text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
from langchain_community.utilities.google_trends import GoogleTrendsAPIWrapper
__all__ = ["GoogleTrendsAPIWrapper"]
| langchain/libs/langchain/langchain/utilities/google_trends.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utilities/google_trends.py",
"repo_id": "langchain",
"token_count": 36
} | 572 |
<!--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/ko/big_models.md/0 | {
"file_path": "transformers/docs/source/ko/big_models.md",
"repo_id": "transformers",
"token_count": 4434
} | 525 |
import { ChatGooglePaLM } from "@langchain/community/chat_models/googlepalm";
import {
AIMessage,
HumanMessage,
SystemMessage,
} from "@langchain/core/messages";
export const run = async () => {
const model = new ChatGooglePaLM({
apiKey: "<YOUR API KEY>", // or set it in environment variable as `GOOGLE_PAL... | langchainjs/examples/src/models/chat/integration_googlepalm.ts/0 | {
"file_path": "langchainjs/examples/src/models/chat/integration_googlepalm.ts",
"repo_id": "langchainjs",
"token_count": 356
} | 800 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/trainer/sft_trainer.py/0 | {
"file_path": "trl/trl/trainer/sft_trainer.py",
"repo_id": "trl",
"token_count": 11056
} | 889 |
use super::ConversionError;
use crate::{
chroma_proto,
errors::{ChromaError, ErrorCodes},
};
use thiserror::Error;
#[derive(Debug, PartialEq)]
pub(crate) enum ScalarEncoding {
FLOAT32,
INT32,
}
#[derive(Error, Debug)]
pub(crate) enum ScalarEncodingConversionError {
#[error("Invalid encoding, valid... | chroma/rust/worker/src/types/scalar_encoding.rs/0 | {
"file_path": "chroma/rust/worker/src/types/scalar_encoding.rs",
"repo_id": "chroma",
"token_count": 914
} | 65 |
import { insecureHash } from "./utils/hash.js";
import type { Generation, ChatGeneration } from "./outputs.js";
import {
type StoredGeneration,
mapStoredMessageToChatMessage,
} from "./messages/index.js";
/**
* This cache key should be consistent across all versions of langchain.
* It is currently NOT consistent... | langchainjs/langchain-core/src/caches.ts/0 | {
"file_path": "langchainjs/langchain-core/src/caches.ts",
"repo_id": "langchainjs",
"token_count": 933
} | 857 |
package funcutil
import (
"fmt"
"strings"
"github.com/golang/protobuf/descriptor"
"github.com/golang/protobuf/proto"
"go.uber.org/zap"
"google.golang.org/protobuf/reflect/protoreflect"
"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
"github.com/milvus-io/milvus-proto/go-api/v2/milvuspb"
"github.com/m... | milvus/pkg/util/funcutil/policy.go/0 | {
"file_path": "milvus/pkg/util/funcutil/policy.go",
"repo_id": "milvus",
"token_count": 1404
} | 1,933 |
"""LlamaPack class."""
from typing import Any, Dict, List
from llama_index.core import ServiceContext, VectorStoreIndex, set_global_tokenizer
from llama_index.core.llama_pack.base import BaseLlamaPack
from llama_index.core.prompts import PromptTemplate
from llama_index.core.schema import Document
from llama_index.ll... | llama_index/llama-index-packs/llama-index-packs-zephyr-query-engine/llama_index/packs/zephyr_query_engine/base.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-zephyr-query-engine/llama_index/packs/zephyr_query_engine/base.py",
"repo_id": "llama_index",
"token_count": 1784
} | 1,740 |
<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<path
d="M7 22V11M2 13V20C2 21.1046 2.89543 22 4 22H17.4262C18.907 22 20.1662 20.9197 20.3914 19.4562L21.4683 12.4562C21.7479 10.6389 20.3418 9 18.5032 9H15C14.4477 9 14 8.55228 14 8V4.46584C14 3.10399 12.896 2 11.5342... | langserve/langserve/playground/src/assets/ThumbsUpIcon.svg/0 | {
"file_path": "langserve/langserve/playground/src/assets/ThumbsUpIcon.svg",
"repo_id": "langserve",
"token_count": 269
} | 1,048 |
use super::ConversionError;
use crate::{
chroma_proto,
errors::{ChromaError, ErrorCodes},
};
use thiserror::Error;
#[derive(Debug, PartialEq)]
pub(crate) enum SegmentScope {
VECTOR,
METADATA,
}
#[derive(Error, Debug)]
pub(crate) enum SegmentScopeConversionError {
#[error("Invalid segment scope, va... | chroma/rust/worker/src/types/segment_scope.rs/0 | {
"file_path": "chroma/rust/worker/src/types/segment_scope.rs",
"repo_id": "chroma",
"token_count": 932
} | 61 |
# flake8: noqa
TOOLKIT_TOOL_DESCRIPTION = """{description}. The tool must be invoked with a complete sentence starting with "{name}" and additional information on {required_params}."""
API_CONTROLLER_PROMPT = """You are turning user input into a json query for an API request tool.
