text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
import datetime
import pytest
from base.client_base import TestcaseBase
from common import common_func as cf
from common import common_type as ct
from common.common_type import CaseLabel
from utils.util_log import test_log as log
from pymilvus import utility
rounds = 100
per_nb = 100000
default_field_name = ct.defau... | milvus/tests/python_client/load/test_workload.py/0 | {
"file_path": "milvus/tests/python_client/load/test_workload.py",
"repo_id": "milvus",
"token_count": 1931
} | 1,908 |
import asyncio
import json
import logging
from abc import abstractmethod
from threading import Thread
from typing import Any, Dict, List, Optional, Tuple, Type, Union, cast, get_args
from llama_index.agent.openai_legacy.utils import get_function_by_name
from llama_index.core.agent.types import BaseAgent
from llama_ind... | llama_index/llama-index-integrations/agent/llama-index-agent-openai-legacy/llama_index/agent/openai_legacy/openai_agent.py/0 | {
"file_path": "llama_index/llama-index-integrations/agent/llama-index-agent-openai-legacy/llama_index/agent/openai_legacy/openai_agent.py",
"repo_id": "llama_index",
"token_count": 10040
} | 1,258 |
// 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/indexnode/indexnode_mock.go/0 | {
"file_path": "milvus/internal/indexnode/indexnode_mock.go",
"repo_id": "milvus",
"token_count": 3199
} | 1,803 |
# C Transformers
This page covers how to use the [C Transformers](https://github.com/marella/ctransformers) library within LangChain.
It is broken into two parts: installation and setup, and then references to specific C Transformers wrappers.
## Installation and Setup
- Install the Python package with `pip install ... | langchain/docs/docs/integrations/providers/ctransformers.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/ctransformers.mdx",
"repo_id": "langchain",
"token_count": 558
} | 130 |
<jupyter_start><jupyter_text>Run TemplateIn `server.py`, set -```add_routes(app, chain_rag_conv, path="/rag-multi-modal-mv-local")```<jupyter_code>from langserve.client import RemoteRunnable
rag_app = RemoteRunnable("http://localhost:8001/rag-multi-modal-mv-local")
rag_app.invoke(" < keywords here > ")<jupyter_output>... | langchain/templates/rag-multi-modal-mv-local/rag-multi-modal-mv-local.ipynb/0 | {
"file_path": "langchain/templates/rag-multi-modal-mv-local/rag-multi-modal-mv-local.ipynb",
"repo_id": "langchain",
"token_count": 131
} | 680 |
// Code generated from Plan.g4 by ANTLR 4.9. DO NOT EDIT.
package planparserv2 // Plan
import "github.com/antlr/antlr4/runtime/Go/antlr"
// A complete Visitor for a parse tree produced by PlanParser.
type PlanVisitor interface {
antlr.ParseTreeVisitor
// Visit a parse tree produced by PlanParser#JSONIdentifier.
V... | milvus/internal/parser/planparserv2/generated/plan_visitor.go/0 | {
"file_path": "milvus/internal/parser/planparserv2/generated/plan_visitor.go",
"repo_id": "milvus",
"token_count": 1005
} | 1,837 |
# CIP 6: OpenTelemetry Monitoring
## **Status**
Current status: `Under Discussion`
## **Motivation**
Chroma currently has very little observability, only offering basic logging. Using Chroma in a high-performance production context requires the ability to understand how Chroma is behaving and responding to requests... | chroma/docs/CIP_6_OpenTelemetry_Monitoring.md/0 | {
"file_path": "chroma/docs/CIP_6_OpenTelemetry_Monitoring.md",
"repo_id": "chroma",
"token_count": 618
} | 36 |
import type { IndexFlatL2 } from "faiss-node";
import type { NameRegistry, Parser } from "pickleparser";
import * as uuid from "uuid";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { SaveableVectorStore } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/docu... | langchainjs/libs/langchain-community/src/vectorstores/faiss.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/faiss.ts",
"repo_id": "langchainjs",
"token_count": 5678
} | 978 |
CREATE TABLE table2 (
name TEXT PRIMARY KEY
);
| chroma/chromadb/test/db/migrations/00002-migration-2.psql.sql/0 | {
"file_path": "chroma/chromadb/test/db/migrations/00002-migration-2.psql.sql",
"repo_id": "chroma",
"token_count": 19
} | 20 |
"""__ModuleName__ vector stores."""
