text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers and 🤗 Datasets. Uncomment the following cell and run it.<jupyter_code>#! pip install datasets transformers[sentencepiece] sacrebleu<jupyter_output><empty_output><jupyter_text>If you're opening this ... | notebooks/examples/translation.ipynb/0 | {
"file_path": "notebooks/examples/translation.ipynb",
"repo_id": "notebooks",
"token_count": 5285
} | 327 |
# coding=utf-8
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/luke/test_tokenization_luke.py/0 | {
"file_path": "transformers/tests/models/luke/test_tokenization_luke.py",
"repo_id": "transformers",
"token_count": 14108
} | 823 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-guru/llama_index/readers/guru/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-guru/llama_index/readers/guru/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,412 |
<jupyter_start><jupyter_text>Human-in-the-loop Tool ValidationThis walkthrough demonstrates how to add human validation to any Tool. We'll do this using the `HumanApprovalCallbackhandler`.Let's suppose we need to make use of the `ShellTool`. Adding this tool to an automated flow poses obvious risks. Let's see how we co... | langchain/cookbook/human_approval.ipynb/0 | {
"file_path": "langchain/cookbook/human_approval.ipynb",
"repo_id": "langchain",
"token_count": 844
} | 76 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/datacoord/metrics_info.go/0 | {
"file_path": "milvus/internal/datacoord/metrics_info.go",
"repo_id": "milvus",
"token_count": 2756
} | 1,829 |
---
YAML tags (full spec here: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1):
- copy-paste the tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging
---
# Dataset Card Creation Guide
## Table of Contents
- [Dataset Card Creation Guide](#datas... | datasets/templates/README_guide.md/0 | {
"file_path": "datasets/templates/README_guide.md",
"repo_id": "datasets",
"token_count": 3254
} | 143 |
# LangServe Playground 🦜️🔗
| langserve/libs/langserve-playground/README.md/0 | {
"file_path": "langserve/libs/langserve-playground/README.md",
"repo_id": "langserve",
"token_count": 14
} | 1,133 |
poetry_requirements(
name="poetry",
)
python_requirements(
name="reqs",
)
| llama_index/llama-index-integrations/tools/llama-index-tools-shopify/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-shopify/BUILD",
"repo_id": "llama_index",
"token_count": 36
} | 1,437 |
from typing import List, Optional
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
import asana
class AsanaReader(BaseReader):
"""Asana reader. Reads data from an Asana workspace.
Args:
asana_token (str): Asana token.
"""
def __init__(self, ... | llama_index/llama-index-integrations/readers/llama-index-readers-asana/llama_index/readers/asana/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-asana/llama_index/readers/asana/base.py",
"repo_id": "llama_index",
"token_count": 2008
} | 1,321 |
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
use candle_transformers::models::stable_diffusion;
use anyhow::{Error as E, Result};
use candle::{DType, Device, IndexOp, Module, Tensor, D};
use clap::Parser;
use tokenizers::Tokenizer;
#[derive(Parser)]... | candle/candle-examples/examples/stable-diffusion/main.rs/0 | {
"file_path": "candle/candle-examples/examples/stable-diffusion/main.rs",
"repo_id": "candle",
"token_count": 9476
} | 50 |
# rewrite_retrieve_read
This template implemenets a method for query transformation (re-writing) in the paper [Query Rewriting for Retrieval-Augmented Large Language Models](https://arxiv.org/pdf/2305.14283.pdf) to optimize for RAG.
## Environment Setup
Set the `OPENAI_API_KEY` environment variable to access the O... | langchain/templates/rewrite-retrieve-read/README.md/0 | {
"file_path": "langchain/templates/rewrite-retrieve-read/README.md",
"repo_id": "langchain",
"token_count": 644
} | 687 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/querynodev2/tsafe/tsafe.go/0 | {
"file_path": "milvus/internal/querynodev2/tsafe/tsafe.go",
"repo_id": "milvus",
"token_count": 433
} | 1,780 |
python_sources()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-timescalevector/llama_index/vector_stores/timescalevector/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-timescalevector/llama_index/vector_stores/timescalevector/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,538 |
<!---
Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/examples/pytorch/multiple-choice/README.md/0 | {
"file_path": "transformers/examples/pytorch/multiple-choice/README.md",
"repo_id": "transformers",
"token_count": 1161
} | 587 |
<!---
Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/docs/source/ja/installation.md/0 | {
"file_path": "transformers/docs/source/ja/installation.md",
"repo_id": "transformers",
"token_count": 4798
} | 514 |
"""Utils for keyword table."""
