diff --git a/Makefile b/Makefile index ade0cdd..3defd88 100644 --- a/Makefile +++ b/Makefile @@ -13,7 +13,7 @@ server-dev: cd server && make run-dev router-dev: - cd router && cargo run + cd router && cargo run -- --port 8080 integration-tests: install-router install-launcher cargo test @@ -22,16 +22,16 @@ python-tests: cd server && HF_HUB_ENABLE_HF_TRANSFER=1 pytest tests run-bloom-560m: - text-generation-launcher --model-id bigscience/bloom-560m --num-shard 2 + text-generation-launcher --model-id bigscience/bloom-560m --num-shard 2 --port 8080 run-bloom-560m-quantize: - text-generation-launcher --model-id bigscience/bloom-560m --num-shard 2 --quantize + text-generation-launcher --model-id bigscience/bloom-560m --num-shard 2 --quantize --port 8080 download-bloom: HF_HUB_ENABLE_HF_TRANSFER=1 text-generation-server download-weights bigscience/bloom run-bloom: - text-generation-launcher --model-id bigscience/bloom --num-shard 8 + text-generation-launcher --model-id bigscience/bloom --num-shard 8 --port 8080 run-bloom-quantize: - text-generation-launcher --model-id bigscience/bloom --num-shard 8 --quantize \ No newline at end of file + text-generation-launcher --model-id bigscience/bloom --num-shard 8 --quantize --port 8080 \ No newline at end of file diff --git a/README.md b/README.md index ae18550..5cd26a0 100644 --- a/README.md +++ b/README.md @@ -89,40 +89,35 @@ You can then query the model using either the `/generate` or `/generate_stream` ```shell curl 127.0.0.1:8080/generate \ -X POST \ - -d '{"inputs":"Testing API","parameters":{"max_new_tokens":9}}' \ + -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17}}' \ -H 'Content-Type: application/json' ``` ```shell curl 127.0.0.1:8080/generate_stream \ -X POST \ - -d '{"inputs":"Testing API","parameters":{"max_new_tokens":9}}' \ + -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17}}' \ -H 'Content-Type: application/json' ``` or from Python: -```python -import requests - -result = requests.post("http://127.0.0.1:8080/generate", json={"inputs":"Testing API","parameters":{"max_new_tokens":9}}) -print(result.json()) -``` - ```shell -pip install sseclient-py +pip install text-generation ``` -````python -import sseclient -import requests +```python +from text_generation import Client -r = requests.post("http://127.0.0.1:8080/generate_stream", stream=True, json={"inputs":"Testing API","parameters":{"max_new_tokens":9}}) -sse_client = sseclient.SSEClient(r) +client = Client("http://127.0.0.1:8080") +print(client.generate("What is Deep Learning?", max_new_tokens=17).generated_text) -for i, event in enumerate(sse_client.events()): - print(i, event.data) -```` +text = "" +for response in client.generate_stream("What is Deep Learning?", max_new_tokens=17): + if not response.token.special: + text += response.token.text +print(text) +``` **Note:** To use GPUs, you need to install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html). diff --git a/clients/python/.gitignore b/clients/python/.gitignore new file mode 100644 index 0000000..5758ba9 --- /dev/null +++ b/clients/python/.gitignore @@ -0,0 +1,158 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +text_generation/__pycache__/ +text_generation/pb/__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +transformers +safetensors \ No newline at end of file diff --git a/clients/python/Makefile b/clients/python/Makefile new file mode 100644 index 0000000..8b4334b --- /dev/null +++ b/clients/python/Makefile @@ -0,0 +1,6 @@ +unit-tests: + python -m pytest --cov=text_generation tests + +install: + pip install pip --upgrade + pip install -e . \ No newline at end of file diff --git a/clients/python/README.md b/clients/python/README.md new file mode 100644 index 0000000..414360b --- /dev/null +++ b/clients/python/README.md @@ -0,0 +1,52 @@ +# Text Generation + +The Hugging Face Text Generation Python library provides a convenient way of interfacing with a +`text-generation-inference` instance running on your own infrastructure or on the Hugging Face Hub. + +## Get Started + +### Install + +```shell +pip install text-generation +``` + +### Usage + +```python +from text_generation import InferenceAPIClient + +client = InferenceAPIClient("bigscience/bloomz") +text = client.generate("Why is the sky blue?").generated_text +print(text) +# ' Rayleigh scattering' + +# Token Streaming +text = "" +for response in client.generate_stream("Why is the sky blue?"): + if not response.token.special: + text += response.token.text + +print(text) +# ' Rayleigh scattering' +``` + +or with the asynchronous client: + +```python +from text_generation import InferenceAPIAsyncClient + +client = InferenceAPIAsyncClient("bigscience/bloomz") +response = await client.generate("Why is the sky blue?") +print(response.generated_text) +# ' Rayleigh scattering' + +# Token Streaming +text = "" +async for response in client.generate_stream("Why is the sky blue?"): + if not response.token.special: + text += response.token.text + +print(text) +# ' Rayleigh scattering' +``` diff --git a/clients/python/poetry.lock b/clients/python/poetry.lock new file 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+huggingface-hub = "^0.12.1" + +[tool.poetry.dev-dependencies] +pytest = "^6.2.5" +pytest-asyncio = "^0.17.2" +pytest-cov = "^3.0.0" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/clients/python/tests/conftest.py b/clients/python/tests/conftest.py new file mode 100644 index 0000000..4298623 --- /dev/null +++ b/clients/python/tests/conftest.py @@ -0,0 +1,56 @@ +import pytest + +from text_generation import __version__ +from huggingface_hub.utils import build_hf_headers + + +@pytest.fixture +def bloom_model(): + return "bigscience/bloom" + + +@pytest.fixture +def flan_t5_xxl(): + return "google/flan-t5-xxl" + + +@pytest.fixture +def fake_model(): + return "fake/model" + + +@pytest.fixture +def unsupported_model(): + return "gpt2" + + +@pytest.fixture +def base_url(): + return "https://api-inference.huggingface.co/models" + + +@pytest.fixture +def bloom_url(base_url, bloom_model): + return f"{base_url}/{bloom_model}" + + +@pytest.fixture +def flan_t5_xxl_url(base_url, flan_t5_xxl): + return f"{base_url}/{flan_t5_xxl}" + + +@pytest.fixture +def fake_url(base_url, fake_model): + return f"{base_url}/{fake_model}" + + +@pytest.fixture +def unsupported_url(base_url, unsupported_model): + return f"{base_url}/{unsupported_model}" + + +@pytest.fixture(scope="session") +def hf_headers(): + return build_hf_headers( + library_name="text-generation-tests", library_version=__version__ + ) diff --git a/clients/python/tests/test_client.py b/clients/python/tests/test_client.py new file mode 100644 index 0000000..2f96aa8 --- /dev/null +++ b/clients/python/tests/test_client.py @@ -0,0 +1,127 @@ +import pytest + +from text_generation import Client, AsyncClient +from text_generation.errors import NotFoundError, ValidationError +from text_generation.types import FinishReason, PrefillToken, Token + + +def test_generate(bloom_url, hf_headers): + client = Client(bloom_url, hf_headers) + response = client.generate("test", max_new_tokens=1) + + assert response.generated_text == "." + assert response.details.finish_reason == FinishReason.Length + assert response.details.generated_tokens == 1 + assert response.details.seed is None + assert len(response.details.prefill) == 1 + assert response.details.prefill[0] == PrefillToken( + id=9234, text="test", logprob=None + ) + assert len(response.details.tokens) == 1 + assert response.details.tokens[0] == Token( + id=17, text=".", logprob=-1.75, special=False + ) + + +def test_generate_not_found(fake_url, hf_headers): + client = Client(fake_url, hf_headers) + with pytest.raises(NotFoundError): + client.generate("test") + + +def test_generate_validation_error(flan_t5_xxl_url, hf_headers): + client = Client(flan_t5_xxl_url, hf_headers) + with pytest.raises(ValidationError): + client.generate("test", max_new_tokens=10_000) + + +def