text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
logger = logging.get_logger(__name__)
def extract_warnings_from_single_artifact(artifact_path, targets):
"""Extract warnings from a downl... | transformers/utils/extract_warnings.py/0 | {
"file_path": "transformers/utils/extract_warnings.py",
"repo_id": "transformers",
"token_count": 2110
} | 766 |
<jupyter_start><jupyter_text>MyScale>[MyScale](https://docs.myscale.com/en/) is an integrated vector database. You can access your database in SQL and also from here, LangChain.>`MyScale` can make use of [various data types and functions for filters](https://blog.myscale.com/2023/06/06/why-integrated-database-solution-... | langchain/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb",
"repo_id": "langchain",
"token_count": 2465
} | 159 |
python_tests()
| llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-postgres/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-postgres/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,406 |
import { YoutubeLoader } from "langchain/document_loaders/web/youtube";
const loader = YoutubeLoader.createFromUrl("https://youtu.be/bZQun8Y4L2A", {
language: "en",
addVideoInfo: true,
});
const docs = await loader.load();
console.log(docs);
| langchainjs/examples/src/document_loaders/youtube.ts/0 | {
"file_path": "langchainjs/examples/src/document_loaders/youtube.ts",
"repo_id": "langchainjs",
"token_count": 85
} | 772 |
import { OpenAI, OpenAIEmbeddings } from "@langchain/openai";
import { VectorStoreRetrieverMemory } from "langchain/memory";
import { LLMChain } from "langchain/chains";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { PromptTemplate } from "@langchain/core/prompts";
const vectorStore = new ... | langchainjs/examples/src/memory/vector_store.ts/0 | {
"file_path": "langchainjs/examples/src/memory/vector_store.ts",
"repo_id": "langchainjs",
"token_count": 696
} | 861 |
"""Bing Search tool spec."""
from typing import List, Optional
import requests
from llama_index.core.tools.tool_spec.base import BaseToolSpec
ENDPOINT_BASE_URL = "https://api.bing.microsoft.com/v7.0/"
class BingSearchToolSpec(BaseToolSpec):
"""Bing Search tool spec."""
spec_functions = ["bing_news_search"... | llama_index/llama-index-integrations/tools/llama-index-tools-bing-search/llama_index/tools/bing_search/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-bing-search/llama_index/tools/bing_search/base.py",
"repo_id": "llama_index",
"token_count": 817
} | 1,616 |
"""Bark TTS module."""
import os
import tempfile
from typing import Any, Optional
import numpy as np
from llama_index.legacy.tts.base import BaseTTS
# text to be chunked into chunks of 10 words
# to avoid hallicunation for bark
DEFAULT_CHUNK_SIZE = 10
class BarkTTS(BaseTTS):
"""Bark TTS.
Args:
te... | llama_index/llama-index-legacy/llama_index/legacy/tts/bark.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/tts/bark.py",
"repo_id": "llama_index",
"token_count": 1213
} | 1,544 |
# 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/stable_diffusion_xl/test_stable_diffusion_xl_k_diffusion.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_k_diffusion.py",
"repo_id": "diffusers",
"token_count": 2096
} | 284 |
package backend
import (
"reflect"
"testing"
"github.com/stretchr/testify/assert"
)
func TestBackupCodec_Serialize(t *testing.T) {
header := &BackupHeader{
Version: BackupHeaderVersionV1,
Instance: "/by-dev",
MetaPath: "meta",
Entries: 0,
Component: "",
Extra: nil,
}
kvs := map[string]str... | milvus/cmd/tools/migration/backend/backup_restore_test.go/0 | {
"file_path": "milvus/cmd/tools/migration/backend/backup_restore_test.go",
"repo_id": "milvus",
"token_count": 280
} | 1,711 |
import os
import re
from typing import Any, List, Union
from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
from langchain_core.messages import AIMessageChunk
from langchain_core.output_parsers import BaseOutputParser
from langchain_core.outputs import ChatGeneration, Generation
from lang... | langchain/libs/partners/google-vertexai/tests/integration_tests/test_tools.py/0 | {
"file_path": "langchain/libs/partners/google-vertexai/tests/integration_tests/test_tools.py",
"repo_id": "langchain",
"token_count": 2491
} | 654 |
{
"endOfLine": "lf"
}
| chat-langchain/chat-langchain/.prettierrc/0 | {
"file_path": "chat-langchain/chat-langchain/.prettierrc",
"repo_id": "chat-langchain",
"token_count": 14
} | 5 |
<!--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/models/controlnet.md/0 | {
"file_path": "diffusers/docs/source/en/api/models/controlnet.md",
"repo_id": "diffusers",
"token_count": 770
} | 177 |
// 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/instruction_set.h/0 | {
"file_path": "milvus/internal/core/src/simd/instruction_set.h",
"repo_id": "milvus",
"token_count": 4100
} | 1,769 |
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgumentParser, set... | transformers/examples/research_projects/codeparrot/scripts/validation_loss.py/0 | {
"file_path": "transformers/examples/research_projects/codeparrot/scripts/validation_loss.py",
"repo_id": "transformers",
"token_count": 1471
} | 522 |
/// A bounding box around an object.
