text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
from rag_multi_index_router.chain import chain
__all__ = ["chain"]
| langchain/templates/rag-multi-index-router/rag_multi_index_router/__init__.py/0 | {
"file_path": "langchain/templates/rag-multi-index-router/rag_multi_index_router/__init__.py",
"repo_id": "langchain",
"token_count": 23
} | 696 |
# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class ASTFeatureExtractor(metaclass=DummyObject):
_backends = ["speech"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["speech"])
class Speech2TextFeatureEx... | transformers/src/transformers/utils/dummy_speech_objects.py/0 | {
"file_path": "transformers/src/transformers/utils/dummy_speech_objects.py",
"repo_id": "transformers",
"token_count": 166
} | 787 |
<jupyter_start><jupyter_text>DashVector Vector Store If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-vector-stores-dashvector
!pip install llama-index
import logging
import sys
import os
logging.basicConfig(stream=sys.stdout, level=loggin... | llama_index/docs/examples/vector_stores/DashvectorIndexDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/vector_stores/DashvectorIndexDemo.ipynb",
"repo_id": "llama_index",
"token_count": 646
} | 1,145 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/internal/core/src/query/visitors/VerifyExprVisitor.cpp/0 | {
"file_path": "milvus/internal/core/src/query/visitors/VerifyExprVisitor.cpp",
"repo_id": "milvus",
"token_count": 508
} | 1,744 |
# Copyright 2024 ETH Zurich Computer Vision Lab and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | diffusers/src/diffusers/schedulers/scheduling_repaint.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_repaint.py",
"repo_id": "diffusers",
"token_count": 6515
} | 241 |
from langchain_experimental.tot.base import ToTChain
from langchain_experimental.tot.checker import ToTChecker
__all__ = ["ToTChain", "ToTChecker"]
| langchain/libs/experimental/langchain_experimental/tot/__init__.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/tot/__init__.py",
"repo_id": "langchain",
"token_count": 51
} | 449 |
import { gmail_v1, google } from "googleapis";
import { z } from "zod";
import { StructuredTool } from "@langchain/core/tools";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
export interface GmailBaseToolParams {
credentials?: {
clientEmail?: string;
privateKey?: string;
keyfile?: s... | langchainjs/libs/langchain-community/src/tools/gmail/base.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/tools/gmail/base.ts",
"repo_id": "langchainjs",
"token_count": 749
} | 1,073 |
"""Test the public API of the tools package."""
from langchain_community.vectorstores import __all__ as public_api
_EXPECTED = [
"AlibabaCloudOpenSearch",
"AlibabaCloudOpenSearchSettings",
"AnalyticDB",
"Annoy",
"AtlasDB",
"AwaDB",
"AzureSearch",
"Bagel",
"Cassandra",
"AstraDB",... | langchain/libs/community/tests/unit_tests/vectorstores/test_public_api.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/vectorstores/test_public_api.py",
"repo_id": "langchain",
"token_count": 778
} | 408 |
python_sources()
| llama_index/llama-index-core/llama_index/core/callbacks/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/callbacks/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,112 |
FROM rust:1.74.1 as builder
ARG CHROMA_KUBERNETES_INTEGRATION=0
ENV CHROMA_KUBERNETES_INTEGRATION $CHROMA_KUBERNETES_INTEGRATION
WORKDIR /
RUN git clone https://github.com/chroma-core/hnswlib.git
WORKDIR /chroma/
COPY . .
ENV PROTOC_ZIP=protoc-25.1-linux-x86_64.zip
RUN curl -OL https://github.com/protocolbuffers/pro... | chroma/rust/worker/Dockerfile/0 | {
"file_path": "chroma/rust/worker/Dockerfile",
"repo_id": "chroma",
"token_count": 263
} | 58 |
import argparse
import itertools
import json
import logging
import math
import uuid
import warnings
from os import environ, listdir, makedirs
from os.path import basename, join
from pathlib import Path
from typing import List
import datasets
import numpy as np
import torch
import torch.nn.functional as F
import torch.... | diffusers/examples/research_projects/multi_subject_dreambooth/train_multi_subject_dreambooth.py/0 | {
"file_path": "diffusers/examples/research_projects/multi_subject_dreambooth/train_multi_subject_dreambooth.py",
"repo_id": "diffusers",
"token_count": 21727
} | 199 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-hubspot/llama_index/readers/hubspot/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-hubspot/llama_index/readers/hubspot/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,378 |
apiVersion: chaos-mesh.org/v1alpha1
kind: PodChaos
metadata:
name: milvus-podchaos
namespace: chaos-testing
spec:
action: pod-kill
duration: 30s
mode: one
scheduler:
cron: '@every 20s'
selector:
labelSelectors:
app.kubernetes.io/name: zong-single-etcd-0
namespaces:
- milvus
value: ... | milvus/tests/benchmark/milvus_benchmark/chaos/pod-new.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/chaos/pod-new.yaml",
"repo_id": "milvus",
"token_count": 139
} | 1,933 |
//! Layer Normalization.
//!
