blob42
/
langchain
forked from Archives/langchain
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Harrison/pinecone hybrid update (#2742)

Browse Source 
Co-authored-by: acatav <39461369+acatav@users.noreply.github.com>
Co-authored-by: Amnon Catav <catav.amnon1@gmail.com>
fix_agent_callbacks
Harrison Chase 1 year ago committed by GitHub
parent 744c25cd0a
commit 507cee5ee5
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 311 additions and 455 deletions
Show Stats Download Patch File Download Diff File

156
docs/modules/indexes/retrievers/examples/pinecone_hybrid_search.ipynb
Unescape Escape View File

@ -1,6 +1,7 @@
{ {
"cells": [ "cells": [
{ {
"attachments": {},
"cell_type": "markdown", "cell_type": "markdown",
"id": "ab66dd43", "id": "ab66dd43",
"metadata": {}, "metadata": {},
@ -9,12 +10,12 @@
"\n", "\n",
"This notebook goes over how to use a retriever that under the hood uses Pinecone and Hybrid Search.\n", "This notebook goes over how to use a retriever that under the hood uses Pinecone and Hybrid Search.\n",
"\n", "\n",
"The logic of this retriever is largely taken from [this blog post](https://www.pinecone.io/learn/hybrid-search-intro/)" "The logic of this retriever is taken from [this documentaion](https://docs.pinecone.io/docs/hybrid-search)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 75,
"id": "393ac030", "id": "393ac030",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -31,43 +32,61 @@
] ]
}, },
{ {
"cell_type": "code", "attachments": {},
"execution_count": 3, "cell_type": "markdown",
"id": "15390796", "id": "95d5d7f9",
"metadata": {}, "metadata": {},
"outputs": [],
"source": [ "source": [
"import pinecone # !pip install pinecone-client\n", "You should only have to do this part once.\n",
"\n", "\n",
"pinecone.init(\n", "Note: it's important to make sure that the \"context\" field that holds the document text in the metadata is not indexed. Currently you need to specify explicitly the fields you do want to index. For more information checkout Pinecone's [docs](https://docs.pinecone.io/docs/manage-indexes#selective-metadata-indexing)."
" api_key=\"...\", # API key here\n",
" environment=\"...\" # find next to api key in console\n",
")\n",
"# choose a name for your index\n",
"index_name = \"...\""
] ]
}, },
{ {
"cell_type": "markdown", "cell_type": "code",
"id": "95d5d7f9", "execution_count": 76,
"id": "3b8f7697",
"metadata": {}, "metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"WhoAmIResponse(username='load', user_label='label', projectname='load-test')"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"You should only have to do this part once." "import os\n",
"import pinecone\n",
"\n",
"api_key = os.getenv(\"PINECONE_API_KEY\") or \"PINECONE_API_KEY\"\n",
"# find environment next to your API key in the Pinecone console\n",
"env = os.getenv(\"PINECONE_ENVIRONMENT\") or \"PINECONE_ENVIRONMENT\"\n",
"\n",
"index_name = \"langchain-pinecone-hybrid-search\"\n",
"\n",
"pinecone.init(api_key=api_key, enviroment=env)\n",
"pinecone.whoami()"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 77,
"id": "cfa3a8d8", "id": "cfa3a8d8",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"# create the index\n", " # create the index\n",
"pinecone.create_index(\n", "pinecone.create_index(\n",
" name = index_name,\n", " name = index_name,\n",
" dimension = 1536, # dimensionality of dense model\n", " dimension = 1536, # dimensionality of dense model\n",
" metric = \"dotproduct\",\n", " metric = \"dotproduct\", # sparse values supported only for dotproduct\n",
" pod_type = \"s1\"\n", " pod_type = \"s1\",\n",
" metadata_config={\"indexed\": []} # see explaination above\n",
")" ")"
] ]
}, },
@ -81,7 +100,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 78,
"id": "bcb3c8c2", "id": "bcb3c8c2",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -90,18 +109,19 @@
] ]
}, },
{ {
"attachments": {},
"cell_type": "markdown", "cell_type": "markdown",
"id": "dbc025d6", "id": "dbc025d6",
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Get embeddings and tokenizers\n", "## Get embeddings and sparse encoders\n",
"\n", "\n",
"Embeddings are used for the dense vectors, tokenizer is used for the sparse vector" "Embeddings are used for the dense vectors, tokenizer is used for the sparse vector"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 79,
"id": "2f63c911", "id": "2f63c911",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -110,19 +130,51 @@
"embeddings = OpenAIEmbeddings()" "embeddings = OpenAIEmbeddings()"
] ]
}, },
{
"attachments": {},
"cell_type": "markdown",
"id": "96bf8879",
"metadata": {},
"source": [
"To encode the text to sparse values you can either choose SPLADE or BM25. For out of domain tasks we recommend using BM25.\n",
"\n",
"For more information about the sparse encoders you can checkout pinecone-text library [docs](https://pinecone-io.github.io/pinecone-text/pinecone_text.html)."
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 80,
"id": "c3f030e5", "id": "c3f030e5",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"from transformers import BertTokenizerFast # !pip install transformers\n", "from pinecone_text.sparse import BM25Encoder\n",
"# or from pinecone_text.sparse import SpladeEncoder if you wish to work with SPLADE\n",
"\n", "\n",
"# load bert tokenizer from huggingface\n", "# use default tf-idf values\n",
"tokenizer = BertTokenizerFast.from_pretrained(\n", "bm25_encoder = BM25Encoder().default()"
" 'bert-base-uncased'\n", ]
")" },
{
"attachments": {},
"cell_type": "markdown",
"id": "23601ddb",
"metadata": {},
"source": [
"The above code is using default tfids values. It's highly recommended to fit the tf-idf values to your own corpus. You can do it as follow:\n",
"\n",
"```python\n",
"corpus = [\"foo\", \"bar\", \"world\", \"hello\"]\n",
"\n",
"# fit tf-idf values on your corpus\n",
"bm25_encoder.fit(corpus)\n",
"\n",
"# store the values to a json file\n",
"bm25_encoder.dump(\"bm25_values.json\")\n",
"\n",
"# load to your BM25Encoder object\n",
"bm25_encoder = BM25Encoder().load(\"bm25_values.json\")\n",
"```"
] ]
}, },
{ {
@ -137,12 +189,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 81,
"id": "ac77d835", "id": "ac77d835",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"retriever = PineconeHybridSearchRetriever(embeddings=embeddings, index=index, tokenizer=tokenizer)" "retriever = PineconeHybridSearchRetriever(embeddings=embeddings, sparse_encoder=bm25_encoder, index=index)"
] ]
}, },
{ {
@ -157,23 +209,16 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 82,
"id": "98b1c017", "id": "98b1c017",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "name": "stderr",
"application/vnd.jupyter.widget-view+json": { "output_type": "stream",
"model_id": "4d6f3ee7ca754d07a1a18d100d99e0cd", "text": [
"version_major": 2, "100%|██████████| 1/1 [00:02<00:00, 2.27s/it]\n"
"version_minor": 0 ]
},
"text/plain": [
" 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
} }
], ],
"source": [ "source": [
@ -192,7 +237,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": 83,
"id": "c0455218", "id": "c0455218",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -202,7 +247,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10, "execution_count": 84,
"id": "7dfa5c29", "id": "7dfa5c29",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -212,7 +257,7 @@
"Document(page_content='foo', metadata={})" "Document(page_content='foo', metadata={})"
] ]
}, },
"execution_count": 10, "execution_count": 84,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -220,19 +265,11 @@
"source": [ "source": [
"result[0]" "result[0]"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"id": "74bd9256",
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {
"kernelspec": { "kernelspec": {
"display_name": "Python 3 (ipykernel)", "display_name": ".venv",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
}, },
@ -246,7 +283,12 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.9.1" "version": "3.9.13"
},
"vscode": {
"interpreter": {
"hash": "7ec0d8babd8cabf695a1d94b1e586d626e046c9df609f6bad065d15d49f67f54"
}
} }
}, },
"nbformat": 4, "nbformat": 4,

101
langchain/retrievers/pinecone_hybrid_search.py
Unescape Escape View File

@ -1,32 +1,23 @@
"""Taken from: https://www.pinecone.io/learn/hybrid-search-intro/""" """Taken from: https://docs.pinecone.io/docs/hybrid-search"""
from collections import Counter import hashlib
from typing import Any, Dict, List, Tuple from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Extra from pydantic import BaseModel, Extra, root_validator
from langchain.embeddings.base import Embeddings from langchain.embeddings.base import Embeddings
from langchain.schema import BaseRetriever, Document from langchain.schema import BaseRetriever, Document
def build_dict(input_batch: List[List[int]]) -> List[Dict]: def hash_text(text: str) -> str:
# store a batch of sparse embeddings return str(hashlib.sha256(text.encode("utf-8")).hexdigest())
sparse_emb = []
