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chore: Update flashrank npm dependency to version 0.2.5 (#2781)

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# Description

Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.

## Checklist before requesting a review

Please delete options that are not relevant.

- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged

## Screenshots (if appropriate):
This commit is contained in:
Stan Girard 2024-06-28 18:09:17 +02:00 committed by GitHub
parent 6f0a757db2
commit 2e4b80138c
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GPG Key ID: B5690EEEBB952194
6 changed files with 78 additions and 137 deletions
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4
backend/Dockerfile
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@ -1,5 +1,5 @@
# Using a slim version for a smaller base image # Using a slim version for a smaller base image
FROM python:3.11.6-slim-bullseye@sha256:0c1fbb294096d842ad795ee232d783cab436c90b034210fe894f2bb2f2be7626 AS base FROM python:3.11.6-slim-bullseye
ARG DEV_MODE ARG DEV_MODE
ENV DEV_MODE=$DEV_MODE ENV DEV_MODE=$DEV_MODE
@ -73,7 +73,7 @@ COPY ./ci-migration.sh /code/
COPY supabase /code/supabase/ COPY supabase /code/supabase/
# Run install # Run install
RUN poetry install --no-root && \ RUN poetry install --no-root --with dev,test && \
playwright install --with-deps && \ playwright install --with-deps && \
rm -rf $POETRY_CACHE_DIR rm -rf $POETRY_CACHE_DIR

1
backend/api/pyproject.toml
View File

@ -75,7 +75,6 @@ ragas = "*"
datasets = "*" datasets = "*"
fpdf2 = "*" fpdf2 = "*"
unidecode = "*" unidecode = "*"
flashrank = "*"
langchain-cohere = "*" langchain-cohere = "*"
pyinstrument = "*" pyinstrument = "*"
playwright = "*" playwright = "*"

11
backend/api/quivr_api/modules/brain/rags/quivr_rag.py
View File

@ -1,5 +1,4 @@
import datetime import datetime
import os
from operator import itemgetter from operator import itemgetter
from typing import List, Optional from typing import List, Optional
from uuid import UUID from uuid import UUID
@ -8,7 +7,6 @@ from langchain.chains import ConversationalRetrievalChain
from langchain.llms.base import BaseLLM from langchain.llms.base import BaseLLM
from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate
from langchain.retrievers import ContextualCompressionRetriever from langchain.retrievers import ContextualCompressionRetriever
from langchain.retrievers.document_compressors import FlashrankRerank
from langchain.schema import format_document from langchain.schema import format_document
from langchain_cohere import CohereRerank from langchain_cohere import CohereRerank
from langchain_community.chat_models import ChatLiteLLM from langchain_community.chat_models import ChatLiteLLM
@ -299,10 +297,11 @@ class QuivrRAG(BaseModel):
# TODO(@aminediro) : Should be a class level attribute # TODO(@aminediro) : Should be a class level attribute
compressor = None compressor = None
if os.getenv("COHERE_API_KEY"): # TODO @stangirard fix
compressor = CohereRerank(top_n=20) # if os.getenv("COHERE_API_KEY"):
else: compressor = CohereRerank(top_n=20)
compressor = FlashrankRerank(model="ms-marco-TinyBERT-L-2-v2", top_n=20) # else:
# compressor = FlashrankRerank(model="ms-marco-TinyBERT-L-2-v2", top_n=20)
retriever_doc = self.get_retriever() retriever_doc = self.get_retriever()
compression_retriever = ContextualCompressionRetriever( compression_retriever = ContextualCompressionRetriever(