from __future__ import annotations
import asyncio
from functools import partial
from typing import (
TYPE_CHECKING,
Any,
Callable,
Iterable,
List,
Optional,
Tuple,
Type,
TypeVar,
)
from langchain_core.embeddings import Embeddings
from langchain_c... | langchain/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py/0 | {
"file_path": "langchain/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py",
"repo_id": "langchain",
"token_count": 2362
} | 217 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-github/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-github/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,369 |
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class AbstractDatasetReader(ABC):
def __init__(
self,
path_or_paths: ... | datasets/src/datasets/io/abc.py/0 | {
"file_path": "datasets/src/datasets/io/abc.py",
"repo_id": "datasets",
"token_count": 721
} | 141 |
""" CrossViT Model
@inproceedings{
chen2021crossvit,
title={{CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification}},
author={Chun-Fu (Richard) Chen and Quanfu Fan and Rameswar Panda},
booktitle={International Conference on Computer Vision (ICCV)},
year={2021}
}
Paper l... | pytorch-image-models/timm/models/crossvit.py/0 | {
"file_path": "pytorch-image-models/timm/models/crossvit.py",
"repo_id": "pytorch-image-models",
"token_count": 12463
} | 362 |
// 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/ScalarIndex.cpp/0 | {
"file_path": "milvus/internal/core/src/segcore/ScalarIndex.cpp",
"repo_id": "milvus",
"token_count": 1532
} | 1,656 |
from rag_chroma_private.chain import chain
__all__ = ["chain"]
| langchain/templates/rag-chroma-private/rag_chroma_private/__init__.py/0 | {
"file_path": "langchain/templates/rag-chroma-private/rag_chroma_private/__init__.py",
"repo_id": "langchain",
"token_count": 21
} | 669 |
use yew_agent::PublicWorker;
fn main() {
console_error_panic_hook::set_once();
candle_wasm_example_yolo::Worker::register();
}
| candle/candle-wasm-examples/yolo/src/bin/worker.rs/0 | {
"file_path": "candle/candle-wasm-examples/yolo/src/bin/worker.rs",
"repo_id": "candle",
"token_count": 53
} | 90 |
from __future__ import annotations
import logging
import warnings
from dataclasses import asdict, dataclass
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Tuple
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from langchain_core.vectorstores impor... | langchain/libs/community/langchain_community/vectorstores/zep.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/zep.py",
"repo_id": "langchain",
"token_count": 10557
} | 332 |
<!---
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 ... | transformers/examples/flax/speech-recognition/README.md/0 | {
"file_path": "transformers/examples/flax/speech-recognition/README.md",
"repo_id": "transformers",
"token_count": 1039
} | 507 |
"""**Embedding models** are wrappers around embedding models
from different APIs and services.
**Embedding models** can be LLMs or not.
**Class hierarchy:**
.. code-block::
Embeddings --> <name>Embeddings # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings
"""
import logging
import warnings
from typing impo... | langchain/libs/langchain/langchain/embeddings/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/embeddings/__init__.py",
"repo_id": "langchain",
"token_count": 1433
} | 495 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-lilac/llama_index/readers/lilac/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-lilac/llama_index/readers/lilac/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,469 |
"""Retriever OpenAI agent."""
from typing import Any, cast
from llama_index.legacy.agent.legacy.openai_agent import (
OpenAIAgent,
)
from llama_index.legacy.objects.base import ObjectRetriever
from llama_index.legacy.tools.types import BaseTool
class FnRetrieverOpenAIAgent(OpenAIAgent):
"""Function Retrieve... | llama_index/llama-index-legacy/llama_index/legacy/agent/legacy/retriever_openai_agent.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/agent/legacy/retriever_openai_agent.py",
"repo_id": "llama_index",
"token_count": 331
} | 1,576 |
# Introduction [[introduction]]
One of the most critical tasks in Deep Reinforcement Learning is to **find a good set of training hyperparameters**.
<img src="https://raw.githubusercontent.com/optuna/optuna/master/docs/image/optuna-logo.png" alt="Optuna Logo"/>
[Optuna](https://optuna.org/) is a library that helps y... | deep-rl-class/units/en/unitbonus2/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus2/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 156
} | 176 |
export {
type TypedPromptInputValues,
BaseStringPromptTemplate,
type BasePromptTemplateInput,
BasePromptTemplate,
} from "@langchain/core/prompts";
export { StringPromptValue } from "@langchain/core/prompt_values";
export { BaseExampleSelector } from "@langchain/core/example_selectors";
| langchainjs/langchain/src/prompts/base.ts/0 | {
"file_path": "langchainjs/langchain/src/prompts/base.ts",
"repo_id": "langchainjs",
"token_count": 92
} | 925 |
""" Pyramid Vision Transformer v2
@misc{wang2021pvtv2,
title={PVTv2: Improved Baselines with Pyramid Vision Transformer},
author={Wenhai Wang and Enze Xie and Xiang Li and Deng-Ping Fan and Kaitao Song and Ding Liang and
Tong Lu and Ping Luo and Ling Shao},
year={2021},
eprint={2106.137... | pytorch-image-models/timm/models/pvt_v2.py/0 | {
"file_path": "pytorch-image-models/timm/models/pvt_v2.py",
"repo_id": "pytorch-image-models",
"token_count": 9047
} | 401 |
<jupyter_start><jupyter_text>GPT4-V Experiments with General, Specific questions and Chain Of Thought (COT) Prompting Technique. GPT-4V has amazed us with its ability to analyze images and even generate website code from visuals.This tutorial notebook investigates GPT-4V's proficiency in interpreting bar charts, scatte... | llama_index/docs/examples/multi_modal/gpt4v_experiments_cot.ipynb/0 | {
"file_path": "llama_index/docs/examples/multi_modal/gpt4v_experiments_cot.ipynb",
"repo_id": "llama_index",
"token_count": 5951
} | 1,073 |
from typing import Any, Dict, Tuple
import numpy as np
class MockFaissIndex:
"""Mock Faiss index."""
def __init__(self, *args: Any, **kwargs: Any) -> None:
"""Initialize params."""
self._index: Dict[int, np.ndarray] = {}
@property
def ntotal(self) -> int:
"""Get ntotal."""
