text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
# LangChain google-gauth
This package contains resources to access Google AI/ML models
and other Google services. Authorization to these services use
either an API Key or service account credentials that are either
stored on the local file system or are provided through the
Google Cloud Platform environment it is runn... | langchainjs/libs/langchain-google-gauth/README.md/0 | {
"file_path": "langchainjs/libs/langchain-google-gauth/README.md",
"repo_id": "langchainjs",
"token_count": 396
} | 1,097 |
# coding=utf-8
# Copyright 2023 Toshiyuki Sakamoto(tanreinama) and 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
#
... | transformers/src/transformers/models/gptsan_japanese/modeling_gptsan_japanese.py/0 | {
"file_path": "transformers/src/transformers/models/gptsan_japanese/modeling_gptsan_japanese.py",
"repo_id": "transformers",
"token_count": 28611
} | 648 |
import functools
import importlib
import inspect
import io
import logging
import multiprocessing
import os
import random
import re
import struct
import sys
import tempfile
import time
import unittest
import urllib.parse
from contextlib import contextmanager
from distutils.util import strtobool
from io import BytesIO, S... | diffusers/src/diffusers/utils/testing_utils.py/0 | {
"file_path": "diffusers/src/diffusers/utils/testing_utils.py",
"repo_id": "diffusers",
"token_count": 14068
} | 268 |
@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo... | langchain/docs/api_reference/make.bat/0 | {
"file_path": "langchain/docs/api_reference/make.bat",
"repo_id": "langchain",
"token_count": 315
} | 84 |
<jupyter_start><jupyter_text>SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge BaseThis notebook demonstrates an implementation of a **Context-Aware** AI Sales agent with a Product Knowledge Base. This notebook was originally published at [filipmichalsky/SalesGPT](https://github.com/filip-michalsky/SalesG... | langchain/cookbook/sales_agent_with_context.ipynb/0 | {
"file_path": "langchain/cookbook/sales_agent_with_context.ipynb",
"repo_id": "langchain",
"token_count": 11415
} | 81 |
# mypy: disable-error-code=attr-defined
import copy
from random import random
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
from uuid import uuid4
import pytest
from langchain_core.documents import Document
from pytest_mock import MockerFixture
from langchain_community.vectorstores import ZepVect... | langchain/libs/community/tests/integration_tests/vectorstores/test_zep.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/vectorstores/test_zep.py",
"repo_id": "langchain",
"token_count": 2641
} | 389 |
import logging
import os
from typing import Any, Dict, List, Mapping, Optional
import requests
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from langchain_core.pydantic_v1 import Field
logger = logging.getLogger(__name__)
class Baseten(LLM):
"... | langchain/libs/community/langchain_community/llms/baseten.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/baseten.py",
"repo_id": "langchain",
"token_count": 1287
} | 277 |
"""Base embeddings file.
Maintain for backwards compatibility.
"""
from llama_index.legacy.core.embeddings.base import (
DEFAULT_EMBED_BATCH_SIZE,
BaseEmbedding,
Embedding,
SimilarityMode,
mean_agg,
similarity,
)
__all__ = [
"BaseEmbedding",
"similarity",
"SimilarityMode",
"D... | llama_index/llama-index-legacy/llama_index/legacy/embeddings/base.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/embeddings/base.py",
"repo_id": "llama_index",
"token_count": 167
} | 1,553 |
<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers as well as some other libraries. Uncomment the following cell and run it.<jupyter_code>#! pip install transformers evaluate datasets requests pandas sklearn<jupyter_output><empty_output><jupyter_text... | notebooks/examples/protein_language_modeling.ipynb/0 | {
"file_path": "notebooks/examples/protein_language_modeling.ipynb",
"repo_id": "notebooks",
"token_count": 7787
} | 324 |
from langchain_core.chat_history import BaseChatMessageHistory
__all__ = ["BaseChatMessageHistory"]
| langchain/libs/langchain/langchain/schema/chat_history.py/0 | {
"file_path": "langchain/libs/langchain/langchain/schema/chat_history.py",
"repo_id": "langchain",
"token_count": 27
} | 538 |
# for backwards compatibility
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
__all__ = [
"BaseQueryEngine",
]
| llama_index/llama-index-legacy/llama_index/legacy/indices/query/base.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/query/base.py",
"repo_id": "llama_index",
"token_count": 44
} | 1,575 |
#ifndef _q_gemm_cuh
#define _q_gemm_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
#include <ATen/cuda/CUDAContext.h>
#include "q_matrix.cuh"
void gemm_half_q_half_cuda
(
cublasHandle_t cublas_handle,
const half* a,
QMatrix* b,
half* c,
int size_m,
i... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm.cuh",
"repo_id": "text-generation-inference",
"token_count": 293
} | 378 |
import {
BaseRetriever,
type BaseRetrieverInput,
} from "@langchain/core/retrievers";
import { Document } from "@langchain/core/documents";
import { VectorStore } from "@langchain/core/vectorstores";
import { CallbackManagerForRetrieverRun } from "@langchain/core/callbacks/manager";
import { LLMChain } from "../../... | langchainjs/langchain/src/retrievers/self_query/index.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/self_query/index.ts",