The final output to the tool should... | langchain/libs/partners/robocorp/langchain_robocorp/_prompts.py/0 | {
"file_path": "langchain/libs/partners/robocorp/langchain_robocorp/_prompts.py",
"repo_id": "langchain",
"token_count": 186
} | 698 |
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import {
type AWSSfnToolkitArgs,
AWSSfnToolkit,
} from "@langchain/community/agents/toolkits/aws_sfn";
import { renderTemplate } from "@langchain/core/prompts";
import { LLMChain } from "../../chains/llm_chain.js";
import { Zero... | langchainjs/langchain/src/agents/toolkits/aws_sfn.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/toolkits/aws_sfn.ts",
"repo_id": "langchainjs",
"token_count": 650
} | 872 |
[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.mypy]
disallow_untyped_defs = true
exclude = ["_static", "build", "examples", "notebooks", "venv"]
ignore_missi... | llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/pyproject.toml",
"repo_id": "llama_index",
"token_count": 626
} | 1,477 |
from __future__ import annotations
import asyncio
import collections
import inspect
import threading
from abc import ABC, abstractmethod
from concurrent.futures import FIRST_COMPLETED, wait
from contextvars import copy_context
from functools import wraps
from itertools import groupby, tee
from operator import itemgett... | langchain/libs/core/langchain_core/runnables/base.py/0 | {
"file_path": "langchain/libs/core/langchain_core/runnables/base.py",
"repo_id": "langchain",
"token_count": 80220
} | 396 |
<jupyter_start><jupyter_text>MosaicML[MosaicML](https://docs.mosaicml.com/en/latest/inference.html) offers a managed inference service. You can either use a variety of open-source models, or deploy your own.This example goes over how to use LangChain to interact with MosaicML Inference for text completion.<jupyter_code... | langchain/docs/docs/integrations/llms/mosaicml.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/mosaicml.ipynb",
"repo_id": "langchain",
"token_count": 338
} | 128 |
<jupyter_start><jupyter_code>! pip install langchain_community tiktoken langchain-openai langchainhub chromadb langchain langgraph<jupyter_output><empty_output><jupyter_text>LangGraph Retrieval AgentWe can implement [Retrieval Agents](https://python.langchain.com/docs/use_cases/question_answering/conversational_retriev... | langgraph/examples/rag/langgraph_agentic_rag.ipynb/0 | {
"file_path": "langgraph/examples/rag/langgraph_agentic_rag.ipynb",
"repo_id": "langgraph",
"token_count": 3679
} | 1,035 |
// 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/msgdispatcher/mock_test.go/0 | {
"file_path": "milvus/pkg/mq/msgdispatcher/mock_test.go",
"repo_id": "milvus",
"token_count": 2656
} | 1,954 |
import { Document } from "@langchain/core/documents";
import { BaseDocumentLoader } from "../base.js";
/**
* See https://docs.sort.xyz/docs/api-keys to get your free Sort API key.
* See https://docs.sort.xyz for more information on the available queries.
* See https://docs.sort.xyz/reference for more information ab... | langchainjs/langchain/src/document_loaders/web/sort_xyz_blockchain.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/web/sort_xyz_blockchain.ts",
"repo_id": "langchainjs",
"token_count": 1925
} | 886 |
import { type ClientOptions } from "openai";
import { type BaseChatModelParams } from "@langchain/core/language_models/chat_models";
import { ChatOpenAI } from "../chat_models.js";
import {
AzureOpenAIInput,
LegacyOpenAIInput,
OpenAIChatInput,
} from "../types.js";
export class AzureChatOpenAI extends ChatOpenAI... | langchainjs/libs/langchain-openai/src/azure/chat_models.ts/0 | {
"file_path": "langchainjs/libs/langchain-openai/src/azure/chat_models.ts",
"repo_id": "langchainjs",
"token_count": 849
} | 1,063 |
# 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/deta/convert_deta_resnet_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/deta/convert_deta_resnet_to_pytorch.py",
"repo_id": "transformers",
"token_count": 7808
} | 593 |
# Metric Card for ROC AUC
## Metric Description
This metric computes the area under the curve (AUC) for the Receiver Operating Characteristic Curve (ROC). The return values represent how well the model used is predicting the correct classes, based on the input data. A score of `0.5` means that the model is predicting... | datasets/metrics/roc_auc/README.md/0 | {
"file_path": "datasets/metrics/roc_auc/README.md",
"repo_id": "datasets",
"token_count": 3273
} | 143 |
"""Main entrypoint into package."""
from importlib import metadata
try:
__version__ = metadata.version(__package__)
except metadata.PackageNotFoundError:
# Case where package metadata is not available.
__version__ = ""
| langchain/libs/partners/together/langchain_together/version.py/0 | {
"file_path": "langchain/libs/partners/together/langchain_together/version.py",
"repo_id": "langchain",
"token_count": 66
} | 681 |
"""A chain for comparing the output of two models using embeddings."""
