text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
search_performance:
collections:
# -
# server:
# db_config.primary_path: /test/milvus/db_data_8/sift_1b_2048_128_l2_sq8_wal
# cache_config.cpu_cache_capacity: 150GB
# engine_config.use_blas_threshold: 0
# engine_config.gpu_search_threshold: 200
# gpu_resource_config.enable: ... | milvus/tests/benchmark/milvus_benchmark/suites/debug.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/debug.yaml",
"repo_id": "milvus",
"token_count": 1646
} | 1,942 |
from langchain.indexes import VectorstoreIndexCreator
from langchain_community.document_loaders import CSVLoader
from langchain_community.vectorstores import FAISS
loader = CSVLoader("/Users/harrisonchase/Downloads/titanic.csv")
docs = loader.load()
index_creator = VectorstoreIndexCreator(vectorstore_cls=FAISS)
inde... | langchain/templates/csv-agent/ingest.py/0 | {
"file_path": "langchain/templates/csv-agent/ingest.py",
"repo_id": "langchain",
"token_count": 123
} | 645 |
from typing import Any, List, Optional
from unittest.mock import MagicMock
import pytest
from llama_index.legacy.schema import NodeRelationship, RelatedNodeInfo, TextNode
from llama_index.legacy.vector_stores.azureaisearch import (
AzureAISearchVectorStore,
IndexManagement,
)
try:
from azure.search.docume... | llama_index/llama-index-legacy/tests/vector_stores/test_azureaisearch.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/vector_stores/test_azureaisearch.py",
"repo_id": "llama_index",
"token_count": 1670
} | 1,684 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _cuda_compat_cuh
#define _cuda_compat_cuh
// atomicAdd for half types, to support CC < 7.x
__device__ __forceinline__ void atomicAdd_half(half* address, half val)
{
unsigned int * address_as_ui = (unsigned int *) ((char *)address - (... | text-generation-inference/server/exllama_kernels/exllama_kernels/cu_compat.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cu_compat.cuh",
"repo_id": "text-generation-inference",
"token_count": 692
} | 419 |
[build-system]
build-backend = "poetry.core.masonry.api"
requires = ["poetry-core"]
[tool.codespell]
check-filenames = true
check-hidden = true
skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
[tool.llamahub]
classes = ["ZendeskReader"]
contains_example = false
import_path = "llama_index.readers.zendesk"
[to... | llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/pyproject.toml",
"repo_id": "llama_index",
"token_count": 697
} | 1,479 |
<jupyter_start><jupyter_text>Knowledge Distillation For Fine-Tuning A GPT-3.5 Judge (Correctness)This notebook has to do with fine-tuning an LLM Judge that evaluates the responses of another LLM to a user query. More specifically, we demonstrate how to use the `llama_index` library to distill knowledge from a GPT-4 Jud... | llama_index/docs/examples/finetuning/llm_judge/correctness/finetune_llm_judge_single_grading_correctness.ipynb/0 | {
"file_path": "llama_index/docs/examples/finetuning/llm_judge/correctness/finetune_llm_judge_single_grading_correctness.ipynb",
"repo_id": "llama_index",
"token_count": 4700
} | 1,120 |
from llama_index.llms.huggingface.base import HuggingFaceInferenceAPI, HuggingFaceLLM
__all__ = ["HuggingFaceLLM", "HuggingFaceInferenceAPI"]
| llama_index/llama-index-integrations/llms/llama-index-llms-huggingface/llama_index/llms/huggingface/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-huggingface/llama_index/llms/huggingface/__init__.py",
"repo_id": "llama_index",
"token_count": 50
} | 1,398 |
import unittest
import pytest
from langchain_community.document_loaders.parsers.language.typescript import (
TypeScriptSegmenter,
)
@pytest.mark.requires("tree_sitter", "tree_sitter_languages")
class TestTypeScriptSegmenter(unittest.TestCase):
def setUp(self) -> None:
self.example_code = """function... | langchain/libs/community/tests/unit_tests/document_loaders/parsers/language/test_typescript.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/document_loaders/parsers/language/test_typescript.py",
"repo_id": "langchain",
"token_count": 764
} | 367 |
import os
import torch
from loguru import logger
from text_generation_server.utils.import_utils import IS_CUDA_SYSTEM, IS_ROCM_SYSTEM
if os.getenv("USE_FLASH_ATTENTION", "").lower() == "false":
raise ImportError("`USE_FLASH_ATTENTION` is false.")