# iterate through input batch
for token_ids in input_batch:
indices = []
values = []
# convert the input_ids list to a dictionary of key to frequency values
d = dict(Counter(token_ids))
for idx in d:
indices.append(idx)
values.append(d[idx])
sparse_emb.append({"indices": indices, "values": values})
# return sparse_emb list
return sparse_emb
def create_index( def create_index(
contexts: List[str], index: Any, embeddings: Embeddings, tokenizer: Any contexts: List[str],
index: Any,
embeddings: Embeddings,
sparse_encoder: Any,
ids: Optional[List[str]] = None,
) -> None: ) -> None:
batch_size = 32 batch_size = 32
_iterator = range(0, len(contexts), batch_size) _iterator = range(0, len(contexts), batch_size)
@ -37,28 +28,33 @@ def create_index(
except ImportError: except ImportError:
pass pass
if ids is None:
# create unique ids using hash of the text
ids = [hash_text(context) for context in contexts]
for i in _iterator: for i in _iterator:
# find end of batch # find end of batch
i_end = min(i + batch_size, len(contexts)) i_end = min(i + batch_size, len(contexts))
# extract batch # extract batch
context_batch = contexts[i:i_end] context_batch = contexts[i:i_end]
# create unique IDs batch_ids = ids[i:i_end]
ids = [str(x) for x in range(i, i_end)]
# add context passages as metadata # add context passages as metadata
meta = [{"context": context} for context in context_batch] meta = [{"context": context} for context in context_batch]
# create dense vectors # create dense vectors
dense_embeds = embeddings.embed_documents(context_batch) dense_embeds = embeddings.embed_documents(context_batch)
# create sparse vectors # create sparse vectors
sparse_embeds = generate_sparse_vectors(context_batch, tokenizer) sparse_embeds = sparse_encoder.encode_documents(context_batch)
for s in sparse_embeds: for s in sparse_embeds:
s["values"] = [float(s1) for s1 in s["values"]] s["values"] = [float(s1) for s1 in s["values"]]
vectors = [] vectors = []
# loop through the data and create dictionaries for upserts # loop through the data and create dictionaries for upserts
for _id, sparse, dense, metadata in zip(ids, sparse_embeds, dense_embeds, meta): for doc_id, sparse, dense, metadata in zip(
batch_ids, sparse_embeds, dense_embeds, meta
):
vectors.append( vectors.append(
{ {
"id": _id, "id": doc_id,
"sparse_values": sparse, "sparse_values": sparse,
"values": dense, "values": dense,
"metadata": metadata, "metadata": metadata,
@ -69,38 +65,10 @@ def create_index(
index.upsert(vectors) index.upsert(vectors)
def generate_sparse_vectors(context_batch: List[str], tokenizer: Any) -> List[Dict]:
# create batch of input_ids
inputs = tokenizer(
context_batch,
padding=True,
truncation=True,
max_length=512, # special_tokens=False
)["input_ids"]
# create sparse dictionaries
sparse_embeds = build_dict(inputs)
return sparse_embeds
def hybrid_scale(
dense: List[float], sparse: Dict, alpha: float
) -> Tuple[List[float], Dict]:
# check alpha value is in range
if alpha < 0 or alpha > 1:
raise ValueError("Alpha must be between 0 and 1")
# scale sparse and dense vectors to create hybrid search vecs
hsparse = {
"indices": sparse["indices"],
"values": [v * (1 - alpha) for v in sparse["values"]],
}
hdense = [v * alpha for v in dense]
return hdense, hsparse
class PineconeHybridSearchRetriever(BaseRetriever, BaseModel): class PineconeHybridSearchRetriever(BaseRetriever, BaseModel):
embeddings: Embeddings embeddings: Embeddings
sparse_encoder: Any
index: Any index: Any
tokenizer: Any
top_k: int = 4 top_k: int = 4
alpha: float = 0.5 alpha: float = 0.5
@ -110,15 +78,32 @@ class PineconeHybridSearchRetriever(BaseRetriever, BaseModel):
extra = Extra.forbid extra = Extra.forbid
arbitrary_types_allowed = True arbitrary_types_allowed = True
def add_texts(self, texts: List[str]) -> None: def add_texts(self, texts: List[str], ids: Optional[List[str]] = None) -> None:
create_index(texts, self.index, self.embeddings, self.tokenizer) create_index(texts, self.index, self.embeddings, self.sparse_encoder, ids=ids)
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key and python package exists in environment."""
try:
from pinecone_text.hybrid import hybrid_convex_scale # noqa:F401
from pinecone_text.sparse.base_sparse_encoder import (
BaseSparseEncoder, # noqa:F401
)
except ImportError:
raise ValueError(
"Could not import pinecone_text python package. "
"Please install it with `pip install pinecone_text`."
)
return values
def get_relevant_documents(self, query: str) -> List[Document]: def get_relevant_documents(self, query: str) -> List[Document]:
sparse_vec = generate_sparse_vectors([query], self.tokenizer)[0] from pinecone_text.hybrid import hybrid_convex_scale
sparse_vec = self.sparse_encoder.encode_queries(query)
# convert the question into a dense vector # convert the question into a dense vector
dense_vec = self.embeddings.embed_query(query) dense_vec = self.embeddings.embed_query(query)
# scale alpha with hybrid_scale # scale alpha with hybrid_scale
dense_vec, sparse_vec = hybrid_scale(dense_vec, sparse_vec, self.alpha) dense_vec, sparse_vec = hybrid_convex_scale(dense_vec, sparse_vec, self.alpha)
sparse_vec["values"] = [float(s1) for s1 in sparse_vec["values"]] sparse_vec["values"] = [float(s1) for s1 in sparse_vec["values"]]
# query pinecone with the query parameters # query pinecone with the query parameters
result = self.index.query( result = self.index.query(

501
poetry.lock generated
Unescape Escape View File

@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand. # This file is automatically @generated by Poetry and should not be changed by hand.
[[package]] [[package]]
name = "absl-py" name = "absl-py"
@ -1066,36 +1066,6 @@ pandas = ["pandas"]
sqlalchemy = ["sqlalchemy (>1.3.21,<1.4)"] sqlalchemy = ["sqlalchemy (>1.3.21,<1.4)"]
superset = ["apache-superset (>=1.4.1)"] superset = ["apache-superset (>=1.4.1)"]
[[package]]
name = "cmake"
version = "3.26.1"
description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "cmake-3.26.1-py2.py3-none-macosx_10_10_universal2.macosx_10_10_x86_64.macosx_11_0_arm64.macosx_11_0_universal2.whl", hash = "sha256:d8a7e0cc8677677a732aff3e3fd0ad64eeff43cac772614b03c436912247d0d8"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2010_i686.manylinux_2_12_i686.whl", hash = "sha256:f2f721f5aebe304c281ee4b1d2dfbf7f4a52fca003834b2b4a3ba838aeded63c"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:63a012b72836702eadfe4fba9642aeb17337f26861f4768e837053f40e98cb46"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2b72be88b7bfaa6ae59566cbb9d6a5553f19b2a8d14efa6ac0cf019a29860a1b"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:1278354f7210e22458aa9137d46a56da1f115a7b76ad2733f0bf6041fb40f1dc"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:de96a5522917fba0ab0da2d01d9dd9462fa80f365218bf27162d539c2335758f"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:449928ad7dfcd41e4dcff64c7d44f86557883c70577666a19e79e22d783bbbd0"},
{file = "cmake-3.26.1-py2.py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:19fa3e457afecf2803265f71652ef17c3f1d317173c330ba46767a0853d38fa0"},
{file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_aarch64.whl", hash = "sha256:43360650d60d177d979e4ad0a5f31afa286e6d88f5350f7a38c29d94514900eb"},
{file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_i686.whl", hash = "sha256:16aac10363bc926da5109a59ef8fe46ddcd7e3d421de61f871b35524eef2f1ae"},
{file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:e460ba5070be4dcac9613cb526a46db4e5fa19d8b909a8d8d5244c6cc3c777e1"},
{file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_s390x.whl", hash = "sha256:fd2ecc0899f7939a014bd906df85e8681bd63ce457de3ab0b5d9e369fa3bdf79"},
{file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:22781a23e274ba9bf380b970649654851c1b4b9d83b65fec12ee2e2e03b6ffc4"},
{file = "cmake-3.26.1-py2.py3-none-win32.whl", hash = "sha256:7b4e81de30ac1fb2f1eb5287063e140b53f376fd9ed7e2060c1c7b5917bd5f83"},
{file = "cmake-3.26.1-py2.py3-none-win_amd64.whl", hash = "sha256:90845b6c87a25be07e9220f67dd7f6c891c6ec14d764d37335218d97f9ea4520"},
{file = "cmake-3.26.1-py2.py3-none-win_arm64.whl", hash = "sha256:43bd96327e2631183bb4829ba20cb810e20b4b0c68f852fcd7082fbb5359d57c"},
{file = "cmake-3.26.1.tar.gz", hash = "sha256:4e0eb3c03dcf2d459f78d96cc85f7482476aeb1ae5ada65150b1db35c0f70cc7"},
]
[package.extras]
test = ["codecov (>=2.0.5)", "coverage (>=4.2)", "flake8 (>=3.0.4)", "path.py (>=11.5.0)", "pytest (>=3.0.3)", "pytest-cov (>=2.4.0)", "pytest-runner (>=2.9)", "pytest-virtualenv (>=1.7.0)", "scikit-build (>=0.10.0)", "setuptools (>=28.0.0)", "virtualenv (>=15.0.3)", "wheel"]
[[package]] [[package]]
name = "cohere" name = "cohere"
version = "3.10.0" version = "3.10.0"
@ -2415,14 +2385,14 @@ files = [
[[package]] [[package]]
name = "httpcore" name = "httpcore"
version = "0.16.3" version = "0.17.0"
description = "A minimal low-level HTTP client." description = "A minimal low-level HTTP client."
