text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import { ToolInterface } from "@langchain/core/tools";
import { PromptTemplate, renderTemplate } from "@langchain/core/prompts";
import { LLMChain } from "../../chains/llm_chain.js";
import { Optional } from "../../types/type-utils.... | langchainjs/langchain/src/agents/mrkl/index.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/mrkl/index.ts",
"repo_id": "langchainjs",
"token_count": 2110
} | 914 |
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.packs.multi_document_agents import MultiDocumentAgentsPack
def test_class():
names_of_base_classes = [b.__name__ for b in MultiDocumentAgentsPack.__mro__]
assert BaseLlamaPack.__name__ in names_of_base_classes
| llama_index/llama-index-packs/llama-index-packs-multi-document-agents/tests/test_packs_multi_document_agents.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-multi-document-agents/tests/test_packs_multi_document_agents.py",
"repo_id": "llama_index",
"token_count": 100
} | 1,679 |
version: '3'
services:
opensearch-node1: # This is also the hostname of the container within the Docker network (i.e. http://opensearch-node1/)
image: opensearchproject/opensearch:2.10.0
container_name: opensearch-node1
environment:
- node.name=opensearch-node1 # Name the node that will run in this ... | langchain/libs/community/tests/integration_tests/vectorstores/docker-compose/opensearch/opensearch.yml/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/vectorstores/docker-compose/opensearch/opensearch.yml",
"repo_id": "langchain",
"token_count": 553
} | 355 |
"""Base schema for callback managers."""
import uuid
from dataclasses import dataclass
from datetime import datetime
from enum import Enum
from typing import Any, Dict, Optional
# timestamp for callback events
TIMESTAMP_FORMAT = "%m/%d/%Y, %H:%M:%S.%f"
# base trace_id for the tracemap in callback_manager
BASE_TRACE_E... | llama_index/llama-index-core/llama_index/core/callbacks/schema.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/callbacks/schema.py",
"repo_id": "llama_index",
"token_count": 1324
} | 1,164 |
import os
import pytest
from typing import Iterable
import astrapy
from llama_index.core.schema import NodeRelationship, RelatedNodeInfo, TextNode
from llama_index.core.vector_stores.types import VectorStoreQuery
from llama_index.vector_stores.astra import AstraDBVectorStore
print(f"astrapy detected: {astrapy.__versi... | llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-astra/tests/test_astra.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-astra/tests/test_astra.py",
"repo_id": "llama_index",
"token_count": 775
} | 1,509 |
// 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/index/StringIndexMarisa.h/0 | {
"file_path": "milvus/internal/core/src/index/StringIndexMarisa.h",
"repo_id": "milvus",
"token_count": 1360
} | 1,647 |
import asyncio
from abc import abstractmethod
from typing import Any, Dict, List, Optional, Sequence, Tuple, cast
import pandas as pd
from tqdm import tqdm
from llama_index.legacy.async_utils import DEFAULT_NUM_WORKERS, run_jobs
from llama_index.legacy.bridge.pydantic import BaseModel, Field, ValidationError
from lla... | llama_index/llama-index-legacy/llama_index/legacy/node_parser/relational/base_element.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/node_parser/relational/base_element.py",
"repo_id": "llama_index",
"token_count": 5871
} | 1,594 |
__all__ = ["LoggingCallbackHandler"]
import logging
from typing import Any, Optional
from uuid import UUID
from langchain_core.exceptions import TracerException
from langchain_core.tracers.stdout import FunctionCallbackHandler
from langchain_core.utils.input import get_bolded_text, get_colored_text
class LoggingCal... | langchain/libs/langchain/langchain/callbacks/tracers/logging.py/0 | {
"file_path": "langchain/libs/langchain/langchain/callbacks/tracers/logging.py",
"repo_id": "langchain",
"token_count": 609
} | 477 |
"""Implement integration tests for AstraDB storage."""
import os
import pytest
from langchain_community.storage.astradb import AstraDBByteStore, AstraDBStore
def _has_env_vars() -> bool:
return all(
[
"ASTRA_DB_APPLICATION_TOKEN" in os.environ,
"ASTRA_DB_API_ENDPOINT" in os.envir... | langchain/libs/community/tests/integration_tests/storage/test_astradb.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/storage/test_astradb.py",
"repo_id": "langchain",
"token_count": 1990
} | 378 |
import time
from typing import Dict, Generator, Union
import docker
import pytest
from docker.models.containers import Container
from llama_index.legacy.storage.kvstore.firestore_kvstore import FirestoreKVStore
from llama_index.legacy.storage.kvstore.mongodb_kvstore import MongoDBKVStore
from llama_index.legacy.storag... | llama_index/llama-index-legacy/tests/storage/conftest.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/storage/conftest.py",
"repo_id": "llama_index",
"token_count": 1428
} | 1,546 |
# coding=utf-8
# Copyright 2018 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.py/0 | {
"file_path": "transformers/tests/trainer/test_trainer.py",
"repo_id": "transformers",
"token_count": 66075
} | 768 |
<jupyter_start><jupyter_text>Firestore DemoThis guide shows you how to directly use our `DocumentStore` abstraction backed by Google Firestore. By putting nodes in the docstore, this allows you to define multiple indices over the same underlying docstore, instead of duplicating data across indices. If you're opening th... | llama_index/docs/examples/docstore/FirestoreDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/docstore/FirestoreDemo.ipynb",
"repo_id": "llama_index",
"token_count": 1426
} | 1,051 |
<!--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/api/pipelines/stable_diffusion/stable_diffusion_xl.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_xl.md",
"repo_id": "diffusers",
"token_count": 1005
} | 176 |
// 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/logutil/logutil.go/0 | {
"file_path": "milvus/pkg/util/logutil/logutil.go",
"repo_id": "milvus",
"token_count": 1571
} | 2,061 |
# 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/vit_hybrid/configuration_vit_hybrid.py/0 | {
"file_path": "transformers/src/transformers/models/vit_hybrid/configuration_vit_hybrid.py",
"repo_id": "transformers",
"token_count": 3255
} | 763 |
"""Vector stores."""