"repo_id": "langchainjs",
"token_count": 1861
} | 1,010 |
# coding=utf-8
# Copyright 2022, Google and HuggingFace Inc.
#
# 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 applicab... | transformers/src/transformers/models/switch_transformers/configuration_switch_transformers.py/0 | {
"file_path": "transformers/src/transformers/models/switch_transformers/configuration_switch_transformers.py",
"repo_id": "transformers",
"token_count": 3660
} | 699 |
from typing import Any
from llama_index.legacy.core.llms.types import (
ChatMessage,
CompletionResponse,
CompletionResponseGen,
LLMMetadata,
)
from llama_index.legacy.llms.custom import CustomLLM
class TestLLM(CustomLLM):
__test__ = False
def __init__(self) -> None:
super().__init__(... | llama_index/llama-index-legacy/tests/llms/test_custom.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/llms/test_custom.py",
"repo_id": "llama_index",
"token_count": 764
} | 1,669 |
import argparse
import itertools
import math
import os
import random
from pathlib import Path
from typing import Iterable
import numpy as np
import PIL
import torch
import torch.nn.functional as F
import torch.utils.checkpoint
from accelerate import Accelerator
from accelerate.utils import ProjectConfiguration, set_se... | diffusers/examples/research_projects/intel_opts/textual_inversion_dfq/textual_inversion.py/0 | {
"file_path": "diffusers/examples/research_projects/intel_opts/textual_inversion_dfq/textual_inversion.py",
"repo_id": "diffusers",
"token_count": 18301
} | 226 |
---
hide_table_of_contents: true
---
import CodeBlock from "@theme/CodeBlock";
# Google Places Tool
The Google Places Tool allows your agent to utilize the Google Places API in order to find addresses,
phone numbers, website, etc. from text about a location listed on Google Places.
## Setup
You will need to get an... | langchainjs/docs/core_docs/docs/integrations/tools/google_places.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/tools/google_places.mdx",
"repo_id": "langchainjs",
"token_count": 294
} | 717 |
<!--Copyright 2024 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... | diffusers/docs/source/en/installation.md/0 | {
"file_path": "diffusers/docs/source/en/installation.md",
"repo_id": "diffusers",
"token_count": 1585
} | 184 |
import { test, expect } from "@jest/globals";
import {
JsonListKeysTool,
JsonSpec,
JsonGetValueTool,
} from "../../tools/json.js";
test("JsonListKeysTool", async () => {
const jsonSpec = new JsonSpec({
foo: "bar",
baz: { test: { foo: [1, 2, 3], qux: [{ x: 1, y: 2, z: 3 }, { a: 1 }] } },
});
const j... | langchainjs/langchain/src/agents/tests/json.test.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/tests/json.test.ts",
"repo_id": "langchainjs",
"token_count": 1747
} | 871 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from eli5_utils import (
embed_questions_for_retrieval,
make_qa_s2s_model,
qa_s2s_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impor... | transformers/examples/research_projects/longform-qa/eli5_app.py/0 | {
"file_path": "transformers/examples/research_projects/longform-qa/eli5_app.py",
"repo_id": "transformers",
"token_count": 5818
} | 579 |
"""NebulaGraph Query Engine Pack."""
import os
from enum import Enum
from typing import Any, Dict, List, Optional
from llama_index.core import (
KnowledgeGraphIndex,
QueryBundle,
ServiceContext,
StorageContext,
VectorStoreIndex,
get_response_synthesizer,
)
from llama_index.core.llama_pack.base... | llama_index/llama-index-packs/llama-index-packs-nebulagraph-query-engine/llama_index/packs/nebulagraph_query_engine/base.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-nebulagraph-query-engine/llama_index/packs/nebulagraph_query_engine/base.py",
"repo_id": "llama_index",
"token_count": 3533
} | 1,802 |
/* eslint-disable @typescript-eslint/no-explicit-any */
import { jest, test, expect } from "@jest/globals";
import { FakeEmbeddings } from "@langchain/core/utils/testing";
import { PineconeStore } from "../vectorstores.js";
test("PineconeStore with external ids", async () => {
const upsert = jest.fn();
const clien... | langchainjs/libs/langchain-pinecone/src/tests/vectorstores.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-pinecone/src/tests/vectorstores.test.ts",
"repo_id": "langchainjs",
"token_count": 1260
} | 1,041 |
// 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/core/src/storage/parquet_c.cpp/0 | {
"file_path": "milvus/internal/core/src/storage/parquet_c.cpp",
"repo_id": "milvus",
"token_count": 6656
} | 1,810 |
""" Random Erasing (Cutout)
Originally inspired by impl at https://github.com/zhunzhong07/Random-Erasing, Apache 2.0
Copyright Zhun Zhong & Liang Zheng
Hacked together by / Copyright 2019, Ross Wightman
"""
import random
import math
import torch
def _get_pixels(per_pixel, rand_color, patch_size, dtype=torch.float3... | pytorch-image-models/timm/data/random_erasing.py/0 | {
