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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/proxy/channels_mgr.go/0
{ "file_path": "milvus/internal/proxy/channels_mgr.go", "repo_id": "milvus", "token_count": 3939 }
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# StackoverflowReader (In Beta) Using the Stackoverflow API, this class will read the Stackoverflow Teams API and return a list of questions and answers based on posts. It also supports caching the results to a local directory, so that you can run the load_data() method multiple times without hitting the API. ## get...
llama_index/llama-index-integrations/readers/llama-index-readers-stackoverflow/README.md/0
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from typing import List, Optional, Type from langchain_core.callbacks import CallbackManagerForToolRun from langchain_core.pydantic_v1 import BaseModel, Field from langchain_community.tools.office365.base import O365BaseTool class CreateDraftMessageSchema(BaseModel): """Input for SendMessageTool.""" body: ...
langchain/libs/community/langchain_community/tools/office365/create_draft_message.py/0
{ "file_path": "langchain/libs/community/langchain_community/tools/office365/create_draft_message.py", "repo_id": "langchain", "token_count": 754 }
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# 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 applicabl...
transformers/tests/pipelines/test_pipelines_zero_shot_image_classification.py/0
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import logging from typing import Any, Dict, List, Optional from langchain_core.callbacks import CallbackManagerForLLMRun from langchain_core.language_models import BaseLanguageModel from langchain_core.language_models.llms import LLM from langchain_core.pydantic_v1 import Extra, root_validator from langchain_core.uti...
langchain/libs/community/langchain_community/llms/opaqueprompts.py/0
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<jupyter_start><jupyter_text>Reddit>[Reddit](https://www.reddit.com) is an American social news aggregation, content rating, and discussion website.This loader fetches the text from the Posts of Subreddits or Reddit users, using the `praw` Python package.Make a [Reddit Application](https://www.reddit.com/prefs/apps/) a...
langchain/docs/docs/integrations/document_loaders/reddit.ipynb/0
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# coding=utf-8 # Copyright 2023 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/tools/test_tools_common.py/0
{ "file_path": "transformers/tests/tools/test_tools_common.py", "repo_id": "transformers", "token_count": 1790 }
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<script lang="ts"> import { createEventDispatcher } from "svelte"; import IconGear from "~icons/bi/gear-fill"; import { base } from "$app/paths"; import type { Assistant } from "$lib/types/Assistant"; export let assistant: Pick< Assistant, "avatar" | "name" | "modelId" | "createdByName" | "exampleInputs" | "_...
chat-ui/src/lib/components/chat/AssistantIntroduction.svelte/0
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use candle_metal_kernels::{call_cast_contiguous, Kernels}; use metal::objc::rc::autoreleasepool; use metal::{Device, MTLResourceOptions}; use rand; use std::any::type_name; use std::time::Instant; fn main() { let device = Device::system_default().unwrap(); let kernels = Kernels::new(); let f32_1k = (0..10...
candle/candle-metal-kernels/tmp/cast.rs/0
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export * from "./document.js"; export * from "./transformers.js";
langchainjs/langchain-core/src/documents/index.ts/0
{ "file_path": "langchainjs/langchain-core/src/documents/index.ts", "repo_id": "langchainjs", "token_count": 21 }
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from llama_index.packs.sub_question_weaviate.base import WeaviateSubQuestionPack __all__ = ["WeaviateSubQuestionPack"]
llama_index/llama-index-packs/llama-index-packs-sub-question-weaviate/llama_index/packs/sub_question_weaviate/__init__.py/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-sub-question-weaviate/llama_index/packs/sub_question_weaviate/__init__.py", "repo_id": "llama_index", "token_count": 39 }
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from abc import abstractmethod from typing import List from llama_index.core.indices.query.schema import QueryBundle, QueryType from llama_index.core.prompts.mixin import PromptMixin from llama_index.core.schema import NodeWithScore class BaseImageRetriever(PromptMixin): """Base Image Retriever Abstraction.""" ...
llama_index/llama-index-core/llama_index/core/image_retriever.py/0
{ "file_path": "llama_index/llama-index-core/llama_index/core/image_retriever.py", "repo_id": "llama_index", "token_count": 1399 }
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// Copyright (C) 2019-2023 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/simd/sse2.cpp/0
{ "file_path": "milvus/internal/core/src/simd/sse2.cpp", "repo_id": "milvus", "token_count": 5359 }
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<jupyter_start><jupyter_text>Activeloop Deep Lake>[Activeloop Deep Lake](https://docs.activeloop.ai/) as a Multi-Modal Vector Store that stores embeddings and their metadata including text, Jsons, images, audio, video, and more. It saves the data locally, in your cloud, or on Activeloop storage. It performs hybrid sear...