from llama_index.core.vector_stores.simple import SimpleVectorStore
from llama_index.core.vector_stores.types import (
ExactMatchFilter,
FilterCondition,
FilterOperator,
MetadataFilter,
MetadataFilters,
VectorStoreQuery,
VectorStoreQueryResult,
)
__all__ = [
"Vect... | llama_index/llama-index-core/llama_index/core/vector_stores/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/vector_stores/__init__.py",
"repo_id": "llama_index",
"token_count": 184
} | 1,305 |
/* eslint-disable no-process-env */
/* eslint-disable @typescript-eslint/no-non-null-assertion */
/* eslint-disable no-promise-executor-return */
import { describe, expect, test } from "@jest/globals";
import { faker } from "@faker-js/faker";
import { Pinecone } from "@pinecone-database/pinecone";
import * as uuid from... | langchainjs/libs/langchain-pinecone/src/tests/vectorstores.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-pinecone/src/tests/vectorstores.int.test.ts",
"repo_id": "langchainjs",
"token_count": 2265
} | 1,065 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/node_parser/file/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/node_parser/file/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,742 |
python_sources()
| llama_index/llama-index-integrations/retrievers/llama-index-retrievers-pathway/llama_index/retrievers/pathway/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/retrievers/llama-index-retrievers-pathway/llama_index/retrievers/pathway/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,400 |
---
sidebar_position: 6
sidebar_class_name: hidden
---
# Experimental
| langchainjs/docs/core_docs/docs/modules/experimental/index.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/experimental/index.mdx",
"repo_id": "langchainjs",
"token_count": 24
} | 759 |
// Copyright (C) 2019-2020 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/pkg/util/retry/options.go/0 | {
"file_path": "milvus/pkg/util/retry/options.go",
"repo_id": "milvus",
"token_count": 557
} | 1,924 |
<!--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/using-diffusers/diffedit.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/diffedit.md",
"repo_id": "diffusers",
"token_count": 3847
} | 187 |
# Discord 101 [[discord-101]]
Hey there! My name is Huggy, the dog 🐕, and I'm looking forward to train with you during this RL Course!
Although I don't know much about fetching sticks (yet), I know one or two things about Discord. So I wrote this guide to help you learn about it!
<img src="https://huggingface.co/dat... | deep-rl-class/units/en/unit0/discord101.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit0/discord101.mdx",
"repo_id": "deep-rl-class",
"token_count": 686
} | 154 |
python_tests()
| llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-firestore/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-firestore/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,599 |
import os
import shutil
from pathlib import Path
from typing import Any, Dict, List, Optional, Sequence
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.data_structs.data_structs import IndexDict
from llama_index.core.indices.base import BaseIndex, IndexNode
from llama_index.core.sc... | llama_index/llama-index-integrations/indices/llama-index-indices-managed-colbert/llama_index/indices/managed/colbert/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/indices/llama-index-indices-managed-colbert/llama_index/indices/managed/colbert/base.py",
"repo_id": "llama_index",
"token_count": 3168
} | 1,293 |
import argparse
from typing import Any, Optional
from llama_index.legacy.command_line.rag import RagCLI, default_ragcli_persist_dir
from llama_index.legacy.embeddings import OpenAIEmbedding
from llama_index.legacy.ingestion import IngestionCache, IngestionPipeline
from llama_index.legacy.llama_dataset.download import ... | llama_index/llama-index-legacy/llama_index/legacy/command_line/command_line.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/command_line/command_line.py",
"repo_id": "llama_index",
"token_count": 2357
} | 1,505 |
# Installation
This section explains how to install the CLI tool as well as installing TGI from source. **The strongly recommended approach is to use Docker, as it does not require much setup. Check [the Quick Tour](./quicktour) to learn how to run TGI with Docker.**
## Install CLI
You can use TGI command-line inter... | text-generation-inference/docs/source/installation.md/0 | {
"file_path": "text-generation-inference/docs/source/installation.md",
"repo_id": "text-generation-inference",
"token_count": 702
} | 397 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...utils import BaseOutput, is_flax_available
@dataclass
class StableDiffusionPipelineOutput(BaseOutput):
"""
Output class for Stable Diffusion pipelines.