//! This layer applies Layer Normalization over a mini-batch of inputs as described in [`Layer
//! Normalization`]. The input is expected to have three dimensions: a batch dimension, a length,
//! and a hidden size, the normalization is applied over the last dimension.
//!
//! # Example
//!... | candle/candle-nn/src/layer_norm.rs/0 | {
"file_path": "candle/candle-nn/src/layer_norm.rs",
"repo_id": "candle",
"token_count": 2263
} | 56 |
import { Redis } from "@upstash/redis";
import { BufferMemory } from "langchain/memory";
import { UpstashRedisChatMessageHistory } from "@langchain/community/stores/message/upstash_redis";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";
// Create your own Redis cli... | langchainjs/examples/src/memory/upstash_redis_advanced.ts/0 | {
"file_path": "langchainjs/examples/src/memory/upstash_redis_advanced.ts",
"repo_id": "langchainjs",
"token_count": 391
} | 890 |
//! ConvNeXt implementation.
//!
//! See "A ConvNet for the 2020s" Liu et al. 2022
//! <https://arxiv.org/abs/2201.03545>
//! and
//! "ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders" Woo et al. 2023
//! <https://arxiv.org/abs/2301.00808>
//! Original code:
//! https://github.com/facebookresear... | candle/candle-transformers/src/models/convnext.rs/0 | {
"file_path": "candle/candle-transformers/src/models/convnext.rs",
"repo_id": "candle",
"token_count": 4881
} | 72 |
<jupyter_start><jupyter_text>Connect to templateIn `server.py`, set -```add_routes(app, nvidia_rag_canonical_chain, path="/nvidia_rag_canonical")```<jupyter_code>from langserve.client import RemoteRunnable
rag_app = RemoteRunnable("http://0.0.0.0:8000/nvidia_rag_canonical")
rag_app.invoke("How many Americans receive S... | langchain/templates/nvidia-rag-canonical/nvidia_rag_canonical.ipynb/0 | {
"file_path": "langchain/templates/nvidia-rag-canonical/nvidia_rag_canonical.ipynb",
"repo_id": "langchain",
"token_count": 136
} | 654 |
# coding=utf-8
# Copyright 2020 The Google AI Language Team Authors, Allegro.pl, Facebook Inc. 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/herbert/tokenization_herbert_fast.py/0 | {
"file_path": "transformers/src/transformers/models/herbert/tokenization_herbert_fast.py",
"repo_id": "transformers",
"token_count": 2812
} | 683 |
# Modules
Notebooks with usage of these components can be found below.
## Response Evaluation
```{toctree}
---
maxdepth: 1
---
/examples/evaluation/faithfulness_eval.ipynb
/examples/evaluation/relevancy_eval.ipynb
/examples/evaluation/answer_and_context_relevancy.ipynb
/examples/evaluation/Deepeval.ipynb
/examples/... | llama_index/docs/module_guides/evaluating/modules.md/0 | {
"file_path": "llama_index/docs/module_guides/evaluating/modules.md",
"repo_id": "llama_index",
"token_count": 287
} | 1,092 |
<!---
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 ... | transformers/docs/source/de/installation.md/0 | {
"file_path": "transformers/docs/source/de/installation.md",
"repo_id": "transformers",
"token_count": 3989
} | 464 |
/* eslint-disable */
var globRequire = require
console.log = (..._args: any[]) => {}
describe('quicktourExample', () => {
function require(mod: string) {
if (mod.startsWith('tokenizers')) {
return globRequire('../../')
} else {
return globRequire(mod)
}
}
it.skip('trains the tokenizer',... | tokenizers/bindings/node/examples/documentation/quicktour.test.ts/0 | {
"file_path": "tokenizers/bindings/node/examples/documentation/quicktour.test.ts",
"repo_id": "tokenizers",
"token_count": 2324
} | 431 |
<jupyter_start><jupyter_text>CitationsHow can we get a model to cite which parts of the source documents it referenced in its response?To explore some techniques for extracting citations, let's first create a simple RAG chain. To start we'll just retrieve from the web using the [TavilySearchAPIRetriever](https://js.lan... | langchainjs/docs/core_docs/docs/use_cases/question_answering/citations.ipynb/0 | {
"file_path": "langchainjs/docs/core_docs/docs/use_cases/question_answering/citations.ipynb",
"repo_id": "langchainjs",
"token_count": 5829
} | 768 |
# 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/nougat/processing_nougat.py/0 | {
"file_path": "transformers/src/transformers/models/nougat/processing_nougat.py",
"repo_id": "transformers",
"token_count": 2932
} | 638 |
import pytest
from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool
# skip all tests if yfinance is not installed
yfinance = pytest.importorskip("yfinance")
def test_success() -> None:
"""Test that the tool runs successfully."""
tool = YahooFinanceNewsTool()
query = "Microsoft"
... | langchain/libs/community/tests/integration_tests/tools/test_yahoo_finance_news.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/tools/test_yahoo_finance_news.py",
"repo_id": "langchain",
"token_count": 302
} | 373 |
## Root Coordinator recovery on power failure
## 1. Basic idea
1. `RootCoord` (Root Coordinator) reads meta from etcd when it starts.