#[derive(Debug, Clone)]
pub struct Bbox<D> {
pub xmin: f32,
pub ymin: f32,
pub xmax: f32,
pub ymax: f32,
pub confidence: f32,
pub data: D,
}
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct KeyPoint {
pub x: f32,
pub y: f32,
pub mask: f32,
}
... | candle/candle-transformers/src/object_detection.rs/0 | {
"file_path": "candle/candle-transformers/src/object_detection.rs",
"repo_id": "candle",
"token_count": 894
} | 86 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use clap::Parser;
use candle::{DType, IndexOp, D};
use candle_nn::VarBuilder;
use candle_transformers::models::vit;
#[derive(Parser)]
struct Args {
#[arg(long)]
model: Option<String>,
#[arg(l... | candle/candle-examples/examples/vit/main.rs/0 | {
"file_path": "candle/candle-examples/examples/vit/main.rs",
"repo_id": "candle",
"token_count": 755
} | 57 |
import os
import pdb
import time
import logging
import hashlib
import traceback
from yaml import full_load, dump
from milvus_benchmark import utils
from milvus_benchmark import config
logger = logging.getLogger("milvus_benchmark.env.helm_utils")
BOOKKEEPER_PULSAR_MEM = '\"-Xms512m -Xmx1024m -XX:MaxDirectMemorySize=102... | milvus/tests/benchmark/milvus_benchmark/env/helm_utils.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/env/helm_utils.py",
"repo_id": "milvus",
"token_count": 9116
} | 1,853 |
from langchain.schema.prompt_template import __all__
EXPECTED_ALL = ["BasePromptTemplate", "format_document"]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
| langchain/libs/langchain/tests/unit_tests/schema/test_prompt_template.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/schema/test_prompt_template.py",
"repo_id": "langchain",
"token_count": 68
} | 609 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-json/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-json/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,371 |
import type { ChainValues } from "../utils/types.js";
import { type BaseMessage, getBufferString } from "../messages/index.js";
import type { LLMResult } from "../outputs.js";
import { getEnvironmentVariable } from "../utils/env.js";
import { BaseTracer, type RunType, type Run } from "./base.js";
export interface Bas... | langchainjs/langchain-core/src/tracers/tracer_langchain_v1.ts/0 | {
"file_path": "langchainjs/langchain-core/src/tracers/tracer_langchain_v1.ts",
"repo_id": "langchainjs",
"token_count": 3187
} | 842 |
use crate::arc_rwlock_serde;
use napi::bindgen_prelude::*;
use napi_derive::napi;
use serde::{Deserialize, Serialize};
use std::sync::{Arc, RwLock};
use tk::normalizers::NormalizerWrapper;
use tk::NormalizedString;
use tokenizers as tk;
/// Normalizer
#[derive(Debug, Clone, Serialize, Deserialize)]
#[napi]
pub struct ... | tokenizers/bindings/node/src/normalizers.rs/0 | {
"file_path": "tokenizers/bindings/node/src/normalizers.rs",
"repo_id": "tokenizers",
"token_count": 1886
} | 437 |
# 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/i2vgen_xl/test_i2vgenxl.py/0 | {
"file_path": "diffusers/tests/pipelines/i2vgen_xl/test_i2vgenxl.py",
"repo_id": "diffusers",
"token_count": 4226
} | 251 |
from __future__ import annotations
import json
import logging
import warnings
from typing import (
TYPE_CHECKING,
Any,
Iterable,
List,
Optional,
Tuple,
Type,
)
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from langchain_core.vectorstores im... | langchain/libs/community/langchain_community/vectorstores/sqlitevss.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/sqlitevss.py",
"repo_id": "langchain",
"token_count": 3419
} | 319 |
# 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 applicabl... | trl/trl/models/sd_utils.py/0 | {
"file_path": "trl/trl/models/sd_utils.py",
"repo_id": "trl",
"token_count": 2507
} | 826 |
<jupyter_start><jupyter_text>Golden Query>[Golden](https://golden.com) provides a set of natural language APIs for querying and enrichment using the Golden Knowledge Graph e.g. queries such as: `Products from OpenAI`, `Generative ai companies with series a funding`, and `rappers who invest` can be used to retrieve stru... | langchain/docs/docs/integrations/tools/golden_query.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/golden_query.ipynb",
"repo_id": "langchain",
"token_count": 333
} | 173 |
# LlamaIndex Embeddings Integration: Nomic
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-nomic/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-nomic/README.md",
"repo_id": "llama_index",
"token_count": 12
} | 1,193 |
"""Quick and dirty representation for OpenAPI specs."""
from dataclasses import dataclass
from typing import List, Tuple
from langchain_core.utils.json_schema import dereference_refs
@dataclass(frozen=True)
class ReducedOpenAPISpec:
"""A reduced OpenAPI spec.