if not torch.cuda.is_available():
raise ImportError("CUDA is ... | text-generation-inference/server/text_generation_server/utils/flash_attn.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/flash_attn.py",
"repo_id": "text-generation-inference",
"token_count": 2911
} | 445 |
use std::f32::consts::E;
use crate::chroma_proto;
use crate::chroma_proto::{
GetVectorsRequest, GetVectorsResponse, QueryVectorsRequest, QueryVectorsResponse,
};
use crate::config::{Configurable, WorkerConfig};
use crate::errors::ChromaError;
use crate::segment::SegmentManager;
use crate::types::ScalarEncoding;
us... | chroma/rust/worker/src/server.rs/0 | {
"file_path": "chroma/rust/worker/src/server.rs",
"repo_id": "chroma",
"token_count": 3371
} | 62 |
# Introduction to Q-Learning [[introduction-q-learning]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/thumbnail.jpg" alt="Unit 2 thumbnail" width="100%">
In the first unit of this class, we learned about Reinforcement Learning (RL), the RL process, and the ... | deep-rl-class/units/en/unit2/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 466
} | 162 |
import json
from typing import Any, Callable, Iterator, List, Mapping, Optional
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
RecordHandler = Callable[[Any, Optional[str]], Document]
class AirbyteCDKReader(BaseReader):
"""AirbyteCDKReader reader.
Retrieve... | llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-cdk/llama_index/readers/airbyte_cdk/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-cdk/llama_index/readers/airbyte_cdk/base.py",
"repo_id": "llama_index",
"token_count": 792
} | 1,448 |
from langchain_core.outputs import (
ChatGeneration,
ChatGenerationChunk,
ChatResult,
Generation,
GenerationChunk,
LLMResult,
RunInfo,
)
__all__ = [
"Generation",
"GenerationChunk",
"ChatGeneration",
"ChatGenerationChunk",
"RunInfo",
"ChatResult",
"LLMResult",
]
| langchain/libs/langchain/langchain/schema/output.py/0 | {
"file_path": "langchain/libs/langchain/langchain/schema/output.py",
"repo_id": "langchain",
"token_count": 139
} | 548 |
// 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/resource_manager.go/0 | {
"file_path": "milvus/internal/querycoordv2/meta/resource_manager.go",
"repo_id": "milvus",
"token_count": 6791
} | 1,862 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Error as E;
use clap::{Parser, ValueEnum};
use candle::{DType, Tensor};
use candle_examples::token_output_stream::TokenOutputStream;
use candle_nn::VarBuilder;
use candle_transformers::models::... | candle/candle-examples/examples/marian-mt/main.rs/0 | {
"file_path": "candle/candle-examples/examples/marian-mt/main.rs",
"repo_id": "candle",
"token_count": 2385
} | 42 |
---
hide_table_of_contents: true
---
# Docx files
This example goes over how to load data from docx files.
# Setup
```bash npm2yarn
npm install mammoth
```
# Usage
```typescript
import { DocxLoader } from "langchain/document_loaders/fs/docx";
const loader = new DocxLoader(
"src/document_loaders/tests/example_d... | langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/docx.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/docx.mdx",
"repo_id": "langchainjs",
"token_count": 137
} | 701 |
from langchain_community.tools.google_lens.tool import GoogleLensQueryRun
__all__ = ["GoogleLensQueryRun"]
| langchain/libs/langchain/langchain/tools/google_lens/tool.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/google_lens/tool.py",
"repo_id": "langchain",
"token_count": 32
} | 561 |
import { test } from "@jest/globals";
test("Test chat model", async () => {
// Your test here
});
| langchainjs/libs/create-langchain-integration/template/src/tests/chat_models.test.ts/0 | {
"file_path": "langchainjs/libs/create-langchain-integration/template/src/tests/chat_models.test.ts",
"repo_id": "langchainjs",
"token_count": 34
} | 1,039 |
"""Utilities for GPT indices."""
import logging
import re
from typing import Dict, List, Optional, Sequence, Set, Tuple
from llama_index.legacy.embeddings.base import BaseEmbedding
from llama_index.legacy.embeddings.multi_modal_base import MultiModalEmbedding
from llama_index.legacy.schema import BaseNode, ImageNode,... | llama_index/llama-index-legacy/llama_index/legacy/indices/utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/utils.py",
"repo_id": "llama_index",
"token_count": 3484
} | 1,724 |
"""BabyAGI agent."""
from collections import deque
from typing import Any, Dict, List, Optional
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.chains.base import Chain
from langchain_core.language_models import BaseLanguageModel
from langchain_core.vectorstores import VectorStore
f... | langchain/libs/experimental/langchain_experimental/autonomous_agents/baby_agi/baby_agi.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/autonomous_agents/baby_agi/baby_agi.py",
"repo_id": "langchain",
"token_count": 3981
} | 426 |
import os
import pytest
from unittest.mock import patch, MagicMock
import chromadb
from chromadb.db.impl.sqlite import SqliteDB
from chromadb.config import System, Settings
@pytest.mark.parametrize("migrations_hash_algorithm", [None, "md5", "sha256"])
@patch("chromadb.api.fastapi.FastAPI")
@patch.dict(os.environ, {}... | chroma/chromadb/test/db/test_hash.py/0 | {
"file_path": "chroma/chromadb/test/db/test_hash.py",
"repo_id": "chroma",
"token_count": 1615
} | 23 |
from langchain.prompts.prompt import PromptTemplate
sentence_template = """Given the following fields, create a sentence about them.
