text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
"""Prompt for the router chain in the multi-prompt chain."""
MULTI_PROMPT_ROUTER_TEMPLATE = """\
Given a raw text input to a language model select the model prompt best suited for \
the input. You will be given the names of the available prompts and a description of \
what the prompt is best suited for. You may also r... | langchain/libs/langchain/langchain/chains/router/multi_prompt_prompt.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/router/multi_prompt_prompt.py",
"repo_id": "langchain",
"token_count": 323
} | 490 |
# 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 applicabl... | transformers/tests/models/clip/test_processor_clip.py/0 | {
"file_path": "transformers/tests/models/clip/test_processor_clip.py",
"repo_id": "transformers",
"token_count": 3365
} | 774 |
# 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/src/transformers/models/mt5/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/mt5/__init__.py",
"repo_id": "transformers",
"token_count": 1418
} | 638 |
"""Test chat model integration."""
from langchain_nvidia_ai_endpoints.chat_models import ChatNVIDIA
def test_integration_initialization() -> None:
"""Test chat model initialization."""
ChatNVIDIA(
model="llama2_13b",
nvidia_api_key="nvapi-...",
temperature=0.5,
top_p=0.9,
... | langchain/libs/partners/nvidia-ai-endpoints/tests/unit_tests/test_chat_models.py/0 | {
"file_path": "langchain/libs/partners/nvidia-ai-endpoints/tests/unit_tests/test_chat_models.py",
"repo_id": "langchain",
"token_count": 172
} | 631 |
#[macro_use]
mod types;
mod collection;
mod embedding_record;
mod metadata;
mod operation;
mod scalar_encoding;
mod segment;
mod segment_scope;
// Re-export the types module, so that we can use it as a single import in other modules.
pub use collection::*;
pub use embedding_record::*;
pub use metadata::*;
pub use oper... | chroma/rust/worker/src/types/mod.rs/0 | {
"file_path": "chroma/rust/worker/src/types/mod.rs",
"repo_id": "chroma",
"token_count": 138
} | 65 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "vectorstores/vectara",
});
export * from "@langchain/community/vectorstores/vectara";
| langchainjs/langchain/src/vectorstores/vectara.ts/0 | {
"file_path": "langchainjs/langchain/src/vectorstores/vectara.ts",
"repo_id": "langchainjs",
"token_count": 74
} | 953 |
import { HNSWLib } from "@langchain/community/vectorstores/hnswlib";
import { OpenAIEmbeddings } from "@langchain/openai";
const vectorStore = await HNSWLib.fromTexts(
["Hello world", "Bye bye", "hello nice world"],
[{ id: 2 }, { id: 1 }, { id: 3 }],
new OpenAIEmbeddings()
);
const result = await vectorStore.si... | langchainjs/examples/src/indexes/vector_stores/hnswlib_filter.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/hnswlib_filter.ts",
"repo_id": "langchainjs",
"token_count": 160
} | 785 |
"""Loading datasets and evaluators."""
from typing import Any, Dict, List, Optional, Sequence, Type, Union
from langchain_community.chat_models.openai import ChatOpenAI
from langchain_core.language_models import BaseLanguageModel
from langchain.chains.base import Chain
from langchain.evaluation.agents.trajectory_eval... | langchain/libs/langchain/langchain/evaluation/loading.py/0 | {
"file_path": "langchain/libs/langchain/langchain/evaluation/loading.py",
"repo_id": "langchain",
"token_count": 2609
} | 551 |
import candle
from typing import Dict, Tuple, Any
from candle import Tensor, QTensor, utils, nn
from candle.nn import Module, ModuleList
def masked_fill(on_false: Tensor, mask: Tensor, on_true: Tensor):
shape = mask.shape
on_true = candle.tensor(on_true).broadcast_as(shape)
return mask.where_cond(on_true,... | candle/candle-pyo3/py_src/candle/models/llama.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/models/llama.py",
"repo_id": "candle",
"token_count": 2981
} | 66 |
python_sources()
| llama_index/llama-index-core/llama_index/core/langchain_helpers/agents/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/langchain_helpers/agents/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,272 |
import base64
from email.message import EmailMessage
from typing import List, Optional, Type
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_community.tools.gmail.base import GmailBaseTool
class CreateDraftSchema(BaseModel):
"... | langchain/libs/community/langchain_community/tools/gmail/create_draft.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/gmail/create_draft.py",
"repo_id": "langchain",
"token_count": 1104
} | 308 |
import {
PaddingDirection,
WordPiece,
punctuationPreTokenizer,
sequencePreTokenizer,
whitespacePreTokenizer,
Encoding,
EncodeOptions,
Tokenizer,
} from '../../'
import { InputSequence } from '../../types'
const MOCKS_DIR = __dirname + '/__mocks__'
describe('Can modify pretokenizers on the fly', () => ... | tokenizers/bindings/node/lib/bindings/encoding.test.ts/0 | {
"file_path": "tokenizers/bindings/node/lib/bindings/encoding.test.ts",
"repo_id": "tokenizers",
"token_count": 3021
} | 432 |
"""Test indices/utils.py."""