import re
from typing import Optional, Set
import pandas as pd
from llama_index.legacy.indices.utils import expand_tokens_with_subtokens
from llama_index.legacy.utils import globals_helper
def simple_extract_keywords(
text_chunk: str, max_keywords: Optional[int] = None, filter_st... | llama_index/llama-index-legacy/llama_index/legacy/indices/keyword_table/utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/keyword_table/utils.py",
"repo_id": "llama_index",
"token_count": 936
} | 1,599 |
import { insecureHash } from "@langchain/core/utils/hash";
import {
type EmbeddingsInterface,
Embeddings,
} from "@langchain/core/embeddings";
import { BaseStore } from "@langchain/core/stores";
import { AsyncCallerParams } from "@langchain/core/utils/async_caller";
import { EncoderBackedStore } from "../storage/e... | langchainjs/langchain/src/embeddings/cache_backed.ts/0 | {
"file_path": "langchainjs/langchain/src/embeddings/cache_backed.ts",
"repo_id": "langchainjs",
"token_count": 1814
} | 887 |
# Supporting Modules
We have two configuration modules that can be configured separately and passed to individual indexes, or set globally.
- The [Settings](settings.md) includes the LLM you're using, the embedding model, your node parser, your callback manager and more.
- The `StorageContext` lets you specify where ... | llama_index/docs/module_guides/supporting_modules/supporting_modules.md/0 | {
"file_path": "llama_index/docs/module_guides/supporting_modules/supporting_modules.md",
"repo_id": "llama_index",
"token_count": 143
} | 1,100 |
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ko/custom_models.md/0 | {
"file_path": "transformers/docs/source/ko/custom_models.md",
"repo_id": "transformers",
"token_count": 10729
} | 501 |
import os
from contextlib import contextmanager
from typing import Generator
from unittest.mock import Mock
import pytest
from ai21 import AI21Client
from ai21.models import (
ChatOutput,
ChatResponse,
Completion,
CompletionData,
CompletionFinishReason,
CompletionsResponse,
FinishReason,
... | langchain/libs/partners/ai21/tests/unit_tests/conftest.py/0 | {
"file_path": "langchain/libs/partners/ai21/tests/unit_tests/conftest.py",
"repo_id": "langchain",
"token_count": 956
} | 659 |
<jupyter_start><jupyter_text>Volc EngineThis notebook provides you with a guide on how to load the Volcano Embedding class. API InitializationTo use the LLM services based on [VolcEngine](https://www.volcengine.com/docs/82379/1099455), you have to initialize these parameters:You could either choose to init the AK,SK in... | langchain/docs/docs/integrations/text_embedding/volcengine.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/text_embedding/volcengine.ipynb",
"repo_id": "langchain",
"token_count": 386
} | 176 |
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import {
BaseRetriever,
type BaseRetrieverInput,
type BaseRetrieverInterface,
} from "@langchain/core/retrievers";
import { Document } from "@langchain/core/documents";
import { BaseOutputParser } from "@langchain/core/output_... | langchainjs/langchain/src/retrievers/multi_query.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/multi_query.ts",
"repo_id": "langchainjs",
"token_count": 1807
} | 916 |
import pickle
import numpy as np
import pytest
from tokenizers import AddedToken, Encoding, Tokenizer
from tokenizers.implementations import BertWordPieceTokenizer
from tokenizers.models import BPE, Model, WordPiece, Unigram
from tokenizers.normalizers import Lowercase
from tokenizers.pre_tokenizers import ByteLevel
... | tokenizers/bindings/python/tests/bindings/test_tokenizer.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_tokenizer.py",
"repo_id": "tokenizers",
"token_count": 8984
} | 408 |
#![allow(dead_code)]
use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT};
use crate::{CpuStorage, DType, Error, Layout, Result, Shape};
#[derive(Debug, Clone)]
pub struct CudaDevice;
#[derive(Debug)]
pub struct CudaStorage;
macro_rules! fail {
() => {
unimplemented!("cuda support has not been enabled, ... | candle/candle-core/src/dummy_cuda_backend.rs/0 | {
"file_path": "candle/candle-core/src/dummy_cuda_backend.rs",
"repo_id": "candle",
"token_count": 2634
} | 30 |
import logging
from typing import Any, List
import requests
from llama_index.core.base.embeddings.base import BaseEmbedding
from requests.adapters import HTTPAdapter, Retry
logger = logging.getLogger(__name__)
class LLMRailsEmbedding(BaseEmbedding):
"""LLMRails embedding models.
