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from neo4j_cypher_ft.chain import chain if __name__ == "__main__": original_query = "Did tom cruis act in top gun?" print(chain.invoke({"question": original_query})) # noqa: T201
langchain/templates/neo4j-cypher-ft/main.py/0
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import { v4 } from "uuid"; import type { D1Database } from "@cloudflare/workers-types"; import { BaseListChatMessageHistory } from "@langchain/core/chat_history"; import { BaseMessage, StoredMessage, StoredMessageData, mapChatMessagesToStoredMessages, mapStoredMessagesToChatMessages, } from "@langchain/core/m...
langchainjs/libs/langchain-community/src/stores/message/cloudflare_d1.ts/0
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use super::k_quants::{ BlockQ2K, BlockQ3K, BlockQ4K, BlockQ4_0, BlockQ5K, BlockQ6K, BlockQ8K, BlockQ8_0, QK8_0, QK_K, }; use crate::Result; use byteorder::{ByteOrder, LittleEndian}; #[allow(unused_imports)] #[cfg(target_arch = "arm")] use core::arch::arm::*; #[allow(unused_imports)] #[cfg(target_arch = "aarch64")...
candle/candle-core/src/quantized/neon.rs/0
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[tool.poetry] name = "rag-multi-index-fusion" version = "0.0.1" description = "RAG with routing and fusion between different domain-specific retrievers" authors = [] readme = "README.md" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" langchain = "^0.1" openai = "<2" xmltodict = "^0.13.0" kay = "^0.1.2" wikipedia =...
langchain/templates/rag-multi-index-fusion/pyproject.toml/0
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import logging from pymongo import MongoClient from .models.env import Env from .models.hardware import Hardware from .models.metric import Metric from .models.server import Server from .config import DB, UNIQUE_ID_COLLECTION, DOC_COLLECTION from milvus_benchmark import config # Initialize the mongoDB client _client...
milvus/tests/benchmark/milvus_benchmark/metrics/api.py/0
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# Metadata Extraction Usage Pattern You can use LLMs to automate metadata extraction with our `Metadata Extractor` modules. Our metadata extractor modules include the following "feature extractors": - `SummaryExtractor` - automatically extracts a summary over a set of Nodes - `QuestionsAnsweredExtractor` - extracts ...
llama_index/docs/module_guides/loading/documents_and_nodes/usage_metadata_extractor.md/0
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# LlamaIndex Output_Parsers Integration: Guardrails
llama_index/llama-index-integrations/output_parsers/llama-index-output-parsers-guardrails/README.md/0
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import os from abc import ABC, abstractmethod from typing import List, Optional import fsspec from llama_index.legacy.data_structs.data_structs import IndexStruct DEFAULT_PERSIST_DIR = "./storage" DEFAULT_PERSIST_FNAME = "index_store.json" DEFAULT_PERSIST_PATH = os.path.join(DEFAULT_PERSIST_DIR, DEFAULT_PERSIST_FNAM...
llama_index/llama-index-legacy/llama_index/legacy/storage/index_store/types.py/0
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"""Test HyDE.""" from typing import Any, List, Optional import numpy as np from langchain_core.embeddings import Embeddings from langchain_core.language_models.llms import BaseLLM from langchain_core.outputs import Generation, LLMResult from langchain.callbacks.manager import ( AsyncCallbackManagerForLLMRun, ...
langchain/libs/langchain/tests/unit_tests/chains/test_hyde.py/0
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#!/usr/bin/env bash set -e function cleanup { # Restore the previous kube context kubectl config use-context $PREV_CHROMA_KUBE_CONTEXT # Kill the tunnel process kill $TUNNEL_PID minikube delete -p chroma-test } trap cleanup EXIT # Save the current kube context into a variable export PREV_CHROMA_...