from enum import Enum
from typing import Any, Dict, List, Optional
import numpy as np
from langchain_community.embeddings.openai import OpenAIEmbeddings
from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import Field, ... | langchain/libs/langchain/langchain/evaluation/embedding_distance/base.py/0 | {
"file_path": "langchain/libs/langchain/langchain/evaluation/embedding_distance/base.py",
"repo_id": "langchain",
"token_count": 6777
} | 511 |
[
{
"server": "idc-sh003",
"suite_params": [
{
"suite": "2_insert_search.yaml",
"image_type": "cpu"
}
]
}
]
| milvus/tests/benchmark/milvus_benchmark/scheduler/search.json/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/scheduler/search.json",
"repo_id": "milvus",
"token_count": 136
} | 1,965 |
# TODO: implement tests for delete
| langchain/libs/community/tests/integration_tests/vectorstores/qdrant/test_delete.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/vectorstores/qdrant/test_delete.py",
"repo_id": "langchain",
"token_count": 9
} | 357 |
"""Base callback handler that can be used to handle callbacks in langchain."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, TypeVar, Union
from uuid import UUID
from tenacity import RetryCallState
if TYPE_CHECKING:
from langchain_core.agents import Age... | langchain/libs/core/langchain_core/callbacks/base.py/0 | {
"file_path": "langchain/libs/core/langchain_core/callbacks/base.py",
"repo_id": "langchain",
"token_count": 8308
} | 387 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/core/src/storage/PayloadStream.cpp/0 | {
"file_path": "milvus/internal/core/src/storage/PayloadStream.cpp",
"repo_id": "milvus",
"token_count": 1103
} | 1,893 |
<jupyter_start><jupyter_text>Label Studio>[Label Studio](https://labelstud.io/guide/get_started) is an open-source data labeling platform that provides LangChain with flexibility when it comes to labeling data for fine-tuning large language models (LLMs). It also enables the preparation of custom training data and the ... | langchain/docs/docs/integrations/callbacks/labelstudio.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/callbacks/labelstudio.ipynb",
"repo_id": "langchain",
"token_count": 1738
} | 93 |
"""Amadeus tools."""
from langchain_community.tools.amadeus.closest_airport import AmadeusClosestAirport
from langchain_community.tools.amadeus.flight_search import AmadeusFlightSearch
__all__ = [
"AmadeusClosestAirport",
"AmadeusFlightSearch",
]
| langchain/libs/community/langchain_community/tools/amadeus/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/amadeus/__init__.py",
"repo_id": "langchain",
"token_count": 93
} | 301 |
/*
* 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... | milvus/pkg/util/expr/expr_test.go/0 | {
"file_path": "milvus/pkg/util/expr/expr_test.go",
"repo_id": "milvus",
"token_count": 587
} | 2,104 |
[package]
name = "grpc-metadata"
version = "0.1.0"
edition = "2021"
[dependencies]
opentelemetry = "^0.20"
tonic = "^0.10"
tracing = "^0.1"
tracing-opentelemetry = "^0.21"
| text-generation-inference/router/grpc-metadata/Cargo.toml/0 | {
"file_path": "text-generation-inference/router/grpc-metadata/Cargo.toml",
"repo_id": "text-generation-inference",
"token_count": 83
} | 404 |
- name: datacoord
docker_container:
name: datacoord
image: "{{image}}"
command: ["milvus", "run", "datacoord"]
env:
ETCD_ENDPOINTS: "{{ETCD_ENDPOINTS}}"
MINIO_ADDRESS: "{{MINIO_ADDRESS}}"
PULSAR_ADDRESS: "{{PULSAR_ADDRESS}}"
DATA_COORD_ADDRESS: "{{DATA_COORD_ADDRESS}}"
M... | milvus/deployments/docker/cluster-distributed-deployment/roles/deploy-datacoord/tasks/main.yml/0 | {
"file_path": "milvus/deployments/docker/cluster-distributed-deployment/roles/deploy-datacoord/tasks/main.yml",
"repo_id": "milvus",
"token_count": 205
} | 1,728 |
"""NebulaGraph graph store index."""
import logging
import os
from string import Template
from typing import Any, Dict, List, Optional
from llama_index.core.graph_stores.types import GraphStore
from nebula3.common import ttypes
from nebula3.Config import SessionPoolConfig
from nebula3.Exception import IOErrorExceptio... | llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-nebula/llama_index/graph_stores/nebula/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-nebula/llama_index/graph_stores/nebula/base.py",
"repo_id": "llama_index",
"token_count": 12859
} | 1,292 |
const file2base64 = (file: File): Promise<string> => {
return new Promise<string>((resolve, reject) => {
const reader = new FileReader();
reader.readAsDataURL(file);
reader.onload = () => {
const dataUrl = reader.result as string;
const base64 = dataUrl.split(",")[1];
resolve(base64);
};
reader.oner... | chat-ui/src/lib/utils/file2base64.ts/0 | {
"file_path": "chat-ui/src/lib/utils/file2base64.ts",
"repo_id": "chat-ui",
"token_count": 142
} | 95 |
""" Gather-Excite Attention Block
Paper: `Gather-Excite: Exploiting Feature Context in CNNs` - https://arxiv.org/abs/1810.12348
Official code here, but it's only partial impl in Caffe: https://github.com/hujie-frank/GENet
I've tried to support all of the extent both w/ and w/o params. I don't believe I've seen anoth... | pytorch-image-models/timm/layers/gather_excite.py/0 | {
"file_path": "pytorch-image-models/timm/layers/gather_excite.py",
"repo_id": "pytorch-image-models",
"token_count": 1956
} | 364 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "retrievers/supabase",
});
export * from "@langchain/community/retrievers/supabase";