... | llama_index/llama-index-legacy/tests/indices/vector_store/mock_faiss.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/vector_store/mock_faiss.py",
"repo_id": "llama_index",
"token_count": 512
} | 1,533 |
import { ChatOpenAI } from "@langchain/openai";
import type { ChatPromptTemplate } from "@langchain/core/prompts";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { pull } from "langchain/hub";
import { z } from "zod";
import { DynamicTool, DynamicStructuredTool } from "@langchain/... | langchainjs/examples/src/agents/custom_tool.ts/0 | {
"file_path": "langchainjs/examples/src/agents/custom_tool.ts",
"repo_id": "langchainjs",
"token_count": 1734
} | 779 |
root ::= "[" items "]" EOF
items ::= item ("," ws* item)*
item ::= string
string ::=
"\"" word (ws+ word)* "\"" ws*
word ::= [a-zA-Z]+
ws ::= " "
EOF ::= "\n" | langchain/libs/langchain/langchain/llms/grammars/list.gbnf/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/grammars/list.gbnf",
"repo_id": "langchain",
"token_count": 81
} | 539 |
python_tests()
| llama_index/llama-index-integrations/llms/llama-index-llms-langchain/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-langchain/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,224 |
#[macro_use]
extern crate criterion;
mod common;
use std::fs::File;
use std::io::{BufRead, BufReader};
use std::path::Path;
use criterion::Criterion;
use tokenizers::models::bpe::{BpeTrainerBuilder, BPE};
use tokenizers::models::TrainerWrapper;
use tokenizers::pre_tokenizers::byte_level::ByteLevel;
use tokenizers::p... | tokenizers/tokenizers/benches/bpe_benchmark.rs/0 | {
"file_path": "tokenizers/tokenizers/benches/bpe_benchmark.rs",
"repo_id": "tokenizers",
"token_count": 1621
} | 471 |
<jupyter_start><jupyter_text>Fake EmbeddingsLangChain also provides a fake embedding class. You can use this to test your pipelines.<jupyter_code>from langchain_community.embeddings import FakeEmbeddings
embeddings = FakeEmbeddings(size=1352)
query_result = embeddings.embed_query("foo")
doc_results = embeddings.embed_d... | langchain/docs/docs/integrations/text_embedding/fake.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/text_embedding/fake.ipynb",
"repo_id": "langchain",
"token_count": 120
} | 175 |
<jupyter_start><jupyter_text>Connery Action ToolUsing this tool, you can integrate individual Connery Action into your LangChain agent.If you want to use more than one Connery Action in your agent,check out the [Connery Toolkit](/docs/integrations/toolkits/connery) documentation. What is Connery?Connery is an open-sour... | langchain/docs/docs/integrations/tools/connery.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/connery.ipynb",
"repo_id": "langchain",
"token_count": 1193
} | 172 |
"""Init file."""
from llama_index.core.data_structs.data_structs import (
IndexDict,
IndexGraph,
IndexList,
KeywordTable,
Node,
)
from llama_index.core.data_structs.table import StructDatapoint
__all__ = [
"IndexGraph",
"KeywordTable",
"IndexList",
"IndexDict",
"StructDatapoint... | llama_index/llama-index-core/llama_index/core/data_structs/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/data_structs/__init__.py",
"repo_id": "llama_index",
"token_count": 145
} | 1,251 |
# 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... | accelerate/tests/test_big_modeling.py/0 | {
"file_path": "accelerate/tests/test_big_modeling.py",
"repo_id": "accelerate",
"token_count": 19558
} | 17 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/examples/community/sd_text2img_k_diffusion.py/0 | {
"file_path": "diffusers/examples/community/sd_text2img_k_diffusion.py",
"repo_id": "diffusers",
"token_count": 9724
} | 207 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/core/src/exec/expression/BinaryRangeExpr.h/0 | {
"file_path": "milvus/internal/core/src/exec/expression/BinaryRangeExpr.h",
"repo_id": "milvus",
"token_count": 4543
} | 1,867 |
import requests
from pytest import MonkeyPatch
from langchain_community.llms.ollama import Ollama
def mock_response_stream(): # type: ignore[no-untyped-def]
mock_response = [b'{ "response": "Response chunk 1" }']
class MockRaw:
def read(self, chunk_size): # type: ignore[no-untyped-def]
... | langchain/libs/community/tests/unit_tests/llms/test_ollama.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/llms/test_ollama.py",
"repo_id": "langchain",
"token_count": 2894
} | 388 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/src/transformers/data/metrics/squad_metrics.py/0 | {
"file_path": "transformers/src/transformers/data/metrics/squad_metrics.py",
"repo_id": "transformers",
"token_count": 13819
} | 592 |
[package]
name = "tantivy-binding"
version = "0.1.0"
edition = "2021"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
tantivy = "0.21.0"
futures = "0.3.21"
libc = "0.2"
scopeguard = "1.2"
[build-dependencies]
cbindgen = "0.26.0"
[lib]
crate-type = ["st... | milvus/internal/core/thirdparty/tantivy/tantivy-binding/Cargo.toml/0 | {
"file_path": "milvus/internal/core/thirdparty/tantivy/tantivy-binding/Cargo.toml",
