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# flake8: noqa import time from sys import platform from typing import ( TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Set, Tuple, TypedDict, Union, ) if TYPE_CHECKING: from playwright.sync_api import Browser, CDPSession, Page, sync_playwright black_listed_elements: S...
langchain/libs/langchain/langchain/chains/natbot/crawler.py/0
{ "file_path": "langchain/libs/langchain/langchain/chains/natbot/crawler.py", "repo_id": "langchain", "token_count": 8044 }
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// 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/unittest/test_relational.cpp/0
{ "file_path": "milvus/internal/core/unittest/test_relational.cpp", "repo_id": "milvus", "token_count": 2287 }
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# Metric Card for CER ## Metric description Character error rate (CER) is a common metric of the performance of an automatic speech recognition (ASR) system. CER is similar to Word Error Rate (WER), but operates on character instead of word. Character error rate can be computed as: `CER = (S + D + I) / N = (S + D...
datasets/metrics/cer/README.md/0
{ "file_path": "datasets/metrics/cer/README.md", "repo_id": "datasets", "token_count": 1192 }
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// 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/unittest/test_query.cpp/0
{ "file_path": "milvus/internal/core/unittest/test_query.cpp", "repo_id": "milvus", "token_count": 17455 }
1,678
python_sources()
llama_index/llama-index-legacy/llama_index/legacy/core/query_pipeline/BUILD/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/core/query_pipeline/BUILD", "repo_id": "llama_index", "token_count": 6 }
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<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers and 🤗 Datasets as well as other dependencies. Uncomment the following cell and run it.<jupyter_code>#! pip install datasets evaluate transformers rouge-score nltk<jupyter_output><empty_output><jupyt...
notebooks/examples/summarization.ipynb/0
{ "file_path": "notebooks/examples/summarization.ipynb", "repo_id": "notebooks", "token_count": 5127 }
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import os from git import Repo from langchain.text_splitter import Language, RecursiveCharacterTextSplitter from langchain_community.document_loaders.generic import GenericLoader from langchain_community.document_loaders.parsers import LanguageParser from langchain_community.embeddings import GPT4AllEmbeddings from la...
langchain/templates/rag-codellama-fireworks/rag_codellama_fireworks/chain.py/0
{ "file_path": "langchain/templates/rag-codellama-fireworks/rag_codellama_fireworks/chain.py", "repo_id": "langchain", "token_count": 707 }
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from llama_index.core.tools.tool_spec.base import BaseToolSpec import yfinance as yf import pandas as pd class YahooFinanceToolSpec(BaseToolSpec): """Yahoo Finance tool spec.""" spec_functions = [ "balance_sheet", "income_statement", "cash_flow", "stock_basic_info", "s...
llama_index/llama-index-integrations/tools/llama-index-tools-yahoo-finance/llama_index/tools/yahoo_finance/base.py/0
{ "file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-yahoo-finance/llama_index/tools/yahoo_finance/base.py", "repo_id": "llama_index", "token_count": 1132 }
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poetry_requirements( name="poetry", )
llama_index/llama-index-integrations/indices/llama-index-indices-managed-vectara/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/indices/llama-index-indices-managed-vectara/BUILD", "repo_id": "llama_index", "token_count": 18 }
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[virtualenvs] in-project = true
langchain/libs/cli/poetry.toml/0
{ "file_path": "langchain/libs/cli/poetry.toml", "repo_id": "langchain", "token_count": 12 }
210
<jupyter_start><jupyter_text>Cohere RAG retrieverThis notebook covers how to get started with Cohere RAG retriever. This allows you to leverage the ability to search documents over various connectors or by supplying your own.<jupyter_code>from langchain.retrievers import CohereRagRetriever from langchain_community.chat...
langchain/docs/docs/integrations/retrievers/cohere.ipynb/0
{ "file_path": "langchain/docs/docs/integrations/retrievers/cohere.ipynb", "repo_id": "langchain", "token_count": 395 }
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import gc import random import traceback import unittest import numpy as np import torch from PIL import Image from transformers import ( CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection, GPT2Tokenizer, ) from diffusers import ( AutoencoderKL, DPMSolverMultis...
diffusers/tests/pipelines/unidiffuser/test_unidiffuser.py/0
{ "file_path": "diffusers/tests/pipelines/unidiffuser/test_unidiffuser.py", "repo_id": "diffusers", "token_count": 14379 }
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<!--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...
accelerate/docs/source/concept_guides/low_precision_training.md/0
{ "file_path": "accelerate/docs/source/concept_guides/low_precision_training.md", "repo_id": "accelerate", "token_count": 1465 }
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from __future__ import annotations import warnings from abc import ABC, abstractmethod from inspect import signature from typing import TYPE_CHECKING, Any, Dict, List, Optional from langchain_core.documents import Document from langchain_core.load.dump import dumpd from langchain_core.runnables import ( Runnable,...