| langchainjs/langchain/src/retrievers/supabase.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/supabase.ts",
"repo_id": "langchainjs",
"token_count": 74
} | 906 |
import { ChatOpenAI } from "@langchain/openai";
import {
ChatPromptTemplate,
MessagesPlaceholder,
} from "@langchain/core/prompts";
import {
RunnableConfig,
RunnableWithMessageHistory,
} from "@langchain/core/runnables";
import { ChatMessageHistory } from "@langchain/community/stores/message/in_memory";
// Ins... | langchainjs/examples/src/guides/expression_language/runnable_history.ts/0 | {
"file_path": "langchainjs/examples/src/guides/expression_language/runnable_history.ts",
"repo_id": "langchainjs",
"token_count": 793
} | 779 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.feedly_rss import FeedlyRssReader
def test_class():
names_of_base_classes = [b.__name__ for b in FeedlyRssReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-feedly-rss/tests/test_readers_feedly_rss.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-feedly-rss/tests/test_readers_feedly_rss.py",
"repo_id": "llama_index",
"token_count": 94
} | 1,290 |
apiVersion: chaos-mesh.org/v1alpha1
kind: PodChaos
metadata:
name: test-querycoord-pod-failure
namespace: chaos-testing
spec:
selector:
namespaces:
- chaos-testing
labelSelectors:
app.kubernetes.io/instance: milvus-chaos
component: querycoord
mode: fixed
value: "1"
action: pod-fail... | milvus/tests/python_client/chaos/chaos_objects/pod_failure/chaos_querycoord_pod_failure.yaml/0 | {
"file_path": "milvus/tests/python_client/chaos/chaos_objects/pod_failure/chaos_querycoord_pod_failure.yaml",
"repo_id": "milvus",
"token_count": 141
} | 2,169 |
from langchain_community.document_loaders.spreedly import (
SpreedlyLoader,
)
__all__ = ["SpreedlyLoader"]
| langchain/libs/langchain/langchain/document_loaders/spreedly.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/spreedly.py",
"repo_id": "langchain",
"token_count": 40
} | 525 |
python_tests()
| llama_index/llama-index-integrations/indices/llama-index-indices-managed-vectara/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/indices/llama-index-indices-managed-vectara/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,213 |
python_sources()
| llama_index/llama-index-core/llama_index/core/indices/query/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/query/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,181 |
<jupyter_start><jupyter_text>Hugging FaceThis notebook shows how to get started using `Hugging Face` LLM's as chat models.In particular, we will:1. Utilize the [HuggingFaceTextGenInference](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/llms/huggingface_text_gen_inference.py), [HuggingFa... | langchain/docs/docs/integrations/chat/huggingface.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/chat/huggingface.ipynb",
"repo_id": "langchain",
"token_count": 2887
} | 100 |
import type { TextGenerationStreamOutput } from "@huggingface/inference";
import type OpenAI from "openai";
import type { Stream } from "openai/streaming";
/**
* Transform a stream of OpenAI.Completions.Completion into a stream of TextGenerationStreamOutput
*/
export async function* openAICompletionToTextGenerationS... | chat-ui/src/lib/server/endpoints/openai/openAICompletionToTextGenerationStream.ts/0 | {
"file_path": "chat-ui/src/lib/server/endpoints/openai/openAICompletionToTextGenerationStream.ts",
"repo_id": "chat-ui",
"token_count": 310
} | 106 |
"""**Callback handlers** allow listening to events in LangChain.
**Class hierarchy:**
.. code-block::
BaseCallbackHandler --> <name>CallbackHandler # Example: AimCallbackHandler
"""
from langchain_community.callbacks.aim_callback import AimCallbackHandler
from langchain_community.callbacks.argilla_callback imp... | langchain/libs/community/langchain_community/callbacks/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/callbacks/__init__.py",
"repo_id": "langchain",
"token_count": 768
} | 229 |
# Optimizing inference
perf_infer_gpu_many: perf_infer_gpu_one
| transformers/docs/source/en/_redirects.yml/0 | {
"file_path": "transformers/docs/source/en/_redirects.yml",
"repo_id": "transformers",
"token_count": 25
} | 494 |
from .base_tokenizer import BaseTokenizer
from .bert_wordpiece import BertWordPieceTokenizer
from .byte_level_bpe import ByteLevelBPETokenizer
from .char_level_bpe import CharBPETokenizer
from .sentencepiece_bpe import SentencePieceBPETokenizer
from .sentencepiece_unigram import SentencePieceUnigramTokenizer
| tokenizers/bindings/python/py_src/tokenizers/implementations/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/__init__.py",
"repo_id": "tokenizers",
"token_count": 94
} | 446 |
import json
from typing import Any, Callable, List
from langchain_core.tracers.base import BaseTracer
from langchain_core.tracers.schemas import Run
from langchain_core.utils.input import get_bolded_text, get_colored_text
def try_json_stringify(obj: Any, fallback: str) -> str:
"""
Try to stringify an object ... | langchain/libs/core/langchain_core/tracers/stdout.py/0 | {
"file_path": "langchain/libs/core/langchain_core/tracers/stdout.py",
"repo_id": "langchain",
"token_count": 2952
} | 432 |
# 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 applicabl... | transformers/src/transformers/models/deta/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/deta/__init__.py",
"repo_id": "transformers",
"token_count": 822
} | 622 |
---
sidebar_position: 0
---
# Custom agent
This notebook goes through how to create your own custom agent.