from llama_index.legacy.indices.utils import expand_tokens_with_subtokens
def test_expand_tokens_with_subtokens() -> None:
"""Test expand tokens."""
tokens = {"foo bar", "baz", "hello hello world bye"}
keywords = expand_tokens_with_subtokens(tokens)
assert keywords == {
... | llama_index/llama-index-legacy/tests/indices/test_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/test_utils.py",
"repo_id": "llama_index",
"token_count": 219
} | 1,664 |
# (Optional) the Policy Gradient Theorem
In this optional section where we're **going to study how we differentiate the objective function that we will use to approximate the policy gradient**.
Let's first recap our different formulas:
1. The Objective function
<img src="https://huggingface.co/datasets/huggingface-... | deep-rl-class/units/en/unit4/pg-theorem.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit4/pg-theorem.mdx",
"repo_id": "deep-rl-class",
"token_count": 1814
} | 160 |
from __future__ import annotations
import logging
import uuid
from typing import (
Any,
Iterable,
List,
Optional,
Tuple,
)
import numpy as np
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from langchain_core.utils import get_from_env
from langchain_... | langchain/libs/community/langchain_community/vectorstores/dashvector.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/dashvector.py",
"repo_id": "langchain",
"token_count": 5693
} | 335 |
"""Test prompt functionality."""
| langchain/libs/langchain/tests/unit_tests/prompts/__init__.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/prompts/__init__.py",
"repo_id": "langchain",
"token_count": 7
} | 664 |
from typing import TYPE_CHECKING
from langchain_community.document_loaders.parsers.language.tree_sitter_segmenter import ( # noqa: E501
TreeSitterSegmenter,
)
if TYPE_CHECKING:
from tree_sitter import Language
CHUNK_QUERY = """
[
(function_definition) @subroutine
]
""".strip()
class PerlS... | langchain/libs/community/langchain_community/document_loaders/parsers/language/perl.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/language/perl.py",
"repo_id": "langchain",
"token_count": 263
} | 244 |
# langchain-pinecone
This package contains the LangChain integration with Pinecone.
## Installation
```bash
pip install -U langchain-pinecone
```
And you should configure credentials by setting the following environment variables:
- `PINECONE_API_KEY`
- `PINECONE_INDEX_NAME`
- `PINECONE_ENVIRONMENT`
## Usage
The... | langchain/libs/partners/pinecone/README.md/0 | {
"file_path": "langchain/libs/partners/pinecone/README.md",
"repo_id": "langchain",
"token_count": 167
} | 679 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-wordlift/llama_index/readers/wordlift/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-wordlift/llama_index/readers/wordlift/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,437 |
# ControlNet training example for Stable Diffusion XL (SDXL)
The `train_controlnet_sdxl.py` script shows how to implement the ControlNet training procedure and adapt it for [Stable Diffusion XL](https://huggingface.co/papers/2307.01952).
## Running locally with PyTorch
### Installing the dependencies
Before running... | diffusers/examples/controlnet/README_sdxl.md/0 | {
"file_path": "diffusers/examples/controlnet/README_sdxl.md",
"repo_id": "diffusers",
"token_count": 1519
} | 205 |
#!/bin/bash
# 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... | milvus/tests/scripts/ci_e2e.sh/0 | {
"file_path": "milvus/tests/scripts/ci_e2e.sh",
"repo_id": "milvus",
"token_count": 1336
} | 2,011 |
[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 = ["DatabaseReader"]
contains_example = false
import_path = "llama_index.readers.database"
[... | llama_index/llama-index-integrations/readers/llama-index-readers-database/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-database/pyproject.toml",
"repo_id": "llama_index",
"token_count": 660
} | 1,356 |
# coding=utf-8
# Copyright 2023 The Meta AI Authors 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/LICEN... | transformers/src/transformers/models/sam/modeling_sam.py/0 | {
"file_path": "transformers/src/transformers/models/sam/modeling_sam.py",
"repo_id": "transformers",
"token_count": 27304
} | 726 |
#!/usr/bin/env python
# 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/L... | transformers/src/transformers/tools/image_question_answering.py/0 | {
"file_path": "transformers/src/transformers/tools/image_question_answering.py",
"repo_id": "transformers",
"token_count": 646
} | 767 |
# 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/src/transformers/models/rembert/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/rembert/__init__.py",
"repo_id": "transformers",
"token_count": 1913
} | 723 |
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.embeddings.sagemaker_endpoint import SageMakerEmbedding
def test_text_inference_embedding_class():
names_of_base_classes = [b.__name__ for b in SageMakerEmbedding.__mro__]
