text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
import { OpenAI } from "@langchain/openai";
const llm = new OpenAI({
modelName: "gpt-3.5-turbo-instruct",
callbacks: [
{
handleLLMEnd(output) {
console.log(JSON.stringify(output, null, 2));
},
},
],
});
await llm.invoke("Tell me a joke.");
/*
{
"generations": [
[
... | langchainjs/examples/src/models/llm/token_usage_tracking.ts/0 | {
"file_path": "langchainjs/examples/src/models/llm/token_usage_tracking.ts",
"repo_id": "langchainjs",
"token_count": 354
} | 833 |
kind: Namespace
apiVersion: v1
metadata:
name: chroma
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: memberlist-reader
rules:
- apiGroups:
- chroma.cluster
resources:
- memberlists
verbs:
- get
- list
- watch
- create
- update
- patch
- delete
---
apiVersion: rb... | chroma/k8s/dev/setup.yaml/0 | {
"file_path": "chroma/k8s/dev/setup.yaml",
"repo_id": "chroma",
"token_count": 883
} | 54 |
<jupyter_start><jupyter_text>Banana[Banana](https://www.banana.dev/about-us) is focused on building the machine learning infrastructure.This example goes over how to use LangChain to interact with Banana models<jupyter_code># Install the package https://docs.banana.dev/banana-docs/core-concepts/sdks/python
%pip instal... | langchain/docs/docs/integrations/llms/banana.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/banana.ipynb",
"repo_id": "langchain",
"token_count": 417
} | 119 |
# Building Performant RAG Applications for Production
Prototyping a RAG application is easy, but making it performant, robust, and scalable to a large knowledge corpus is hard.
This guide contains a variety of tips and tricks to improve the performance of your RAG pipeline. We first outline
some general techniques - ... | llama_index/docs/optimizing/production_rag.md/0 | {
"file_path": "llama_index/docs/optimizing/production_rag.md",
"repo_id": "llama_index",
"token_count": 1943
} | 1,164 |
import { applyPatch } from "@langchain/core/utils/json_patch";
import { RemoteRunnable } from "../remote.js";
test("streamLog hosted langserve", async () => {
const remote = new RemoteRunnable({
url: `https://chat-langchain-backend.langchain.dev/chat`,
});
const result = await remote.streamLog({
question... | langchainjs/langchain/src/runnables/tests/runnable_remote.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/runnables/tests/runnable_remote.int.test.ts",
"repo_id": "langchainjs",
"token_count": 267
} | 921 |
python_tests(
interpreter_constraints=["==3.9.*", "==3.10.*"],
)
| llama_index/llama-index-integrations/readers/llama-index-readers-agent-search/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-agent-search/tests/BUILD",
"repo_id": "llama_index",
"token_count": 29
} | 1,325 |
from llama_index.core.tools.tool_spec.base import BaseToolSpec
from llama_index.tools.vector_db import VectorDBToolSpec
def test_class():
names_of_base_classes = [b.__name__ for b in VectorDBToolSpec.__mro__]
assert BaseToolSpec.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/tools/llama-index-tools-vector-db/tests/test_tools_vector_db.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-vector-db/tests/test_tools_vector_db.py",
"repo_id": "llama_index",
"token_count": 95
} | 1,505 |
import random
import time
import random
import string
from faker import Faker
import numpy as np
from sklearn import preprocessing
import requests
from loguru import logger
import datetime
fake = Faker()
def random_string(length=8):
letters = string.ascii_letters
return ''.join(random.choice(letters) for _ i... | milvus/tests/restful_client/utils/utils.py/0 | {
"file_path": "milvus/tests/restful_client/utils/utils.py",
"repo_id": "milvus",
"token_count": 2053
} | 1,906 |
from llama_index.readers.reddit.base import RedditReader
__all__ = ["RedditReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-reddit/llama_index/readers/reddit/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-reddit/llama_index/readers/reddit/__init__.py",
"repo_id": "llama_index",
"token_count": 26
} | 1,545 |
<jupyter_start><jupyter_text>Recursive Retriever + Node References + BraintrustThis guide shows how you can use recursive retrieval to traverse node relationships and fetch nodes based on "references".Node references are a powerful concept. When you first perform retrieval, you may want to retrieve the reference as opp... | llama_index/docs/examples/retrievers/recurisve_retriever_nodes_braintrust.ipynb/0 | {
"file_path": "llama_index/docs/examples/retrievers/recurisve_retriever_nodes_braintrust.ipynb",
"repo_id": "llama_index",
"token_count": 4676
} | 1,131 |
"""Azblob file and directory reader.
A loader that fetches a file or iterates through a directory on Azblob or.