This class provides an inte... | llama_index/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/llama_index/embeddings/llm_rails/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/llama_index/embeddings/llm_rails/base.py",
"repo_id": "llama_index",
"token_count": 1678
} | 1,280 |
from __future__ import annotations
from concurrent.futures import Executor
from typing import Any, ClassVar, Dict, Iterator, List, Optional, Union
import vertexai # type: ignore[import-untyped]
from google.api_core.client_options import ClientOptions
from google.cloud.aiplatform.gapic import (
PredictionServiceA... | langchain/libs/partners/google-vertexai/langchain_google_vertexai/llms.py/0 | {
"file_path": "langchain/libs/partners/google-vertexai/langchain_google_vertexai/llms.py",
"repo_id": "langchain",
"token_count": 9066
} | 629 |
from llama_index.readers.snscrape_twitter.base import SnscrapeTwitterReader
__all__ = ["SnscrapeTwitterReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-snscrape-twitter/llama_index/readers/snscrape_twitter/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-snscrape-twitter/llama_index/readers/snscrape_twitter/__init__.py",
"repo_id": "llama_index",
"token_count": 36
} | 1,421 |
import csv
import os
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _check_csv_dataset(dataset, expected_features):
ass... | datasets/tests/io/test_csv.py/0 | {
"file_path": "datasets/tests/io/test_csv.py",
"repo_id": "datasets",
"token_count": 2815
} | 140 |
python_sources()
| llama_index/llama-index-packs/llama-index-packs-fusion-retriever/llama_index/packs/fusion_retriever/query_rewrite/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-fusion-retriever/llama_index/packs/fusion_retriever/query_rewrite/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,702 |
"""Chain of table.
All prompts adapted from original paper by Wang et al.:
https://arxiv.org/pdf/2401.04398v1.pdf
"""
import re
from abc import abstractmethod
from typing import Any, Callable, Dict, List, Optional, Tuple
import pandas as pd
from llama_index.core.base.query_pipeline.query import QueryComponent
from ... | llama_index/llama-index-packs/llama-index-packs-tables/llama_index/packs/tables/chain_of_table/base.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-tables/llama_index/packs/tables/chain_of_table/base.py",
"repo_id": "llama_index",
"token_count": 10091
} | 1,689 |
<jupyter_start><jupyter_text>Evaluating Multi-Modal RAGIn this notebook guide, we'll demonstrate how to evaluate a Multi-Modal RAG system. As in the text-only case, we will consider the evaluation of Retrievers and Generators separately. As we alluded in our [blog](https://fix-me.link) on the topic of Evaluating Multi-... | llama_index/docs/examples/evaluation/multi_modal/multi_modal_rag_evaluation.ipynb/0 | {
"file_path": "llama_index/docs/examples/evaluation/multi_modal/multi_modal_rag_evaluation.ipynb",
"repo_id": "llama_index",
"token_count": 10057
} | 1,137 |
import { test, expect } from "@jest/globals";
import { YandexGPTEmbeddings } from "../embeddings.js";
test("Test YandexGPTEmbeddings.embedQuery", async () => {
const embeddings = new YandexGPTEmbeddings({
maxRetries: 1,
});
const res = await embeddings.embedQuery("Hello world");
expect(typeof res[0]).toBe(... | langchainjs/libs/langchain-yandex/src/tests/embeddings.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-yandex/src/tests/embeddings.int.test.ts",
"repo_id": "langchainjs",
"token_count": 240
} | 1,014 |
/**
* Copyright (c) Meta Platforms, Inc. and affiliates.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*
* @format
*/
/**
* Any CSS included here will be global. The classic template
* bundles Infima by default. Infima is a CSS fr... | langchainjs/docs/core_docs/src/css/custom.css/0 | {
"file_path": "langchainjs/docs/core_docs/src/css/custom.css",
"repo_id": "langchainjs",
"token_count": 2347
} | 802 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/src/transformers/data/data_collator.py/0 | {
"file_path": "transformers/src/transformers/data/data_collator.py",
"repo_id": "transformers",
"token_count": 32221
} | 551 |
package console
type ErrorCode = int
const (
NormalCode ErrorCode = 0
FailWithBackupUnfinished ErrorCode = 1
FailButBackupFinished ErrorCode = 2
Unexpected ErrorCode = 100
)
| milvus/cmd/tools/migration/console/code.go/0 | {
"file_path": "milvus/cmd/tools/migration/console/code.go",
"repo_id": "milvus",
"token_count": 87
} | 1,618 |
"""Init file."""