Args:
images (`List[PIL.... | diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_output.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_output.py",
"repo_id": "diffusers",
"token_count": 598
} | 249 |
# The Exploration/Exploitation trade-off [[exp-exp-tradeoff]]
Finally, before looking at the different methods to solve Reinforcement Learning problems, we must cover one more very important topic: *the exploration/exploitation trade-off.*
- *Exploration* is exploring the environment by trying random actions in order... | deep-rl-class/units/en/unit1/exp-exp-tradeoff.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/exp-exp-tradeoff.mdx",
"repo_id": "deep-rl-class",
"token_count": 699
} | 155 |
# [DreamBooth](https://github.com/huggingface/diffusers/tree/main/examples/dreambooth) by [colossalai](https://github.com/hpcaitech/ColossalAI.git)
[DreamBooth](https://arxiv.org/abs/2208.12242) is a method to personalize text2image models like stable diffusion given just a few(3~5) images of a subject.
The `train_dre... | diffusers/examples/research_projects/colossalai/README.md/0 | {
"file_path": "diffusers/examples/research_projects/colossalai/README.md",
"repo_id": "diffusers",
"token_count": 1659
} | 208 |
import { OpenAIChat } from "@langchain/openai";
export const run = async () => {
const model = new OpenAIChat({
prefixMessages: [
{
role: "system",
content: "You are a helpful assistant that answers in pirate language",
},
],
maxTokens: 50,
});
const res = await model.call... | langchainjs/examples/src/llms/openai-chat.ts/0 | {
"file_path": "langchainjs/examples/src/llms/openai-chat.ts",
"repo_id": "langchainjs",
"token_count": 152
} | 827 |
<!--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 agreed... | transformers/docs/source/ko/preprocessing.md/0 | {
"file_path": "transformers/docs/source/ko/preprocessing.md",
"repo_id": "transformers",
"token_count": 17104
} | 505 |
"""Loads .ipynb notebook files."""
import json
from pathlib import Path
from typing import Any, List
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
def concatenate_cells(
cell: dict, include_outputs: bool, max_output_length: int, traceback: bool
) ... | langchain/libs/community/langchain_community/document_loaders/notebook.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/notebook.py",
"repo_id": "langchain",
"token_count": 1999
} | 241 |
from langchain_community.document_loaders.powerpoint import UnstructuredPowerPointLoader
__all__ = ["UnstructuredPowerPointLoader"]
| langchain/libs/langchain/langchain/document_loaders/powerpoint.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/powerpoint.py",
"repo_id": "langchain",
"token_count": 35
} | 491 |
import { test, expect } from "@jest/globals";
import { preprocessJsonInput } from "../output_parser.js";
test("should parse outputs correctly", () => {
expect(preprocessJsonInput("{'escaped':'\\a'}")).toBe("{'escaped':'\\\\a'}");
expect(preprocessJsonInput("```\n{}\n```")).toBe("{}");
expect(preprocessJsonInput... | langchainjs/langchain/src/experimental/autogpt/tests/output_parser.test.ts/0 | {
"file_path": "langchainjs/langchain/src/experimental/autogpt/tests/output_parser.test.ts",
"repo_id": "langchainjs",
"token_count": 182
} | 907 |
package model
import (
"github.com/chroma/chroma-coordinator/internal/types"
)
type Collection struct {
ID types.UniqueID
Name string
Topic string
Dimension *int32
Metadata *CollectionMetadata[CollectionMetadataValueType]
Created bool
TenantID string
DatabaseName stri... | chroma/go/coordinator/internal/model/collection.go/0 | {
"file_path": "chroma/go/coordinator/internal/model/collection.go",
"repo_id": "chroma",
"token_count": 561
} | 48 |
import tokenize
from langchain_community.document_loaders.text import TextLoader
class PythonLoader(TextLoader):
"""Load `Python` files, respecting any non-default encoding if specified."""
def __init__(self, file_path: str):
"""Initialize with a file path.
Args:
file_path: The ... | langchain/libs/community/langchain_community/document_loaders/python.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/python.py",
"repo_id": "langchain",
"token_count": 206
} | 260 |
// Copyright (C) 2019-2020 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/unittest/test_index_c_api.cpp/0 | {
"file_path": "milvus/internal/core/unittest/test_index_c_api.cpp",
"repo_id": "milvus",
"token_count": 7622
} | 1,782 |
import glob
import subprocess
import sys
from typing import List
sys.path.append(".")