"""
from typing import Dict, List, Optional, Union
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
from llama_index.readers.opendal.base import OpendalRea... | llama_index/llama-index-integrations/readers/llama-index-readers-opendal/llama_index/readers/opendal/azblob/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-opendal/llama_index/readers/opendal/azblob/base.py",
"repo_id": "llama_index",
"token_count": 884
} | 1,397 |
package etcdkv
import (
"testing"
"github.com/stretchr/testify/suite"
"github.com/milvus-io/milvus/internal/kv/predicates"
)
type EtcdKVUtilSuite struct {
suite.Suite
}
func (s *EtcdKVUtilSuite) TestParsePredicateType() {
type testCase struct {
tag string
pt predicates.PredicateType
... | milvus/internal/kv/etcd/util_test.go/0 | {
"file_path": "milvus/internal/kv/etcd/util_test.go",
"repo_id": "milvus",
"token_count": 729
} | 1,806 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.linear import LinearReader
def test_class():
names_of_base_classes = [b.__name__ for b in LinearReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-linear/tests/test_readers_linear.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-linear/tests/test_readers_linear.py",
"repo_id": "llama_index",
"token_count": 85
} | 1,329 |
from __future__ import annotations
import contextlib
import enum
import logging
import uuid
from typing import (
Any,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
Tuple,
Type,
Union,
)
import numpy as np
import sqlalchemy
from sqlalchemy import delete, func
from sqlalch... | langchain/libs/community/langchain_community/vectorstores/lantern.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/lantern.py",
"repo_id": "langchain",
"token_count": 17112
} | 326 |
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
... | candle/candle-core/LICENSE/0 | {
"file_path": "candle/candle-core/LICENSE",
"repo_id": "candle",
"token_count": 3168
} | 35 |
from typing import Dict, List
from uuid import UUID
from langchain.callbacks.tracers.base import BaseTracer
from langsmith.schemas import Run
class FakeTracer(BaseTracer):
"""Fake tracer that records LangChain execution.
It replaces run ids with deterministic UUIDs."""
def __init__(self) -> None:
... | langserve/tests/unit_tests/utils/tracer.py/0 | {
"file_path": "langserve/tests/unit_tests/utils/tracer.py",
"repo_id": "langserve",
"token_count": 702
} | 1,054 |
from llama_index.callbacks.argilla.base import argilla_callback_handler
__all__ = ["argilla_callback_handler"]
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-argilla/llama_index/callbacks/argilla/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-argilla/llama_index/callbacks/argilla/__init__.py",
"repo_id": "llama_index",
"token_count": 35
} | 1,208 |
# coding=utf-8
# Copyright 2019 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | transformers/tests/test_configuration_utils.py/0 | {
"file_path": "transformers/tests/test_configuration_utils.py",
"repo_id": "transformers",
"token_count": 5459
} | 845 |
document.addEventListener("DOMContentLoaded", () => {
// Load the external dependencies
function loadScript(src, onLoadCallback) {
const script = document.createElement("script");
script.src = src;
script.onload = onLoadCallback;
document.head.appendChild(script);
}
function createRootElement()... | llama_index/docs/_static/js/mendablesearch.js/0 | {
"file_path": "llama_index/docs/_static/js/mendablesearch.js",
"repo_id": "llama_index",
"token_count": 795
} | 1,078 |
# Validates training data and estimates token usage
# Copied from https://platform.openai.com/docs/guides/fine-tuning/preparing-your-dataset
# Usage:
# python validate_json.py <path_to_jsonl_file>
# We start by importing the required packages
import json
import os
import sys
from collections import defaultdict
from... | llama_index/llama-index-legacy/llama_index/legacy/finetuning/openai/validate_json.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/finetuning/openai/validate_json.py",
"repo_id": "llama_index",
"token_count": 2760
} | 1,594 |
<jupyter_start><jupyter_text>Unit 5: An Introduction to ML-Agents In this notebook, you'll learn about ML-Agents and train two agents.- The first one will learn to **shoot snowballs onto spawning targets**.- The second need to press a button to spawn a pyramid, then navigate to the pyramid, knock it over, **and move to... | deep-rl-class/notebooks/unit5/unit5.ipynb/0 | {
"file_path": "deep-rl-class/notebooks/unit5/unit5.ipynb",
"repo_id": "deep-rl-class",
"token_count": 4123
} | 148 |
use tokenizers::models::bpe::{BpeTrainerBuilder, BPE};
use tokenizers::normalizers::{Sequence, Strip, NFC};
use tokenizers::pre_tokenizers::byte_level::ByteLevel;
use tokenizers::{AddedToken, TokenizerBuilder};
use tokenizers::{DecoderWrapper, NormalizerWrapper, PostProcessorWrapper, PreTokenizerWrapper};
use tokenizer... | tokenizers/tokenizers/tests/documentation.rs/0 | {
"file_path": "tokenizers/tokenizers/tests/documentation.rs",
"repo_id": "tokenizers",
"token_count": 7402
} | 483 |
from ._builder import *
from ._helpers import *
from ._manipulate import *
from ._prune import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", DeprecationWarning)
| pytorch-image-models/timm/models/helpers.py/0 | {
"file_path": "pytorch-image-models/timm/models/helpers.py",
"repo_id": "pytorch-image-models",
"token_count": 64
} | 373 |
<jupyter_start><jupyter_text>Fine Tuning Llama2 for Better Structured Outputs With Gradient and LlamaIndexIn this notebook we show you how to fine-tune llama2-7b to be better at outputting structured outputs.We do this by using [gradient.ai](https://gradient.ai)This is similar in format to our [OpenAI Functions Fine-tu... | llama_index/docs/examples/finetuning/gradient/gradient_structured.ipynb/0 | {
"file_path": "llama_index/docs/examples/finetuning/gradient/gradient_structured.ipynb",
"repo_id": "llama_index",
"token_count": 5479
} | 1,186 |
from langchain_community.graphs.neo4j_graph import Neo4jGraph
SCHEMA_QUERY = """
CALL llm_util.schema("raw")
YIELD *
RETURN *
"""
class MemgraphGraph(Neo4jGraph):
"""Memgraph wrapper for graph operations.