This is a quick and dirty representation for Op... | langchain/libs/community/langchain_community/agent_toolkits/openapi/spec.py/0 | {
"file_path": "langchain/libs/community/langchain_community/agent_toolkits/openapi/spec.py",
"repo_id": "langchain",
"token_count": 985
} | 208 |
// 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/cache/local_cache_test.go/0 | {
"file_path": "milvus/pkg/util/cache/local_cache_test.go",
"repo_id": "milvus",
"token_count": 4585
} | 1,904 |
import { v4 as uuidv4 } from "uuid";
// eslint-disable-next-line import/no-extraneous-dependencies
import { FakeStreamingLLM } from "@langchain/core/utils/testing";
import { Client } from "../client.js";
import { isTraceableFunction, traceable } from "../traceable.js";
import { RunTree } from "../run_trees.js";
async ... | langsmith-sdk/js/src/tests/traceable.int.test.ts/0 | {
"file_path": "langsmith-sdk/js/src/tests/traceable.int.test.ts",
"repo_id": "langsmith-sdk",
"token_count": 2012
} | 1,018 |
import argparse
import os
from typing import List, Dict
from openai.types.chat import ChatCompletionMessageParam
import openai
import chromadb
def build_prompt(query: str, context: List[str]) -> List[ChatCompletionMessageParam]:
"""
Builds a prompt for the LLM. #
This function builds a prompt for the LLM... | chroma/examples/chat_with_your_documents/main.py/0 | {
"file_path": "chroma/examples/chat_with_your_documents/main.py",
"repo_id": "chroma",
"token_count": 1729
} | 37 |
import logging
from typing import Dict, Iterator, List, Union
import requests
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseBlobParser
from langchain_community.document_loaders.blob_loaders import Blob
logger = logging.getLogger(__name__)
class ServerUnavai... | langchain/libs/community/langchain_community/document_loaders/parsers/grobid.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/grobid.py",
"repo_id": "langchain",
"token_count": 3406
} | 238 |
// 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/querycoordv2/meta/segment_dist_manager_test.go/0 | {
"file_path": "milvus/internal/querycoordv2/meta/segment_dist_manager_test.go",
"repo_id": "milvus",
"token_count": 1815
} | 1,762 |
<!--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/en/model_doc/gptsan-japanese.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/gptsan-japanese.md",
"repo_id": "transformers",
"token_count": 1659
} | 463 |
[tool.poetry]
name = "chat-bot-feedback"
version = "0.0.1"
description = "Evaluate your chatbot without human feedback"
authors = []
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
openai = "<2"
langsmith = ">=0.0.54"
langchainhub = ">=0.1.13"
[tool.poetry.group.dev.dependen... | langchain/templates/chat-bot-feedback/pyproject.toml/0 | {
"file_path": "langchain/templates/chat-bot-feedback/pyproject.toml",
"repo_id": "langchain",
"token_count": 304
} | 686 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.snscrape_twitter import SnscrapeTwitterReader
def test_class():
names_of_base_classes = [b.__name__ for b in SnscrapeTwitterReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-snscrape-twitter/tests/test_readers_snscrape_twitter.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-snscrape-twitter/tests/test_readers_snscrape_twitter.py",
"repo_id": "llama_index",
"token_count": 95
} | 1,433 |
from __future__ import annotations
import os
from enum import Enum
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
import numpy as np
import yaml
from langchain_core.pydantic_v1 import BaseModel, Field, validator
from typing_extensions import TYPE_CHECKING, Literal
from langchain_communi... | langchain/libs/community/langchain_community/vectorstores/redis/schema.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/redis/schema.py",
"repo_id": "langchain",
"token_count": 4680
} | 312 |
<jupyter_start><jupyter_text>NebulaGraphQAChainThis notebook shows how to use LLMs to provide a natural language interface to NebulaGraph database. You will need to have a running NebulaGraph cluster, for which you can run a containerized cluster by running the following script:```bashcurl -fsSL nebula-up.siwei.io/inst... | langchain/docs/docs/use_cases/graph/graph_nebula_qa.ipynb/0 | {
"file_path": "langchain/docs/docs/use_cases/graph/graph_nebula_qa.ipynb",
"repo_id": "langchain",
"token_count": 1243
} | 212 |
# 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/kandinsky/pipeline_kandinsky_img2img.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky/pipeline_kandinsky_img2img.py",
"repo_id": "diffusers",
"token_count": 9768
} | 237 |
import { ZepRetriever } from "@langchain/community/retrievers/zep";
import { ZepMemory } from "@langchain/community/memory/zep";
import { Memory as MemoryModel, Message } from "@getzep/zep-js";
import { randomUUID } from "crypto";
function sleep(ms: number) {
// eslint-disable-next-line no-promise-executor-return
... | langchainjs/examples/src/retrievers/zep.ts/0 | {
"file_path": "langchainjs/examples/src/retrievers/zep.ts",
"repo_id": "langchainjs",
"token_count": 1592
} | 842 |
# 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: Chose the option which fits better when comparing di... | deep-rl-class/units/en/unit7/quiz.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit7/quiz.mdx",
"repo_id": "deep-rl-class",
"token_count": 1361
} | 163 |
"""Test the public API of the tools package."""