"file_path": "pytorch-image-models/timm/data/random_erasing.py",
"repo_id": "pytorch-image-models",
"token_count": 2258
} | 339 |
# LlamaIndex Readers Integration: File
| llama_index/llama-index-integrations/readers/llama-index-readers-file/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-file/README.md",
"repo_id": "llama_index",
"token_count": 9
} | 1,434 |
import { Redis, type RedisConfigNodejs } from "@upstash/redis";
import { Generation } from "@langchain/core/outputs";
import {
BaseCache,
deserializeStoredGeneration,
getCacheKey,
serializeGeneration,
} from "@langchain/core/caches";
import { StoredGeneration } from "@langchain/core/messages";
export type Ups... | langchainjs/libs/langchain-community/src/caches/upstash_redis.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/caches/upstash_redis.ts",
"repo_id": "langchainjs",
"token_count": 947
} | 947 |
from typing import Any, List
def _get_anthropic_client() -> Any:
try:
import anthropic
except ImportError:
raise ImportError(
"Could not import anthropic python package. "
"This is needed in order to accurately tokenize the text "
"for anthropic models. Plea... | langchain/libs/community/langchain_community/utilities/anthropic.py/0 | {
"file_path": "langchain/libs/community/langchain_community/utilities/anthropic.py",
"repo_id": "langchain",
"token_count": 317
} | 298 |
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
... | chroma/clients/js/LICENSE/0 | {
"file_path": "chroma/clients/js/LICENSE",
"repo_id": "chroma",
"token_count": 3168
} | 29 |
"""Init params."""
| llama_index/llama-index-legacy/tests/postprocessor/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/postprocessor/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,630 |
<!--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/zh/internal/modeling_utils.md/0 | {
"file_path": "transformers/docs/source/zh/internal/modeling_utils.md",
"repo_id": "transformers",
"token_count": 845
} | 549 |
import glob
import time
from yaml import full_load
import json
import pandas as pd
from utils.util_log import test_log as log
def gen_experiment_config(yaml):
"""load the yaml file of chaos experiment"""
with open(yaml) as f:
_config = full_load(f)
f.close()
return _config
def findkeys(no... | milvus/tests/python_client/utils/util_common.py/0 | {
"file_path": "milvus/tests/python_client/utils/util_common.py",
"repo_id": "milvus",
"token_count": 2037
} | 1,976 |
<!--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/en/model_doc/dialogpt.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/dialogpt.md",
"repo_id": "transformers",
"token_count": 789
} | 502 |
# Generated content DO NOT EDIT
from .. import functional
avg_pool2d = functional.avg_pool2d
gelu = functional.gelu
max_pool2d = functional.max_pool2d
relu = functional.relu
silu = functional.silu
softmax = functional.softmax
tanh = functional.tanh
| candle/candle-pyo3/py_src/candle/functional/__init__.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/functional/__init__.py",
"repo_id": "candle",
"token_count": 84
} | 72 |
import json
import uuid
from typing import List
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
from langchain_community.tools.nuclia.tool import NucliaUnderstandingAPI
class NucliaLoader(BaseLoader):
"""Load from any file type using `Nuclia Underst... | langchain/libs/community/langchain_community/document_loaders/nuclia.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/nuclia.py",
"repo_id": "langchain",
"token_count": 465
} | 260 |
import { test, expect, jest } from "@jest/globals";
import { HumanMessage, ToolMessage } from "@langchain/core/messages";
import { InMemoryCache } from "@langchain/core/caches";
import { ChatOpenAI } from "../chat_models.js";
test("Test ChatOpenAI JSON mode", async () => {
const chat = new ChatOpenAI({
modelName... | langchainjs/libs/langchain-openai/src/tests/chat_models-extended.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-openai/src/tests/chat_models-extended.int.test.ts",
"repo_id": "langchainjs",
"token_count": 2600
} | 1,105 |
import { OpenAI } from "@langchain/openai";
import { ConsoleCallbackHandler } from "@langchain/core/tracers/console";
const llm = new OpenAI({
temperature: 0,
// These tags will be attached to all calls made with this LLM.
tags: ["example", "callbacks", "constructor"],
// This handler will be used for all call... | langchainjs/examples/src/callbacks/docs_constructor_callbacks.ts/0 | {
"file_path": "langchainjs/examples/src/callbacks/docs_constructor_callbacks.ts",
"repo_id": "langchainjs",
"token_count": 112
} | 758 |
// 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/core/src/exec/Driver.cpp/0 | {
"file_path": "milvus/internal/core/src/exec/Driver.cpp",
"repo_id": "milvus",
"token_count": 7248
} | 1,642 |
"""
Develop integration packages for LangChain.