2. `RootCoord` needs to store the `position` of the msgstream into etcd every time it consumes the msgstream.
3. `RootCoord` reads the `position` of msgstream from etcd when it starts ... | milvus/docs/design_docs/20220105-root_coordinator_recovery_on_power_failure.md/0 | {
"file_path": "milvus/docs/design_docs/20220105-root_coordinator_recovery_on_power_failure.md",
"repo_id": "milvus",
"token_count": 2147
} | 1,714 |
[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 = ["TelegramReader"]
contains_example = false
import_path = "llama_index.readers.telegram"
[... | llama_index/llama-index-integrations/readers/llama-index-readers-telegram/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-telegram/pyproject.toml",
"repo_id": "llama_index",
"token_count": 662
} | 1,426 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/internal/core/src/segcore/segcore_init_c.cpp/0 | {
"file_path": "milvus/internal/core/src/segcore/segcore_init_c.cpp",
"repo_id": "milvus",
"token_count": 1166
} | 1,659 |
from llama_index.core.storage.docstore.keyval_docstore import KVDocumentStore
from llama_index.storage.docstore.redis import RedisDocumentStore
def test_class():
names_of_base_classes = [b.__name__ for b in RedisDocumentStore.__mro__]
assert KVDocumentStore.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/storage/docstore/llama-index-storage-docstore-redis/tests/test_storage_docstore_redis.py/0 | {
"file_path": "llama_index/llama-index-integrations/storage/docstore/llama-index-storage-docstore-redis/tests/test_storage_docstore_redis.py",
"repo_id": "llama_index",
"token_count": 102
} | 1,492 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package datacoord
import (
datapb "github.com/milvus-io/milvus/internal/proto/datapb"
mock "github.com/stretchr/testify/mock"
)
// MockCompactionPlanContext is an autogenerated mock type for the compactionPlanContext type
type MockCompactionPlanContext struct {
m... | milvus/internal/datacoord/mock_compaction_plan_context.go/0 | {
"file_path": "milvus/internal/datacoord/mock_compaction_plan_context.go",
"repo_id": "milvus",
"token_count": 4103
} | 1,914 |
from llama_index.legacy.param_tuner.base import (
AsyncParamTuner,
BaseParamTuner,
ParamTuner,
RayTuneParamTuner,
)
__all__ = ["BaseParamTuner", "ParamTuner", "AsyncParamTuner", "RayTuneParamTuner"]
| llama_index/llama-index-legacy/llama_index/legacy/param_tuner/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/param_tuner/__init__.py",
"repo_id": "llama_index",
"token_count": 89
} | 1,510 |
from langchain.schema.runnable.router import __all__
EXPECTED_ALL = ["RouterInput", "RouterRunnable"]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
| langchain/libs/langchain/tests/unit_tests/schema/runnable/test_router.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/schema/runnable/test_router.py",
"repo_id": "langchain",
"token_count": 71
} | 607 |
// 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/importutil/import_options.go/0 | {
"file_path": "milvus/internal/util/importutil/import_options.go",
"repo_id": "milvus",
"token_count": 1322
} | 1,802 |
# Metric Card for *Current Metric*
***Metric Card Instructions:*** *Copy this file into the relevant metric folder, then fill it out and save it as README.md. Feel free to take a look at existing metric cards if you'd like examples.*
## Metric Description
*Give a brief overview of this metric.*
## How to Use
*Give g... | datasets/templates/metric_card_template.md/0 | {
"file_path": "datasets/templates/metric_card_template.md",
"repo_id": "datasets",
"token_count": 397
} | 161 |
[build-system]
build-backend = "poetry.core.masonry.api"
requires = ["poetry-core"]
[tool.codespell]
check-filenames = true
check-hidden = true
ignore-words-list = "Gere"
skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
[tool.llamahub]
classes = ["arize_phoenix_callback_handler"]
contains_example = false
impo... | llama_index/llama-index-integrations/callbacks/llama-index-callbacks-arize-phoenix/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-arize-phoenix/pyproject.toml",
"repo_id": "llama_index",
"token_count": 730
} | 1,345 |
<jupyter_start><jupyter_text>Embedded Tables PackThis LlamaPack provides an example of our embedded-tables pack (with recursive retrieval + Unstructured.io).<jupyter_code>%pip install llama-index-packs-recursive-retriever
!pip install llama-index llama-hub unstructured==0.10.18 lxml
import nest_asyncio
nest_asyncio.ap... | llama_index/llama-index-packs/llama-index-packs-recursive-retriever/examples/embedded_tables.ipynb/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-recursive-retriever/examples/embedded_tables.ipynb",
"repo_id": "llama_index",
"token_count": 649
} | 1,867 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.hive import HiveReader
def test_class():
names_of_base_classes = [b.__name__ for b in HiveReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-hive/tests/test_readers_hive.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-hive/tests/test_readers_hive.py",
"repo_id": "llama_index",
"token_count": 86
} | 1,384 |
package crypto
import (
"crypto/md5" // #nosec
"crypto/sha256"
"encoding/base64"
"encoding/hex"
"golang.org/x/crypto/bcrypt"
)
func SHA256(src string, salt string) string {
h := sha256.New()
h.Write([]byte(src + salt))
sum := h.Sum(nil)
s := hex.EncodeToString(sum)
return s
}
// PasswordEncrypt encrypt p... | milvus/pkg/util/crypto/crypto.go/0 | {
"file_path": "milvus/pkg/util/crypto/crypto.go",
"repo_id": "milvus",
"token_count": 366
} | 2,048 |
from langchain_core.utils.function_calling import format_tool_to_openai_function