19
backend/api/quivr_api/packages/quivr_core/quivr_rag.py
View File

@ -1,11 +1,8 @@
import logging import logging
import os
from operator import itemgetter from operator import itemgetter
from typing import AsyncGenerator from typing import AsyncGenerator
from flashrank import Ranker
from langchain.retrievers import ContextualCompressionRetriever from langchain.retrievers import ContextualCompressionRetriever
from langchain.retrievers.document_compressors.flashrank_rerank import FlashrankRerank
from langchain_cohere import CohereRerank from langchain_cohere import CohereRerank
from langchain_community.chat_models import ChatLiteLLM from langchain_community.chat_models import ChatLiteLLM
from langchain_core.messages.ai import AIMessageChunk from langchain_core.messages.ai import AIMessageChunk
@ -13,7 +10,6 @@ from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import RunnableLambda, RunnablePassthrough from langchain_core.runnables import RunnableLambda, RunnablePassthrough
from langchain_core.vectorstores import VectorStore from langchain_core.vectorstores import VectorStore
from langchain_openai import ChatOpenAI from langchain_openai import ChatOpenAI
from quivr_api.modules.knowledge.entity.knowledge import Knowledge from quivr_api.modules.knowledge.entity.knowledge import Knowledge
from quivr_api.packages.quivr_core.config import RAGConfig from quivr_api.packages.quivr_core.config import RAGConfig
from quivr_api.packages.quivr_core.models import ( from quivr_api.packages.quivr_core.models import (
@ -59,14 +55,13 @@ class QuivrQARAG:
def _create_reranker(self): def _create_reranker(self):
# TODO: reranker config # TODO: reranker config
if os.getenv("COHERE_API_KEY"): compressor = CohereRerank(top_n=20)
compressor = CohereRerank(top_n=20) # else:
else: # ranker_model_name = "ms-marco-TinyBERT-L-2-v2"
ranker_model_name = "ms-marco-TinyBERT-L-2-v2" # flashrank_client = Ranker(model_name=ranker_model_name)
flashrank_client = Ranker(model_name=ranker_model_name) # compressor = FlashrankRerank(
compressor = FlashrankRerank( # client=flashrank_client, model=ranker_model_name, top_n=20
client=flashrank_client, model=ranker_model_name, top_n=20 # ) # TODO @stangirard fix
)
return compressor return compressor
# TODO : refactor and simplify # TODO : refactor and simplify

20
backend/core/quivr_core/quivr_rag.py
View File

@ -1,11 +1,8 @@
import logging import logging
import os
from operator import itemgetter from operator import itemgetter
from typing import AsyncGenerator from typing import AsyncGenerator
from flashrank import Ranker
from langchain.retrievers import ContextualCompressionRetriever from langchain.retrievers import ContextualCompressionRetriever
from langchain.retrievers.document_compressors.flashrank_rerank import FlashrankRerank
from langchain_cohere import CohereRerank from langchain_cohere import CohereRerank
from langchain_community.chat_models import ChatLiteLLM from langchain_community.chat_models import ChatLiteLLM
from langchain_core.messages.ai import AIMessageChunk from langchain_core.messages.ai import AIMessageChunk
@ -55,14 +52,15 @@ class QuivrQARAG:
def _create_reranker(self): def _create_reranker(self):
# TODO: reranker config # TODO: reranker config
if os.getenv("COHERE_API_KEY"): # if os.getenv("COHERE_API_KEY"):
compressor = CohereRerank(top_n=20) compressor = CohereRerank(top_n=20)
else: # else:
ranker_model_name = "ms-marco-TinyBERT-L-2-v2" # ranker_model_name = "ms-marco-TinyBERT-L-2-v2"
flashrank_client = Ranker(model_name=ranker_model_name) # flashrank_client = Ranker(model_name=ranker_model_name)
compressor = FlashrankRerank( # compressor = FlashrankRerank(
client=flashrank_client, model=ranker_model_name, top_n=20 # client=flashrank_client, model=ranker_model_name, top_n=20
) # )
# TODO @stangirard fix
return compressor return compressor
# TODO : refactor and simplify # TODO : refactor and simplify