chroma/bin/cluster-test.sh/0
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# Porting a custom kernel
candle/candle-book/src/inference/cuda/porting.md/0
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from typing import Sequence from uuid import UUID from overrides import overrides from chromadb.config import System from chromadb.ingest import CollectionAssignmentPolicy from chromadb.ingest.impl.utils import create_topic_name class SimpleAssignmentPolicy(CollectionAssignmentPolicy): """Simple assignment policy...
chroma/chromadb/ingest/impl/simple_policy.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 ...
transformers/examples/pytorch/question-answering/README.md/0
{ "file_path": "transformers/examples/pytorch/question-answering/README.md", "repo_id": "transformers", "token_count": 2413 }
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[tool.poetry] name = "rag-codellama-fireworks" version = "0.1.0" description = "RAG using OSS LLMs via Fireworks" authors = [ "Lance Martin <lance@langchain.dev>", ] readme = "README.md" [tool.poetry.dependencies] python = ">=3.9,<4.0" langchain = "^0.1" gpt4all = ">=1.0.8" tiktoken = ">=0.5.1" chromadb = ">=0.4.1...
langchain/templates/rag-codellama-fireworks/pyproject.toml/0
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FROM rocm/dev-ubuntu-22.04:5.6 LABEL maintainer="Hugging Face" ARG DEBIAN_FRONTEND=noninteractive ARG PYTORCH='2.1.1' ARG TORCH_VISION='0.16.1' ARG TORCH_AUDIO='2.1.1' ARG ROCM='5.6' RUN apt update && \ apt install -y --no-install-recommends \ libaio-dev \ git \ # These are required to build deepspeed...
transformers/docker/transformers-pytorch-deepspeed-amd-gpu/Dockerfile/0
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-- SQLite does not support adding check with alter table, as a result, adding a check -- involve creating a new table and copying the data over. It is over kill with adding -- a boolean type column. The application write to the table needs to ensure the data -- integrity. ALTER TABLE embedding_metadata ADD COLUMN bool_...
chroma/chromadb/migrations/metadb/00002-embedding-metadata.sqlite.sql/0
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"""Pytorch impl of Aligned Xception 41, 65, 71 This is a correct, from scratch impl of Aligned Xception (Deeplab) models compatible with TF weights at https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md Hacked together by / Copyright 2020 Ross Wightman """ from functools import partia...
pytorch-image-models/timm/models/xception_aligned.py/0
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""" MobileViT Paper: V1: `MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer` - https://arxiv.org/abs/2110.02178 V2: `Separable Self-attention for Mobile Vision Transformers` - https://arxiv.org/abs/2206.02680 MobileVitBlock and checkpoints adapted from https://github.com/apple/ml-cvnets...
pytorch-image-models/timm/models/mobilevit.py/0
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<jupyter_start><jupyter_text>ElasticsearchWalkthrough of how to generate embeddings using a hosted embedding model in ElasticsearchThe easiest way to instantiate the `ElasticsearchEmbeddings` class it either- using the `from_credentials` constructor if you are using Elastic Cloud- or using the `from_es_connection` cons...
langchain/docs/docs/integrations/text_embedding/elasticsearch.ipynb/0
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diff --git a/package.json b/package.json index 1823128f20579c0c70acfb394d84d5f2997aafb9..663f5b611870e762cf355b1d4810765f9c89b318 100644 --- a/package.json +++ b/package.json @@ -1,5 +1,7 @@ { "name": "voy-search", + "type": "module", + "main": "voy_search.js", "collaborators": [ "Daw-Chih Liou <dawochih....
langchainjs/.yarn/patches/voy-search-npm-0.6.2-d4aca30a0e.patch/0
{ "file_path": "langchainjs/.yarn/patches/voy-search-npm-0.6.2-d4aca30a0e.patch", "repo_id": "langchainjs", "token_count": 165 }
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<jupyter_start><jupyter_text>Multidoc Autoretrieval PackThis is the LlamaPack version of our structured hierarchical retrieval guide in the [core repo](https://docs.llamaindex.ai/en/stable/examples/query_engine/multi_doc_auto_retrieval/multi_doc_auto_retrieval.html). Setup and Download DataIn this section, we'll load ...