"repo_id": "milvus",
"token_count": 147
} | 1,761 |
{
"en-ru": {
"src": [
"Welsh AMs worried about 'looking like muppets'",
"There is consternation among some AMs at a suggestion their title should change to MWPs (Member of the Welsh Parliament).",
"It has arisen because of plans to change the name of the assembly to the Welsh Parliament.",
... | transformers/examples/legacy/seq2seq/test_data/fsmt/fsmt_val_data.json/0 | {
"file_path": "transformers/examples/legacy/seq2seq/test_data/fsmt/fsmt_val_data.json",
"repo_id": "transformers",
"token_count": 4034
} | 583 |
from langchain_community.llms.petals import Petals
__all__ = ["Petals"]
| langchain/libs/langchain/langchain/llms/petals.py/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/petals.py",
"repo_id": "langchain",
"token_count": 25
} | 542 |
// 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/storage/binlog_writer.go/0 | {
"file_path": "milvus/internal/storage/binlog_writer.go",
"repo_id": "milvus",
"token_count": 3207
} | 1,926 |
import { logVersion010MigrationWarning } from "../../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "chat_models/iflytek_xinghuo",
});
export * from "@langchain/community/chat_models/iflytek_xinghuo";
| langchainjs/langchain/src/chat_models/iflytek_xinghuo/index.ts/0 | {
"file_path": "langchainjs/langchain/src/chat_models/iflytek_xinghuo/index.ts",
"repo_id": "langchainjs",
"token_count": 87
} | 861 |
from llama_index.embeddings.ollama.base import OllamaEmbedding
__all__ = ["OllamaEmbedding"]
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-ollama/llama_index/embeddings/ollama/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-ollama/llama_index/embeddings/ollama/__init__.py",
"repo_id": "llama_index",
"token_count": 36
} | 1,236 |
/* eslint-disable import/first */
/* eslint-disable arrow-body-style */
import { z } from "zod";
import { DynamicStructuredTool } from "@langchain/core/tools";
const addTool = new DynamicStructuredTool({
name: "add",
description: "Add two integers together.",
schema: z.object({
firstInt: z.number(),
sec... | langchainjs/examples/src/use_cases/tool_use/agents.ts/0 | {
"file_path": "langchainjs/examples/src/use_cases/tool_use/agents.ts",
"repo_id": "langchainjs",
"token_count": 661
} | 847 |
from pathlib import Path
import pytest
from langchain_community.document_loaders import CSVLoader, DirectoryLoader, TextLoader
from langchain_community.document_loaders.helpers import detect_file_encodings
@pytest.mark.requires("chardet")
def test_loader_detect_encoding_text() -> None:
"""Test text loader."""
... | langchain/libs/community/tests/unit_tests/document_loaders/test_detect_encoding.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/document_loaders/test_detect_encoding.py",
"repo_id": "langchain",
"token_count": 1025
} | 371 |
from typing import Callable, Dict, Iterator, List, Optional
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
from langchain_community.utilities.tensorflow_datasets import TensorflowDatasets
class TensorflowDatasetLoader(BaseLoader):
"""Load from `Ten... | langchain/libs/community/langchain_community/document_loaders/tensorflow_datasets.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/tensorflow_datasets.py",
"repo_id": "langchain",
"token_count": 1359
} | 263 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.rayyan import RayyanReader
def test_class():
names_of_base_classes = [b.__name__ for b in RayyanReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-rayyan/tests/test_readers_rayyan.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-rayyan/tests/test_readers_rayyan.py",
"repo_id": "llama_index",
"token_count": 88
} | 1,410 |
from llama_index.packs.amazon_product_extraction.base import (
AmazonProductExtractionPack,
)
__all__ = ["AmazonProductExtractionPack"]
| llama_index/llama-index-packs/llama-index-packs-amazon-product-extraction/llama_index/packs/amazon_product_extraction/__init__.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-amazon-product-extraction/llama_index/packs/amazon_product_extraction/__init__.py",
"repo_id": "llama_index",
"token_count": 44
} | 1,831 |
<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers and 🤗 Datasets. Uncomment the following cell and run it.<jupyter_code>#! pip install datasets transformers<jupyter_output><empty_output><jupyter_text>If you're opening this notebook locally, make su... | notebooks/examples/text_classification.ipynb/0 | {
"file_path": "notebooks/examples/text_classification.ipynb",
"repo_id": "notebooks",
"token_count": 7676
} | 311 |
# 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/poolformer/test_modeling_poolformer.py/0 | {
"file_path": "transformers/tests/models/poolformer/test_modeling_poolformer.py",
"repo_id": "transformers",
"token_count": 3675
} | 832 |
from abc import ABC, abstractmethod
from typing import Dict, List, Optional, Tuple
import fsspec
DEFAULT_COLLECTION = "data"
DEFAULT_BATCH_SIZE = 1
class BaseKVStore(ABC):
"""Base key-value store."""
