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# Modal This page covers how to use the Modal ecosystem to run LangChain custom LLMs. It is broken into two parts: 1. Modal installation and web endpoint deployment 2. Using deployed web endpoint with `LLM` wrapper class. ## Installation and Setup - Install with `pip install modal` - Run `modal token new` ## Defi...
langchain/docs/docs/integrations/providers/modal.mdx/0
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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/zh/quicktour.md/0
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// @ts-nocheck // Inlined to deal with portability issues // Originally from: https://github.com/isaacs/sax-js const initializeSax = function () { const sax: any = {}; sax.parser = function (strict, opt) { return new SAXParser(strict, opt); }; sax.SAXParser = SAXParser; sax.SAXStream = SAXStream; sax....
langchainjs/langchain-core/src/utils/sax-js/sax.ts/0
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from langchain_community.callbacks.arthur_callback import ( ArthurCallbackHandler, ) __all__ = [ "ArthurCallbackHandler", ]
langchain/libs/langchain/langchain/callbacks/arthur_callback.py/0
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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...
transformers/tests/models/owlvit/test_processor_owlvit.py/0
{ "file_path": "transformers/tests/models/owlvit/test_processor_owlvit.py", "repo_id": "transformers", "token_count": 4354 }
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import { NextRequest, NextResponse } from "next/server"; import { ChatWindowMessage } from "@/schema/ChatWindowMessage"; import { ChatOpenAI } from "langchain/chat_models/openai"; import { BytesOutputParser } from "langchain/schema/output_parser"; import { PromptTemplate } from "langchain/prompts"; export const runti...
langsmith-cookbook/feedback-examples/nextjs/app/api/chat/route.ts/0
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from typing import Any from unittest.mock import patch import pytest from llama_index.core.base.response.schema import Response from llama_index.core.query_engine.cogniswitch_query_engine import ( CogniswitchQueryEngine, ) @pytest.fixture() def query_engine() -> CogniswitchQueryEngine: return CogniswitchQuer...
llama_index/llama-index-core/tests/query_engine/test_cogniswitch_query_engine.py/0
{ "file_path": "llama_index/llama-index-core/tests/query_engine/test_cogniswitch_query_engine.py", "repo_id": "llama_index", "token_count": 409 }
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"""Module for fetching data from the SEC EDGAR Archives.""" import json import os import re import sys from typing import List, Optional, Tuple, Union import requests if sys.version_info < (3, 8): # noqa: UP036 from typing import Final else: from typing import Final import webbrowser try: from ratelim...
llama_index/llama-index-integrations/readers/llama-index-readers-sec-filings/llama_index/readers/sec_filings/prepline_sec_filings/fetch.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-sec-filings/llama_index/readers/sec_filings/prepline_sec_filings/fetch.py", "repo_id": "llama_index", "token_count": 3355 }
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"""Load agent.""" from typing import Any, Optional, Sequence from langchain_core._api import deprecated from langchain_core.callbacks import BaseCallbackManager from langchain_core.language_models import BaseLanguageModel from langchain_core.tools import BaseTool from langchain.agents.agent import AgentExecutor from ...
langchain/libs/langchain/langchain/agents/initialize.py/0
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""" CUDA / AMP utils Hacked together by / Copyright 2020 Ross Wightman """ import torch try: from apex import amp has_apex = True except ImportError: amp = None has_apex = False from .clip_grad import dispatch_clip_grad class ApexScaler: state_dict_key = "amp" def __call__( sel...
pytorch-image-models/timm/utils/cuda.py/0
{ "file_path": "pytorch-image-models/timm/utils/cuda.py", "repo_id": "pytorch-image-models", "token_count": 980 }
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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/pt/custom_models.md/0
{ "file_path": "transformers/docs/source/pt/custom_models.md", "repo_id": "transformers", "token_count": 5915 }
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# coding=utf-8 # Copyright 2022 The Salesforce authors, 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/l...
transformers/src/transformers/models/codegen/tokenization_codegen.py/0
{ "file_path": "transformers/src/transformers/models/codegen/tokenization_codegen.py", "repo_id": "transformers", "token_count": 6731 }
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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...
accelerate/tests/test_examples.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/core/unittest/test_chunk_cache.cpp/0
{ "file_path": "milvus/internal/core/unittest/test_chunk_cache.cpp", "repo_id": "milvus", "token_count": 2722 }
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python_tests()
llama_index/llama-index-packs/llama-index-packs-streamlit-chatbot/tests/BUILD/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-streamlit-chatbot/tests/BUILD", "repo_id": "llama_index", "token_count": 5 }
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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/src/transformers/utils/model_parallel_utils.py/0
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from llama_index.packs.arize_phoenix_query_engine.base import ( ArizePhoenixQueryEnginePack, ) __all__ = ["ArizePhoenixQueryEnginePack"]
llama_index/llama-index-packs/llama-index-packs-arize-phoenix-query-engine/llama_index/packs/arize_phoenix_query_engine/__init__.py/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-arize-phoenix-query-engine/llama_index/packs/arize_phoenix_query_engine/__init__.py", "repo_id": "llama_index", "token_count": 49 }
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python_sources()
llama_index/llama-index-integrations/llms/llama-index-llms-openrouter/llama_index/llms/openrouter/BUILD/0
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from typing import Any, List, Optional from langchain_core.language_models import BaseLanguageModel from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate from langchain_core.pydantic_v1 import BaseModel from langchain.chains.base import Chain from langchain.chains.llm import LLMChain from langchai...