from langchain.vectorstores import __all__ as public_api
_EXPECTED = [
"AlibabaCloudOpenSearch",
"AlibabaCloudOpenSearchSettings",
"AnalyticDB",
"Annoy",
"AtlasDB",
"AwaDB",
"AzureSearch",
"Bagel",
"Cassandra",
"AstraDB",
"Chro... | langchain/libs/langchain/tests/unit_tests/vectorstores/test_public_api.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/vectorstores/test_public_api.py",
"repo_id": "langchain",
"token_count": 727
} | 645 |
<jupyter_start><jupyter_text>SparkLLM ChatSparkLLM chat models API by iFlyTek. For more information, see [iFlyTek Open Platform](https://www.xfyun.cn/). Basic use<jupyter_code>"""For basic init and call"""
from langchain.chat_models import ChatSparkLLM
from langchain.schema import HumanMessage
chat = ChatSparkLLM(
... | langchain/docs/docs/integrations/chat/sparkllm.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/chat/sparkllm.ipynb",
"repo_id": "langchain",
"token_count": 394
} | 102 |
<!--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/main_classes/callback.md/0 | {
"file_path": "transformers/docs/source/zh/main_classes/callback.md",
"repo_id": "transformers",
"token_count": 2183
} | 562 |
<!--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/tflite.md/0 | {
"file_path": "transformers/docs/source/ko/tflite.md",
"repo_id": "transformers",
"token_count": 1845
} | 534 |
<jupyter_start><jupyter_text>SearxNG SearchThis notebook goes over how to use a self hosted `SearxNG` search API to search the web.You can [check this link](https://docs.searxng.org/dev/search_api.html) for more informations about `Searx API` parameters.<jupyter_code>import pprint
from langchain_community.utilities im... | langchain/docs/docs/integrations/tools/searx_search.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/searx_search.ipynb",
"repo_id": "langchain",
"token_count": 2174
} | 171 |
# Copyright 2021 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 required by appl... | accelerate/examples/by_feature/checkpointing.py/0 | {
"file_path": "accelerate/examples/by_feature/checkpointing.py",
"repo_id": "accelerate",
"token_count": 5198
} | 7 |
import * as url from "node:url";
import * as path from "node:path";
import * as fs from "node:fs/promises";
import { test, expect } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import { CSVLoader } from "../fs/csv.js";
test("Test CSV loader from blob", async () => {
const filePath = pa... | langchainjs/langchain/src/document_loaders/tests/csv-blob.test.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/tests/csv-blob.test.ts",
"repo_id": "langchainjs",
"token_count": 772
} | 940 |
from langchain_core.utils.function_calling import (
format_tool_to_openai_function,
format_tool_to_openai_tool,
)
__all__ = ["format_tool_to_openai_function", "format_tool_to_openai_tool"]
| langchain/libs/community/langchain_community/tools/convert_to_openai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/convert_to_openai.py",
"repo_id": "langchain",
"token_count": 76
} | 294 |
search_performance:
collections:
-
server:
db_config.primary_path: /test/milvus/db_data_gpu/sift_50m_1024_128_l2_ivf
cache_config.cpu_cache_capacity: 32
engine_config.use_blas_threshold: 1100
engine_config.gpu_search_threshold: 200
gpu_resource_config.enable: true
... | milvus/tests/benchmark/milvus_benchmark/suites/gpu_search_performance_sift50m.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/gpu_search_performance_sift50m.yaml",
"repo_id": "milvus",
"token_count": 2642
} | 1,976 |
<jupyter_start><jupyter_text>Redis Vector Store In this notebook we are going to show a quick demo of using the RedisVectorStore. If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-vector-stores-redis
!pip install llama-index
import os
import... | llama_index/docs/examples/vector_stores/RedisIndexDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/vector_stores/RedisIndexDemo.ipynb",
"repo_id": "llama_index",
"token_count": 3396
} | 1,137 |
"""Prompts for scoring the outputs of a models for a given question.
This prompt is used to socre the responses and evaluate how it follows the instructions
and answers the question. The prompt is based on the paper from
Zheng, et. al. https://arxiv.org/abs/2306.05685
"""
# flake8: noqa
from langchain_core.prompts.cha... | langchain/libs/langchain/langchain/evaluation/scoring/prompt.py/0 | {
"file_path": "langchain/libs/langchain/langchain/evaluation/scoring/prompt.py",
"repo_id": "langchain",
"token_count": 700
} | 505 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/indices/empty/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/empty/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,496 |
python_tests(
name="tests",
skip_tests=True,
)
| llama_index/llama-index-legacy/tests/indices/composability/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/composability/BUILD",
"repo_id": "llama_index",
"token_count": 25
} | 1,619 |
"""LLM reranker."""