category = "main" category = "main"
optional = true optional = true
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "httpcore-0.16.3-py3-none-any.whl", hash = "sha256:da1fb708784a938aa084bde4feb8317056c55037247c787bd7e19eb2c2949dc0"}, {file = "httpcore-0.17.0-py3-none-any.whl", hash = "sha256:0fdfea45e94f0c9fd96eab9286077f9ff788dd186635ae61b312693e4d943599"},
{file = "httpcore-0.16.3.tar.gz", hash = "sha256:c5d6f04e2fc530f39e0c077e6a30caa53f1451096120f1f38b954afd0b17c0cb"}, {file = "httpcore-0.17.0.tar.gz", hash = "sha256:cc045a3241afbf60ce056202301b4d8b6af08845e3294055eb26b09913ef903c"},
] ]
[package.dependencies] [package.dependencies]
@ -2506,26 +2476,26 @@ test = ["Cython (>=0.29.24,<0.30.0)"]
[[package]] [[package]]
name = "httpx" name = "httpx"
version = "0.23.3" version = "0.24.0"
description = "The next generation HTTP client." description = "The next generation HTTP client."
category = "main" category = "main"
optional = true optional = true
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "httpx-0.23.3-py3-none-any.whl", hash = "sha256:a211fcce9b1254ea24f0cd6af9869b3d29aba40154e947d2a07bb499b3e310d6"}, {file = "httpx-0.24.0-py3-none-any.whl", hash = "sha256:447556b50c1921c351ea54b4fe79d91b724ed2b027462ab9a329465d147d5a4e"},
{file = "httpx-0.23.3.tar.gz", hash = "sha256:9818458eb565bb54898ccb9b8b251a28785dd4a55afbc23d0eb410754fe7d0f9"}, {file = "httpx-0.24.0.tar.gz", hash = "sha256:507d676fc3e26110d41df7d35ebd8b3b8585052450f4097401c9be59d928c63e"},
] ]
[package.dependencies] [package.dependencies]
certifi = "*" certifi = "*"
h2 = {version = ">=3,<5", optional = true, markers = "extra == \"http2\""} h2 = {version = ">=3,<5", optional = true, markers = "extra == \"http2\""}
httpcore = ">=0.15.0,<0.17.0" httpcore = ">=0.15.0,<0.18.0"
rfc3986 = {version = ">=1.3,<2", extras = ["idna2008"]} idna = "*"
sniffio = "*" sniffio = "*"
[package.extras] [package.extras]
brotli = ["brotli", "brotlicffi"] brotli = ["brotli", "brotlicffi"]
cli = ["click (>=8.0.0,<9.0.0)", "pygments (>=2.0.0,<3.0.0)", "rich (>=10,<13)"] cli = ["click (>=8.0.0,<9.0.0)", "pygments (>=2.0.0,<3.0.0)", "rich (>=10,<14)"]
http2 = ["h2 (>=3,<5)"] http2 = ["h2 (>=3,<5)"]
socks = ["socksio (>=1.0.0,<2.0.0)"] socks = ["socksio (>=1.0.0,<2.0.0)"]
@ -3375,17 +3345,6 @@ beautifulsoup4 = ">=4.8.1"
dnspython = ">=2.0" dnspython = ">=2.0"
requests = ">=2.20" requests = ">=2.20"
[[package]]
name = "lit"
version = "16.0.0"
description = "A Software Testing Tool"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "lit-16.0.0.tar.gz", hash = "sha256:3c4ac372122a1de4a88deb277b956f91b7209420a0bef683b1ab2d2b16dabe11"},
]
[[package]] [[package]]
name = "livereload" name = "livereload"
version = "2.6.3" version = "2.6.3"
@ -3404,14 +3363,14 @@ tornado = {version = "*", markers = "python_version > \"2.7\""}
[[package]] [[package]]
name = "loguru" name = "loguru"
version = "0.6.0" version = "0.7.0"
description = "Python logging made (stupidly) simple" description = "Python logging made (stupidly) simple"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.5" python-versions = ">=3.5"
files = [ files = [
{file = "loguru-0.6.0-py3-none-any.whl", hash = "sha256:4e2414d534a2ab57573365b3e6d0234dfb1d84b68b7f3b948e6fb743860a77c3"}, {file = "loguru-0.7.0-py3-none-any.whl", hash = "sha256:b93aa30099fa6860d4727f1b81f8718e965bb96253fa190fab2077aaad6d15d3"},
{file = "loguru-0.6.0.tar.gz", hash = "sha256:066bd06758d0a513e9836fd9c6b5a75bfb3fd36841f4b996bc60b547a309d41c"}, {file = "loguru-0.7.0.tar.gz", hash = "sha256:1612053ced6ae84d7959dd7d5e431a0532642237ec21f7fd83ac73fe539e03e1"},
] ]
[package.dependencies] [package.dependencies]
@ -3419,7 +3378,7 @@ colorama = {version = ">=0.3.4", markers = "sys_platform == \"win32\""}
win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""} win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
[package.extras] [package.extras]
dev = ["Sphinx (>=4.1.1)", "black (>=19.10b0)", "colorama (>=0.3.4)", "docutils (==0.16)", "flake8 (>=3.7.7)", "isort (>=5.1.1)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)", "tox (>=3.9.0)"] dev = ["Sphinx (==5.3.0)", "colorama (==0.4.5)", "colorama (==0.4.6)", "freezegun (==1.1.0)", "freezegun (==1.2.2)", "mypy (==v0.910)", "mypy (==v0.971)", "mypy (==v0.990)", "pre-commit (==3.2.1)", "pytest (==6.1.2)", "pytest (==7.2.1)", "pytest-cov (==2.12.1)", "pytest-cov (==4.0.0)", "pytest-mypy-plugins (==1.10.1)", "pytest-mypy-plugins (==1.9.3)", "sphinx-autobuild (==2021.3.14)", "sphinx-rtd-theme (==1.2.0)", "tox (==3.27.1)", "tox (==4.4.6)"]
[[package]] [[package]]
name = "lz4" name = "lz4"
@ -3690,6 +3649,51 @@ files = [
{file = "mistune-2.0.5.tar.gz", hash = "sha256:0246113cb2492db875c6be56974a7c893333bf26cd92891c85f63151cee09d34"}, {file = "mistune-2.0.5.tar.gz", hash = "sha256:0246113cb2492db875c6be56974a7c893333bf26cd92891c85f63151cee09d34"},
] ]
[[package]]
name = "mmh3"
version = "3.1.0"
description = "Python wrapper for MurmurHash (MurmurHash3), a set of fast and robust hash functions."