@abstractmethod
def put(self, key: str, val: dict, collection: str = DEFAULT_COLLECTION) -> None:
... | llama_index/llama-index-core/llama_index/core/storage/kvstore/types.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/storage/kvstore/types.py",
"repo_id": "llama_index",
"token_count": 1071
} | 1,210 |
import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
import { OllamaInput, OllamaRequestParams } from "../utils/ollama.js";
type CamelCasedRequestOptions = Omit<
OllamaInput,
"baseUrl" | "model" | "format"
>;
/**
* Interface for OllamaEmbeddings parameters. Extends EmbeddingsParams and
* d... | langchainjs/libs/langchain-community/src/embeddings/ollama.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/embeddings/ollama.ts",
"repo_id": "langchainjs",
"token_count": 1727
} | 981 |
<!--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/schedulers/multistep_dpm_solver_inverse.md/0 | {
"file_path": "diffusers/docs/source/en/api/schedulers/multistep_dpm_solver_inverse.md",
"repo_id": "diffusers",
"token_count": 547
} | 188 |
"use node";
import { ConvexVectorStore } from "@langchain/community/vectorstores/convex";
import { OpenAIEmbeddings } from "@langchain/openai";
import { action } from "./_generated/server.js";
export const ingest = action({
args: {},
handler: async (ctx) => {
await ConvexVectorStore.fromTexts(
["Hello w... | langchainjs/examples/src/indexes/vector_stores/convex/fromTexts.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/convex/fromTexts.ts",
"repo_id": "langchainjs",
"token_count": 179
} | 815 |
"""Tool for the Google Trends"""
from typing import Optional
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.tools import BaseTool
from langchain_community.utilities.google_jobs import GoogleJobsAPIWrapper
class GoogleJobsQueryRun(BaseTool):
"""Tool that queries the Google Jo... | langchain/libs/community/langchain_community/tools/google_jobs/tool.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/google_jobs/tool.py",
"repo_id": "langchain",
"token_count": 293
} | 292 |
import datetime
from pathlib import Path
from unittest import TestCase
import numpy as np
import pandas as pd
import pyarrow as pa
import pytest
from datasets import Audio, Features, Image, IterableDataset
from datasets.formatting import NumpyFormatter, PandasFormatter, PythonFormatter, query_table
from datasets.form... | datasets/tests/test_formatting.py/0 | {
"file_path": "datasets/tests/test_formatting.py",
"repo_id": "datasets",
"token_count": 19116
} | 148 |
import torch
import torch.distributed
from opentelemetry import trace
from transformers import AutoConfig, AutoTokenizer
from transformers.models.llama import LlamaTokenizer
from typing import Optional
from text_generation_server.models import FlashCausalLM
from text_generation_server.models.custom_modeling.flash_lla... | text-generation-inference/server/text_generation_server/models/flash_llama.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/flash_llama.py",
"repo_id": "text-generation-inference",
"token_count": 1942
} | 416 |
from llama_index.readers.awadb.base import AwadbReader
__all__ = ["AwadbReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-awadb/llama_index/readers/awadb/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-awadb/llama_index/readers/awadb/__init__.py",
"repo_id": "llama_index",
"token_count": 32
} | 1,408 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import GenericTensor, Pipeline, PipelineException, build_pipeline_init_args
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if is_... | transformers/src/transformers/pipelines/fill_mask.py/0 | {
"file_path": "transformers/src/transformers/pipelines/fill_mask.py",
"repo_id": "transformers",
"token_count": 4992
} | 682 |
import { Document } from "@langchain/core/documents";
import { BaseStore } from "@langchain/core/stores";
/**
* Class that provides a layer of abstraction over the base storage,
* allowing for the encoding and decoding of keys and values. It extends
* the BaseStore class.