# For backwards compatibility
__all__ = ["format_tool_to_openai_function"]
| langchain/libs/langchain/langchain/tools/convert_to_openai.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/convert_to_openai.py",
"repo_id": "langchain",
"token_count": 46
} | 546 |
<!---
Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/docs/source/es/performance.md/0 | {
"file_path": "transformers/docs/source/es/performance.md",
"repo_id": "transformers",
"token_count": 1751
} | 470 |
import { test, expect, describe } from "@jest/globals";
import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai";
import { WebBrowser } from "../webbrowser.js";
import fetchAdapter from "../../util/axios-fetch-adapter.js";
describe("webbrowser Test suite", () => {
test("get word of the day", async () => {
... | langchainjs/langchain/src/tools/tests/webbrowser.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/tools/tests/webbrowser.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1567
} | 932 |
import { expect, test } from "@jest/globals";
import {
LengthBasedExampleSelector,
SemanticSimilarityExampleSelector,
} from "@langchain/core/example_selectors";
import { PromptTemplate } from "@langchain/core/prompts";
import { FakeEmbeddings } from "@langchain/core/utils/testing";
import { MemoryVectorStore } fro... | langchainjs/langchain/src/prompts/tests/selectors.test.ts/0 | {
"file_path": "langchainjs/langchain/src/prompts/tests/selectors.test.ts",
"repo_id": "langchainjs",
"token_count": 996
} | 957 |
// 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/allocator/id_allocator.go/0 | {
"file_path": "milvus/internal/allocator/id_allocator.go",
"repo_id": "milvus",
"token_count": 1682
} | 1,636 |
python_sources()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-docarray/llama_index/vector_stores/docarray/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-docarray/llama_index/vector_stores/docarray/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,458 |
# 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... | trl/tests/test_modeling_value_head.py/0 | {
"file_path": "trl/tests/test_modeling_value_head.py",
"repo_id": "trl",
"token_count": 9527
} | 779 |
"""Init file."""
| llama_index/llama-index-core/tests/playground/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/tests/playground/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,271 |
from __future__ import annotations
from typing import Any, Dict, Optional
from langchain_community.chat_message_histories import ZepChatMessageHistory
from langchain.memory import ConversationBufferMemory
class ZepMemory(ConversationBufferMemory):
"""Persist your chain history to the Zep MemoryStore.
The ... | langchain/libs/langchain/langchain/memory/zep_memory.py/0 | {
"file_path": "langchain/libs/langchain/langchain/memory/zep_memory.py",
"repo_id": "langchain",
"token_count": 2377
} | 527 |
<jupyter_start><jupyter_text>Zep>[Zep](https://docs.getzep.com/) is an open-source platform for LLM apps. Go from a prototype>built in LangChain or LlamaIndex, or a custom app, to production in minutes without rewriting code. Key Features:- **Fast!** `Zep` operates independently of your chat loop, ensuring a snappy use... | langchain/docs/docs/integrations/vectorstores/zep.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/zep.ipynb",
"repo_id": "langchain",
"token_count": 3288
} | 182 |
insert_search_performance:
collections:
# -
# milvus:
# db_config.primary_path: /test/milvus/distribued/sift_10m_128_l2_flat
# cache_config.cpu_cache_capacity: 8GB
# engine_config.use_blas_threshold: 0
# engine_config.gpu_search_threshold: 200
# gpu_resource_config.enable: t... | milvus/tests/benchmark/milvus_benchmark/suites/2_insert_search.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/2_insert_search.yaml",
"repo_id": "milvus",
"token_count": 2512
} | 2,148 |
import { NextRequest, NextResponse } from "next/server";
import { Message as VercelChatMessage, StreamingTextResponse } from "ai";
import { createClient } from "@supabase/supabase-js";
import { SupabaseVectorStore } from "@langchain/community/vectorstores/supabase";
import { AIMessage, ChatMessage, HumanMessage } fro... | langchain-nextjs-template/app/api/chat/retrieval_agents/route.ts/0 | {
"file_path": "langchain-nextjs-template/app/api/chat/retrieval_agents/route.ts",
"repo_id": "langchain-nextjs-template",
"token_count": 2185
} | 66 |
/* eslint-disable no-promise-executor-return */
/* eslint-disable @typescript-eslint/no-explicit-any */
import { test } from "@jest/globals";
import { FakeLLM } from "../../utils/testing/index.js";
test("RunnableWithFallbacks", async () => {
const llm = new FakeLLM({
thrownErrorString: "Bad error!",
});
awai... | langchainjs/langchain-core/src/runnables/tests/runnable_with_fallbacks.test.ts/0 | {
"file_path": "langchainjs/langchain-core/src/runnables/tests/runnable_with_fallbacks.test.ts",
"repo_id": "langchainjs",
"token_count": 433
} | 933 |
from langchain_community.tools.brave_search.tool import BraveSearch
__all__ = ["BraveSearch"]
| langchain/libs/langchain/langchain/tools/brave_search/tool.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/brave_search/tool.py",
"repo_id": "langchain",
"token_count": 28
} | 572 |
python_tests()
| llama_index/llama-index-integrations/llms/llama-index-llms-sagemaker-endpoint/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-sagemaker-endpoint/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,316 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-snowflake/llama_index/readers/snowflake/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-snowflake/llama_index/readers/snowflake/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,441 |
"""Chain for question-answering with self-verification."""