test_generate_stream(bloom_url, hf_headers): + client = Client(bloom_url, hf_headers) + responses = [ + response for response in client.generate_stream("test", max_new_tokens=1) + ] + + assert len(responses) == 1 + response = responses[0] + + assert response.generated_text == "." + assert response.details.finish_reason == FinishReason.Length + assert response.details.generated_tokens == 1 + assert response.details.seed is None + + +def test_generate_stream_not_found(fake_url, hf_headers): + client = Client(fake_url, hf_headers) + with pytest.raises(NotFoundError): + list(client.generate_stream("test")) + + +def test_generate_stream_validation_error(flan_t5_xxl_url, hf_headers): + client = Client(flan_t5_xxl_url, hf_headers) + with pytest.raises(ValidationError): + list(client.generate_stream("test", max_new_tokens=10_000)) + + +@pytest.mark.asyncio +async def test_generate_async(bloom_url, hf_headers): + client = AsyncClient(bloom_url, hf_headers) + response = await client.generate("test", max_new_tokens=1) + + assert response.generated_text == "." + assert response.details.finish_reason == FinishReason.Length + assert response.details.generated_tokens == 1 + assert response.details.seed is None + assert len(response.details.prefill) == 1 + assert response.details.prefill[0] == PrefillToken( + id=9234, text="test", logprob=None + ) + assert len(response.details.tokens) == 1 + assert response.details.tokens[0] == Token( + id=17, text=".", logprob=-1.75, special=False + ) + + +@pytest.mark.asyncio +async def test_generate_async_not_found(fake_url, hf_headers): + client = AsyncClient(fake_url, hf_headers) + with pytest.raises(NotFoundError): + await client.generate("test") + + +@pytest.mark.asyncio +async def test_generate_async_validation_error(flan_t5_xxl_url, hf_headers): + client = AsyncClient(flan_t5_xxl_url, hf_headers) + with pytest.raises(ValidationError): + await client.generate("test", max_new_tokens=10_000) + + +@pytest.mark.asyncio +async def test_generate_stream_async(bloom_url, hf_headers): + client = AsyncClient(bloom_url, hf_headers) + responses = [ + response async for response in client.generate_stream("test", max_new_tokens=1) + ] + + assert len(responses) == 1 + response = responses[0] + + assert response.generated_text == "." + assert response.details.finish_reason == FinishReason.Length + assert response.details.generated_tokens == 1 + assert response.details.seed is None + + +@pytest.mark.asyncio +async def test_generate_stream_async_not_found(fake_url, hf_headers): + client = AsyncClient(fake_url, hf_headers) + with pytest.raises(NotFoundError): + async for _ in client.generate_stream("test"): + pass + + +@pytest.mark.asyncio +async def test_generate_stream_async_validation_error(flan_t5_xxl_url, hf_headers): + client = AsyncClient(flan_t5_xxl_url, hf_headers) + with pytest.raises(ValidationError): + async for _ in client.generate_stream("test", max_new_tokens=10_000): + pass diff --git a/clients/python/tests/test_errors.py b/clients/python/tests/test_errors.py new file mode 100644 index 0000000..8389ed3 --- /dev/null +++ b/clients/python/tests/test_errors.py @@ -0,0 +1,64 @@ +from text_generation.errors import ( + parse_error, + GenerationError, + IncompleteGenerationError, + OverloadedError, + ValidationError, + BadRequestError, + ShardNotReadyError, + ShardTimeoutError, + NotFoundError, + RateLimitExceededError, + UnknownError, +) + + +def test_generation_error(): + payload = {"error_type": "generation", "error": "test"} + assert isinstance(parse_error(400, payload), GenerationError) + + +def test_incomplete_generation_error(): + payload = {"error_type": "incomplete_generation", "error": "test"} + assert isinstance(parse_error(400, payload), IncompleteGenerationError) + + +def test_overloaded_error(): + payload = {"error_type": "overloaded", "error": "test"} + assert isinstance(parse_error(400, payload), OverloadedError) + + +def test_validation_error(): + payload = {"error_type": "validation", "error": "test"} + assert isinstance(parse_error(400, payload), ValidationError) + + +def test_bad_request_error(): + payload = {"error": "test"} + assert isinstance(parse_error(400, payload), BadRequestError) + + +def test_shard_not_ready_error(): + payload = {"error": "test"} + assert isinstance(parse_error(403, payload), ShardNotReadyError) + assert isinstance(parse_error(424, payload), ShardNotReadyError) + + +def test_shard_timeout_error(): + payload = {"error": "test"} + assert isinstance(parse_error(504, payload), ShardTimeoutError) + + +def test_not_found_error(): + payload = {"error": "test"} + assert isinstance(parse_error(404, payload), NotFoundError) + + +def test_rate_limit_exceeded_error(): + payload = {"error": "test"} + assert isinstance(parse_error(429, payload), RateLimitExceededError) + + +def test_unknown_error(): + payload = {"error": "test"} + assert isinstance(parse_error(500, payload), UnknownError) diff --git a/clients/python/tests/test_inference_api.py b/clients/python/tests/test_inference_api.py new file mode 100644 index 0000000..dc74494 --- /dev/null +++ b/clients/python/tests/test_inference_api.py @@ -0,0 +1,34 @@ +import pytest + +from text_generation import ( + InferenceAPIClient, + InferenceAPIAsyncClient, + Client, + AsyncClient, +) +from text_generation.errors import NotSupportedError +from text_generation.inference_api import get_supported_models + + +def test_get_supported_models(): + assert isinstance(get_supported_models(), list) + + +def test_client(bloom_model): + client = InferenceAPIClient(bloom_model) + assert isinstance(client, Client) + + +def test_client_unsupported_model(unsupported_model): + with pytest.raises(NotSupportedError): + InferenceAPIClient(unsupported_model) + + +def test_async_client(bloom_model): + client = InferenceAPIAsyncClient(bloom_model) + assert isinstance(client, AsyncClient) + + +def test_async_client_unsupported_model(unsupported_model): + with pytest.raises(NotSupportedError): + InferenceAPIAsyncClient(unsupported_model) diff --git a/clients/python/tests/test_types.py b/clients/python/tests/test_types.py new file mode 100644 index 0000000..d319b57 --- /dev/null +++ b/clients/python/tests/test_types.py @@ -0,0 +1,39 @@ +import pytest + +from text_generation.types import Parameters +from text_generation.errors import ValidationError + + +def test_parameters_validation(): + # Test repetition_penalty + Parameters(repetition_penalty=1) + with pytest.raises(ValidationError): + Parameters(repetition_penalty=0) + with pytest.raises(ValidationError): + Parameters(repetition_penalty=-1) + + # Test seed + Parameters(seed=1) + with pytest.raises(ValidationError): + Parameters(seed=-1) + + # Test temperature + Parameters(temperature=1) + with pytest.raises(ValidationError): + Parameters(temperature=0) + with pytest.raises(ValidationError): + Parameters(temperature=-1) + + # Test top_k + Parameters(top_k=1) + with pytest.raises(ValidationError): + Parameters(top_k=0) + with pytest.raises(ValidationError): + Parameters(top_k=-1) + + # Test top_p + Parameters(top_p=1) + with pytest.raises(ValidationError): + Parameters(top_p=0) + with pytest.raises(ValidationError): + Parameters(top_p=-1) diff --git a/clients/python/text_generation/__init__.py b/clients/python/text_generation/__init__.py new file mode 100644 index 0000000..88861b3 --- /dev/null +++ b/clients/python/text_generation/__init__.py @@ -0,0 +1,18 @@ +# Copyright 2023 The HuggingFace Team. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +__version__ = "0.3.2" + +from text_generation.client import Client, AsyncClient +from text_generation.inference_api import InferenceAPIClient, InferenceAPIAsyncClient diff --git a/clients/python/text_generation/client.py b/clients/python/text_generation/client.py new file mode 100644 index 0000000..d0a6791 --- /dev/null +++ b/clients/python/text_generation/client.py @@ -0,0 +1,415 @@ +import json +import requests + +from aiohttp import ClientSession, ClientTimeout +from pydantic import ValidationError +from typing import Dict, Optional, List, AsyncIterator, Iterator + +from text_generation.types import ( + StreamResponse, + Response, + Request, + Parameters, +) +from text_generation.errors import parse_error + + +class Client: + """Client to make calls to a text-generation-inference instance + + Example: + + ```python + >>> from text_generation import Client + + >>> client = Client("https://api-inference.huggingface.co/models/bigscience/bloomz") + >>> client.generate("Why is the sky blue?").generated_text + ' Rayleigh scattering' + + >>> result = "" + >>> for response in client.generate_stream("Why is the sky blue?"): + >>> if not response.token.special: + >>> result += response.token.text + >>> result + ' Rayleigh scattering' + ``` + """ + + def __init__( + self, base_url: str, headers: Optional[Dict[str, str]] = None, timeout: int = 10 + ): + """ + Args: + base_url (`str`): + text-generation-inference instance base url + headers (`Optional[Dict[str, str]]`): + Additional headers + timeout (`int`): + Timeout in seconds + """ + self.base_url = base_url + self.headers = headers + self.timeout = timeout + + def generate( + self, + prompt: str, + do_sample: bool = False, + max_new_tokens: int = 20, + repetition_penalty: Optional[float] = None, + return_full_text: bool = False, + seed: Optional[int] = None, + stop_sequences: Optional[List[str]] = None, + temperature: Optional[float] = None, + top_k: Optional[int] = None, + top_p: Optional[float] = None, + watermarking: bool = False, + ) -> Response: + """ + Given a prompt, generate the following text + + Args: + prompt (`str`): + Input text + do_sample (`bool`): + Activate logits sampling + max_new_tokens (`int`): + Maximum number of generated tokens + repetition_penalty (`float`): + The parameter for repetition penalty. 1.0 means no penalty. See [this + paper](https://arxiv.org/pdf/1909.05858.pdf) for more details. + return_full_text (`bool`): + Whether to prepend the prompt to the generated text + seed (`int`): + Random sampling seed + stop_sequences (`List[str]`): + Stop generating tokens if a member of `stop_sequences` is generated + temperature (`float`): + The value used to module the logits distribution. + top_k (`int`): + The number of highest probability vocabulary tokens to keep for top-k-filtering. + top_p (`float`): + If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or + higher are kept for generation. + watermarking (`bool`): + Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226) + + Returns: + Response: generated response + """ + # Validate parameters + parameters = Parameters( + details=True, + do_sample=do_sample, + max_new_tokens=max_new_tokens, + repetition_penalty=repetition_penalty, + return_full_text=return_full_text, + seed=seed, + stop=stop_sequences if stop_sequences is not None else [], + temperature=temperature, + top_k=top_k, + top_p=top_p, + watermark=watermarking, + ) + request = Request(inputs=prompt, stream=False, parameters=parameters) + + resp = requests.post( + self.base_url, + json=request.dict(), + headers=self.headers, + timeout=self.timeout, + ) + payload = resp.json() + if resp.status_code != 200: + raise parse_error(resp.status_code, payload) + return Response(**payload[0]) + + def generate_stream( + self, + prompt: str, + do_sample: bool = False, + max_new_tokens: int = 20, + repetition_penalty: Optional[float] = None, + return_full_text: bool = False, + seed: Optional[int] = None, + stop_sequences: Optional[List[str]] = None, + temperature: Optional[float] = None, + top_k: Optional[int] = None, + top_p: Optional[float] = None, + watermarking: bool = False, + ) -> Iterator[StreamResponse]: + """ + Given a prompt, generate the following stream of tokens + + Args: + prompt (`str`): + Input text + do_sample (`bool`): + Activate logits sampling + max_new_tokens (`int`): + Maximum number of generated tokens + repetition_penalty (`float`): + The parameter for repetition penalty. 1.0 means no penalty. See [this + paper](https://arxiv.org/pdf/1909.05858.pdf) for more details. + return_full_text (`bool`): + Whether to prepend the prompt to the generated text + seed (`int`): + Random sampling seed + stop_sequences (`List[str]`): + Stop generating tokens if a member of `stop_sequences` is generated + temperature (`float`): + The value used to module the logits distribution. + top_k (`int`): + The number of highest probability vocabulary tokens to keep for top-k-filtering. + top_p (`float`): + If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or + higher are kept for generation. + watermarking (`bool`): + Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226) + + Returns: + Iterator[StreamResponse]: stream of generated tokens + """ + # Validate parameters + parameters = Parameters( + details=True, + do_sample=do_sample, + max_new_tokens=max_new_tokens, + repetition_penalty=repetition_penalty, + return_full_text=return_full_text, + seed=seed, + stop=stop_sequences if stop_sequences is not None else [], + temperature=temperature, + top_k=top_k, + top_p=top_p, + watermark=watermarking, + ) + request = Request(inputs=prompt, stream=True, parameters=parameters) + + resp = requests.post( + self.base_url, + json=request.dict(), + headers=self.headers, + timeout=self.timeout, + stream=False, + ) + + if resp.status_code != 200: + raise parse_error(resp.status_code, resp.json()) + + # Parse ServerSentEvents + for byte_payload in resp.iter_lines(): + # Skip line + if byte_payload == b"\n": + continue + + payload = byte_payload.decode("utf-8") + + # Event data + if payload.startswith("data:"): + # Decode payload + json_payload = json.loads(payload.lstrip("data:").rstrip("/n")) + # Parse payload + try: + response = StreamResponse(**json_payload) + except ValidationError: + # If we failed to parse the payload, then it is an error payload + raise parse_error(resp.status_code, json_payload) + yield response + + +class AsyncClient: + """Asynchronous Client to make calls to a text-generation-inference instance + + Example: + + ```python + >>> from text_generation import AsyncClient + + >>> client = AsyncClient("https://api-inference.huggingface.co/models/bigscience/bloomz") + >>> response = await client.generate("Why is the sky blue?") + >>> response.generated_text + ' Rayleigh scattering' + + >>> result = "" + >>> async for response in client.generate_stream("Why is the sky blue?"): + >>> if not response.token.special: + >>> result += response.token.text + >>> result + ' Rayleigh scattering' + ``` + """ + + def __init__( + self, base_url: str, headers: Optional[Dict[str, str]] = None, timeout: int = 10 + ): + """ + Args: + base_url (`str`): + text-generation-inference instance base url + headers (`Optional[Dict[str, str]]`): + Additional headers + timeout (`int`): + Timeout in seconds + """ + self.base_url = base_url + self.headers = headers + self.timeout = ClientTimeout(timeout * 60) + + async def generate( + self, + prompt: str, + do_sample: bool = False, + max_new_tokens: int = 20, + repetition_penalty: Optional[float] = None, + return_full_text: bool = False, + seed: Optional[int] = None, + stop_sequences: Optional[List[str]] = None, + temperature: Optional[float] = None, + top_k: Optional[int] = None, + top_p: Optional[float] = None, + watermarking: bool = False, + ) -> Response: + """ + Given a prompt, generate the following text asynchronously + + Args: + prompt (`str`): + Input text + do_sample (`bool`): + Activate logits sampling + max_new_tokens (`int`): + Maximum number of generated tokens + repetition_penalty (`float`): + The parameter for repetition penalty. 