"""
import re
import shutil
import subprocess
from pathlib import Path
from typing import Optional
import typer
from typing_extensions import Annotated, TypedDict
from langchain_cli.utils.find_replace import replace_glob
integration_cli = typer.Typer(no_args_is_help=T... | langchain/libs/cli/langchain_cli/namespaces/integration.py/0 | {
"file_path": "langchain/libs/cli/langchain_cli/namespaces/integration.py",
"repo_id": "langchain",
"token_count": 1625
} | 209 |
# Module Guides
## Basic
First, check out our [module guide on Indexes](/module_guides/indexing/modules.md) for in-depth guides for each index (vector index, summary index, knowledge graph index). Each index corresponds to a default query engine for that index.
Then check out the rest of the sections below.
```{toc... | llama_index/docs/module_guides/deploying/query_engine/modules.md/0 | {
"file_path": "llama_index/docs/module_guides/deploying/query_engine/modules.md",
"repo_id": "llama_index",
"token_count": 852
} | 1,098 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "embeddings/tensorflow",
});
export * from "@langchain/community/embeddings/tensorflow";
| langchainjs/langchain/src/embeddings/tensorflow.ts/0 | {
"file_path": "langchainjs/langchain/src/embeddings/tensorflow.ts",
"repo_id": "langchainjs",
"token_count": 76
} | 917 |
"""Test the LangSmith client."""
import asyncio
import dataclasses
import gc
import itertools
import json
import os
import threading
import time
import uuid
import weakref
from datetime import datetime
from enum import Enum
from io import BytesIO
from typing import Any, NamedTuple, Optional
from unittest import mock
f... | langsmith-sdk/python/tests/unit_tests/test_client.py/0 | {
"file_path": "langsmith-sdk/python/tests/unit_tests/test_client.py",
"repo_id": "langsmith-sdk",
"token_count": 10665
} | 1,072 |
## The relevant files are currently on a shared Google
## drive at https://drive.google.com/drive/folders/1kC0I2UGl2ltrluI9NqDjaQJGw5iliw_J
## Monitor for changes and eventually migrate to use the `datasets` library
curl -L 'https://drive.google.com/uc?export=download&id=1Jjhbal535VVz2ap4v4r_rN1UEHTdLK5P' \
| grep -v "... | transformers/examples/legacy/token-classification/run.sh/0 | {
"file_path": "transformers/examples/legacy/token-classification/run.sh",
"repo_id": "transformers",
"token_count": 648
} | 584 |
import { test, expect } from "@jest/globals";
import { ChatOpenAI, OpenAIChat } from "@langchain/openai";
import { SystemMessage } from "@langchain/core/messages";
import { ConversationSummaryMemory } from "../summary.js";
test("Test summary memory", async () => {
const memory = new ConversationSummaryMemory({
l... | langchainjs/langchain/src/memory/tests/summary.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/memory/tests/summary.int.test.ts",
"repo_id": "langchainjs",
"token_count": 664
} | 972 |
// 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/crossclusterrouting/cross_cluster_routing_test.go/0 | {
"file_path": "milvus/tests/integration/crossclusterrouting/cross_cluster_routing_test.go",
"repo_id": "milvus",
"token_count": 1902
} | 1,980 |
/*
* 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... | milvus/pkg/mq/msgstream/msg_for_collection_test.go/0 | {
"file_path": "milvus/pkg/mq/msgstream/msg_for_collection_test.go",
"repo_id": "milvus",
"token_count": 1762
} | 1,819 |
<jupyter_start><jupyter_text>IFTTT WebHooksThis notebook shows how to use IFTTT Webhooks.From https://github.com/SidU/teams-langchain-js/wiki/Connecting-IFTTT-Services. Creating a webhook- Go to https://ifttt.com/create Configuring the "If This"- Click on the "If This" button in the IFTTT interface.- Search for "Webhoo... | langchain/docs/docs/integrations/tools/ifttt.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/ifttt.ipynb",
"repo_id": "langchain",
"token_count": 575
} | 175 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# 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 ag... | diffusers/tests/pipelines/text_to_video_synthesis/test_text_to_video_zero_sdxl.py/0 | {
"file_path": "diffusers/tests/pipelines/text_to_video_synthesis/test_text_to_video_zero_sdxl.py",
"repo_id": "diffusers",
"token_count": 7187
} | 286 |
<jupyter_start><jupyter_text>Exact Match[](https://colab.research.google.com/github/langchain-ai/langchain/blob/master/docs/docs/guides/evaluation/string/exact_match.ipynb)Probably the simplest ways to evaluate an LLM or runnable's string output against a reference label is by a simple string equivalence.This can be ac... | langchain/docs/docs/guides/evaluation/string/exact_match.ipynb/0 | {
"file_path": "langchain/docs/docs/guides/evaluation/string/exact_match.ipynb",
"repo_id": "langchain",
"token_count": 453
} | 90 |
use anyhow::Result;
use candle_core::{DType, Device::Cpu, Tensor};
#[test]
fn display_scalar() -> Result<()> {
let t = Tensor::new(1234u32, &Cpu)?;
let s = format!("{t}");
assert_eq!(&s, "[1234]\nTensor[[], u32]");
let t = t.to_dtype(DType::F32)?.neg()?;
let s = format!("{}", (&t / 10.0)?);
ass... | candle/candle-core/tests/display_tests.rs/0 | {
"file_path": "candle/candle-core/tests/display_tests.rs",