from __future__ import annotations
import warnings
from typing import Any, Dict, List, Optional
from langchain_core.callbacks import CallbackManagerForChainRun
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import Pro... | langchain/libs/langchain/langchain/chains/llm_checker/base.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/llm_checker/base.py",
"repo_id": "langchain",
"token_count": 2761
} | 469 |
import { Chroma } from "@langchain/community/vectorstores/chroma";
import { OpenAIEmbeddings } from "@langchain/openai";
const embeddings = new OpenAIEmbeddings();
const vectorStore = new Chroma(embeddings, {
collectionName: "test-deletion",
});
const documents = [
{
pageContent: `Tortoise: Labyrinth? Labyrin... | langchainjs/examples/src/indexes/vector_stores/chroma/delete.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/chroma/delete.ts",
"repo_id": "langchainjs",
"token_count": 622
} | 813 |
#!/usr/bin/env 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... | milvus/build/set_docker_mirror.sh/0 | {
"file_path": "milvus/build/set_docker_mirror.sh",
"repo_id": "milvus",
"token_count": 723
} | 1,697 |
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/tasks_explained.md/0 | {
"file_path": "transformers/docs/source/en/tasks_explained.md",
"repo_id": "transformers",
"token_count": 6963
} | 512 |
import { expect } from "@jest/globals";
import {
ICacheClient,
IMomentoCache,
CacheDelete,
CacheGet,
CacheIncrement,
CacheKeyExists,
CacheKeysExist,
CacheSet,
CacheSetIfNotExists,
CacheSetFetch,
CacheSetAddElements,
CacheSetAddElement,
CacheSetRemoveElements,
CacheSetRemoveElement,
CacheL... | langchainjs/libs/langchain-community/src/caches/tests/momento.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/caches/tests/momento.test.ts",
"repo_id": "langchainjs",
"token_count": 2813
} | 975 |
# Copyright 2023-present 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 law or... | peft/src/peft/tuners/lora/config.py/0 | {
"file_path": "peft/src/peft/tuners/lora/config.py",
"repo_id": "peft",
"token_count": 5276
} | 335 |
<jupyter_start><jupyter_text>Together AI> The Together API makes it easy to fine-tune or run leading open-source models with a couple lines of code. We have integrated the world’s leading open-source models, including Llama-2, RedPajama, Falcon, Alpaca, Stable Diffusion XL, and more. Read more: https://together.aiTo us... | langchain/docs/docs/integrations/llms/together.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/together.ipynb",
"repo_id": "langchain",
"token_count": 462
} | 131 |
import type { protos } from "@google-ai/generativelanguage";
import type { google } from "@google-ai/generativelanguage/build/protos/protos.js";
import { GoogleAuth, GoogleAuthOptions } from "google-auth-library";
import type { BaseLanguageModel } from "@langchain/core/language_models/base";
import { ChatGooglePaLM } f... | langchainjs/langchain/src/experimental/hubs/makersuite/googlemakersuitehub.ts/0 | {
"file_path": "langchainjs/langchain/src/experimental/hubs/makersuite/googlemakersuitehub.ts",
"repo_id": "langchainjs",
"token_count": 4397
} | 924 |
from langchain_experimental.prompts.load import load_prompt
__all__ = ["load_prompt"]
| langchain/libs/experimental/langchain_experimental/prompts/__init__.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/prompts/__init__.py",
"repo_id": "langchain",
"token_count": 30
} | 435 |
""" Exponential Moving Average (EMA) of model updates
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
from collections import OrderedDict
from copy import deepcopy
from typing import Optional
import torch
import torch.nn as nn
_logger = logging.getLogger(__name__)
class ModelEma:
""" Model... | pytorch-image-models/timm/utils/model_ema.py/0 | {
"file_path": "pytorch-image-models/timm/utils/model_ema.py",
"repo_id": "pytorch-image-models",
"token_count": 4590
} | 397 |
{
"collection_name": "book",
"output_fields": ["book_id"],
"search_params": [
{"key": "anns_field", "value": "book_intro"},
{"key": "topk", "value": "2"},
{"key": "params", "value": "{\"nprobe\": 10}"},
{"key": "metric_type", "value": "L2"},
{"key": "round_decimal", "value": "-1"}
],
"vect... | milvus/tests/scripts/restful-data/search.json/0 | {
"file_path": "milvus/tests/scripts/restful-data/search.json",
"repo_id": "milvus",
"token_count": 166
} | 2,049 |
from langchain_community.utils.openai_functions import (
FunctionDescription,
ToolDescription,
convert_pydantic_to_openai_function,
convert_pydantic_to_openai_tool,
)
__all__ = [
"FunctionDescription",
"ToolDescription",
"convert_pydantic_to_openai_function",
"convert_pydantic_to_openai... | langchain/libs/langchain/langchain/utils/openai_functions.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utils/openai_functions.py",
"repo_id": "langchain",
"token_count": 129
} | 599 |
"""Generative Agents primitives."""