from typing import Callable, List, Optional
from llama_index.legacy.bridge.pydantic import Field, PrivateAttr
from llama_index.legacy.indices.utils import (
default_format_node_batch_fn,
default_parse_choice_select_answer_fn,
)
from llama_index.legacy.postprocessor.types import BaseNodePos... | llama_index/llama-index-legacy/llama_index/legacy/postprocessor/llm_rerank.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/postprocessor/llm_rerank.py",
"repo_id": "llama_index",
"token_count": 1843
} | 1,748 |
from typing import List, Optional
import fsspec
from llama_index.legacy.bridge.pydantic import BaseModel, Field
from llama_index.legacy.schema import BaseNode
from llama_index.legacy.storage.docstore.utils import doc_to_json, json_to_doc
from llama_index.legacy.storage.kvstore import (
FirestoreKVStore as Firesto... | llama_index/llama-index-legacy/llama_index/legacy/ingestion/cache.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/ingestion/cache.py",
"repo_id": "llama_index",
"token_count": 1176
} | 1,524 |
{
"swagger": "2.0",
"info": {
"version": "v2.0",
"title": "SchoolDigger API V2.0",
"description": "Get detailed data on over 120,000 schools and 18,500 districts in the U.S.<br />Version 2.0 incorporates the ATTOM School Boundary Level add-on and spending per pupil metrics",
"termsOfServic... | langchain/libs/community/tests/unit_tests/examples/test_specs/schooldigger/apispec.json/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/examples/test_specs/schooldigger/apispec.json",
"repo_id": "langchain",
"token_count": 47737
} | 416 |
from llama_index.readers.airbyte_zendesk_support.base import AirbyteZendeskSupportReader
__all__ = ["AirbyteZendeskSupportReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-zendesk-support/llama_index/readers/airbyte_zendesk_support/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-zendesk-support/llama_index/readers/airbyte_zendesk_support/__init__.py",
"repo_id": "llama_index",
"token_count": 46
} | 1,402 |
import asyncio
import logging
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Literal,
Optional,
Sequence,
)
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
CompletionResponse,
Comple... | llama_index/llama-index-integrations/llms/llama-index-llms-openllm/llama_index/llms/openllm/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-openllm/llama_index/llms/openllm/base.py",
"repo_id": "llama_index",
"token_count": 7895
} | 1,366 |
"""Test Baseten API wrapper."""
import os
from langchain_community.llms.baseten import Baseten
# This test requires valid BASETEN_MODEL_ID and BASETEN_API_KEY environment variables
def test_baseten_call() -> None:
"""Test valid call to Baseten."""
llm = Baseten(model=os.environ["BASETEN_MODEL_ID"])
outp... | langchain/libs/community/tests/integration_tests/llms/test_baseten.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_baseten.py",
"repo_id": "langchain",
"token_count": 140
} | 361 |
from llama_index.core.llms.base import BaseLLM
from llama_index.llms.openai_like import OpenAILike
def test_embedding_class():
names_of_base_classes = [b.__name__ for b in OpenAILike.__mro__]
assert BaseLLM.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/llms/llama-index-llms-openai-like/tests/test_llms_openai_like.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-openai-like/tests/test_llms_openai_like.py",
"repo_id": "llama_index",
"token_count": 97
} | 1,323 |
// 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/datanode/mock_test.go/0 | {
"file_path": "milvus/internal/datanode/mock_test.go",
"repo_id": "milvus",
"token_count": 15197
} | 1,700 |
import { test, expect } from "@jest/globals";
import { OpenAPIV3, OpenAPIV3_1 } from "openapi-types";
import {
JsonSchema7StringType,
JsonSchema7NumberType,
JsonSchema7ObjectType,
JsonSchema7ArrayType,
JsonSchema7Type,
} from "zod-to-json-schema";
import { OpenAPISpec } from "../../../util/openapi.js";
impor... | langchainjs/langchain/src/chains/openai_functions/tests/openapi.test.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/openai_functions/tests/openapi.test.ts",
"repo_id": "langchainjs",
"token_count": 3610
} | 853 |
# coding=utf-8
# Copyright 2022 The OpenBMB 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/LIC... | transformers/tests/models/cpmant/test_modeling_cpmant.py/0 | {
"file_path": "transformers/tests/models/cpmant/test_modeling_cpmant.py",
"repo_id": "transformers",
"token_count": 4461
} | 792 |
<jupyter_start><jupyter_text>Select by n-gram overlapThe `NGramOverlapExampleSelector` selects and orders examples based on which examples are most similar to the input, according to an ngram overlap score. The ngram overlap score is a float between 0.0 and 1.0, inclusive. The selector allows for a threshold score to b... | langchain/docs/docs/modules/model_io/prompts/example_selector_types/ngram_overlap.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/model_io/prompts/example_selector_types/ngram_overlap.ipynb",
"repo_id": "langchain",
"token_count": 976
} | 207 |
use byteorder::{LittleEndian, ReadBytesExt};
use candle::{DType, Device, IndexOp, Result, Shape, Tensor};
use candle_nn::VarBuilder;
use super::llama2_c::Config;
pub struct TransformerWeights {
// token embedding table
token_embedding_table: Tensor, // (vocab_size, dim)
// weights for rmsnorms
rms_att... | candle/candle-transformers/src/models/llama2_c_weights.rs/0 | {
"file_path": "candle/candle-transformers/src/models/llama2_c_weights.rs",
"repo_id": "candle",
"token_count": 3322
} | 73 |
import {
CallbackManagerForLLMRun,
Callbacks,
} from "@langchain/core/callbacks/manager";
import { LLM } from "@langchain/core/language_models/llms";
import { type BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
import { BaseMessage, MessageContent } from "@langchain/core/messages";
impo... | langchainjs/libs/langchain-google-common/src/llms.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-common/src/llms.ts",
"repo_id": "langchainjs",
"token_count": 1881
} | 1,005 |
import {
BaseRetriever,
type BaseRetrieverInput,
} from "@langchain/core/retrievers";
import type { VectorStoreInterface } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/documents";
import { BaseStore, type BaseStoreInterface } from "@langchain/core/stores";
import { createDocumentSt... | langchainjs/langchain/src/retrievers/multi_vector.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/multi_vector.ts",
"repo_id": "langchainjs",
"token_count": 917
} | 903 |
#![allow(dead_code)]
//! # Variational Auto-Encoder (VAE) Models.