langchain/docs/docs/integrations/vectorstores/activeloop_deeplake.ipynb/0
{ "file_path": "langchain/docs/docs/integrations/vectorstores/activeloop_deeplake.ipynb", "repo_id": "langchain", "token_count": 3473 }
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import { ChatOpenAI } from "@langchain/openai"; import { HumanMessage } from "@langchain/core/messages"; const chat = new ChatOpenAI({ temperature: 1 }); const response = await chat.call( [ new HumanMessage( "What is a good name for a company that makes colorful socks?" ), ], { timeout: 1000 } // ...
langchainjs/examples/src/models/chat/chat_timeout.ts/0
{ "file_path": "langchainjs/examples/src/models/chat/chat_timeout.ts", "repo_id": "langchainjs", "token_count": 133 }
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"""Finetuning Engine.""" from abc import ABC, abstractmethod from typing import Any from llama_index.core.base.embeddings.base import BaseEmbedding from llama_index.core.llms.llm import LLM from llama_index.core.postprocessor import SentenceTransformerRerank from llama_index.postprocessor.cohere_rerank import CohereR...
llama_index/llama-index-finetuning/llama_index/finetuning/types.py/0
{ "file_path": "llama_index/llama-index-finetuning/llama_index/finetuning/types.py", "repo_id": "llama_index", "token_count": 624 }
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import gc import json import os import time from pathlib import Path from typing import Any, Callable, Dict, Optional, Sequence from llama_index.legacy.bridge.pydantic import Field, PrivateAttr from llama_index.legacy.callbacks import CallbackManager from llama_index.legacy.constants import DEFAULT_CONTEXT_WINDOW, DEF...
llama_index/llama-index-legacy/llama_index/legacy/llms/nvidia_tensorrt.py/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/llms/nvidia_tensorrt.py", "repo_id": "llama_index", "token_count": 5175 }
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import { Writer as WriterClient } from "@writerai/writer-sdk"; import { type BaseLLMParams, LLM } from "@langchain/core/language_models/llms"; import { getEnvironmentVariable } from "@langchain/core/utils/env"; /** * Interface for the input parameters specific to the Writer model. */ export interface WriterInput ex...
langchainjs/libs/langchain-community/src/llms/writer.ts/0
{ "file_path": "langchainjs/libs/langchain-community/src/llms/writer.ts", "repo_id": "langchainjs", "token_count": 1661 }
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import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js"; /* #__PURE__ */ logVersion010MigrationWarning({ oldEntrypointName: "storage/vercel_kv", }); export * from "@langchain/community/storage/vercel_kv";
langchainjs/langchain/src/storage/vercel_kv.ts/0
{ "file_path": "langchainjs/langchain/src/storage/vercel_kv.ts", "repo_id": "langchainjs", "token_count": 76 }
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# coding=utf-8 # Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/models/gpt2/test_modeling_tf_gpt2.py/0
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# 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 applicabl...
transformers/tests/models/albert/test_modeling_flax_albert.py/0
{ "file_path": "transformers/tests/models/albert/test_modeling_flax_albert.py", "repo_id": "transformers", "token_count": 2637 }
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# coding=utf-8 # Copyright 2022 The HuggingFace Team and Microsoft Research AI4Science 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/licen...
transformers/src/transformers/models/biogpt/modeling_biogpt.py/0
{ "file_path": "transformers/src/transformers/models/biogpt/modeling_biogpt.py", "repo_id": "transformers", "token_count": 17918 }
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import CodeBlock from "@theme/CodeBlock"; # Replicate Here's an example of calling a Replicate model as an LLM: import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx"; <IntegrationInstallTooltip></IntegrationInstallTooltip> ```bash npm2yarn npm install replicate @langchain/communit...
langchainjs/docs/core_docs/docs/integrations/llms/replicate.mdx/0
{ "file_path": "langchainjs/docs/core_docs/docs/integrations/llms/replicate.mdx", "repo_id": "langchainjs", "token_count": 192 }
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/src/transformers/models/convnext/convert_convnext_to_pytorch.py/0
{ "file_path": "transformers/src/transformers/models/convnext/convert_convnext_to_pytorch.py", "repo_id": "transformers", "token_count": 4224 }
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import argparse import math import traceback import dateutil.parser as date_parser import requests def extract_time_from_single_job(job): """Extract time info from a single job in a GitHub Actions workflow run""" job_info = {} start = job["started_at"] end = job["completed_at"] start_datetime ...