1.0 means no penalty. See [this + paper](https://arxiv.org/pdf/1909.05858.pdf) for more details. + return_full_text (`bool`): + Whether to prepend the prompt to the generated text + seed (`int`): + Random sampling seed + stop_sequences (`List[str]`): + Stop generating tokens if a member of `stop_sequences` is generated + temperature (`float`): + The value used to module the logits distribution. + top_k (`int`): + The number of highest probability vocabulary tokens to keep for top-k-filtering. + top_p (`float`): + If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or + higher are kept for generation. + watermarking (`bool`): + Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226) + + Returns: + Response: generated response + """ + # Validate parameters + parameters = Parameters( + details=True, + do_sample=do_sample, + max_new_tokens=max_new_tokens, + repetition_penalty=repetition_penalty, + return_full_text=return_full_text, + seed=seed, + stop=stop_sequences if stop_sequences is not None else [], + temperature=temperature, + top_k=top_k, + top_p=top_p, + watermark=watermarking, + ) + request = Request(inputs=prompt, stream=False, parameters=parameters) + + async with ClientSession(headers=self.headers, timeout=self.timeout) as session: + async with session.post(self.base_url, json=request.dict()) as resp: + payload = await resp.json() + + if resp.status != 200: + raise parse_error(resp.status, payload) + return Response(**payload[0]) + + async def generate_stream( + self, + prompt: str, + do_sample: bool = False, + max_new_tokens: int = 20, + repetition_penalty: Optional[float] = None, + return_full_text: bool = False, + seed: Optional[int] = None, + stop_sequences: Optional[List[str]] = None, + temperature: Optional[float] = None, + top_k: Optional[int] = None, + top_p: Optional[float] = None, + watermarking: bool = False, + ) -> AsyncIterator[StreamResponse]: + """ + Given a prompt, generate the following stream of tokens asynchronously + + Args: + prompt (`str`): + Input text + do_sample (`bool`): + Activate logits sampling + max_new_tokens (`int`): + Maximum number of generated tokens + repetition_penalty (`float`): + The parameter for repetition penalty. 1.0 means no penalty. See [this + paper](https://arxiv.org/pdf/1909.05858.pdf) for more details. + return_full_text (`bool`): + Whether to prepend the prompt to the generated text + seed (`int`): + Random sampling seed + stop_sequences (`List[str]`): + Stop generating tokens if a member of `stop_sequences` is generated + temperature (`float`): + The value used to module the logits distribution. + top_k (`int`): + The number of highest probability vocabulary tokens to keep for top-k-filtering. + top_p (`float`): + If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or + higher are kept for generation. + watermarking (`bool`): + Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226) + + Returns: + AsyncIterator[StreamResponse]: stream of generated tokens + """ + # Validate parameters + parameters = Parameters( + details=True, + do_sample=do_sample, + max_new_tokens=max_new_tokens, + repetition_penalty=repetition_penalty, + return_full_text=return_full_text, + seed=seed, + stop=stop_sequences if stop_sequences is not None else [], + temperature=temperature, + top_k=top_k, + top_p=top_p, + watermark=watermarking, + ) + request = Request(inputs=prompt, stream=True, parameters=parameters) + + async with ClientSession(headers=self.headers, timeout=self.timeout) as session: + async with session.post(self.base_url, json=request.dict()) as resp: + + if resp.status != 200: + raise parse_error(resp.status, await resp.json()) + + # Parse ServerSentEvents + async for byte_payload in resp.content: + # Skip line + if byte_payload == b"\n": + continue + + payload = byte_payload.decode("utf-8") + + # Event data + if payload.startswith("data:"): + # Decode payload + json_payload = json.loads(payload.lstrip("data:").rstrip("/n")) + # Parse payload + try: + response = StreamResponse(**json_payload) + except ValidationError: + # If we failed to parse the payload, then it is an error payload + raise parse_error(resp.status, json_payload) + yield response diff --git a/clients/python/text_generation/errors.py b/clients/python/text_generation/errors.py new file mode 100644 index 0000000..dbf0b76 --- /dev/null +++ b/clients/python/text_generation/errors.py @@ -0,0 +1,106 @@ +from typing import Dict + + +# Text Generation Inference Errors +class ValidationError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class GenerationError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class OverloadedError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class IncompleteGenerationError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +# API Inference Errors +class BadRequestError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class ShardNotReadyError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class ShardTimeoutError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class NotFoundError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class RateLimitExceededError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +class NotSupportedError(Exception): + def __init__(self, model_id: str): + message = ( + f"Model `{model_id}` is not available for inference with this client. \n" + "Use `huggingface_hub.inference_api.InferenceApi` instead." + ) + super(NotSupportedError, self).__init__(message) + + +# Unknown error +class UnknownError(Exception): + def __init__(self, message: str): + super().__init__(message) + + +def parse_error(status_code: int, payload: Dict[str, str]) -> Exception: + """ + Parse error given an HTTP status code and a json payload + + Args: + status_code (`int`): + HTTP status code + payload (`Dict[str, str]`): + Json payload + + Returns: + Exception: parsed exception + + """ + # Try to parse a Text Generation Inference error + message = payload["error"] + if "error_type" in payload: + error_type = payload["error_type"] + if error_type == "generation": + return GenerationError(message) + if error_type == "incomplete_generation": + return IncompleteGenerationError(message) + if error_type == "overloaded": + return OverloadedError(message) + if error_type == "validation": + return ValidationError(message) + + # Try to parse a APIInference error + if status_code == 400: + return BadRequestError(message) + if status_code == 403 or status_code == 424: + return ShardNotReadyError(message) + if status_code == 504: + return ShardTimeoutError(message) + if status_code == 404: + return NotFoundError(message) + if status_code == 429: + return RateLimitExceededError(message) + + # Fallback to an unknown error + return UnknownError(message) diff --git a/clients/python/text_generation/inference_api.py b/clients/python/text_generation/inference_api.py new file mode 100644 index 0000000..bc6022b --- /dev/null +++ b/clients/python/text_generation/inference_api.py @@ -0,0 +1,150 @@ +import os +import requests +import base64 +import json +import warnings + +from typing import List, Optional +from huggingface_hub.utils import build_hf_headers + +from text_generation import Client, AsyncClient, __version__ +from text_generation.errors import NotSupportedError + +INFERENCE_ENDPOINT = os.environ.get( + "HF_INFERENCE_ENDPOINT", "https://api-inference.huggingface.co" +) + +SUPPORTED_MODELS = None + + +def get_supported_models() -> Optional[List[str]]: + """ + Get the list of supported text-generation models from GitHub + + Returns: + Optional[List[str]]: supported models list or None if unable to get the list from GitHub + """ + global SUPPORTED_MODELS + if SUPPORTED_MODELS is not None: + return SUPPORTED_MODELS + + response = requests.get( + "https://api.github.com/repos/huggingface/text-generation-inference/contents/supported_models.json", + timeout=5, + ) + if response.status_code == 200: + file_content = response.json()["content"] + SUPPORTED_MODELS = json.loads(base64.b64decode(file_content).decode("utf-8")) + return SUPPORTED_MODELS + + warnings.warn("Could not retrieve list of supported models.") + return None + + +class InferenceAPIClient(Client): + """Client to