text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
package utils
import (
"errors"
"github.com/spaolacci/murmur3"
)
type Hasher = func(member string, key string) uint64
type Member = string
type Members = []Member
type Key = string
// assign assigns a key to a member using the rendezvous hashing algorithm.
func Assign(key Key, members Members, hasher Hasher) (Mem... | chroma/go/coordinator/internal/utils/rendezvous_hash.go/0 | {
"file_path": "chroma/go/coordinator/internal/utils/rendezvous_hash.go",
"repo_id": "chroma",
"token_count": 517
} | 51 |
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding
def test_azure_openai_embedding_class():
names_of_base_classes = [b.__name__ for b in AzureOpenAIEmbedding.__mro__]
assert BaseEmbedding.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/tests/test_embeddings_azure_openai.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/tests/test_embeddings_azure_openai.py",
"repo_id": "llama_index",
"token_count": 116
} | 1,253 |
# coding=utf-8
# Copyright 2022 The Microsoft, The Google 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/lic... | transformers/examples/research_projects/tapex/wikisql_utils.py/0 | {
"file_path": "transformers/examples/research_projects/tapex/wikisql_utils.py",
"repo_id": "transformers",
"token_count": 3100
} | 578 |
"""
We provide two strategies for generating thoughts in the Tree of Thoughts (ToT)
framework to avoid repetition:
These strategies ensure that the language model generates diverse and
non-repeating thoughts, which are crucial for problem-solving tasks that require
exploration.
"""
from abc import abstractmethod
from ... | langchain/libs/experimental/langchain_experimental/tot/thought_generation.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/tot/thought_generation.py",
"repo_id": "langchain",
"token_count": 1177
} | 451 |
terraform {
backend "gcs" {
bucket = "YOUR BUCKET"
prefix = "YOUR PREFIX"
}
}
| chat-langchain/terraform/backend.tf/0 | {
"file_path": "chat-langchain/terraform/backend.tf",
"repo_id": "chat-langchain",
"token_count": 43
} | 9 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/tests/benchmark/test_benchmark_tf.py/0 | {
"file_path": "transformers/tests/benchmark/test_benchmark_tf.py",
"repo_id": "transformers",
"token_count": 4131
} | 714 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-typesense/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-typesense/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,545 |
3.0 (quilt)
| milvus/build/deb/debian/source/format/0 | {
"file_path": "milvus/build/deb/debian/source/format",
"repo_id": "milvus",
"token_count": 8
} | 1,746 |
[
{
"server": "idc-sh003",
"suite_params": [
{
"suite": "2_insert_search_sift50m_2048.yaml",
"image_type": "cpu"
}
]
}
]
| milvus/tests/benchmark/milvus_benchmark/scheduler/nlist.json/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/scheduler/nlist.json",
"repo_id": "milvus",
"token_count": 144
} | 1,997 |
package typeutil
import (
"testing"
"github.com/stretchr/testify/assert"
"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
"github.com/milvus-io/milvus/pkg/common"
)
func TestNewKvPairs(t *testing.T) {
kvPairs := []*commonpb.KeyValuePair{
{Key: common.DimKey, Value: "128"},
}
h := NewKvPairs(kvPairs)
... | milvus/pkg/util/typeutil/kv_pair_helper_test.go/0 | {
"file_path": "milvus/pkg/util/typeutil/kv_pair_helper_test.go",
"repo_id": "milvus",
"token_count": 212
} | 1,917 |
from chromadb.db.base import SqlDB, ParameterValue, get_sql
from chromadb.ingest import (
Producer,
Consumer,
encode_vector,
decode_vector,
ConsumerCallbackFn,
)
from chromadb.types import (
SubmitEmbeddingRecord,
EmbeddingRecord,
SeqId,
ScalarEncoding,
Operation,
)
from chromadb... | chroma/chromadb/db/mixins/embeddings_queue.py/0 | {
"file_path": "chroma/chromadb/db/mixins/embeddings_queue.py",
"repo_id": "chroma",
"token_count": 6695
} | 15 |
<jupyter_start><jupyter_text>Real-time Automated Feedback[](https://colab.research.google.com/github/langchain-ai/langsmith-cookbook/blob/main/feedback-examples/realtime-algorithmic-feedback/realtime_feedback.ipynb)This tutorial shows how to attach a reference-free evaluator as a callback to your chain to automatically... | langsmith-cookbook/feedback-examples/realtime-algorithmic-feedback/realtime_feedback.ipynb/0 | {
"file_path": "langsmith-cookbook/feedback-examples/realtime-algorithmic-feedback/realtime_feedback.ipynb",
"repo_id": "langsmith-cookbook",
"token_count": 1576
} | 1,020 |
<jupyter_start><jupyter_text>Azure AI Data>[Azure AI Studio](https://ai.azure.com/) provides the capability to upload data assets to cloud storage and register existing data assets from the following sources:>>- `Microsoft OneLake`>- `Azure Blob Storage`>- `Azure Data Lake gen 2`The benefit of this approach over `Azure... | langchain/docs/docs/integrations/document_loaders/azure_ai_data.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/azure_ai_data.ipynb",