*Security note*: Make sure that the database connection uses credentials
that are narrowly-scop... | langchain/libs/community/langchain_community/graphs/memgraph_graph.py/0 | {
"file_path": "langchain/libs/community/langchain_community/graphs/memgraph_graph.py",
"repo_id": "langchain",
"token_count": 1055
} | 275 |
---
sidebar_position: 1
sidebar_class_name: hidden
---
# Retrieval
Many LLM applications require user-specific data that is not part of the model's training set.
The primary way of accomplishing this is through Retrieval Augmented Generation (RAG).
In this process, external data is *retrieved* and then passed to the ... | langchain/docs/docs/modules/data_connection/index.mdx/0 | {
"file_path": "langchain/docs/docs/modules/data_connection/index.mdx",
"repo_id": "langchain",
"token_count": 1051
} | 186 |
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ja/main_classes/deepspeed.md/0 | {
"file_path": "transformers/docs/source/ja/main_classes/deepspeed.md",
"repo_id": "transformers",
"token_count": 49392
} | 511 |
from llama_index.vector_stores.lancedb.base import LanceDBVectorStore
__all__ = ["LanceDBVectorStore"]
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-lancedb/llama_index/vector_stores/lancedb/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-lancedb/llama_index/vector_stores/lancedb/__init__.py",
"repo_id": "llama_index",
"token_count": 34
} | 1,659 |
import { PromptTemplate } from "@langchain/core/prompts";
import { RunnableMap } from "@langchain/core/runnables";
import { ChatAnthropic } from "@langchain/anthropic";
const model = new ChatAnthropic({});
const jokeChain = PromptTemplate.fromTemplate(
"Tell me a joke about {topic}"
).pipe(model);
const poemChain = ... | langchainjs/examples/src/guides/expression_language/runnable_maps_basic.ts/0 | {
"file_path": "langchainjs/examples/src/guides/expression_language/runnable_maps_basic.ts",
"repo_id": "langchainjs",
"token_count": 390
} | 868 |
# 🦜️🏓 LangServe
[](https://github.com/langchain-ai/langserve/releases)
[](https://pepy.tech/project/langserve)
[![Open Issues](https://img.shields.io/github/issues-raw/langchain-a... | langserve/README.md/0 | {
"file_path": "langserve/README.md",
"repo_id": "langserve",
"token_count": 14915
} | 1,007 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 563,
"logprob": null,
"text": "def"
},
{
"id": 942,
"logprob": -5.1367188,
"text": " print... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_santacoder/test_flash_santacoder_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_santacoder/test_flash_santacoder_load.json",
"repo_id": "text-generation-inference",
"token_count": 5188
} | 407 |
python_sources()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-upstash/llama_index/vector_stores/upstash/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-upstash/llama_index/vector_stores/upstash/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,540 |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a cop... | transformers/src/transformers/data/processors/xnli.py/0 | {
"file_path": "transformers/src/transformers/data/processors/xnli.py",
"repo_id": "transformers",
"token_count": 1505
} | 620 |
from typing import Any, Dict
from llama_index.legacy.embeddings import (
HuggingFaceEmbedding,
OpenAIEmbedding,
)
from llama_index.legacy.embeddings.utils import resolve_embed_model
from llama_index.legacy.token_counter.mock_embed_model import MockEmbedding
from pytest import MonkeyPatch
def mock_hf_embeddin... | llama_index/llama-index-legacy/tests/embeddings/test_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/embeddings/test_utils.py",
"repo_id": "llama_index",
"token_count": 529
} | 1,731 |
import json
import hashlib
class Hardware:
"""
{
"_version": "0.1",
"_type": "hardware",
"name": string,
"cpus": float
}
"""
def __init__(self, name=None, cpus=0.0):
self._version = '0.1'
self._type = 'hardware'
self.name = name
sel... | milvus/tests/benchmark/milvus_benchmark/metrics/models/hardware.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/metrics/models/hardware.py",
"repo_id": "milvus",
"token_count": 243
} | 2,078 |
/* eslint-disable @typescript-eslint/no-explicit-any */
import weaviate, { ApiKey } from "weaviate-ts-client";
import { WeaviateStore } from "@langchain/weaviate";
import { OpenAIEmbeddings } from "@langchain/openai";
export async function run() {
// Something wrong with the weaviate-ts-client types, so we need to d... | langchainjs/examples/src/indexes/vector_stores/weaviate_search.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/weaviate_search.ts",
"repo_id": "langchainjs",
"token_count": 502
} | 825 |
from llama_index.core.base.response.schema import Response
__all__ = ["Response"]
| llama_index/llama-index-core/llama_index/core/response/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/response/__init__.py",