category = "main"
optional = false
python-versions = "*"
files = [
{file = "mmh3-3.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:16ee043b1bac040b4324b8baee39df9fdca480a560a6d74f2eef66a5009a234e"},
{file = "mmh3-3.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:04ac865319e5b36148a4b6cdf27f8bda091c47c4ab7b355d7f353dfc2b8a3cce"},
{file = "mmh3-3.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9e751f5433417a21c2060b0efa1afc67cfbe29977c867336148c8edb086fae70"},
{file = "mmh3-3.1.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bdb863b89c1b34e3681d4a3b15d424734940eb8036f3457cb35ef34fb87a503c"},
{file = "mmh3-3.1.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1230930fbf2faec4ddf5b76d0768ae73c102de173c301962bdd468177275adf9"},
{file = "mmh3-3.1.0-cp310-cp310-win32.whl", hash = "sha256:b8ed7a2361718795a1b519a08d05f44947a20b27e202b53946561a00dde669c1"},
{file = "mmh3-3.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:29e878e7467a000f34ab68c218ad7ad81312c0a94bc10df3c50a48bcad39dd83"},
{file = "mmh3-3.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c271472325b70d64a4fbb1f2e964ca5b093ac10258e1390f8408890b065868fe"},
{file = "mmh3-3.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:0109320f7e0e262123ff4f1acd06acfbc8b3bf19cc13d98c0bc369264430aaeb"},
{file = "mmh3-3.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:524e29dfe66499695f9496edcfc96782d130aabd6ba12c50c72372163cc6f3ea"},
{file = "mmh3-3.1.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66bdb06a03074e65e614da1aa199b1d16c90608bec9d8fc3faa81d887ffe93cc"},
{file = "mmh3-3.1.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2a4d471eb75df8320061ab3b8cbe11c970be9f116b01bc2222ebda9c0a777520"},
{file = "mmh3-3.1.0-cp311-cp311-win32.whl", hash = "sha256:a886d9ce995a4bdfd7a600ddf61b9015cccbc73c50b898f8ff3c78af24384710"},
{file = "mmh3-3.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:5edb5ac882c04aff8a2a18ae8b74a0c339ac9b83db9820d8456f518bb558e0d8"},
{file = "mmh3-3.1.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:190fd10981fbd6c67e10ce3b56bcc021562c0df0fee2e2864347d64e65b1783a"},
{file = "mmh3-3.1.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cd781b115cf649811cfde76368c33d2e553b6f88bb41131c314f30d8e65e9d24"},
{file = "mmh3-3.1.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f48bb0a867077acc1f548591ad49506389f36d18f36dccd10becf071e5cbdda4"},
{file = "mmh3-3.1.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7d0936a82438e340636a11b9a938378870fc1c7a139632dac09a9a9277351704"},
{file = "mmh3-3.1.0-cp37-cp37m-win32.whl", hash = "sha256:d196cc035c2238493248522ae4e54c3cb790549b1564f6dea4d88dfe4b326313"},
{file = "mmh3-3.1.0-cp37-cp37m-win_amd64.whl", hash = "sha256:731d37f089b6c212fab1beea24e673161146eb6c76baf9ac074a3424d1172d41"},
{file = "mmh3-3.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:9977fb81f8c66f4eee8439734a18dba7826fe78723d15ab53f42db977005be0f"},
{file = "mmh3-3.1.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:bf4f3f20a8b8405c08b13bc9e4ac33bf55129b50b535cd07ce1891b7f96326ac"},
{file = "mmh3-3.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:87cdbc6e70099ad92f17a28b4054ffb1938657e8fb7c1e4e03b194a1b4683fd6"},
{file = "mmh3-3.1.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6dd81321d14f62aa3711f30533c85a74dc7596e0fee63c8eddd375bc92ab846c"},
{file = "mmh3-3.1.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2e6eba88e5c1a2778f3de00a9502e3c214ebb757337ece2a7d71e060d188ddfa"},
{file = "mmh3-3.1.0-cp38-cp38-win32.whl", hash = "sha256:d91e696925f208d28f3bb7bdf29815524ce955248276af256519bd3538c411ce"},
{file = "mmh3-3.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:cbc2917df568aeb86ec5aa863bfb20fa14e01039cbdce7650efbabc30960df49"},
{file = "mmh3-3.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3b22832d565128be83d69f5d49243bb567840a954df377c9f5b26646a6eec39b"},
{file = "mmh3-3.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ced92a0e285a9111413541c197b0c17d280cee96f7c564b258caf5de5ab8ee01"},
{file = "mmh3-3.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f906833753b4ddcb690c2c1b74e77725868bc3a8b762b7a77737d08be89ae41d"},
{file = "mmh3-3.1.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:72b5685832a7a87a55ebff481794bc410484d7bd4c5e80dae4d8ac50739138ef"},
{file = "mmh3-3.1.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8d2aa4d422c7c088bbc5d367b45431268ebe6742a0a64eade93fab708e25757c"},
{file = "mmh3-3.1.0-cp39-cp39-win32.whl", hash = "sha256:4459bec818f534dc8378568ad89ab310ff47cda3e00ab322edce48dd899bba32"},
{file = "mmh3-3.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:03e04b3480e71828f48d17653451a3286555f0534942cb6ba93065b10ad5f9dc"},
{file = "mmh3-3.1.0.tar.gz", hash = "sha256:9b0f2b2ab4a915333c9d1089572e290a021ebb5b900bb7f7114dccc03995d732"},
]
[[package]] [[package]]
name = "monotonic" name = "monotonic"
version = "1.6" version = "1.6"
@ -3714,24 +3718,6 @@ files = [
{file = "more_itertools-9.1.0-py3-none-any.whl", hash = "sha256:d2bc7f02446e86a68911e58ded76d6561eea00cddfb2a91e7019bbb586c799f3"}, {file = "more_itertools-9.1.0-py3-none-any.whl", hash = "sha256:d2bc7f02446e86a68911e58ded76d6561eea00cddfb2a91e7019bbb586c799f3"},
] ]
[[package]]
name = "mpmath"
version = "1.3.0"
description = "Python library for arbitrary-precision floating-point arithmetic"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"},
{file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"},
]
[package.extras]
develop = ["codecov", "pycodestyle", "pytest (>=4.6)", "pytest-cov", "wheel"]
docs = ["sphinx"]
gmpy = ["gmpy2 (>=2.1.0a4)"]
tests = ["pytest (>=4.6)"]
[[package]] [[package]]
name = "multidict" name = "multidict"
version = "6.0.4" version = "6.0.4"
@ -4060,14 +4046,14 @@ test = ["black", "check-manifest", "flake8", "ipykernel", "ipython (<8.0.0)", "i
[[package]] [[package]]
name = "nbconvert" name = "nbconvert"
version = "7.3.0" version = "7.3.1"
description = "Converting Jupyter Notebooks" description = "Converting Jupyter Notebooks"
category = "dev" category = "dev"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "nbconvert-7.3.0-py3-none-any.whl", hash = "sha256:8983a83d0b083d56b076019f0a319f63bc16af70c9372892b86a0aab0a264b1d"}, {file = "nbconvert-7.3.1-py3-none-any.whl", hash = "sha256:d2e95904666f1ff77d36105b9de4e0801726f93b862d5b28f69e93d99ad3b19c"},
{file = "nbconvert-7.3.0.tar.gz", hash = "sha256:b970a13aba97529c223d805dd0706c2fe04dfc05e250ad4e6f7ae33daf6fede1"}, {file = "nbconvert-7.3.1.tar.gz", hash = "sha256:78685362b11d2e8058e70196fe83b09abed8df22d3e599cf271f4d39fdc48b9e"},
] ]
[package.dependencies] [package.dependencies]
@ -4156,7 +4142,7 @@ name = "networkx"
version = "2.8.8" version = "2.8.8"
description = "Python package for creating and manipulating graphs and networks" description = "Python package for creating and manipulating graphs and networks"
category = "main" category = "main"
optional = false optional = true
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
{file = "networkx-2.8.8-py3-none-any.whl", hash = "sha256:e435dfa75b1d7195c7b8378c3859f0445cd88c6b0375c181ed66823a9ceb7524"}, {file = "networkx-2.8.8-py3-none-any.whl", hash = "sha256:e435dfa75b1d7195c7b8378c3859f0445cd88c6b0375c181ed66823a9ceb7524"},
@ -4379,22 +4365,6 @@ files = [
setuptools = "*" setuptools = "*"
wheel = "*" wheel = "*"
[[package]]
name = "nvidia-cuda-cupti-cu11"
version = "11.7.101"
description = "CUDA profiling tools runtime libs."