from langchain_experimental.generative_agents.generative_agent import GenerativeAgent
from langchain_experimental.generative_agents.memory import GenerativeAgentMemory
__all__ = ["GenerativeAgent", "GenerativeAgentMemory"]
| langchain/libs/experimental/langchain_experimental/generative_agents/__init__.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/generative_agents/__init__.py",
"repo_id": "langchain",
"token_count": 66
} | 418 |
import hashlib
import json
import logging
import os
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import Iterable, Optional, Union
import torch
from torch.hub import HASH_REGEX, download_url_to_file, urlparse
try:
from torch.hub import get_dir
except Im... | pytorch-image-models/timm/models/_hub.py/0 | {
"file_path": "pytorch-image-models/timm/models/_hub.py",
"repo_id": "pytorch-image-models",
"token_count": 6737
} | 370 |
# Feature Extraction
All of the models in `timm` have consistent mechanisms for obtaining various types of features from the model for tasks besides classification.
## Penultimate Layer Features (Pre-Classifier Features)
The features from the penultimate model layer can be obtained in several ways without requiring ... | pytorch-image-models/hfdocs/source/feature_extraction.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/feature_extraction.mdx",
"repo_id": "pytorch-image-models",
"token_count": 2004
} | 343 |
from langchain.memory import chat_message_histories
from tests.unit_tests import assert_all_importable
EXPECTED_ALL = [
"AstraDBChatMessageHistory",
"ChatMessageHistory",
"CassandraChatMessageHistory",
"CosmosDBChatMessageHistory",
"DynamoDBChatMessageHistory",
"ElasticsearchChatMessageHistory"... | langchain/libs/langchain/tests/unit_tests/memory/chat_message_histories/test_imports.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/memory/chat_message_histories/test_imports.py",
"repo_id": "langchain",
"token_count": 323
} | 662 |
.. _Ref-Indices-Empty:
Empty Index
===========
Building the Empty Index
.. automodule:: llama_index.core.indices.empty
:members:
:inherited-members:
:exclude-members: delete, docstore, index_struct, index_struct_cls
| llama_index/docs/api_reference/indices/empty.rst/0 | {
"file_path": "llama_index/docs/api_reference/indices/empty.rst",
"repo_id": "llama_index",
"token_count": 81
} | 1,035 |
from __future__ import annotations
import logging
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
Tuple,
TypeVar,
Union,
)
import numpy as np
from langchain_core.documents import Document
from langchain_core.embeddings import Em... | langchain/libs/community/langchain_community/vectorstores/mongodb_atlas.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/mongodb_atlas.py",
"repo_id": "langchain",
"token_count": 6020
} | 333 |
nodeLinker: node-modules
| chat-langchain/chat-langchain/.yarnrc.yml/0 | {
"file_path": "chat-langchain/chat-langchain/.yarnrc.yml",
"repo_id": "chat-langchain",
"token_count": 8
} | 7 |
import { type ClientOptions, OpenAI as OpenAIClient } from "openai";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { GenerationChunk } from "@langchain/core/outputs";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { type BaseLLMParams, LLM } from "@lang... | langchainjs/libs/langchain-openai/src/legacy.ts/0 | {
"file_path": "langchainjs/libs/langchain-openai/src/legacy.ts",
"repo_id": "langchainjs",
"token_count": 5220
} | 996 |
"""Google Calendar reader."""
import datetime
import os
from typing import Any, List, Optional, Union
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
SCOPES = ["https://www.googleapis.com/auth/calendar.readonly"]
# Copyright 2018 Google LLC
#
# Licensed under the Ap... | llama_index/llama-index-integrations/readers/llama-index-readers-google/llama_index/readers/google/calendar/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-google/llama_index/readers/google/calendar/base.py",
"repo_id": "llama_index",
"token_count": 2049
} | 1,451 |
python_sources()
| llama_index/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/llama_index/indices/managed/llama_cloud/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/indices/llama-index-indices-managed-llama-cloud/llama_index/indices/managed/llama_cloud/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,338 |
python_sources()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-astra/llama_index/vector_stores/astra/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-astra/llama_index/vector_stores/astra/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,510 |
# candle-dinov2
[DINOv2](https://github.com/facebookresearch/dinov2) is a computer vision model.
In this example, it is used as an ImageNet classifier: the model returns the
probability for the image to belong to each of the 1000 ImageNet categories.