from benchmark_text_to_image import ALL_T2I_CKPTS # noqa: E402
PATTERN = "benchmark_*.py"
class SubprocessCallException(Exception):
pass
# Taken from `test_examples_utils.py`
def run_command(command: List[str], return_std... | diffusers/benchmarks/run_all.py/0 | {
"file_path": "diffusers/benchmarks/run_all.py",
"repo_id": "diffusers",
"token_count": 1436
} | 163 |
- sections:
- local: index
title: 🤗 Transformers
- local: quicktour
title: Tour rápido
- local: installation
title: Instalación
title: Empezar
- sections:
- local: pipeline_tutorial
title: Pipelines para inferencia
- local: autoclass_tutorial
title: Carga instancias preentrenadas con un... | transformers/docs/source/es/_toctree.yml/0 | {
"file_path": "transformers/docs/source/es/_toctree.yml",
"repo_id": "transformers",
"token_count": 948
} | 481 |
export * from "@langchain/core/utils/async_caller";
| langchainjs/langchain/src/util/async_caller.ts/0 | {
"file_path": "langchainjs/langchain/src/util/async_caller.ts",
"repo_id": "langchainjs",
"token_count": 18
} | 976 |
<!--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/tasks/object_detection.md/0 | {
"file_path": "transformers/docs/source/en/tasks/object_detection.md",
"repo_id": "transformers",
"token_count": 9638
} | 478 |
from langchain_community.chat_message_histories.momento import (
MomentoChatMessageHistory,
)
__all__ = ["MomentoChatMessageHistory"]
| langchain/libs/langchain/langchain/memory/chat_message_histories/momento.py/0 | {
"file_path": "langchain/libs/langchain/langchain/memory/chat_message_histories/momento.py",
"repo_id": "langchain",
"token_count": 43
} | 524 |
<jupyter_start><jupyter_text>Tonic Validate EvaluatorsThis notebook has some basic usage examples of how to use [Tonic Validate](https://github.com/TonicAI/tonic_validate)'s RAGs metrics using LlamaIndex. To use these evaluators, you need to have `tonic_validate` installed, which you can install via `pip install tonic-... | llama_index/docs/examples/evaluation/TonicValidateEvaluators.ipynb/0 | {
"file_path": "llama_index/docs/examples/evaluation/TonicValidateEvaluators.ipynb",
"repo_id": "llama_index",
"token_count": 2226
} | 1,183 |
# coding=utf-8
# Copyright The HuggingFace Team 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/LICE... | transformers/src/transformers/models/rembert/configuration_rembert.py/0 | {
"file_path": "transformers/src/transformers/models/rembert/configuration_rembert.py",
"repo_id": "transformers",
"token_count": 2855
} | 713 |
package typeutil
import (
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/pkg/util/typeutil"
)
func preHandleEmptyResult(result RetrieveResults) {
result.PreHandle()
}
func appendFieldData(result RetrieveResults, fieldData *schemapb.FieldData) {
result.AppendFieldData(fieldDat... | milvus/internal/util/typeutil/result_helper.go/0 | {
"file_path": "milvus/internal/util/typeutil/result_helper.go",
"repo_id": "milvus",
"token_count": 333
} | 1,877 |
from __future__ import annotations
from typing import Union
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.exceptions import OutputParserException
from langchain.agents import AgentOutputParser
from langchain.agents.conversational_chat.prompt import FORMAT_INSTRUCTIONS
from langchain.... | langchain/libs/langchain/langchain/agents/conversational_chat/output_parser.py/0 | {
"file_path": "langchain/libs/langchain/langchain/agents/conversational_chat/output_parser.py",
"repo_id": "langchain",
"token_count": 913
} | 443 |
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::type_object::PyTypeInfo;
use std::fmt::{Display, Formatter, Result as FmtResult};
use tokenizers::tokenizer::Result;
#[derive(Debug)]
pub struct PyError(pub String);
impl PyError {
#[allow(dead_code)]
pub fn from(s: &str) -> Self {
PyError(String::f... | tokenizers/bindings/python/src/error.rs/0 | {
"file_path": "tokenizers/bindings/python/src/error.rs",
"repo_id": "tokenizers",
"token_count": 531
} | 406 |
#!/usr/bin/env python
# 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... | transformers/examples/legacy/seq2seq/run_distributed_eval.py/0 | {
"file_path": "transformers/examples/legacy/seq2seq/run_distributed_eval.py",
"repo_id": "transformers",
"token_count": 4159
} | 519 |
<!--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 agreed... | transformers/docs/source/ko/attention.md/0 | {
"file_path": "transformers/docs/source/ko/attention.md",
"repo_id": "transformers",
"token_count": 3070
} | 556 |
# Vespa Retriever
This shows how to use Vespa.ai as a LangChain retriever.
Vespa.ai is a platform for highly efficient structured text and vector search.
Please refer to [Vespa.ai](https://vespa.ai) for more information.