langchain/libs/core/langchain_core/retrievers.py/0
{ "file_path": "langchain/libs/core/langchain_core/retrievers.py", "repo_id": "langchain", "token_count": 4781 }
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<jupyter_start><jupyter_text>Pathway Retriever > [Pathway](https://pathway.com/) is an open data processing framework. It allows you to easily develop data transformation pipelines and Machine Learning applications that work with live data sources and changing data.This notebook demonstrates how to set up a live data i...
llama_index/docs/examples/retrievers/pathway_retriever.ipynb/0
{ "file_path": "llama_index/docs/examples/retrievers/pathway_retriever.ipynb", "repo_id": "llama_index", "token_count": 1873 }
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# rag-pinecone-multi-query This template performs RAG using Pinecone and OpenAI with a multi-query retriever. It uses an LLM to generate multiple queries from different perspectives based on the user's input query. For each query, it retrieves a set of relevant documents and takes the unique union across all quer...
langchain/templates/rag-pinecone-multi-query/README.md/0
{ "file_path": "langchain/templates/rag-pinecone-multi-query/README.md", "repo_id": "langchain", "token_count": 692 }
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"""Test for Serializable base class""" import pytest from langchain_community.llms.openai import OpenAI as CommunityOpenAI from langchain_core.load.dump import dumpd, dumps from langchain_core.load.load import load, loads from langchain_core.prompts.prompt import PromptTemplate from langchain.chains.llm import LLMCha...
langchain/libs/langchain/tests/unit_tests/load/test_load.py/0
{ "file_path": "langchain/libs/langchain/tests/unit_tests/load/test_load.py", "repo_id": "langchain", "token_count": 1965 }
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/** @type {import('tailwindcss').Config} */ module.exports = { content: [ './pages/**/*.{js,ts,jsx,tsx,mdx}', './components/**/*.{js,ts,jsx,tsx,mdx}', './app/**/*.{js,ts,jsx,tsx,mdx}', ], theme: { extend: { backgroundImage: { 'gradient-radial': 'radial-gradient(var(--tw-gradient-stop...
langchain-nextjs-template/tailwind.config.js/0
{ "file_path": "langchain-nextjs-template/tailwind.config.js", "repo_id": "langchain-nextjs-template", "token_count": 230 }
71
poetry_requirements( name="poetry", ) python_sources( interpreter_constraints=["==3.10.*"], )
llama_index/llama-index-integrations/readers/llama-index-readers-pathway/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-pathway/BUILD", "repo_id": "llama_index", "token_count": 48 }
1,536
from langchain_community.vectorstores.usearch import USearch __all__ = ["USearch"]
langchain/libs/langchain/langchain/vectorstores/usearch.py/0
{ "file_path": "langchain/libs/langchain/langchain/vectorstores/usearch.py", "repo_id": "langchain", "token_count": 25 }
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// 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/tests/integration/suite.go/0
{ "file_path": "milvus/tests/integration/suite.go", "repo_id": "milvus", "token_count": 1029 }
2,159
from langchain_community.tools.google_places.tool import ( GooglePlacesSchema, GooglePlacesTool, ) __all__ = ["GooglePlacesSchema", "GooglePlacesTool"]
langchain/libs/langchain/langchain/tools/google_places/tool.py/0
{ "file_path": "langchain/libs/langchain/langchain/tools/google_places/tool.py", "repo_id": "langchain", "token_count": 56 }
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"""Test PromptLayerChatOpenAI wrapper.""" import pytest from langchain_core.callbacks import CallbackManager from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult from langchain_community.chat_models.promptlayer_openai imp...
langchain/libs/community/tests/integration_tests/chat_models/test_promptlayer_openai.py/0
{ "file_path": "langchain/libs/community/tests/integration_tests/chat_models/test_promptlayer_openai.py", "repo_id": "langchain", "token_count": 1673 }
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# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
trl/trl/trainer/utils.py/0
{ "file_path": "trl/trl/trainer/utils.py", "repo_id": "trl", "token_count": 14555 }
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from langchain_core.utils.env import get_from_dict_or_env, get_from_env __all__ = ["get_from_dict_or_env", "get_from_env"]
langchain/libs/langchain/langchain/utils/env.py/0
{ "file_path": "langchain/libs/langchain/langchain/utils/env.py", "repo_id": "langchain", "token_count": 50 }
622
from langchain_community.agent_toolkits.azure_cognitive_services import ( AzureCognitiveServicesToolkit, ) __all__ = ["AzureCognitiveServicesToolkit"]
langchain/libs/langchain/langchain/agents/agent_toolkits/azure_cognitive_services.py/0
{ "file_path": "langchain/libs/langchain/langchain/agents/agent_toolkits/azure_cognitive_services.py", "repo_id": "langchain", "token_count": 50 }
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// Copyright (C) 2019-2020 Zilliz. All rights reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance // with the License. You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable l...