langchain/libs/langchain/langchain/chains/openai_functions/extraction.py/0
{ "file_path": "langchain/libs/langchain/langchain/chains/openai_functions/extraction.py", "repo_id": "langchain", "token_count": 1548 }
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import CodeBlock from "@theme/CodeBlock"; import TimeoutExample from "@examples/models/chat/chat_timeout.ts"; # Adding a timeout By default, LangChain will wait indefinitely for a response from the model provider. If you want to add a timeout, you can pass a `timeout` option, in milliseconds, when you call the model....
langchainjs/docs/core_docs/docs/modules/model_io/chat/timeouts.mdx/0
{ "file_path": "langchainjs/docs/core_docs/docs/modules/model_io/chat/timeouts.mdx", "repo_id": "langchainjs", "token_count": 170 }
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import os from langchain.text_splitter import RecursiveCharacterTextSplitter from langchain_community.chat_models import ChatOpenAI from langchain_community.document_loaders import PyPDFLoader from langchain_community.embeddings import OpenAIEmbeddings from langchain_community.vectorstores import MongoDBAtlasVectorSea...
langchain/templates/rag-mongo/rag_mongo/chain.py/0
{ "file_path": "langchain/templates/rag-mongo/rag_mongo/chain.py", "repo_id": "langchain", "token_count": 825 }
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import { Document } from "@langchain/core/documents"; import { SearchApiLoader } from "../web/searchapi.js"; test("Test buildUrl method without engine", () => { const loader = new SearchApiLoader({ apiKey: "ApiKey", q: "Query" }); expect(loader.buildUrl()).toBe( "https://www.searchapi.io/api/v1/search?engine=...
langchainjs/langchain/src/document_loaders/tests/searchapi.test.ts/0
{ "file_path": "langchainjs/langchain/src/document_loaders/tests/searchapi.test.ts", "repo_id": "langchainjs", "token_count": 426 }
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[package] name = "candle-examples" version.workspace = true edition.workspace = true description.workspace = true repository.workspace = true keywords.workspace = true categories.workspace = true license.workspace = true readme = "README.md" [dependencies] accelerate-src = { workspace = true, optional = true } candle ...
candle/candle-examples/Cargo.toml/0
{ "file_path": "candle/candle-examples/Cargo.toml", "repo_id": "candle", "token_count": 946 }
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import { test, expect } from "@jest/globals"; import Exa from "exa-js"; import { ExaFindSimilarResults, ExaSearchResults } from "../tools.js"; test("ExaSearchResults can perform a search given a string query", async () => { const exaTool = new ExaSearchResults<{ text: true }>({ // @ts-expect-error type errors ...
langchainjs/libs/langchain-exa/src/tests/tools.int.test.ts/0
{ "file_path": "langchainjs/libs/langchain-exa/src/tests/tools.int.test.ts", "repo_id": "langchainjs", "token_count": 373 }
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from llama_index.core.readers.base import BaseReader from llama_index.readers.pinecone import PineconeReader def test_class(): names_of_base_classes = [b.__name__ for b in PineconeReader.__mro__] assert BaseReader.__name__ in names_of_base_classes
llama_index/llama-index-integrations/readers/llama-index-readers-pinecone/tests/test_readers_pinecone.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-pinecone/tests/test_readers_pinecone.py", "repo_id": "llama_index", "token_count": 88 }
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from langchain_astradb import __all__ EXPECTED_ALL = [ "AstraDBVectorStore", ] def test_all_imports() -> None: assert sorted(EXPECTED_ALL) == sorted(__all__)
langchain/libs/partners/astradb/tests/unit_tests/test_imports.py/0
{ "file_path": "langchain/libs/partners/astradb/tests/unit_tests/test_imports.py", "repo_id": "langchain", "token_count": 67 }
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import { expect, test } from "@jest/globals"; import { z } from "zod"; import { OpenAI, ChatOpenAI } from "@langchain/openai"; import { ChatPromptTemplate, PromptTemplate, SystemMessagePromptTemplate, } from "@langchain/core/prompts"; import { LLMChain } from "../../chains/index.js"; import { StructuredOutputPar...