In this example, we will use OpenAI Function Calling to create this agent.
**This is generally the most reliable way to create agents.**
We will first create it WITHOUT memory, but we will then show how to add... | langchainjs/docs/core_docs/docs/modules/agents/how_to/custom_agent.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/agents/how_to/custom_agent.mdx",
"repo_id": "langchainjs",
"token_count": 2306
} | 734 |
import { initializeAgentExecutorWithOptions } from "langchain/agents";
import { OpenAI } from "@langchain/openai";
import { Calculator } from "langchain/tools/calculator";
import { SerpAPI } from "@langchain/community/tools/serpapi";
const model = new OpenAI({ temperature: 0 });
const tools = [
new SerpAPI(process.e... | langchainjs/examples/src/agents/agent_callbacks.ts/0 | {
"file_path": "langchainjs/examples/src/agents/agent_callbacks.ts",
"repo_id": "langchainjs",
"token_count": 1050
} | 765 |
# Chat Engine
## Concept
Chat engine is a high-level interface for having a conversation with your data
(multiple back-and-forth instead of a single question & answer).
Think ChatGPT, but augmented with your knowledge base.
Conceptually, it is a **stateful** analogy of a [Query Engine](../query_engine/root.md).
By k... | llama_index/docs/module_guides/deploying/chat_engines/root.md/0 | {
"file_path": "llama_index/docs/module_guides/deploying/chat_engines/root.md",
"repo_id": "llama_index",
"token_count": 340
} | 1,118 |
# CerebriumAI
This page covers how to use the CerebriumAI ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific CerebriumAI wrappers.
## Installation and Setup
- Install with `pip install cerebrium`
- Get an CerebriumAI api key and set it as an environment va... | langchain/docs/docs/integrations/providers/cerebriumai.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/cerebriumai.mdx",
"repo_id": "langchain",
"token_count": 147
} | 131 |
---
hide_table_of_contents: true
---
# College Confidential
This example goes over how to load data from the college confidential website, using Cheerio. One document will be created for each page.
## Setup
```bash npm2yarn
npm install cheerio
```
## Usage
```typescript
import { CollegeConfidentialLoader } from "... | langchainjs/docs/core_docs/docs/integrations/document_loaders/web_loaders/college_confidential.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/document_loaders/web_loaders/college_confidential.mdx",
"repo_id": "langchainjs",
"token_count": 157
} | 703 |
from overrides import EnforceOverrides, override
from typing import List, Optional, Sequence
from chromadb.config import System
from chromadb.proto.convert import (
from_proto_vector_embedding_record,
from_proto_vector_query_result,
to_proto_vector,
)
from chromadb.segment import VectorReader
from chromadb.... | chroma/chromadb/segment/impl/vector/grpc_segment.py/0 | {
"file_path": "chroma/chromadb/segment/impl/vector/grpc_segment.py",
"repo_id": "chroma",
"token_count": 1473
} | 19 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/src/transformers/models/seamless_m4t/modeling_seamless_m4t.py/0 | {
"file_path": "transformers/src/transformers/models/seamless_m4t/modeling_seamless_m4t.py",
"repo_id": "transformers",
"token_count": 89454
} | 740 |
"""Test parsing logic."""
import mimetypes
from langchain.document_loaders import Blob
from app.parsing import MIMETYPE_BASED_PARSER, SUPPORTED_MIMETYPES
from tests.unit_tests.fixtures import get_sample_paths
def test_list_of_supported_mimetypes() -> None:
"""This list should generally grow! Protecting against ... | opengpts/backend/tests/unit_tests/agent_executor/test_parsing.py/0 | {
"file_path": "opengpts/backend/tests/unit_tests/agent_executor/test_parsing.py",
"repo_id": "opengpts",
"token_count": 599
} | 1,987 |
from llama_index.llms.sagemaker_endpoint.base import SageMakerLLM
__all__ = ["SageMakerLLM"]
| llama_index/llama-index-integrations/llms/llama-index-llms-sagemaker-endpoint/llama_index/llms/sagemaker_endpoint/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-sagemaker-endpoint/llama_index/llms/sagemaker_endpoint/__init__.py",
"repo_id": "llama_index",
"token_count": 36
} | 1,247 |
# Inception v4
**Inception-v4** is a convolutional neural network architecture that builds on previous iterations of the Inception family by simplifying the architecture and using more inception modules than [Inception-v3](https://paperswithcode.com/method/inception-v3).