milvus/internal/core/src/query/Utils.h/0
{ "file_path": "milvus/internal/core/src/query/Utils.h", "repo_id": "milvus", "token_count": 1788 }
1,653
package funcutil import ( "testing" "github.com/stretchr/testify/assert" ) func Test_flattenedByteVectorsToByteVectors(t *testing.T) { flattenedVectors := []byte{0, 1, 2, 3, 4, 5} dimension := 3 actual := flattenedByteVectorsToByteVectors(flattenedVectors, dimension) expected := [][]byte{ {0, 1, 2}, {3, 4...
milvus/pkg/util/funcutil/placeholdergroup_test.go/0
{ "file_path": "milvus/pkg/util/funcutil/placeholdergroup_test.go", "repo_id": "milvus", "token_count": 431 }
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from llama_index.core.llama_pack import BaseLlamaPack from llama_index.packs.redis_ingestion_pipeline import RedisIngestionPipelinePack def test_class(): names_of_base_classes = [b.__name__ for b in RedisIngestionPipelinePack.__mro__] assert BaseLlamaPack.__name__ in names_of_base_classes
llama_index/llama-index-packs/llama-index-packs-redis-ingestion-pipeline/tests/test_packs_redis_ingestion_pipeline.py/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-redis-ingestion-pipeline/tests/test_packs_redis_ingestion_pipeline.py", "repo_id": "llama_index", "token_count": 113 }
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from llama_index.core.readers.base import BaseReader from llama_index.readers.zendesk import ZendeskReader def test_class(): names_of_base_classes = [b.__name__ for b in ZendeskReader.__mro__] assert BaseReader.__name__ in names_of_base_classes
llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/tests/test_readers_zendesk.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/tests/test_readers_zendesk.py", "repo_id": "llama_index", "token_count": 94 }
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from __future__ import annotations import uuid from typing import Any, Dict, Iterable, List, Literal, Optional, Tuple, Union from langchain_core.documents import Document from langchain_core.embeddings import Embeddings from langchain_core.vectorstores import VectorStore class PGVecto_rs(VectorStore): """Vector...
langchain/libs/community/langchain_community/vectorstores/pgvecto_rs.py/0
{ "file_path": "langchain/libs/community/langchain_community/vectorstores/pgvecto_rs.py", "repo_id": "langchain", "token_count": 3723 }
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# Astra DB > DataStax [Astra DB](https://docs.datastax.com/en/astra/home/astra.html) is a serverless vector-capable database built on Apache Cassandra® and made conveniently available > through an easy-to-use JSON API. ### Setup Install the following Python package: ```bash pip install "astrapy>=0.7.1" ``` ## Vect...
langchain/docs/docs/integrations/providers/astradb.mdx/0
{ "file_path": "langchain/docs/docs/integrations/providers/astradb.mdx", "repo_id": "langchain", "token_count": 1047 }
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--- sidebar_position: 1 hide_table_of_contents: true --- # Folders with multiple files This example goes over how to load data from folders with multiple files. The second argument is a map of file extensions to loader factories. Each file will be passed to the matching loader, and the resulting documents will be con...
langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/directory.mdx/0
{ "file_path": "langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/directory.mdx", "repo_id": "langchainjs", "token_count": 372 }
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python_sources()
llama_index/llama-index-integrations/postprocessor/llama-index-postprocessor-rankgpt-rerank/llama_index/postprocessor/rankgpt_rerank/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/postprocessor/llama-index-postprocessor-rankgpt-rerank/llama_index/postprocessor/rankgpt_rerank/BUILD", "repo_id": "llama_index", "token_count": 6 }
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python_sources()
llama_index/llama-index-integrations/callbacks/llama-index-callbacks-honeyhive/llama_index/callbacks/honeyhive/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-honeyhive/llama_index/callbacks/honeyhive/BUILD", "repo_id": "llama_index", "token_count": 6 }
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<jupyter_start><jupyter_text>Custom Trajectory Evaluator[](https://colab.research.google.com/github/langchain-ai/langchain/blob/master/docs/docs/guides/evaluation/trajectory/custom.ipynb)You can make your own custom trajectory evaluators by inheriting from the [AgentTrajectoryEvaluator](https://api.python.langchain.com...
langchain/docs/docs/guides/evaluation/trajectory/custom.ipynb/0
{ "file_path": "langchain/docs/docs/guides/evaluation/trajectory/custom.ipynb", "repo_id": "langchain", "token_count": 1152 }
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# Time-weighted vector store retriever This retriever uses a combination of semantic similarity and a time decay. The algorithm for scoring them is: ``` semantic_similarity + (1.0 - decay_rate) ^ hours_passed ``` Notably, `hours_passed` refers to the hours passed since the object in the retriever **was last accesse...