"repo_id": "llama_index",
"token_count": 26
} | 1,215 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "llms/cloudflare_workersai",
newEntrypointName: "",
newPackageName: "@langchain/cloudflare",
});
export * from "@langchain/community/llms/cloudflare_workersai";
| langchainjs/langchain/src/llms/cloudflare_workersai.ts/0 | {
"file_path": "langchainjs/langchain/src/llms/cloudflare_workersai.ts",
"repo_id": "langchainjs",
"token_count": 103
} | 929 |
<jupyter_start><jupyter_text>Données massives ? 🤗 Datasets à la rescousse ! Installez les bibliothèques 🤗 Transformers et 🤗 Datasets pour exécuter ce *notebook*.<jupyter_code>!pip install datasets evaluate transformers[sentencepiece]
!pip install zstandard
from datasets import load_dataset
# Cela prend quelques min... | notebooks/course/fr/chapter5/section4.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter5/section4.ipynb",
"repo_id": "notebooks",
"token_count": 1168
} | 312 |
from langchain import embeddings
from tests.unit_tests import assert_all_importable
EXPECTED_ALL = [
"OpenAIEmbeddings",
"AzureOpenAIEmbeddings",
"CacheBackedEmbeddings",
"ClarifaiEmbeddings",
"CohereEmbeddings",
"DatabricksEmbeddings",
"ElasticsearchEmbeddings",
"FastEmbedEmbeddings",
... | langchain/libs/langchain/tests/unit_tests/embeddings/test_imports.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/embeddings/test_imports.py",
"repo_id": "langchain",
"token_count": 759
} | 623 |
import logging
from .helm import HelmEnv
from .docker import DockerEnv
from .local import LocalEnv
logger = logging.getLogger("milvus_benchmark.env")
def get_env(env_mode, deploy_mode=None):
return {
"helm": HelmEnv(deploy_mode),
"docker": DockerEnv(None),
"local": LocalEnv(None),
}.g... | milvus/tests/benchmark/milvus_benchmark/env/__init__.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/env/__init__.py",
"repo_id": "milvus",
"token_count": 136
} | 1,957 |
from llama_index.core.data_structs.data_structs import IndexGraph
from llama_index.core.storage.index_store.simple_index_store import (
SimpleIndexStore,
)
def test_simple_index_store_dict() -> None:
index_struct = IndexGraph()
index_store = SimpleIndexStore()
index_store.add_index_struct(index_struct... | llama_index/llama-index-core/tests/storage/index_store/test_simple_index_store.py/0 | {
"file_path": "llama_index/llama-index-core/tests/storage/index_store/test_simple_index_store.py",
"repo_id": "llama_index",
"token_count": 195
} | 1,170 |
from threading import Lock
from chromadb.segment import (
SegmentImplementation,
SegmentManager,
MetadataReader,
SegmentType,
VectorReader,
S,
)
from chromadb.config import System, get_class
from chromadb.db.system import SysDB
from overrides import override
from chromadb.segment.distributed imp... | chroma/chromadb/segment/impl/manager/distributed.py/0 | {
"file_path": "chroma/chromadb/segment/impl/manager/distributed.py",
"repo_id": "chroma",
"token_count": 3064
} | 22 |
export {
calculateMaxTokens,
getModelContextSize,
getEmbeddingContextSize,
} from "@langchain/core/language_models/base";
| langchainjs/langchain/src/base_language/count_tokens.ts/0 | {
"file_path": "langchainjs/langchain/src/base_language/count_tokens.ts",
"repo_id": "langchainjs",
"token_count": 40
} | 900 |
from llama_index.core.tools.tool_spec.base import BaseToolSpec
from llama_index.tools.zapier import ZapierToolSpec
def test_class():
names_of_base_classes = [b.__name__ for b in ZapierToolSpec.__mro__]
assert BaseToolSpec.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/tools/llama-index-tools-zapier/tests/test_tools_zapier.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-zapier/tests/test_tools_zapier.py",
"repo_id": "llama_index",
"token_count": 95
} | 1,645 |
// 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/job/job_release.go/0 | {
"file_path": "milvus/internal/querycoordv2/job/job_release.go",
"repo_id": "milvus",
"token_count": 2548
} | 1,829 |
import logging
import re
from typing import TYPE_CHECKING, Any, List, Optional, Pattern
import numpy as np
_logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from redis.client import Redis as RedisType
from redis.commands.search.query import Query
class TokenEscaper:
"""
Escape punctuation wit... | llama_index/llama-index-legacy/llama_index/legacy/readers/redis/utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/redis/utils.py",
"repo_id": "llama_index",
"token_count": 1390
} | 1,610 |
from llama_index.tools.playgrounds.subgraph_connector.base import (
PlaygroundsSubgraphConnectorToolSpec,
)
from llama_index.tools.playgrounds.subgraph_inspector.base import (
PlaygroundsSubgraphInspectorToolSpec,
)
__all__ = [
"PlaygroundsSubgraphConnectorToolSpec",