Make the sentence detailed and interesting. Use every given field.
If any additional preferences are given, use them during sentence construction as well.
Fields:
{fields}
Preferences:
... | langchain/libs/experimental/langchain_experimental/synthetic_data/prompts.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/synthetic_data/prompts.py",
"repo_id": "langchain",
"token_count": 126
} | 449 |
"""Utils for LLM Compiler."""
import ast
import re
from typing import Any, Dict, List, Sequence, Tuple, Union
from llama_index.core.tools.function_tool import FunctionTool
from llama_index.core.tools.types import BaseTool, adapt_to_async_tool
from .schema import (
LLMCompilerParseResult,
LLMCompilerTask,
)
#... | llama_index/llama-index-packs/llama-index-packs-agents-llm-compiler/llama_index/packs/agents_llm_compiler/utils.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-agents-llm-compiler/llama_index/packs/agents_llm_compiler/utils.py",
"repo_id": "llama_index",
"token_count": 2042
} | 1,690 |
// 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/handlers.go/0 | {
"file_path": "milvus/internal/querycoordv2/handlers.go",
"repo_id": "milvus",
"token_count": 5096
} | 1,975 |
package common
import (
"reflect"
"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
)
type KeyDataPairs []*commonpb.KeyDataPair
func (pairs KeyDataPairs) Clone() KeyDataPairs {
clone := make(KeyDataPairs, 0, len(pairs))
for _, pair := range pairs {
clone = append(clone, &commonpb.KeyDataPair{
Key: pa... | milvus/pkg/common/key_data_pairs.go/0 | {
"file_path": "milvus/pkg/common/key_data_pairs.go",
"repo_id": "milvus",
"token_count": 315
} | 1,879 |
# coding=utf-8
# 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 r... | transformers/tests/models/hubert/test_modeling_hubert.py/0 | {
"file_path": "transformers/tests/models/hubert/test_modeling_hubert.py",
"repo_id": "transformers",
"token_count": 18040
} | 819 |
// Code generated by mockery v2.33.3. DO NOT EDIT.
package mocks
import (
dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel"
mock "github.com/stretchr/testify/mock"
)
// INotificationDb is an autogenerated mock type for the INotificationDb type
type INotificationDb struct {
mock.Mock
}
... | chroma/go/coordinator/internal/metastore/db/dbmodel/mocks/INotificationDb.go/0 | {
"file_path": "chroma/go/coordinator/internal/metastore/db/dbmodel/mocks/INotificationDb.go",
"repo_id": "chroma",
"token_count": 1121
} | 51 |
# 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/complete_cv_example.py/0 | {
"file_path": "accelerate/examples/complete_cv_example.py",
"repo_id": "accelerate",
"token_count": 5356
} | 5 |
<jupyter_start><jupyter_text>Rerank can speed up an LLM query without sacrificing accuracy (and in fact, probably improving it). It does so by pruning away irrelevant nodes from the context. If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-... | llama_index/docs/examples/node_postprocessor/FlagEmbeddingReranker.ipynb/0 | {
"file_path": "llama_index/docs/examples/node_postprocessor/FlagEmbeddingReranker.ipynb",
"repo_id": "llama_index",
"token_count": 1476
} | 1,070 |
module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
}
| weblangchain/nextjs/postcss.config.js/0 | {
"file_path": "weblangchain/nextjs/postcss.config.js",
"repo_id": "weblangchain",
"token_count": 38
} | 1,997 |
- sections:
- local: index
title: 🤗 Transformers
- local: quicktour
title: Quick tour
- local: installation
title: Installation
title: Get started
- sections:
- local: pipeline_tutorial
title: Run inference with pipelines
- local: autoclass_tutorial
title: Write portable code with AutoC... | transformers/docs/source/en/_toctree.yml/0 | {
"file_path": "transformers/docs/source/en/_toctree.yml",
"repo_id": "transformers",
"token_count": 10798
} | 491 |
# 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/tests/test_iterative_sft_trainer.py/0 | {
"file_path": "trl/tests/test_iterative_sft_trainer.py",
"repo_id": "trl",
"token_count": 1898
} | 790 |
import sys
from typing import Any, AsyncIterator, Iterator
import pytest
from syrupy import SnapshotAssertion
from langchain_core.load import dumps
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import (
Runnable,
RunnableGenerator,
RunnableLambda,
RunnableParallel,
... | langchain/libs/core/tests/unit_tests/runnables/test_fallbacks.py/0 | {
"file_path": "langchain/libs/core/tests/unit_tests/runnables/test_fallbacks.py",
"repo_id": "langchain",
"token_count": 3715
} | 419 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.semanticscholar import SemanticScholarReader
def test_class():
names_of_base_classes = [b.__name__ for b in SemanticScholarReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-semanticscholar/tests/test_readers_semanticscholar.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-semanticscholar/tests/test_readers_semanticscholar.py",
"repo_id": "llama_index",
"token_count": 94
} | 1,521 |
// 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/hook.cpp/0 | {
"file_path": "milvus/internal/core/src/simd/hook.cpp",
"repo_id": "milvus",
"token_count": 9710
} | 1,887 |
# 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/kandinsky2_2/test_kandinsky_prior_emb2emb.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky2_2/test_kandinsky_prior_emb2emb.py",
"repo_id": "diffusers",
"token_count": 3478
} | 252 |
from typing import Any, List, Literal
from langchain_core.messages.base import (
BaseMessage,
BaseMessageChunk,
merge_content,
)
class ChatMessage(BaseMessage):
"""Message that can be assigned an arbitrary speaker (i.e. role)."""