langchainjs/docs/core_docs/docs/modules/data_connection/retrievers/time_weighted_vectorstore.mdx/0
{ "file_path": "langchainjs/docs/core_docs/docs/modules/data_connection/retrievers/time_weighted_vectorstore.mdx", "repo_id": "langchainjs", "token_count": 411 }
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python_sources()
llama_index/llama-index-legacy/llama_index/legacy/core/BUILD/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/core/BUILD", "repo_id": "llama_index", "token_count": 6 }
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# LlamaIndex Extractors Integration: Entity
llama_index/llama-index-integrations/extractors/llama-index-extractors-entity/README.md/0
{ "file_path": "llama_index/llama-index-integrations/extractors/llama-index-extractors-entity/README.md", "repo_id": "llama_index", "token_count": 10 }
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ko/run_scripts.md/0
{ "file_path": "transformers/docs/source/ko/run_scripts.md", "repo_id": "transformers", "token_count": 10775 }
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package broker import ( "context" "testing" "time" "github.com/cockroachdb/errors" "github.com/samber/lo" "github.com/stretchr/testify/mock" "github.com/stretchr/testify/suite" "google.golang.org/grpc" "github.com/milvus-io/milvus-proto/go-api/v2/commonpb" "github.com/milvus-io/milvus-proto/go-api/v2/msgpb...
milvus/internal/datanode/broker/datacoord_test.go/0
{ "file_path": "milvus/internal/datanode/broker/datacoord_test.go", "repo_id": "milvus", "token_count": 4556 }
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python_tests( name="tests", skip_tests=True, )
llama_index/llama-index-legacy/tests/utilities/BUILD/0
{ "file_path": "llama_index/llama-index-legacy/tests/utilities/BUILD", "repo_id": "llama_index", "token_count": 25 }
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vllm-cuda: # Clone vllm pip install -U ninja packaging --no-cache-dir git clone https://github.com/vllm-project/vllm.git vllm build-vllm-cuda: vllm-cuda cd vllm && git fetch && git checkout f8a1e39fae05ca610be8d5a78be9d40f5274e5fc cd vllm && python setup.py build install-vllm-cuda: build-vllm-cuda pip uninst...
text-generation-inference/server/Makefile-vllm/0
{ "file_path": "text-generation-inference/server/Makefile-vllm", "repo_id": "text-generation-inference", "token_count": 332 }
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// Licensed to the LF AI & Data foundation under one // or more contributor license agreements. See the NOTICE file // distributed with this work for additional information // regarding copyright ownership. The ASF licenses this file // to you under the Apache License, Version 2.0 (the // "License"); you may not use th...
milvus/internal/util/flowgraph/node_test.go/0
{ "file_path": "milvus/internal/util/flowgraph/node_test.go", "repo_id": "milvus", "token_count": 1400 }
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from llama_index.readers.smart_pdf_loader.base import SmartPDFLoader __all__ = ["SmartPDFLoader"]
llama_index/llama-index-integrations/readers/llama-index-readers-smart-pdf-loader/llama_index/readers/smart_pdf_loader/__init__.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-smart-pdf-loader/llama_index/readers/smart_pdf_loader/__init__.py", "repo_id": "llama_index", "token_count": 36 }
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from llama_index.core.readers.base import BaseReader from llama_index.readers.azstorage_blob import AzStorageBlobReader def test_class(): names_of_base_classes = [b.__name__ for b in AzStorageBlobReader.__mro__] assert BaseReader.__name__ in names_of_base_classes
llama_index/llama-index-integrations/readers/llama-index-readers-azstorage-blob/tests/test_readers_azstorage_blob.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-azstorage-blob/tests/test_readers_azstorage_blob.py", "repo_id": "llama_index", "token_count": 95 }
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// 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/distributed/querynode/client/client_test.go/0
{ "file_path": "milvus/internal/distributed/querynode/client/client_test.go", "repo_id": "milvus", "token_count": 1676 }
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<html> <head> <meta content="text/html;charset=utf-8" http-equiv="Content-Type" /> <title>Candle Whisper Rust/WASM</title> </head> <body></body> </html> <!DOCTYPE html> <html> <head> <meta charset="UTF-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <style> ...
candle/candle-wasm-examples/whisper/lib-example.html/0
{ "file_path": "candle/candle-wasm-examples/whisper/lib-example.html", "repo_id": "candle", "token_count": 6488 }
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from typing import TYPE_CHECKING, Any, Dict, Generator, List, Mapping, Optional, Union from langchain_core.callbacks import CallbackManagerForLLMRun from langchain_core.language_models.llms import LLM if TYPE_CHECKING: from xinference.client import RESTfulChatModelHandle, RESTfulGenerateModelHandle from xinfe...