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:e0cfd9854e1f2edaa36ca20d21cd0bdd5dcfca4e3b9e130a082e05b33b6c5895"},
{file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-win_amd64.whl", hash = "sha256:7cc5b8f91ae5e1389c3c0ad8866b3b016a175e827ea8f162a672990a402ab2b0"},
]
[package.dependencies]
setuptools = "*"
wheel = "*"
[[package]] [[package]]
name = "nvidia-cuda-nvrtc-cu11" name = "nvidia-cuda-nvrtc-cu11"
version = "11.7.99" version = "11.7.99"
@ -4444,94 +4414,6 @@ files = [
setuptools = "*" setuptools = "*"
wheel = "*" wheel = "*"
[[package]]
name = "nvidia-cufft-cu11"
version = "10.9.0.58"
description = "CUFFT native runtime libraries"
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl", hash = "sha256:222f9da70c80384632fd6035e4c3f16762d64ea7a843829cb278f98b3cb7dd81"},
{file = "nvidia_cufft_cu11-10.9.0.58-py3-none-win_amd64.whl", hash = "sha256:c4d316f17c745ec9c728e30409612eaf77a8404c3733cdf6c9c1569634d1ca03"},
]
[[package]]
name = "nvidia-curand-cu11"
version = "10.2.10.91"
description = "CURAND native runtime libraries"
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:eecb269c970fa599a2660c9232fa46aaccbf90d9170b96c462e13bcb4d129e2c"},
{file = "nvidia_curand_cu11-10.2.10.91-py3-none-win_amd64.whl", hash = "sha256:f742052af0e1e75523bde18895a9ed016ecf1e5aa0ecddfcc3658fd11a1ff417"},
]
[package.dependencies]
setuptools = "*"
wheel = "*"
[[package]]
name = "nvidia-cusolver-cu11"
version = "11.4.0.1"
description = "CUDA solver native runtime libraries"
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:72fa7261d755ed55c0074960df5904b65e2326f7adce364cbe4945063c1be412"},
{file = "nvidia_cusolver_cu11-11.4.0.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:700b781bfefd57d161443aff9ace1878584b93e0b2cfef3d6e9296d96febbf99"},
{file = "nvidia_cusolver_cu11-11.4.0.1-py3-none-win_amd64.whl", hash = "sha256:00f70b256add65f8c1eb3b6a65308795a93e7740f6df9e273eccbba770d370c4"},
]
[package.dependencies]
setuptools = "*"
wheel = "*"
[[package]]
name = "nvidia-cusparse-cu11"
version = "11.7.4.91"
description = "CUSPARSE native runtime libraries"
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_cusparse_cu11-11.7.4.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:a3389de714db63321aa11fbec3919271f415ef19fda58aed7f2ede488c32733d"},
{file = "nvidia_cusparse_cu11-11.7.4.91-py3-none-win_amd64.whl", hash = "sha256:304a01599534f5186a8ed1c3756879282c72c118bc77dd890dc1ff868cad25b9"},
]
[package.dependencies]
setuptools = "*"
wheel = "*"
[[package]]
name = "nvidia-nccl-cu11"
version = "2.14.3"
description = "NVIDIA Collective Communication Library (NCCL) Runtime"
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:5e5534257d1284b8e825bc3a182c6f06acd6eb405e9f89d49340e98cd8f136eb"},
]
[[package]]
name = "nvidia-nvtx-cu11"
version = "11.7.91"
description = "NVIDIA Tools Extension"
category = "main"
optional = false
python-versions = ">=3"
files = [
{file = "nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:b22c64eee426a62fc00952b507d6d29cf62b4c9df7a480fcc417e540e05fd5ac"},
{file = "nvidia_nvtx_cu11-11.7.91-py3-none-win_amd64.whl", hash = "sha256:dfd7fcb2a91742513027d63a26b757f38dd8b07fecac282c4d132a9d373ff064"},
]
[package.dependencies]
setuptools = "*"
wheel = "*"
[[package]] [[package]]
name = "oauthlib" name = "oauthlib"
version = "3.2.2" version = "3.2.2"
@ -5201,6 +5083,26 @@ urllib3 = ">=1.21.1"
[package.extras] [package.extras]
grpc = ["googleapis-common-protos (>=1.53.0)", "grpc-gateway-protoc-gen-openapiv2 (==0.1.0)", "grpcio (>=1.44.0)", "lz4 (>=3.1.3)", "protobuf (==3.19.3)"] grpc = ["googleapis-common-protos (>=1.53.0)", "grpc-gateway-protoc-gen-openapiv2 (==0.1.0)", "grpcio (>=1.44.0)", "lz4 (>=3.1.3)", "protobuf (==3.19.3)"]
[[package]]
name = "pinecone-text"
version = "0.4.2"
description = "Text utilities library by Pinecone.io"
category = "main"
optional = false
python-versions = ">=3.8,<4.0"
files = [
{file = "pinecone_text-0.4.2-py3-none-any.whl", hash = "sha256:79468c197b2fc7738c1511a6b5b8e7697fad613604ad935661a438f621ad2004"},
{file = "pinecone_text-0.4.2.tar.gz", hash = "sha256:131d9d1cc5654bdff8c4e497bb00e54fcab07a3b501e38aa16a6f19c2f00d4c6"},
]
[package.dependencies]
mmh3 = ">=3.1.0,<4.0.0"
nltk = ">=3.6.5,<4.0.0"
sentence-transformers = ">=2.0.0,<3.0.0"
torch = ">=1.13.1,<2.0.0"
transformers = ">=4.26.1,<5.0.0"
wget = ">=3.2,<4.0"
[[package]] [[package]]
name = "pkgutil-resolve-name" name = "pkgutil-resolve-name"
version = "1.3.10" version = "1.3.10"
@ -5790,14 +5692,14 @@ typing-extensions = "*"
[[package]] [[package]]
name = "pygments" name = "pygments"
version = "2.14.0" version = "2.15.0"
description = "Pygments is a syntax highlighting package written in Python." description = "Pygments is a syntax highlighting package written in Python."
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.6" python-versions = ">=3.7"
files = [ files = [
{file = "Pygments-2.14.0-py3-none-any.whl", hash = "sha256:fa7bd7bd2771287c0de303af8bfdfc731f51bd2c6a47ab69d117138893b82717"}, {file = "Pygments-2.15.0-py3-none-any.whl", hash = "sha256:77a3299119af881904cd5ecd1ac6a66214b6e9bed1f2db16993b54adede64094"},
{file = "Pygments-2.14.0.tar.gz", hash = "sha256:b3ed06a9e8ac9a9aae5a6f5dbe78a8a58655d17b43b93c078f094ddc476ae297"}, {file = "Pygments-2.15.0.tar.gz", hash = "sha256:f7e36cffc4c517fbc252861b9a6e4644ca0e5abadf9a113c72d1358ad09b9500"},
] ]
[package.extras] [package.extras]
@ -5858,14 +5760,14 @@ diagrams = ["jinja2", "railroad-diagrams"]
[[package]] [[package]]
name = "pypdf" name = "pypdf"
version = "3.7.0" version = "3.7.1"
description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files" description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files"
category = "main" category = "main"
optional = true optional = true
python-versions = ">=3.6" python-versions = ">=3.6"
files = [ files = [
{file = "pypdf-3.7.0-py3-none-any.whl", hash = "sha256:b50c2d3c807af2f75c945b7bdd8f8bb01d513a0c25d6b66bf299b9fad1cbc91c"}, {file = "pypdf-3.7.1-py3-none-any.whl", hash = "sha256:fa780c9464ec3b49fd16dabd110a40a291439bc6edd0f21f302add63c1f5ade5"},
{file = "pypdf-3.7.0.tar.gz", hash = "sha256:da98eb41428b26f5ab23561cc125eedff450147598d6b6159e62943edc0008fe"}, {file = "pypdf-3.7.1.tar.gz", hash = "sha256:dfb61fcccd4bc6d321aae612c01924b3c953aa5857e6e39d31e24dbb9b49da13"},
] ]
[package.dependencies] [package.dependencies]
@ -6540,24 +6442,6 @@ files = [
[package.dependencies] [package.dependencies]
six = "*" six = "*"
[[package]]
name = "rfc3986"
version = "1.5.0"
description = "Validating URI References per RFC 3986"
category = "main"
optional = true
python-versions = "*"
files = [
{file = "rfc3986-1.5.0-py2.py3-none-any.whl", hash = "sha256:a86d6e1f5b1dc238b218b012df0aa79409667bb209e58da56d0b94704e712a97"},
{file = "rfc3986-1.5.0.tar.gz", hash = "sha256:270aaf10d87d0d4e095063c65bf3ddbc6ee3d0b226328ce21e036f946e421835"},
]
[package.dependencies]
idna = {version = "*", optional = true, markers = "extra == \"idna2008\""}
[package.extras]
idna2008 = ["idna"]
[[package]] [[package]]
name = "rfc3986-validator" name = "rfc3986-validator"
version = "0.1.1" version = "0.1.1"
@ -7333,7 +7217,7 @@ files = [
] ]
[package.dependencies] [package.dependencies]
greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and platform_machine == \"aarch64\" or python_version >= \"3\" and platform_machine == \"ppc64le\" or python_version >= \"3\" and platform_machine == \"x86_64\" or python_version >= \"3\" and platform_machine == \"amd64\" or python_version >= \"3\" and platform_machine == \"AMD64\" or python_version >= \"3\" and platform_machine == \"win32\" or python_version >= \"3\" and platform_machine == \"WIN32\""} greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"}
[package.extras] [package.extras]
aiomysql = ["aiomysql", "greenlet (!=0.4.17)"] aiomysql = ["aiomysql", "greenlet (!=0.4.17)"]
@ -7447,21 +7331,6 @@ typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""
[package.extras] [package.extras]
full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"] full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"]
[[package]]
name = "sympy"
version = "1.11.1"
description = "Computer algebra system (CAS) in Python"
category = "main"
optional = false
python-versions = ">=3.8"
files = [
{file = "sympy-1.11.1-py3-none-any.whl", hash = "sha256:938f984ee2b1e8eae8a07b884c8b7a1146010040fccddc6539c54f401c8f6fcf"},
{file = "sympy-1.11.1.tar.gz", hash = "sha256:e32380dce63cb7c0108ed525570092fd45168bdae2faa17e528221ef72e88658"},
]
[package.dependencies]
mpmath = ">=0.19"
[[package]] [[package]]
name = "tabulate" name = "tabulate"
version = "0.9.0" version = "0.9.0"
@ -7983,55 +7852,40 @@ files = [
[[package]] [[package]]
name = "torch" name = "torch"
version = "2.0.0" version = "1.13.1"