langchainjs/langchain/src/output_parsers/tests/structured.int.test.ts/0
{ "file_path": "langchainjs/langchain/src/output_parsers/tests/structured.int.test.ts", "repo_id": "langchainjs", "token_count": 2115 }
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from typing import Generator import pytest from llama_index.legacy.storage.kvstore.s3_kvstore import S3DBKVStore try: import boto3 from moto import mock_s3 has_boto_libs = True except ImportError: has_boto_libs = False @pytest.fixture() def kvstore_from_mocked_bucket() -> Generator[S3DBKVStore, Non...
llama_index/llama-index-legacy/tests/storage/kvstore/test_s3_kvstore.py/0
{ "file_path": "llama_index/llama-index-legacy/tests/storage/kvstore/test_s3_kvstore.py", "repo_id": "llama_index", "token_count": 1476 }
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<jupyter_start><jupyter_text>Apache CassandraThis page provides a quickstart for using [Apache Cassandra®](https://cassandra.apache.org/) as a Vector Store. > [Cassandra](https://cassandra.apache.org/) is a NoSQL, row-oriented, highly scalable and highly available database.Starting with version 5.0, the database ships ...
langchain/docs/docs/integrations/vectorstores/cassandra.ipynb/0
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from operator import itemgetter from typing import Literal from langchain.output_parsers.openai_functions import PydanticAttrOutputFunctionsParser from langchain.retrievers import ( ArxivRetriever, KayAiRetriever, PubMedRetriever, WikipediaRetriever, ) from langchain.schema import StrOutputParser from ...
langchain/templates/rag-multi-index-router/rag_multi_index_router/chain.py/0
{ "file_path": "langchain/templates/rag-multi-index-router/rag_multi_index_router/chain.py", "repo_id": "langchain", "token_count": 1234 }
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from typing import TYPE_CHECKING from ...utils import DIFFUSERS_SLOW_IMPORT, _LazyModule _import_structure = {"pipeline_dit": ["DiTPipeline"]} if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: from .pipeline_dit import DiTPipeline else: import sys sys.modules[__name__] = _LazyModule( __name__, ...
diffusers/src/diffusers/pipelines/dit/__init__.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/dit/__init__.py", "repo_id": "diffusers", "token_count": 177 }
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import io import itertools import json from dataclasses import dataclass from typing import Optional import pyarrow as pa import pyarrow.json as paj import datasets from datasets.table import table_cast from datasets.utils.file_utils import readline logger = datasets.utils.logging.get_logger(__name__) @dataclass ...
datasets/src/datasets/packaged_modules/json/json.py/0
{ "file_path": "datasets/src/datasets/packaged_modules/json/json.py", "repo_id": "datasets", "token_count": 4907 }
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python_sources()
llama_index/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/paged_csv/BUILD/0
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import random from typing import ( Any, Dict, Optional, Sequence, ) from llama_index.core.bridge.pydantic import Field, PrivateAttr from llama_index.core.callbacks import CallbackManager from llama_index.core.llms.base import ( ChatMessage, ChatResponse, ChatResponseAsyncGen, ChatRespon...
llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-triton/llama_index/llms/nvidia_triton/base.py/0
{ "file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-triton/llama_index/llms/nvidia_triton/base.py", "repo_id": "llama_index", "token_count": 3580 }
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//! The shape of a tensor is a tuple with the size of each of its dimensions. #![allow(clippy::redundant_closure_call)] use crate::{Error, Result}; #[derive(Clone, PartialEq, Eq)] pub struct Shape(Vec<usize>); pub const SCALAR: Shape = Shape(vec![]); impl std::fmt::Debug for Shape { fn fmt(&self, f: &mut std::fm...
candle/candle-core/src/shape.rs/0
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from pathlib import Path import pytest from langchain_community.document_loaders.concurrent import ConcurrentLoader from langchain_community.document_loaders.generic import GenericLoader from langchain_community.document_loaders.parsers import LanguageParser def test_language_loader_for_python() -> None: """Tes...
langchain/libs/community/tests/integration_tests/document_loaders/parsers/test_language.py/0
{ "file_path": "langchain/libs/community/tests/integration_tests/document_loaders/parsers/test_language.py", "repo_id": "langchain", "token_count": 2008 }
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import json import tempfile from copy import deepcopy from pathlib import Path from typing import Any, Dict, List, Optional, Sequence, Union from langchain_core.agents import AgentAction, AgentFinish from langchain_core.callbacks import BaseCallbackHandler from langchain_core.outputs import LLMResult from langchain_c...
langchain/libs/community/langchain_community/callbacks/wandb_callback.py/0
{ "file_path": "langchain/libs/community/langchain_community/callbacks/wandb_callback.py", "repo_id": "langchain", "token_count": 9834 }
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package kafka import ( "bytes" "context" "encoding/binary" "fmt" "math/rand" "os" "testing" "time" "github.com/confluentinc/confluent-kafka-go/kafka" "github.com/stretchr/testify/assert" "go.uber.org/zap" "github.com/milvus-io/milvus/pkg/common" "github.com/milvus-io/milvus/pkg/config" "github.com/milv...