langchain/libs/community/langchain_community/llms/xinference.py/0
{ "file_path": "langchain/libs/community/langchain_community/llms/xinference.py", "repo_id": "langchain", "token_count": 2825 }
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import importlib import importlib.metadata import logging import os import platform from pathlib import Path from typing import Optional from packaging import version logger = logging.getLogger(__name__.split(".", 1)[0]) # to avoid circular import from .utils.logging # Datasets S3_DATASETS_BUCKET_PREFIX = "https:/...
datasets/src/datasets/config.py/0
{ "file_path": "datasets/src/datasets/config.py", "repo_id": "datasets", "token_count": 4310 }
149
package proxy import ( "context" "testing" "github.com/golang/protobuf/proto" "github.com/stretchr/testify/assert" "google.golang.org/grpc" "google.golang.org/grpc/metadata" "github.com/milvus-io/milvus-proto/go-api/v2/milvuspb" "github.com/milvus-io/milvus/pkg/util" ) func TestDatabaseInterceptor(t *testin...
milvus/internal/proxy/database_interceptor_test.go/0
{ "file_path": "milvus/internal/proxy/database_interceptor_test.go", "repo_id": "milvus", "token_count": 1813 }
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# rag_supabase This template performs RAG with Supabase. [Supabase](https://supabase.com/docs) is an open-source Firebase alternative. It is built on top of [PostgreSQL](https://en.wikipedia.org/wiki/PostgreSQL), a free and open-source relational database management system (RDBMS) and uses [pgvector](https://github....
langchain/templates/rag-supabase/README.md/0
{ "file_path": "langchain/templates/rag-supabase/README.md", "repo_id": "langchain", "token_count": 1381 }
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from text_generation_server.utils.convert import convert_file, convert_files from text_generation_server.utils.dist import initialize_torch_distributed from text_generation_server.utils.weights import Weights from text_generation_server.utils.peft import download_and_unload_peft from text_generation_server.utils.hub im...
text-generation-inference/server/text_generation_server/utils/__init__.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/utils/__init__.py", "repo_id": "text-generation-inference", "token_count": 417 }
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from langchain_core.utils.iter import NoLock, Tee, batch_iterate, tee_peer __all__ = ["NoLock", "tee_peer", "Tee", "batch_iterate"]
langchain/libs/langchain/langchain/utils/iter.py/0
{ "file_path": "langchain/libs/langchain/langchain/utils/iter.py", "repo_id": "langchain", "token_count": 50 }
568
// Code generated by mockery v2.32.4. DO NOT EDIT. package optimizers import mock "github.com/stretchr/testify/mock" // MockQueryHook is an autogenerated mock type for the QueryHook type type MockQueryHook struct { mock.Mock } type MockQueryHook_Expecter struct { mock *mock.Mock } func (_m *MockQueryHook) EXPECT...
milvus/internal/querynodev2/optimizers/mock_query_hook.go/0
{ "file_path": "milvus/internal/querynodev2/optimizers/mock_query_hook.go", "repo_id": "milvus", "token_count": 2213 }
1,906
# 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/loaders/controlnet.py/0
{ "file_path": "diffusers/src/diffusers/loaders/controlnet.py", "repo_id": "diffusers", "token_count": 3018 }
224
python_tests()
llama_index/llama-index-packs/llama-index-packs-snowflake-query-engine/tests/BUILD/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-snowflake-query-engine/tests/BUILD", "repo_id": "llama_index", "token_count": 5 }
1,699
# coding=utf-8 # Copyright 2018 The Open AI Team Authors and The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # ...
transformers/src/transformers/models/openai/tokenization_openai_fast.py/0
{ "file_path": "transformers/src/transformers/models/openai/tokenization_openai_fast.py", "repo_id": "transformers", "token_count": 1098 }
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import { getEndpoint, OpenAIEndpointConfig } from "@langchain/openai"; describe("getEndpoint", () => { it("should return the correct endpoint with azureOpenAIBasePath and azureOpenAIApiDeploymentName", () => { const config: OpenAIEndpointConfig = { azureOpenAIApiKey: "API-KEY", azureOpenAIApiDeployme...
langchainjs/langchain/src/util/tests/azure.test.ts/0
{ "file_path": "langchainjs/langchain/src/util/tests/azure.test.ts", "repo_id": "langchainjs", "token_count": 813 }
1,001
from llama_index.readers.zendesk.base import ZendeskReader __all__ = ["ZendeskReader"]
llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/llama_index/readers/zendesk/__init__.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/llama_index/readers/zendesk/__init__.py", "repo_id": "llama_index", "token_count": 35 }
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from pathlib import Path from typing import List from llama_index.legacy.indices.composability.graph import ComposableGraph from llama_index.legacy.indices.list.base import SummaryIndex from llama_index.legacy.indices.loading import load_graph_from_storage from llama_index.legacy.indices.vector_store.base import Vecto...