//!
//! Auto-encoder models compress their input to a usually smaller latent space
//! before expanding it back to its original shape. This results in the latent values
//! compressing the original information.
use super::unet_2d_blocks::{
DownEncode... | candle/candle-transformers/src/models/stable_diffusion/vae.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/vae.rs",
"repo_id": "candle",
"token_count": 6006
} | 72 |
# Copyright 2024 Zhejiang University Team and 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
#
#... | diffusers/src/diffusers/schedulers/scheduling_pndm.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_pndm.py",
"repo_id": "diffusers",
"token_count": 9519
} | 263 |
from .activations import *
from .adaptive_avgmax_pool import \
adaptive_avgmax_pool2d, select_adaptive_pool2d, AdaptiveAvgMaxPool2d, SelectAdaptivePool2d
from .attention_pool import AttentionPoolLatent
from .attention_pool2d import AttentionPool2d, RotAttentionPool2d, RotaryEmbedding
from .blur_pool import BlurPool... | pytorch-image-models/timm/layers/__init__.py/0 | {
"file_path": "pytorch-image-models/timm/layers/__init__.py",
"repo_id": "pytorch-image-models",
"token_count": 1381
} | 385 |
"""Async utils."""
import asyncio
from itertools import zip_longest
from typing import Any, Coroutine, Iterable, List
def asyncio_module(show_progress: bool = False) -> Any:
if show_progress:
from tqdm.asyncio import tqdm_asyncio
module = tqdm_asyncio
else:
module = asyncio
retur... | llama_index/llama-index-legacy/llama_index/legacy/async_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/async_utils.py",
"repo_id": "llama_index",
"token_count": 1255
} | 1,547 |
"""Unit tests for chat_message_history modules"""
| langchain/libs/community/tests/unit_tests/chat_message_histories/__init__.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/chat_message_histories/__init__.py",
"repo_id": "langchain",
"token_count": 12
} | 398 |
from langchain_community.document_loaders.bigquery import BigQueryLoader
__all__ = ["BigQueryLoader"]
| langchain/libs/langchain/langchain/document_loaders/bigquery.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/bigquery.py",
"repo_id": "langchain",
"token_count": 29
} | 476 |
"""Genius Reader."""
from typing import List, Optional
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
class GeniusReader(BaseReader):
"""GeniusReader for various operations with lyricsgenius."""
def __init__(self, access_token: str):
"""Initialize ... | llama_index/llama-index-integrations/readers/llama-index-readers-genius/llama_index/readers/genius/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-genius/llama_index/readers/genius/base.py",
"repo_id": "llama_index",
"token_count": 2447
} | 1,356 |
import pytest
from llama_index.legacy.llms import ChatMessage
from llama_index.legacy.storage.chat_store.redis_chat_store import RedisChatStore
try:
from redis import Redis
except ImportError:
Redis = None # type: ignore
@pytest.mark.skipif(Redis is None, reason="redis not installed")
def test_add_messages(... | llama_index/llama-index-legacy/tests/storage/chat_store/test_redis_chat_store.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/storage/chat_store/test_redis_chat_store.py",
"repo_id": "llama_index",
"token_count": 1526
} | 1,632 |
from langchain_community.tools.office365.messages_search import (
O365SearchEmails,
SearchEmailsInput,
)
__all__ = ["SearchEmailsInput", "O365SearchEmails"]
| langchain/libs/langchain/langchain/tools/office365/messages_search.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/office365/messages_search.py",
"repo_id": "langchain",
"token_count": 58
} | 565 |
<jupyter_start><jupyter_text>Together AI LLMThis notebook shows how to use `Together AI` as an LLM. Together AI provides access to many state-of-the-art LLM models. Check out the full list of models [here](https://docs.together.ai/docs/inference-models).Visit https://together.ai and sign up to get an API key. Setup If... | llama_index/docs/examples/llm/together.ipynb/0 | {
"file_path": "llama_index/docs/examples/llm/together.ipynb",
"repo_id": "llama_index",
"token_count": 1137
} | 1,116 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/storage/docstore/llama-index-storage-docstore-firestore/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/docstore/llama-index-storage-docstore-firestore/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,453 |
"""Test AI21 API wrapper."""