milvus/pkg/mq/msgstream/mqwrapper/kafka/kafka_client_test.go/0
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# coding=utf-8 # Copyright 2022 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/models/mask2former/test_image_processing_mask2former.py/0
{ "file_path": "transformers/tests/models/mask2former/test_image_processing_mask2former.py", "repo_id": "transformers", "token_count": 10079 }
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[ { "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 1, "logprob": null, "text": "<s>" }, { "id": 1724, "logprob": -7.6914062, "text": "What" ...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_awq_sharded/test_flash_llama_awq_load_sharded.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_awq_sharded/test_flash_llama_awq_load_sharded.json", "repo_id": "text-generation-inference", "token_count": 5776 }
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"""All tests for this package."""
langchain/libs/langchain/tests/__init__.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 agreed...
transformers/docs/source/ja/main_classes/quantization.md/0
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import { OpenAIEmbeddings } from "@langchain/openai"; const embeddings = new OpenAIEmbeddings({ modelName: "text-embedding-3-large", }); const vectors = await embeddings.embedDocuments(["some text"]); console.log(vectors[0].length); const embeddings1024 = new OpenAIEmbeddings({ modelName: "text-embedding-3-large...
langchainjs/examples/src/embeddings/openai_dimensions.ts/0
{ "file_path": "langchainjs/examples/src/embeddings/openai_dimensions.ts", "repo_id": "langchainjs", "token_count": 152 }
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from typing import ClassVar, Dict, Optional, Sequence from uuid import UUID import uuid from overrides import override import requests from chromadb.api import AdminAPI, ClientAPI, ServerAPI from chromadb.api.types import ( CollectionMetadata, DataLoader, Documents, Embeddable, EmbeddingFunction, ...
chroma/chromadb/api/client.py/0
{ "file_path": "chroma/chromadb/api/client.py", "repo_id": "chroma", "token_count": 6688 }
13
package httpserver import ( "encoding/binary" "encoding/json" "fmt" "math" "github.com/cockroachdb/errors" "github.com/golang/protobuf/proto" "github.com/milvus-io/milvus-proto/go-api/v2/commonpb" "github.com/milvus-io/milvus-proto/go-api/v2/milvuspb" "github.com/milvus-io/milvus-proto/go-api/v2/schemapb" )...
milvus/internal/distributed/proxy/httpserver/wrap_request.go/0
{ "file_path": "milvus/internal/distributed/proxy/httpserver/wrap_request.go", "repo_id": "milvus", "token_count": 5515 }
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/src/transformers/models/swinv2/configuration_swinv2.py/0
{ "file_path": "transformers/src/transformers/models/swinv2/configuration_swinv2.py", "repo_id": "transformers", "token_count": 2994 }
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from typing import Any, Dict, List, Optional import requests from langchain_core.embeddings import Embeddings from langchain_core.pydantic_v1 import BaseModel, SecretStr, root_validator from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env BAICHUAN_API_URL: str = "http://api.baichuan-ai.com/v1/...
langchain/libs/community/langchain_community/embeddings/baichuan.py/0
{ "file_path": "langchain/libs/community/langchain_community/embeddings/baichuan.py", "repo_id": "langchain", "token_count": 1990 }
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# Copyright 2024 The Intel Labs Team Authors and the HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 ...
diffusers/examples/community/pipeline_stable_diffusion_upscale_ldm3d.py/0
{ "file_path": "diffusers/examples/community/pipeline_stable_diffusion_upscale_ldm3d.py", "repo_id": "diffusers", "token_count": 17030 }
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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 = ["SelfRAGPack", "SelfRAGQueryEngine"] contains_example = false import_path = "llama_index.p...
llama_index/llama-index-packs/llama-index-packs-self-rag/pyproject.toml/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-self-rag/pyproject.toml", "repo_id": "llama_index", "token_count": 684 }
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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/lora/gptq.py/0
{ "file_path": "peft/src/peft/tuners/lora/gptq.py", "repo_id": "peft", "token_count": 1509 }
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import argparse import logging import os import random import sys from datasets import load_from_disk from sklearn.metrics import accuracy_score, precision_recall_fscore_support import torch from transformers import AutoModelForSequenceClassification, Trainer, TrainingArguments, AutoTokenizer if __name__ == "__main_...