llama_index/llama-index-legacy/tests/indices/test_loading_graph.py/0
{ "file_path": "llama_index/llama-index-legacy/tests/indices/test_loading_graph.py", "repo_id": "llama_index", "token_count": 812 }
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export { type RouterInput, RouterRunnable } from "@langchain/core/runnables";
langchainjs/langchain/src/schema/runnable/router.ts/0
{ "file_path": "langchainjs/langchain/src/schema/runnable/router.ts", "repo_id": "langchainjs", "token_count": 23 }
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import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base"; import type { BaseRetrieverInterface } from "@langchain/core/retrievers"; import { PromptTemplate } from "@langchain/core/prompts"; import { BaseMessage, HumanMessage, AIMessage } from "@langchain/core/messages"; import { ChainValue...
langchainjs/langchain/src/chains/conversational_retrieval_chain.ts/0
{ "file_path": "langchainjs/langchain/src/chains/conversational_retrieval_chain.ts", "repo_id": "langchainjs", "token_count": 3393 }
861
python_tests()
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-chatgpt-plugin/tests/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-chatgpt-plugin/tests/BUILD", "repo_id": "llama_index", "token_count": 5 }
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<jupyter_start><jupyter_text>LlamaCPP In this short notebook, we show how to use the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) library with LlamaIndex.In this notebook, we use the [`llama-2-chat-13b-ggml`](https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML) model, along with the proper prompt f...
llama_index/docs/examples/llm/llama_2_llama_cpp.ipynb/0
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<jupyter_start><jupyter_text>Llama.cpp[llama-cpp-python](https://github.com/abetlen/llama-cpp-python) is a Python binding for [llama.cpp](https://github.com/ggerganov/llama.cpp).It supports inference for [many LLMs](https://github.com/ggerganov/llama.cppdescription) models, which can be accessed on [Hugging Face](https...
langchain/docs/docs/integrations/llms/llamacpp.ipynb/0
{ "file_path": "langchain/docs/docs/integrations/llms/llamacpp.ipynb", "repo_id": "langchain", "token_count": 4513 }
123
import asyncio import json import os from typing import Any, Dict, List, Optional import numpy as np from langchain_core.embeddings import Embeddings from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator from langchain_core.runnables.config import run_in_executor class BedrockEmbeddings(BaseModel, ...
langchain/libs/community/langchain_community/embeddings/bedrock.py/0
{ "file_path": "langchain/libs/community/langchain_community/embeddings/bedrock.py", "repo_id": "langchain", "token_count": 3045 }
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[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 = ["RedisVectorStore"] contains_example = false import_path = "llama_index.vector_stores.redi...
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-redis/pyproject.toml/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-redis/pyproject.toml", "repo_id": "llama_index", "token_count": 649 }
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"""Test the WriteFile tool.""" from pathlib import Path from tempfile import TemporaryDirectory from langchain_community.tools.file_management.utils import ( INVALID_PATH_TEMPLATE, ) from langchain_community.tools.file_management.write import WriteFileTool def test_write_file_with_root_dir() -> None: """Tes...
langchain/libs/community/tests/unit_tests/tools/file_management/test_write.py/0
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# Configuration File for CodeCov codecov: require_ci_to_pass: no notify: require_ci_to_pass: no wait_for_ci: false ci: - jenkins.milvus.io:18080 coverage: precision: 2 round: down range: "70...100" status: project: default: target: 77% threshold: 0% #Allow the covera...
milvus/codecov.yml/0
{ "file_path": "milvus/codecov.yml", "repo_id": "milvus", "token_count": 364 }
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import inspect import time from pathlib import Path from typing import Callable, List, Optional, Union import numpy as np import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from diffusers import DiffusionPipeline from diffusers.configuration_utils import FrozenDict from diffusers.m...
diffusers/examples/community/interpolate_stable_diffusion.py/0
{ "file_path": "diffusers/examples/community/interpolate_stable_diffusion.py", "repo_id": "diffusers", "token_count": 11720 }
202
python_sources()
llama_index/llama-index-legacy/llama_index/legacy/multi_modal_llms/BUILD/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/multi_modal_llms/BUILD", "repo_id": "llama_index", "token_count": 6 }
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# (Tensorflow) EfficientNet CondConv **EfficientNet** is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a *compound coefficient*. Unlike conventional practice that arbitrary scales these factors, the EfficientNet scaling method unifo...