role: str
"""The speaker / role of the Message."""
type: ... | langchain/libs/core/langchain_core/messages/chat.py/0 | {
"file_path": "langchain/libs/core/langchain_core/messages/chat.py",
"repo_id": "langchain",
"token_count": 886
} | 417 |
[tool.poetry]
name = "rag-singlestoredb"
version = "0.0.1"
description = "RAG using SingleStoreDB"
authors = [
"Alex Peng <apeng@singlestore.com>"
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
openai = "<2"
singlestoredb = ">=0.8.1"
tiktoken = "^0.5.1"
[tool.poetry.g... | langchain/templates/rag-singlestoredb/pyproject.toml/0 | {
"file_path": "langchain/templates/rag-singlestoredb/pyproject.toml",
"repo_id": "langchain",
"token_count": 312
} | 689 |
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Sequence, Union
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
if TYPE_CHECKING:
import tweepy
from tweepy import OAuth2BearerHandler, OAu... | langchain/libs/community/langchain_community/document_loaders/twitter.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/twitter.py",
"repo_id": "langchain",
"token_count": 1547
} | 246 |
# coding=utf-8
# Copyright 2018 The Google AI Language Team 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 License.
# You may obtain a cop... | transformers/examples/legacy/token-classification/run_ner.py/0 | {
"file_path": "transformers/examples/legacy/token-classification/run_ner.py",
"repo_id": "transformers",
"token_count": 5023
} | 560 |
"""
Test Amazon Bedrock API wrapper and services i.e 'Guardrails for Amazon Bedrock'.
You can get a list of models from the bedrock client by running 'bedrock_models()'
"""
import os
from typing import Any
import pytest
from langchain_core.callbacks import AsyncCallbackHandler
from langchain_community.llms.bedrock ... | langchain/libs/community/tests/integration_tests/llms/test_bedrock.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_bedrock.py",
"repo_id": "langchain",
"token_count": 1878
} | 356 |
import {
MaskingParser,
RegexMaskingTransformer,
} from "langchain/experimental/masking";
// A simple hash function for demonstration purposes
function simpleHash(input: string): string {
let hash = 0;
for (let i = 0; i < input.length; i += 1) {
const char = input.charCodeAt(i);
hash = (hash << 5) - ha... | langchainjs/examples/src/experimental/masking/kitchen_sink.ts/0 | {
"file_path": "langchainjs/examples/src/experimental/masking/kitchen_sink.ts",
"repo_id": "langchainjs",
"token_count": 1270
} | 775 |
// 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/task/scheduler.go/0 | {
"file_path": "milvus/internal/querycoordv2/task/scheduler.go",
"repo_id": "milvus",
"token_count": 9357
} | 2,037 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/metrics/precision/precision.py/0 | {
"file_path": "datasets/metrics/precision/precision.py",
"repo_id": "datasets",
"token_count": 2663
} | 123 |
include LICENSE
include src/diffusers/utils/model_card_template.md
| diffusers/MANIFEST.in/0 | {
"file_path": "diffusers/MANIFEST.in",
"repo_id": "diffusers",
"token_count": 20
} | 178 |
from langchain_community.tools.e2b_data_analysis.tool import (
E2BDataAnalysisTool,
E2BDataAnalysisToolArguments,
UploadedFile,
)
__all__ = [
"UploadedFile",
"E2BDataAnalysisToolArguments",
"E2BDataAnalysisTool",
]
| langchain/libs/langchain/langchain/tools/e2b_data_analysis/tool.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/e2b_data_analysis/tool.py",
"repo_id": "langchain",
"token_count": 98
} | 552 |
# HuggingFace Inference
This Embeddings integration uses the HuggingFace Inference API to generate embeddings for a given text using by default the `sentence-transformers/distilbert-base-nli-mean-tokens` model. You can pass a different model name to the constructor to use a different model.