160
backend/poetry.lock generated
View File

@ -402,17 +402,17 @@ uvloop = ["uvloop (>=0.15.2)"]
[[package]] [[package]]
name = "boto3" name = "boto3"
version = "1.34.134" version = "1.34.135"
description = "The AWS SDK for Python" description = "The AWS SDK for Python"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
{file = "boto3-1.34.134-py3-none-any.whl", hash = "sha256:342782c02ff077aae118c9c61179eed95c585831fba666baacc5588ff04aa6e1"}, {file = "boto3-1.34.135-py3-none-any.whl", hash = "sha256:6f5d7a20afbe45e3f7c6b5e96071752d36c3942535b1f7924964f1fdf25376a7"},
{file = "boto3-1.34.134.tar.gz", hash = "sha256:f6d6e5b0c9ab022a75373fa16c01f0cd54bc1bb64ef3b6ac64ac7cedd56cbe9c"}, {file = "boto3-1.34.135.tar.gz", hash = "sha256:344f635233c85dbb509b87638232ff9132739f90bb5e6bf01fa0e0a521a9107e"},
] ]
[package.dependencies] [package.dependencies]
botocore = ">=1.34.134,<1.35.0" botocore = ">=1.34.135,<1.35.0"
jmespath = ">=0.7.1,<2.0.0" jmespath = ">=0.7.1,<2.0.0"
s3transfer = ">=0.10.0,<0.11.0" s3transfer = ">=0.10.0,<0.11.0"
@ -421,13 +421,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
[[package]] [[package]]
name = "botocore" name = "botocore"
version = "1.34.134" version = "1.34.135"
description = "Low-level, data-driven core of boto 3." description = "Low-level, data-driven core of boto 3."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
{file = "botocore-1.34.134-py3-none-any.whl", hash = "sha256:45219e00639755f92569b29f8f279d5dde721494791412c1f7026a3779e8d9f4"}, {file = "botocore-1.34.135-py3-none-any.whl", hash = "sha256:3aa9e85e7c479babefb5a590e844435449df418085f3c74d604277bc52dc3109"},
{file = "botocore-1.34.134.tar.gz", hash = "sha256:e29c299599426ed16dd2d4c1e20eef784f96b15e1850ebbc59a3250959285b95"}, {file = "botocore-1.34.135.tar.gz", hash = "sha256:2e72f37072f75cb1391fca9d7a4c32cecb52a3557d62431d0f59d5311dc7d0cf"},
] ]
[package.dependencies] [package.dependencies]
@ -1186,17 +1186,6 @@ files = [
{file = "dirtyjson-1.0.8.tar.gz", hash = "sha256:90ca4a18f3ff30ce849d100dcf4a003953c79d3a2348ef056f1d9c22231a25fd"}, {file = "dirtyjson-1.0.8.tar.gz", hash = "sha256:90ca4a18f3ff30ce849d100dcf4a003953c79d3a2348ef056f1d9c22231a25fd"},
] ]
[[package]]
name = "diskcache"
version = "5.6.3"
description = "Disk Cache -- Disk and file backed persistent cache."
optional = false
python-versions = ">=3"
files = [
{file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
{file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
]
[[package]] [[package]]
name = "distlib" name = "distlib"
version = "0.3.8" version = "0.3.8"
@ -1634,25 +1623,6 @@ flake8 = ">=3"
[package.extras] [package.extras]
develop = ["build", "twine"] develop = ["build", "twine"]
[[package]]
name = "flashrank"
version = "0.2.6"
description = "Ultra lite & Super fast SoTA cross-encoder based re-ranking for your search & retrieval pipelines."
optional = false
python-versions = ">=3.6"
files = [
{file = "FlashRank-0.2.6-py3-none-any.whl", hash = "sha256:afe3a8db9909b375b7a0805ae653e8ec8beaf0cf0b3ea908250ff05b67dbe953"},
{file = "FlashRank-0.2.6.tar.gz", hash = "sha256:46c3763d23f5de6fa8d11df699adef2578168686b724b5adc873fe5ee4525822"},
]
[package.dependencies]
llama-cpp-python = "0.2.76"
numpy = "*"
onnxruntime = "*"
requests = "*"
tokenizers = "*"
tqdm = "*"
[[package]] [[package]]
name = "flatbuffers" name = "flatbuffers"
version = "24.3.25" version = "24.3.25"
@ -1947,13 +1917,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
[[package]] [[package]]
name = "google-api-python-client" name = "google-api-python-client"
version = "2.134.0" version = "2.135.0"