"repo_id": "langchain",
"token_count": 527
} | 98 |
from llama_index.core.question_gen.llm_generators import LLMQuestionGenerator
from llama_index.core.question_gen.types import SubQuestion
from llama_index.core.schema import QueryBundle
from llama_index.core.service_context import ServiceContext
from llama_index.core.tools.types import ToolMetadata
def test_llm_quest... | llama_index/llama-index-core/tests/question_gen/test_llm_generators.py/0 | {
"file_path": "llama_index/llama-index-core/tests/question_gen/test_llm_generators.py",
"repo_id": "llama_index",
"token_count": 282
} | 1,214 |
# Generated content DO NOT EDIT
from typing import Any, Callable, Dict, List, Optional, Tuple, Union, Sequence
from os import PathLike
from candle.typing import _ArrayLike, Device, Scalar, Index, Shape
class bf16(DType):
pass
@staticmethod
def cat(tensors: List[Tensor], dim: int) -> Tensor:
"""
Concatenat... | candle/candle-pyo3/py_src/candle/__init__.pyi/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/__init__.pyi",
"repo_id": "candle",
"token_count": 5785
} | 60 |
use rand::Rng;
pub(super) fn generate_random_data(n: usize, d: usize) -> Vec<f32> {
let mut rng: rand::prelude::ThreadRng = rand::thread_rng();
let mut data = vec![0.0f32; n * d];
// Generate random data
for i in 0..n {
for j in 0..d {
data[i * d + j] = rng.gen();
}
}
... | chroma/rust/worker/src/index/utils.rs/0 | {
"file_path": "chroma/rust/worker/src/index/utils.rs",
"repo_id": "chroma",
"token_count": 168
} | 61 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/internal/core/src/segcore/load_index_c.cpp/0 | {
"file_path": "milvus/internal/core/src/segcore/load_index_c.cpp",
"repo_id": "milvus",
"token_count": 8502
} | 1,739 |
import { zodToJsonSchema, JsonSchema7ObjectType } from "zod-to-json-schema";
import { StructuredToolInterface } from "@langchain/core/tools";
/**
* Render the tool name and description in plain text.
*
* Output will be in the format of:
* ```
* search: This tool is used for search
* calculator: This tool is used... | langchainjs/langchain/src/tools/render.ts/0 | {
"file_path": "langchainjs/langchain/src/tools/render.ts",
"repo_id": "langchainjs",
"token_count": 418
} | 956 |
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import { ChainValues } from "@langchain/core/utils/types";
import { CallbackManagerForChainRun } from "@langchain/core/callbacks/manager";
import { BaseChain, ChainInputs } from "../base.js";
import { LLMChain } from "../llm_chain.j... | langchainjs/langchain/src/chains/constitutional_ai/constitutional_chain.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/constitutional_ai/constitutional_chain.ts",
"repo_id": "langchainjs",
"token_count": 2064
} | 903 |
from llama_index.core.vector_stores.types import BasePydanticVectorStore
from llama_index.vector_stores.faiss import FaissVectorStore
def test_class():
names_of_base_classes = [b.__name__ for b in FaissVectorStore.__mro__]
assert BasePydanticVectorStore.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-faiss/tests/test_vector_stores_faiss.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-faiss/tests/test_vector_stores_faiss.py",
"repo_id": "llama_index",
"token_count": 100
} | 1,607 |
## Appendix A. Basic Components
#### A.1 System Component
Milvus has 9 different components and can be abstracted into basic Components.
```go
type Component interface {
Init() error
Start() error
Stop() error
GetComponentStates(ctx context.Context) (*milvuspb.ComponentStates, error)
GetStatisticsChannel(ctx co... | milvus/docs/developer_guides/appendix_a_basic_components.md/0 | {
"file_path": "milvus/docs/developer_guides/appendix_a_basic_components.md",
"repo_id": "milvus",
"token_count": 5696
} | 1,770 |
<jupyter_start><jupyter_text>Tree Summarize If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>!pip install llama-index<jupyter_output><empty_output><jupyter_text>Download Data<jupyter_code>!mkdir -p 'data/paul_graham/'
!wget 'https://raw.githubusercontent.com/run-ll... | llama_index/docs/examples/response_synthesizers/tree_summarize.ipynb/0 | {
"file_path": "llama_index/docs/examples/response_synthesizers/tree_summarize.ipynb",
"repo_id": "llama_index",
"token_count": 451
} | 1,161 |
import type { StructuredToolInterface } from "@langchain/core/tools";
import type {
BaseChatModel,
BaseChatModelCallOptions,
} from "@langchain/core/language_models/chat_models";
import { ChatPromptTemplate } from "@langchain/core/prompts";
import {
RunnablePassthrough,
RunnableSequence,
} from "@langchain/core... | langchainjs/langchain/src/agents/openai_tools/index.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/openai_tools/index.ts",
"repo_id": "langchainjs",
"token_count": 1287
} | 943 |
"""Dataset generation from documents."""