*/
// eslint-disable-next-line @typescript... | langchainjs/langchain/src/storage/encoder_backed.ts/0 | {
"file_path": "langchainjs/langchain/src/storage/encoder_backed.ts",
"repo_id": "langchainjs",
"token_count": 1108
} | 910 |
[tool.poetry]
name = "basic_critique_revise"
version = "0.0.1"
description = "Iteratively generate schema candidates and revise based on errors"
authors = []
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
openai = "<2"
[tool.poetry.group.dev.dependencies]
langchain-cli = ">... | langchain/templates/basic-critique-revise/pyproject.toml/0 | {
"file_path": "langchain/templates/basic-critique-revise/pyproject.toml",
"repo_id": "langchain",
"token_count": 278
} | 636 |
from langchain.schema.output_parser import __all__
EXPECTED_ALL = [
"BaseCumulativeTransformOutputParser",
"BaseGenerationOutputParser",
"BaseLLMOutputParser",
"BaseOutputParser",
"BaseTransformOutputParser",
"NoOpOutputParser",
"OutputParserException",
"StrOutputParser",
"T",
]
d... | langchain/libs/langchain/tests/unit_tests/schema/test_output_parser.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/schema/test_output_parser.py",
"repo_id": "langchain",
"token_count": 148
} | 617 |
# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class FlaxControlNetModel(metaclass=DummyObject):
_backends = ["flax"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"])
@classmethod
def from_c... | diffusers/src/diffusers/utils/dummy_flax_objects.py/0 | {
"file_path": "diffusers/src/diffusers/utils/dummy_flax_objects.py",
"repo_id": "diffusers",
"token_count": 2343
} | 243 |
from langchain_community.vectorstores.milvus import Milvus
__all__ = ["Milvus"]
| langchain/libs/langchain/langchain/vectorstores/milvus.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/milvus.py",
"repo_id": "langchain",
"token_count": 28
} | 606 |
Welcome to LlamaIndex 🦙 !
##########################
LlamaIndex is a data framework for `LLM <https://en.wikipedia.org/wiki/Large_language_model>`_-based applications which benefit from context augmentation. Such LLM systems have been termed as RAG systems, standing for "Retrieval-Augemented Generation". LlamaIndex p... | llama_index/docs/index.rst/0 | {
"file_path": "llama_index/docs/index.rst",
"repo_id": "llama_index",
"token_count": 2237
} | 1,173 |
# coding=utf-8
# Copyright 2021 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... | transformers/tests/models/vision_encoder_decoder/test_modeling_flax_vision_encoder_decoder.py/0 | {
"file_path": "transformers/tests/models/vision_encoder_decoder/test_modeling_flax_vision_encoder_decoder.py",
"repo_id": "transformers",
"token_count": 9435
} | 755 |
import { XataVectorSearch } from "@langchain/community/vectorstores/xata";
import { OpenAIEmbeddings, OpenAI } from "@langchain/openai";
import { BaseClient } from "@xata.io/client";
import { VectorDBQAChain } from "langchain/chains";
import { Document } from "@langchain/core/documents";
// First, follow set-up instru... | langchainjs/examples/src/indexes/vector_stores/xata.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/xata.ts",
"repo_id": "langchainjs",
"token_count": 659
} | 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 applicabl... | diffusers/src/diffusers/models/attention_flax.py/0 | {
"file_path": "diffusers/src/diffusers/models/attention_flax.py",
"repo_id": "diffusers",
"token_count": 9031
} | 233 |
"""Load summarizing chains."""
from typing import Any, Mapping, Optional, Protocol
from langchain_core.callbacks import Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate
from langchain.chains.combine_documents.base import BaseCombineDocumentsC... | langchain/libs/langchain/langchain/chains/summarize/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/summarize/__init__.py",
"repo_id": "langchain",
"token_count": 2349
} | 470 |
# flake8: noqa
REQUEST_TEMPLATE = """You are a helpful AI Assistant. Please provide JSON arguments to agentFunc() based on the user's instructions.
API_SCHEMA: ```typescript
{schema}
```
USER_INSTRUCTIONS: "{instructions}"
Your arguments must be plain json provided in a markdown block:
ARGS: ```json
{{valid json co... | langchain/libs/langchain/langchain/chains/api/openapi/prompts.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/api/openapi/prompts.py",
"repo_id": "langchain",
"token_count": 497
} | 476 |
# Adversarial Inception v3
**Inception v3** is a convolutional neural network architecture from the Inception family that makes several improvements including using [Label Smoothing](https://paperswithcode.com/method/label-smoothing), Factorized 7 x 7 convolutions, and the use of an [auxiliary classifer](https://paper... | pytorch-image-models/docs/models/.templates/models/adversarial-inception-v3.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/adversarial-inception-v3.md",
"repo_id": "pytorch-image-models",
"token_count": 1432
} | 314 |
python_sources()
| llama_index/llama-index-integrations/output_parsers/llama-index-output-parsers-guardrails/llama_index/output_parsers/guardrails/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/output_parsers/llama-index-output-parsers-guardrails/llama_index/output_parsers/guardrails/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,385 |
<!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/deit.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/deit.md",
"repo_id": "transformers",
"token_count": 1955
} | 481 |
"""Run tests for all models
Tests that run on CI should have a specific marker, e.g. @pytest.mark.base. This
marker is used to parallelize the CI runs, with one runner for each marker.