assert BaseEmbedding.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-sagemaker-endpoint/tests/test_embeddings_sagemaker_endpoint.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-sagemaker-endpoint/tests/test_embeddings_sagemaker_endpoint.py",
"repo_id": "llama_index",
"token_count": 112
} | 1,256 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/pkg/util/metricsinfo/utils_test.go/0 | {
"file_path": "milvus/pkg/util/metricsinfo/utils_test.go",
"repo_id": "milvus",
"token_count": 440
} | 1,847 |
from llama_index.legacy.core.base_retriever import BaseRetriever
from llama_index.legacy.core.image_retriever import BaseImageRetriever
from llama_index.legacy.indices.empty.retrievers import EmptyIndexRetriever
from llama_index.legacy.indices.keyword_table.retrievers import (
KeywordTableSimpleRetriever,
)
from ll... | llama_index/llama-index-legacy/llama_index/legacy/retrievers/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/retrievers/__init__.py",
"repo_id": "llama_index",
"token_count": 1101
} | 1,614 |
import bz2
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from ._filelock import FileLock
from .logging import get_logger
... | datasets/src/datasets/utils/extract.py/0 | {
"file_path": "datasets/src/datasets/utils/extract.py",
"repo_id": "datasets",
"token_count": 6410
} | 140 |
python_tests()
| llama_index/llama-index-packs/llama-index-packs-rag-fusion-query-pipeline/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-rag-fusion-query-pipeline/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,810 |
#include "common.h"
template<typename T>
__device__ int set_insert(T *set, int set_size, T value) {
int slot = value % set_size;
int start_slot = slot;
while (true) {
T prev = atomicCAS(&set[slot], EMPTY_VALUE, value);
if (prev == EMPTY_VALUE || prev == value) {
return slot;
}
slot = (slot... | transformers/src/transformers/kernels/yoso/common_cuda_device.h/0 | {
"file_path": "transformers/src/transformers/kernels/yoso/common_cuda_device.h",
"repo_id": "transformers",
"token_count": 892
} | 613 |
"""Light weight unit test that attempts to import UpstashRedisStore.
"""
import pytest
@pytest.mark.requires("upstash_redis")
def test_import_storage() -> None:
from langchain_community.storage.upstash_redis import UpstashRedisStore # noqa
| langchain/libs/community/tests/unit_tests/storage/test_upstash_redis.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/storage/test_upstash_redis.py",
"repo_id": "langchain",
"token_count": 80
} | 405 |
use crate::{Result, Tensor};
#[macro_export]
macro_rules! test_device {
// TODO: Switch to generating the two last arguments automatically once concat_idents is
// stable. https://github.com/rust-lang/rust/issues/29599
($fn_name: ident, $test_cpu: ident, $test_cuda: ident, $test_metal: ident) => {
... | candle/candle-core/src/test_utils.rs/0 | {
"file_path": "candle/candle-core/src/test_utils.rs",
"repo_id": "candle",
"token_count": 923
} | 42 |
import pytest
from llama_index.core.storage.kvstore.simple_kvstore import SimpleKVStore
@pytest.fixture()
def simple_kvstore() -> SimpleKVStore:
return SimpleKVStore()
| llama_index/llama-index-core/tests/storage/conftest.py/0 | {
"file_path": "llama_index/llama-index-core/tests/storage/conftest.py",
"repo_id": "llama_index",
"token_count": 62
} | 1,277 |
# 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 applicabl... | accelerate/setup.py/0 | {
"file_path": "accelerate/setup.py",
"repo_id": "accelerate",
"token_count": 1631
} | 9 |
from llama_index.extractors.entity.base import EntityExtractor
__all__ = ["EntityExtractor"]
| llama_index/llama-index-integrations/extractors/llama-index-extractors-entity/llama_index/extractors/entity/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/extractors/llama-index-extractors-entity/llama_index/extractors/entity/__init__.py",
"repo_id": "llama_index",
"token_count": 29
} | 1,328 |
# 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/competition_math/competition_math.py/0 | {
"file_path": "datasets/metrics/competition_math/competition_math.py",
"repo_id": "datasets",
"token_count": 1181
} | 138 |
# rag-codellama-fireworks
This template performs RAG on a codebase.
It uses codellama-34b hosted by Fireworks' [LLM inference API](https://blog.fireworks.ai/accelerating-code-completion-with-fireworks-fast-llm-inference-f4e8b5ec534a).
## Environment Setup
Set the `FIREWORKS_API_KEY` environment variable to acces... | langchain/templates/rag-codellama-fireworks/README.md/0 | {
"file_path": "langchain/templates/rag-codellama-fireworks/README.md",
"repo_id": "langchain",
"token_count": 707
} | 727 |
# flake8: noqa
from langchain.prompts.prompt import PromptTemplate
template = (
"""
# Generate Python3 Code to solve problems
# Q: On the nightstand, there is a red pencil, a purple mug, a burgundy keychain, a fuchsia teddy bear, a black plate, and a blue stress ball. What color is the stress ball?