"repo_id": "candle",
"token_count": 1395
} | 34 |
libdir=@CMAKE_INSTALL_FULL_LIBDIR@
includedir=@CMAKE_INSTALL_FULL_INCLUDEDIR@
Name: Rocksdb
Description: Rocksdb
Version: @ROCKSDB_VERSION@
Libs: -L${libdir} -lrocksdb
Libs.private: -lz -lbz2
Cflags: -I${includedir}
| milvus/internal/core/thirdparty/rocksdb/rocksdb.pc.in/0 | {
"file_path": "milvus/internal/core/thirdparty/rocksdb/rocksdb.pc.in",
"repo_id": "milvus",
"token_count": 101
} | 1,671 |
const fs = require("node:fs/promises");
const { glob } = require("glob");
async function main() {
const allIpynb = await glob("./docs/**/*.ipynb");
// iterate over each & rename to `.mdx` if a `.md` already exists
const renamePromise = allIpynb.flatMap(async (ipynb) => {
const md = ipynb.replace(".ipynb", ".... | langchainjs/docs/core_docs/scripts/quatro-build.js/0 | {
"file_path": "langchainjs/docs/core_docs/scripts/quatro-build.js",
"repo_id": "langchainjs",
"token_count": 651
} | 746 |
from langchain_core.stores import BaseStore, K, V
__all__ = ["BaseStore", "K", "V"]
| langchain/libs/langchain/langchain/schema/storage.py/0 | {
"file_path": "langchain/libs/langchain/langchain/schema/storage.py",
"repo_id": "langchain",
"token_count": 31
} | 550 |
// 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/proxy/management_test.go/0 | {
"file_path": "milvus/internal/proxy/management_test.go",
"repo_id": "milvus",
"token_count": 1978
} | 1,739 |
from typing import (
Any,
AsyncIterator,
Awaitable,
Callable,
Iterator,
List,
Mapping,
Optional,
Sequence,
Tuple,
Type,
Union,
cast,
)
from langchain_core.load.dump import dumpd
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnables.base impor... | langchain/libs/core/langchain_core/runnables/branch.py/0 | {
"file_path": "langchain/libs/core/langchain_core/runnables/branch.py",
"repo_id": "langchain",
"token_count": 8017
} | 397 |
# vertexai-chuck-norris
This template makes jokes about Chuck Norris using Vertex AI PaLM2.
## Environment Setup
First, make sure you have a Google Cloud project with
an active billing account, and have the [gcloud CLI installed](https://cloud.google.com/sdk/docs/install).
Configure [application default credentia... | langchain/templates/vertexai-chuck-norris/README.md/0 | {
"file_path": "langchain/templates/vertexai-chuck-norris/README.md",
"repo_id": "langchain",
"token_count": 813
} | 759 |
import enum
# Before Python 3.11 native StrEnum is not available
class StrEnum(str, enum.Enum):
"""A string enum."""
pass
| langgraph/langgraph/utils.py/0 | {
"file_path": "langgraph/langgraph/utils.py",
"repo_id": "langgraph",
"token_count": 46
} | 1,006 |
""" Adan Optimizer
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models[J]. arXiv preprint arXiv:2208.06677, 2022.
https://arxiv.org/abs/2208.06677
Implementation adapted from https://github.com/sail-sg/Adan
"""
import math
import torch
from torch.optim import Optimizer
class Adan(Opt... | pytorch-image-models/timm/optim/adan.py/0 | {
"file_path": "pytorch-image-models/timm/optim/adan.py",
"repo_id": "pytorch-image-models",
"token_count": 2501
} | 361 |
"""Chroma Auto-retrieval Pack."""
from typing import Any, Dict, List, Optional
from llama_index.core.indices.vector_store import VectorStoreIndex
from llama_index.core.indices.vector_store.retrievers import (
VectorIndexAutoRetriever,
)
from llama_index.core.llama_pack.base import BaseLlamaPack
from llama_index.... | llama_index/llama-index-packs/llama-index-packs-chroma-autoretrieval/llama_index/packs/chroma_autoretrieval/base.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-chroma-autoretrieval/llama_index/packs/chroma_autoretrieval/base.py",
"repo_id": "llama_index",
"token_count": 1034
} | 1,776 |
from llama_index.readers.earnings_call_transcript.base import EarningsCallTranscript
__all__ = ["EarningsCallTranscript"]
| llama_index/llama-index-integrations/readers/llama-index-readers-earnings-call-transcript/llama_index/readers/earnings_call_transcript/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-earnings-call-transcript/llama_index/readers/earnings_call_transcript/__init__.py",
"repo_id": "llama_index",
"token_count": 38
} | 1,286 |
# Copyright 2024 Peter Willemsen <peter@codebuffet.co>. 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 requ... | diffusers/examples/community/tiled_upscaling.py/0 | {
"file_path": "diffusers/examples/community/tiled_upscaling.py",
"repo_id": "diffusers",
"token_count": 5904
} | 191 |
syntax = "proto3";
package chroma;
option go_package = "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb";
import "chromadb/proto/chroma.proto";
import "google/protobuf/empty.proto";
message CreateDatabaseRequest {
string id = 1;
string name = 2;
string tenant = 3;
}
message GetDatabaseReques... | chroma/idl/chromadb/proto/coordinator.proto/0 | {
"file_path": "chroma/idl/chromadb/proto/coordinator.proto",
"repo_id": "chroma",
"token_count": 1020
} | 52 |
# Reddit Reader
For any subreddit(s) you're interested in, search for relevant posts using keyword(s) and load the resulting text in the post and and top-level comments into LLMs/ LangChains.