transformers/utils/get_github_job_time.py/0
{ "file_path": "transformers/utils/get_github_job_time.py", "repo_id": "transformers", "token_count": 835 }
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package planparserv2 import ( "fmt" "math" "github.com/milvus-io/milvus-proto/go-api/v2/schemapb" parser "github.com/milvus-io/milvus/internal/parser/planparserv2/generated" "github.com/milvus-io/milvus/internal/proto/planpb" ) var arithExprMap = map[int]planpb.ArithOpType{ parser.PlanParserADD: planpb.ArithOp...
milvus/internal/parser/planparserv2/operators.go/0
{ "file_path": "milvus/internal/parser/planparserv2/operators.go", "repo_id": "milvus", "token_count": 7442 }
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import { test, expect } from "@jest/globals"; import { z } from "zod"; import { ChatOpenAI } from "@langchain/openai"; import { createExtractionChainFromZod } from "../extraction.js"; test("extraction chain", async () => { const chain = createExtractionChainFromZod( z.object({ "person-name": z.string().op...
langchainjs/langchain/src/chains/openai_functions/tests/extraction.int.test.ts/0
{ "file_path": "langchainjs/langchain/src/chains/openai_functions/tests/extraction.int.test.ts", "repo_id": "langchainjs", "token_count": 515 }
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"""dad_jokes reader.""" from typing import List import requests from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document class DadJokesReader(BaseReader): """Dad jokes reader. Reads a random dad joke. """ def _get_random_dad_joke(self): response = ...
llama_index/llama-index-integrations/readers/llama-index-readers-dad-jokes/llama_index/readers/dad_jokes/base.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-dad-jokes/llama_index/readers/dad_jokes/base.py", "repo_id": "llama_index", "token_count": 298 }
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package metautil import ( "path" "github.com/milvus-io/milvus/pkg/common" ) func BuildSegmentIndexFilePath(rootPath string, buildID, indexVersion, partID, segID int64, fileKey string) string { k := JoinIDPath(buildID, indexVersion, partID, segID) return path.Join(rootPath, common.SegmentIndexPath, k, fileKey) } ...
milvus/pkg/util/metautil/segment_index.go/0
{ "file_path": "milvus/pkg/util/metautil/segment_index.go", "repo_id": "milvus", "token_count": 237 }
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"""DEPRECATED: Kept for backwards compatibility.""" from langchain_core.utils.formatting import StrictFormatter, formatter __all__ = ["StrictFormatter", "formatter"]
langchain/libs/langchain/langchain/formatting.py/0
{ "file_path": "langchain/libs/langchain/langchain/formatting.py", "repo_id": "langchain", "token_count": 48 }
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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/pkg/mq/msgstream/mqwrapper/nmq/nmq_id_test.go/0
{ "file_path": "milvus/pkg/mq/msgstream/mqwrapper/nmq/nmq_id_test.go", "repo_id": "milvus", "token_count": 870 }
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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/rootcoord/root_coord.go/0
{ "file_path": "milvus/internal/rootcoord/root_coord.go", "repo_id": "milvus", "token_count": 39890 }
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from llama_index.core.readers.base import BaseReader from llama_index.readers.docstring_walker import DocstringWalker def test_class(): names_of_base_classes = [b.__name__ for b in DocstringWalker.__mro__] assert BaseReader.__name__ in names_of_base_classes
llama_index/llama-index-integrations/readers/llama-index-readers-docstring-walker/tests/test_readers_docstring_walker.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-docstring-walker/tests/test_readers_docstring_walker.py", "repo_id": "llama_index", "token_count": 90 }
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# Copyright 2024 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 required by appl...
transformers/src/transformers/quantizers/auto.py/0
{ "file_path": "transformers/src/transformers/quantizers/auto.py", "repo_id": "transformers", "token_count": 2583 }
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# Querying Now you've loaded your data, built an index, and stored that index for later, you're ready to get to the most significant part of an LLM application: querying. At its simplest, querying is just a prompt call to an LLM: it can be a question and get an answer, or a request for summarization, or a much more c...