## How do I use this model on an image?
To load... | pytorch-image-models/docs/models/inception-v4.md/0 | {
"file_path": "pytorch-image-models/docs/models/inception-v4.md",
"repo_id": "pytorch-image-models",
"token_count": 1622
} | 369 |
# coding=utf-8
# Copyright 2022 {{cookiecutter.authors}}. 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 re... | transformers/templates/adding_a_missing_tokenization_test/cookiecutter-template-{{cookiecutter.modelname}}/test_tokenization_{{cookiecutter.lowercase_modelname}}.py/0 | {
"file_path": "transformers/templates/adding_a_missing_tokenization_test/cookiecutter-template-{{cookiecutter.modelname}}/test_tokenization_{{cookiecutter.lowercase_modelname}}.py",
"repo_id": "transformers",
"token_count": 1016
} | 738 |
// 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/util/mock/grpc_querycoord_client.go/0 | {
"file_path": "milvus/internal/util/mock/grpc_querycoord_client.go",
"repo_id": "milvus",
"token_count": 2312
} | 1,801 |
// 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/proxy/channels_mgr_test.go/0 | {
"file_path": "milvus/internal/proxy/channels_mgr_test.go",
"repo_id": "milvus",
"token_count": 5273
} | 1,735 |
from llama_index.readers.wordpress.base import WordpressReader
__all__ = ["WordpressReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-wordpress/llama_index/readers/wordpress/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-wordpress/llama_index/readers/wordpress/__init__.py",
"repo_id": "llama_index",
"token_count": 28
} | 1,451 |
python_sources()
python_tests(
name="tests",
skip_tests=True,
)
| llama_index/llama-index-legacy/tests/indices/keyword_table/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/keyword_table/BUILD",
"repo_id": "llama_index",
"token_count": 32
} | 1,797 |
# 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/tests/others/test_dependencies.py/0 | {
"file_path": "diffusers/tests/others/test_dependencies.py",
"repo_id": "diffusers",
"token_count": 775
} | 248 |
"""Test logic on base chain class."""
from typing import Any, Dict, List, Optional
import pytest
from langchain_core.memory import BaseMemory
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.chains.base import Chain
from langchain.schema import RUN_KEY
from tests.unit_tests.callbacks.... | langchain/libs/langchain/tests/unit_tests/chains/test_base.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/chains/test_base.py",
"repo_id": "langchain",
"token_count": 2033
} | 650 |
import os
import torch
from accelerate import Accelerator
from datasets import load_dataset
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, default_data_collator, get_linear_schedule_with_warmup
from peft import LoraConfig, TaskType, get_pef... | peft/examples/conditional_generation/peft_lora_seq2seq_accelerate_fsdp.py/0 | {
"file_path": "peft/examples/conditional_generation/peft_lora_seq2seq_accelerate_fsdp.py",
"repo_id": "peft",
"token_count": 2543
} | 337 |
from langchain_community.vectorstores.alibabacloud_opensearch import (
AlibabaCloudOpenSearch,
AlibabaCloudOpenSearchSettings,
)
__all__ = [
"AlibabaCloudOpenSearchSettings",
"AlibabaCloudOpenSearch",
]
| langchain/libs/langchain/langchain/vectorstores/alibabacloud_opensearch.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/alibabacloud_opensearch.py",
"repo_id": "langchain",
"token_count": 74
} | 624 |
<jupyter_start><jupyter_text>OpenAI metadata taggerIt can often be useful to tag ingested documents with structured metadata, such as the title, tone, or length of a document, to allow for a more targeted similarity search later. However, for large numbers of documents, performing this labelling process manually can be... | langchain/docs/docs/integrations/document_transformers/openai_metadata_tagger.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_transformers/openai_metadata_tagger.ipynb",
"repo_id": "langchain",
"token_count": 1617
} | 114 |
# coding=utf-8
# Copyright 2021 Microsoft Research and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | transformers/src/transformers/models/beit/modeling_flax_beit.py/0 | {
"file_path": "transformers/src/transformers/models/beit/modeling_flax_beit.py",
"repo_id": "transformers",
"token_count": 15754
} | 572 |
<jupyter_start><jupyter_text>Yuan2.0[Yuan2.0](https://github.com/IEIT-Yuan/Yuan-2.0) is a new generation Fundamental Large Language Model developed by IEIT System. We have published all three models, Yuan 2.0-102B, Yuan 2.0-51B, and Yuan 2.0-2B. And we provide relevant scripts for pretraining, fine-tuning, and inferenc... | langchain/docs/docs/integrations/llms/yuan2.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/yuan2.ipynb",
"repo_id": "langchain",
"token_count": 560
} | 134 |
from llama_index.readers.docugami.base import DocugamiReader
__all__ = ["DocugamiReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-docugami/llama_index/readers/docugami/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-docugami/llama_index/readers/docugami/__init__.py",
"repo_id": "llama_index",
"token_count": 32
} | 1,427 |
import logging
import platform
import warnings
from typing import Any, List, Optional, Type, Union
from langchain_core.callbacks import (
CallbackManagerForToolRun,
)
from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
from langchain_core.tools import BaseTool
logger = logging.getLogger(__name... | langchain/libs/community/langchain_community/tools/shell/tool.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/shell/tool.py",
"repo_id": "langchain",
"token_count": 1242
} | 308 |
"""
coding=utf-8
Copyright 2018, Antonio Mendoza Hao Tan, Mohit Bansal, Huggingface team :)
Adapted From Facebook Inc, Detectron2
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://w... | transformers/examples/research_projects/visual_bert/utils.py/0 | {
"file_path": "transformers/examples/research_projects/visual_bert/utils.py",
"repo_id": "transformers",
"token_count": 8356
} | 577 |
# 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/pipelines/test_pipelines_fill_mask.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_fill_mask.py",
"repo_id": "transformers",
"token_count": 9728
} | 784 |
# Stable Diffusion text-to-image fine-tuning
The `train_text_to_image.py` script shows how to fine-tune stable diffusion model on your own dataset.