## Get your Reddit credentials ready
1. Visit Reddit App Preferences (https://www.reddit.com/prefs/apps) or [https://old.redd... | llama_index/llama-index-integrations/readers/llama-index-readers-reddit/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-reddit/README.md",
"repo_id": "llama_index",
"token_count": 819
} | 1,372 |
"""Simple file node parser."""
from typing import Any, Dict, List, Optional, Sequence, Type
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.node_parser.file.html import HTMLNodeParser
from llama_index.legacy.node_parser.file.json import JSONNodeParser
from llama_index.legacy.node... | llama_index/llama-index-legacy/llama_index/legacy/node_parser/file/simple_file.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/node_parser/file/simple_file.py",
"repo_id": "llama_index",
"token_count": 1157
} | 1,583 |
# coding=utf-8
# Copyright 2020 The Google AI Language Team Authors, The HuggingFace Inc. team and Microsoft Corporation.
# Copyright (c) 2018, NVIDIA CORPORATION. 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.... | transformers/examples/research_projects/bert-loses-patience/pabee/modeling_pabee_bert.py/0 | {
"file_path": "transformers/examples/research_projects/bert-loses-patience/pabee/modeling_pabee_bert.py",
"repo_id": "transformers",
"token_count": 6750
} | 530 |
# AlephAlpha
LangChain.js supports AlephAlpha's Luminous family of models. You'll need to sign up for an API key [on their website](https://www.aleph-alpha.com/).
Here's an example:
import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
<IntegrationInstallTooltip></IntegrationInsta... | langchainjs/docs/core_docs/docs/integrations/llms/aleph_alpha.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/llms/aleph_alpha.mdx",
"repo_id": "langchainjs",
"token_count": 175
} | 783 |
"""Default query for EmptyIndex."""
from typing import Any, List, Optional
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.callbacks.base import CallbackManager
from llama_index.core.indices.empty.base import EmptyIndex
from llama_index.core.prompts import BasePromptTemplate
from l... | llama_index/llama-index-core/llama_index/core/indices/empty/retrievers.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/empty/retrievers.py",
"repo_id": "llama_index",
"token_count": 488
} | 1,127 |
// Copyright (C) 2019-2023 Zilliz. 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 l... | milvus/internal/core/src/simd/neon.cpp/0 | {
"file_path": "milvus/internal/core/src/simd/neon.cpp",
"repo_id": "milvus",
"token_count": 1544
} | 1,741 |
"""Mock LLM Predictor."""
from typing import Any, Dict
from deprecated import deprecated
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.constants import DEFAULT_NUM_OUTPUTS
from llama_index.legacy.core.llms.types... | llama_index/llama-index-legacy/llama_index/legacy/llm_predictor/mock.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/llm_predictor/mock.py",
"repo_id": "llama_index",
"token_count": 2339
} | 1,675 |
<!--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/xlm-roberta-xl.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/xlm-roberta-xl.md",
"repo_id": "transformers",
"token_count": 969
} | 523 |
import unittest
import torch
from transformers import AutoTokenizer, GenerationConfig
from trl import AutoModelForCausalLMWithValueHead
from trl.core import LengthSampler
from trl.extras import BestOfNSampler
def queries_to_scores(list_of_strings):
return [torch.rand(1).item() for _ in list_of_strings]
class ... | trl/tests/test_best_of_n_sampler.py/0 | {
"file_path": "trl/tests/test_best_of_n_sampler.py",
"repo_id": "trl",
"token_count": 1507
} | 789 |
{
"name": "test-exports-tsc",
"version": "0.0.0",
"type": "module",
"workspaces": [
"libs/*"
],
"private": true,
"description": "TSC Tests for the things exported by the langchain package",
"main": "./index.mjs",
"scripts": {
"build": "tsc -m nodenext main.ts",
"test": "node ./main.js"
}... | langchainjs/environment_tests/test-exports-tsc/package.json/0 | {
"file_path": "langchainjs/environment_tests/test-exports-tsc/package.json",
"repo_id": "langchainjs",
"token_count": 303
} | 752 |
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, List
from langchain_core.callbacks import (
AsyncCallbackManagerForRetrieverRun,
CallbackManagerForRetrieverRun,
)
from langchain_core.documents import Document
from langchain_core.language_models.chat_models import BaseChatModel
... | langchain/libs/community/langchain_community/retrievers/cohere_rag_retriever.py/0 | {
"file_path": "langchain/libs/community/langchain_community/retrievers/cohere_rag_retriever.py",
"repo_id": "langchain",
"token_count": 1222
} | 276 |
from langchain_community.chat_models.databricks import ChatDatabricks
__all__ = ["ChatDatabricks"]
| langchain/libs/langchain/langchain/chat_models/databricks.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chat_models/databricks.py",
"repo_id": "langchain",
"token_count": 31
} | 479 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/indices/composability/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/composability/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,713 |
from langchain_community.chat_models.baichuan import (
ChatBaichuan,
)
__all__ = [
"ChatBaichuan",
]
| langchain/libs/langchain/langchain/chat_models/baichuan.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chat_models/baichuan.py",
"repo_id": "langchain",
"token_count": 46
} | 516 |
# langchain-robocorp
This package contains the LangChain integrations for [Robocorp](https://github.com/robocorp/robocorp).