description = "Google API Client Library for Python" description = "Google API Client Library for Python"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "google-api-python-client-2.134.0.tar.gz", hash = "sha256:4a8f0bea651a212997cc83c0f271fc86f80ef93d1cee9d84de7dfaeef2a858b6"}, {file = "google-api-python-client-2.135.0.tar.gz", hash = "sha256:b552a28123ed95493035698db80e8ed78c9106a8b422e63a175150b9b55b704e"},
{file = "google_api_python_client-2.134.0-py2.py3-none-any.whl", hash = "sha256:ba05d60f6239990b7994f6328f17bb154c602d31860fb553016dc9f8ce886945"}, {file = "google_api_python_client-2.135.0-py2.py3-none-any.whl", hash = "sha256:91742fa4c779d48456c0256ef346fa1cc185ba427176d3277e35141fa3268026"},
] ]
[package.dependencies] [package.dependencies]
@ -2559,13 +2529,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
[[package]] [[package]]
name = "ipython" name = "ipython"
version = "8.25.0" version = "8.26.0"
description = "IPython: Productive Interactive Computing" description = "IPython: Productive Interactive Computing"
optional = false optional = false
python-versions = ">=3.10" python-versions = ">=3.10"
files = [ files = [
{file = "ipython-8.25.0-py3-none-any.whl", hash = "sha256:53eee7ad44df903a06655871cbab66d156a051fd86f3ec6750470ac9604ac1ab"}, {file = "ipython-8.26.0-py3-none-any.whl", hash = "sha256:e6b347c27bdf9c32ee9d31ae85defc525755a1869f14057e900675b9e8d6e6ff"},
{file = "ipython-8.25.0.tar.gz", hash = "sha256:c6ed726a140b6e725b911528f80439c534fac915246af3efc39440a6b0f9d716"}, {file = "ipython-8.26.0.tar.gz", hash = "sha256:1cec0fbba8404af13facebe83d04436a7434c7400e59f47acf467c64abd0956c"},
] ]
[package.dependencies] [package.dependencies]
@ -2591,7 +2561,7 @@ nbformat = ["nbformat"]
notebook = ["ipywidgets", "notebook"] notebook = ["ipywidgets", "notebook"]
parallel = ["ipyparallel"] parallel = ["ipyparallel"]
qtconsole = ["qtconsole"] qtconsole = ["qtconsole"]
test = ["pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"] test = ["packaging", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"]
test-extra = ["curio", "ipython[test]", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "trio"] test-extra = ["curio", "ipython[test]", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "trio"]
[[package]] [[package]]
@ -3061,18 +3031,18 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
[[package]] [[package]]
name = "langchain-openai" name = "langchain-openai"
version = "0.1.10" version = "0.1.11"
description = "An integration package connecting OpenAI and LangChain" description = "An integration package connecting OpenAI and LangChain"
optional = false optional = false
python-versions = "<4.0,>=3.8.1" python-versions = "<4.0,>=3.8.1"
files = [ files = [
{file = "langchain_openai-0.1.10-py3-none-any.whl", hash = "sha256:62eb000980eb45e4f16c88acdbaeccf3d59266554b0dd3ce6bebea1bbe8143dd"}, {file = "langchain_openai-0.1.11-py3-none-any.whl", hash = "sha256:12676e02846db63938ed40177d3271c8419a0659023afaee6da42518a0a28630"},
{file = "langchain_openai-0.1.10.tar.gz", hash = "sha256:30f881f8ccaec28c054759837c41fd2a2264fcc5564728ce12e1715891a9ce3c"}, {file = "langchain_openai-0.1.11.tar.gz", hash = "sha256:a5901bfee091060b7915fd6de6fd98aa429544de8cab51ac9b13ba484d9caffb"},
] ]
[package.dependencies] [package.dependencies]
langchain-core = ">=0.2.2,<0.3" langchain-core = ">=0.2.2,<0.3"
openai = ">=1.26.0,<2.0.0" openai = ">=1.32.0,<2.0.0"
tiktoken = ">=0.7,<1" tiktoken = ">=0.7,<1"
[[package]] [[package]]
@ -3129,13 +3099,13 @@ openai = ["openai (>=0.27.8)"]
[[package]] [[package]]