from __future__ import annotations
import asyncio
import re
from typing import List, Optional
from llama_index.core import Document, ServiceContext, SummaryIndex
from llama_index.core.async_utils import DEFAULT_NUM_WORKERS, run_jobs
from llama_index.core.base.response.schema i... | llama_index/llama-index-core/llama_index/core/llama_dataset/generator.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/llama_dataset/generator.py",
"repo_id": "llama_index",
"token_count": 4696
} | 1,186 |
// 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/mqwrapper/nmq/nmq_consumer_test.go/0 | {
"file_path": "milvus/pkg/mq/msgstream/mqwrapper/nmq/nmq_consumer_test.go",
"repo_id": "milvus",
"token_count": 5035
} | 1,957 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.obsidian import ObsidianReader
def test_class():
names_of_base_classes = [b.__name__ for b in ObsidianReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-obsidian/tests/test_readers_obsidian.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-obsidian/tests/test_readers_obsidian.py",
"repo_id": "llama_index",
"token_count": 88
} | 1,394 |
import json
import re
from abc import abstractmethod
from typing import Dict, NamedTuple
from langchain.schema import BaseOutputParser
class AutoGPTAction(NamedTuple):
"""Action returned by AutoGPTOutputParser."""
name: str
args: Dict
class BaseAutoGPTOutputParser(BaseOutputParser):
"""Base Output... | langchain/libs/experimental/langchain_experimental/autonomous_agents/autogpt/output_parser.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/autonomous_agents/autogpt/output_parser.py",
"repo_id": "langchain",
"token_count": 825
} | 443 |
export interface Timestamps {
createdAt: Date;
updatedAt: Date;
}
| chat-ui/src/lib/types/Timestamps.ts/0 | {
"file_path": "chat-ui/src/lib/types/Timestamps.ts",
"repo_id": "chat-ui",
"token_count": 23
} | 96 |
# LlamaIndex Vector_Stores Integration: Elasticsearch
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-elasticsearch/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-elasticsearch/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,604 |
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import { ChainValues } from "@langchain/core/utils/types";
import { Tool, DynamicStructuredTool } from "@langchain/core/tools";
import { CallbackManagerForChainRun } from "@langchain/core/callbacks/manager";
import { BaseChain, Chai... | langchainjs/langchain/src/experimental/plan_and_execute/agent_executor.ts/0 | {
"file_path": "langchainjs/langchain/src/experimental/plan_and_execute/agent_executor.ts",
"repo_id": "langchainjs",
"token_count": 2513
} | 925 |
<jupyter_start><jupyter_text>Local Embeddings with HuggingFaceLlamaIndex has support for HuggingFace embedding models, including BGE, Instructor, and more.Furthermore, we provide utilties to create and use ONNX models using the [Optimum library](https://huggingface.co/docs/transformers/serializationexporting-a-transfor... | llama_index/docs/examples/embeddings/huggingface.ipynb/0 | {
"file_path": "llama_index/docs/examples/embeddings/huggingface.ipynb",
"repo_id": "llama_index",
"token_count": 1672
} | 1,053 |
<!--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/ja/model_doc/bartpho.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/bartpho.md",
"repo_id": "transformers",
"token_count": 1761
} | 513 |
# timm
<img class="float-left !m-0 !border-0 !dark:border-0 !shadow-none !max-w-lg w-[150px]" src="https://huggingface.co/front/thumbnails/docs/timm.png"/>
`timm` is a library containing SOTA computer vision models, layers, utilities, optimizers, schedulers, data-loaders, augmentations, and training/evaluation script... | pytorch-image-models/hfdocs/source/index.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/index.mdx",
"repo_id": "pytorch-image-models",
"token_count": 560
} | 334 |
from enum import Enum
from typing import Any, AsyncGenerator, Generator, Optional
from llama_index.legacy.bridge.pydantic import BaseModel, Field
from llama_index.legacy.constants import DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS
class MessageRole(str, Enum):
"""Message role."""
SYSTEM = "system"
USER ... | llama_index/llama-index-legacy/llama_index/legacy/core/llms/types.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/core/llms/types.py",
"repo_id": "llama_index",
"token_count": 1388
} | 1,585 |
"""Mock embedding model."""
from typing import Any, List
from llama_index.core.base.embeddings.base import BaseEmbedding
class MockEmbedding(BaseEmbedding):
"""Mock embedding.
Used for token prediction.
Args:
embed_dim (int): embedding dimension
"""
embed_dim: int
def __init__(s... | llama_index/llama-index-core/llama_index/core/embeddings/mock_embed_model.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/embeddings/mock_embed_model.py",
"repo_id": "llama_index",
"token_count": 439
} | 1,253 |
"""Tool mapping."""
from typing import Any, Dict, Optional, Sequence
from llama_index.legacy.objects.base_node_mapping import (
DEFAULT_PERSIST_DIR,
DEFAULT_PERSIST_FNAME,
BaseObjectNodeMapping,
)
from llama_index.legacy.schema import BaseNode, TextNode
from llama_index.legacy.tools.query_engine import Qu... | llama_index/llama-index-legacy/llama_index/legacy/objects/tool_node_mapping.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/objects/tool_node_mapping.py",
"repo_id": "llama_index",
"token_count": 1928
} | 1,586 |
# Router
Also named `webserver` throughout the docs.