description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration" description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.8.0" python-versions = ">=3.7.0"
files = [ files = [
{file = "torch-2.0.0-1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:c9090bda7d2eeeecd74f51b721420dbeb44f838d4536cc1b284e879417e3064a"}, {file = "torch-1.13.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:fd12043868a34a8da7d490bf6db66991108b00ffbeecb034228bfcbbd4197143"},
{file = "torch-2.0.0-1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:bd42db2a48a20574d2c33489e120e9f32789c4dc13c514b0c44272972d14a2d7"}, {file = "torch-1.13.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:d9fe785d375f2e26a5d5eba5de91f89e6a3be5d11efb497e76705fdf93fa3c2e"},
{file = "torch-2.0.0-1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:8969aa8375bcbc0c2993e7ede0a7f889df9515f18b9b548433f412affed478d9"}, {file = "torch-1.13.1-cp310-cp310-win_amd64.whl", hash = "sha256:98124598cdff4c287dbf50f53fb455f0c1e3a88022b39648102957f3445e9b76"},
{file = "torch-2.0.0-1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:ab2da16567cb55b67ae39e32d520d68ec736191d88ac79526ca5874754c32203"}, {file = "torch-1.13.1-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:393a6273c832e047581063fb74335ff50b4c566217019cc6ace318cd79eb0566"},
{file = "torch-2.0.0-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:7a9319a67294ef02459a19738bbfa8727bb5307b822dadd708bc2ccf6c901aca"}, {file = "torch-1.13.1-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:0122806b111b949d21fa1a5f9764d1fd2fcc4a47cb7f8ff914204fd4fc752ed5"},
{file = "torch-2.0.0-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:9f01fe1f6263f31bd04e1757946fd63ad531ae37f28bb2dbf66f5c826ee089f4"}, {file = "torch-1.13.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:22128502fd8f5b25ac1cd849ecb64a418382ae81dd4ce2b5cebaa09ab15b0d9b"},
{file = "torch-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:527f4ae68df7b8301ee6b1158ca56350282ea633686537b30dbb5d7b4a52622a"}, {file = "torch-1.13.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:76024be052b659ac1304ab8475ab03ea0a12124c3e7626282c9c86798ac7bc11"},
{file = "torch-2.0.0-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:ce9b5a49bd513dff7950a5a07d6e26594dd51989cee05ba388b03e8e366fd5d5"}, {file = "torch-1.13.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:ea8dda84d796094eb8709df0fcd6b56dc20b58fdd6bc4e8d7109930dafc8e419"},
{file = "torch-2.0.0-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:53e1c33c6896583cdb9a583693e22e99266444c4a43392dddc562640d39e542b"}, {file = "torch-1.13.1-cp37-cp37m-win_amd64.whl", hash = "sha256:2ee7b81e9c457252bddd7d3da66fb1f619a5d12c24d7074de91c4ddafb832c93"},
{file = "torch-2.0.0-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:09651bff72e439d004c991f15add0c397c66f98ab36fe60d5514b44e4da722e8"}, {file = "torch-1.13.1-cp37-none-macosx_10_9_x86_64.whl", hash = "sha256:0d9b8061048cfb78e675b9d2ea8503bfe30db43d583599ae8626b1263a0c1380"},
{file = "torch-2.0.0-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:d439aec349c98f12819e8564b8c54008e4613dd4428582af0e6e14c24ca85870"}, {file = "torch-1.13.1-cp37-none-macosx_11_0_arm64.whl", hash = "sha256:f402ca80b66e9fbd661ed4287d7553f7f3899d9ab54bf5c67faada1555abde28"},
{file = "torch-2.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:2802f84f021907deee7e9470ed10c0e78af7457ac9a08a6cd7d55adef835fede"}, {file = "torch-1.13.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:727dbf00e2cf858052364c0e2a496684b9cb5aa01dc8a8bc8bbb7c54502bdcdd"},
{file = "torch-2.0.0-cp311-none-macosx_10_9_x86_64.whl", hash = "sha256:01858620f25f25e7a9ec4b547ff38e5e27c92d38ec4ccba9cfbfb31d7071ed9c"}, {file = "torch-1.13.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:df8434b0695e9ceb8cc70650afc1310d8ba949e6db2a0525ddd9c3b2b181e5fe"},
{file = "torch-2.0.0-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:9a2e53b5783ef5896a6af338b36d782f28e83c8ddfc2ac44b67b066d9d76f498"}, {file = "torch-1.13.1-cp38-cp38-win_amd64.whl", hash = "sha256:5e1e722a41f52a3f26f0c4fcec227e02c6c42f7c094f32e49d4beef7d1e213ea"},
{file = "torch-2.0.0-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:ec5fff2447663e369682838ff0f82187b4d846057ef4d119a8dea7772a0b17dd"}, {file = "torch-1.13.1-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:33e67eea526e0bbb9151263e65417a9ef2d8fa53cbe628e87310060c9dcfa312"},
{file = "torch-2.0.0-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:11b0384fe3c18c01b8fc5992e70fc519cde65e44c51cc87be1838c1803daf42f"}, {file = "torch-1.13.1-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:eeeb204d30fd40af6a2d80879b46a7efbe3cf43cdbeb8838dd4f3d126cc90b2b"},
{file = "torch-2.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:e54846aa63855298cfb1195487f032e413e7ac9cbfa978fda32354cc39551475"}, {file = "torch-1.13.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:50ff5e76d70074f6653d191fe4f6a42fdbe0cf942fbe2a3af0b75eaa414ac038"},
{file = "torch-2.0.0-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:cc788cbbbbc6eb4c90e52c550efd067586c2693092cf367c135b34893a64ae78"}, {file = "torch-1.13.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:2c3581a3fd81eb1f0f22997cddffea569fea53bafa372b2c0471db373b26aafc"},
{file = "torch-2.0.0-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:d292640f0fd72b7a31b2a6e3b635eb5065fcbedd4478f9cad1a1e7a9ec861d35"}, {file = "torch-1.13.1-cp39-cp39-win_amd64.whl", hash = "sha256:0aa46f0ac95050c604bcf9ef71da9f1172e5037fdf2ebe051962d47b123848e7"},
{file = "torch-2.0.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:6befaad784004b7af357e3d87fa0863c1f642866291f12a4c2af2de435e8ac5c"}, {file = "torch-1.13.1-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:6930791efa8757cb6974af73d4996b6b50c592882a324b8fb0589c6a9ba2ddaf"},
{file = "torch-2.0.0-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:a83b26bd6ae36fbf5fee3d56973d9816e2002e8a3b7d9205531167c28aaa38a7"}, {file = "torch-1.13.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:e0df902a7c7dd6c795698532ee5970ce898672625635d885eade9976e5a04949"},
{file = "torch-2.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:c7e67195e1c3e33da53954b026e89a8e1ff3bc1aeb9eb32b677172d4a9b5dcbf"}, ]
{file = "torch-2.0.0-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:6e0b97beb037a165669c312591f242382e9109a240e20054d5a5782d9236cad0"},
{file = "torch-2.0.0-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:297a4919aff1c0f98a58ebe969200f71350a1d4d4f986dbfd60c02ffce780e99"}, [package.dependencies]
] nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\""}
nvidia-cuda-nvrtc-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""}
[package.dependencies] nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""}
filelock = "*" nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\""}
jinja2 = "*"
networkx = "*"
nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cuda-cupti-cu11 = {version = "11.7.101", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cuda-nvrtc-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cufft-cu11 = {version = "10.9.0.58", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-curand-cu11 = {version = "10.2.10.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cusolver-cu11 = {version = "11.4.0.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-cusparse-cu11 = {version = "11.7.4.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-nccl-cu11 = {version = "2.14.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
nvidia-nvtx-cu11 = {version = "11.7.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
sympy = "*"
triton = {version = "2.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
typing-extensions = "*" typing-extensions = "*"
[package.extras] [package.extras]
@ -8039,39 +7893,39 @@ opt-einsum = ["opt-einsum (>=3.3)"]
[[package]] [[package]]
name = "torchvision" name = "torchvision"
version = "0.15.1" version = "0.14.1"
description = "image and video datasets and models for torch deep learning" description = "image and video datasets and models for torch deep learning"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.7"
files = [ files = [
{file = "torchvision-0.15.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bc10d48e9a60d006d0c1b48dea87f1ec9b63d856737d592f7c5c44cd87f3f4b7"}, {file = "torchvision-0.14.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:eeb05dd9dd3af5428fee525400759daf8da8e4caec45ddd6908cfb36571f6433"},
{file = "torchvision-0.15.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3708d3410fdcaf6280e358cda9de2a4ab06cc0b4c0fd9aeeac550ec2563a887e"}, {file = "torchvision-0.14.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8d0766ea92affa7af248e327dd85f7c9cfdf51a57530b43212d4e1858548e9d7"},