| llama_index/llama-index-legacy/tests/indices/keyword_table/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/keyword_table/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,734 |
import uuid
from collections import defaultdict
from typing import Any, Dict, List, Optional
from unittest.mock import Mock
class MockMongoCollection:
def __init__(self) -> None:
self._data: Dict[str, dict] = {}
def find_one(self, filter: dict) -> Optional[dict]:
for data in self._data.values... | llama_index/llama-index-legacy/tests/storage/kvstore/mock_mongodb.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/storage/kvstore/mock_mongodb.py",
"repo_id": "llama_index",
"token_count": 1282
} | 1,568 |
# DenseNet
**DenseNet** is a type of convolutional neural network that utilises dense connections between layers, through [Dense Blocks](http://www.paperswithcode.com/method/dense-block), where we connect *all layers* (with matching feature-map sizes) directly with each other. To preserve the feed-forward nature, each... | pytorch-image-models/hfdocs/source/models/densenet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/densenet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 4188
} | 376 |
# coding=utf-8
# Copyright 2023 Authors of "A Watermark for Large Language Models"
# available at https://arxiv.org/abs/2301.10226
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http... | text-generation-inference/server/text_generation_server/utils/watermark.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/watermark.py",
"repo_id": "text-generation-inference",
"token_count": 1489
} | 447 |
"""
Test of Astra DB document loader class `AstraDBLoader`
Required to run this test:
- a recent `astrapy` Python package available
- an Astra DB instance;
- the two environment variables set:
export ASTRA_DB_API_ENDPOINT="https://<DB-ID>-us-east1.apps.astra.datastax.com"
export ASTRA_DB_AP... | langchain/libs/community/tests/integration_tests/document_loaders/test_astradb.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/document_loaders/test_astradb.py",
"repo_id": "langchain",
"token_count": 2817
} | 339 |
# ResNeSt
A **ResNeSt** is a variant on a [ResNet](https://paperswithcode.com/method/resnet), which instead stacks [Split-Attention blocks](https://paperswithcode.com/method/split-attention). The cardinal group representations are then concatenated along the channel dimension: $V = \text{Concat}${$V^{1},V^{2},\cdots{V... | pytorch-image-models/docs/models/.templates/models/resnest.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/resnest.md",
"repo_id": "pytorch-image-models",
"token_count": 4643
} | 318 |
import argparse
import safetensors.torch
from diffusers import AutoencoderTiny
"""
Example - From the diffusers root directory:
Download the weights:
```sh
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd_encoder.safetensors
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd... | diffusers/scripts/convert_tiny_autoencoder_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_tiny_autoencoder_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 990
} | 229 |
from __future__ import annotations
import json
import logging
from typing import Any, List, Optional, Tuple
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from langchain_core.vectorstores import VectorStore
logger = logging.getLogger(__name__)
class Jaguar(VectorStor... | langchain/libs/community/langchain_community/vectorstores/jaguar.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/jaguar.py",
"repo_id": "langchain",
"token_count": 7505
} | 309 |
import argparse
import logging
import os
import sys
import time
import tensorflow as tf
from datasets import load_dataset
from tqdm import tqdm
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
from transformers.modeling_tf_utils import keras
from transformers.utils import is_sagemaker_dp_e... | transformers/tests/sagemaker/scripts/tensorflow/run_tf_dist.py/0 | {
"file_path": "transformers/tests/sagemaker/scripts/tensorflow/run_tf_dist.py",
"repo_id": "transformers",
"token_count": 3191
} | 835 |
"""Load question answering chains."""
from typing import Any, Mapping, Optional, Protocol
from langchain_core.callbacks import BaseCallbackManager, Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate
from langchain.chains import ReduceDocumentsC... | langchain/libs/langchain/langchain/chains/question_answering/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/question_answering/__init__.py",
"repo_id": "langchain",
"token_count": 3530
} | 473 |
# coding=utf-8
# Copyright 2021 Facebook AI Research (FAIR), Ross Wightman, The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.... | transformers/src/transformers/models/deit/modeling_deit.py/0 | {
"file_path": "transformers/src/transformers/models/deit/modeling_deit.py",
"repo_id": "transformers",
"token_count": 15850
} | 656 |
python_tests()
| llama_index/llama-index-integrations/readers/llama-index-readers-kibela/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-kibela/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,468 |
//! EfficientNet implementation.
//!
//! https://arxiv.org/abs/1905.11946
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle::{DType, IndexOp, D};
use candle_nn::{Module, VarBuilder};
use candle_transformers::models::efficientnet::{EfficientNet,... | candle/candle-examples/examples/efficientnet/main.rs/0 | {
"file_path": "candle/candle-examples/examples/efficientnet/main.rs",
"repo_id": "candle",
"token_count": 1414
} | 41 |
python_sources()