llama_index/llama-index-packs/llama-index-packs-multidoc-autoretrieval/examples/multidoc_autoretrieval.ipynb/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-multidoc-autoretrieval/examples/multidoc_autoretrieval.ipynb", "repo_id": "llama_index", "token_count": 2378 }
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import os import re import subprocess # nosec import tempfile from langchain.agents import AgentType, initialize_agent from langchain.agents.tools import Tool from langchain.pydantic_v1 import BaseModel, Field, ValidationError, validator from langchain_community.chat_models import ChatOpenAI from langchain_core.langu...
langchain/templates/python-lint/python_lint/agent_executor.py/0
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import { PromptTemplate } from "@langchain/core/prompts"; export const NAIVE_FIX_TEMPLATE = `Instructions: -------------- {instructions} -------------- Completion: -------------- {completion} -------------- Above, the Completion did not satisfy the constraints given in the Instructions. Error: -------------- {error} ...
langchainjs/langchain/src/output_parsers/prompts.ts/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/pkg/util/gc/gc_tuner.go/0
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#!/usr/bin/env bash # 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...
milvus/scripts/core_build.sh/0
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# College Confidential >[College Confidential](https://www.collegeconfidential.com/) gives information on 3,800+ colleges and universities. ## Installation and Setup There isn't any special setup for it. ## Document Loader See a [usage example](/docs/integrations/document_loaders/college_confidential). ```python...
langchain/docs/docs/integrations/providers/college_confidential.mdx/0
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poetry_requirements( name="poetry", ) python_requirements( name="reqs", )
llama_index/llama-index-integrations/readers/llama-index-readers-snscrape-twitter/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-snscrape-twitter/BUILD", "repo_id": "llama_index", "token_count": 36 }
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poetry_requirements( name="poetry", ) python_requirements( name="reqs", )
llama_index/llama-index-packs/llama-index-packs-multidoc-autoretrieval/BUILD/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-multidoc-autoretrieval/BUILD", "repo_id": "llama_index", "token_count": 36 }
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import pytest import torch from copy import copy from transformers import AutoTokenizer from text_generation_server.pb import generate_pb2 from text_generation_server.models.causal_lm import CausalLMBatch from text_generation_server.utils import weight_hub_files, download_weights from text_generation_server.models.bl...
text-generation-inference/server/tests/models/test_bloom.py/0
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# LlamaIndex Postprocessor Integration: Rankgpt Rerank
llama_index/llama-index-integrations/postprocessor/llama-index-postprocessor-rankgpt-rerank/README.md/0
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package dbmodel import ( "time" "github.com/chroma/chroma-coordinator/internal/types" ) type CollectionMetadata struct { CollectionID string `gorm:"collection_id;primaryKey"` Key *string `gorm:"key;primaryKey"` StrValue *string `gorm:"str_value"` IntValue *int64 ...
chroma/go/coordinator/internal/metastore/db/dbmodel/collection_metadata.go/0
{ "file_path": "chroma/go/coordinator/internal/metastore/db/dbmodel/collection_metadata.go", "repo_id": "chroma", "token_count": 379 }
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<?xml version="1.0" encoding="UTF-8"?> <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:news="http://www.google.com/schemas/sitemap-news/0.9" xmlns:xhtml="http://www.w3.org/1999/xhtml" xmlns:image="http://www.google.com/schemas/sitemap-image/1.1" xmlns:video="http://www.google.com/schemas/sitem...
langchain/libs/community/tests/integration_tests/examples/docusaurus-sitemap.xml/0
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# LlamaIndex Llms Integration: Rungpt
llama_index/llama-index-integrations/llms/llama-index-llms-rungpt/README.md/0
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import asyncio from typing import Any, Dict, List, Optional, Sequence, Tuple, cast from llama_index.core.async_utils import asyncio_module from llama_index.core.base.base_query_engine import BaseQueryEngine from llama_index.core.base.response.schema import RESPONSE_TYPE, Response from llama_index.core.evaluation.base ...