llama_index/docs/understanding/querying/querying.md/0
{ "file_path": "llama_index/docs/understanding/querying/querying.md", "repo_id": "llama_index", "token_count": 1860 }
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<!--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/ja/stable_diffusion.md/0
{ "file_path": "diffusers/docs/source/ja/stable_diffusion.md", "repo_id": "diffusers", "token_count": 6241 }
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<!--Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ja/model_doc/bart.md/0
{ "file_path": "transformers/docs/source/ja/model_doc/bart.md", "repo_id": "transformers", "token_count": 5122 }
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# coding=utf-8 # Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved. # # This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX # and OPT implementations in this library. It has been modified from its # original forms to accommodate minor architectural differences compared # to G...
text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_modeling.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_modeling.py", "repo_id": "text-generation-inference", "token_count": 28422 }
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"""Azure Speech tool spec.""" import time from typing import List, Optional from llama_index.core.tools.tool_spec.base import BaseToolSpec class AzureSpeechToolSpec(BaseToolSpec): """Azure Speech tool spec.""" spec_functions = ["speech_to_text", "text_to_speech"] def __init__( self, region: st...
llama_index/llama-index-integrations/tools/llama-index-tools-azure-speech/llama_index/tools/azure_speech/base.py/0
{ "file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-azure-speech/llama_index/tools/azure_speech/base.py", "repo_id": "llama_index", "token_count": 1231 }
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# Copyright 2022 The HuggingFace Team and Brian Chao. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
accelerate/src/accelerate/commands/menu/selection_menu.py/0
{ "file_path": "accelerate/src/accelerate/commands/menu/selection_menu.py", "repo_id": "accelerate", "token_count": 2186 }
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<jupyter_start><jupyter_text>Connect to templateIn `server.py`, set -```add_routes(app, chain_ext, path="/rag_opensearch")```<jupyter_code>from langserve.client import RemoteRunnable rag_app = RemoteRunnable("http://localhost:8001/rag-opensearch") rag_app.invoke("What is the ip address used in the image processing log...
langchain/templates/rag-opensearch/rag_opensearch.ipynb/0
{ "file_path": "langchain/templates/rag-opensearch/rag_opensearch.ipynb", "repo_id": "langchain", "token_count": 124 }
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import { test, expect } from "@jest/globals"; import * as uuid from "uuid"; import { CallbackManager } from "../manager.js"; import { BaseCallbackHandler, type BaseCallbackHandlerInput } from "../base.js"; import type { Serialized } from "../../load/serializable.js"; import { Document } from "../../documents/document.j...
langchainjs/langchain-core/src/callbacks/tests/callbacks.test.ts/0
{ "file_path": "langchainjs/langchain-core/src/callbacks/tests/callbacks.test.ts", "repo_id": "langchainjs", "token_count": 5013 }
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import { OpenAI } from "@langchain/openai"; import { PythonInterpreterTool } from "langchain/experimental/tools/pyinterpreter"; import { ChatPromptTemplate } from "@langchain/core/prompts"; import { StringOutputParser } from "@langchain/core/output_parsers"; const prompt = ChatPromptTemplate.fromTemplate( `Generate ...
langchainjs/examples/src/tools/pyinterpreter.ts/0
{ "file_path": "langchainjs/examples/src/tools/pyinterpreter.ts", "repo_id": "langchainjs", "token_count": 490 }
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from dataclasses import dataclass, field from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union import pyarrow as pa if TYPE_CHECKING: from .features import FeatureType @dataclass class Translation: """`FeatureConnector` for translations with fixed languages per example. Here for ...
datasets/src/datasets/features/translation.py/0
{ "file_path": "datasets/src/datasets/features/translation.py", "repo_id": "datasets", "token_count": 1680 }
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<jupyter_start><jupyter_text>Guidance Pydantic Program Generate structured data with [**guidance**](https://github.com/microsoft/guidance) via LlamaIndex. With guidance, you can guarantee the output structure is correct by *forcing* the LLM to output desired tokens. This is especialy helpful when you are using lower-...
llama_index/docs/examples/output_parsing/guidance_pydantic_program.ipynb/0
{ "file_path": "llama_index/docs/examples/output_parsing/guidance_pydantic_program.ipynb", "repo_id": "llama_index", "token_count": 570 }
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from typing import List from llama_index.core.embeddings.mock_embed_model import MockEmbedding from llama_index.core.extractors import ( QuestionsAnsweredExtractor, SummaryExtractor, TitleExtractor, ) from llama_index.core.indices.prompt_helper import PromptHelper from llama_index.core.llms.mock import Moc...