{file = "torchvision-0.15.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:d4de10c837f1493c1c54344388e300a06c96914c6cc55fcb2527c21f2f010bbd"}, {file = "torchvision-0.14.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:6d7b35653113664ea3fdcb71f515cfbf29d2fe393000fd8aaff27a1284de6908"},
{file = "torchvision-0.15.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:b82fcc5abc9b5c96495c76596a1573025cc1e09d97d2d6fda717c44b9ca45881"}, {file = "torchvision-0.14.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:8a9eb773a2fa8f516e404ac09c059fb14e6882c48fdbb9c946327d2ce5dba6cd"},
{file = "torchvision-0.15.1-cp310-cp310-win_amd64.whl", hash = "sha256:c84e97d8cc4fe167d87adad0a2a6424cff90544365545b20669bc50e6ea46875"}, {file = "torchvision-0.14.1-cp310-cp310-win_amd64.whl", hash = "sha256:13986f0c15377ff23039e1401012ccb6ecf71024ce53def27139e4eac5a57592"},
{file = "torchvision-0.15.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:97b90eb3b7333a31d049c4ccfd1064361e8491874959d38f466af64d67418cef"}, {file = "torchvision-0.14.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:fb7a793fd33ce1abec24b42778419a3fb1e3159d7dfcb274a3ca8fb8cbc408dc"},
{file = "torchvision-0.15.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6b60e1c839ae2a071befbba69b17468d67feafdf576e90ff9645bfbee998de17"}, {file = "torchvision-0.14.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:89fb0419780ec9a9eb9f7856a0149f6ac9f956b28f44b0c0080c6b5b48044db7"},
{file = "torchvision-0.15.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:13f71a3372d9168b01481a754ebaa171207f3dc455bf2fd86906c69222443738"}, {file = "torchvision-0.14.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:a2d4237d3c9705d7729eb4534e4eb06f1d6be7ff1df391204dfb51586d9b0ecb"},
{file = "torchvision-0.15.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:b2e8394726009090b40f6cc3a95cc878cc011dfac3d8e7a6060c79213d360880"}, {file = "torchvision-0.14.1-cp37-cp37m-win_amd64.whl", hash = "sha256:92a324712a87957443cc34223274298ae9496853f115c252f8fc02b931f2340e"},
{file = "torchvision-0.15.1-cp311-cp311-win_amd64.whl", hash = "sha256:2852f501189483187ce9eb0ccd01b3f4f0918d29057e4a18b3cce8dad9a8a964"}, {file = "torchvision-0.14.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:68ed03359dcd3da9cd21b8ab94da21158df8a6a0c5bad0bf4a42f0e448d28cb3"},
{file = "torchvision-0.15.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:e5861baaeea87d19b6fd7d131e11a4a6bd17be14234c490a259bb360775e9520"}, {file = "torchvision-0.14.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:30fcf0e9fe57d4ac4ce6426659a57dce199637ccb6c70be1128670f177692624"},
{file = "torchvision-0.15.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e714f362b9d8217cf4d68509b679ebc9ddf128cfe80f6c1def8e3f8a18466e75"}, {file = "torchvision-0.14.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:0ed02aefd09bf1114d35f1aa7dce55aa61c2c7e57f9aa02dce362860be654e85"},
{file = "torchvision-0.15.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:43624accad1e47f16824be4db37ad678dd89326ad90b69c9c6363eeb22b9467e"}, {file = "torchvision-0.14.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:a541e49fc3c4e90e49e6988428ab047415ed52ea97d0c0bfd147d8bacb8f4df8"},
{file = "torchvision-0.15.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:7fe9b0cd3311b0db9e6d45ffab594ced06418fa4e2aa15eb2e60d55e5c51135c"}, {file = "torchvision-0.14.1-cp38-cp38-win_amd64.whl", hash = "sha256:6099b3191dc2516099a32ae38a5fb349b42e863872a13545ab1a524b6567be60"},
{file = "torchvision-0.15.1-cp38-cp38-win_amd64.whl", hash = "sha256:b45324ea4911a23a4b00b5a15cdbe36d47f93137206dab9f8c606d81b69dd3a7"}, {file = "torchvision-0.14.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c5e744f56e5f5b452deb5fc0f3f2ba4d2f00612d14d8da0dbefea8f09ac7690b"},
{file = "torchvision-0.15.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1dfdec7c7df967330bba3341a781e0c047d4e0163e67164a9918500362bf7d91"}, {file = "torchvision-0.14.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:758b20d079e810b4740bd60d1eb16e49da830e3360f9be379eb177ee221fa5d4"},
{file = "torchvision-0.15.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c153710186cec0338d4fff411459a57ddbc8504436123ca73b3f0bdc26ff918c"}, {file = "torchvision-0.14.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:83045507ef8d3c015d4df6be79491375b2f901352cfca6e72b4723e9c4f9a55d"},
{file = "torchvision-0.15.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:ff4e650aa601f32ab97bce06704868dd2baad69ca4d454fa1f0012a51199f2bc"}, {file = "torchvision-0.14.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:eaed58cf454323ed9222d4e0dd5fb897064f454b400696e03a5200e65d3a1e76"},
{file = "torchvision-0.15.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:e9b4bb2a15849391df0415d2f76dd36e6528e4253f7b69322b7a0d682535544b"}, {file = "torchvision-0.14.1-cp39-cp39-win_amd64.whl", hash = "sha256:b337e1245ca4353623dd563c03cd8f020c2496a7c5d12bba4d2e381999c766e0"},
{file = "torchvision-0.15.1-cp39-cp39-win_amd64.whl", hash = "sha256:21e6beb69e77ef6575c4fdd0ab332b96e8a7f144eee0d333acff469c827a4b5e"},
] ]
[package.dependencies] [package.dependencies]
numpy = "*" numpy = "*"
pillow = ">=5.3.0,<8.3.0 || >=8.4.0" pillow = ">=5.3.0,<8.3.0 || >=8.4.0"
requests = "*" requests = "*"
torch = "2.0.0" torch = "1.13.1"
typing-extensions = "*"
[package.extras] [package.extras]
scipy = ["scipy"] scipy = ["scipy"]
@ -8202,44 +8056,6 @@ torchhub = ["filelock", "huggingface-hub (>=0.11.0,<1.0)", "importlib-metadata",
video = ["av (==9.2.0)", "decord (==0.6.0)"] video = ["av (==9.2.0)", "decord (==0.6.0)"]
vision = ["Pillow"] vision = ["Pillow"]
[[package]]
name = "triton"
version = "2.0.0"
description = "A language and compiler for custom Deep Learning operations"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:38806ee9663f4b0f7cd64790e96c579374089e58f49aac4a6608121aa55e2505"},
{file = "triton-2.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:226941c7b8595219ddef59a1fdb821e8c744289a132415ddd584facedeb475b1"},
{file = "triton-2.0.0-1-cp36-cp36m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4c9fc8c89874bc48eb7e7b2107a9b8d2c0bf139778637be5bfccb09191685cfd"},
{file = "triton-2.0.0-1-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d2684b6a60b9f174f447f36f933e9a45f31db96cb723723ecd2dcfd1c57b778b"},
{file = "triton-2.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9d4978298b74fcf59a75fe71e535c092b023088933b2f1df933ec32615e4beef"},
{file = "triton-2.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:74f118c12b437fb2ca25e1a04759173b517582fcf4c7be11913316c764213656"},
{file = "triton-2.0.0-1-pp37-pypy37_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9618815a8da1d9157514f08f855d9e9ff92e329cd81c0305003eb9ec25cc5add"},
{file = "triton-2.0.0-1-pp38-pypy38_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1aca3303629cd3136375b82cb9921727f804e47ebee27b2677fef23005c3851a"},
{file = "triton-2.0.0-1-pp39-pypy39_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e3e13aa8b527c9b642e3a9defcc0fbd8ffbe1c80d8ac8c15a01692478dc64d8a"},
{file = "triton-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f05a7e64e4ca0565535e3d5d3405d7e49f9d308505bb7773d21fb26a4c008c2"},
{file = "triton-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb4b99ca3c6844066e516658541d876c28a5f6e3a852286bbc97ad57134827fd"},
{file = "triton-2.0.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47b4d70dc92fb40af553b4460492c31dc7d3a114a979ffb7a5cdedb7eb546c08"},
{file = "triton-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fedce6a381901b1547e0e7e1f2546e4f65dca6d91e2d8a7305a2d1f5551895be"},
{file = "triton-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75834f27926eab6c7f00ce73aaf1ab5bfb9bec6eb57ab7c0bfc0a23fac803b4c"},
{file = "triton-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0117722f8c2b579cd429e0bee80f7731ae05f63fe8e9414acd9a679885fcbf42"},
{file = "triton-2.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcd9be5d0c2e45d2b7e6ddc6da20112b6862d69741576f9c3dbaf941d745ecae"},
{file = "triton-2.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42a0d2c3fc2eab4ba71384f2e785fbfd47aa41ae05fa58bf12cb31dcbd0aeceb"},
{file = "triton-2.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52c47b72c72693198163ece9d90a721299e4fb3b8e24fd13141e384ad952724f"},
]
[package.dependencies]
cmake = "*"
filelock = "*"
lit = "*"
torch = "*"
[package.extras]
tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
tutorials = ["matplotlib", "pandas", "tabulate"]
[[package]] [[package]]
name = "typer" name = "typer"
version = "0.7.0" version = "0.7.0"
@ -8500,13 +8316,13 @@ test = ["Cython (>=0.29.32,<0.30.0)", "aiohttp", "flake8 (>=3.9.2,<3.10.0)", "my
[[package]] [[package]]
name = "validators" name = "validators"
version = "0.19.0" version = "0.20.0"
description = "Python Data Validation for Humans™." description = "Python Data Validation for Humans™."