from pathlib import Path
from langchain_community.llms.ai21 import AI21
from langchain_community.llms.loading import load_llm
def test_ai21_call() -> None:
"""Test valid call to ai21."""
llm = AI21(maxTokens=10)
output = llm("Say foo:")
assert isinstance(output, str)
d... | langchain/libs/community/tests/integration_tests/llms/test_ai21.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_ai21.py",
"repo_id": "langchain",
"token_count": 313
} | 334 |
from langchain_community.document_loaders.chatgpt import ChatGPTLoader, concatenate_rows
__all__ = ["concatenate_rows", "ChatGPTLoader"]
| langchain/libs/langchain/langchain/document_loaders/chatgpt.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/chatgpt.py",
"repo_id": "langchain",
"token_count": 46
} | 511 |
# 测试框架使用指南
## 简介
基于 pytest 编写的 **PyMilvus** 的测试框架。
**测试代码：** https://github.com/milvus-io/milvus/tree/master/tests/python_client
## 快速开始
### 部署 Milvus
Milvus 支持4种部署方式，请根据需求选择部署方式，PyMilvus 支持任意部署下的 Milvus。
* [源码编译部署](https://github.com/milvus-io/milvus/blob/master/DEVELOPMENT.md)
* Docker Compose 部署([单机版本](https:... | milvus/tests/python_client/README_CN.md/0 | {
"file_path": "milvus/tests/python_client/README_CN.md",
"repo_id": "milvus",
"token_count": 6808
} | 2,016 |
import inspect
from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers.image_processor import VaeImageProcessor
from diffusers.loaders import FromSingleFileMixin, LoraLoaderMixin, TextualInve... | diffusers/examples/community/latent_consistency_interpolate.py/0 | {
"file_path": "diffusers/examples/community/latent_consistency_interpolate.py",
"repo_id": "diffusers",
"token_count": 23228
} | 199 |
import * as fs from "fs";
import { setGlobalDispatcher, Agent } from "undici";
/**
* Load client certificates for mutual TLS authentication. This function must be called before any HTTP requests are made.
* This is a global setting that affects all HTTP requests made by the application using the native fetch API.
*... | chat-ui/src/lib/utils/loadClientCerts.ts/0 | {
"file_path": "chat-ui/src/lib/utils/loadClientCerts.ts",
"repo_id": "chat-ui",
"token_count": 551
} | 105 |
from functools import partial
from typing import Any, Optional, Type, cast
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.core.program.llm_prompt_program import BaseLLMFunctionProgram
from llama_index.core.prompts.base import PromptTemplate
from llama_index.program.guidance.utils import (
... | llama_index/llama-index-integrations/program/llama-index-program-guidance/llama_index/program/guidance/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/program/llama-index-program-guidance/llama_index/program/guidance/base.py",
"repo_id": "llama_index",
"token_count": 1342
} | 1,392 |
<jupyter_start><jupyter_code>import argparse
import json
import logging
import math
import os
import random
from pathlib import Path
from tqdm import tqdm
import datasets
from datasets import load_dataset, DatasetDict
import evaluate
import torch
from torch import nn
from torch.utils.data import DataLoader
import tr... | peft/examples/feature_extraction/peft_lora_embedding_semantic_similarity_inference.ipynb/0 | {
"file_path": "peft/examples/feature_extraction/peft_lora_embedding_semantic_similarity_inference.ipynb",
"repo_id": "peft",
"token_count": 2663
} | 311 |
import { PromptTemplate } from "@langchain/core/prompts";
export const SONG_DATA_SOURCE = `\
\`\`\`json
{
"content": "Lyrics of a song",
"attributes": {
"artist": {
"type": "string",
"description": "Name of the song artist"
},
"length": {
"type": "int... | langchainjs/langchain/src/chains/query_constructor/prompt.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/query_constructor/prompt.ts",
"repo_id": "langchainjs",
"token_count": 1325
} | 854 |
from langchain_community.embeddings.gradient_ai import GradientEmbeddings
__all__ = ["GradientEmbeddings"]
| langchain/libs/langchain/langchain/embeddings/gradient_ai.py/0 | {
"file_path": "langchain/libs/langchain/langchain/embeddings/gradient_ai.py",
"repo_id": "langchain",
"token_count": 33
} | 507 |
from dataclasses import dataclass
import tyro
from huggingface_hub import HfApi
@dataclass
class Args:
folder_path: str = "benchmark/trl"
path_in_repo: str = "images/benchmark"
repo_id: str = "trl-internal-testing/example-images"
repo_type: str = "dataset"
args = tyro.cli(Args)
api = HfApi()
api.u... | trl/benchmark/upload_benchmark.py/0 | {
"file_path": "trl/benchmark/upload_benchmark.py",
"repo_id": "trl",
"token_count": 200
} | 815 |
// 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/mq/msgstream/mq_factory.go/0 | {
"file_path": "milvus/pkg/mq/msgstream/mq_factory.go",
"repo_id": "milvus",
"token_count": 3063
} | 1,919 |
"""Google GenerativeAI Semantic Vector Store & Attributed Question and Answering.