llama_index/llama-index-core/tests/indices/test_service_context.py/0
{ "file_path": "llama_index/llama-index-core/tests/indices/test_service_context.py", "repo_id": "llama_index", "token_count": 725 }
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from langchain_community.document_loaders.pyspark_dataframe import ( PySparkDataFrameLoader, ) __all__ = ["PySparkDataFrameLoader"]
langchain/libs/langchain/langchain/document_loaders/pyspark_dataframe.py/0
{ "file_path": "langchain/libs/langchain/langchain/document_loaders/pyspark_dataframe.py", "repo_id": "langchain", "token_count": 47 }
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python_sources()
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-typesense/llama_index/vector_stores/typesense/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-typesense/llama_index/vector_stores/typesense/BUILD", "repo_id": "llama_index", "token_count": 6 }
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""" Knowledge Graph Query Engine.""" import logging from typing import Any, Dict, List, Optional, Sequence from llama_index.legacy.callbacks.schema import CBEventType, EventPayload from llama_index.legacy.core.base_query_engine import BaseQueryEngine from llama_index.legacy.core.response.schema import RESPONSE_TYPE f...
llama_index/llama-index-legacy/llama_index/legacy/query_engine/knowledge_graph_query_engine.py/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/query_engine/knowledge_graph_query_engine.py", "repo_id": "llama_index", "token_count": 5318 }
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""" This tool allows agents to interact with the clickup library and operate on a Clickup instance. To use this tool, you must first set as environment variables: client_secret client_id code Below is a sample script that uses the Clickup tool: ```python from langchain_community.agent_toolkits.clickup.too...
langchain/libs/community/langchain_community/tools/clickup/tool.py/0
{ "file_path": "langchain/libs/community/langchain_community/tools/clickup/tool.py", "repo_id": "langchain", "token_count": 402 }
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import logging from langchain.output_parsers.openai_tools import JsonOutputToolsParser from langchain_community.chat_models import ChatOpenAI from langchain_core.prompts import ChatPromptTemplate from langchain_core.runnables import RunnableLambda logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__...
langchain/templates/propositional-retrieval/propositional_retrieval/proposal_chain.py/0
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- sections: - local: index title: 🤗 Transformers - local: quicktour title: Tour rápido - local: installation title: Instalação title: Início - sections: - local: pipeline_tutorial title: Pipelines para inferência - local: training title: Fine-tuning de um modelo pré-treinado - local: ...
transformers/docs/source/pt/_toctree.yml/0
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"""Handle chained inputs.""" from typing import Dict, List, Optional, TextIO _TEXT_COLOR_MAPPING = { "blue": "36;1", "yellow": "33;1", "pink": "38;5;200", "green": "32;1", "red": "31;1", } def get_color_mapping( items: List[str], excluded_colors: Optional[List] = None ) -> Dict[str, str]: ...
langchain/libs/core/langchain_core/utils/input.py/0
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import sys from numpy import NaN from pymilvus import Partition sys.path.append("..") from check.func_check import ResponseChecker from utils.api_request import api_request from common.common_func import param_info TIMEOUT = 180 class ApiPartitionWrapper: partition = None def init_partition(self, collect...
milvus/tests/python_client/base/partition_wrapper.py/0
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"""Test Fireworks chat model""" import sys import pytest from langchain_core.pydantic_v1 import SecretStr from pytest import CaptureFixture from langchain_community.chat_models import ChatFireworks if sys.version_info < (3, 9): pytest.skip("fireworks-ai requires Python > 3.8", allow_module_level=True) @pytest...
langchain/libs/community/tests/unit_tests/chat_models/test_fireworks.py/0
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"""Init params."""
llama_index/llama-index-legacy/tests/indices/knowledge_graph/__init__.py/0
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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/proxy/task_search_test.go/0
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--- hide_table_of_contents: true sidebar_class_name: node-only --- # Couchbase [Couchbase](http://couchbase.com/) is an award-winning distributed NoSQL cloud database that delivers unmatched versatility, performance, scalability, and financial value for all of your cloud, mobile, AI, and edge computing applications. ...
langchainjs/docs/core_docs/docs/integrations/document_loaders/web_loaders/couchbase.mdx/0
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""" BlurPool layer inspired by - Kornia's Max_BlurPool2d - Making Convolutional Networks Shift-Invariant Again :cite:`zhang2019shiftinvar` Hacked together by Chris Ha and Ross Wightman """ import torch import torch.nn as nn import torch.nn.functional as F import numpy as np from .padding import get_padding class ...