# Put objects i... | langchain/libs/experimental/langchain_experimental/pal_chain/colored_object_prompt.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/pal_chain/colored_object_prompt.py",
"repo_id": "langchain",
"token_count": 863
} | 464 |
python_sources()
| llama_index/llama-index-packs/llama-index-packs-gmail-openai-agent/llama_index/packs/gmail_openai_agent/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-gmail-openai-agent/llama_index/packs/gmail_openai_agent/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,569 |
<jupyter_start><jupyter_text>SQL Router Query EngineIn this tutorial, we define a custom router query engine that can route to either a SQL database or a vector database. Setup If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-readers-wikip... | llama_index/docs/examples/query_engine/SQLRouterQueryEngine.ipynb/0 | {
"file_path": "llama_index/docs/examples/query_engine/SQLRouterQueryEngine.ipynb",
"repo_id": "llama_index",
"token_count": 2398
} | 1,123 |
# 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/models/unets/test_models_unet_motion.py/0 | {
"file_path": "diffusers/tests/models/unets/test_models_unet_motion.py",
"repo_id": "diffusers",
"token_count": 4946
} | 258 |
import importlib
import os
import tempfile
import types
from contextlib import nullcontext as does_not_raise
from multiprocessing import Process
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from... | datasets/tests/test_builder.py/0 | {
"file_path": "datasets/tests/test_builder.py",
"repo_id": "datasets",
"token_count": 26439
} | 159 |
"""Unit tests for document transformers."""
from langchain_community.document_transformers.embeddings_redundant_filter import (
_filter_similar_embeddings,
)
from langchain.utils.math import cosine_similarity
def test__filter_similar_embeddings() -> None:
threshold = 0.79
embedded_docs = [[1.0, 2.0], [1.... | langchain/libs/langchain/tests/unit_tests/test_document_transformers.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/test_document_transformers.py",
"repo_id": "langchain",
"token_count": 236
} | 611 |
import pytest
@pytest.fixture(scope="module")
def flash_starcoder_gptq_handle(launcher):
with launcher("Narsil/starcoder-gptq", num_shard=2, quantize="gptq") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_starcoder_gptq(flash_starcoder_gptq_handle):
await flash_starcoder_gpt... | text-generation-inference/integration-tests/models/test_flash_starcoder_gptq.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_starcoder_gptq.py",
"repo_id": "text-generation-inference",
"token_count": 734
} | 407 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-pdb/llama_index/readers/pdb/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-pdb/llama_index/readers/pdb/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,538 |
import { AgentExecutor } from "langchain/agents";
import { XMLAgentOutputParser } from "langchain/agents/xml/output_parser";
import { renderTextDescription } from "langchain/tools/render";
import { formatLogToMessage } from "langchain/agents/format_scratchpad/log_to_message";
import { Tool } from "@langchain/core/tools... | langchainjs/examples/src/agents/xml_runnable.ts/0 | {
"file_path": "langchainjs/examples/src/agents/xml_runnable.ts",
"repo_id": "langchainjs",
"token_count": 1075
} | 841 |
//! Popular tokenizer models.
pub mod bpe;
pub mod unigram;
pub mod wordlevel;
pub mod wordpiece;
use std::collections::HashMap;
use std::path::{Path, PathBuf};
use serde::{Deserialize, Serialize, Serializer};
use crate::models::bpe::{BpeTrainer, BPE};
use crate::models::unigram::{Unigram, UnigramTrainer};
use crat... | tokenizers/tokenizers/src/models/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/mod.rs",
"repo_id": "tokenizers",
"token_count": 3660
} | 430 |
pub mod bpe;
pub mod byte_fallback;
pub mod ctc;
pub mod fuse;
pub mod sequence;
pub mod strip;
pub mod wordpiece;
// Re-export these as decoders
pub use super::pre_tokenizers::byte_level;
pub use super::pre_tokenizers::metaspace;
use serde::{Deserialize, Serialize};
use crate::decoders::bpe::BPEDecoder;
use crate::... | tokenizers/tokenizers/src/decoders/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/decoders/mod.rs",
"repo_id": "tokenizers",
"token_count": 1434
} | 434 |
<jupyter_start><jupyter_text>Préparer des données (PyTorch) Installez les bibliothèques 🤗 *Transformers* et 🤗 *Datasets* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
import torch
from transformers import AdamW, AutoTokenizer, AutoModelForSequenceClassification