## Installation
```bash
pip install -U langchain-robocorp
```
## Action Server Toolkit
See [ActionServerToolkit](https://python.langchain.com/docs/integrations/toolkits/robocorp) for detailed... | langchain/libs/partners/robocorp/README.md/0 | {
"file_path": "langchain/libs/partners/robocorp/README.md",
"repo_id": "langchain",
"token_count": 104
} | 640 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-uptrain/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-uptrain/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,171 |
# agent runner + agent worker
from llama_index.core.agent.custom.pipeline_worker import QueryPipelineAgentWorker
from llama_index.core.agent.custom.simple import CustomSimpleAgentWorker
from llama_index.core.agent.react.base import ReActAgent
from llama_index.core.agent.react.formatter import ReActChatFormatter
from ll... | llama_index/llama-index-core/llama_index/core/agent/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/agent/__init__.py",
"repo_id": "llama_index",
"token_count": 336
} | 1,173 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
URL = "http://www.mocksite.com/file1.txt"
CONTENT = '"text": ["foo", "fo... | datasets/tests/test_download_manager.py/0 | {
"file_path": "datasets/tests/test_download_manager.py",
"repo_id": "datasets",
"token_count": 2407
} | 143 |
from typing import Iterator, List, Optional
from langchain_community.docstore.document import Document
from langchain_community.document_loaders.base import BaseLoader
from langchain_community.document_loaders.unstructured import UnstructuredFileIOLoader
class AzureAIDataLoader(BaseLoader):
"""Load from Azure AI... | langchain/libs/community/langchain_community/document_loaders/azure_ai_data.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/azure_ai_data.py",
"repo_id": "langchain",
"token_count": 630
} | 231 |
import { ChatOpenAI } from "@langchain/openai";
import { PromptTemplate } from "@langchain/core/prompts";
const model = new ChatOpenAI({});
const promptTemplate = PromptTemplate.fromTemplate(
"Tell me a joke about {topic}"
);
const chain = promptTemplate.pipe(model);
const stream = await chain.stream({ topic: "bea... | langchainjs/examples/src/guides/expression_language/interface_stream.ts/0 | {
"file_path": "langchainjs/examples/src/guides/expression_language/interface_stream.ts",
"repo_id": "langchainjs",
"token_count": 154
} | 809 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.chroma import ChromaReader
def test_class():
names_of_base_classes = [b.__name__ for b in ChromaReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-chroma/tests/test_readers_chroma.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-chroma/tests/test_readers_chroma.py",
"repo_id": "llama_index",
"token_count": 88
} | 1,347 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-semanticscholar/llama_index/readers/semanticscholar/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-semanticscholar/llama_index/readers/semanticscholar/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,551 |
"""Playwright web browser toolkit."""
from __future__ import annotations
from typing import TYPE_CHECKING, List, Optional, Type, cast
from langchain_core.pydantic_v1 import Extra, root_validator
from langchain_core.tools import BaseTool
from langchain_community.agent_toolkits.base import BaseToolkit
from langchain_c... | langchain/libs/community/langchain_community/agent_toolkits/playwright/toolkit.py/0 | {
"file_path": "langchain/libs/community/langchain_community/agent_toolkits/playwright/toolkit.py",
"repo_id": "langchain",
"token_count": 1478
} | 227 |
import argparse
import logging
import os
import sys
import tensorflow as tf
from datasets import load_dataset
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification, DataCollatorWithPadding, create_optimizer
if __name__ == "__main__":
parser = argparse.ArgumentParser()
# Hyperparamete... | notebooks/sagemaker/02_getting_started_tensorflow/scripts/train.py/0 | {
"file_path": "notebooks/sagemaker/02_getting_started_tensorflow/scripts/train.py",
"repo_id": "notebooks",
"token_count": 1677
} | 311 |
from sql_llamacpp.chain import chain
__all__ = ["chain"]
| langchain/templates/sql-llamacpp/sql_llamacpp/__init__.py/0 | {
"file_path": "langchain/templates/sql-llamacpp/sql_llamacpp/__init__.py",
"repo_id": "langchain",
"token_count": 20
} | 703 |
"""Init params."""