"PlaygroundsSubgraphInspectorToolSp... | llama_index/llama-index-integrations/tools/llama-index-tools-playgrounds/llama_index/tools/playgrounds/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-playgrounds/llama_index/tools/playgrounds/__init__.py",
"repo_id": "llama_index",
"token_count": 110
} | 1,522 |
import os
import logging
import pdb
import time
import random
from multiprocessing import Process
import numpy as np
from client import MilvusClient
import utils
import parser
from runner import Runner
logger = logging.getLogger("milvus_benchmark.docker")
class DockerRunner(Runner):
"""run docker mode"""
def... | milvus/tests/benchmark/milvus_benchmark/runners/docker_runner.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/runners/docker_runner.py",
"repo_id": "milvus",
"token_count": 12562
} | 1,992 |
/* eslint-disable no-process-env */
/* eslint-disable @typescript-eslint/no-non-null-assertion */
import { test } from "@jest/globals";
import { HumanMessage } from "@langchain/core/messages";
import { OllamaFunctions } from "../ollama_functions.js";
test.skip("Test OllamaFunctions", async () => {
const chat = new O... | langchainjs/langchain/src/experimental/chat_models/tests/ollama_functions.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/experimental/chat_models/tests/ollama_functions.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1056
} | 895 |
python_sources()
| llama_index/llama-index-cli/llama_index/cli/new_package/BUILD/0 | {
"file_path": "llama_index/llama-index-cli/llama_index/cli/new_package/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,107 |
<jupyter_start><jupyter_text>MarkdownHeaderTextSplitter MotivationMany chat or Q+A applications involve chunking input documents prior to embedding and vector storage.[These notes](https://www.pinecone.io/learn/chunking-strategies/) from Pinecone provide some useful tips:```When a full paragraph or document is embedded... | langchain/docs/docs/modules/data_connection/document_transformers/markdown_header_metadata.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/data_connection/document_transformers/markdown_header_metadata.ipynb",
"repo_id": "langchain",
"token_count": 1207
} | 189 |
# 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 to in writing, software
# distributed under th... | transformers/src/transformers/data/metrics/__init__.py/0 | {
"file_path": "transformers/src/transformers/data/metrics/__init__.py",
"repo_id": "transformers",
"token_count": 1413
} | 593 |
pub mod audio;
pub mod model;
pub mod quantized_model;
use serde::Deserialize;
// The names in comments correspond to the original implementation:
// https://github.com/openai/whisper/blob/f572f2161ba831bae131364c3bffdead7af6d210/whisper/model.py#L17
#[derive(Debug, Clone, PartialEq, Deserialize)]
pub struct Config {... | candle/candle-transformers/src/models/whisper/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/whisper/mod.rs",
"repo_id": "candle",
"token_count": 812
} | 77 |
python_tests()
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-tencentvectordb/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-tencentvectordb/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,542 |
package model
import (
"testing"
"github.com/stretchr/testify/assert"
"github.com/milvus-io/milvus/internal/proto/internalpb"
)
var (
credentialModel = &Credential{
Username: "user",
EncryptedPassword: "password",
Tenant: "tenant-1",
IsSuper: true,
Sha256Password: "xxx... | milvus/internal/metastore/model/credential_test.go/0 | {
"file_path": "milvus/internal/metastore/model/credential_test.go",
"repo_id": "milvus",
"token_count": 329
} | 1,721 |
"""Keyword-table based index.
Similar to a "hash table" in concept. LlamaIndex first tries
to extract keywords from the source text, and stores the
keywords as keys per item. It similarly extracts keywords
from the query text. Then, it tries to match those keywords to
existing keywords in the table.
"""
from abc imp... | llama_index/llama-index-core/llama_index/core/indices/keyword_table/base.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/keyword_table/base.py",
"repo_id": "llama_index",
"token_count": 3945
} | 1,192 |
"""Code for generic / auxiliary parsers.
This module contains some logic to help assemble more sophisticated parsers.
"""
from typing import Iterator, Mapping, Optional
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseBlobParser
from langchain_community.document... | langchain/libs/community/langchain_community/document_loaders/parsers/generic.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/generic.py",
"repo_id": "langchain",
"token_count": 1064
} | 242 |
import os
import re
import time
from enum import Enum
from typing import List, Optional
import requests
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
class BlockchainType(Enum):
"""Enumerator of the supported blockchains."""