notebooks/sagemaker/06_sagemaker_metrics/scripts/train.py/0
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from llama_index.vector_stores.postgres.base import PGVectorStore __all__ = ["PGVectorStore"]
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-postgres/llama_index/vector_stores/postgres/__init__.py/0
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#include "binary_op_macros.cuh" #include<stdint.h> #if __CUDA_ARCH__ >= 800 BINARY_OP(__nv_bfloat16, badd_bf16, x + y) BINARY_OP(__nv_bfloat16, bdiv_bf16, x / y) BINARY_OP(__nv_bfloat16, bmul_bf16, x * y) BINARY_OP(__nv_bfloat16, bsub_bf16, x - y) BINARY_OP(__nv_bfloat16, bmaximum_bf16, maxg(x, y)) BINARY_OP(__nv_bflo...
candle/candle-kernels/src/binary.cu/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/querycoordv2/balance/utils.go/0
{ "file_path": "milvus/internal/querycoordv2/balance/utils.go", "repo_id": "milvus", "token_count": 2645 }
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# coding=utf-8 # Copyright 2021 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/feature_extraction_utils.py/0
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//! Attention Based Building Blocks use candle::{DType, IndexOp, Result, Tensor, D}; use candle_nn as nn; use candle_nn::Module; #[derive(Debug)] struct GeGlu { proj: nn::Linear, span: tracing::Span, } impl GeGlu { fn new(vs: nn::VarBuilder, dim_in: usize, dim_out: usize) -> Result<Self> { let pro...
candle/candle-transformers/src/models/stable_diffusion/attention.rs/0
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# coding=utf-8 # Copyright 2022 ABEJA, Inc. 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-...
transformers/src/transformers/models/gpt_neox_japanese/modeling_gpt_neox_japanese.py/0
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"""Test Hologres functionality.""" import os from typing import List from langchain_core.documents import Document from langchain_community.vectorstores.hologres import Hologres from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings CONNECTION_STRING = Hologres.connection_string_from_db_para...
langchain/libs/community/tests/integration_tests/vectorstores/test_hologres.py/0
{ "file_path": "langchain/libs/community/tests/integration_tests/vectorstores/test_hologres.py", "repo_id": "langchain", "token_count": 2178 }
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// Generated by modified Perl script at https://github.com/google/sentencepiece/blob/master/data/gen_unicode_scripts_code.pl // Unicode scripts : https://gist.github.com/Narsil/07556f26dc84a6baeff4d499e68d3cd2 // Rust adaptation : https://gist.github.com/Narsil/1df9fbbf5296a8d4d62de55dcb2fe700 #[derive(PartialEq, Debu...
tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/scripts.rs/0
{ "file_path": "tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/scripts.rs", "repo_id": "tokenizers", "token_count": 46440 }
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"""Wrapper around Minimax APIs.""" from __future__ import annotations import logging from typing import ( Any, Dict, List, Optional, ) import requests from langchain_core.callbacks import ( CallbackManagerForLLMRun, ) from langchain_core.language_models.llms import LLM from langchain_core.pydantic...
langchain/libs/community/langchain_community/llms/minimax.py/0
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is_thin_client = True
chroma/clients/python/is_thin_client.py/0
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33
{ "compilerOptions": { "target": "ESNext", "useDefineForClassFields": true, "module": "ESNext", "lib": ["ESNext", "DOM"], "moduleResolution": "Node", "strict": true, "resolveJsonModule": true, "isolatedModules": true, "esModuleInterop": true, "noEmit": true, "noUnusedLocals...
langchainjs/environment_tests/test-exports-vite/tsconfig.json/0
{ "file_path": "langchainjs/environment_tests/test-exports-vite/tsconfig.json", "repo_id": "langchainjs", "token_count": 191 }
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from llama_index.core.llms.base import BaseLLM from llama_index.llms.mistralai import MistralAI def test_embedding_class(): names_of_base_classes = [b.__name__ for b in MistralAI.__mro__] assert BaseLLM.__name__ in names_of_base_classes
llama_index/llama-index-integrations/llms/llama-index-llms-mistralai/tests/test_llms_mistral.py/0
{ "file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-mistralai/tests/test_llms_mistral.py", "repo_id": "llama_index", "token_count": 94 }
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try: from torch import _assert except ImportError: def _assert(condition: bool, message: str): assert condition, message def _float_to_int(x: float) -> int: """ Symbolic tracing helper to substitute for inbuilt `int`. Hint: Inbuilt `int` can't accept an argument of type `Proxy` """ ...
pytorch-image-models/timm/layers/trace_utils.py/0
{ "file_path": "pytorch-image-models/timm/layers/trace_utils.py", "repo_id": "pytorch-image-models", "token_count": 119 }
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package utils import ( "testing" "github.com/stretchr/testify/assert" ) func TestSplitBySeparator(t *testing.T) { tsKey := "435783141193354561_ts435783141193154564" k, ts, err := SplitBySeparator(tsKey) assert.NoError(t, err) assert.Equal(t, "435783141193354561", k) assert.Equal(t, Timestamp(43578314119315456...