The following sets up a retriever that fetches results from Vespa's documentation search:
import... | langchainjs/docs/core_docs/docs/integrations/retrievers/vespa-retriever.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/retrievers/vespa-retriever.mdx",
"repo_id": "langchainjs",
"token_count": 350
} | 767 |
<jupyter_start><jupyter_text>Derrière le pipeline (PyTorch) Installez la bibliothèque 🤗 *Transformers* pour exécuter ce *notebook*.<jupyter_code>!pip install transformers[sentencepiece]
from transformers import pipeline
classifier = pipeline("sentiment-analysis", model="tblard/tf-allocine")
classifier(
["J'ai att... | notebooks/course/fr/chapter2/section2_pt.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter2/section2_pt.ipynb",
"repo_id": "notebooks",
"token_count": 471
} | 306 |
from typing import Any, Dict, List, Optional, Union, cast
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from langchain_core.pydantic_v1 import Extra, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_en... | langchain/libs/community/langchain_community/llms/arcee.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/arcee.py",
"repo_id": "langchain",
"token_count": 2116
} | 265 |
<!--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/it/accelerate.md/0 | {
"file_path": "transformers/docs/source/it/accelerate.md",
"repo_id": "transformers",
"token_count": 1891
} | 518 |
import unittest
import pytest
from langchain_community.document_loaders.parsers.language.c import CSegmenter
@pytest.mark.requires("tree_sitter", "tree_sitter_languages")
class TestCSegmenter(unittest.TestCase):
def setUp(self) -> None:
self.example_code = """int main() {
return 0;
}
struct S {
};
... | langchain/libs/community/tests/unit_tests/document_loaders/parsers/language/test_c.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/document_loaders/parsers/language/test_c.py",
"repo_id": "langchain",
"token_count": 594
} | 364 |
from typing import Any, Dict, Tuple
import pytest
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
)
from langchain.retrievers.self_query.myscale import MyScaleTranslator
DEFAULT_TRANSLATOR = MyScaleTranslator()
@pytest.mark.param... | langchain/libs/langchain/tests/unit_tests/retrievers/self_query/test_myscale.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/retrievers/self_query/test_myscale.py",
"repo_id": "langchain",
"token_count": 1074
} | 603 |
<jupyter_start><jupyter_text>Merge Documents LoaderMerge the documents returned from a set of specified data loaders.<jupyter_code>from langchain_community.document_loaders import WebBaseLoader
loader_web = WebBaseLoader(
"https://github.com/basecamp/handbook/blob/master/37signals-is-you.md"
)
from langchain_commu... | langchain/docs/docs/integrations/document_loaders/merge_doc.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/merge_doc.ipynb",
"repo_id": "langchain",
"token_count": 210
} | 114 |
export interface IEmbeddingFunction {
generate(texts: string[]): Promise<number[][]>;
}
| chroma/clients/js/src/embeddings/IEmbeddingFunction.ts/0 | {
"file_path": "chroma/clients/js/src/embeddings/IEmbeddingFunction.ts",
"repo_id": "chroma",
"token_count": 31
} | 31 |
"""Fake ChatModel for testing purposes."""
import asyncio
import time
from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Union
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models.chat_models import BaseChatMod... | langchain/libs/community/langchain_community/chat_models/fake.py/0 | {
"file_path": "langchain/libs/community/langchain_community/chat_models/fake.py",
"repo_id": "langchain",
"token_count": 1392
} | 226 |
<jupyter_start><jupyter_text>Knowledge Graph RAG Query Engine Graph RAGGraph RAG is an Knowledge-enabled RAG approach to retrieve information from Knowledge Graph on given task. Typically, this is to build context based on entities' SubGraph related to the task. GraphStore backed RAG vs VectorStore RAGAs we compared ho... | llama_index/docs/examples/query_engine/knowledge_graph_rag_query_engine.ipynb/0 | {
"file_path": "llama_index/docs/examples/query_engine/knowledge_graph_rag_query_engine.ipynb",
"repo_id": "llama_index",
"token_count": 4840
} | 1,124 |
import {
BaseCallbackConfig,
CallbackManager,
CallbackManagerForRetrieverRun,
Callbacks,
parseCallbackConfigArg,
} from "./callbacks/manager.js";
import type { DocumentInterface } from "./documents/document.js";
import { Runnable, type RunnableInterface } from "./runnables/base.js";
import { RunnableConfig, e... | langchainjs/langchain-core/src/retrievers.ts/0 | {
"file_path": "langchainjs/langchain-core/src/retrievers.ts",
"repo_id": "langchainjs",
"token_count": 1076
} | 879 |
# Lantern
This page covers how to use the [Lantern](https://github.com/lanterndata/lantern) within LangChain
It is broken into two parts: setup, and then references to specific Lantern wrappers.
## Setup
1. The first step is to create a database with the `lantern` extension installed.
Follow the steps at [Lanter... | langchain/docs/docs/integrations/providers/lantern.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/lantern.mdx",
"repo_id": "langchain",
"token_count": 232
} | 148 |
---
keywords: [gemini, gemini-pro]
---
# Google
Functionality related to [Google Cloud Platform](https://cloud.google.com/)
## Chat models
### ChatGoogleGenerativeAI
Access Gemini models such as `gemini-pro` and `gemini-pro-vision` through the [`ChatGoogleGenerativeAI`](/docs/integrations/chat/google_generativeai)... | langchainjs/docs/core_docs/docs/integrations/platforms/google.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/platforms/google.mdx",
"repo_id": "langchainjs",
"token_count": 1094
} | 739 |
# LlamaIndex Retrievers Integration: Pathway Retriever
| llama_index/llama-index-integrations/retrievers/llama-index-retrievers-pathway/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/retrievers/llama-index-retrievers-pathway/README.md",
"repo_id": "llama_index",
"token_count": 15
} | 1,408 |
import { test, expect } from "@jest/globals";
import { OpenAIEmbeddings } from "@langchain/openai";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { CloseVectorNode } from "../closevector/node.js";
test.skip("Test CloseVectorNode.fromTexts + addVectors", async () => {
const key = getEnvir... | langchainjs/libs/langchain-community/src/vectorstores/tests/closevector_node.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/tests/closevector_node.int.test.ts",
"repo_id": "langchainjs",
"token_count": 438
} | 1,026 |
"""Unit tests for logger."""