name = "langgraph" name = "langgraph"
version = "0.1.2" version = "0.1.3"
description = "Building stateful, multi-actor applications with LLMs" description = "Building stateful, multi-actor applications with LLMs"
optional = false optional = false
python-versions = "<4.0,>=3.9.0" python-versions = "<4.0,>=3.9.0"
files = [ files = [
{file = "langgraph-0.1.2-py3-none-any.whl", hash = "sha256:92ca172839e11f8ed166a9d31ad1946a5d657430009a47bf4ba9d03cb4ef0810"}, {file = "langgraph-0.1.3-py3-none-any.whl", hash = "sha256:4d12b16f57a47763796c78a7e55a70ce1bd84d9989d064d63c1819370af6f3a8"},
{file = "langgraph-0.1.2.tar.gz", hash = "sha256:2a90df777afc920a777b854773d4ce77d44b2b70691481c6fb5f2bca69564944"}, {file = "langgraph-0.1.3.tar.gz", hash = "sha256:bc6cd90d6cecfa67ae4e807b226362c057e94d5e0832f490917ff1a872760775"},
] ]
[package.dependencies] [package.dependencies]
@ -3196,13 +3166,13 @@ tesseract = ["pytesseract"]
[[package]] [[package]]
name = "litellm" name = "litellm"
version = "1.40.28" version = "1.40.29"
description = "Library to easily interface with LLM API providers" description = "Library to easily interface with LLM API providers"
optional = false optional = false
python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8" python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
files = [ files = [
{file = "litellm-1.40.28-py3-none-any.whl", hash = "sha256:aa6d59390f24d1b1168a202b966249f9f5f93d08deba38ed9528654544065e96"}, {file = "litellm-1.40.29-py3-none-any.whl", hash = "sha256:f541c6a868e62a9018d1502a2043d9e3a669833a6a4ed4946635eec26329540a"},
{file = "litellm-1.40.28.tar.gz", hash = "sha256:08fdfcb01715006f9dadb8d05b94143f782e08d1944e5691d9faf20300e62739"}, {file = "litellm-1.40.29.tar.gz", hash = "sha256:167357fcfe33813bf3410c5f13058c7d8ca39a38a476a4ddb80ffd3c18dab770"},
] ]
[package.dependencies] [package.dependencies]
@ -3237,28 +3207,6 @@ files = [
httpx = ">=0.20.0" httpx = ">=0.20.0"
pydantic = ">=1.10" pydantic = ">=1.10"
[[package]]
name = "llama-cpp-python"
version = "0.2.76"
description = "Python bindings for the llama.cpp library"
optional = false
python-versions = ">=3.8"
files = [
{file = "llama_cpp_python-0.2.76.tar.gz", hash = "sha256:a4e2ab6b74dc87f565a21e4f1617c030f92d5b341375d7173876d238613a50ab"},
]
[package.dependencies]
diskcache = ">=5.6.1"
jinja2 = ">=2.11.3"
numpy = ">=1.20.0"
typing-extensions = ">=4.5.0"
[package.extras]
all = ["llama_cpp_python[dev,server,test]"]
dev = ["black (>=23.3.0)", "httpx (>=0.24.1)", "mkdocs (>=1.4.3)", "mkdocs-material (>=9.1.18)", "mkdocstrings[python] (>=0.22.0)", "pytest (>=7.4.0)", "twine (>=4.0.2)"]
server = ["PyYAML (>=5.1)", "fastapi (>=0.100.0)", "pydantic-settings (>=2.0.1)", "sse-starlette (>=1.6.1)", "starlette-context (>=0.3.6,<0.4)", "uvicorn (>=0.22.0)"]
test = ["httpx (>=0.24.1)", "pytest (>=7.4.0)", "scipy (>=1.10)"]
[[package]] [[package]]
name = "llama-index" name = "llama-index"
version = "0.10.50" version = "0.10.50"
@ -4445,6 +4393,7 @@ description = "Nvidia JIT LTO Library"
optional = false optional = false
python-versions = ">=3" python-versions = ">=3"
files = [ files = [
{file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_aarch64.whl", hash = "sha256:004186d5ea6a57758fd6d57052a123c73a4815adf365eb8dd6a85c9eaa7535ff"},
{file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl", hash = "sha256:d9714f27c1d0f0895cd8915c07a87a1d0029a0aa36acaf9156952ec2a8a12189"}, {file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl", hash = "sha256:d9714f27c1d0f0895cd8915c07a87a1d0029a0aa36acaf9156952ec2a8a12189"},