make calls to the HuggingFace Inference API. + + Only supports a subset of the available text-generation or text2text-generation models that are served using + text-generation-inference + + Example: + + ```python + >>> from text_generation import InferenceAPIClient + + >>> client = InferenceAPIClient("bigscience/bloomz") + >>> client.generate("Why is the sky blue?").generated_text + ' Rayleigh scattering' + + >>> result = "" + >>> for response in client.generate_stream("Why is the sky blue?"): + >>> if not response.token.special: + >>> result += response.token.text + >>> result + ' Rayleigh scattering' + ``` + """ + + def __init__(self, repo_id: str, token: Optional[str] = None, timeout: int = 10): + """ + Init headers and API information + + Args: + repo_id (`str`): + Id of repository (e.g. `bigscience/bloom`). + token (`str`, `optional`): + The API token to use as HTTP bearer authorization. This is not + the authentication token. You can find the token in + https://huggingface.co/settings/token. Alternatively, you can + find both your organizations and personal API tokens using + `HfApi().whoami(token)`. + timeout (`int`): + Timeout in seconds + """ + + # Text Generation Inference client only supports a subset of the available hub models + supported_models = get_supported_models() + if supported_models is not None and repo_id not in supported_models: + raise NotSupportedError(repo_id) + + headers = build_hf_headers( + token=token, library_name="text-generation", library_version=__version__ + ) + base_url = f"{INFERENCE_ENDPOINT}/models/{repo_id}" + + super(InferenceAPIClient, self).__init__(base_url, headers, timeout) + + +class InferenceAPIAsyncClient(AsyncClient): + """Aynschronous Client to make calls to the HuggingFace Inference API. + + Only supports a subset of the available text-generation or text2text-generation models that are served using + text-generation-inference + + Example: + + ```python + >>> from text_generation import InferenceAPIAsyncClient + + >>> client = InferenceAPIAsyncClient("bigscience/bloomz") + >>> response = await client.generate("Why is the sky blue?") + >>> response.generated_text + ' Rayleigh scattering' + + >>> result = "" + >>> async for response in client.generate_stream("Why is the sky blue?"): + >>> if not response.token.special: + >>> result += response.token.text + >>> result + ' Rayleigh scattering' + ``` + """ + + def __init__(self, repo_id: str, token: Optional[str] = None, timeout: int = 10): + """ + Init headers and API information + + Args: + repo_id (`str`): + Id of repository (e.g. `bigscience/bloom`). + token (`str`, `optional`): + The API token to use as HTTP bearer authorization. This is not + the authentication token. You can find the token in + https://huggingface.co/settings/token. Alternatively, you can + find both your organizations and personal API tokens using + `HfApi().whoami(token)`. + timeout (`int`): + Timeout in seconds + """ + + # Text Generation Inference client only supports a subset of the available hub models + supported_models = get_supported_models() + if supported_models is not None and repo_id not in supported_models: + raise NotSupportedError(repo_id) + + headers = build_hf_headers( + token=token, library_name="text-generation", library_version=__version__ + ) + base_url = f"{INFERENCE_ENDPOINT}/models/{repo_id}" + + super(InferenceAPIAsyncClient, self).__init__(base_url, headers, timeout) diff --git a/clients/python/text_generation/types.py b/clients/python/text_generation/types.py new file mode 100644 index 0000000..d276b60 --- /dev/null +++ b/clients/python/text_generation/types.py @@ -0,0 +1,99 @@ +from enum import Enum +from pydantic import BaseModel, validator +from typing import Optional, List + +from text_generation.errors import ValidationError + + +class Parameters(BaseModel): + do_sample: bool = False + max_new_tokens: int = 20 + repetition_penalty: Optional[float] = None + return_full_text: bool = False + stop: List[str] = [] + seed: Optional[int] + temperature: Optional[float] + top_k: Optional[int] + top_p: Optional[float] + watermark: bool = False + details: bool = False + + @validator("repetition_penalty") + def valid_repetition_penalty(cls, v): + if v is not None and v is v <= 0: + raise ValidationError("`repetition_penalty` must be strictly positive") + return v + + @validator("seed") + def valid_seed(cls, v): + if v is not None and v is v < 0: + raise ValidationError("`seed` must be positive") + return v + + @validator("temperature") + def valid_temp(cls, v): + if v is not None and v <= 0: + raise ValidationError("`temperature` must be strictly positive") + return v + + @validator("top_k") + def valid_top_k(cls, v): + if v is not None and v <= 0: + raise ValidationError("`top_k` must be strictly positive") + return v + + @validator("top_p") + def valid_top_p(cls, v): + if v is not None and (v <= 0 or v > 1.0): + raise ValidationError("`top_p` must be > 0.0 and <= 1.0") + return v + + +class Request(BaseModel): + inputs: str + parameters: Parameters + stream: bool = False + + +class PrefillToken(BaseModel): + id: int + text: str + logprob: Optional[float] + + +class Token(BaseModel): + id: int + text: str + logprob: float + special: bool + + +class FinishReason(Enum): + Length = "length" + EndOfSequenceToken = "eos_token" + StopSequence = "stop_sequence" + + +class Details(BaseModel): + finish_reason: FinishReason + generated_tokens: int + seed: Optional[int] + prefill: List[PrefillToken] + tokens: List[Token] + + +class StreamDetails(BaseModel): + finish_reason: FinishReason + generated_tokens: int + seed: Optional[int] + + +class Response(BaseModel): + generated_text: str + details: Details + + +class StreamResponse(BaseModel): + token: Token + generated_text: Optional[str] + details: Optional[StreamDetails] diff --git a/router/src/infer.rs b/router/src/infer.rs index 598c2fc..d0964f9 100644 --- a/router/src/infer.rs +++ b/router/src/infer.rs @@ -439,3 +439,14 @@ pub enum InferError { #[error("Incomplete generation")] IncompleteGeneration, } + +impl InferError { + pub(crate) fn error_type(&self) -> &str { + match self { + InferError::GenerationError(_) => "generation", + InferError::Overloaded(_) => "overloaded", + InferError::ValidationError(_) => "validation", + InferError::IncompleteGeneration => "incomplete_generation", + } + } +} diff --git a/router/src/lib.rs b/router/src/lib.rs index 1386f6b..1819541 100644 --- a/router/src/lib.rs +++ b/router/src/lib.rs @@ -152,8 +152,8 @@ pub(crate) struct Details { pub generated_tokens: u32, #[schema(example = 42)] pub seed: Option, - pub prefill: Option>, - pub tokens: Option>, + pub prefill: Vec, + pub tokens: Vec, } #[derive(Serialize, ToSchema)] @@ -185,6 +185,6 @@ pub(crate) struct StreamResponse { #[derive(Serialize, ToSchema)] pub(crate) struct ErrorResponse { - #[schema(inline)] pub error: String, + pub error_type: String, } diff --git a/router/src/server.rs b/router/src/server.rs index 247c55b..b8b6b44 100644 --- a/router/src/server.rs +++ b/router/src/server.rs @@ -133,8 +133,8 @@ async fn generate( true => Some(Details { finish_reason: FinishReason::from(response.generated_text.finish_reason), generated_tokens: response.generated_text.generated_tokens, - prefill: Some(response.prefill), - tokens: Some(response.tokens), + prefill: response.prefill, + tokens: response.tokens, seed: response.generated_text.seed, }), false => None, @@ -554,6 +554,7 @@ impl From for (StatusCode, Json) { status_code, Json(ErrorResponse { error: err.to_string(), + error_type: err.error_type().to_string(), }), ) } @@ -564,6 +565,7 @@ impl From for Event { Event::default() .json_data(ErrorResponse { error: err.to_string(), + error_type: err.error_type().to_string(), }) .unwrap() } diff --git a/router/src/validation.rs b/router/src/validation.rs index 29c2967..43f8b0f 100644 --- a/router/src/validation.rs +++ b/router/src/validation.rs @@ -271,23 +271,23 @@ pub(crate) struct ValidGenerateRequest { #[derive(Error, Debug)] pub enum ValidationError { - #[error("temperature must be strictly positive")] + #[error("`temperature` must be strictly positive")] Temperature, - #[error("repetition_penalty must be strictly positive")] + #[error("`repetition_penalty` must be strictly positive")] RepetitionPenalty, - #[error("top_p must be > 0.0 and <= 1.0")] + #[error("`top_p` must be > 0.0 and <= 1.0")] TopP, - #[error("top_k must be strictly positive")] + #[error("`top_k` must be strictly positive")] TopK, - #[error("max_new_tokens must be strictly positive")] + #[error("`max_new_tokens` must be strictly positive")] MaxNewTokens, - #[error("input tokens + max_new_tokens must be <= {0}. Given: {1} input tokens and {2} max_new_tokens")] + #[error("`inputs` tokens + `max_new_tokens` must be <= {0}. Given: {1} `inputs` tokens and {2} `max_new_tokens`")] MaxTotalTokens(usize, usize, u32), - #[error("inputs must have less than {0} tokens. Given: {1}")] + #[error("`inputs` must have less than {0} tokens. Given: {1}")] InputLength(usize, usize), - #[error("inputs cannot be empty")] + #[error("`inputs` cannot be empty")] EmptyInput, - #[error("stop supports up to {0} stop sequences. Given: {1}")] + #[error("`stop` supports up to {0} stop sequences. Given: {1}")] StopSequence(usize, usize), #[error("tokenizer error {0}")] Tokenizer(String), diff --git a/server/.gitignore b/server/.gitignore index 5758ba9..aef74bb 100644 --- a/server/.gitignore +++ b/server/.gitignore @@ -1,7 +1,7 @@ # Byte-compiled / optimized / DLL files __pycache__/ -text_generation/__pycache__/ -text_generation/pb/__pycache__/ +text_generation_server/__pycache__/ +text_generation_server/pb/__pycache__/ *.py[cod] *$py.class diff --git a/server/Makefile b/server/Makefile index 3926cf5..3de13e8 100644 --- a/server/Makefile +++ b/server/Makefile @@ -3,10 +3,10 @@ transformers_commit := 2f87dca1ca3e5663d0637da9bb037a6956e57a5e gen-server: # Compile protos pip install grpcio-tools==1.51.1 --no-cache-dir - mkdir text_generation/pb || true - python -m grpc_tools.protoc -I../proto --python_out=text_generation/pb --grpc_python_out=text_generation/pb ../proto/generate.proto - find text_generation/pb/ -type f -name "*.py" -print0 -exec sed -i -e 's/^\(import.*pb2\)/from . \1/g' {} \; - touch text_generation/pb/__init__.py + mkdir text_generation_server/pb || true + python -m grpc_tools.protoc -I../proto --python_out=text_generation_server/pb --grpc_python_out=text_generation_server/pb ../proto/generate.proto + find text_generation_server/pb/ -type f -name "*.py" -print0 -exec sed -i -e 's/^\(import.*pb2\)/from . \1/g' {} \; + touch text_generation_server/pb/__init__.py install-transformers: # Install specific version of transformers with custom cuda kernels @@ -28,4 +28,4 @@ install: gen-server install-torch install-transformers pip install -e . --no-cache-dir run-dev: - SAFETENSORS_FAST_GPU=1 python -m torch.distributed.run --nproc_per_node=2 text_generation/cli.py serve bigscience/bloom-560m --sharded \ No newline at end of file + SAFETENSORS_FAST_GPU=1 python -m torch.distributed.run --nproc_per_node=2 text_generation_server/cli.py serve bigscience/bloom-560m --sharded \ No newline at end of file diff --git a/server/pyproject.toml b/server/pyproject.toml index 2127793..b8e188b 100644 --- a/server/pyproject.toml +++ b/server/pyproject.toml @@ -1,11 +1,11 @@ [tool.poetry] -name = "text-generation" +name = "text-generation-server" version = "0.3.2" description = "Text Generation Inference Python gRPC Server" authors = ["Olivier Dehaene "] [tool.poetry.scripts] -text-generation-server = 'text_generation.cli:app' +text-generation-server = 'text_generation_server.cli:app' [tool.poetry.dependencies] python = "^3.9" diff --git a/server/tests/conftest.py b/server/tests/conftest.py index 9fae8ee..04c909e 100644 --- a/server/tests/conftest.py +++ b/server/tests/conftest.py @@ -1,6 +1,6 @@ import pytest -from text_generation.pb import generate_pb2 +from text_generation_server.pb import generate_pb2 @pytest.fixture diff --git a/server/tests/models/test_bloom.py b/server/tests/models/test_bloom.py index bc36276..90239f9 100644 --- a/server/tests/models/test_bloom.py +++ b/server/tests/models/test_bloom.py @@ -4,9 +4,9 @@ import torch from copy import copy from transformers import AutoTokenizer -from text_generation.pb import generate_pb2 -from text_generation.models.causal_lm import CausalLMBatch -from text_generation.models.bloom import BloomCausalLMBatch, BLOOM +from text_generation_server.pb import generate_pb2 +from text_generation_server.models.causal_lm import CausalLMBatch +from text_generation_server.models.bloom import BloomCausalLMBatch, BLOOM @pytest.fixture(scope="session") diff --git a/server/tests/models/test_causal_lm.py b/server/tests/models/test_causal_lm.py index 723017c..869022f 100644 --- a/server/tests/models/test_causal_lm.py +++ b/server/tests/models/test_causal_lm.py @@ -4,8 +4,8 @@ import torch from copy import copy from transformers import AutoTokenizer -from text_generation.pb import generate_pb2 -from text_generation.models.causal_lm import CausalLM, CausalLMBatch +from text_generation_server.pb import generate_pb2 +from text_generation_server.models.causal_lm import CausalLM, CausalLMBatch @pytest.fixture(scope="session") diff --git a/server/tests/models/test_santacoder.py b/server/tests/models/test_santacoder.py index 1596e41..d089def 100644 --- a/server/tests/models/test_santacoder.py +++ b/server/tests/models/test_santacoder.py @@ -1,8 +1,8 @@ import pytest -from text_generation.pb import generate_pb2 -from text_generation.models.causal_lm import CausalLMBatch -from text_generation.models.santacoder import SantaCoder +from text_generation_server.pb import generate_pb2 +from text_generation_server.models.causal_lm import CausalLMBatch +from text_generation_server.models.santacoder import SantaCoder @pytest.fixture(scope="session") diff --git a/server/tests/models/test_seq2seq_lm.py b/server/tests/models/test_seq2seq_lm.py index f717339..764f8f8 100644 --- a/server/tests/models/test_seq2seq_lm.py +++ b/server/tests/models/test_seq2seq_lm.py @@ -5,8 +5,8 @@ from copy import copy from transformers import AutoTokenizer -from text_generation.pb import generate_pb2 -from text_generation.models.seq2seq_lm import Seq2SeqLM, Seq2SeqLMBatch +from text_generation_server.pb import generate_pb2 +from text_generation_server.models.seq2seq_lm import Seq2SeqLM, Seq2SeqLMBatch @pytest.fixture(scope="session") diff --git a/server/tests/utils/test_convert.py b/server/tests/utils/test_convert.py index 5f284be..7dfe6a1 100644 --- a/server/tests/utils/test_convert.py +++ b/server/tests/utils/test_convert.py @@ -1,6 +1,10 @@ -from text_generation.utils.hub import download_weights, weight_hub_files, weight_files +from text_generation_server.utils.hub import ( + download_weights, + weight_hub_files, + weight_files, +) -from text_generation.utils.convert import convert_files +from text_generation_server.utils.convert import convert_files def test_convert_files(): diff --git a/server/tests/utils/test_hub.py b/server/tests/utils/test_hub.py index b312016..fac9a64 100644 --- a/server/tests/utils/test_hub.py +++ b/server/tests/utils/test_hub.py @@ -1,6 +1,6 @@ import pytest -from text_generation.utils.hub import ( +from text_generation_server.utils.hub import ( weight_hub_files, download_weights, weight_files, diff --git a/server/tests/utils/test_tokens.py b/server/tests/utils/test_tokens.py index 7eca482..3883ad9 100644 --- a/server/tests/utils/test_tokens.py +++ b/server/tests/utils/test_tokens.py @@ -1,4 +1,4 @@ -from text_generation.utils.tokens import ( +from text_generation_server.utils.tokens import ( StopSequenceCriteria, StoppingCriteria, FinishReason, diff --git a/server/text_generation/__init__.py b/server/text_generation_server/__init__.py similarity index 100% rename from server/text_generation/__init__.py