from llama_index.legacy.logger.base import LlamaLogger
def test_logger() -> None:
"""Test logger."""
logger = LlamaLogger()
# test add
for i in range(4):
logger.add_log({"foo": "bar", "item": i})
logs = logger.get_logs()
assert logs == [
{"foo": "b... | llama_index/llama-index-legacy/tests/logger/test_base.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/logger/test_base.py",
"repo_id": "llama_index",
"token_count": 584
} | 1,561 |
<jupyter_start><jupyter_text>Curate fine-tuning data with Lilac[](https://colab.research.google.com/github/langchain-ai/langsmith-cookbook/blob/main/fine-tuning-examples/lilac/lilac.ipynb)Lilac is an open-source product that helps you analyze, structure, and clean unstructured data with AI. You can use it to enrich dat... | langsmith-cookbook/fine-tuning-examples/lilac/lilac.ipynb/0 | {
"file_path": "langsmith-cookbook/fine-tuning-examples/lilac/lilac.ipynb",
"repo_id": "langsmith-cookbook",
"token_count": 3229
} | 1,059 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-hive/llama_index/readers/hive/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-hive/llama_index/readers/hive/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,383 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size", [None, 400 * 2**20, 600 * 2**20])
@pytest.mark.parametrize("input_in_memory_max_size", ["default", 0, 100 * 2**20, 900 * 2**20])
def test_is_small_dataset(dataset_size, input_in_memory... | datasets/tests/test_info_utils.py/0 | {
"file_path": "datasets/tests/test_info_utils.py",
"repo_id": "datasets",
"token_count": 366
} | 161 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "llms/fireworks",
});
export * from "@langchain/community/llms/fireworks";
| langchainjs/langchain/src/llms/fireworks.ts/0 | {
"file_path": "langchainjs/langchain/src/llms/fireworks.ts",
"repo_id": "langchainjs",
"token_count": 72
} | 902 |
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import type { VectorStoreInterface } from "@langchain/core/vectorstores";
import { ChainValues } from "@langchain/core/utils/types";
import { CallbackManagerForChainRun } from "@langchain/core/callbacks/manager";
import { PromptTemp... | langchainjs/langchain/src/chains/chat_vector_db_chain.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/chat_vector_db_chain.ts",
"repo_id": "langchainjs",
"token_count": 2256
} | 878 |
"""Toolkit for interacting with an SQL database."""
from typing import List
from langchain_core.language_models import BaseLanguageModel
from langchain_core.pydantic_v1 import Field
from langchain_community.agent_toolkits.base import BaseToolkit
from langchain_community.tools import BaseTool
from langchain_community.... | langchain/libs/community/langchain_community/agent_toolkits/sql/toolkit.py/0 | {
"file_path": "langchain/libs/community/langchain_community/agent_toolkits/sql/toolkit.py",
"repo_id": "langchain",
"token_count": 1171
} | 225 |
"""Pairwise evaluation."""
import asyncio
from enum import Enum
from typing import Any, Callable, Optional, Sequence, Tuple, Union
from llama_index.core import ServiceContext
from llama_index.core.evaluation.base import (
BaseEvaluator,
EvaluationResult,
)
from llama_index.core.llms.llm import LLM
from llama_... | llama_index/llama-index-core/llama_index/core/evaluation/pairwise.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/evaluation/pairwise.py",
"repo_id": "llama_index",
"token_count": 4313
} | 1,256 |
"""Data Connectors for LlamaIndex.
This module contains the data connectors for LlamaIndex. Each connector inherits
from a `BaseReader` class, connects to a data source, and loads Document objects
from that data source.
You may also choose to construct Document objects manually, for instance
in our `Insert How-To Gui... | llama_index/llama-index-core/llama_index/core/readers/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/readers/__init__.py",
"repo_id": "llama_index",
"token_count": 254
} | 1,292 |
<!--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/ko/training/overview.md/0 | {
"file_path": "diffusers/docs/source/ko/training/overview.md",
"repo_id": "diffusers",
"token_count": 4744
} | 190 |
# ControlNet training example
[Adding Conditional Control to Text-to-Image Diffusion Models](https://arxiv.org/abs/2302.05543) by Lvmin Zhang and Maneesh Agrawala.
This example is based on the [training example in the original ControlNet repository](https://github.com/lllyasviel/ControlNet/blob/main/docs/train.md). I... | diffusers/examples/controlnet/README.md/0 | {
"file_path": "diffusers/examples/controlnet/README.md",
"repo_id": "diffusers",
"token_count": 6041
} | 213 |
<jupyter_start><jupyter_text>Fleet AI Libraries ContextThe Fleet AI team is on a mission to embed the world's most important data. They've started by embedding the top 1200 Python libraries to enable code generation with up-to-date knowledge. They've been kind enough to share their embeddings of the [LangChain docs](ht... | langchain/docs/docs/integrations/retrievers/fleet_context.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/retrievers/fleet_context.ipynb",
"repo_id": "langchain",
"token_count": 2121
} | 156 |
# Quiz
The best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf) **is to test yourself.** This will help you to find **where you need to reinforce your knowledge**.