{file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-win_amd64.whl", hash = "sha256:c3401dc8543b52d3a8158007a0c1ab4e9c768fcbd24153a48c86972102197ddd"}, {file = "nvidia_nvjitlink_cu12-12.5.40-py3-none-win_amd64.whl", hash = "sha256:c3401dc8543b52d3a8158007a0c1ab4e9c768fcbd24153a48c86972102197ddd"},
] ]
@ -4590,13 +4539,13 @@ sympy = "*"
[[package]] [[package]]
name = "openai" name = "openai"
version = "1.35.5" version = "1.35.7"
description = "The official Python library for the openai API" description = "The official Python library for the openai API"
optional = false optional = false
python-versions = ">=3.7.1" python-versions = ">=3.7.1"
files = [ files = [
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[package.dependencies] [package.dependencies]
@ -4635,13 +4584,13 @@ numpy = [
[[package]] [[package]]
name = "openpyxl" name = "openpyxl"
version = "3.1.4" version = "3.1.5"
description = "A Python library to read/write Excel 2010 xlsx/xlsm files" description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
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{file = "openpyxl-3.1.4.tar.gz", hash = "sha256:8d2c8adf5d20d6ce8f9bca381df86b534835e974ed0156dacefa76f68c1d69fb"}, {file = "openpyxl-3.1.5.tar.gz", hash = "sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050"},
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[package.dependencies] [package.dependencies]
@ -6497,7 +6446,6 @@ datasets = "*"
docx2txt = "*" docx2txt = "*"
duckduckgo-search = "*" duckduckgo-search = "*"
fastapi = "*" fastapi = "*"
flashrank = "*"
flower = "*" flower = "*"
fpdf2 = "*" fpdf2 = "*"
gitpython = "*" gitpython = "*"
@ -7171,13 +7119,13 @@ test = ["Cython", "array-api-strict", "asv", "gmpy2", "hypothesis (>=6.30)", "me
[[package]] [[package]]
name = "sentry-sdk" name = "sentry-sdk"
version = "2.7.0" version = "2.7.1"
description = "Python client for Sentry (https://sentry.io)" description = "Python client for Sentry (https://sentry.io)"
optional = false optional = false
python-versions = ">=3.6" python-versions = ">=3.6"
files = [ files = [
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@ -7218,7 +7166,7 @@ sanic = ["sanic (>=0.8)"]
sqlalchemy = ["sqlalchemy (>=1.2)"] sqlalchemy = ["sqlalchemy (>=1.2)"]
starlette = ["starlette (>=0.19.1)"] starlette = ["starlette (>=0.19.1)"]
starlite = ["starlite (>=1.48)"] starlite = ["starlite (>=1.48)"]
tornado = ["tornado (>=5)"] tornado = ["tornado (>=6)"]
[[package]] [[package]]
name = "setuptools" name = "setuptools"
@ -7389,13 +7337,13 @@ sqlcipher = ["sqlcipher3_binary"]
[[package]] [[package]]
name = "sqlglot" name = "sqlglot"
version = "25.3.3" version = "25.4.0"
description = "An easily customizable SQL parser and transpiler" description = "An easily customizable SQL parser and transpiler"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "sqlglot-25.3.3-py3-none-any.whl", hash = "sha256:678adad59a01ce58a7f33463b907dcdb43a0309caa5d55d6ac0af33acf698494"}, {file = "sqlglot-25.4.0-py3-none-any.whl", hash = "sha256:c8eb1b45ff7e3382639012aca050a3d40c373049c2d2d47393bf23666135c8bb"},
{file = "sqlglot-25.3.3.tar.gz", hash = "sha256:6b9a4c740fb8c78509eb3f51ab1d79f7c4ab3dc9d274251007acdd85faf4aeeb"}, {file = "sqlglot-25.4.0.tar.gz", hash = "sha256:12f198afd0b5d5722be9eecb1f364e4e01cb63935086f1b3af1b333b22b78254"},
] ]
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@ -8108,19 +8056,19 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
[[package]] [[package]]
name = "transformers" name = "transformers"
version = "4.41.2" version = "4.42.3"