## Running some example
```bash
cargo run --example dinov2 --relea... | candle/candle-examples/examples/dinov2/README.md/0 | {
"file_path": "candle/candle-examples/examples/dinov2/README.md",
"repo_id": "candle",
"token_count": 250
} | 48 |
import { expect, test } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import { MozillaReadabilityTransformer } from "../mozilla_readability.js";
test("Test HTML to text transformer", async () => {
const webpageText = `<!DOCTYPE html>
<html>
<head>
<title>🦜️🔗 LangChain</title>
... | langchainjs/libs/langchain-community/src/document_transformers/tests/mozilla_readability.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/document_transformers/tests/mozilla_readability.test.ts",
"repo_id": "langchainjs",
"token_count": 515
} | 1,054 |
from collections.abc import Generator
from unittest.mock import MagicMock, patch
import pytest
from langchain_community.tools.edenai import EdenAiTextModerationTool
tool = EdenAiTextModerationTool(
providers=["openai"], language="en", edenai_api_key="fake_key"
)
@pytest.fixture
def mock_post() -> Generator:
... | langchain/libs/community/tests/unit_tests/tools/eden_ai/test_tools.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/tools/eden_ai/test_tools.py",
"repo_id": "langchain",
"token_count": 1339
} | 406 |
#include "cuda_utils.cuh"
#define BINARY_OP_OUT(TYPENAME, OUT_TYPENAME, FN_NAME, FUNC) \
extern "C" __global__ void FN_NAME( \
const size_t numel, \
const size_t num_dims, \
const size_t *dims_and_strides, \
const TYPENAME *lhs, \
const TYPENAME *rhs, \
OUT_TYPENAME *out \
) { \
const size_... | candle/candle-kernels/src/binary_op_macros.cuh/0 | {
"file_path": "candle/candle-kernels/src/binary_op_macros.cuh",
"repo_id": "candle",
"token_count": 1539
} | 55 |
# Copyright 2024 Stanford University Team and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | diffusers/src/diffusers/schedulers/scheduling_lcm.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_lcm.py",
"repo_id": "diffusers",
"token_count": 13495
} | 272 |
"""Pebblo's safe dataloader is a wrapper for document loaders"""
import logging
import os
import uuid
from http import HTTPStatus
from typing import Any, Dict, Iterator, List
import requests
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
from langchain_... | langchain/libs/community/langchain_community/document_loaders/pebblo.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/pebblo.py",
"repo_id": "langchain",
"token_count": 5010
} | 257 |
package datacoord
import (
"fmt"
"github.com/samber/lo"
"go.uber.org/zap"
"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
"github.com/milvus-io/milvus-proto/go-api/v2/msgpb"
"github.com/milvus-io/milvus/internal/proto/datapb"
"github.com/milvus-io/milvus/pkg/log"
)
type CompactionView interface {
Get... | milvus/internal/datacoord/compaction_view.go/0 | {
"file_path": "milvus/internal/datacoord/compaction_view.go",
"repo_id": "milvus",
"token_count": 2083
} | 1,773 |
package planparserv2
import (
"fmt"
"github.com/antlr/antlr4/runtime/Go/antlr"
"github.com/samber/lo"
"go.uber.org/zap"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/internal/proto/planpb"
"github.com/milvus-io/milvus/pkg/log"
"github.com/milvus-io/milvus/pkg/util/typeut... | milvus/internal/parser/planparserv2/plan_parser_v2.go/0 | {
"file_path": "milvus/internal/parser/planparserv2/plan_parser_v2.go",
"repo_id": "milvus",
"token_count": 2244
} | 1,872 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "vectorstores/cloudflare_vectorize",
newEntrypointName: "",
newPackageName: "@langchain/cloudflare",
});
export * from "@langchain/community/vectorstores/cloudflar... | langchainjs/langchain/src/vectorstores/cloudflare_vectorize.ts/0 | {
"file_path": "langchainjs/langchain/src/vectorstores/cloudflare_vectorize.ts",
"repo_id": "langchainjs",
"token_count": 103
} | 1,031 |
# TensorFlow
This Embeddings integration runs the embeddings entirely in your browser or Node.js environment, using [TensorFlow.js](https://www.tensorflow.org/js). This means that your data isn't sent to any third party, and you don't need to sign up for any API keys. However, it does require more memory and processin... | langchainjs/docs/core_docs/docs/integrations/text_embedding/tensorflow.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/text_embedding/tensorflow.mdx",
"repo_id": "langchainjs",
"token_count": 357
} | 715 |
import { z } from "zod";
import {
zodToJsonSchema,
type JsonSchema7ObjectType,
} from "zod-to-json-schema";
import {
Document,
MappingDocumentTransformer,
} from "@langchain/core/documents";
import { ChatOpenAI } from "@langchain/openai";
import { BaseChain } from "../chains/base.js";
import {
TaggingChainOp... | langchainjs/langchain/src/document_transformers/openai_functions.ts/0 | {
"file_path": "langchainjs/langchain/src/document_transformers/openai_functions.ts",
"repo_id": "langchainjs",
"token_count": 724
} | 928 |
"""Chain for question-answering against a vector database."""