This router is handling most of the logic to handle the "batches" tell
when to pass new `prefill` requests and pausing `decode` requests, which ones etc...
It uses gRPC to communicate with the shards which can therefore be kept
much simpler and focus on having the... | text-generation-inference/router/README.md/0 | {
"file_path": "text-generation-inference/router/README.md",
"repo_id": "text-generation-inference",
"token_count": 1177
} | 403 |
"""Embedding adapter model."""
import logging
from typing import Any, List, Optional, Type, cast
from llama_index.legacy.bridge.pydantic import PrivateAttr
from llama_index.legacy.callbacks import CallbackManager
from llama_index.legacy.constants import DEFAULT_EMBED_BATCH_SIZE
from llama_index.legacy.core.embeddings... | llama_index/llama-index-legacy/llama_index/legacy/embeddings/adapter.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/embeddings/adapter.py",
"repo_id": "llama_index",
"token_count": 1695
} | 1,699 |
from ssl import ALERT_DESCRIPTION_UNKNOWN_PSK_IDENTITY
import threading
import numpy as np
import pandas as pd
import random
import pytest
from pymilvus import Index, DataType
from pymilvus.exceptions import MilvusException
from base.client_base import TestcaseBase
from utils.util_log import test_log as log
from comm... | milvus/tests/python_client/testcases/test_insert.py/0 | {
"file_path": "milvus/tests/python_client/testcases/test_insert.py",
"repo_id": "milvus",
"token_count": 47941
} | 1,975 |
python_tests()
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-anyscale/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-anyscale/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,219 |
export function isUrl(url: string): boolean {
try {
new URL(url);
return true;
} catch (error) {
return false;
}
}
| langchainjs/libs/create-langchain-integration/helpers/is-url.ts/0 | {
"file_path": "langchainjs/libs/create-langchain-integration/helpers/is-url.ts",
"repo_id": "langchainjs",
"token_count": 52
} | 969 |
# coding=utf-8
# Copyright 2023 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... | transformers/tests/models/pix2struct/test_image_processing_pix2struct.py/0 | {
"file_path": "transformers/tests/models/pix2struct/test_image_processing_pix2struct.py",
"repo_id": "transformers",
"token_count": 6116
} | 831 |
<!--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/ko/debugging.md/0 | {
"file_path": "transformers/docs/source/ko/debugging.md",
"repo_id": "transformers",
"token_count": 9860
} | 552 |
<jupyter_start><jupyter_text>DreamBooth Hackathon 🏆 Welcome to the DreamBooth Hackathon! In this competition, you'll **personalise a Stable Diffusion model by fine-tuning it on a handful of your own images.** To do so, we'll use a technique called [_DreamBooth_](https://arxiv.org/abs/2208.12242), which allows one to i... | diffusion-models-class/hackathon/dreambooth.ipynb/0 | {
"file_path": "diffusion-models-class/hackathon/dreambooth.ipynb",
"repo_id": "diffusion-models-class",
"token_count": 9167
} | 303 |
import {
EnhancedGenerateContentResponse,
Content,
Part,
} from "@google/generative-ai";
import {
AIMessage,
AIMessageChunk,
BaseMessage,
ChatMessage,
MessageContent,
isBaseMessage,
} from "@langchain/core/messages";
import {
ChatGeneration,
ChatGenerationChunk,
ChatResult,
} from "@langchain/co... | langchainjs/libs/langchain-google-genai/src/utils.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-genai/src/utils.ts",
"repo_id": "langchainjs",
"token_count": 2077
} | 980 |
<jupyter_start><jupyter_text>Google DriveThis notebook walks through connecting a LangChain to the `Google Drive API`. Prerequisites1. Create a Google Cloud project or use an existing project1. Enable the [Google Drive API](https://console.cloud.google.com/flows/enableapi?apiid=drive.googleapis.com)1. [Authorize creden... | langchain/docs/docs/integrations/tools/google_drive.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/google_drive.ipynb",
"repo_id": "langchain",
"token_count": 1230
} | 183 |
from __future__ import annotations
import enum
import threading
from abc import abstractmethod
from typing import (
Any,
AsyncIterator,
Callable,
Dict,
Iterator,
List,
Optional,
Sequence,
Tuple,
Type,
Union,
cast,
)
from weakref import WeakValueDictionary
from langchain... | langchain/libs/core/langchain_core/runnables/configurable.py/0 | {
"file_path": "langchain/libs/core/langchain_core/runnables/configurable.py",
"repo_id": "langchain",
"token_count": 8410
} | 429 |
# order by contributions
reviewers:
- FluorineDog
- DragonDriver
- fishpenguin
- czs007
- xiaocai2333
- godchen0212
- bigsheeper
approvers:
- maintainers
| milvus/internal/core/OWNERS/0 | {
"file_path": "milvus/internal/core/OWNERS",
"repo_id": "milvus",
"token_count": 66
} | 1,650 |
from langchain_community.document_loaders.chromium import AsyncChromiumLoader
__all__ = ["AsyncChromiumLoader"]
| langchain/libs/langchain/langchain/document_loaders/chromium.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/chromium.py",
"repo_id": "langchain",
"token_count": 34
} | 503 |
"""Base retriever."""
