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@ -5480,7 +5480,7 @@ zfpy = ["zfpy (>=1.0.0)"]
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name = "numexpr"
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version = "2.8.5"
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description = "Fast numerical expression evaluator for NumPy"
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optional = false
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optional = true
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python-versions = ">=3.7"
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files = [
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{file = "numexpr-2.8.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:51f3ab160c3847ebcca93cd88f935a7802b54a01ab63fe93152994a64d7a6cf2"},
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@ -10666,7 +10666,7 @@ clarifai = ["clarifai"]
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cohere = ["cohere"]
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docarray = ["docarray"]
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embeddings = ["sentence-transformers"]
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extended-testing = ["amazon-textract-caller", "anthropic", "arxiv", "assemblyai", "atlassian-python-api", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "dashvector", "esprima", "faiss-cpu", "feedparser", "geopandas", "gitpython", "gql", "html2text", "jinja2", "jq", "lxml", "markdownify", "motor", "mwparserfromhell", "mwxml", "newspaper3k", "openai", "openai", "openapi-schema-pydantic", "pandas", "pdfminer-six", "pgvector", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "requests-toolbelt", "scikit-learn", "sqlite-vss", "streamlit", "sympy", "telethon", "timescale-vector", "tqdm", "xata", "xmltodict"]
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extended-testing = ["amazon-textract-caller", "anthropic", "arxiv", "assemblyai", "atlassian-python-api", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "dashvector", "esprima", "faiss-cpu", "feedparser", "geopandas", "gitpython", "gql", "html2text", "jinja2", "jq", "lxml", "markdownify", "motor", "mwparserfromhell", "mwxml", "newspaper3k", "numexpr", "openai", "openai", "openapi-schema-pydantic", "pandas", "pdfminer-six", "pgvector", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "requests-toolbelt", "scikit-learn", "sqlite-vss", "streamlit", "sympy", "telethon", "timescale-vector", "tqdm", "xata", "xmltodict"]
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javascript = ["esprima"]
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llms = ["clarifai", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "openlm", "torch", "transformers"]
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openai = ["openai", "tiktoken"]
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@ -10676,4 +10676,4 @@ text-helpers = ["chardet"]
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.8.1,<4.0"
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content-hash = "bb3019a7df3d22c5cd8d8c6a9a22effb86ca7e41e1d45d41db0b9d8173fac5ed"
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content-hash = "e8e9b8e119fb300c0caf889b7169421095a3888f20fd75d1e03a80ea16852146"
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