category = "main" category = "main"
optional = true optional = true
python-versions = ">=3.4" python-versions = ">=3.4"
files = [ files = [
{file = "validators-0.19.0.tar.gz", hash = "sha256:dec45f4381f042f1e705cfa74949505b77f1e27e8b05409096fee8152c839cbe"}, {file = "validators-0.20.0.tar.gz", hash = "sha256:24148ce4e64100a2d5e267233e23e7afeb55316b47d30faae7eb6e7292bc226a"},
] ]
[package.dependencies] [package.dependencies]
@ -8637,21 +8453,21 @@ files = [
[[package]] [[package]]
name = "weaviate-client" name = "weaviate-client"
version = "3.15.4" version = "3.15.5"
description = "A python native weaviate client" description = "A python native weaviate client"
category = "main" category = "main"
optional = true optional = true
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "weaviate-client-3.15.4.tar.gz", hash = "sha256:5e61ebffefbedf62b0751d7de562ffd5384717c8ee6adfca4ea6eb150d012e1c"}, {file = "weaviate-client-3.15.5.tar.gz", hash = "sha256:6da7e5d08dc9bb8b7879661d1a457c50af7d73e621a5305efe131160e83da69e"},
{file = "weaviate_client-3.15.4-py3-none-any.whl", hash = "sha256:e765b2f434d2a4301ad8d63052833ab7708d0ef430033496e3e7020ef72c9da0"}, {file = "weaviate_client-3.15.5-py3-none-any.whl", hash = "sha256:24d0be614e5494534e758cc67a45e7e15f3929a89bf512afd642de53d08723c7"},
] ]
[package.dependencies] [package.dependencies]
authlib = ">=1.1.0" authlib = ">=1.1.0"
requests = ">=2.28.0,<2.29.0" requests = ">=2.28.0,<2.29.0"
tqdm = ">=4.59.0,<5.0.0" tqdm = ">=4.59.0,<5.0.0"
validators = ">=0.18.2,<0.20.0" validators = ">=0.18.2,<=0.21.0"
[[package]] [[package]]
name = "webcolors" name = "webcolors"
@ -8796,6 +8612,17 @@ MarkupSafe = ">=2.1.1"
[package.extras] [package.extras]
watchdog = ["watchdog"] watchdog = ["watchdog"]
[[package]]
name = "wget"
version = "3.2"
description = "pure python download utility"
category = "main"
optional = false
python-versions = "*"
files = [
{file = "wget-3.2.zip", hash = "sha256:35e630eca2aa50ce998b9b1a127bb26b30dfee573702782aa982f875e3f16061"},
]
[[package]] [[package]]
name = "wheel" name = "wheel"
version = "0.40.0" version = "0.40.0"
@ -9158,13 +8985,13 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\
cffi = ["cffi (>=1.11)"] cffi = ["cffi (>=1.11)"]
[extras] [extras]
all = ["aleph-alpha-client", "anthropic", "beautifulsoup4", "cohere", "deeplake", "elasticsearch", "faiss-cpu", "google-api-python-client", "google-search-results", "huggingface_hub", "jina", "jinja2", "manifest-ml", "networkx", "nlpcloud", "nltk", "nomic", "openai", "opensearch-py", "pgvector", "pinecone-client", "psycopg2-binary", "pyowm", "pypdf", "qdrant-client", "redis", "sentence-transformers", "spacy", "tensorflow-text", "tiktoken", "torch", "transformers", "weaviate-client", "wikipedia", "wolframalpha"] all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence-transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "pinecone-text", "weaviate-client", "redis", "google-api-python-client", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary", "pyowm"]
cohere = ["cohere"] cohere = ["cohere"]
llms = ["anthropic", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "torch", "transformers"] llms = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "manifest-ml", "torch", "transformers"]
openai = ["openai"] openai = ["openai"]
qdrant = ["qdrant-client"] qdrant = ["qdrant-client"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.8.1,<4.0" python-versions = ">=3.8.1,<4.0"
content-hash = "a8fde2558f92b4c5ec1dce45f830adc6158dd2cf8c425a34a06523ee8e74487d" content-hash = "11bbe0042c3c1e56a5d1abbaab33185efad5dcdacb095fc91e91c382f2c9ebb7"

8
pyproject.toml
Unescape Escape View File

@ -28,10 +28,11 @@ spacy = {version = "^3", optional = true}
nltk = {version = "^3", optional = true} nltk = {version = "^3", optional = true}
transformers = {version = "^4", optional = true} transformers = {version = "^4", optional = true}
beautifulsoup4 = {version = "^4", optional = true} beautifulsoup4 = {version = "^4", optional = true}
torch = {version = "^2", optional = true} torch = {version = "^1", optional = true}
jinja2 = {version = "^3", optional = true} jinja2 = {version = "^3", optional = true}
tiktoken = {version = "^0.3.2", optional = true, python="^3.9"} tiktoken = {version = "^0.3.2", optional = true, python="^3.9"}
pinecone-client = {version = "^2", optional = true} pinecone-client = {version = "^2", optional = true}
pinecone-text = {version = "^0.4.2", optional = true}
weaviate-client = {version = "^3", optional = true} weaviate-client = {version = "^3", optional = true}
google-api-python-client = {version = "2.70.0", optional = true} google-api-python-client = {version = "2.70.0", optional = true}
wolframalpha = {version = "5.0.0", optional = true} wolframalpha = {version = "5.0.0", optional = true}
@ -94,11 +95,12 @@ openai = "^0.27.4"
elasticsearch = {extras = ["async"], version = "^8.6.2"} elasticsearch = {extras = ["async"], version = "^8.6.2"}
redis = "^4.5.4" redis = "^4.5.4"
pinecone-client = "^2.2.1" pinecone-client = "^2.2.1"
pinecone-text = "^0.4.2"
pgvector = "^0.1.6" pgvector = "^0.1.6"
transformers = "^4.27.4" transformers = "^4.27.4"
pandas = "^2.0.0" pandas = "^2.0.0"
deeplake = "^3.2.21" deeplake = "^3.2.21"
torch = "^2.0.0" torch = "^1.0.0"
chromadb = "^0.3.21" chromadb = "^0.3.21"
tiktoken = "^0.3.3" tiktoken = "^0.3.3"
@ -126,7 +128,7 @@ llms = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "manifes
qdrant = ["qdrant-client"] qdrant = ["qdrant-client"]
openai = ["openai"] openai = ["openai"]
cohere = ["cohere"] cohere = ["cohere"]
all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence_transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "weaviate-client", "redis", "google-api-python-client", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary", "boto3", "pyowm"] all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence_transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "pinecone-text", "weaviate-client", "redis", "google-api-python-client", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary", "boto3", "pyowm"]
[tool.ruff] [tool.ruff]
select = [ select = [

Write Preview
Loading…
Cancel
Save