from abc import abstractmethod
from typing import Any, Dict, List, Optional
from llama_index.legacy.bridge.pydantic import Field
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload
from llama_index.legacy.core.ba... | llama_index/llama-index-legacy/llama_index/legacy/core/base_retriever.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/core/base_retriever.py",
"repo_id": "llama_index",
"token_count": 5618
} | 1,584 |
package indexparamcheck
type flatChecker struct {
floatVectorBaseChecker
}
func (c flatChecker) StaticCheck(m map[string]string) error {
return c.staticCheck(m)
}
func newFlatChecker() IndexChecker {
return &flatChecker{}
}
| milvus/pkg/util/indexparamcheck/flat_checker.go/0 | {
"file_path": "milvus/pkg/util/indexparamcheck/flat_checker.go",
"repo_id": "milvus",
"token_count": 79
} | 1,912 |
# coding=utf-8
# Copyright 2022 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/xlm_roberta_xl/configuration_xlm_roberta_xl.py/0 | {
"file_path": "transformers/src/transformers/models/xlm_roberta_xl/configuration_xlm_roberta_xl.py",
"repo_id": "transformers",
"token_count": 2935
} | 680 |
from langchain_community.embeddings.edenai import EdenAiEmbeddings
__all__ = ["EdenAiEmbeddings"]
| langchain/libs/langchain/langchain/embeddings/edenai.py/0 | {
"file_path": "langchain/libs/langchain/langchain/embeddings/edenai.py",
"repo_id": "langchain",
"token_count": 35
} | 506 |
# coding=utf-8
# Copyright (c) 2020, VinAI Research and the HuggingFace Inc. team.
# Copyright 2018 The Open AI Team Authors 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 th... | transformers/src/transformers/models/bertweet/tokenization_bertweet.py/0 | {
"file_path": "transformers/src/transformers/models/bertweet/tokenization_bertweet.py",
"repo_id": "transformers",
"token_count": 12290
} | 609 |
# Débruitage inverse des modèles de diffusion implicites (DDIM)
<CourseFloatingBanner unit={4}
classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Débruitage inverse des modèles de diffusion implicites (DDIM)", value: "https://colab.research.google.com/github/huggingface/diffusion-models-class/blob/mai... | diffusion-models-class/units/fr/unit4/2.mdx/0 | {
"file_path": "diffusion-models-class/units/fr/unit4/2.mdx",
"repo_id": "diffusion-models-class",
"token_count": 9611
} | 287 |
<jupyter_start><jupyter_text>Guidance for Sub-Question Query Engine In this notebook, we showcase how to use [**guidance**](https://github.com/microsoft/guidance) to improve the robustness of our sub-question query engine. The sub-question query engine is designed to accept swappable question generators that implemen... | llama_index/docs/examples/output_parsing/guidance_sub_question.ipynb/0 | {
"file_path": "llama_index/docs/examples/output_parsing/guidance_sub_question.ipynb",
"repo_id": "llama_index",
"token_count": 1576
} | 1,099 |
"""Gmail toolkit."""
| langchain/libs/community/langchain_community/agent_toolkits/gmail/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/agent_toolkits/gmail/__init__.py",
"repo_id": "langchain",
"token_count": 8
} | 222 |
package datacoord
import (
"context"
"testing"
"github.com/cockroachdb/errors"
"github.com/stretchr/testify/mock"
"github.com/stretchr/testify/suite"
"github.com/milvus-io/milvus/internal/mocks"
"github.com/milvus-io/milvus/internal/proto/datapb"
"github.com/milvus-io/milvus/internal/types"
"github.com/milv... | milvus/internal/datacoord/session_manager_test.go/0 | {
"file_path": "milvus/internal/datacoord/session_manager_test.go",
"repo_id": "milvus",
"token_count": 1247
} | 1,770 |
# JSON files
The JSON loader use [JSON pointer](https://github.com/janl/node-jsonpointer) to target keys in your JSON files you want to target.
### No JSON pointer example
The most simple way of using it, is to specify no JSON pointer.
The loader will load all strings it finds in the JSON object.