# Comme ... | notebooks/course/fr/chapter3/section2_pt.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter3/section2_pt.ipynb",
"repo_id": "notebooks",
"token_count": 784
} | 289 |
import logging
from typing import Any, Dict, List, Optional
import requests
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from langchain_core.pydantic_v1 import Field, root_validator
from langchain_core.utils import get_from_dict_or_env
logger = logg... | langchain/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py",
"repo_id": "langchain",
"token_count": 5173
} | 270 |
import logging
from typing import Any, Callable, Dict, List, Optional, Sequence, Type
from openai.resources import Completions
from tenacity import (
before_sleep_log,
retry,
retry_if_exception_type,
stop_after_attempt,
wait_exponential,
)
from llama_index.legacy.bridge.pydantic import BaseModel
f... | llama_index/llama-index-legacy/llama_index/legacy/llms/litellm_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/llms/litellm_utils.py",
"repo_id": "llama_index",
"token_count": 2496
} | 1,734 |
from abc import ABC, abstractmethod
from enum import Enum
from typing import (
Any,
AsyncGenerator,
Dict,
Generator,
Generic,
List,
Protocol,
Type,
TypeVar,
Union,
runtime_checkable,
)
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from llama_index.cor... | llama_index/llama-index-core/llama_index/core/types.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/types.py",
"repo_id": "llama_index",
"token_count": 905
} | 1,304 |
import { logVersion010MigrationWarning } from "../../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "stores/message/xata",
});
export * from "@langchain/community/stores/message/xata";
| langchainjs/langchain/src/stores/message/xata.ts/0 | {
"file_path": "langchainjs/langchain/src/stores/message/xata.ts",
"repo_id": "langchainjs",
"token_count": 75
} | 992 |
python_sources()
| llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-mongodb/llama_index/storage/kvstore/mongodb/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-mongodb/llama_index/storage/kvstore/mongodb/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,467 |
use candle::{DType, Device, IndexOp, Result, Tensor};
use candle_nn::{batch_norm, conv2d, conv2d_no_bias, Func, Module, VarBuilder};
use std::collections::BTreeMap;
use std::fs::File;
use std::io::{BufRead, BufReader};
use std::path::Path;
#[derive(Debug)]
struct Block {
block_type: String,
parameters: BTreeMa... | candle/candle-examples/examples/yolo-v3/darknet.rs/0 | {
"file_path": "candle/candle-examples/examples/yolo-v3/darknet.rs",
"repo_id": "candle",
"token_count": 5403
} | 46 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/it/pipeline_tutorial.md/0 | {
"file_path": "transformers/docs/source/it/pipeline_tutorial.md",
"repo_id": "transformers",
"token_count": 2390
} | 521 |
import datetime
import uuid
from enum import Enum
from typing import Any
import pytest
from langchain.schema.messages import (
HumanMessage,
HumanMessageChunk,
SystemMessage,
)
from langchain.schema.output import ChatGeneration
try:
from pydantic.v1 import BaseModel
except ImportError:
from pydant... | langserve/tests/unit_tests/test_serialization.py/0 | {
"file_path": "langserve/tests/unit_tests/test_serialization.py",
"repo_id": "langserve",
"token_count": 2691
} | 1,016 |
# Notion Tool
This tool loads and updates documents from Notion. The user specifies an API token to initialize the NotionToolSpec.
## Usage
This tool has more extensive example usage documented in a Jupyter notebook [here](https://github.com/emptycrown/llama-hub/tree/main/llama_hub/tools/notebooks/notion.ipynb)
Her... | llama_index/llama-index-integrations/tools/llama-index-tools-notion/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-notion/README.md",
"repo_id": "llama_index",
"token_count": 294
} | 1,487 |
---
hide_table_of_contents: true
sidebar_position: 6
---
# Summarization
A common use case is wanting to summarize long documents.
This naturally runs into the context window limitations.
Unlike in question-answering, you can't just do some semantic search hacks to only select the chunks of text most relevant to the ... | langchainjs/docs/core_docs/docs/use_cases/summarization.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/use_cases/summarization.mdx",
"repo_id": "langchainjs",
"token_count": 313
} | 770 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
# ------------
# Data loading
# ------------
class CNNDMDataset(Dataset):
"""Abstracts the dataset used to train seq2seq models.