```bash npm2yarn
npm insta... | langchainjs/docs/core_docs/docs/integrations/text_embedding/hugging_face_inference.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/text_embedding/hugging_face_inference.mdx",
"repo_id": "langchainjs",
"token_count": 189
} | 769 |
import json
import os
import re
import string
from collections import Counter
from shutil import rmtree
from typing import Any, Dict, List, Optional, Tuple
import requests
import tqdm
from llama_index.core.base.base_query_engine import BaseQueryEngine
from llama_index.core.base.base_retriever import BaseRetriever
from... | llama_index/llama-index-core/llama_index/core/evaluation/benchmarks/hotpotqa.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/evaluation/benchmarks/hotpotqa.py",
"repo_id": "llama_index",
"token_count": 3380
} | 1,145 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/readers/redis/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/redis/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,706 |
# coding=utf-8
# Copyright 2022 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/test_onnx_stable_diffusion_upscale.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_upscale.py",
"repo_id": "diffusers",
"token_count": 3918
} | 282 |
"""Finetuning modules."""
from llama_index.legacy.finetuning.embeddings.adapter import (
EmbeddingAdapterFinetuneEngine,
)
from llama_index.legacy.finetuning.embeddings.common import (
EmbeddingQAFinetuneDataset,
generate_qa_embedding_pairs,
)
from llama_index.legacy.finetuning.embeddings.sentence_transfor... | llama_index/llama-index-legacy/llama_index/legacy/finetuning/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/finetuning/__init__.py",
"repo_id": "llama_index",
"token_count": 410
} | 1,653 |
from llama_index.embeddings.cohere.base import CohereEmbedding
__all__ = ["CohereEmbedding"]
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/__init__.py",
"repo_id": "llama_index",
"token_count": 34
} | 1,225 |
import pytest
from llama_index.legacy.embeddings.elasticsearch import ElasticsearchEmbedding
try:
import elasticsearch
except ImportError:
elasticsearch = None # type: ignore
@pytest.fixture()
def model_id() -> str:
# Replace with your actual model_id
return "your_model_id"
@pytest.fixture()
def e... | llama_index/llama-index-legacy/tests/embeddings/test_elasticsearch.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/embeddings/test_elasticsearch.py",
"repo_id": "llama_index",
"token_count": 386
} | 1,617 |
# Using MKL
| candle/candle-book/src/advanced/mkl.md/0 | {
"file_path": "candle/candle-book/src/advanced/mkl.md",
"repo_id": "candle",
"token_count": 5
} | 21 |
from llama_index.callbacks.openinference.base import OpenInferenceCallbackHandler
__all__ = ["OpenInferenceCallbackHandler"]
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-openinference/llama_index/callbacks/openinference/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-openinference/llama_index/callbacks/openinference/__init__.py",
"repo_id": "llama_index",
"token_count": 34
} | 1,230 |
# 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/musicgen/convert_musicgen_transformers.py/0 | {
"file_path": "transformers/src/transformers/models/musicgen/convert_musicgen_transformers.py",
"repo_id": "transformers",
"token_count": 3641
} | 636 |
<!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/clip.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/clip.md",
"repo_id": "transformers",
"token_count": 2696
} | 486 |
from typing import Any, Dict, Type
from llama_index.legacy.readers.base import BasePydanticReader
from llama_index.legacy.readers.discord_reader import DiscordReader
from llama_index.legacy.readers.elasticsearch import ElasticsearchReader
from llama_index.legacy.readers.google_readers.gdocs import GoogleDocsReader
fro... | llama_index/llama-index-legacy/llama_index/legacy/readers/loading.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/loading.py",
"repo_id": "llama_index",
"token_count": 741
} | 1,635 |
from langchain_community.llms.volcengine_maas import (
VolcEngineMaasBase,
VolcEngineMaasLLM,
)
__all__ = ["VolcEngineMaasBase", "VolcEngineMaasLLM"]
| langchain/libs/langchain/langchain/llms/volcengine_maas.py/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/volcengine_maas.py",
"repo_id": "langchain",
"token_count": 66
} | 517 |
"""Office365 toolkit."""
| langchain/libs/community/langchain_community/agent_toolkits/office365/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/agent_toolkits/office365/__init__.py",
"repo_id": "langchain",
"token_count": 8
} | 230 |
<jupyter_start><jupyter_text>iMessageThis notebook shows how to use the iMessage chat loader. This class helps convert iMessage conversations to LangChain chat messages.On MacOS, iMessage stores conversations in a sqlite database at `~/Library/Messages/chat.db` (at least for macOS Ventura 13.4). The `IMessageChatLoader... | langchain/docs/docs/integrations/chat_loaders/imessage.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/chat_loaders/imessage.ipynb",
"repo_id": "langchain",
"token_count": 2103
} | 94 |
<jupyter_start><jupyter_text>YouTube audioBuilding chat or QA applications on YouTube videos is a topic of high interest.Below we show how to easily go from a `YouTube url` to `audio of the video` to `text` to `chat`!We wil use the `OpenAIWhisperParser`, which will use the OpenAI Whisper API to transcribe audio to text... | langchain/docs/docs/integrations/document_loaders/youtube_audio.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/youtube_audio.ipynb",
"repo_id": "langchain",
"token_count": 1055
} | 113 |
import torch
import torch.distributed
from typing import List, Optional, Tuple
from transformers import (
AutoTokenizer,
AutoConfig,
AutoProcessor,
)
from text_generation_server.models.custom_modeling.idefics_config import IdeficsConfig
from text_generation_server.models.custom_modeling.idefics_processin... | text-generation-inference/server/text_generation_server/models/idefics.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/idefics.py",
"repo_id": "text-generation-inference",
"token_count": 1306
} | 404 |
"""
This module maintains the list of transformations that are supported by the system.