___Note___:
___This script is experimental. The script fine-tunes the whole model and often times the model overfits and runs into issues like catastrophic forgetting. I... | diffusers/examples/research_projects/onnxruntime/text_to_image/README.md/0 | {
"file_path": "diffusers/examples/research_projects/onnxruntime/text_to_image/README.md",
"repo_id": "diffusers",
"token_count": 847
} | 222 |
# coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University 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 the License at
#
# http://ww... | transformers/src/transformers/models/xlm_roberta/tokenization_xlm_roberta.py/0 | {
"file_path": "transformers/src/transformers/models/xlm_roberta/tokenization_xlm_roberta.py",
"repo_id": "transformers",
"token_count": 6160
} | 721 |
""" Scheduler Factory
Hacked together by / Copyright 2021 Ross Wightman
"""
from typing import List, Optional, Union
from torch.optim import Optimizer
from .cosine_lr import CosineLRScheduler
from .multistep_lr import MultiStepLRScheduler
from .plateau_lr import PlateauLRScheduler
from .poly_lr import PolyLRScheduler... | pytorch-image-models/timm/scheduler/scheduler_factory.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/scheduler_factory.py",
"repo_id": "pytorch-image-models",
"token_count": 3467
} | 383 |
<jupyter_start><jupyter_text>Vanna AI LlamaPackVanna AI is an open-source RAG framework for SQL generation. It works in two steps:1. Train a RAG model on your data2. Ask questions (use reference corpus to generate SQL queries that can run on your db).Check out the [Github project](https://github.com/vanna-ai/vanna) and... | llama_index/llama-index-packs/llama-index-packs-vanna/examples/vanna.ipynb/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-vanna/examples/vanna.ipynb",
"repo_id": "llama_index",
"token_count": 440
} | 1,694 |
Transform Query Engine
=======================
.. automodule:: llama_index.core.query_engine.transform_query_engine
:members:
:inherited-members:
| llama_index/docs/api_reference/query/query_engines/transform_query_engine.rst/0 | {
"file_path": "llama_index/docs/api_reference/query/query_engines/transform_query_engine.rst",
"repo_id": "llama_index",
"token_count": 47
} | 1,034 |
"""Test WatsonxLLM API wrapper.
You'll need to set WATSONX_APIKEY and WATSONX_PROJECT_ID environment variables.
"""
import os
from langchain_core.outputs import LLMResult
from langchain_ibm import WatsonxLLM
PROJECT_ID = os.environ.get("WATSONX_PROJECT_ID", "")
def test_watsonxllm_invoke() -> None:
watsonxll... | langchain/libs/partners/ibm/tests/integration_tests/test_llms.py/0 | {
"file_path": "langchain/libs/partners/ibm/tests/integration_tests/test_llms.py",
"repo_id": "langchain",
"token_count": 1046
} | 630 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package syncmgr
import (
context "context"
conc "github.com/milvus-io/milvus/pkg/util/conc"
mock "github.com/stretchr/testify/mock"
msgpb "github.com/milvus-io/milvus-proto/go-api/v2/msgpb"
)
// MockSyncManager is an autogenerated mock type for the SyncManage... | milvus/internal/datanode/syncmgr/mock_sync_manager.go/0 | {
"file_path": "milvus/internal/datanode/syncmgr/mock_sync_manager.go",
"repo_id": "milvus",
"token_count": 2276
} | 1,791 |
# (Automatic) Curriculum Learning for RL
While most of the RL methods seen in this course work well in practice, there are some cases where using them alone fails. This can happen, for instance, when:
- the task to learn is hard and requires an **incremental acquisition of skills** (for instance when one wants to mak... | deep-rl-class/units/en/unitbonus3/curriculum-learning.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus3/curriculum-learning.mdx",
"repo_id": "deep-rl-class",
"token_count": 1058
} | 173 |
from typing import List
from llama_index.core.base.embeddings.base import BaseEmbedding
from llama_index.core.node_parser.text.semantic_splitter import (
SemanticSplitterNodeParser,
)
from llama_index.core.schema import Document
class MockEmbedding(BaseEmbedding):
@classmethod
def class_name(cls) -> str:... | llama_index/llama-index-core/tests/node_parser/test_semantic_splitter.py/0 | {
"file_path": "llama_index/llama-index-core/tests/node_parser/test_semantic_splitter.py",
"repo_id": "llama_index",
"token_count": 1822
} | 1,195 |
from langchain_community.llms.modal import Modal
__all__ = ["Modal"]
| langchain/libs/langchain/langchain/llms/modal.py/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/modal.py",
"repo_id": "langchain",
"token_count": 25
} | 563 |
from langchain_core.documents import Document
from langchain_community.docstore.arbitrary_fn import DocstoreFn
def test_document_found() -> None:
# we use a dict here for simiplicity, but this could be any function
# including a remote lookup
dummy_dict = {"foo": Document(page_content="bar")}
docstor... | langchain/libs/community/tests/unit_tests/docstore/test_arbitrary_fn.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/docstore/test_arbitrary_fn.py",
"repo_id": "langchain",
"token_count": 154
} | 401 |
# coding=utf-8
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/xglm/test_modeling_xglm.py/0 | {
"file_path": "transformers/tests/models/xglm/test_modeling_xglm.py",
"repo_id": "transformers",
"token_count": 9446
} | 758 |
# LlamaIndex Llms Integration: Konko
| llama_index/llama-index-integrations/llms/llama-index-llms-konko/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-konko/README.md",
"repo_id": "llama_index",
"token_count": 11
} | 1,298 |
import type { LayoutServerLoad } from "./$types";
import { collections } from "$lib/server/database";
import type { Conversation } from "$lib/types/Conversation";
import { UrlDependency } from "$lib/types/UrlDependency";
import { defaultModel, models, oldModels, validateModel } from "$lib/server/models";
import { authC... | chat-ui/src/routes/+layout.server.ts/0 | {
"file_path": "chat-ui/src/routes/+layout.server.ts",
"repo_id": "chat-ui",
"token_count": 2036
} | 108 |
.PHONY: all clean docs_build docs_clean docs_linkcheck api_docs_build api_docs_clean api_docs_linkcheck format lint test tests test_watch integration_tests docker_tests help extended_tests