pytorch-image-models/timm/layers/blur_pool.py/0
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python_sources()
llama_index/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/html/BUILD/0
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<!--Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/es/custom_models.md/0
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# Cohere >[Cohere](https://cohere.ai/about) is a Canadian startup that provides natural language processing models > that help companies improve human-machine interactions. ## Installation and Setup - Install the Python SDK : ```bash pip install cohere ``` Get a [Cohere api key](https://dashboard.cohere.ai/) and set...
langchain/docs/docs/integrations/providers/cohere.mdx/0
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/** From https://github.com/SidU/teams-langchain-js/wiki/Connecting-IFTTT-Services. # Creating a webhook - Go to https://ifttt.com/create # Configuring the "If This" - Click on the "If This" button in the IFTTT interface. - Search for "Webhooks" in the search bar. - Choose the first option for "Receive a web request ...
langchainjs/libs/langchain-community/src/tools/ifttt.ts/0
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from llama_index.core.vector_stores.types import VectorStore from llama_index.vector_stores.typesense import TypesenseVectorStore def test_class(): names_of_base_classes = [b.__name__ for b in TypesenseVectorStore.__mro__] assert VectorStore.__name__ in names_of_base_classes
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-typesense/tests/test_vector_stores_typesense.py/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-typesense/tests/test_vector_stores_typesense.py", "repo_id": "llama_index", "token_count": 92 }
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import ast import copy from types import CodeType, ModuleType from typing import Any, Dict, Mapping, Sequence, Union ALLOWED_IMPORTS = { "math", "time", "datetime", "pandas", "scipy", "numpy", "matplotlib", "plotly", "seaborn", } def _restricted_import( name: str, globals:...
llama_index/llama-index-core/llama_index/core/exec_utils.py/0
{ "file_path": "llama_index/llama-index-core/llama_index/core/exec_utils.py", "repo_id": "llama_index", "token_count": 1648 }
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"""Jira Toolkit."""
langchain/libs/community/langchain_community/agent_toolkits/jira/__init__.py/0
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<!--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/ja/model_doc/deplot.md/0
{ "file_path": "transformers/docs/source/ja/model_doc/deplot.md", "repo_id": "transformers", "token_count": 2027 }
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"""Test pandas index.""" import os import sys from pathlib import Path from typing import Any, Dict, cast import pandas as pd import pytest from llama_index.legacy.core.response.schema import Response from llama_index.legacy.indices.query.schema import QueryBundle from llama_index.legacy.indices.service_context impor...
llama_index/llama-index-legacy/tests/query_engine/test_pandas.py/0
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from chromadb.proto import chroma_pb2 as _chroma_pb2 from google.protobuf import empty_pb2 as _empty_pb2 from google.protobuf.internal import containers as _containers from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from typing import ClassVar as _ClassVar, Iterable...
chroma/chromadb/proto/coordinator_pb2.pyi/0
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/* eslint-disable no-promise-executor-return */ /* eslint-disable @typescript-eslint/no-explicit-any */ import { jest, test } from "@jest/globals"; import { AIMessage, AIMessageChunk, HumanMessage, SystemMessage, } from "../../messages/index.js"; import { RemoteRunnable } from "../remote.js"; import { ChatProm...
langchainjs/langchain-core/src/runnables/tests/runnable_remote.test.ts/0
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<!--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/unispeech-sat.md/0
{ "file_path": "transformers/docs/source/en/model_doc/unispeech-sat.md", "repo_id": "transformers", "token_count": 1045 }
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from __future__ import annotations import json import re from json import JSONDecodeError from typing import Any, Callable, List, Optional, Type import jsonpatch # type: ignore[import] from langchain_core.exceptions import OutputParserException from langchain_core.output_parsers.format_instructions import JSON_FORM...
langchain/libs/core/langchain_core/output_parsers/json.py/0
{ "file_path": "langchain/libs/core/langchain_core/output_parsers/json.py", "repo_id": "langchain", "token_count": 3270 }
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"""Summarization checker chain for verifying accuracy of text generation. Chain that tries to verify the accuracy of text generation by splitting it into a list of facts, then checking if those facts are true or not, and rewriting the text to make it more truth-ful. It will repeat this loop until it hits `max_tries` ...
