_cases: - got = build_history(tc["messages"]) - assert got == tc["want"] - - def test_prompt(self): - test_cases = [ - { - "name": "prompt with user_prompt", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="你是谁"), - ], - "expected": """[Round 1] - -问：你是谁 - -答：""", - }, - { - "name": "prompt with another round conservation", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="你是谁"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="我是一个智能机器人"), - ChatMessage(role=consts.USER_PROMPT, content="你能给我写作业吗"), - ], - "expected": """[Round 1] - -问：你是谁 - -答：我是一个智能机器人 - -[Round 2] - -问：你能给我写作业吗 - -答：""", - }, - ] - - for tc in test_cases: - got = ChatLLM.prompt("chatglm2", tc["messages"]) - assert got == tc["expected"] diff --git a/tests/unit_tests/llms/test_llama.py b/tests/unit_tests/llms/test_llama.py deleted file mode 100644 index 2ae9a10..0000000 --- a/tests/unit_tests/llms/test_llama.py +++ /dev/null @@ -1,169 +0,0 @@ -from llmlite.llms.llama import format_llama_prompt -from llmlite.apis import ChatLLM -from llmlite import consts -from llmlite.llms.messages import ChatMessage - - -class TestLlama: - def test_format_llama_prompt_with_system_prompt(self): - # format system prompt - system_prompt = "Please complete the code in python" - system_prompt_generated = """[INST] <> -Please complete the code in python -<> - -""" - - content = format_llama_prompt( - role=consts.SYSTEM_PROMPT, content=system_prompt, history=None - ) - assert content == system_prompt_generated - - # format user prompt - user_prompt = "Please output `hello world`" - user_prompt_generated = """[INST] <> -Please complete the code in python -<> - -Please output `hello world` [/INST] """ - - content = format_llama_prompt( - role=consts.USER_PROMPT, content=user_prompt, history=content - ) - assert content == user_prompt_generated - - # format the answer - answer = 'print("hello world")' - user_prompt_generated = """[INST] <> -Please complete the code in python -<> - -Please output `hello world` [/INST] print("hello world") """ - - content = format_llama_prompt( - role=consts.ASSISTANT_PROMPT, - content=answer, - history=content, - ) - assert content == user_prompt_generated - - # format user prompt again - user_prompt = "Thanks for the answer" - user_prompt_generated = """[INST] <> -Please complete the code in python -<> - -Please output `hello world` [/INST] print("hello world") [INST] Thanks for the answer [/INST] """ - content = format_llama_prompt( - role=consts.USER_PROMPT, content=user_prompt, history=content - ) - assert content == user_prompt_generated - - def test_format_llama_prompt_with_no_system_prompt(self): - # format user prompt - user_prompt = "Please output `hello world`" - user_prompt_generated = "[INST] Please output `hello world` [/INST] " - content = format_llama_prompt( - role=consts.USER_PROMPT, content=user_prompt, history=None - ) - assert content == user_prompt_generated - - # format the answer - answer = 'print("hello world")' - user_prompt_generated = ( - '[INST] Please output `hello world` [/INST] print("hello world") ' - ) - content = format_llama_prompt( - role=consts.ASSISTANT_PROMPT, content=answer, history=content - ) - assert content == user_prompt_generated - - # format user prompt again - user_prompt = "Thanks for the answer" - user_prompt_generated = '[INST] Please output `hello world` [/INST] print("hello world") [INST] Thanks for the answer [/INST] ' - content = format_llama_prompt( - role=consts.USER_PROMPT, content=user_prompt, history=content - ) - assert content == user_prompt_generated - - def test_prompt(self): - test_cases = [ - { - "name": "prompt with both system_prompt and user_prompt", - "messages": [ - ChatMessage( - role=consts.SYSTEM_PROMPT, - content="You are an intelligent agent", - ), - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ], - "expected": """[INST] <> -You are an intelligent agent -<> - -Who you are [/INST] """, - }, - { - "name": "prompt with both system_prompt user_prompt and assistant_prompt", - "messages": [ - ChatMessage( - role=consts.SYSTEM_PROMPT, - content="You are an intelligent agent", - ), - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="I'm an agent"), - ], - "expected": """[INST] <> -You are an intelligent agent -<> - -Who you are [/INST] I'm an agent """, - }, - { - "name": "continuous conversation with system_prompt exists", - "messages": [ - ChatMessage( - role=consts.SYSTEM_PROMPT, - content="You are an intelligent agent", - ), - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="I'm an agent"), - ChatMessage(role=consts.USER_PROMPT, content="You're so clever"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="Thanks"), - ], - "expected": """[INST] <> -You are an intelligent agent -<> - -Who you are [/INST] I'm an agent [INST] You're so clever [/INST] Thanks """, - }, - { - "name": "prompt with only user_prompt", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ], - "expected": """[INST] Who you are [/INST] """, - }, - { - "name": "prompt with user_prompt and assistant_prompt", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="I'm an agent"), - ], - "expected": """[INST] Who you are [/INST] I'm an agent """, - }, - { - "name": "continuous conversation with no system_prompt", - "messages": [ - ChatMessage(role=consts.USER_PROMPT, content="Who you