Example JSON file:... | langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/json.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/json.mdx",
"repo_id": "langchainjs",
"token_count": 801
} | 757 |
# DropCollection release resources
## Before this enhancement
**When dropping a collection**
1. DataNode releases the flowgraph of this collection and drops all the data in a buffer.
2. DataCoord has no idea whether a collection is dropped or not.
- DataCoord will make DataNode watch DmChannels of dropped collec... | milvus/docs/design_docs/20211224-drop_collection_release_resources.md/0 | {
"file_path": "milvus/docs/design_docs/20211224-drop_collection_release_resources.md",
"repo_id": "milvus",
"token_count": 847
} | 1,852 |
from typing import Optional
from urllib.parse import urlparse
import pytest
from hypothesis import given, strategies as st
from chromadb.api.fastapi import FastAPI
def hostname_strategy() -> st.SearchStrategy[str]:
label = st.text(
alphabet=st.characters(min_codepoint=97, max_codepoint=122),
min... | chroma/chromadb/test/property/test_client_url.py/0 | {
"file_path": "chroma/chromadb/test/property/test_client_url.py",
"repo_id": "chroma",
"token_count": 1760
} | 22 |
"""The Chain runs self-critique based on the Constitutional AI method proposed by \
(Bai et al., 2022)."""
| langchain/libs/langchain/langchain/chains/constitutional_ai/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/constitutional_ai/__init__.py",
"repo_id": "langchain",
"token_count": 28
} | 478 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-packs/llama-index-packs-cogniswitch-agent/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-cogniswitch-agent/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,777 |
""" Checkpoint Saver
Track top-n training checkpoints and maintain recovery checkpoints on specified intervals.
Hacked together by / Copyright 2020 Ross Wightman
"""
import glob
import operator
import os
import logging
import torch
from .model import unwrap_model, get_state_dict
_logger = logging.getLogger(__nam... | pytorch-image-models/timm/utils/checkpoint_saver.py/0 | {
"file_path": "pytorch-image-models/timm/utils/checkpoint_saver.py",
"repo_id": "pytorch-image-models",
"token_count": 2818
} | 413 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/using-diffusers/write_own_pipeline.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/write_own_pipeline.md",
"repo_id": "diffusers",
"token_count": 4162
} | 176 |
"""VectorStore wrapper around a Postgres-TimescaleVector database."""
from __future__ import annotations
import enum
import logging
import uuid
from datetime import timedelta
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterable,
List,
Optional,
Tuple,
Type,
Union,
)... | langchain/libs/community/langchain_community/vectorstores/timescalevector.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/timescalevector.py",
"repo_id": "langchain",
"token_count": 13739
} | 315 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/src/diffusers/loaders/lora.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/lora.py",
"repo_id": "diffusers",
"token_count": 28473
} | 221 |
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import AddedToken, EncodeInput, Encoding, InputSequence, Tokenizer
from tokenizers.decoders import Decoder
from tokenizers.models import Model
from tokenizers.normalizers import Normalizer
from tokenizers.pre_tokenizers import PreTokenizer
from toke... | tokenizers/bindings/python/py_src/tokenizers/implementations/base_tokenizer.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/base_tokenizer.py",
"repo_id": "tokenizers",
"token_count": 6036
} | 435 |
from langchain_community.retrievers.svm import SVMRetriever
__all__ = ["SVMRetriever"]
| langchain/libs/langchain/langchain/retrievers/svm.py/0 | {
"file_path": "langchain/libs/langchain/langchain/retrievers/svm.py",
"repo_id": "langchain",
"token_count": 32
} | 543 |
#!/usr/bin/env groovy
def app="meta-migration"
def date=""
def gitShortCommit=""
pipeline {
agent {
kubernetes {
defaultContainer 'main'
yamlFile "ci/jenkins/pod/meta-migration.yaml"
customWorkspace '/home/jenkins/agent/workspace'
}
}
options {
ti... | milvus/ci/jenkins/PublishMigrationImage.groovy/0 | {
"file_path": "milvus/ci/jenkins/PublishMigrationImage.groovy",
"repo_id": "milvus",
"token_count": 1597
} | 1,707 |
## 🌲 Tree Index
Currently the tree index refers to the `TreeIndex` class. It organizes external data into a tree structure that can be queried.
### Index Construction
The `TreeIndex` first takes in a set of text documents as input. It then builds up a tree-index in a bottom-up fashion; each parent node is able to s... | llama_index/llama-index-core/llama_index/core/indices/tree/README.md/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/tree/README.md",
"repo_id": "llama_index",
"token_count": 693
} | 1,222 |
import re
# regular expressions to match the different syntax of YouTube links
YOUTUBE_URL_PATTERNS = [
r"^https?://(?:www\.)?youtube\.com/watch\?v=([\w-]+)",
r"^https?://(?:www\.)?youtube\.com/embed/([\w-]+)",
r"^https?://youtu\.be/([\w-]+)", # youtu.be does not use www
]
def is_youtube_video(url: str)... | llama_index/llama-index-integrations/readers/llama-index-readers-youtube-transcript/llama_index/readers/youtube_transcript/utils.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-youtube-transcript/llama_index/readers/youtube_transcript/utils.py",
"repo_id": "llama_index",
"token_count": 225
} | 1,452 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/internal/core/unittest/test_string_index.cpp/0 | {
"file_path": "milvus/internal/core/unittest/test_string_index.cpp",
"repo_id": "milvus",
"token_count": 7063
} | 1,906 |
"""Multidoc Autoretriever."""