"""
from enum import Enum
from typing import Generic, Sequence, Type, TypeVar
from llama_index.core.bridge.pydantic import BaseModel, Field, GenericModel
from llama_index.core.extractors import (
KeywordExtractor,
Question... | llama_index/llama-index-core/llama_index/core/ingestion/transformations.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/ingestion/transformations.py",
"repo_id": "llama_index",
"token_count": 4769
} | 1,184 |
# Copyright 2024 Harutatsu Akiyama, Jinbin Bai, 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... | diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py",
"repo_id": "diffusers",
"token_count": 39925
} | 244 |
"""Init file."""
from llama_index.readers.papers.arxiv.base import ArxivReader
from llama_index.readers.papers.pubmed.base import PubmedReader
__all__ = ["ArxivReader", "PubmedReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-papers/llama_index/readers/papers/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-papers/llama_index/readers/papers/__init__.py",
"repo_id": "llama_index",
"token_count": 65
} | 1,399 |
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/electra.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/electra.md",
"repo_id": "transformers",
"token_count": 2211
} | 474 |
from abc import ABC, abstractmethod
from typing import List
from langchain_core.runnables.config import run_in_executor
class Embeddings(ABC):
"""Interface for embedding models."""
@abstractmethod
def embed_documents(self, texts: List[str]) -> List[List[float]]:
"""Embed search docs."""
@ab... | langchain/libs/core/langchain_core/embeddings.py/0 | {
"file_path": "langchain/libs/core/langchain_core/embeddings.py",
"repo_id": "langchain",
"token_count": 286
} | 399 |
import { test, expect } from "@jest/globals";
import { SystemMessage, HumanMessage } from "@langchain/core/messages";
import { ChatAlibabaTongyi } from "../alibaba_tongyi.js";
interface TestConfig {
modelName: string | undefined;
config: {
description?: string;
temperature?: number;
topP?: number;
... | langchainjs/libs/langchain-community/src/chat_models/tests/chatalitongyi.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/chat_models/tests/chatalitongyi.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1271
} | 978 |
# coding=utf-8
# Copyright 2020 Microsoft and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... | transformers/src/transformers/models/deberta_v2/tokenization_deberta_v2.py/0 | {
"file_path": "transformers/src/transformers/models/deberta_v2/tokenization_deberta_v2.py",
"repo_id": "transformers",
"token_count": 9944
} | 669 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-bitbucket/llama_index/readers/bitbucket/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-bitbucket/llama_index/readers/bitbucket/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,328 |
import os
import argparse
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
set_seed,
default_data_collator,
BitsAndBytesConfig,
Trainer,
TrainingArguments,
)
from datasets import load_from_disk
import torch
from peft import PeftConfig, PeftModel
def parse_arge():
"""Pars... | notebooks/sagemaker/28_train_llms_with_qlora/scripts/run_clm.py/0 | {
"file_path": "notebooks/sagemaker/28_train_llms_with_qlora/scripts/run_clm.py",
"repo_id": "notebooks",
"token_count": 2378
} | 331 |
// TODO: Add an offline mode.
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
use anyhow::{Error as E, Result};
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::generation::LogitsProcessor;
use clap::Parser;
use h... | candle/candle-examples/examples/falcon/main.rs/0 | {
"file_path": "candle/candle-examples/examples/falcon/main.rs",
"repo_id": "candle",
"token_count": 2723
} | 37 |
python_tests()
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,251 |
# Fireworks
This page covers how to use [Fireworks](https://app.fireworks.ai/) models within
Langchain.
## Installation and setup
- Install the Fireworks client library.
```
pip install fireworks-ai
```
- Get a Fireworks API key by signing up at [app.fireworks.ai](https://app.fireworks.ai).