The class will process the documents that are located in the specified
folder. The ... | transformers/examples/research_projects/bertabs/utils_summarization.py/0 | {
"file_path": "transformers/examples/research_projects/bertabs/utils_summarization.py",
"repo_id": "transformers",
"token_count": 2180
} | 556 |
package registry
import (
"context"
"sync"
"go.uber.org/atomic"
qnClient "github.com/milvus-io/milvus/internal/distributed/querynode/client"
"github.com/milvus-io/milvus/internal/types"
"github.com/milvus-io/milvus/internal/util/wrappers"
"github.com/milvus-io/milvus/pkg/util/typeutil"
)
var (
once sync.Onc... | milvus/internal/registry/in_mem_resolver.go/0 | {
"file_path": "milvus/internal/registry/in_mem_resolver.go",
"repo_id": "milvus",
"token_count": 457
} | 2,053 |
<jupyter_start><jupyter_text>Nvidia TensorRT-LLM TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.[TensorRT-LLM Github](https://github.com/NVIDIA/Tensor... | llama_index/docs/examples/llm/nvidia_tensorrt.ipynb/0 | {
"file_path": "llama_index/docs/examples/llm/nvidia_tensorrt.ipynb",
"repo_id": "llama_index",
"token_count": 753
} | 1,068 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-earnings-call-transcript/llama_index/readers/earnings_call_transcript/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-earnings-call-transcript/llama_index/readers/earnings_call_transcript/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,309 |
// 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/index_builder.go/0 | {
"file_path": "milvus/internal/datacoord/index_builder.go",
"repo_id": "milvus",
"token_count": 7725
} | 1,765 |
package paramtable
import (
"testing"
"github.com/stretchr/testify/assert"
"github.com/milvus-io/milvus/pkg/config"
)
func TestRoleConfig_Init(t *testing.T) {
params := ComponentParam{}
params.Init(NewBaseTable(SkipRemote(true)))
cfg := ¶ms.RoleCfg
assert.Equal(t, cfg.Enabled.GetAsBool(), false)
assert.... | milvus/pkg/util/paramtable/role_param_test.go/0 | {
"file_path": "milvus/pkg/util/paramtable/role_param_test.go",
"repo_id": "milvus",
"token_count": 677
} | 2,119 |
# RAG with Timescale Vector using hybrid search
This template shows how to use timescale-vector with the self-query retriver to perform hybrid search on similarity and time.
This is useful any time your data has a strong time-based component. Some examples of such data are:
- News articles (politics, business, etc)
- ... | langchain/templates/rag-timescale-hybrid-search-time/README.md/0 | {
"file_path": "langchain/templates/rag-timescale-hybrid-search-time/README.md",
"repo_id": "langchain",
"token_count": 1479
} | 701 |
python_tests(
interpreter_constraints=["==3.9.*", "==3.10.*"],
)
| llama_index/llama-index-packs/llama-index-packs-agent-search-retriever/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-agent-search-retriever/tests/BUILD",
"repo_id": "llama_index",
"token_count": 29
} | 1,768 |
<jupyter_start><jupyter_text>NomicNomic currently offers two products:- Atlas: their Visual Data Engine- GPT4All: their Open Source Edge Language Model EcosystemThe Nomic integration exists in its own [partner package](https://pypi.org/project/langchain-nomic/). You can install it with:<jupyter_code>%pip install -qU la... | langchain/docs/docs/integrations/providers/nomic.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/providers/nomic.ipynb",
"repo_id": "langchain",
"token_count": 180
} | 151 |
from langchain_community.tools.google_jobs.tool import GoogleJobsQueryRun
__all__ = ["GoogleJobsQueryRun"]
| langchain/libs/langchain/langchain/tools/google_jobs/tool.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/google_jobs/tool.py",
"repo_id": "langchain",
"token_count": 33
} | 577 |
import { execSync } from 'child_process';
import fs from 'fs';
import { fileURLToPath } from 'url';
import path from 'path';
// Convert the URL to a file path
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
// Adjust the path to your package.json as necessary
const packa... | langsmith-sdk/js/scripts/check-npm-version.js/0 | {
"file_path": "langsmith-sdk/js/scripts/check-npm-version.js",
"repo_id": "langsmith-sdk",
"token_count": 358
} | 1,065 |
<jupyter_start><jupyter_text>How to scale LLM workloads to 20B+ with multi-node clusters on Amazon SageMaker using Hugging Face and PyTorch FSDPIn this tutorial, we will fine-tune the new [GPT-NeoXT-Chat-Base-20B](https://huggingface.co/togethercomputer/GPT-NeoXT-Chat-Base-20B) on the [ELI5](https://huggingface.co/data... | notebooks/sagemaker/25_pytorch_fsdp_model_parallelism/sagemaker-notebook.ipynb/0 | {
"file_path": "notebooks/sagemaker/25_pytorch_fsdp_model_parallelism/sagemaker-notebook.ipynb",
"repo_id": "notebooks",
"token_count": 3866
} | 291 |
# 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/kandinsky/test_kandinsky_prior.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky/test_kandinsky_prior.py",
"repo_id": "diffusers",
"token_count": 3239
} | 270 |
# TruLens
This page covers how to use [TruLens](https://trulens.org) to evaluate and track LLM apps built on langchain.
## What is TruLens?
TruLens is an [open-source](https://github.com/truera/trulens) package that provides instrumentation and evaluation tools for large language model (LLM) based applications.