llama_index/llama-index-core/llama_index/core/evaluation/batch_runner.py/0
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poetry_requirements( name="poetry", ) python_requirements( name="reqs", )
llama_index/llama-index-integrations/readers/llama-index-readers-spotify/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-spotify/BUILD", "repo_id": "llama_index", "token_count": 36 }
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# Introduction [[introduction]] <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit0/thumbnail.png" alt="Thumbnail"/> Since the beginning of this course, we learned to train agents in a *single-agent system* where our agent was alone in its environment: it was **no...
deep-rl-class/units/en/unit7/introduction.mdx/0
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# SingleStore Loader The SingleStore Loader retrieves a set of documents from a specified table in a SingleStore database. The user initializes the loader with database information and then provides a search embedding for retrieving similar documents. ## Usage Here's an example usage of the SingleStoreReader: ```py...
llama_index/llama-index-integrations/readers/llama-index-readers-singlestore/README.md/0
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export * from "./qa/index.js"; export * from "./criteria/index.js"; export * from "./agents/index.js"; export * from "./embedding_distance/index.js"; export * from "./comparison/index.js"; export * from "./types.js"; export * from "./loader.js";
langchainjs/langchain/src/evaluation/index.ts/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/storage/primary_keys.go/0
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<jupyter_start><jupyter_text>RSS FeedsThis covers how to load HTML news articles from a list of RSS feed URLs into a document format that we can use downstream.<jupyter_code>%pip install --upgrade --quiet feedparser newspaper3k listparser from langchain_community.document_loaders import RSSFeedLoader urls = ["https://...
langchain/docs/docs/integrations/document_loaders/rss.ipynb/0
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<jupyter_start><jupyter_text>Getting Started Installing Vertex AI To Install Vertex AI you need to follow the following steps* Install Vertex Cloud SDK (https://googleapis.dev/python/aiplatform/latest/index.html)* Setup your Default Project, credentials, region Basic auth example for service account<jupyter_code>%pip i...
llama_index/docs/examples/llm/vertex.ipynb/0
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from __future__ import annotations from copy import deepcopy from typing import Any, Dict, List, Optional, Sequence, Union from langchain_core.documents import Document from langchain_core.pydantic_v1 import Extra, root_validator from langchain.callbacks.manager import Callbacks from langchain.retrievers.document_co...
langchain/libs/langchain/langchain/retrievers/document_compressors/cohere_rerank.py/0
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<jupyter_start><jupyter_text>Diffusion Models from ScratchSometimes it is helpful to consider the simplest possible version of something to better understand how it works. We're going to try that in this notebook, beginning with a 'toy' diffusion model to see how the different pieces work, and then examining how they d...
diffusion-models-class/unit1/02_diffusion_models_from_scratch.ipynb/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/pkg/mq/msgstream/mqwrapper/pulsar/pulsar_consumer.go/0
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import { ChatOpenAI } from "@langchain/openai"; import { UpstashRedisCache } from "@langchain/community/caches/upstash_redis"; // See https://docs.upstash.com/redis/howto/connectwithupstashredis#quick-start for connection options const cache = new UpstashRedisCache({ config: { url: "UPSTASH_REDIS_REST_URL", ...
langchainjs/examples/src/cache/chat_models/upstash_redis.ts/0
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from langchain.chains import LLMChain from langchain.prompts import PromptTemplate from langchain_core.language_models import BaseLanguageModel class TaskExecutionChain(LLMChain): """Chain to execute tasks.""" @classmethod def from_llm(cls, llm: BaseLanguageModel, verbose: bool = True) -> LLMChain: ...
langchain/libs/experimental/langchain_experimental/autonomous_agents/baby_agi/task_execution.py/0
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"""Wrapper around Redis vector database.""" from __future__ import annotations import logging import os import uuid from typing import ( TYPE_CHECKING, Any, Callable, Dict, Iterable, List, Mapping, Optional, Tuple, Type, Union, cast, ) import numpy as np import yaml fr...