If new tests are added, ensure that they use one of the existing markers
(documented in pyproject.toml > pytest > markers) or that a ... | pytorch-image-models/tests/test_models.py/0 | {
"file_path": "pytorch-image-models/tests/test_models.py",
"repo_id": "pytorch-image-models",
"token_count": 9191
} | 346 |
from contextlib import contextmanager
from typing import TYPE_CHECKING, Callable, Iterator
from llama_index.legacy.llms.huggingface import HuggingFaceLLM
from llama_index.legacy.llms.llama_cpp import LlamaCPP
from llama_index.legacy.llms.llm import LLM
if TYPE_CHECKING:
from lmformatenforcer import CharacterLevel... | llama_index/llama-index-legacy/llama_index/legacy/prompts/lmformatenforcer_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/prompts/lmformatenforcer_utils.py",
"repo_id": "llama_index",
"token_count": 850
} | 1,602 |
# LlamaIndex Multi-Modal-Llms Integration: Gemini
| llama_index/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-gemini/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-gemini/README.md",
"repo_id": "llama_index",
"token_count": 16
} | 1,323 |
[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 = ["BagelVectorStore"]
contains_example = false
import_path = "llama_index.vector_stores.bage... | llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-bagel/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-bagel/pyproject.toml",
"repo_id": "llama_index",
"token_count": 638
} | 1,511 |
<!--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/model_doc/blip.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/blip.md",
"repo_id": "transformers",
"token_count": 1242
} | 503 |
"""Simple graph store index."""
import logging
from typing import Any, Dict, List, Optional
import redis
from llama_index.core.graph_stores.types import GraphStore
logger = logging.getLogger(__name__)
class FalkorDBGraphStore(GraphStore):
"""FalkorDB Graph Store.
In this graph store, triplets are stored w... | llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-falkordb/llama_index/graph_stores/falkordb/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-falkordb/llama_index/graph_stores/falkordb/base.py",
"repo_id": "llama_index",
"token_count": 2847
} | 1,291 |
python_sources()
| llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-postgres/llama_index/storage/index_store/postgres/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-postgres/llama_index/storage/index_store/postgres/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,464 |
from llama_index.storage.kvstore.mongodb.base import MongoDBKVStore
__all__ = ["MongoDBKVStore"]
| llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-mongodb/llama_index/storage/kvstore/mongodb/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-mongodb/llama_index/storage/kvstore/mongodb/__init__.py",
"repo_id": "llama_index",
"token_count": 38
} | 1,469 |
# What is Reinforcement Learning? [[what-is-reinforcement-learning]]
To understand Reinforcement Learning, let’s start with the big picture.
## The big picture [[the-big-picture]]
The idea behind Reinforcement Learning is that an agent (an AI) will learn from the environment by **interacting with it** (through trial... | deep-rl-class/units/en/unit1/what-is-rl.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/what-is-rl.mdx",
"repo_id": "deep-rl-class",
"token_count": 624
} | 151 |
from langchain_astradb.vectorstores.astradb import AstraDBVectorStore
__all__ = [
"AstraDBVectorStore",
]
| langchain/libs/partners/astradb/langchain_astradb/vectorstores/__init__.py/0 | {
"file_path": "langchain/libs/partners/astradb/langchain_astradb/vectorstores/__init__.py",
"repo_id": "langchain",
"token_count": 41
} | 681 |
# coding=utf-8
# Copyright 2018 The Microsoft Research Asia LayoutLM Team Authors, The Hugging Face 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/license... | transformers/tests/models/layoutlm/test_tokenization_layoutlm.py/0 | {
"file_path": "transformers/tests/models/layoutlm/test_tokenization_layoutlm.py",
"repo_id": "transformers",
"token_count": 1057
} | 807 |
import { Neo4jGraph } from "@langchain/community/graphs/neo4j_graph";
import { OpenAI } from "@langchain/openai";
import { GraphCypherQAChain } from "langchain/chains/graph_qa/cypher";
import { PromptTemplate } from "@langchain/core/prompts";
/**
* This example uses Neo4j database, which is native graph database.
* ... | langchainjs/examples/src/chains/graph_db_custom_prompt.ts/0 | {
"file_path": "langchainjs/examples/src/chains/graph_db_custom_prompt.ts",
"repo_id": "langchainjs",
"token_count": 634
} | 760 |
# # Ensemble Adversarial Inception ResNet v2
**Inception-ResNet-v2** is a convolutional neural architecture that builds on the Inception family of architectures but incorporates [residual connections](https://paperswithcode.com/method/residual-connection) (replacing the filter concatenation stage of the Inception arch... | pytorch-image-models/docs/models/.templates/models/ensemble-adversarial.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/ensemble-adversarial.md",
"repo_id": "pytorch-image-models",
"token_count": 1379
} | 346 |
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple
import torch
from .configuration_utils import PretrainedConfig
@dataclass
class Cache:
"""
Base, abstract class for all caches. The actual data structure is specific to each subclass.