milvus/cmd/tools/migration/utils/util_test.go/0
{ "file_path": "milvus/cmd/tools/migration/utils/util_test.go", "repo_id": "milvus", "token_count": 406 }
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from pathlib import Path import pytest from langchain_community.document_loaders.mhtml import MHTMLLoader HERE = Path(__file__).parent EXAMPLES = HERE.parent.parent / "integration_tests" / "examples" @pytest.mark.requires("bs4", "lxml") def test_mhtml_loader() -> None: """Test mhtml loader.""" file_path = ...
langchain/libs/community/tests/unit_tests/document_loaders/test_mhtml.py/0
{ "file_path": "langchain/libs/community/tests/unit_tests/document_loaders/test_mhtml.py", "repo_id": "langchain", "token_count": 245 }
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import { JSDOM, VirtualConsole } from "jsdom"; export async function searchWebLocal(query: string) { const abortController = new AbortController(); setTimeout(() => abortController.abort(), 10000); const htmlString = await fetch("https://www.google.com/search?hl=en&q=" + query, { signal: abortController.signal, ...
chat-ui/src/lib/server/websearch/searchWebLocal.ts/0
{ "file_path": "chat-ui/src/lib/server/websearch/searchWebLocal.ts", "repo_id": "chat-ui", "token_count": 438 }
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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/util/interceptor/server_id_interceptor.go/0
{ "file_path": "milvus/pkg/util/interceptor/server_id_interceptor.go", "repo_id": "milvus", "token_count": 1203 }
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package tasks import ( "context" "fmt" "math/rand" "testing" "time" "github.com/stretchr/testify/assert" "github.com/stretchr/testify/suite" "go.uber.org/atomic" "github.com/milvus-io/milvus/pkg/util/conc" "github.com/milvus-io/milvus/pkg/util/lifetime" "github.com/milvus-io/milvus/pkg/util/paramtable" ) ...
milvus/internal/querynodev2/tasks/concurrent_safe_scheduler_test.go/0
{ "file_path": "milvus/internal/querynodev2/tasks/concurrent_safe_scheduler_test.go", "repo_id": "milvus", "token_count": 1549 }
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import pytest from llama_index.legacy.core.llms.types import ChatMessage, MessageRole from llama_index.legacy.llms.anthropic_utils import ( anthropic_modelname_to_contextsize, messages_to_anthropic_prompt, ) def test_messages_to_anthropic_prompt() -> None: messages = [ ChatMessage(role=MessageRole...
llama_index/llama-index-legacy/tests/llms/test_anthropic_utils.py/0
{ "file_path": "llama_index/llama-index-legacy/tests/llms/test_anthropic_utils.py", "repo_id": "llama_index", "token_count": 365 }
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<jupyter_start><jupyter_text>Plan-and-executePlan-and-execute agents accomplish an objective by first planning what to do, then executing the sub tasks. This idea is largely inspired by [BabyAGI](https://github.com/yoheinakajima/babyagi) and then the ["Plan-and-Solve" paper](https://arxiv.org/abs/2305.04091).The planni...
langchain/cookbook/plan_and_execute_agent.ipynb/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/mobilevit/test_modeling_tf_mobilevit.py/0
{ "file_path": "transformers/tests/models/mobilevit/test_modeling_tf_mobilevit.py", "repo_id": "transformers", "token_count": 7977 }
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import logging import os import sys from dataclasses import dataclass, field from typing import List, Optional import torch from datasets import Dataset from torch import nn from tqdm.auto import tqdm from transformers import ( AutoModelForSequenceClassification, AutoTokenizer, HfArgumentParser, Train...
transformers/examples/research_projects/zero-shot-distillation/distill_classifier.py/0
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<jupyter_start><jupyter_text>SQL Join Query EngineIn this tutorial, we show you how to use our SQLJoinQueryEngine.This query engine allows you to combine insights from your structured tables with your unstructured data.It first decides whether to query your structured tables for insights.Once it does, it can then infer...
llama_index/docs/examples/query_engine/SQLJoinQueryEngine.ipynb/0
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import json from typing import List, Sequence, Tuple from langchain_core.agents import AgentAction from langchain_core.messages import ( AIMessage, BaseMessage, ToolMessage, ) from langchain.agents.output_parsers.openai_tools import OpenAIToolAgentAction def _create_tool_message( agent_action: OpenA...
langchain/libs/langchain/langchain/agents/format_scratchpad/openai_tools.py/0
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"""Base types for ReAct agent.""" from abc import abstractmethod from typing import Dict from llama_index.legacy.bridge.pydantic import BaseModel class BaseReasoningStep(BaseModel): """Reasoning step.""" @abstractmethod def get_content(self) -> str: """Get content.""" @property @abstra...
llama_index/llama-index-legacy/llama_index/legacy/agent/react/types.py/0
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# coding=utf-8 # Copyright 2022 NVIDIA and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Un...