## ... | langchain/docs/docs/integrations/providers/trulens.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/trulens.mdx",
"repo_id": "langchain",
"token_count": 637
} | 155 |
# coding=utf-8
# Copyright 2023 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/fuyu/processing_fuyu.py/0 | {
"file_path": "transformers/src/transformers/models/fuyu/processing_fuyu.py",
"repo_id": "transformers",
"token_count": 13839
} | 668 |
{
"modelname": "FlaxNewENCDEC",
"uppercase_modelname": "FLAX_NEW_ENC_DEC",
"lowercase_modelname": "flax_new_enc_dec_template",
"camelcase_modelname": "FlaxNewEncDec",
"authors": "The HuggingFace Team",
"checkpoint_identifier": "new-flax-enc-dec-base",
"tokenizer_type": "Based on BART",
"generate_tensorf... | transformers/templates/adding_a_new_model/tests/flax-seq-2-seq-bart-tokenizer.json/0 | {
"file_path": "transformers/templates/adding_a_new_model/tests/flax-seq-2-seq-bart-tokenizer.json",
"repo_id": "transformers",
"token_count": 161
} | 722 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/basic_tutorials/notebook.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/notebook.md",
"repo_id": "accelerate",
"token_count": 5538
} | 2 |
"""Base class for Amadeus tools."""
from __future__ import annotations
from typing import TYPE_CHECKING
from langchain_core.pydantic_v1 import Field
from langchain_core.tools import BaseTool
from langchain_community.tools.amadeus.utils import authenticate
if TYPE_CHECKING:
from amadeus import Client
class Ama... | langchain/libs/community/langchain_community/tools/amadeus/base.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/amadeus/base.py",
"repo_id": "langchain",
"token_count": 133
} | 295 |
# LlamaIndex Vector_Stores Integration: Opensearch
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/README.md",
"repo_id": "llama_index",
"token_count": 14
} | 1,529 |
export {
RemoteRetriever,
type RemoteRetrieverParams,
type RemoteRetrieverAuth,
type RemoteRetrieverValues,
} from "./base.js";
| langchainjs/libs/langchain-community/src/retrievers/remote/index.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/retrievers/remote/index.ts",
"repo_id": "langchainjs",
"token_count": 47
} | 1,007 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package mocks
import (
context "context"
mmap "golang.org/x/exp/mmap"
mock "github.com/stretchr/testify/mock"
storage "github.com/milvus-io/milvus/internal/storage"
time "time"
)
// ChunkManager is an autogenerated mock type for the ChunkManager type
type C... | milvus/internal/mocks/mock_chunk_manager.go/0 | {
"file_path": "milvus/internal/mocks/mock_chunk_manager.go",
"repo_id": "milvus",
"token_count": 10009
} | 1,812 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/pkg/util/typeutil/time.go/0 | {
"file_path": "milvus/pkg/util/typeutil/time.go",
"repo_id": "milvus",
"token_count": 435
} | 1,982 |
from langchain.chains import ConversationChain
from langchain.memory import ConversationBufferMemory
from langchain_community.chat_message_histories import StreamlitChatMessageHistory
from langchain_core.runnables import RunnableConfig
from langchain_core.tracers import LangChainTracer
from langchain_core.tracers.run_c... | streamlit-agent/streamlit_agent/simple_feedback.py/0 | {
"file_path": "streamlit-agent/streamlit_agent/simple_feedback.py",
"repo_id": "streamlit-agent",
"token_count": 1181
} | 2,146 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/main_classes/text_generation.md/0 | {
"file_path": "transformers/docs/source/en/main_classes/text_generation.md",
"repo_id": "transformers",
"token_count": 625
} | 449 |
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/zh/transformers_agents.md/0 | {
"file_path": "transformers/docs/source/zh/transformers_agents.md",
"repo_id": "transformers",
"token_count": 8118
} | 536 |
# LlamaIndex Indices Integration: Llama-Cloud
| llama_index/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,383 |
python_sources()
| llama_index/llama-index-core/llama_index/core/llama_pack/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/llama_pack/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,199 |
language: generic
dist: bionic
matrix:
include:
- env: CXX=g++-10 CC=gcc-10
addons:
apt:
packages:
- g++-10
sources:
- sourceline: 'ppa:ubuntu-toolchain-r/test'
- env: CXX=g++-9 CC=gcc-9
addons:
apt:
packages:
- ... | milvus/internal/core/thirdparty/NamedType/.travis.yml/0 | {
"file_path": "milvus/internal/core/thirdparty/NamedType/.travis.yml",
"repo_id": "milvus",
"token_count": 1419
} | 1,778 |
from typing import Any, List, Tuple
from unittest.mock import patch
from llama_index.core.graph_stores import SimpleGraphStore
from llama_index.core.embeddings import BaseEmbedding
from llama_index.core.indices.knowledge_graph.base import KnowledgeGraphIndex
from llama_index.core.indices.knowledge_graph.retrievers imp... | llama_index/llama-index-core/tests/indices/knowledge_graph/test_retrievers.py/0 | {