from llama_index.finetuning.embeddings.adapter import EmbeddingAdapterFinetuneEngine
from llama_index.finetuning.embeddings.sentence_transformer import (
SentenceTransformersFinetuneEngine,
)
__all__ = ["EmbeddingAdapterFinetuneEngine", "SentenceTransformersFinetuneEngine"]
| llama_index/llama-index-finetuning/llama_index/finetuning/embeddings/__init__.py/0 | {
"file_path": "llama_index/llama-index-finetuning/llama_index/finetuning/embeddings/__init__.py",
"repo_id": "llama_index",
"token_count": 95
} | 1,252 |
# coding=utf-8
# Copyright 2022 SHI Labs and 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... | transformers/src/transformers/models/nat/modeling_nat.py/0 | {
"file_path": "transformers/src/transformers/models/nat/modeling_nat.py",
"repo_id": "transformers",
"token_count": 16471
} | 720 |
# Time Travel Implementation (Segment Level)
Currently， there are two paths to implement time travel:
1. Restrict with vec_count, used in growing segment.
2. Generate bitmask and combine it with DSL calculation results. It is mainly used in the sealed segment.
## Growing Segment Time Travel
1. When inserting, ensure... | milvus/docs/design_docs/segcore/timetravel.md/0 | {
"file_path": "milvus/docs/design_docs/segcore/timetravel.md",
"repo_id": "milvus",
"token_count": 357
} | 1,908 |
"""Vector-store based data structures."""
from llama_index.legacy.indices.multi_modal.base import MultiModalVectorStoreIndex
from llama_index.legacy.indices.multi_modal.retriever import (
MultiModalVectorIndexRetriever,
)
__all__ = [
"MultiModalVectorStoreIndex",
"MultiModalVectorIndexRetriever",
]
| llama_index/llama-index-legacy/llama_index/legacy/indices/multi_modal/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/multi_modal/__init__.py",
"repo_id": "llama_index",
"token_count": 110
} | 1,563 |
// 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/channel_checker_test.go/0 | {
"file_path": "milvus/internal/datacoord/channel_checker_test.go",
"repo_id": "milvus",
"token_count": 3007
} | 1,824 |
# Copyright 2024 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... | diffusers/src/diffusers/pipelines/stable_diffusion/safety_checker_flax.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/safety_checker_flax.py",
"repo_id": "diffusers",
"token_count": 1822
} | 263 |
import { test } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import { OpenAIEmbeddings, OpenAI } from "@langchain/openai";
import { Chroma } from "@langchain/community/vectorstores/chroma";
import { AttributeInfo } from "../../../schema/query_constructor.js";
import { SelfQueryRetriever }... | langchainjs/langchain/src/retrievers/self_query/tests/chroma_self_query.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/self_query/tests/chroma_self_query.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1196
} | 930 |
# coding=utf-8
# Copyright 2019-present, 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 a... | transformers/examples/research_projects/distillation/scripts/token_counts.py/0 | {
"file_path": "transformers/examples/research_projects/distillation/scripts/token_counts.py",
"repo_id": "transformers",
"token_count": 725
} | 560 |
# 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/tests/trainer/test_trainer_seq2seq.py/0 | {
"file_path": "transformers/tests/trainer/test_trainer_seq2seq.py",
"repo_id": "transformers",
"token_count": 3232
} | 863 |
# WatsonX AI
LangChain.js supports integration with IBM WatsonX AI. Checkout [WatsonX AI](https://www.ibm.com/products/watsonx-ai) for a list of available models.
## Setup
You will need to set the following environment variables for using the WatsonX AI API.
1. `IBM_CLOUD_API_KEY` which can be generated via [IBM Cl... | langchainjs/docs/core_docs/docs/integrations/llms/watsonx_ai.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/llms/watsonx_ai.mdx",
"repo_id": "langchainjs",
"token_count": 372
} | 732 |
<jupyter_start><jupyter_text>Cloudflare Workers AI[Cloudflare AI documentation](https://developers.cloudflare.com/workers-ai/models/text-generation/) listed all generative text models available.Both Cloudflare account ID and API token are required. Find how to obtain them from [this document](https://developers.cloudfl... | langchain/docs/docs/integrations/llms/cloudflare_workersai.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/cloudflare_workersai.ipynb",
"repo_id": "langchain",
"token_count": 770
} | 120 |
# coding=utf-8
# Copyright 2018 Google AI, Google Brain and 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
#
# U... | transformers/src/transformers/models/albert/tokenization_albert.py/0 | {
"file_path": "transformers/src/transformers/models/albert/tokenization_albert.py",
"repo_id": "transformers",
"token_count": 6859
} | 630 |
// 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/pkg/util/funcutil/parallel.go/0 | {
"file_path": "milvus/pkg/util/funcutil/parallel.go",
"repo_id": "milvus",
"token_count": 1924
} | 1,827 |
// 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/segments/plan.go/0 | {
"file_path": "milvus/internal/querynodev2/segments/plan.go",
"repo_id": "milvus",
"token_count": 2119
} | 1,911 |
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