| llama_index/llama-index-integrations/agent/llama-index-agent-openai/llama_index/agent/openai/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/agent/llama-index-agent-openai/llama_index/agent/openai/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,178 |
# LlamaIndex Embeddings Integration: Huggingface
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-huggingface/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-huggingface/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,244 |
import { GoogleGenerativeAI, GenerativeModel } from "@google/generative-ai";
import type { TaskType, EmbedContentRequest } from "@google/generative-ai";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
import { chunkArray } fr... | langchainjs/libs/langchain-google-genai/src/embeddings.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-genai/src/embeddings.ts",
"repo_id": "langchainjs",
"token_count": 1813
} | 1,061 |
import logging
from .constants import *
_logger = logging.getLogger(__name__)
def resolve_data_config(
args=None,
pretrained_cfg=None,
model=None,
use_test_size=False,
verbose=False
):
assert model or args or pretrained_cfg, "At least one of model, args, or pretrained_cfg... | pytorch-image-models/timm/data/config.py/0 | {
"file_path": "pytorch-image-models/timm/data/config.py",
"repo_id": "pytorch-image-models",
"token_count": 1927
} | 326 |
<jupyter_start><jupyter_code>import chromadb
from chromadb.utils import embedding_functions
sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="all-MiniLM-L6-v2")
client = chromadb.Client()
# client.heartbeat()
# client.reset()
collection = client.get_or_create_collection(... | chroma/examples/basic_functionality/in_not_in_filtering.ipynb/0 | {
"file_path": "chroma/examples/basic_functionality/in_not_in_filtering.ipynb",
"repo_id": "chroma",
"token_count": 553
} | 36 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/util/wrappers/qn_wrapper_test.go/0 | {
"file_path": "milvus/internal/util/wrappers/qn_wrapper_test.go",
"repo_id": "milvus",
"token_count": 3648
} | 1,888 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/src/transformers/tokenization_utils_base.py/0 | {
"file_path": "transformers/src/transformers/tokenization_utils_base.py",
"repo_id": "transformers",
"token_count": 84984
} | 782 |
# flake8: noqa
ENDPOINT_DESCRIPTION = "Solve math word problems"
ENDPOINT_NAME = "math-problems"
INPUT_NAME = "input"
OUTPUT_KEY = "output"
NAME_FOR_MODEL = "MathWordProblems"
NAME_FOR_HUMAN = "Math Problems Solver"
DESCRIPTION_FOR_MODEL = "This plugin provides access to a LangChain Agent hooked up to a calculator, so ... | langchain-aiplugin/agent/constants.py/0 | {
"file_path": "langchain-aiplugin/agent/constants.py",
"repo_id": "langchain-aiplugin",
"token_count": 140
} | 60 |
python_sources()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-cassandra/llama_index/vector_stores/cassandra/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-cassandra/llama_index/vector_stores/cassandra/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,512 |
import { GoogleAuthOptions } from "google-auth-library";
import { BaseChatGoogleVertexAI, GoogleVertexAIChatInput } from "./common.js";
import { GoogleVertexAILLMConnection } from "../../utils/googlevertexai-connection.js";
import { GAuthClient } from "../../utils/googlevertexai-gauth.js";
/**
* Enables calls to the ... | langchainjs/libs/langchain-community/src/chat_models/googlevertexai/index.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/chat_models/googlevertexai/index.ts",
"repo_id": "langchainjs",
"token_count": 640
} | 992 |
<jupyter_start><jupyter_text>ModelScope>[ModelScope](https://www.modelscope.cn/home) is big repository of the models and datasets.Let's load the ModelScope Embedding class.<jupyter_code>from langchain_community.embeddings import ModelScopeEmbeddings
model_id = "damo/nlp_corom_sentence-embedding_english-base"
embeddings... | langchain/docs/docs/integrations/text_embedding/modelscope_hub.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/text_embedding/modelscope_hub.ipynb",
"repo_id": "langchain",
"token_count": 173
} | 177 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use std::str::FromStr;
use anyhow::Result;
use candle_core::{Device, Tensor};
fn cos_sin(n: usize, device: &Device) -> Result<Tensor> {
let thetas: Vec<_> = (0..n).map(|i| (i as f32 / n as f32)).colle... | candle/candle-core/examples/cuda_sum_benchmark.rs/0 | {
"file_path": "candle/candle-core/examples/cuda_sum_benchmark.rs",
"repo_id": "candle",
"token_count": 827
} | 33 |
from langchain.utilities import DuckDuckGoSearchAPIWrapper
from langchain_community.chat_models import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnables import Runnable... | langchain/templates/rewrite-retrieve-read/rewrite_retrieve_read/chain.py/0 | {
"file_path": "langchain/templates/rewrite-retrieve-read/rewrite_retrieve_read/chain.py",
"repo_id": "langchain",
"token_count": 441
} | 730 |
"""Tracers that record execution of LangChain runs."""
from langchain_core.tracers.langchain import LangChainTracer
from langchain_core.tracers.langchain_v1 import LangChainTracerV1
from langchain_core.tracers.stdout import (
ConsoleCallbackHandler,
FunctionCallbackHandler,
)
from langchain_community.callback... | langchain/libs/community/langchain_community/callbacks/tracers/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/callbacks/tracers/__init__.py",
"repo_id": "langchain",
"token_count": 169
} | 237 |
"""Util that calls WolframAlpha."""
from typing import Any, Dict, Optional
from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
from langchain_core.utils import get_from_dict_or_env
class WolframAlphaAPIWrapper(BaseModel):
"""Wrapper for Wolfram Alpha.