description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow" description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
optional = false optional = false
python-versions = ">=3.8.0" python-versions = ">=3.8.0"
files = [ files = [
{file = "transformers-4.41.2-py3-none-any.whl", hash = "sha256:05555d20e43f808de1ef211ab64803cdb513170cef70d29a888b589caebefc67"}, {file = "transformers-4.42.3-py3-none-any.whl", hash = "sha256:a61a0df9609b7d69229d941b2fd857c841ba3043d6da503d0da1a4b133f65b92"},
{file = "transformers-4.41.2.tar.gz", hash = "sha256:80a4db216533d573e9cc7388646c31ed9480918feb7c55eb211249cb23567f87"}, {file = "transformers-4.42.3.tar.gz", hash = "sha256:7539873ff45809145265cbc94ea4619d2713c41ceaa277b692d8b0be3430f7eb"},
] ]
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filelock = "*" filelock = "*"
huggingface-hub = ">=0.23.0,<1.0" huggingface-hub = ">=0.23.2,<1.0"
numpy = ">=1.17" numpy = ">=1.17,<2.0"
packaging = ">=20.0" packaging = ">=20.0"
pyyaml = ">=5.1" pyyaml = ">=5.1"
regex = "!=2019.12.17" regex = "!=2019.12.17"
@ -8132,14 +8080,15 @@ tqdm = ">=4.27"
[package.extras] [package.extras]
accelerate = ["accelerate (>=0.21.0)"] accelerate = ["accelerate (>=0.21.0)"]
agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"] agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
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audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
benchmark = ["optimum-benchmark (>=0.2.0)"]
codecarbon = ["codecarbon (==1.2.0)"] codecarbon = ["codecarbon (==1.2.0)"]
deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"] deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"] dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"]
dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"] flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
ftfy = ["ftfy"] ftfy = ["ftfy"]
@ -8150,25 +8099,26 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"] onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"] onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
optuna = ["optuna"] optuna = ["optuna"]
quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"] quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.4.4)", "urllib3 (<2.0.0)"]
ray = ["ray[tune] (>=2.7.0)"] ray = ["ray[tune] (>=2.7.0)"]
retrieval = ["datasets (!=2.5.0)", "faiss-cpu"] retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
ruff = ["ruff (==0.4.4)"]
sagemaker = ["sagemaker (>=2.31.0)"] sagemaker = ["sagemaker (>=2.31.0)"]
sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"] sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
serving = ["fastapi", "pydantic", "starlette", "uvicorn"] serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
sigopt = ["sigopt"] sigopt = ["sigopt"]
sklearn = ["scikit-learn"] sklearn = ["scikit-learn"]
speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
timm = ["timm"] timm = ["timm (<=0.9.16)"]
tokenizers = ["tokenizers (>=0.19,<0.20)"] tokenizers = ["tokenizers (>=0.19,<0.20)"]
torch = ["accelerate (>=0.21.0)", "torch"] torch = ["accelerate (>=0.21.0)", "torch"]
torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"] torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
torchhub = ["filelock", "huggingface-hub (>=0.23.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"] torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17,<2.0)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
video = ["av (==9.2.0)", "decord (==0.6.0)"] video = ["av (==9.2.0)", "decord (==0.6.0)"]
vision = ["Pillow (>=10.0.1,<=15.0)"] vision = ["Pillow (>=10.0.1,<=15.0)"]