- Authenticate by... | langchain/docs/docs/integrations/providers/fireworks.md/0 | {
"file_path": "langchain/docs/docs/integrations/providers/fireworks.md",
"repo_id": "langchain",
"token_count": 404
} | 140 |
from langchain_community.llms.titan_takeoff_pro import TitanTakeoffPro
__all__ = ["TitanTakeoffPro"]
| langchain/libs/langchain/langchain/llms/titan_takeoff_pro.py/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/titan_takeoff_pro.py",
"repo_id": "langchain",
"token_count": 35
} | 566 |
<jupyter_start><jupyter_text>IntroductionIn this notebook, we will learn how to use [LoRA](https://arxiv.org/abs/2106.09685) from 🤗 PEFT to fine-tune an image classification model by ONLY using **0.77%** of the original trainable parameters of the model. LoRA adds low-rank "update matrices" to certain blocks in the un... | peft/examples/image_classification/image_classification_peft_lora.ipynb/0 | {
"file_path": "peft/examples/image_classification/image_classification_peft_lora.ipynb",
"repo_id": "peft",
"token_count": 6369
} | 327 |
import {
GoogleAbstractedClient,
GoogleBaseLLM,
GoogleBaseLLMInput,
} from "@langchain/google-common";
import { GoogleAuthOptions } from "google-auth-library";
import { GAuthClient } from "./auth.js";
/**
* Input to LLM class.
*/
export interface GoogleLLMInput extends GoogleBaseLLMInput<GoogleAuthOptions> {}
... | langchainjs/libs/langchain-google-gauth/src/llms.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-gauth/src/llms.ts",
"repo_id": "langchainjs",
"token_count": 257
} | 1,098 |
from abc import abstractmethod
class Reader:
def __init__(self):
pass
@abstractmethod
def _filename(self, index, basename=False, absolute=False):
pass
def filename(self, index, basename=False, absolute=False):
return self._filename(index, basename=basename, absolute=absolute)... | pytorch-image-models/timm/data/readers/reader.py/0 | {
"file_path": "pytorch-image-models/timm/data/readers/reader.py",
"repo_id": "pytorch-image-models",
"token_count": 171
} | 359 |
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.packs.rag_fusion_query_pipeline import RAGFusionPipelinePack
def test_class():
names_of_base_classes = [b.__name__ for b in RAGFusionPipelinePack.__mro__]
assert BaseLlamaPack.__name__ in names_of_base_classes
| llama_index/llama-index-packs/llama-index-packs-rag-fusion-query-pipeline/tests/test_packs_query.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-rag-fusion-query-pipeline/tests/test_packs_query.py",
"repo_id": "llama_index",
"token_count": 111
} | 1,691 |
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.embeddings.cohere import CohereEmbedding
def test_anyscale_class():
emb = CohereEmbedding(cohere_api_key="fake_key")
assert isinstance(emb, BaseEmbedding)
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/tests/test_embeddings_cohere.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/tests/test_embeddings_cohere.py",
"repo_id": "llama_index",
"token_count": 89
} | 1,271 |
[tool.poetry]
name = "bedrock-jcvd"
version = "0.1.0"
description = "LangChain template that behaves like JCVD using Anthropic's Claude on Amazon Bedrock"
authors = ["JGalego <jgalego1990@gmail.com>"]
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11"
uvicorn = "^0.23.2"
langserve = {extras = ["server"],... | langchain/templates/bedrock-jcvd/pyproject.toml/0 | {
"file_path": "langchain/templates/bedrock-jcvd/pyproject.toml",
"repo_id": "langchain",
"token_count": 304
} | 629 |
# LlamaIndex Callbacks Integration: OpenInference
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-openinference/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-openinference/README.md",
"repo_id": "llama_index",
"token_count": 12
} | 1,247 |
<jupyter_start><jupyter_text>Anyscale[Anyscale](https://www.anyscale.com/) is a fully-managed [Ray](https://www.ray.io/) platform, on which you can build, deploy, and manage scalable AI and Python applicationsThis example goes over how to use LangChain to interact with [Anyscale Endpoint](https://app.endpoints.anyscale... | langchain/docs/docs/integrations/llms/anyscale.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/anyscale.ipynb",
"repo_id": "langchain",
"token_count": 622
} | 111 |
[build-system]
build-backend = "poetry.core.masonry.api"
requires = ["poetry-core"]
[tool.codespell]
check-filenames = true
check-hidden = true
skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
[tool.llamahub]
classes = ["SpotifyReader"]
contains_example = false
import_path = "llama_index.readers.spotify"
[to... | llama_index/llama-index-integrations/readers/llama-index-readers-spotify/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-spotify/pyproject.toml",
"repo_id": "llama_index",
"token_count": 664
} | 1,445 |
"""Golden API toolkit."""
from langchain_community.tools.golden_query.tool import GoldenQueryRun
__all__ = [
"GoldenQueryRun",
]
| langchain/libs/langchain/langchain/tools/golden_query/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/golden_query/__init__.py",
"repo_id": "langchain",
"token_count": 46
} | 556 |
<!--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/serialization.md/0 | {
"file_path": "transformers/docs/source/zh/serialization.md",
"repo_id": "transformers",
"token_count": 4917
} | 516 |
python_sources()
| llama_index/llama-index-integrations/retrievers/llama-index-retrievers-bm25/llama_index/retrievers/bm25/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/retrievers/llama-index-retrievers-bm25/llama_index/retrievers/bm25/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,456 |
use crate::models::with_tracing::QMatMul;
use crate::quantized_nn::{layer_norm, linear, Embedding, Linear};
pub use crate::quantized_var_builder::VarBuilder;
use candle::{Module, Result, Tensor, D};
use candle_nn::LayerNorm;
pub type Config = super::blip_text::Config;
#[derive(Debug, Clone)]
struct TextEmbeddings {
... | candle/candle-transformers/src/models/quantized_blip_text.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_blip_text.rs",
"repo_id": "candle",
"token_count": 7022
} | 66 |
"""Utilities for loading configurations from langchain_core-hub."""