transformers/src/transformers/models/groupvit/modeling_tf_groupvit.py/0
{ "file_path": "transformers/src/transformers/models/groupvit/modeling_tf_groupvit.py", "repo_id": "transformers", "token_count": 39518 }
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[tool.poetry] name = "csv-agent" version = "0.0.1" description = "Analyze csv data with Pandas and OpenAI" authors = [] readme = "README.md" [tool.poetry.dependencies] python = ">=3.9,<3.13" langchain = "^0.1" openai = "<2" tiktoken = "^0.5.1" faiss-cpu = "^1.7.4" pandas = "^2.1.1" setuptools = "^68.2.2" tabulate = "^...
langchain/templates/csv-agent/pyproject.toml/0
{ "file_path": "langchain/templates/csv-agent/pyproject.toml", "repo_id": "langchain", "token_count": 338 }
641
python_tests()
llama_index/llama-index-packs/llama-index-packs-rag-cli-local/tests/BUILD/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-rag-cli-local/tests/BUILD", "repo_id": "llama_index", "token_count": 5 }
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use std::fmt::Debug; use super::{Component, ComponentContext, Handler}; use async_trait::async_trait; use thiserror::Error; // Message Wrapper #[derive(Debug)] pub(crate) struct Wrapper<C> where C: Component, { wrapper: Box<dyn WrapperTrait<C>>, } impl<C: Component> Wrapper<C> { pub(super) async fn handl...
chroma/rust/worker/src/system/sender.rs/0
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# retrieval-agent-fireworks This package uses open source models hosted on FireworksAI to do retrieval using an agent architecture. By default, this does retrieval over Arxiv. We will use `Mixtral8x7b-instruct-v0.1`, which is shown in this blog to yield reasonable results with function calling even though it is not f...
langchain/templates/retrieval-agent-fireworks/README.md/0
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""" An implementation of GhostNet & GhostNetV2 Models as defined in: GhostNet: More Features from Cheap Operations. https://arxiv.org/abs/1911.11907 GhostNetV2: Enhance Cheap Operation with Long-Range Attention. https://proceedings.neurips.cc/paper_files/paper/2022/file/40b60852a4abdaa696b5a1a78da34635-Paper-Conference...
pytorch-image-models/timm/models/ghostnet.py/0
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# coding=utf-8 # Copyright The HuggingFace 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/LICE...
transformers/src/transformers/models/xglm/tokenization_xglm.py/0
{ "file_path": "transformers/src/transformers/models/xglm/tokenization_xglm.py", "repo_id": "transformers", "token_count": 5538 }
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# YandexGPT LangChain.js supports calling [YandexGPT](https://cloud.yandex.com/en/services/yandexgpt) LLMs. ## Setup First, you should [create service account](https://cloud.yandex.com/en/docs/iam/operations/sa/create) with the `ai.languageModels.user` role. Next, you have two authentication options: - [IAM token]...
langchainjs/docs/core_docs/docs/integrations/llms/yandex.mdx/0
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<jupyter_start><jupyter_text>Partager ses démos avec d'autres Installez les bibliothèques 🤗 Transformers et 🤗 Gradio pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece] !pip install gradio import gradio as gr title = "Poser une question (en anglais) à Rick" description = """ L...
notebooks/course/fr/chapter9/section4.ipynb/0
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export default `# QA and Chat over Documents Chat and Question-Answering (QA) over \`data\` are popular LLM use-cases. \`data\` can include many things, including: * \`Unstructured data\` (e.g., PDFs) * \`Structured data\` (e.g., SQL) * \`Code\` (e.g., Python) Below we will review Chat and QA on \`Unstructured data...
langchain-nextjs-template/data/DefaultRetrievalText.ts/0
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# Self-querying A self-querying retriever is one that, as the name suggests, has the ability to query itself. Specifically, given any natural language query, the retriever uses a query-constructing LLM chain to write a structured query and then applies that structured query to it's underlying VectorStore. This allows ...
langchainjs/docs/core_docs/docs/modules/data_connection/retrievers/self_query/index.mdx/0
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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 = ["AzStorageBlobReader"] contains_example = false import_path = "llama_index.readers.azstora...
llama_index/llama-index-integrations/readers/llama-index-readers-azstorage-blob/pyproject.toml/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-azstorage-blob/pyproject.toml", "repo_id": "llama_index", "token_count": 704 }
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from typing import List from langchain_core.documents import Document from langchain_community.document_loaders.web_base import WebBaseLoader class IMSDbLoader(WebBaseLoader): """Load `IMSDb` webpages.""" def load(self) -> List[Document]: """Load webpage.""" soup = self.scrape() tex...
langchain/libs/community/langchain_community/document_loaders/imsdb.py/0
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"""Test EdenAi's speech to text Tool . In order to run this test, you need to have an EdenAI api key. You can get it by registering for free at https://app.edenai.run/user/register. A test key can be found at https://app.edenai.run/admin/account/settings by clicking on the 'sandbox' toggle. (calls will be free, and wi...