langchain/libs/langchain/langchain/chains/llm_summarization_checker/__init__.py/0
{ "file_path": "langchain/libs/langchain/langchain/chains/llm_summarization_checker/__init__.py", "repo_id": "langchain", "token_count": 87 }
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--- aFloat: 13.12345 anInt: 15 aBool: true aString: string value anArray: - one - two - three aDict: dictId1: "58417" dictId2: 1500 tags: ["onetag", "twotag"] --- # Tags ()#notatag #12345 #read something #tagWithCases - #tag-with-dash #tag_with_underscore #tag/with/nesting # Dataview Here is some data ...
langchainjs/langchain/src/document_loaders/tests/example_data/obsidian/tags_and_frontmatter.md/0
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import { z } from "zod"; import { zodToJsonSchema } from "zod-to-json-schema"; import { ChatOpenAI } from "@langchain/openai"; import { JsonOutputFunctionsParser } from "langchain/output_parsers"; import { ChatPromptTemplate } from "@langchain/core/prompts"; const schema = z.object({ setup: z.string().describe("The ...
langchainjs/examples/src/prompts/json_structured_output_parser_streaming.ts/0
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import logging.config from datetime import datetime import os import yaml import config cur_path = os.path.abspath(os.path.dirname(__file__)) LOG_CONFIG_PATH = cur_path + "/logging.yaml" FILE_NAME = config.LOG_PATH + 'benchmark-{:%Y-%m-%d}.log'.format(datetime.now()) def setup_logging(config_path=LOG_CONFIG_PATH, de...
milvus/tests/benchmark/milvus_benchmark/logs/log.py/0
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// Code generated by command: go run l2.go -out l2_amd64.s -stubs l2_stub_amd64.go. DO NOT EDIT. package asm // squared l2 between x and y func L2(x []float32, y []float32) float32
milvus/pkg/util/distance/asm/l2_stub_amd64.go/0
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# coding=utf-8 # Copyright 2023 Microsoft Research 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/L...
transformers/src/transformers/models/kosmos2/modeling_kosmos2.py/0
{ "file_path": "transformers/src/transformers/models/kosmos2/modeling_kosmos2.py", "repo_id": "transformers", "token_count": 41274 }
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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/PlanProto.cpp/0
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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/pkg/util/metric/metric_type.go/0
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# This is a Dockerfile for the Development Container # Use the Python base image ARG VARIANT="3.11-bullseye" FROM mcr.microsoft.com/devcontainers/python:0-${VARIANT} AS langchain-dev-base USER vscode # Define the version of Poetry to install (default is 1.4.2) # Define the directory of python virtual environment ARG...
langchain/libs/langchain/dev.Dockerfile/0
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<jupyter_start><jupyter_text>Passthrough informationAn example that shows how to pass through additional info with the request, and get it back with the response.<jupyter_code>from langchain.prompts.chat import ChatPromptTemplate from langserve import RemoteRunnable chain = RemoteRunnable("http://localhost:8000/v1/")<...
langserve/examples/passthrough_dict/client.ipynb/0
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"""Test optimization.""" from typing import Any, List from unittest.mock import patch from llama_index.core.embeddings.mock_embed_model import MockEmbedding from llama_index.core.postprocessor.optimizer import SentenceEmbeddingOptimizer from llama_index.core.schema import NodeWithScore, QueryBundle, TextNode def mo...
llama_index/llama-index-core/tests/postprocessor/test_optimizer.py/0
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from langchain_core.callbacks.manager import ( AsyncCallbackManager, AsyncCallbackManagerForChainGroup, AsyncCallbackManagerForChainRun, AsyncCallbackManagerForLLMRun, AsyncCallbackManagerForRetrieverRun, AsyncCallbackManagerForToolRun, AsyncParentRunManager, AsyncRunManager, BaseRun...
langchain/libs/langchain/langchain/schema/callbacks/manager.py/0
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/** * Checks if the provided argument is an object and not an array. */ // eslint-disable-next-line @typescript-eslint/no-explicit-any export function isObject(obj: any): obj is object { return obj && typeof obj === "object" && !Array.isArray(obj); } /** * Checks if a provided filter is empty. The filter can be a...
langchainjs/langchain/src/retrievers/self_query/utils.ts/0
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# Sitemap Loader This loader is an asynchronous web scraper that fetches the text from static websites by using its sitemap and optionally converting the HTML to text. It is based on the [Async Website Loader](https://llama-hub-ui.vercel.app/l/web-async_web) ## Usage To use this loader, you just declare the sitemap...
llama_index/llama-index-integrations/readers/llama-index-readers-web/llama_index/readers/web/sitemap/README.md/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::{Error as E, Result}; use clap::{Parser, ValueEnum}; use candle_transformers::models::mixformer::{Config, MixFormerSequentialForCausalLM as MixFormer}; use candle_transformers::models::phi::{Co...