pytorch-image-models/docs/models/.templates/models/tf-efficientnet-condconv.md/0
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# flake8: noqa from langchain_core.prompts.prompt import PromptTemplate web_search_template = """Please write a passage to answer the question Question: {QUESTION} Passage:""" web_search = PromptTemplate(template=web_search_template, input_variables=["QUESTION"]) sci_fact_template = """Please write a scientific paper...
langchain/libs/langchain/langchain/chains/hyde/prompts.py/0
{ "file_path": "langchain/libs/langchain/langchain/chains/hyde/prompts.py", "repo_id": "langchain", "token_count": 630 }
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import { test, expect } from "@jest/globals"; import { Document, DocumentInterface } from "@langchain/core/documents"; import { SyntheticEmbeddings } from "@langchain/core/utils/testing"; import { similarity } from "ml-distance"; import { MemoryVectorStore } from "../memory.js"; test("MemoryVectorStore with external ...
langchainjs/langchain/src/vectorstores/tests/memory.test.ts/0
{ "file_path": "langchainjs/langchain/src/vectorstores/tests/memory.test.ts", "repo_id": "langchainjs", "token_count": 954 }
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import { useCallback, useMemo, useState } from "react"; import { InformationCircleIcon } from "@heroicons/react/24/outline"; import { Chat } from "./components/Chat"; import { ChatList } from "./components/ChatList"; import { Layout } from "./components/Layout"; import { NewChat } from "./components/NewChat"; import { ...
opengpts/frontend/src/App.tsx/0
{ "file_path": "opengpts/frontend/src/App.tsx", "repo_id": "opengpts", "token_count": 1789 }
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// 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/index/Utils.cpp/0
{ "file_path": "milvus/internal/core/src/index/Utils.cpp", "repo_id": "milvus", "token_count": 4395 }
1,788
python_tests()
llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-s3/tests/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-s3/tests/BUILD", "repo_id": "llama_index", "token_count": 5 }
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--- sidebar_class_name: hidden --- # Modules LangChain provides standard, extendable interfaces and external integrations for the following main modules: #### [Model I/O](/docs/modules/model_io/) Interface with language models #### [Retrieval](/docs/modules/data_connection/) Interface with application-specific data ...
langchain/docs/docs/modules/index.mdx/0
{ "file_path": "langchain/docs/docs/modules/index.mdx", "repo_id": "langchain", "token_count": 179 }
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/* eslint-disable no-process-env */ /* eslint-disable @typescript-eslint/no-non-null-assertion */ import * as fs from "node:fs"; import * as url from "node:url"; import * as path from "node:path"; import { test } from "@jest/globals"; import { DatabaseObjectResponse, NotionAPILoader, PageObjectResponse, } from "....
langchainjs/langchain/src/document_loaders/tests/notionapi.test.ts/0
{ "file_path": "langchainjs/langchain/src/document_loaders/tests/notionapi.test.ts", "repo_id": "langchainjs", "token_count": 1756 }
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# Copyright 2024 The Qwen Team and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unles...
transformers/src/transformers/models/qwen2/__init__.py/0
{ "file_path": "transformers/src/transformers/models/qwen2/__init__.py", "repo_id": "transformers", "token_count": 894 }
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/poly/layer.py/0
{ "file_path": "peft/src/peft/tuners/poly/layer.py", "repo_id": "peft", "token_count": 3322 }
307
extern crate napi_build; fn main() { napi_build::setup(); }
tokenizers/bindings/node/build.rs/0
{ "file_path": "tokenizers/bindings/node/build.rs", "repo_id": "tokenizers", "token_count": 26 }
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use crate::models::with_tracing::{layer_norm, linear, Embedding, LayerNorm, Linear}; /// Phi model. /// https://huggingface.co/microsoft/phi-2 /// There is an alternative implementation of the phi model in mixformers.rs. /// This corresponds to the model update made with the following commit: /// https://huggingface.co...
candle/candle-transformers/src/models/phi.rs/0
{ "file_path": "candle/candle-transformers/src/models/phi.rs", "repo_id": "candle", "token_count": 6392 }
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import { BaseEntityStore } from "./base.js"; /** * An entity store that keeps data in memory. It extends from the * `BaseEntityStore` class and is used to store and manage entities. */ export class InMemoryEntityStore extends BaseEntityStore { lc_namespace = ["langchain", "stores", "entity", "in_memory"]; priv...
langchainjs/langchain/src/memory/stores/entity/in_memory.ts/0
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#include <metal_stdlib> using namespace metal; #define MAX(x, y) ((x) > (y) ? (x) : (y)) #define MIN(x, y) ((x) < (y) ? (x) : (y)) METAL_FUNC uint get_strided_index( uint idx, constant size_t &num_dims, constant size_t *dims, constant size_t *strides ) { uint strided_i = 0; for (uint d = 0; d ...