langchain/libs/community/tests/integration_tests/tools/edenai/test_audio_speech_to_text.py/0
{ "file_path": "langchain/libs/community/tests/integration_tests/tools/edenai/test_audio_speech_to_text.py", "repo_id": "langchain", "token_count": 326 }
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"""Util that calls several NASA APIs.""" import json import requests from langchain_core.pydantic_v1 import BaseModel IMAGE_AND_VIDEO_LIBRARY_URL = "https://images-api.nasa.gov" class NasaAPIWrapper(BaseModel): """Wrapper for NASA API.""" def get_media(self, query: str) -> str: params = json.loads(...
langchain/libs/community/langchain_community/utilities/nasa.py/0
{ "file_path": "langchain/libs/community/langchain_community/utilities/nasa.py", "repo_id": "langchain", "token_count": 786 }
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[package] authors = ["Anthony MOI <m.anthony.moi@gmail.com>", "Nicolas Patry <patry.nicolas@protonmail.com>"] edition = "2018" name = "tokenizers" version = "0.15.3-dev.0" homepage = "https://github.com/huggingface/tokenizers" repository = "https://github.com/huggingface/tokenizers" documentation = "https://docs.rs/tok...
tokenizers/tokenizers/Cargo.toml/0
{ "file_path": "tokenizers/tokenizers/Cargo.toml", "repo_id": "tokenizers", "token_count": 838 }
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"""Base vector store index query.""" from typing import Any, Dict, List, Optional from llama_index.core.base.base_retriever import BaseRetriever from llama_index.core.base.embeddings.base import BaseEmbedding from llama_index.core.callbacks.base import CallbackManager from llama_index.core.constants import DEFAULT_S...
llama_index/llama-index-core/llama_index/core/indices/vector_store/retrievers/retriever.py/0
{ "file_path": "llama_index/llama-index-core/llama_index/core/indices/vector_store/retrievers/retriever.py", "repo_id": "llama_index", "token_count": 3364 }
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from langchain_together.embeddings import TogetherEmbeddings from langchain_together.llms import Together from langchain_together.version import __version__ __all__ = [ "__version__", "Together", "TogetherEmbeddings", ]
langchain/libs/partners/together/langchain_together/__init__.py/0
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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 applicabl...
diffusers/src/diffusers/models/attention_processor.py/0
{ "file_path": "diffusers/src/diffusers/models/attention_processor.py", "repo_id": "diffusers", "token_count": 46806 }
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build_performance: collections: # - # server: # db_config.primary_path: /test/milvus/db_data_011/sift_1b_128_l2_sq8h # cache_config.cpu_cache_capacity: 8GB # engine_config.use_blas_threshold: 1100 # engine_config.gpu_search_threshold: 1 # gpu_resource_config.enable: true # ...
milvus/tests/benchmark/milvus_benchmark/suites/011_gpu_build_sift1b.yaml/0
{ "file_path": "milvus/tests/benchmark/milvus_benchmark/suites/011_gpu_build_sift1b.yaml", "repo_id": "milvus", "token_count": 705 }
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import { ChatGoogleVertexAI } from "@langchain/community/chat_models/googlevertexai"; // Or, if using the web entrypoint: // import { ChatGoogleVertexAI } from "@langchain/community/chat_models/googlevertexai/web"; const model = new ChatGoogleVertexAI({ temperature: 0.7, }); const stream = await model.stream([ ["s...
langchainjs/examples/src/models/chat/integration_googlevertexai-streaming.ts/0
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# Annoy > [Annoy](https://github.com/spotify/annoy) (`Approximate Nearest Neighbors Oh Yeah`) is a C++ library with Python bindings to search for points in space that are close to a given query point. It also creates large read-only file-based data structures that are mmapped into memory so that many processes may sha...
langchain/docs/docs/integrations/providers/annoy.mdx/0
{ "file_path": "langchain/docs/docs/integrations/providers/annoy.mdx", "repo_id": "langchain", "token_count": 151 }
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import torch import torch.nn as nn class AsymmetricLossMultiLabel(nn.Module): def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-8, disable_torch_grad_focal_loss=False): super(AsymmetricLossMultiLabel, self).__init__() self.gamma_neg = gamma_neg self.gamma_pos = gamma_pos ...
pytorch-image-models/timm/loss/asymmetric_loss.py/0
{ "file_path": "pytorch-image-models/timm/loss/asymmetric_loss.py", "repo_id": "pytorch-image-models", "token_count": 1620 }
349
#!/usr/bin/env bash export VERSION=`python -m setuptools_scm` if [[ -n `git status --porcelain` ]]; then VERSION=$VERSION-dirty fi echo $VERSION
chroma/bin/version/0
{ "file_path": "chroma/bin/version", "repo_id": "chroma", "token_count": 59 }
12