rename to server/text_generation_server/__init__.py diff --git a/server/text_generation/cache.py b/server/text_generation_server/cache.py similarity index 90% rename from server/text_generation/cache.py rename to server/text_generation_server/cache.py index 5a3a8d3..72dc485 100644 --- a/server/text_generation/cache.py +++ b/server/text_generation_server/cache.py @@ -1,6 +1,6 @@ from typing import Dict, Optional, TypeVar -from text_generation.models.types import Batch +from text_generation_server.models.types import Batch B = TypeVar("B", bound=Batch) diff --git a/server/text_generation/cli.py b/server/text_generation_server/cli.py similarity index 94% rename from server/text_generation/cli.py rename to server/text_generation_server/cli.py index 678dce1..6308ef6 100644 --- a/server/text_generation/cli.py +++ b/server/text_generation_server/cli.py @@ -6,8 +6,8 @@ from pathlib import Path from loguru import logger from typing import Optional -from text_generation import server, utils -from text_generation.tracing import setup_tracing +from text_generation_server import server, utils +from text_generation_server.tracing import setup_tracing app = typer.Typer() @@ -42,7 +42,7 @@ def serve( logger.add( sys.stdout, format="{message}", - filter="text_generation", + filter="text_generation_server", level=logger_level, serialize=json_output, backtrace=True, @@ -68,7 +68,7 @@ def download_weights( logger.add( sys.stdout, format="{message}", - filter="text_generation", + filter="text_generation_server", level=logger_level, serialize=json_output, backtrace=True, diff --git a/server/text_generation/interceptor.py b/server/text_generation_server/interceptor.py similarity index 100% rename from server/text_generation/interceptor.py rename to server/text_generation_server/interceptor.py diff --git a/server/text_generation/models/__init__.py b/server/text_generation_server/models/__init__.py similarity index 79% rename from server/text_generation/models/__init__.py rename to server/text_generation_server/models/__init__.py index 386b7dc..0035c1c 100644 --- a/server/text_generation/models/__init__.py +++ b/server/text_generation_server/models/__init__.py @@ -3,14 +3,14 @@ import torch from transformers import AutoConfig from typing import Optional -from text_generation.models.model import Model -from text_generation.models.causal_lm import CausalLM -from text_generation.models.bloom import BLOOM, BLOOMSharded -from text_generation.models.seq2seq_lm import Seq2SeqLM -from text_generation.models.galactica import Galactica, GalacticaSharded -from text_generation.models.santacoder import SantaCoder -from text_generation.models.gpt_neox import GPTNeox, GPTNeoxSharded -from text_generation.models.t5 import T5Sharded +from text_generation_server.models.model import Model +from text_generation_server.models.causal_lm import CausalLM +from text_generation_server.models.bloom import BLOOM, BLOOMSharded +from text_generation_server.models.seq2seq_lm import Seq2SeqLM +from text_generation_server.models.galactica import Galactica, GalacticaSharded +from text_generation_server.models.santacoder import SantaCoder +from text_generation_server.models.gpt_neox import GPTNeox, GPTNeoxSharded +from text_generation_server.models.t5 import T5Sharded __all__ = [ "Model", diff --git a/server/text_generation/models/bloom.py b/server/text_generation_server/models/bloom.py similarity index 97% rename from server/text_generation/models/bloom.py rename to server/text_generation_server/models/bloom.py index 83a0d63..0d83abe 100644 --- a/server/text_generation/models/bloom.py +++ b/server/text_generation_server/models/bloom.py @@ -17,10 +17,10 @@ from transformers.models.bloom.parallel_layers import ( TensorParallelRowLinear, ) -from text_generation.models import CausalLM -from text_generation.models.causal_lm import CausalLMBatch -from text_generation.pb import generate_pb2 -from text_generation.utils import ( +from text_generation_server.models import CausalLM +from text_generation_server.models.causal_lm import CausalLMBatch +from text_generation_server.pb import generate_pb2 +from text_generation_server.utils import ( initialize_torch_distributed, weight_files, ) diff --git a/server/text_generation/models/causal_lm.py b/server/text_generation_server/models/causal_lm.py similarity index 98% rename from server/text_generation/models/causal_lm.py rename to server/text_generation_server/models/causal_lm.py index 23c94dd..4cfc15b 100644 --- a/server/text_generation/models/causal_lm.py +++ b/server/text_generation_server/models/causal_lm.py @@ -5,10 +5,15 @@ from opentelemetry import trace from transformers import AutoTokenizer, AutoModelForCausalLM, PreTrainedTokenizerBase from typing import Optional, Tuple, List, Type -from text_generation.models import Model -from text_generation.models.types import Batch, PrefillTokens, Generation, GeneratedText -from text_generation.pb import generate_pb2 -from text_generation.utils import NextTokenChooser, StoppingCriteria, Sampling +from text_generation_server.models import Model +from text_generation_server.models.types import ( + Batch, + PrefillTokens, + Generation, + GeneratedText, +) +from text_generation_server.pb import generate_pb2 +from text_generation_server.utils import NextTokenChooser, StoppingCriteria, Sampling tracer = trace.get_tracer(__name__) diff --git a/server/text_generation/models/galactica.py b/server/text_generation_server/models/galactica.py similarity index 98% rename from server/text_generation/models/galactica.py rename to server/text_generation_server/models/galactica.py index 9a71c5d..b4d1c55 100644 --- a/server/text_generation/models/galactica.py +++ b/server/text_generation_server/models/galactica.py @@ -18,10 +18,10 @@ from transformers.models.opt.parallel_layers import ( TensorParallelRowLinear, ) -from text_generation.models import CausalLM -from text_generation.pb import generate_pb2 -from text_generation.models.causal_lm import CausalLMBatch -from text_generation.utils import ( +from text_generation_server.models import CausalLM +from text_generation_server.pb import generate_pb2 +from text_generation_server.models.causal_lm import CausalLMBatch +from text_generation_server.utils import ( NextTokenChooser, StoppingCriteria, initialize_torch_distributed, diff --git a/server/text_generation/models/gpt_neox.py b/server/text_generation_server/models/gpt_neox.py similarity index 99% rename from server/text_generation/models/gpt_neox.py rename to server/text_generation_server/models/gpt_neox.py index 0197f97..5e1960f 100644 --- a/server/text_generation/models/gpt_neox.py +++ b/server/text_generation_server/models/gpt_neox.py @@ -16,8 +16,8 @@ from transformers.models.gpt_neox.parallel_layers import ( TensorParallelRowLinear, ) -from text_generation.models import CausalLM -from text_generation.utils import ( +from text_generation_server.models import CausalLM +from text_generation_server.utils import ( initialize_torch_distributed, weight_files, ) diff --git a/server/text_generation/models/model.py b/server/text_generation_server/models/model.py similarity index 95% rename from server/text_generation/models/model.py rename to server/text_generation_server/models/model.py index 09fa6a2..e0ce668 100644 --- a/server/text_generation/models/model.py +++ b/server/text_generation_server/models/model.py @@ -4,7 +4,7 @@ from abc import ABC, abstractmethod from typing import List, Tuple, Optional, TypeVar, Type from transformers import PreTrainedTokenizerBase -from text_generation.models.types import Batch, GeneratedText +from text_generation_server.models.types import Batch, GeneratedText B = TypeVar("B", bound=Batch) diff --git a/server/text_generation/models/santacoder.py b/server/text_generation_server/models/santacoder.py similarity index 97% rename from server/text_generation/models/santacoder.py rename to server/text_generation_server/models/santacoder.py index 