langchain/libs/community/langchain_community/vectorstores/redis/base.py/0
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#!/usr/bin/env bash SCRIPTS_DIR=$(dirname "$0") THIRD_PARTY_DIR=$SCRIPTS_DIR/../cmake_build/thirdparty API_VERSION=$(go list -m github.com/milvus-io/milvus-proto/go-api/v2 | awk -F' ' '{print $2}') if [ ! -d "$THIRD_PARTY_DIR/milvus-proto" ]; then mkdir -p $THIRD_PARTY_DIR pushd $THIRD_PARTY_DIR git clone https...
milvus/scripts/download_milvus_proto.sh/0
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# Metric Card for Recall ## Metric Description Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation: Recall = TP / (TP + FN) Where TP is the number of true positives and FN is the number of false negatives. ## How to Use At mini...
datasets/metrics/recall/README.md/0
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<p align="center"> <br> <img src="https://huggingface.co/landing/assets/tokenizers/tokenizers-logo.png" width="600"/> <br> <p> <p align="center"> <img alt="Build" src="https://github.com/huggingface/tokenizers/workflows/Rust/badge.svg"> <a href="https://github.com/huggingface/tokenizers/blob/main/LI...
tokenizers/README.md/0
{ "file_path": "tokenizers/README.md", "repo_id": "tokenizers", "token_count": 945 }
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python_sources()
llama_index/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-dashscope/llama_index/multi_modal_llms/dashscope/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-dashscope/llama_index/multi_modal_llms/dashscope/BUILD", "repo_id": "llama_index", "token_count": 6 }
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-- Create "collection_metadata" table CREATE TABLE "public"."collection_metadata" ( "collection_id" text NOT NULL, "key" text NOT NULL, "str_value" text NULL, "int_value" bigint NULL, "float_value" numeric NULL, "ts" bigint NULL DEFAULT 0, "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, "upda...
chroma/go/coordinator/migrations/20231116210409.sql/0
{ "file_path": "chroma/go/coordinator/migrations/20231116210409.sql", "repo_id": "chroma", "token_count": 908 }
57
poetry_requirements( name="poetry", )
llama_index/llama-index-integrations/readers/llama-index-readers-deeplake/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-deeplake/BUILD", "repo_id": "llama_index", "token_count": 18 }
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package datacoord import ( "context" "sync" "time" "github.com/samber/lo" "go.uber.org/zap" "github.com/milvus-io/milvus/internal/proto/datapb" "github.com/milvus-io/milvus/pkg/log" "github.com/milvus-io/milvus/pkg/util/logutil" ) type CompactionViewManager struct { view *FullViews viewGuard sync.RWM...
milvus/internal/datacoord/compaction_view_manager.go/0
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# ForefrontAI This page covers how to use the ForefrontAI ecosystem within LangChain. It is broken into two parts: installation and setup, and then references to specific ForefrontAI wrappers. ## Installation and Setup - Get an ForefrontAI api key and set it as an environment variable (`FOREFRONTAI_API_KEY`) ## Wrap...
langchain/docs/docs/integrations/providers/forefrontai.mdx/0
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--- sidebar-position: 0 --- # Self-querying retriever Learn about how the self-querying retriever works [here](/docs/modules/data_connection/retrievers/self_query). import DocCardList from "@theme/DocCardList"; <DocCardList />
langchain/docs/docs/integrations/retrievers/self_query/index.mdx/0
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// Just enough pickle support to be able to read PyTorch checkpoints. // This hardcodes objects that are required for tensor reading, we may want to make this a bit more // composable/tensor agnostic at some point. use crate::{DType, Error as E, Layout, Result, Tensor}; use byteorder::{LittleEndian, ReadBytesExt}; use ...
candle/candle-core/src/pickle.rs/0
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32
import { test, expect } from "@jest/globals"; import * as url from "node:url"; import * as path from "node:path"; import { TextLoader } from "../fs/text.js"; test("Test Text loader from file", async () => { const filePath = path.resolve( path.dirname(url.fileURLToPath(import.meta.url)), "./example_data/examp...