# Default target executed when no arguments are given to make.
all: help
######################
# TESTING AND COVERAGE
##########... | langchain/libs/langchain/Makefile/0 | {
"file_path": "langchain/libs/langchain/Makefile",
"repo_id": "langchain",
"token_count": 1615
} | 431 |
<jupyter_start><jupyter_text>StarRocks>[StarRocks](https://www.starrocks.io/) is a High-Performance Analytical Database.`StarRocks` is a next-gen sub-second MPP database for full analytics scenarios, including multi-dimensional analytics, real-time analytics and ad-hoc query.>Usually `StarRocks` is categorized into OLA... | langchain/docs/docs/integrations/vectorstores/starrocks.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/starrocks.ipynb",
"repo_id": "langchain",
"token_count": 1375
} | 195 |
//! # Template Processing
//!
//! Provides a way to specify templates in order to add the special tokens to each
//! input sequence as relevant.
//!
//! ## Example
//!
//! Let's take `BERT` tokenizer as an example. It uses two special tokens, used to
//! delimitate each sequence. `[CLS]` is always used at the beginning... | tokenizers/tokenizers/src/processors/template.rs/0 | {
"file_path": "tokenizers/tokenizers/src/processors/template.rs",
"repo_id": "tokenizers",
"token_count": 21195
} | 440 |
import { writable } from "svelte/store";
export const isAborted = writable<boolean>(false);
| chat-ui/src/lib/stores/isAborted.ts/0 | {
"file_path": "chat-ui/src/lib/stores/isAborted.ts",
"repo_id": "chat-ui",
"token_count": 30
} | 99 |
# Xorbits Inference (Xinference)
This page demonstrates how to use [Xinference](https://github.com/xorbitsai/inference)
with LangChain.
`Xinference` is a powerful and versatile library designed to serve LLMs,
speech recognition models, and multimodal models, even on your laptop.
With Xorbits Inference, you can effo... | langchain/docs/docs/integrations/providers/xinference.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/xinference.mdx",
"repo_id": "langchain",
"token_count": 772
} | 165 |
from __future__ import annotations
import logging
from typing import Any, Callable, Dict, List, Optional
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models.llms import LLM
from langchain_core.load.serializable import Serializab... | langchain/libs/community/langchain_community/llms/cohere.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/cohere.py",
"repo_id": "langchain",
"token_count": 3252
} | 276 |
---
sidebar_position: 2
sidebar_label: Puppeteer
hide_table_of_contents: true
sidebar_class_name: node-only
---
# Webpages, with Puppeteer
:::tip Compatibility
Only available on Node.js.
:::
This example goes over how to load data from webpages using Puppeteer. One document will be created for each webpage.
Puppete... | langchainjs/docs/core_docs/docs/integrations/document_loaders/web_loaders/web_puppeteer.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/document_loaders/web_loaders/web_puppeteer.mdx",
"repo_id": "langchainjs",
"token_count": 841
} | 736 |
from llama_index.core.node_parser.text.code import CodeSplitter
from llama_index.core.node_parser.text.langchain import LangchainNodeParser
from llama_index.core.node_parser.text.semantic_splitter import (
SemanticSplitterNodeParser,
)
from llama_index.core.node_parser.text.sentence import SentenceSplitter
from lla... | llama_index/llama-index-core/llama_index/core/node_parser/text/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/node_parser/text/__init__.py",
"repo_id": "llama_index",
"token_count": 225
} | 1,202 |
# Deprecated Pipelines
This folder contains pipelines that have very low usage as measured by model downloads, issues and PRs. While you can still use the pipelines just as before, we will stop testing the pipelines and will not accept any changes to existing files. | diffusers/src/diffusers/pipelines/deprecated/README.md/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/README.md",
"repo_id": "diffusers",
"token_count": 54
} | 254 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/querycoordv2/dist/dist_controller.go/0 | {
"file_path": "milvus/internal/querycoordv2/dist/dist_controller.go",
"repo_id": "milvus",
"token_count": 1104
} | 1,828 |
python_tests()
| llama_index/llama-index-integrations/tools/llama-index-tools-database/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-database/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,477 |
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