5d271c8..fe15cde 100644 --- a/server/text_generation/models/santacoder.py +++ b/server/text_generation_server/models/santacoder.py @@ -4,7 +4,7 @@ import torch.distributed from typing import Optional, List from transformers import AutoTokenizer, AutoModelForCausalLM -from text_generation.models import CausalLM +from text_generation_server.models import CausalLM FIM_PREFIX = "" FIM_MIDDLE = "" diff --git a/server/text_generation/models/seq2seq_lm.py b/server/text_generation_server/models/seq2seq_lm.py similarity index 97% rename from server/text_generation/models/seq2seq_lm.py rename to server/text_generation_server/models/seq2seq_lm.py index 4b88bae..73a1087 100644 --- a/server/text_generation/models/seq2seq_lm.py +++ b/server/text_generation_server/models/seq2seq_lm.py @@ -5,10 +5,15 @@ from opentelemetry import trace from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, PreTrainedTokenizerBase from typing import Optional, Tuple, List, Type -from text_generation.models import Model -from text_generation.models.types import GeneratedText, Batch, Generation, PrefillTokens -from text_generation.pb import generate_pb2 -from text_generation.utils import NextTokenChooser, StoppingCriteria, Sampling +from text_generation_server.models import Model +from text_generation_server.models.types import ( + GeneratedText, + Batch, + Generation, + PrefillTokens, +) +from text_generation_server.pb import generate_pb2 +from text_generation_server.utils import NextTokenChooser, StoppingCriteria, Sampling tracer = trace.get_tracer(__name__) @@ -45,7 +50,7 @@ class Seq2SeqLMBatch(Batch): padding_right_offset: int def to_pb(self) -> generate_pb2.Batch: - """Convert a Seq2SeqLMBatch to a text_generation.v1.Batch protobuf""" + """Convert a Seq2SeqLMBatch to a text_generation_server.v1.Batch protobuf""" return generate_pb2.Batch( id=self.batch_id, requests=self.requests, @@ -59,7 +64,7 @@ class Seq2SeqLMBatch(Batch): tokenizer: PreTrainedTokenizerBase, device: torch.device, ) -> "Seq2SeqLMBatch": - """Convert a text_generation.v1.Batch protobuf to a Seq2SeqLMBatch""" + """Convert a text_generation_server.v1.Batch protobuf to a Seq2SeqLMBatch""" inputs = [] next_token_choosers = [] stopping_criterias = [] diff --git a/server/text_generation/models/t5.py b/server/text_generation_server/models/t5.py similarity index 98% rename from server/text_generation/models/t5.py rename to server/text_generation_server/models/t5.py index 5550753..cb4f7f2 100644 --- a/server/text_generation/models/t5.py +++ b/server/text_generation_server/models/t5.py @@ -16,8 +16,8 @@ from transformers.models.t5.parallel_layers import ( TensorParallelRowLinear, ) -from text_generation.models import Seq2SeqLM -from text_generation.utils import ( +from text_generation_server.models import Seq2SeqLM +from text_generation_server.utils import ( initialize_torch_distributed, weight_files, ) diff --git a/server/text_generation/models/types.py b/server/text_generation_server/models/types.py similarity index 95% rename from server/text_generation/models/types.py rename to server/text_generation_server/models/types.py index a3fbd6e..93c3b9d 100644 --- a/server/text_generation/models/types.py +++ b/server/text_generation_server/models/types.py @@ -6,8 +6,8 @@ from typing import List, Optional from transformers import PreTrainedTokenizerBase -from text_generation.pb import generate_pb2 -from text_generation.pb.generate_pb2 import FinishReason +from text_generation_server.pb import generate_pb2 +from text_generation_server.pb.generate_pb2 import FinishReason class Batch(ABC): diff --git a/server/text_generation/pb/.gitignore b/server/text_generation_server/pb/.gitignore similarity index 100% rename from server/text_generation/pb/.gitignore rename to server/text_generation_server/pb/.gitignore diff --git a/server/text_generation/server.py b/server/text_generation_server/server.py similarity index 92% rename from server/text_generation/server.py rename to server/text_generation_server/server.py index f3129cb..0b75c3c 100644 --- a/server/text_generation/server.py +++ b/server/text_generation_server/server.py @@ -9,11 +9,11 @@ from grpc_reflection.v1alpha import reflection from pathlib import Path from typing import List, Optional -from text_generation.cache import Cache -from text_generation.interceptor import ExceptionInterceptor -from text_generation.models import Model, get_model -from text_generation.pb import generate_pb2_grpc, generate_pb2 -from text_generation.tracing import UDSOpenTelemetryAioServerInterceptor +from text_generation_server.cache import Cache +from text_generation_server.interceptor import ExceptionInterceptor +from text_generation_server.models import Model, get_model +from text_generation_server.pb import generate_pb2_grpc, generate_pb2 +from text_generation_server.tracing import UDSOpenTelemetryAioServerInterceptor class TextGenerationService(generate_pb2_grpc.TextGenerationServiceServicer): diff --git a/server/text_generation/tracing.py b/server/text_generation_server/tracing.py similarity index 100% rename from server/text_generation/tracing.py rename to server/text_generation_server/tracing.py diff --git a/server/text_generation/utils/__init__.py b/server/text_generation_server/utils/__init__.py similarity index 71% rename from server/text_generation/utils/__init__.py rename to server/text_generation_server/utils/__init__.py index a390b71..50d6451 100644 --- a/server/text_generation/utils/__init__.py +++ b/server/text_generation_server/utils/__init__.py @@ -1,6 +1,6 @@ -from text_generation.utils.convert import convert_file, convert_files -from text_generation.utils.dist import initialize_torch_distributed -from text_generation.utils.hub import ( +from text_generation_server.utils.convert import convert_file, convert_files +from text_generation_server.utils.dist import initialize_torch_distributed +from text_generation_server.utils.hub import ( weight_files, weight_hub_files, download_weights, @@ -8,7 +8,7 @@ from text_generation.utils.hub import ( LocalEntryNotFoundError, RevisionNotFoundError, ) -from text_generation.utils.tokens import ( +from text_generation_server.utils.tokens import ( Greedy, NextTokenChooser, Sampling, diff --git a/server/text_generation/utils/convert.py b/server/text_generation_server/utils/convert.py similarity index 100% rename from server/text_generation/utils/convert.py rename to server/text_generation_server/utils/convert.py diff --git a/server/text_generation/utils/dist.py b/server/text_generation_server/utils/dist.py similarity index 100% rename from server/text_generation/utils/dist.py rename to server/text_generation_server/utils/dist.py diff --git a/server/text_generation/utils/hub.py b/server/text_generation_server/utils/hub.py similarity index 100% rename from server/text_generation/utils/hub.py rename to server/text_generation_server/utils/hub.py diff --git a/server/text_generation/utils/tokens.py b/server/text_generation_server/utils/tokens.py similarity index 96% rename from server/text_generation/utils/tokens.py rename to server/text_generation_server/utils/tokens.py index 797a563..41dfabd 100644 --- a/server/text_generation/utils/tokens.py +++ b/server/text_generation_server/utils/tokens.py @@ -11,9 +11,9 @@ from transformers import ( ) from typing import List, Tuple, Optional -from text_generation.pb import generate_pb2 -from text_generation.pb.generate_pb2 import FinishReason -from text_generation.utils.watermark import WatermarkLogitsProcessor +from text_generation_server.pb import generate_pb2 +from text_generation_server.pb.generate_pb2 import FinishReason +from text_generation_server.utils.watermark import WatermarkLogitsProcessor class Sampling: diff --git a/server/text_generation/utils/watermark.py b/server/text_generation_server/utils/watermark.py similarity index 100% rename from server/text_generation/utils/watermark.py rename to server/text_generation_server/utils/watermark.py