langchainjs/langchain/src/document_loaders/tests/text.test.ts/0
{ "file_path": "langchainjs/langchain/src/document_loaders/tests/text.test.ts", "repo_id": "langchainjs", "token_count": 246 }
911
{ "name": "tokenizers-darwin-x64", "version": "0.13.4-rc1", "os": [ "darwin" ], "cpu": [ "x64" ], "main": "tokenizers.darwin-x64.node", "files": [ "tokenizers.darwin-x64.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", "NAPI", "N-API...
tokenizers/bindings/node/npm/darwin-x64/package.json/0
{ "file_path": "tokenizers/bindings/node/npm/darwin-x64/package.json", "repo_id": "tokenizers", "token_count": 268 }
439
from __future__ import annotations from typing import TYPE_CHECKING, Dict, Optional, Sequence from langchain_core.documents import Document from langchain_core.pydantic_v1 import Extra, root_validator from langchain.callbacks.manager import Callbacks from langchain.retrievers.document_compressors.base import BaseDoc...
langchain/libs/langchain/langchain/retrievers/document_compressors/flashrank_rerank.py/0
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534
"""Xorbits toolkit."""
langchain/libs/experimental/langchain_experimental/agents/agent_toolkits/xorbits/__init__.py/0
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436
""" This tool allows agents to interact with the NASA API, specifically the the NASA Image & Video Library and Exoplanet """ from typing import Optional from langchain_core.callbacks import CallbackManagerForToolRun from langchain_core.pydantic_v1 import Field from langchain_core.tools import BaseTool from langchai...
langchain/libs/community/langchain_community/tools/nasa/tool.py/0
{ "file_path": "langchain/libs/community/langchain_community/tools/nasa/tool.py", "repo_id": "langchain", "token_count": 276 }
302
from llama_index.retrievers.you.base import YouRetriever __all__ = ["YouRetriever"]
llama_index/llama-index-integrations/retrievers/llama-index-retrievers-you/llama_index/retrievers/you/__init__.py/0
{ "file_path": "llama_index/llama-index-integrations/retrievers/llama-index-retrievers-you/llama_index/retrievers/you/__init__.py", "repo_id": "llama_index", "token_count": 31 }
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from langchain_community.chat_message_histories.in_memory import ChatMessageHistory __all__ = ["ChatMessageHistory"]
langchain/libs/langchain/langchain/memory/chat_message_histories/in_memory.py/0
{ "file_path": "langchain/libs/langchain/langchain/memory/chat_message_histories/in_memory.py", "repo_id": "langchain", "token_count": 32 }
546
from langchain_community.callbacks.sagemaker_callback import ( SageMakerCallbackHandler, ) __all__ = ["SageMakerCallbackHandler"]
langchain/libs/langchain/langchain/callbacks/sagemaker_callback.py/0
{ "file_path": "langchain/libs/langchain/langchain/callbacks/sagemaker_callback.py", "repo_id": "langchain", "token_count": 41 }
475
from llama_index.vector_stores.docarray.hnsw import DocArrayHnswVectorStore from llama_index.vector_stores.docarray.in_memory import DocArrayInMemoryVectorStore __all__ = [ "DocArrayInMemoryVectorStore", "DocArrayHnswVectorStore", ]
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-docarray/llama_index/vector_stores/docarray/__init__.py/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-docarray/llama_index/vector_stores/docarray/__init__.py", "repo_id": "llama_index", "token_count": 82 }
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# coding=utf-8 # Copyright 2024 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...
diffusers/src/diffusers/utils/dynamic_modules_utils.py/0
{ "file_path": "diffusers/src/diffusers/utils/dynamic_modules_utils.py", "repo_id": "diffusers", "token_count": 7559 }
276
<jupyter_start><jupyter_text>SingleStoreDB>[SingleStoreDB](https://singlestore.com/) is a high-performance distributed SQL database that supports deployment both in the [cloud](https://www.singlestore.com/cloud/) and on-premises. It provides vector storage, and vector functions including [dot_product](https://docs.sing...