Docs for using:
1. Go to wolfra... | langchain/libs/community/langchain_community/utilities/wolfram_alpha.py/0 | {
"file_path": "langchain/libs/community/langchain_community/utilities/wolfram_alpha.py",
"repo_id": "langchain",
"token_count": 818
} | 304 |
import fs from "fs";
export async function isWriteable(directory: string): Promise<boolean> {
try {
await fs.promises.access(directory, (fs.constants || fs).W_OK);
return true;
} catch (err) {
return false;
}
}
| langchainjs/libs/create-langchain-integration/helpers/is-writeable.ts/0 | {
"file_path": "langchainjs/libs/create-langchain-integration/helpers/is-writeable.ts",
"repo_id": "langchainjs",
"token_count": 83
} | 954 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/tests/integration/minicluster_v2.go/0 | {
"file_path": "milvus/tests/integration/minicluster_v2.go",
"repo_id": "milvus",
"token_count": 3934
} | 1,959 |
<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# Traduction en cours. | transformers/docs/source/fr/in_translation.md/0 | {
"file_path": "transformers/docs/source/fr/in_translation.md",
"repo_id": "transformers",
"token_count": 54
} | 517 |
package memberlist_manager
import (
"errors"
"sync"
"time"
"github.com/chroma/chroma-coordinator/internal/common"
"github.com/pingcap/log"
"go.uber.org/zap"
v1 "k8s.io/api/core/v1"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
"k8s.io/apimachinery/pkg/labels"
"k8s.io/client-go/informers"
"k8s.io/client-go/... | chroma/go/coordinator/internal/memberlist_manager/node_watcher.go/0 | {
"file_path": "chroma/go/coordinator/internal/memberlist_manager/node_watcher.go",
"repo_id": "chroma",
"token_count": 1861
} | 44 |
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage } from "@langchain/core/messages";
// See https://cookbook.openai.com/examples/using_logprobs for details
const model = new ChatOpenAI({
logprobs: true,
// topLogprobs: 5,
});
const generations = await model.generate([[new HumanMessage("Hi ther... | langchainjs/examples/src/models/chat/integration_openai_generation_info.ts/0 | {
"file_path": "langchainjs/examples/src/models/chat/integration_openai_generation_info.ts",
"repo_id": "langchainjs",
"token_count": 1321
} | 868 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package session
import (
context "context"
commonpb "github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
milvuspb "github.com/milvus-io/milvus-proto/go-api/v2/milvuspb"
mock "github.com/stretchr/testify/mock"
querypb "github.com/milvus-io/milvus/internal/p... | milvus/internal/querycoordv2/session/mock_cluster.go/0 | {
"file_path": "milvus/internal/querycoordv2/session/mock_cluster.go",
"repo_id": "milvus",
"token_count": 9052
} | 1,982 |
"""ArangoDB client."""
from typing import Any, Dict, Iterator, List, Optional, Union, cast
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
class SimpleArangoDBReader(BaseReader):
"""Simple arangodb reader.
Concatenates each ArangoDB doc into Document used by... | llama_index/llama-index-integrations/readers/llama-index-readers-arango-db/llama_index/readers/arango_db/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-arango-db/llama_index/readers/arango_db/base.py",
"repo_id": "llama_index",
"token_count": 2506
} | 1,290 |
<jupyter_start><jupyter_text>Program-aided language model (PAL) chainImplements Program-Aided Language Models, as in https://arxiv.org/pdf/2211.10435.pdf.<jupyter_code>from langchain_experimental.pal_chain import PALChain
from langchain_openai import OpenAI
llm = OpenAI(temperature=0, max_tokens=512)<jupyter_output><em... | langchain/cookbook/program_aided_language_model.ipynb/0 | {
"file_path": "langchain/cookbook/program_aided_language_model.ipynb",
"repo_id": "langchain",
"token_count": 825
} | 79 |
import getpass
import os
from langchain.text_splitter import CharacterTextSplitter
from langchain_community.document_loaders import PyPDFLoader
from langchain_community.vectorstores import Milvus
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langch... | langchain/templates/nvidia-rag-canonical/nvidia_rag_canonical/chain.py/0 | {
"file_path": "langchain/templates/nvidia-rag-canonical/nvidia_rag_canonical/chain.py",
"repo_id": "langchain",
"token_count": 983
} | 702 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class CustomTokenizerFast(BertTokenizerFast):
slow_tokenizer_class = CustomTokenizer
pass
| transformers/utils/test_module/custom_tokenization_fast.py/0 | {
"file_path": "transformers/utils/test_module/custom_tokenization_fast.py",
"repo_id": "transformers",
"token_count": 54
} | 779 |
[build-system]
requires = [
"setuptools>=57.4.0",
"wheel>=0.37.0",
"transformers>=4.9.2"
]
build-backend = "setuptools.build_meta" | transformers/examples/research_projects/fsner/pyproject.toml/0 | {
"file_path": "transformers/examples/research_projects/fsner/pyproject.toml",
"repo_id": "transformers",
"token_count": 71
} | 542 |
# coding=utf-8
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/auto/test_modeling_tf_pytorch.py/0 | {
"file_path": "transformers/tests/models/auto/test_modeling_tf_pytorch.py",
"repo_id": "transformers",
"token_count": 4447
} | 767 |
"""Test AI21 llm"""
from typing import cast
from langchain_core.pydantic_v1 import SecretStr
from pytest import CaptureFixture, MonkeyPatch
from langchain_community.llms.ai21 import AI21
def test_api_key_is_secret_string() -> None:
llm = AI21(ai21_api_key="secret-api-key")
assert isinstance(llm.ai21_api_ke... | langchain/libs/community/tests/unit_tests/llms/test_ai21.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/llms/test_ai21.py",
"repo_id": "langchain",
"token_count": 496
} | 376 |
from unittest.mock import MagicMock, patch
from llama_index.core.graph_stores.types import GraphStore
from llama_index.graph_stores.nebula import NebulaGraphStore
@patch("llama_index.graph_stores.nebula.NebulaGraphStore")
def test_kuzu_graph_store(MockNebulaGraphStore: MagicMock):
instance: NebulaGraphStore = Mo... | llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-nebula/tests/test_graph_stores_nebula.py/0 | {
"file_path": "llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-nebula/tests/test_graph_stores_nebula.py",
"repo_id": "llama_index",
"token_count": 132
} | 1,207 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/extractors/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/extractors/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,592 |
# coding=utf-8
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/gptj/test_modeling_tf_gptj.py/0 | {
"file_path": "transformers/tests/models/gptj/test_modeling_tf_gptj.py",
"repo_id": "transformers",
"token_count": 8856
} | 749 |
"""Test agent functionality."""