| langchain/libs/langchain/langchain/chains/retrieval_qa/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/retrieval_qa/__init__.py",
"repo_id": "langchain",
"token_count": 15
} | 489 |
# Copyright 2023-present 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 law or... | peft/src/peft/tuners/poly/router.py/0 | {
"file_path": "peft/src/peft/tuners/poly/router.py",
"repo_id": "peft",
"token_count": 1117
} | 351 |
# coding=utf-8
# Copyright 2023 The Kakao Enterprise Authors, the MMS-TTS Authors and the HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# h... | transformers/src/transformers/models/vits/tokenization_vits.py/0 | {
"file_path": "transformers/src/transformers/models/vits/tokenization_vits.py",
"repo_id": "transformers",
"token_count": 3981
} | 749 |
import * as uuid from "uuid";
import {
VectorizeIndex,
VectorizeVectorMetadata,
} from "@cloudflare/workers-types";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { VectorStore } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/documents";
import {
Asy... | langchainjs/libs/langchain-community/src/vectorstores/cloudflare_vectorize.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/cloudflare_vectorize.ts",
"repo_id": "langchainjs",
"token_count": 2531
} | 1,002 |
/// Pretty printing of tensors
/// This implementation should be in line with the PyTorch version.
/// https://github.com/pytorch/pytorch/blob/7b419e8513a024e172eae767e24ec1b849976b13/torch/_tensor_str.py
use crate::{DType, Result, Tensor, WithDType};
use half::{bf16, f16};
impl Tensor {
fn fmt_dt<T: WithDType + s... | candle/candle-core/src/display.rs/0 | {
"file_path": "candle/candle-core/src/display.rs",
"repo_id": "candle",
"token_count": 9501
} | 34 |
# Add DATABASE_URL to .env file in this directory
DATABASE_URL=postgresql://[USERNAME]:[PASSWORD]@[ADDR]/[DBNAME] | langchainjs/examples/src/indexes/vector_stores/prisma_vectorstore/.env.example/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/prisma_vectorstore/.env.example",
"repo_id": "langchainjs",
"token_count": 46
} | 817 |
import argparse
import os
import torch
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import AutoencoderKL, DPMSolverMultistepScheduler, PixArtAlphaPipeline, Transformer2DModel
ckpt_id = "PixArt-alpha/PixArt-alpha"
# https://github.com/PixArt-alpha/PixArt-alpha/blob/0f55e922376d8b797edd44d25d0e... | diffusers/scripts/convert_pixart_alpha_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_pixart_alpha_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 4086
} | 220 |
__version__ = "0.28.0.dev0"
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .inference impo... | accelerate/src/accelerate/__init__.py/0 | {
"file_path": "accelerate/src/accelerate/__init__.py",
"repo_id": "accelerate",
"token_count": 322
} | 12 |
A markdown document with no additional metadata.
| langchainjs/langchain/src/document_loaders/tests/example_data/obsidian/no_metadata.md/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/tests/example_data/obsidian/no_metadata.md",
"repo_id": "langchainjs",
"token_count": 10
} | 920 |
import { describe, expect, test, jest } from "@jest/globals";
import { SQLiteRecordManager } from "../sqlite.js";
describe("SQLiteRecordManager", () => {
const tableName = "upsertion_record";
let recordManager: SQLiteRecordManager;
beforeAll(async () => {
const localPath = ":memory:";
recordManager = ne... | langchainjs/libs/langchain-community/src/indexes/tests/sqlite.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/indexes/tests/sqlite.int.test.ts",
"repo_id": "langchainjs",
"token_count": 2218
} | 956 |
import inspect
from typing import Callable, Dict, List, Optional, Union
import numpy as np
import PIL
import PIL.Image
import torch
from transformers import T5EncoderModel, T5Tokenizer
from ...loaders import LoraLoaderMixin
from ...models import Kandinsky3UNet, VQModel
from ...schedulers import DDPMScheduler
from ...... | diffusers/src/diffusers/pipelines/kandinsky3/pipeline_kandinsky3_img2img.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky3/pipeline_kandinsky3_img2img.py",
"repo_id": "diffusers",
"token_count": 14216
} | 238 |
from pathlib import Path
from langchain.memory import ConversationBufferMemory
from langchain.pydantic_v1 import BaseModel
from langchain_community.chat_models import ChatOllama, ChatOpenAI
from langchain_community.utilities import SQLDatabase
from langchain_core.output_parsers import StrOutputParser
from langchain_co... | langchain/templates/sql-research-assistant/sql_research_assistant/search/sql.py/0 | {
"file_path": "langchain/templates/sql-research-assistant/sql_research_assistant/search/sql.py",
"repo_id": "langchain",
"token_count": 909
} | 711 |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/roc_bert/test_modeling_roc_bert.py/0 | {
"file_path": "transformers/tests/models/roc_bert/test_modeling_roc_bert.py",
"repo_id": "transformers",
"token_count": 13598
} | 786 |
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