### Q1: Which of the following tools are specifically designe... | deep-rl-class/units/en/unit5/quiz.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/quiz.mdx",
"repo_id": "deep-rl-class",
"token_count": 1511
} | 181 |
from collections import defaultdict
from typing import Any, Dict
from llama_index.core.base.response.schema import RESPONSE_TYPE
from llama_index.core.llama_pack.base import BaseLlamaPack
from llama_index.core.node_parser.text.utils import split_by_sentence_tokenizer
from llama_index.core.query_engine import BaseQuery... | llama_index/llama-index-packs/llama-index-packs-fuzzy-citation/llama_index/packs/fuzzy_citation/base.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-fuzzy-citation/llama_index/packs/fuzzy_citation/base.py",
"repo_id": "llama_index",
"token_count": 2474
} | 1,671 |
<jupyter_start><jupyter_text>SageMakerEndpoint[Amazon SageMaker](https://aws.amazon.com/sagemaker/) is a system that can build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.This notebooks goes over how to use an LLM hosted on a `SageMaker endpoi... | langchain/docs/docs/integrations/llms/sagemaker.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/sagemaker.ipynb",
"repo_id": "langchain",
"token_count": 1638
} | 119 |
from typing import Iterator
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseBlobParser
from langchain_community.document_loaders.blob_loaders import Blob
class MsWordParser(BaseBlobParser):
"""Parse the Microsoft Word documents from a blob."""
def laz... | langchain/libs/community/langchain_community/document_loaders/parsers/msword.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/msword.py",
"repo_id": "langchain",
"token_count": 693
} | 246 |
search_performance:
collections:
-
milvus:
db_config.primary_path: /test/milvus/db_data_011/sift_50m_128_l2
cache_config.cpu_cache_capacity: 32GB
engine_config.use_blas_threshold: 0
engine_config.gpu_search_threshold: 100
gpu_resource_config.enable: true
gpu_r... | milvus/tests/benchmark/milvus_benchmark/suites/011_gpu_search.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/011_gpu_search.yaml",
"repo_id": "milvus",
"token_count": 4000
} | 1,865 |
import { Replicate } from "@langchain/community/llms/replicate";
const modelA = new Replicate({
model:
"a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5",
});
// `call` is a simple string-in, string-out method for interacting with the model.
const resA = await modelA.... | langchainjs/examples/src/models/llm/replicate.ts/0 | {
"file_path": "langchainjs/examples/src/models/llm/replicate.ts",
"repo_id": "langchainjs",
"token_count": 607
} | 810 |
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any, Dict, List
from langchain_core.load.serializable import Serializable
from langchain_core.runnables import run_in_executor
class BaseMemory(Serializable, ABC):
"""Abstract base class for memory in Chains.
Memory r... | langchain/libs/core/langchain_core/memory.py/0 | {
"file_path": "langchain/libs/core/langchain_core/memory.py",
"repo_id": "langchain",
"token_count": 1014
} | 391 |
import candle
from candle import Tensor
from .module import Module
from typing import Union, List, Tuple, Optional, Any
_shape_t = Union[int, List[int]]
import numbers
class LayerNorm(Module):
r"""Applies Layer Normalization over a mini-batch of inputs as described in
the paper `Layer Normalization <https://... | candle/candle-pyo3/py_src/candle/nn/normalization.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/nn/normalization.py",
"repo_id": "candle",
"token_count": 803
} | 73 |
# RAG Local CLI Pack
This LlamaPack implements a fully local version of our [RAG CLI](https://docs.llamaindex.ai/en/stable/use_cases/q_and_a/rag_cli.html),
with Mistral (through Ollama) and [BGE-M3](https://huggingface.co/BAAI/bge-m3).
## CLI Usage
You can download llamapacks directly using `llamaindex-cli`, which c... | llama_index/llama-index-packs/llama-index-packs-rag-cli-local/README.md/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-rag-cli-local/README.md",
"repo_id": "llama_index",
"token_count": 555
} | 1,807 |
import logging
from typing import Any, List
from llama_index.core.base.embeddings.base import Embedding
from llama_index.core.bridge.pydantic import Field, PrivateAttr
from llama_index.core.constants import DEFAULT_EMBED_BATCH_SIZE
from llama_index.core.embeddings.multi_modal_base import MultiModalEmbedding
from llama... | llama_index/llama-index-integrations/embeddings/llama-index-embeddings-clip/llama_index/embeddings/clip/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-clip/llama_index/embeddings/clip/base.py",
"repo_id": "llama_index",
"token_count": 2087
} | 1,303 |
"""Test PGVector functionality."""
import os
from typing import List
import sqlalchemy
from langchain_core.documents import Document
from sqlalchemy.orm import Session
from langchain_community.vectorstores.pgvector import PGVector
from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
CONNEC... | langchain/libs/community/tests/integration_tests/vectorstores/test_pgvector.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/vectorstores/test_pgvector.py",
"repo_id": "langchain",
"token_count": 5642
} | 357 |
# coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# 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 Lice... | transformers/src/transformers/models/deprecated/transfo_xl/modeling_tf_transfo_xl.py/0 | {
"file_path": "transformers/src/transformers/models/deprecated/transfo_xl/modeling_tf_transfo_xl.py",
"repo_id": "transformers",
"token_count": 20972
} | 593 |
# Process image data
This guide shows specific methods for processing image datasets. Learn how to:
- Use [`~Dataset.map`] with image dataset.