from typing import Any, Dict, List, Optional, cast
from llama_index.core import VectorStoreIndex
from llama_index.core.indices.query.schema import QueryBundle
from llama_index.core.llama_pack.base import BaseLlamaPack
from llama_index.core.query_engine import RetrieverQueryEngine
from ll... | llama_index/llama-index-packs/llama-index-packs-multidoc-autoretrieval/llama_index/packs/multidoc_autoretrieval/base.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-multidoc-autoretrieval/llama_index/packs/multidoc_autoretrieval/base.py",
"repo_id": "llama_index",
"token_count": 2682
} | 1,681 |
python_sources()
| llama_index/llama-index-legacy/llama_index/legacy/utilities/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/utilities/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,651 |
# Evaluating
Evaluation and benchmarking are crucial concepts in LLM development. To improve the performance of an LLM app (RAG, agents), you must have a way to measure it.
LlamaIndex offers key modules to measure the quality of generated results. We also offer key modules to measure retrieval quality. You can learn ... | llama_index/docs/understanding/evaluating/evaluating.md/0 | {
"file_path": "llama_index/docs/understanding/evaluating/evaluating.md",
"repo_id": "llama_index",
"token_count": 777
} | 1,109 |
// 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/config/event.go/0 | {
"file_path": "milvus/pkg/config/event.go",
"repo_id": "milvus",
"token_count": 590
} | 1,890 |
<jupyter_start><jupyter_text>Connery ToolkitUsing this toolkit, you can integrate Connery Actions into your LangChain agent.If you want to use only one particular Connery Action in your agent,check out the [Connery Action Tool](/docs/integrations/tools/connery) documentation. What is Connery?Connery is an open-source p... | langchain/docs/docs/integrations/toolkits/connery.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/toolkits/connery.ipynb",
"repo_id": "langchain",
"token_count": 1144
} | 174 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/tools/llama-index-tools-openai/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-openai/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,448 |
# coding=utf-8
# Copyright 2023 The Kakao Enterprise Authors 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/... | transformers/src/transformers/models/vits/modeling_vits.py/0 | {
"file_path": "transformers/src/transformers/models/vits/modeling_vits.py",
"repo_id": "transformers",
"token_count": 28934
} | 765 |
<!--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... | peft/docs/source/developer_guides/custom_models.md/0 | {
"file_path": "peft/docs/source/developer_guides/custom_models.md",
"repo_id": "peft",
"token_count": 3721
} | 334 |
from typing import Any, Dict, List, Optional
from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import (
BaseModel,
Extra,
Field,
SecretStr,
root_validator,
)
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
from langchain_community.utiliti... | langchain/libs/community/langchain_community/embeddings/edenai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/embeddings/edenai.py",
"repo_id": "langchain",
"token_count": 1551
} | 251 |
<jupyter_start><jupyter_text>GPT4All[GitHub:nomic-ai/gpt4all](https://github.com/nomic-ai/gpt4all) an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue.This example goes over how to use LangChain to interact with `GPT4All` models.<jupyter_cod... | langchain/docs/docs/integrations/llms/gpt4all.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/gpt4all.ipynb",
"repo_id": "langchain",
"token_count": 654
} | 128 |
from llama_index.embeddings.gradient.base import GradientEmbedding
__all__ = ["GradientEmbedding"]
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-gradient/llama_index/embeddings/gradient/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-gradient/llama_index/embeddings/gradient/__init__.py",
"repo_id": "llama_index",
"token_count": 33
} | 1,260 |
python_tests(
name="tests",
)
python_sources()
| llama_index/llama-index-core/tests/vector_stores/BUILD/0 | {
"file_path": "llama_index/llama-index-core/tests/vector_stores/BUILD",
"repo_id": "llama_index",
"token_count": 22
} | 1,248 |
from llama_index.core.tools.tool_spec.base import BaseToolSpec
from llama_index.tools.multion import MultionToolSpec
def test_class():
names_of_base_classes = [b.__name__ for b in MultionToolSpec.__mro__]
assert BaseToolSpec.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/tools/llama-index-tools-multion/tests/test_tools_multion.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-multion/tests/test_tools_multion.py",
"repo_id": "llama_index",
"token_count": 94
} | 1,430 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team, Microsoft Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | transformers/tests/models/mpnet/test_modeling_mpnet.py/0 | {
"file_path": "transformers/tests/models/mpnet/test_modeling_mpnet.py",
"repo_id": "transformers",
"token_count": 4626
} | 799 |
from typing import List
import pytest
from langchain_core.tools import BaseTool, tool
from langchain.tools.render import (
render_text_description,
render_text_description_and_args,
)
@tool
def search(query: str) -> str:
"""Lookup things online."""