ETH_MAINNET = "et... | langchain/libs/community/langchain_community/document_loaders/blockchain.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/blockchain.py",
"repo_id": "langchain",
"token_count": 2518
} | 233 |
import { test } from "@jest/globals";
import { HumanMessage, AIMessage } from "@langchain/core/messages";
import {
PromptTemplate,
ChatPromptTemplate,
AIMessagePromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
} from "@langchain/core/prompts";
import { ChatGooglePaLM } from "../googlepa... | langchainjs/libs/langchain-community/src/chat_models/tests/chatgooglepalm.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/chat_models/tests/chatgooglepalm.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1022
} | 938 |
import { zodToJsonSchema, JsonSchema7ObjectType } from "zod-to-json-schema";
import type { StructuredToolInterface } from "@langchain/core/tools";
import type {
BaseLanguageModel,
BaseLanguageModelInterface,
} from "@langchain/core/language_models/base";
import {
RunnablePassthrough,
RunnableSequence,
} from "@... | langchainjs/langchain/src/agents/structured_chat/index.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/structured_chat/index.ts",
"repo_id": "langchainjs",
"token_count": 3723
} | 879 |
python_sources()
| llama_index/llama-index-integrations/tools/llama-index-tools-neo4j/llama_index/tools/neo4j/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-neo4j/llama_index/tools/neo4j/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,490 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "embeddings/hf",
});
export * from "@langchain/community/embeddings/hf";
| langchainjs/langchain/src/embeddings/hf.ts/0 | {
"file_path": "langchainjs/langchain/src/embeddings/hf.ts",
"repo_id": "langchainjs",
"token_count": 74
} | 914 |
<jupyter_start><jupyter_text>Notion DB 2/2>[Notion](https://www.notion.so/) is a collaboration platform with modified Markdown support that integrates kanban boards, tasks, wikis and databases. It is an all-in-one workspace for notetaking, knowledge and data management, and project and task management.`NotionDBLoader` ... | langchain/docs/docs/integrations/document_loaders/notiondb.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/notiondb.ipynb",
"repo_id": "langchain",
"token_count": 833
} | 108 |
from __future__ import annotations
import logging
import os
import warnings
from typing import (
Any,
Callable,
Dict,
List,
Literal,
Mapping,
Optional,
Sequence,
Set,
Tuple,
Union,
cast,
)
import numpy as np
from langchain_core._api.deprecation import deprecated
from la... | langchain/libs/community/langchain_community/embeddings/openai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/embeddings/openai.py",
"repo_id": "langchain",
"token_count": 13407
} | 270 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-couchbase/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-couchbase/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,334 |
import {
APIResponseError,
Client,
isFullBlock,
isFullPage,
iteratePaginatedAPI,
APIErrorCode,
isNotionClientError,
isFullDatabase,
} from "@notionhq/client";
import { NotionToMarkdown } from "notion-to-md";
import { getBlockChildren } from "notion-to-md/build/utils/notion.js";
import type {
ListBlock... | langchainjs/langchain/src/document_loaders/web/notionapi.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/web/notionapi.ts",
"repo_id": "langchainjs",
"token_count": 5518
} | 913 |
# coding=utf-8
# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.
#
# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
# and OPT implementations in this library. It has been modified from its
# original forms to accommodate minor architectural differences compared
# to G... | transformers/src/transformers/models/llama/tokenization_llama.py/0 | {
"file_path": "transformers/src/transformers/models/llama/tokenization_llama.py",
"repo_id": "transformers",
"token_count": 9293
} | 658 |
[tool.poetry]
name = "rag-aws-bedrock"
version = "0.1.0"
description = "RAG using AWS Bedrock"
authors = [
"Lance Martin <lance@langchain.dev>",
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
tiktoken = ">=0.5.1"
faiss-cpu = ">=1.7.4"
boto3 = ">=1.28.57"
awscli = ">=1.... | langchain/templates/rag-aws-bedrock/pyproject.toml/0 | {
"file_path": "langchain/templates/rag-aws-bedrock/pyproject.toml",
"repo_id": "langchain",
"token_count": 312
} | 681 |
"""Test toolkit integration."""
from langchain_robocorp.toolkits import ActionServerToolkit
from ._fixtures import FakeChatLLMT
def test_initialization() -> None:
"""Test toolkit initialization."""
ActionServerToolkit(url="http://localhost", llm=FakeChatLLMT())
| langchain/libs/partners/robocorp/tests/unit_tests/test_toolkits.py/0 | {
"file_path": "langchain/libs/partners/robocorp/tests/unit_tests/test_toolkits.py",
"repo_id": "langchain",
"token_count": 81
} | 699 |
<jupyter_start><jupyter_text>OpenAI FunctionsThese output parsers use OpenAI function calling to structure its outputs. This means they are only usable with models that support function calling. There are a few different variants:- JsonOutputFunctionsParser: Returns the arguments of the function call as JSON- PydanticO... | langchain/docs/docs/modules/model_io/output_parsers/types/openai_functions.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/model_io/output_parsers/types/openai_functions.ipynb",
"repo_id": "langchain",
"token_count": 1623
} | 198 |
from openai_functions_agent.agent import agent_executor
if __name__ == "__main__":
question = (
"Write a draft response to LangChain's last email. "
"First do background research on the sender and topics to make sure you"
" understand the context, then write the draft."