| langchain/libs/langchain/tests/unit_tests/agents/__init__.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/agents/__init__.py",
"repo_id": "langchain",
"token_count": 7
} | 628 |
from langchain_community.utilities.dataforseo_api_search import DataForSeoAPIWrapper
__all__ = ["DataForSeoAPIWrapper"]
| langchain/libs/langchain/langchain/utilities/dataforseo_api_search.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utilities/dataforseo_api_search.py",
"repo_id": "langchain",
"token_count": 41
} | 616 |
# 🦜️🧑🤝🧑 LangChain Community
[](https://pepy.tech/project/langchain_community)
[](https://opensource.org/licenses/MIT)
## Quick Install
```bash
pip install langchain-communit... | langchain/libs/community/README.md/0 | {
"file_path": "langchain/libs/community/README.md",
"repo_id": "langchain",
"token_count": 371
} | 217 |
# Lilac reader
[Lilac](https://lilacml.com/) is an open-source product that helps you analyze, enrich, and clean unstructured data with AI.
It can be used to analyze, clean, structure, and label data that can be used in downstream LlamaIndex and LangChain applications.
## Lilac projects
This assumes you've already ... | llama_index/llama-index-integrations/readers/llama-index-readers-lilac/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-lilac/README.md",
"repo_id": "llama_index",
"token_count": 765
} | 1,514 |
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "huggingface/datasets"
authors:
- family-names: Lhoest
given-names: Quentin
- family-names: Villanova del Moral
given-names: Albert
orcid: "https://orcid.org/0000-0003-1727-1045"
- family-names: von Platen
given-names: Patri... | datasets/CITATION.cff/0 | {
"file_path": "datasets/CITATION.cff",
"repo_id": "datasets",
"token_count": 1428
} | 116 |
from abc import abstractmethod
from typing import Any, Dict, List, Optional, Sequence, get_args
from llama_index.legacy.bridge.pydantic import BaseModel, Field
from llama_index.legacy.constants import (
DEFAULT_CONTEXT_WINDOW,
DEFAULT_NUM_INPUT_FILES,
DEFAULT_NUM_OUTPUTS,
)
from llama_index.legacy.core.llm... | llama_index/llama-index-legacy/llama_index/legacy/multi_modal_llms/base.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/multi_modal_llms/base.py",
"repo_id": "llama_index",
"token_count": 3146
} | 1,582 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/owlvit.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/owlvit.md",
"repo_id": "transformers",
"token_count": 1986
} | 450 |
# Testing the notion markdownloader
# 🦜️🔗 LangChain.js
⚡ Building applications with LLMs through composability ⚡
**Production Support:** As you move your LangChains into production, we'd love to offer more comprehensive support.
Please fill out [this form](https://forms.gle/57d8AmXBYp8PP8tZA) and we'll set up a de... | langchainjs/examples/src/document_loaders/example_data/notion.md/0 | {
"file_path": "langchainjs/examples/src/document_loaders/example_data/notion.md",
"repo_id": "langchainjs",
"token_count": 471
} | 827 |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/src/transformers/models/donut/image_processing_donut.py/0 | {
"file_path": "transformers/src/transformers/models/donut/image_processing_donut.py",
"repo_id": "transformers",
"token_count": 9138
} | 597 |
from langchain_core.prompts import PromptTemplate
REFINE_PROMPT_TMPL = """\
Your job is to produce a final summary.
We have provided an existing summary up to a certain point: {existing_answer}
We have the opportunity to refine the existing summary (only if needed) with some more context below.