import os
import re
import tempfile
from pathlib import Path, PurePosixPath
from typing import Any, Callable, Optional, Set, TypeVar, Union
from urllib.parse import urljoin
import requests
DEFAULT_REF = os.environ.get("LANGCHAIN_HUB_DEFAULT_REF", "m... | langchain/libs/core/langchain_core/utils/loading.py/0 | {
"file_path": "langchain/libs/core/langchain_core/utils/loading.py",
"repo_id": "langchain",
"token_count": 759
} | 401 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/core/src/exec/operator/FilterBits.cpp/0 | {
"file_path": "milvus/internal/core/src/exec/operator/FilterBits.cpp",
"repo_id": "milvus",
"token_count": 932
} | 1,925 |
import itertools
import warnings
from dataclasses import InitVar, dataclass
from io import StringIO
from typing import Optional
import pyarrow as pa
import datasets
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
logger = datasets.utils.logging.get_logger(__name__)
... | datasets/src/datasets/packaged_modules/text/text.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/text/text.py",
"repo_id": "datasets",
"token_count": 3042
} | 146 |
# coding=utf-8
# Copyright 2022 Meta Platforms, Inc. 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... | transformers/src/transformers/models/levit/modeling_levit.py/0 | {
"file_path": "transformers/src/transformers/models/levit/modeling_levit.py",
"repo_id": "transformers",
"token_count": 12814
} | 681 |
package compressor
import (
"bytes"
"fmt"
"io"
"strings"
"sync"
"testing"
"github.com/klauspost/compress/zstd"
"github.com/stretchr/testify/assert"
"github.com/milvus-io/milvus/pkg/util/hardware"
)
func TestZstdCompress(t *testing.T) {
data := "hello zstd algorithm!"
compressed := new(bytes.Buffer)
orig... | milvus/pkg/util/compressor/compressor_test.go/0 | {
"file_path": "milvus/pkg/util/compressor/compressor_test.go",
"repo_id": "milvus",
"token_count": 1695
} | 1,897 |
import { initializeAgentExecutorWithOptions } from "langchain/agents";
import { OpenAI } from "@langchain/openai";
import {
GmailCreateDraft,
GmailGetMessage,
GmailGetThread,
GmailSearch,
GmailSendMessage,
} from "@langchain/community/tools/gmail";
import { StructuredTool } from "@langchain/core/tools";
expo... | langchainjs/examples/src/tools/gmail.ts/0 | {
"file_path": "langchainjs/examples/src/tools/gmail.ts",
"repo_id": "langchainjs",
"token_count": 725
} | 823 |
""" EvoNorm in PyTorch
Based on `Evolving Normalization-Activation Layers` - https://arxiv.org/abs/2004.02967
@inproceedings{NEURIPS2020,
author = {Liu, Hanxiao and Brock, Andy and Simonyan, Karen and Le, Quoc},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato ... | pytorch-image-models/timm/layers/evo_norm.py/0 | {
"file_path": "pytorch-image-models/timm/layers/evo_norm.py",
"repo_id": "pytorch-image-models",
"token_count": 6684
} | 344 |
reviewers:
- binbinlv
- ThreadDao
- wangting0128
- yanliang567
- zhuwenxing
approvers:
- maintainers
labels:
- area/test
- sig/testing
| milvus/tests/OWNERS/0 | {
"file_path": "milvus/tests/OWNERS",
"repo_id": "milvus",
"token_count": 66
} | 1,849 |
from rag_aws_bedrock.chain import chain
if __name__ == "__main__":
query = "What is this data about?"
print(chain.invoke(query)) # noqa: T201
| langchain/templates/rag-aws-bedrock/main.py/0 | {
"file_path": "langchain/templates/rag-aws-bedrock/main.py",
"repo_id": "langchain",
"token_count": 56
} | 711 |
[build-system]
build-backend = "poetry.core.masonry.api"
requires = ["poetry-core"]
[tool.codespell]
check-filenames = true
check-hidden = true
skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
[tool.llamahub]
classes = ["GuruReader"]
contains_example = false
import_path = "llama_index.readers.guru"
[tool.myp... | llama_index/llama-index-integrations/readers/llama-index-readers-guru/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-guru/pyproject.toml",
"repo_id": "llama_index",
"token_count": 661
} | 1,332 |
// 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/eventlog/logger.go/0 | {
"file_path": "milvus/pkg/eventlog/logger.go",
"repo_id": "milvus",
"token_count": 495
} | 1,817 |
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