are"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="I'm an agent"), - ChatMessage(role=consts.USER_PROMPT, content="You're so clever"), - ChatMessage(role=consts.ASSISTANT_PROMPT, content="Thanks"), - ], - "expected": """[INST] Who you are [/INST] I'm an agent [INST] You're so clever [/INST] Thanks """, - }, - ] - - for tc in test_cases: - got = ChatLLM.prompt("llama-2", tc["messages"]) - assert got == tc["expected"] diff --git a/tests/unit_tests/llms/test_model.py b/tests/unit_tests/llms/test_model.py deleted file mode 100644 index 43f2116..0000000 --- a/tests/unit_tests/llms/test_model.py +++ /dev/null @@ -1,136 +0,0 @@ -import pytest - -from llmlite.llms.messages import ChatMessage -from llmlite.llms.model import Model -from llmlite import consts - - -class TestModel: - def test_validation(self): - test_cases = [ - { - "name": "validation passed", - "messages": [ - ChatMessage(role="system", content="You are a intelligent agent"), - ChatMessage(role="user", content="Who you are"), - ], - "support_system_prompt": True, - "succeed": True, - }, - { - "name": "messages should not be empty", - "messages": [], - "support_system_prompt": True, - }, - { - "name": "last message should be user prompt", - "messages": [ - ChatMessage(role="assistant", content="Who you are"), - ], - "support_system_prompt": False, - }, - { - "name": "system prompt should be in the first role", - "messages": [ - ChatMessage(role="assistant", content="Who you are"), - ChatMessage(role="system", content="You are an intelligent agent"), - ChatMessage(role="user", content="Who you are"), - ], - "support_system_prompt": True, - }, - { - "name": "system prompt not supported", - "messages": [ - ChatMessage(role="system", content="You are a intelligent agent"), - ChatMessage(role="user", content="Who you are"), - ], - "support_system_prompt": False, - }, - { - "name": "only user prompt support system_prompt", - "messages": [ - ChatMessage(role="user", content="Who you are"), - ], - "support_system_prompt": True, - "succeed": True, - }, - { - "name": "batch messages all passed", - "messages": [ - [ - ChatMessage(role="user", content="Who you are"), - ], - [ - ChatMessage( - role="system", content="You are a intelligent agent" - ), - ChatMessage(role="user", content="Who you are"), - ], - ], - "backend": "vllm", - "support_system_prompt": True, - "succeed": True, - }, - { - "name": "messages should not be empty", - "messages": [ - [ - ChatMessage(role="user", content="Who you are"), - ], - [], - ], - "backend": "vllm", - "support_system_prompt": True, - }, - { - "name": "system prompt not supported", - "messages": [ - [ - ChatMessage(role="user", content="Who you are"), - ], - [ - ChatMessage( - role="system", content="You are a intelligent agent" - ), - ChatMessage(role="user", content="Who you are"), - ], - ], - "backend": "vllm", - "support_system_prompt": False, - }, - { - "name": "vLLM only supports batch inference", - "backend": "vllm", - "messages": [ - ChatMessage(role="user", content="Who you are"), - ], - "support_system_prompt": False, - }, - { - "name": "batch inference only supports with vLLM backend", - "messages": [ - [ - ChatMessage(role="user", content="Who you are"), - ], - [ - ChatMessage( - role="system", content="You are a intelligent agent" - ), - ChatMessage(role="user", content="Who you are"), - ], - ], - "support_system_prompt": True, - }, - ] - - for tc in test_cases: - backend = tc.get("backend", consts.BACKEND_HF) - model = Model("llama-2", backend=backend) - model.__config__.update( - {"support_system_prompt": tc["support_system_prompt"]}, - ) - if tc.get("succeed", False): - model.validation(tc["messages"]) - else: - with pytest.raises(AssertionError, match=tc["name"]): - model.validation(tc["messages"]) diff --git a/tests/unit_tests/utils/__init__.py b/tests/unit_tests/utils/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/tests/unit_tests/utils/test_util.py b/tests/unit_tests/utils/test_util.py deleted file mode 100644 index 6e63457..0000000 --- a/tests/unit_tests/utils/test_util.py +++ /dev/null @@ -1,55 +0,0 @@ -from llmlite.utils import util -from llmlite import consts - - -class TestValidation: - def test_parse_model_name(self): - test_cases = [ - { - "name": "parse llama2", - "model_name": "Llama-2-13b-chat-hf", - "want_model_type": consts.MODEL_TYPE_LLAMA, - "want_version": 2, - }, - { - "name": "parse codellama", - "model_name": "CodeLlama-7b-hf", - "want_model_type": consts.MODEL_TYPE_LLAMA, - "want_version": 2, - }, - { - "name": "parse chatglm2", - "model_name": "chatglm2-6b", - "want_model_type": consts.MODEL_TYPE_CHATGLM, - "want_version": 2, - }, - { - "name": "parse chatglm3", - "model_name": "chatglm3-6b", - "want_model_type": consts.MODEL_TYPE_CHATGLM, - "want_version": 3, - }, - { - "name": "parse baichuan2", - "model_name": "Baichuan2-13B-Chat", - "want_model_type": consts.MODEL_TYPE_BAICHUAN, - "want_version": 2, - }, - { - "name": "parse gpt-3.5", - "model_name": "gpt-3.5turbo", - "want_model_type": consts.MODEL_TYPE_GPT, - "want_version": 3.5, - }, - { - "name": "parse gpt-4", - "model_name": "gpt-4", - "want_model_type": consts.MODEL_TYPE_GPT, - "want_version": 4, - }, - ] - - for tc in test_cases: - model_type, version = util.parse_model_name(tc["model_name"]) - assert model_type == tc["want_model_type"] - assert version == tc["want_version"]