candle/candle-metal-kernels/src/reduce.metal/0
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import { Tool } from "@langchain/core/tools"; /** * Interface for the parameters that can be passed to the * WikipediaQueryRun constructor. */ export interface WikipediaQueryRunParams { topKResults?: number; maxDocContentLength?: number; baseUrl?: string; } /** * Type alias for URL parameters. Represents a ...
langchainjs/libs/langchain-community/src/tools/wikipedia_query_run.ts/0
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import CodeBlock from "@theme/CodeBlock"; import Example from "@examples/agents/connery_mrkl.ts"; import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx"; # Connery Toolkit Using this toolkit, you can integrate Connery Actions into your LangChain agent. :::note If you want to use only...
langchainjs/docs/core_docs/docs/integrations/toolkits/connery.mdx/0
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import torch from diffusers import DDIMInverseScheduler from .test_schedulers import SchedulerCommonTest class DDIMInverseSchedulerTest(SchedulerCommonTest): scheduler_classes = (DDIMInverseScheduler,) forward_default_kwargs = (("num_inference_steps", 50),) def get_scheduler_config(self, **kwargs): ...
diffusers/tests/schedulers/test_scheduler_ddim_inverse.py/0
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import html import inspect import re import urllib.parse as ul from typing import Any, Callable, Dict, List, Optional, Union import numpy as np import PIL.Image import torch from transformers import CLIPImageProcessor, T5EncoderModel, T5Tokenizer from ...loaders import LoraLoaderMixin from ...models import UNet2DCond...
diffusers/src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py/0
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250
"""Zapier Toolkit."""
langchain/libs/community/langchain_community/agent_toolkits/zapier/__init__.py/0
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# CIP-4: In and Not In Metadata Filters Proposal ## Status Current Status: `Under Discussion` ## **Motivation** Currently, Chroma does not provide a way to filter metadata through `in` and `not in`. This appears to be a frequent ask from community members. ## **Public Interfaces** The changes will affect the foll...
chroma/docs/CIP_4_In_Nin_Metadata_Filters.md/0
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40
"""Embedding utils for LlamaIndex.""" import os from typing import TYPE_CHECKING, List, Optional, Union if TYPE_CHECKING: from llama_index.core.bridge.langchain import Embeddings as LCEmbeddings from llama_index.core.base.embeddings.base import BaseEmbedding from llama_index.core.callbacks import CallbackManager ...
llama_index/llama-index-core/llama_index/core/embeddings/utils.py/0
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# coding=utf-8 # Copyright 2022 NVIDIA 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 # # U...
transformers/src/transformers/models/segformer/modeling_tf_segformer.py/0
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import srtParser2 from "srt-parser-2"; import { TextLoader } from "./text.js"; /** * A class that extends the `TextLoader` class. It represents a document * loader that loads documents from SRT (SubRip) subtitle files. It has a * constructor that takes a `filePathOrBlob` parameter representing the * path to the SR...
langchainjs/langchain/src/document_loaders/fs/srt.ts/0
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863
--- sidebar_position: 3 --- # Tool usage This section will cover how to create conversational agents: chatbots that can interact with other systems and APIs using tools. Before reading this guide, we recommend you read both [the chatbot quickstart](/docs/use_cases/chatbots/quickstart) in this section and be familiar...
langchainjs/docs/core_docs/docs/use_cases/chatbots/tool_usage.mdx/0
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# LlamaIndex Readers Integration: ClickHouse
llama_index/llama-index-integrations/readers/llama-index-readers-clickhouse/README.md/0
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1,274
# flake8: noqa # There's no way to ignore "F401 '...' imported but unused" warnings in this # module, but to preserve other warnings. So, don't check this module at all. # coding=utf-8 # Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not ...
peft/src/peft/__init__.py/0
{ "file_path": "peft/src/peft/__init__.py", "repo_id": "peft", "token_count": 952 }
303
from langchain_community.retrievers.tavily_search_api import ( SearchDepth, TavilySearchAPIRetriever, ) __all__ = ["SearchDepth", "TavilySearchAPIRetriever"]
langchain/libs/langchain/langchain/retrievers/tavily_search_api.py/0
{ "file_path": "langchain/libs/langchain/langchain/retrievers/tavily_search_api.py", "repo_id": "langchain", "token_count": 63 }
535
from langchain_community.utilities.openweathermap import OpenWeatherMapAPIWrapper def test_openweathermap_api_wrapper() -> None: """Test that OpenWeatherMapAPIWrapper returns correct data for London, GB.""" weather = OpenWeatherMapAPIWrapper() weather_data = weather.run("London,GB") assert weather_d...
langchain/libs/community/tests/integration_tests/utilities/test_openweathermap.py/0
{ "file_path": "langchain/libs/community/tests/integration_tests/utilities/test_openweathermap.py", "repo_id": "langchain", "token_count": 273 }
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