"""
def update(
self,... | transformers/src/transformers/cache_utils.py/0 | {
"file_path": "transformers/src/transformers/cache_utils.py",
"repo_id": "transformers",
"token_count": 8237
} | 616 |
# 🦜️🔗 LangChain.js
⚡ Building applications with LLMs through composability ⚡
[](https://github.com/langchain-ai/langchainjs/actions/workflows/ci.yml)  [![License: MIT](https://img.shie... | langchainjs/langchain/README.md/0 | {
"file_path": "langchainjs/langchain/README.md",
"repo_id": "langchainjs",
"token_count": 2118
} | 911 |
from typing import List, Optional
from langchain_core.outputs.chat_generation import ChatGeneration
from langchain_core.pydantic_v1 import BaseModel
class ChatResult(BaseModel):
"""Class that contains all results for a single chat model call."""
generations: List[ChatGeneration]
"""List of the chat gene... | langchain/libs/core/langchain_core/outputs/chat_result.py/0 | {
"file_path": "langchain/libs/core/langchain_core/outputs/chat_result.py",
"repo_id": "langchain",
"token_count": 147
} | 426 |
import logging
from typing import Any, Dict, List, Optional, Sequence
from llama_index.core.bridge.pydantic import Field
from llama_index.core.llms import LLM, ChatMessage, ChatResponse, OpenAI
from llama_index.core.postprocessor.types import BaseNodePostprocessor
from llama_index.core.prompts import BasePromptTemplat... | llama_index/llama-index-core/llama_index/core/postprocessor/rankGPT_rerank.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/postprocessor/rankGPT_rerank.py",
"repo_id": "llama_index",
"token_count": 2668
} | 1,205 |
"""Util that sends calendar events in Office 365.
Free, but setup is required. See link below.
https://learn.microsoft.com/en-us/graph/auth/
"""
from datetime import datetime as dt
from typing import List, Optional, Type
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 i... | langchain/libs/community/langchain_community/tools/office365/send_event.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/office365/send_event.py",
"repo_id": "langchain",
"token_count": 1126
} | 303 |
# LlamaIndex Graph Stores Integration: Falkordb
| llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-falkordb/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/graph_stores/llama-index-graph-stores-falkordb/README.md",
"repo_id": "llama_index",
"token_count": 12
} | 1,204 |
---
sidebar_position: 4
sidebar_class_name: hidden
---
# Agents
The core idea of agents is to use a language model to choose a sequence of actions to take.
In chains, a sequence of actions is hardcoded (in code). In agents, a language model is used as a reasoning engine to determine which actions to take and in which... | langchainjs/docs/core_docs/docs/modules/agents/index.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/agents/index.mdx",
"repo_id": "langchainjs",
"token_count": 506
} | 724 |
import * as uuid from "uuid";
import flatten from "flat";
import { GoogleAuth, GoogleAuthOptions } from "google-auth-library";
import { VectorStore } from "@langchain/core/vectorstores";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { Document, DocumentInput } from "@langchain/core/docum... | langchainjs/libs/langchain-community/src/vectorstores/googlevertexai.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/googlevertexai.ts",
"repo_id": "langchainjs",
"token_count": 7524
} | 966 |
import { z } from "zod";
import { OpenAI, ChatOpenAI } from "@langchain/openai";
import { StructuredOutputParser } from "langchain/output_parsers";
import { PromptTemplate } from "@langchain/core/prompts";
const prompt = PromptTemplate.fromTemplate(
`Return a JSON object containing the following value wrapped in an ... | langchainjs/examples/src/guides/fallbacks/better_model.ts/0 | {
"file_path": "langchainjs/examples/src/guides/fallbacks/better_model.ts",
"repo_id": "langchainjs",
"token_count": 619
} | 810 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/src/diffusers/models/unets/unet_2d_blocks_flax.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/unet_2d_blocks_flax.py",
"repo_id": "diffusers",
"token_count": 6961
} | 247 |
"""Logic for selecting examples to include in prompts."""
from langchain_core.example_selectors.length_based import (
LengthBasedExampleSelector,
)
from langchain_core.example_selectors.semantic_similarity import (
MaxMarginalRelevanceExampleSelector,
SemanticSimilarityExampleSelector,
)
from langchain.pro... | langchain/libs/langchain/langchain/prompts/example_selector/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/prompts/example_selector/__init__.py",
"repo_id": "langchain",
"token_count": 184
} | 576 |
<jupyter_start><jupyter_text>Connect to RAG AppAssuming you are already running this server:```bashlangserve start```<jupyter_code>from langserve.client import RemoteRunnable
rag_redis = RemoteRunnable("http://localhost:8000/rag-redis")
print(rag_redis.invoke("What was Nike's revenue in 2023?"))
print(rag_redis.invok... | langchain/templates/rag-redis/rag_redis.ipynb/0 | {
"file_path": "langchain/templates/rag-redis/rag_redis.ipynb",
"repo_id": "langchain",
"token_count": 179
} | 726 |
# 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/pop2piano/feature_extraction_pop2piano.py/0 | {
"file_path": "transformers/src/transformers/models/pop2piano/feature_extraction_pop2piano.py",
"repo_id": "transformers",
"token_count": 8827
} | 709 |
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