)
print(agen... | langchain/templates/openai-functions-agent-gmail/main.py/0 | {
"file_path": "langchain/templates/openai-functions-agent-gmail/main.py",
"repo_id": "langchain",
"token_count": 135
} | 718 |
from __future__ import annotations
from typing import Any, Dict, Iterator, List, Optional
from langchain_core._api.deprecation import deprecated
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models import LanguageModelInput
from langchain_core.outputs import Generation, Ge... | langchain/libs/community/langchain_community/llms/google_palm.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/google_palm.py",
"repo_id": "langchain",
"token_count": 3950
} | 267 |
# Common environment variables
locals {
voyager_vars = var.voyage_ai_model != "" && var.voyage_api_key != "" ? {
VOYAGE_AI_MODEL = var.voyage_ai_model
VOYAGE_API_KEY = var.voyage_api_key
} : {}
env_vars = merge(local.voyager_vars, {
OPENAI_API_KEY = var.openai_api_key
WEAVIATE_URL =... | chat-langchain/terraform/modules/chat_langchain_backend/main.tf/0 | {
"file_path": "chat-langchain/terraform/modules/chat_langchain_backend/main.tf",
"repo_id": "chat-langchain",
"token_count": 1967
} | 12 |
from typing import List, Optional
from fastapi import FastAPI
from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
def instrument_fastapi(app: FastAPI, excluded_urls: Optional[List[str]] = None) -> None:
"""Instrument FastAPI to emit OpenTelemetry spans."""
FastAPIInstrumentor.instrument_app(... | chroma/chromadb/telemetry/opentelemetry/fastapi.py/0 | {
"file_path": "chroma/chromadb/telemetry/opentelemetry/fastapi.py",
"repo_id": "chroma",
"token_count": 132
} | 24 |
import { test, expect } from "@jest/globals";
import { HuggingFaceTransformersEmbeddings } from "../hf_transformers.js";
import { HNSWLib } from "../../vectorstores/hnswlib.js";
test("HuggingFaceTransformersEmbeddings", async () => {
const embeddings = new HuggingFaceTransformersEmbeddings();
const texts = [
... | langchainjs/libs/langchain-community/src/embeddings/tests/hf_transformers.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/embeddings/tests/hf_transformers.int.test.ts",
"repo_id": "langchainjs",
"token_count": 375
} | 997 |
from langchain_exa import __all__
EXPECTED_ALL = [
"ExaSearchResults",
"ExaSearchRetriever",
"HighlightsContentsOptions",
"TextContentsOptions",
"ExaFindSimilarResults",
]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
| langchain/libs/partners/exa/tests/unit_tests/test_imports.py/0 | {
"file_path": "langchain/libs/partners/exa/tests/unit_tests/test_imports.py",
"repo_id": "langchain",
"token_count": 107
} | 643 |
"""Composable graph."""
# TODO: remove this file, only keep for backwards compatibility
from llama_index.core.indices.composability.graph import ComposableGraph # noqa
| llama_index/llama-index-core/llama_index/core/composability/base.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/composability/base.py",
"repo_id": "llama_index",
"token_count": 48
} | 1,141 |
python_tests()
| llama_index/llama-index-packs/llama-index-packs-resume-screener/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-resume-screener/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,814 |
[tool.poetry]
name = "langserve"
version = "0.0.41"
description = ""
readme = "README.md"
authors = ["LangChain"]
license = "LangServe"
repository = "https://github.com/langchain-ai/langserve"
exclude = ["langserve/playground"]
include = ["langserve/playground/dist/**/*"]
[tool.poetry.dependencies]
python = "^3.8.1"
h... | langserve/pyproject.toml/0 | {
"file_path": "langserve/pyproject.toml",
"repo_id": "langserve",
"token_count": 1092
} | 1,006 |
import { Chroma } from "@langchain/community/vectorstores/chroma";
import { OpenAIEmbeddings } from "@langchain/openai";
// text sample from Godel, Escher, Bach
const vectorStore = await Chroma.fromTexts(
[
`Tortoise: Labyrinth? Labyrinth? Could it Are we in the notorious Little
Harmonic Labyrinth of the... | langchainjs/examples/src/indexes/vector_stores/chroma/fromTexts.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/chroma/fromTexts.ts",
"repo_id": "langchainjs",
"token_count": 508
} | 811 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/using-diffusers/ip_adapter.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/ip_adapter.md",
"repo_id": "diffusers",
"token_count": 7790
} | 195 |
# 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_swin_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/deta/convert_deta_swin_to_pytorch.py",
"repo_id": "transformers",
"token_count": 8242
} | 595 |
import adapter from "@sveltejs/adapter-node";
import { vitePreprocess } from "@sveltejs/kit/vite";
import dotenv from "dotenv";
dotenv.config({ path: "./.env.local" });
dotenv.config({ path: "./.env" });
process.env.PUBLIC_VERSION = process.env.npm_package_version;
/** @type {import('@sveltejs/kit').Config} */
const... | chat-ui/svelte.config.js/0 | {
"file_path": "chat-ui/svelte.config.js",
"repo_id": "chat-ui",
"token_count": 253
} | 105 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import ChunkPipeline, build_pipeline_init_args
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_av... | transformers/src/transformers/pipelines/zero_shot_object_detection.py/0 | {
"file_path": "transformers/src/transformers/pipelines/zero_shot_object_detection.py",
"repo_id": "transformers",
"token_count": 4201
} | 709 |
from langchain_community.vectorstores.matching_engine import MatchingEngine
__all__ = ["MatchingEngine"]
| langchain/libs/langchain/langchain/vectorstores/matching_engine.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/matching_engine.py",
"repo_id": "langchain",
"token_count": 29
} | 628 |
"""Sleep tool."""
| langchain/libs/community/langchain_community/tools/sleep/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/sleep/__init__.py",
"repo_id": "langchain",
"token_count": 6
} | 309 |
# coding=utf-8
# 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 requir... | transformers/tests/models/albert/test_modeling_tf_albert.py/0 | {
"file_path": "transformers/tests/models/albert/test_modeling_tf_albert.py",
"repo_id": "transformers",
"token_count": 5940
} | 781 |
#![allow(dead_code)]
// https://huggingface.co/facebook/musicgen-small/tree/main
// https://github.com/huggingface/transformers/blob/cd4584e3c809bb9e1392ccd3fe38b40daba5519a/src/transformers/models/musicgen/modeling_musicgen.py
// TODO: Add an offline mode.