return "foo"
@tool
def calculator(expression: str... | langchain/libs/langchain/tests/unit_tests/tools/test_render.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/tools/test_render.py",
"repo_id": "langchain",
"token_count": 396
} | 656 |
from langchain_community.retrievers.kendra import (
AdditionalResultAttribute,
AdditionalResultAttributeValue,
AmazonKendraRetriever,
DocumentAttribute,
DocumentAttributeValue,
DocumentAttributeValueType,
Highlight,
QueryResult,
QueryResultItem,
ResultItem,
RetrieveResult,
... | langchain/libs/langchain/langchain/retrievers/kendra.py/0 | {
"file_path": "langchain/libs/langchain/langchain/retrievers/kendra.py",
"repo_id": "langchain",
"token_count": 292
} | 557 |
//! 2D UNet Building Blocks
//!
use super::attention::{
AttentionBlock, AttentionBlockConfig, SpatialTransformer, SpatialTransformerConfig,
};
use super::resnet::{ResnetBlock2D, ResnetBlock2DConfig};
use crate::models::with_tracing::{conv2d, Conv2d};
use candle::{Module, Result, Tensor, D};
use candle_nn as nn;
#[... | candle/candle-transformers/src/models/stable_diffusion/unet_2d_blocks.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/unet_2d_blocks.rs",
"repo_id": "candle",
"token_count": 13815
} | 77 |
""" Conv2d w/ Same Padding
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Tuple, Optional
from .config import is_exportable, is_scriptable
from .padding import pad_same, pad_same_arg, get_padding_value
_USE_EXPORT_CONV = Fa... | pytorch-image-models/timm/layers/conv2d_same.py/0 | {
"file_path": "pytorch-image-models/timm/layers/conv2d_same.py",
"repo_id": "pytorch-image-models",
"token_count": 1560
} | 331 |
python_sources()
| llama_index/llama-index-core/llama_index/core/llama_dataset/legacy/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/llama_dataset/legacy/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,136 |
python_tests()
| llama_index/llama-index-integrations/llms/llama-index-llms-mistralai/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-mistralai/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,232 |
import importlib.util
import pytest
from llama_index.core.node_parser.file.html import HTMLNodeParser
from llama_index.core.schema import Document
@pytest.mark.xfail(
raises=ImportError,
reason="Requires beautifulsoup4.",
condition=importlib.util.find_spec("beautifulsoup4") is None,
)
def test_no_splits(... | llama_index/llama-index-core/tests/node_parser/test_html.py/0 | {
"file_path": "llama_index/llama-index-core/tests/node_parser/test_html.py",
"repo_id": "llama_index",
"token_count": 1748
} | 1,320 |
import * as fs from "fs";
import { OpenAI, OpenAIEmbeddings } from "@langchain/openai";
import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
import { HNSWLib } from "@langchain/community/vectorstores/hnswlib";
import { ContextualCompressionRetriever } from "langchain/retrievers/contextual_compress... | langchainjs/examples/src/retrievers/contextual_compression.ts/0 | {
"file_path": "langchainjs/examples/src/retrievers/contextual_compression.ts",
"repo_id": "langchainjs",
"token_count": 588
} | 882 |
import * as uuid from "uuid";
import {
SearchClient,
SearchIndexClient,
AzureKeyCredential,
IndexingResult,
SearchIndex,
SearchIndexingBufferedSender,
VectorFilterMode,
} from "@azure/search-documents";
import {
MaxMarginalRelevanceSearchOptions,
VectorStore,
} from "@langchain/core/vectorstores";
imp... | langchainjs/libs/langchain-community/src/vectorstores/azure_aisearch.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/azure_aisearch.ts",
"repo_id": "langchainjs",
"token_count": 8869
} | 1,001 |
"""Test ChatGoogleVertexAI chat model."""
import json
from typing import Optional, cast
import pytest
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
HumanMessage,
SystemMessage,
)
from langchain_core.outputs import ChatGeneration, LLMResult
from langchain_core.pydantic_v1 import Base... | langchain/libs/partners/google-vertexai/tests/integration_tests/test_chat_models.py/0 | {
"file_path": "langchain/libs/partners/google-vertexai/tests/integration_tests/test_chat_models.py",
"repo_id": "langchain",
"token_count": 3496
} | 628 |
# RegNetX
**RegNetX** is a convolutional network design space with simple, regular models with parameters: depth $d$, initial width $w\_{0} > 0$, and slope $w\_{a} > 0$, and generates a different block width $u\_{j}$ for each block $j < d$. The key restriction for the RegNet types of model is that there is a linear pa... | pytorch-image-models/docs/models/regnetx.md/0 | {
"file_path": "pytorch-image-models/docs/models/regnetx.md",
"repo_id": "pytorch-image-models",
"token_count": 6551
} | 352 |
<jupyter_start><jupyter_text>Google Cloud Document AI Document AI is a document understanding platform from Google Cloud to transform unstructured data from documents into structured data, making it easier to understand, analyze, and consume.Learn more:- [Document AI overview](https://cloud.google.com/document-ai/docs/... | langchain/docs/docs/integrations/document_transformers/docai.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_transformers/docai.ipynb",
"repo_id": "langchain",
"token_count": 1195
} | 125 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/datacoord/metrics_info_test.go/0 | {
"file_path": "milvus/internal/datacoord/metrics_info_test.go",
"repo_id": "milvus",
"token_count": 2491
} | 1,794 |
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