------------
{text}
---... | langchain/libs/langchain/langchain/chains/summarize/refine_prompts.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/summarize/refine_prompts.py",
"repo_id": "langchain",
"token_count": 192
} | 467 |
"""JSON Reader."""
import json
import re
from typing import Any, Generator, List, Optional
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
def _depth_first_yield(
json_data: Any,
levels_back: int,
collapse_length: Optional[int],
path: List[str],
... | llama_index/llama-index-legacy/llama_index/legacy/readers/json.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/json.py",
"repo_id": "llama_index",
"token_count": 2239
} | 1,705 |
# the proper usage is documented in the README, you need to specify data_dir, output_dir and model_name_or_path
# run ./finetune.sh --help to see all the possible options
python finetune.py \
--learning_rate=3e-5 \
--fp16 \
--gpus 1 \
--do_train \
--do_predict \
--n_val 1000 \
--val_check_in... | transformers/examples/research_projects/seq2seq-distillation/finetune.sh/0 | {
"file_path": "transformers/examples/research_projects/seq2seq-distillation/finetune.sh",
"repo_id": "transformers",
"token_count": 138
} | 602 |
"""Awadb reader."""
from typing import Any, List
import numpy as np
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class AwadbReader(BaseReader):
"""Awadb reader.
Retrieves documents through an existing awadb client.
These documents can then be us... | llama_index/llama-index-legacy/llama_index/legacy/readers/awadb.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/awadb.py",
"repo_id": "llama_index",
"token_count": 892
} | 1,701 |
<jupyter_start><jupyter_text>MilvusReader If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-readers-milvus
!pip install llama-index
import logging
import sys
import random
# Uncomment to see debug logs
# logging.basicConfig(stream=sys.stdou... | llama_index/docs/examples/data_connectors/MilvusReaderDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/data_connectors/MilvusReaderDemo.ipynb",
"repo_id": "llama_index",
"token_count": 253
} | 1,074 |
from llama_index.core.tools.tool_spec.base import BaseToolSpec
from llama_index.tools.azure_speech import AzureSpeechToolSpec
def test_class():
names_of_base_classes = [b.__name__ for b in AzureSpeechToolSpec.__mro__]
assert BaseToolSpec.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/tools/llama-index-tools-azure-speech/tests/test_tools_azure_speech.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-azure-speech/tests/test_tools_azure_speech.py",
"repo_id": "llama_index",
"token_count": 98
} | 1,505 |
from abc import abstractmethod
from typing import Any
from langchain.callbacks.manager import Callbacks
from langchain.chains.base import Chain
from langchain_experimental.plan_and_execute.schema import StepResponse
from langchain_experimental.pydantic_v1 import BaseModel
class BaseExecutor(BaseModel):
"""Base ... | langchain/libs/experimental/langchain_experimental/plan_and_execute/executors/base.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/plan_and_execute/executors/base.py",
"repo_id": "langchain",
"token_count": 462
} | 422 |
import { PortkeyChat } from "@langchain/community/chat_models/portkey";
import { SystemMessage } from "@langchain/core/messages";
export const run = async () => {
const model = new PortkeyChat({
mode: "single",
llms: [
{
provider: "openai",
virtual_key: "open-ai-key-1234",
model... | langchainjs/examples/src/llms/portkey-chat.ts/0 | {
"file_path": "langchainjs/examples/src/llms/portkey-chat.ts",
"repo_id": "langchainjs",
"token_count": 343
} | 823 |
"""Test the server and client together."""
import asyncio
import datetime
import json
from asyncio import AbstractEventLoop
from contextlib import asynccontextmanager, contextmanager
from dataclasses import dataclass
from enum import Enum
from itertools import cycle
from typing import (
Any,
Dict,
Iterable,... | langserve/tests/unit_tests/test_server_client.py/0 | {
"file_path": "langserve/tests/unit_tests/test_server_client.py",
"repo_id": "langserve",
"token_count": 44314
} | 1,007 |
from langchain.schema.storage import __all__
EXPECTED_ALL = ["BaseStore", "K", "V"]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
| langchain/libs/langchain/tests/unit_tests/schema/test_storage.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/schema/test_storage.py",
"repo_id": "langchain",
"token_count": 64
} | 673 |
"""Base embeddings file."""
import asyncio
from abc import abstractmethod
from typing import Coroutine, List, Tuple
from llama_index.core.base.embeddings.base import (
BaseEmbedding,
Embedding,
)
from llama_index.core.callbacks.schema import CBEventType, EventPayload
from llama_index.core.schema import ImageT... | llama_index/llama-index-core/llama_index/core/embeddings/multi_modal_base.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/embeddings/multi_modal_base.py",
"repo_id": "llama_index",
"token_count": 3409
} | 1,207 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/storage/event_writer.go/0 | {
"file_path": "milvus/internal/storage/event_writer.go",
"repo_id": "milvus",
"token_count": 3858
} | 1,870 |
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