"file_path": "llama_index/llama-index-core/tests/indices/knowledge_graph/test_retrievers.py",
"repo_id": "llama_index",
"token_count": 2855
} | 1,312 |
use super::*;
use half::{bf16, f16};
use metal::{Buffer, Device, MTLResourceOptions};
fn read_to_vec<T: Clone>(buffer: &Buffer, n: usize) -> Vec<T> {
let ptr = buffer.contents() as *const T;
assert!(!ptr.is_null());
let slice = unsafe { std::slice::from_raw_parts(ptr, n) };
slice.to_vec()
}
fn new_buf... | candle/candle-metal-kernels/src/tests.rs/0 | {
"file_path": "candle/candle-metal-kernels/src/tests.rs",
"repo_id": "candle",
"token_count": 15812
} | 58 |
#[cfg(feature = "progressbar")]
pub(crate) use indicatif::{ProgressBar, ProgressStyle};
#[cfg(not(feature = "progressbar"))]
mod progressbar {
use std::borrow::Cow;
pub struct ProgressBar;
impl ProgressBar {
pub fn new(_length: u64) -> Self {
Self {}
}
pub fn set_length... | tokenizers/tokenizers/src/utils/progress.rs/0 | {
"file_path": "tokenizers/tokenizers/src/utils/progress.rs",
"repo_id": "tokenizers",
"token_count": 403
} | 442 |
---
sidebar_label: Together AI
---
# Together AI
The `TogetherAIEmbeddings` class uses the Together AI API to generate embeddings for a given text.
## Setup
In order to use the Together API you'll need an API key. You can sign up for a Together account and create an API key [here](https://www.api.together.ai/).
Yo... | langchainjs/docs/core_docs/docs/integrations/text_embedding/togetherai.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/text_embedding/togetherai.mdx",
"repo_id": "langchainjs",
"token_count": 242
} | 790 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/src/diffusers/pipelines/animatediff/pipeline_animatediff.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/animatediff/pipeline_animatediff.py",
"repo_id": "diffusers",
"token_count": 23366
} | 234 |
from typing import Any, Dict, List, Optional
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
class MetalReader(BaseReader):
"""Metal reader.
Args:
api_key (str): Metal API key.
client_id (str): Metal client ID.
index_id (str): Metal i... | llama_index/llama-index-integrations/readers/llama-index-readers-metal/llama_index/readers/metal/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-metal/llama_index/readers/metal/base.py",
"repo_id": "llama_index",
"token_count": 1006
} | 1,384 |
""" Class-Attention in Image Transformers (CaiT)
Paper: 'Going deeper with Image Transformers' - https://arxiv.org/abs/2103.17239
Original code and weights from https://github.com/facebookresearch/deit, copyright below
Modifications and additions for timm hacked together by / Copyright 2021, Ross Wightman
"""
# Copy... | pytorch-image-models/timm/models/cait.py/0 | {
"file_path": "pytorch-image-models/timm/models/cait.py",
"repo_id": "pytorch-image-models",
"token_count": 9133
} | 399 |
from typing import List
import requests
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
class MainContentExtractorReader(BaseReader):
"""MainContentExtractor web page reader.
Reads pages from the web.
Args:
text_format (str, optional): The forma... | llama_index/llama-index-integrations/readers/llama-index-readers-web/llama_index/readers/web/main_content_extractor/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-web/llama_index/readers/web/main_content_extractor/base.py",
"repo_id": "llama_index",
"token_count": 516
} | 1,467 |
python_sources()
| llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-redis/llama_index/storage/kvstore/redis/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-redis/llama_index/storage/kvstore/redis/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,469 |
# Remote Page/File Loader
This loader makes it easy to extract the text from the links available in a webpage URL, and extract the links presents in the page. It's based on `RemoteReader` (reading single page), that is based on `SimpleDirectoryReader` (parsing the document if file is a pdf, etc). It is an all-in-one t... | llama_index/llama-index-integrations/readers/llama-index-readers-remote-depth/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-remote-depth/README.md",
"repo_id": "llama_index",
"token_count": 424
} | 1,412 |
[tool.poetry]
name = "neo4j-semantic-layer"
version = "0.1.0"
description = "Build a semantic layer to allow an agent to interact with a graph database in consistent and robust way."
authors = [
"Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
l... | langchain/templates/neo4j-semantic-layer/pyproject.toml/0 | {
"file_path": "langchain/templates/neo4j-semantic-layer/pyproject.toml",
"repo_id": "langchain",
"token_count": 322
} | 700 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2024 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/LI... | diffusers/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py/0 | {
"file_path": "diffusers/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py",
"repo_id": "diffusers",
"token_count": 43852
} | 209 |
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