candle/candle-examples/examples/phi/main.rs/0
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import { initializeAgentExecutorWithOptions } from "langchain/agents"; import { ChatOpenAI } from "@langchain/openai"; import { Calculator } from "langchain/tools/calculator"; import { SerpAPI } from "@langchain/community/tools/serpapi"; export const run = async () => { const model = new ChatOpenAI({ temperature: 0 ...
langchainjs/examples/src/agents/chat_mrkl.ts/0
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from typing import Any, Dict, List, Optional, Tuple from google.cloud.firestore_v1.async_client import AsyncClient from google.cloud.firestore_v1.client import Client from google.cloud.firestore_v1.services.firestore.transports.base import ( DEFAULT_CLIENT_INFO, ) from llama_index.core.storage.kvstore.types import...
llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-firestore/llama_index/storage/kvstore/firestore/base.py/0
{ "file_path": "llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-firestore/llama_index/storage/kvstore/firestore/base.py", "repo_id": "llama_index", "token_count": 3391 }
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import pickle as pkl import unittest from dataclasses import dataclass from typing import List, Union import numpy as np import PIL.Image from diffusers.utils.outputs import BaseOutput from diffusers.utils.testing_utils import require_torch @dataclass class CustomOutput(BaseOutput): images: Union[List[PIL.Image...
diffusers/tests/others/test_outputs.py/0
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267
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/src/transformers/models/mvp/__init__.py/0
{ "file_path": "transformers/src/transformers/models/mvp/__init__.py", "repo_id": "transformers", "token_count": 983 }
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<jupyter_start><jupyter_text>Vector Store Index usage examplesIn this guide, we show how to use the vector store index with different vector storeimplementations. From how to get started with few lines of code with the defaultin-memory vector store with default query configuration, to using a custom hosted vectorstor...
llama_index/docs/module_guides/indexing/vector_store_guide.ipynb/0
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from time import sleep from pymilvus import connections, list_collections, utility from chaos.checker import (CollectionCreateChecker, InsertFlushChecker, SearchChecker, QueryChecker, IndexCreateChecker, Op) from common.milvus_sys import MilvusSys from utils.util_log import test_log as log fr...
milvus/tests/python_client/loadbalance/test_auto_load_balance.py/0
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from langchain_community.document_loaders.joplin import JoplinLoader def test_joplin_loader() -> None: loader = JoplinLoader() docs = loader.load() assert isinstance(docs, list) assert isinstance(docs[0].page_content, str) assert isinstance(docs[0].metadata["source"], str) assert isinstance(d...
langchain/libs/community/tests/integration_tests/document_loaders/test_joplin.py/0
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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 ...
transformers/docs/source/ko/model_memory_anatomy.md/0
{ "file_path": "transformers/docs/source/ko/model_memory_anatomy.md", "repo_id": "transformers", "token_count": 8869 }
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# LlamaIndex Readers Integration: Json
llama_index/llama-index-integrations/readers/llama-index-readers-json/README.md/0
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python_sources()
llama_index/llama-index-integrations/readers/llama-index-readers-zep/llama_index/readers/zep/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zep/llama_index/readers/zep/BUILD", "repo_id": "llama_index", "token_count": 6 }
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<jupyter_start><jupyter_text>Building Data Ingestion from ScratchIn this tutorial, we show you how to build a data ingestion pipeline into a vector database.We use Pinecone as the vector database.We will show how to do the following:1. How to load in documents.2. How to use a text splitter to split documents.3. How to ...
llama_index/docs/examples/low_level/ingestion.ipynb/0
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# coding=utf-8 # Copyright 2023 The Suno AI Authors and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/...
transformers/src/transformers/models/bark/processing_bark.py/0
{ "file_path": "transformers/src/transformers/models/bark/processing_bark.py", "repo_id": "transformers", "token_count": 6074 }
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import pytest from langchain_community.document_loaders import UnstructuredURLLoader def test_continue_on_failure_true() -> None: """Test exception is not raised when continue_on_failure=True.""" loader = UnstructuredURLLoader(["badurl.foobar"]) loader.load() def test_continue_on_failure_false() -> Non...
langchain/libs/community/tests/integration_tests/document_loaders/test_url.py/0
{ "file_path": "langchain/libs/community/tests/integration_tests/document_loaders/test_url.py", "repo_id": "langchain", "token_count": 184 }
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