- Apply data augmentations to a dataset with [`~Dataset.set_transform`].
For a guide on how to process any type of dataset, take a look at the <a class="underline decoration-... | datasets/docs/source/image_process.mdx/0 | {
"file_path": "datasets/docs/source/image_process.mdx",
"repo_id": "datasets",
"token_count": 1031
} | 112 |
"""Test Replicate API wrapper."""
from langchain_core.callbacks import CallbackManager
from langchain_community.llms.replicate import Replicate
from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
TEST_MODEL = "replicate/dolly-v2-12b:ef0e1aefc61f8e096ebe4db6b2bacc297daf2ef6899f0f7e001ec44... | langchain/libs/community/tests/integration_tests/llms/test_replicate.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_replicate.py",
"repo_id": "langchain",
"token_count": 603
} | 339 |
from llama_index.tools.google.calendar.base import GoogleCalendarToolSpec
from llama_index.tools.google.gmail.base import GmailToolSpec
from llama_index.tools.google.search.base import (
QUERY_URL_TMPL,
GoogleSearchToolSpec,
)
__all__ = [
"GoogleCalendarToolSpec",
"GmailToolSpec",
"GoogleSearchTool... | llama_index/llama-index-integrations/tools/llama-index-tools-google/llama_index/tools/google/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-google/llama_index/tools/google/__init__.py",
"repo_id": "llama_index",
"token_count": 131
} | 1,438 |
import torch
from diffusers import KDPM2AncestralDiscreteScheduler
from diffusers.utils.testing_utils import torch_device
from .test_schedulers import SchedulerCommonTest
class KDPM2AncestralDiscreteSchedulerTest(SchedulerCommonTest):
scheduler_classes = (KDPM2AncestralDiscreteScheduler,)
num_inference_step... | diffusers/tests/schedulers/test_scheduler_kdpm2_ancestral.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_kdpm2_ancestral.py",
"repo_id": "diffusers",
"token_count": 2516
} | 299 |
# Noisy Student (EfficientNet)
**Noisy Student Training** is a semi-supervised learning approach. It extends the idea of self-training
and distillation with the use of equal-or-larger student models and noise added to the student during learning. It has three main steps:
1. train a teacher model on labeled images
2.... | pytorch-image-models/docs/models/noisy-student.md/0 | {
"file_path": "pytorch-image-models/docs/models/noisy-student.md",
"repo_id": "pytorch-image-models",
"token_count": 6680
} | 367 |
# coding=utf-8
# Copyright 2023 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/encodec/feature_extraction_encodec.py/0 | {
"file_path": "transformers/src/transformers/models/encodec/feature_extraction_encodec.py",
"repo_id": "transformers",
"token_count": 4073
} | 666 |
# 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/loaders/autoencoder.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/autoencoder.py",
"repo_id": "diffusers",
"token_count": 3239
} | 231 |
from llama_index.core.vector_stores.types import BasePydanticVectorStore
from llama_index.vector_stores.txtai import TxtaiVectorStore
def test_class():
names_of_base_classes = [b.__name__ for b in TxtaiVectorStore.__mro__]
assert BasePydanticVectorStore.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-txtai/tests/test_vector_stores_txtai.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-txtai/tests/test_vector_stores_txtai.py",
"repo_id": "llama_index",
"token_count": 102
} | 1,541 |
# coding=utf-8
# Copyright 2023 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/tests/models/mra/test_modeling_mra.py/0 | {
"file_path": "transformers/tests/models/mra/test_modeling_mra.py",
"repo_id": "transformers",
"token_count": 7505
} | 828 |
import { TavilySearchResults } from "@langchain/community/tools/tavily_search";
import { OpenAIEmbeddings, ChatOpenAI } from "@langchain/openai";
import { RunnableWithMessageHistory } from "@langchain/core/runnables";
import { HumanMessage, AIMessage } from "@langchain/core/messages";
import { pull } from "langchain/h... | langchainjs/examples/src/agents/quickstart.ts/0 | {
"file_path": "langchainjs/examples/src/agents/quickstart.ts",
"repo_id": "langchainjs",
"token_count": 1514
} | 793 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team, The Microsoft Research 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/tests/models/xlm_prophetnet/test_modeling_xlm_prophetnet.py/0 | {
"file_path": "transformers/tests/models/xlm_prophetnet/test_modeling_xlm_prophetnet.py",
"repo_id": "transformers",
"token_count": 3737
} | 782 |
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