// TODO: Add a KV cache.
#[cfg(feature = "mkl")]
extern crate... | candle/candle-examples/examples/musicgen/main.rs/0 | {
"file_path": "candle/candle-examples/examples/musicgen/main.rs",
"repo_id": "candle",
"token_count": 1164
} | 40 |
# SWSL ResNet
**Residual Networks**, or **ResNets**, learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. Instead of hoping each few stacked layers directly fit a desired underlying mapping, residual nets let these layers fit a residual mapping. They stack [residual ... | pytorch-image-models/docs/models/.templates/models/swsl-resnet.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/swsl-resnet.md",
"repo_id": "pytorch-image-models",
"token_count": 1630
} | 348 |
# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class DPMSolverSDEScheduler(metaclass=DummyObject):
_backends = ["torch", "torchsde"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "torchsde"])
... | diffusers/src/diffusers/utils/dummy_torch_and_torchsde_objects.py/0 | {
"file_path": "diffusers/src/diffusers/utils/dummy_torch_and_torchsde_objects.py",
"repo_id": "diffusers",
"token_count": 224
} | 266 |
import { OpenAIEmbeddings } from "@langchain/openai";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { InMemoryStore } from "langchain/storage/in_memory";
import { ParentDocumentRetriever } from "langchain/retrievers/parent_document";
import { RecursiveCharacterTextSplitter } from "langchain/... | langchainjs/examples/src/retrievers/parent_document_retriever_score_threshold.ts/0 | {
"file_path": "langchainjs/examples/src/retrievers/parent_document_retriever_score_threshold.ts",
"repo_id": "langchainjs",
"token_count": 643
} | 862 |
python_sources()
| llama_index/llama-index-integrations/llms/llama-index-llms-dashscope/llama_index/llms/dashscope/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-dashscope/llama_index/llms/dashscope/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,253 |
# coding=utf-8
# 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 requir... | transformers/tests/models/longformer/test_modeling_longformer.py/0 | {
"file_path": "transformers/tests/models/longformer/test_modeling_longformer.py",
"repo_id": "transformers",
"token_count": 15408
} | 822 |
## How to release
# Before the release
Simple checklist on how to make releases for `tokenizers`.
- Freeze `master` branch.
- Run all tests (Check CI has properly run)
- If any significant work, check benchmarks:
- `cd tokenizers && cargo bench` (needs to be run on latest release tag to measure difference if it's ... | tokenizers/RELEASE.md/0 | {
"file_path": "tokenizers/RELEASE.md",
"repo_id": "tokenizers",
"token_count": 1519
} | 430 |
import { logVersion010MigrationWarning } from "../../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "llms/bedrock/web",
});
export * from "@langchain/community/llms/bedrock/web";
| langchainjs/langchain/src/llms/bedrock/web.ts/0 | {
"file_path": "langchainjs/langchain/src/llms/bedrock/web.ts",
"repo_id": "langchainjs",
"token_count": 77
} | 943 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/api/pipelines/ddim.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/ddim.md",
"repo_id": "diffusers",
"token_count": 477
} | 172 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/pkg/util/paramtable/param_item.go/0 | {
"file_path": "milvus/pkg/util/paramtable/param_item.go",
"repo_id": "milvus",
"token_count": 2119
} | 1,922 |
use candle::{
quantized::{self, k_quants, GgmlDType, GgmlType},
test_utils::to_vec2_round,
Device, Module, Result, Tensor,
};
use wasm_bindgen_test::*;
wasm_bindgen_test_configure!(run_in_browser);
#[wasm_bindgen_test]
fn quantized_matmul_neg() -> Result<()> {
let cpu = &Device::Cpu;
let (m, k, n)... | candle/candle-wasm-tests/tests/quantized_tests.rs/0 | {
"file_path": "candle/candle-wasm-tests/tests/quantized_tests.rs",
"repo_id": "candle",
"token_count": 3145
} | 87 |
from __future__ import annotations
from typing import List, Optional
import aiohttp
import requests
from langchain_core.callbacks import (
AsyncCallbackManagerForRetrieverRun,
CallbackManagerForRetrieverRun,
)
from langchain_core.documents import Document
from langchain_core.retrievers import BaseRetriever
... | langchain/libs/community/langchain_community/retrievers/chatgpt_plugin_retriever.py/0 | {
"file_path": "langchain/libs/community/langchain_community/retrievers/chatgpt_plugin_retriever.py",
"repo_id": "langchain",
"token_count": 1324
} | 277 |
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