Google Generative AI Semantic Retriever API is a managed end to end service that
allows developers to create a corpus of documents to perform semantic search on
related passages given a user query.
Google Generative AI Attributed Questi... | llama_index/llama-index-integrations/indices/llama-index-indices-managed-google/llama_index/indices/managed/google/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/indices/llama-index-indices-managed-google/llama_index/indices/managed/google/base.py",
"repo_id": "llama_index",
"token_count": 4013
} | 1,209 |
"""Test chat model integration."""
from __module_name__.chat_models import Chat__ModuleName__
def test_initialization() -> None:
"""Test chat model initialization."""
Chat__ModuleName__()
| langchain/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py/0 | {
"file_path": "langchain/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py",
"repo_id": "langchain",
"token_count": 58
} | 205 |
<jupyter_start><jupyter_text>Chat Engine - Best Mode The default chat engine mode is "best", which uses the "openai" mode if you are using an OpenAI model that supports the latest function calling API, otherwise uses the "react" mode If you're opening this Notebook on colab, you will probably need to install LlamaIndex... | llama_index/docs/examples/chat_engine/chat_engine_best.ipynb/0 | {
"file_path": "llama_index/docs/examples/chat_engine/chat_engine_best.ipynb",
"repo_id": "llama_index",
"token_count": 826
} | 1,105 |
import copy
import os
import pickle
import pytest
from tokenizers import (
AddedToken,
SentencePieceUnigramTokenizer,
Tokenizer,
models,
normalizers,
pre_tokenizers,
trainers,
)
from ..utils import data_dir, train_files
class TestBpeTrainer:
def test_can_modify(self):
traine... | tokenizers/bindings/python/tests/bindings/test_trainers.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_trainers.py",
"repo_id": "tokenizers",
"token_count": 4957
} | 419 |
"""Summarize query."""
import logging
from typing import Any, List, Optional, cast
from llama_index.core.base.base_retriever import BaseRetriever
from llama_index.core.callbacks.base import CallbackManager
from llama_index.core.data_structs.data_structs import IndexGraph
from llama_index.core.indices.tree.base import... | llama_index/llama-index-core/llama_index/core/indices/tree/all_leaf_retriever.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/tree/all_leaf_retriever.py",
"repo_id": "llama_index",
"token_count": 731
} | 1,183 |
# 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/src/transformers/models/electra/convert_electra_original_tf_checkpoint_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/electra/convert_electra_original_tf_checkpoint_to_pytorch.py",
"repo_id": "transformers",
"token_count": 1018
} | 681 |
<!--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/de/testing.md/0 | {
"file_path": "transformers/docs/source/de/testing.md",
"repo_id": "transformers",
"token_count": 19303
} | 471 |
# 🗂️ LlamaIndex 🦙
[](https://pypi.org/project/llama-index/)
[](https://github.com/jerryjliu/llama_index/graphs/contributors)
[![Discord](https://img.shields.io/discor... | llama_index/README.md/0 | {
"file_path": "llama_index/README.md",
"repo_id": "llama_index",
"token_count": 2219
} | 1,025 |
FROM python:3.10
LABEL maintainer="Hugging Face"
RUN apt update
RUN git clone https://github.com/huggingface/transformers
RUN python3 -m pip install --no-cache-dir --upgrade pip && python3 -m pip install --no-cache-dir git+https://github.com/huggingface/doc-builder ./transformers[dev]
RUN apt-get -y update && apt-get... | transformers/docker/transformers-doc-builder/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-doc-builder/Dockerfile",
"repo_id": "transformers",
"token_count": 292
} | 474 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | transformers/examples/tensorflow/translation/run_translation.py/0 | {
"file_path": "transformers/examples/tensorflow/translation/run_translation.py",
"repo_id": "transformers",
"token_count": 13554
} | 584 |
from langchain.prompts.few_shot import FewShotPromptTemplate
from langchain.prompts.prompt import PromptTemplate
fallacy_critique_example = PromptTemplate(
template="""Human: {input_prompt}
Model: {output_from_model}
Fallacy Critique Request: {fallacy_critique_request}
Fallacy Critique: {fallacy_critique}""",
... | langchain/libs/experimental/langchain_experimental/fallacy_removal/prompts.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/fallacy_removal/prompts.py",
"repo_id": "langchain",
"token_count": 1855
} | 418 |
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