langchain/docs/docs/integrations/vectorstores/singlestoredb.ipynb/0
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185
version: "3" services: clickhouse: image: clickhouse/clickhouse-server:24.1 user: "101:101" container_name: clickhouse-server hostname: clickhouse-server ports: - "8123:8123" - "9000:9000" ulimits: nofile: soft: 262144 hard: 262144
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-clickhouse/docker-compose.yml/0
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import { logVersion010MigrationWarning } from "../../util/entrypoint_deprecation.js"; /* #__PURE__ */ logVersion010MigrationWarning({ oldEntrypointName: "stores/message/planetscale", }); export * from "@langchain/community/stores/message/planetscale";
langchainjs/langchain/src/stores/message/planetscale.ts/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/tasks/visual_question_answering.md/0
{ "file_path": "transformers/docs/source/ja/tasks/visual_question_answering.md", "repo_id": "transformers", "token_count": 7952 }
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# coding=utf-8 # Copyright 2021 Google 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/LICE...
transformers/src/transformers/models/big_bird/configuration_big_bird.py/0
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# Motherduck >[Motherduck](https://motherduck.com/) is a managed DuckDB-in-the-cloud service. ## Installation and Setup First, you need to install `duckdb` python package. ```bash pip install duckdb ``` You will also need to sign up for an account at [Motherduck](https://motherduck.com/) After that, you should se...
langchain/docs/docs/integrations/providers/motherduck.mdx/0
{ "file_path": "langchain/docs/docs/integrations/providers/motherduck.mdx", "repo_id": "langchain", "token_count": 429 }
143
python_sources() python_tests( name="tests", dependencies=["llama-index-core/tests/playground:playground"] )
llama_index/llama-index-core/tests/node_parser/BUILD/0
{ "file_path": "llama_index/llama-index-core/tests/node_parser/BUILD", "repo_id": "llama_index", "token_count": 44 }
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from langchain.indexes import __all__ EXPECTED_ALL = [ # Keep sorted "aindex", "GraphIndexCreator", "index", "IndexingResult", "SQLRecordManager", "VectorstoreIndexCreator", ] def test_all_imports() -> None: assert set(__all__) == set(EXPECTED_ALL)
langchain/libs/langchain/tests/unit_tests/indexes/test_imports.py/0
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# This example shows how the candle Python api can be used to replicate llama.cpp. import sys from typing import Dict, Tuple, Any import candle from candle.models.llama import QuantizedLlama from candle import utils MAX_SEQ_LEN = 4096 def gguf_rename(tensor_name: str): if tensor_name == "token_embd.weight": ...
candle/candle-pyo3/quant-llama.py/0
{ "file_path": "candle/candle-pyo3/quant-llama.py", "repo_id": "candle", "token_count": 1318 }
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# coding=utf-8 # Copyright 2023 Microsoft and the HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
transformers/src/transformers/models/phi/configuration_phi.py/0
{ "file_path": "transformers/src/transformers/models/phi/configuration_phi.py", "repo_id": "transformers", "token_count": 3668 }
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from llama_index.packs.fusion_retriever.hybrid_fusion.base import ( HybridFusionRetrieverPack, ) from llama_index.packs.fusion_retriever.query_rewrite.base import ( QueryRewritingRetrieverPack, ) __all__ = ["HybridFusionRetrieverPack", "QueryRewritingRetrieverPack"]
llama_index/llama-index-packs/llama-index-packs-fusion-retriever/llama_index/packs/fusion_retriever/__init__.py/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-fusion-retriever/llama_index/packs/fusion_retriever/__init__.py", "repo_id": "llama_index", "token_count": 104 }
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// Licensed to the LF AI & Data foundation under one // or more contributor license agreements. See the NOTICE file // distributed with this work for additional information // regarding copyright ownership. The ASF licenses this file // to you under the Apache License, Version 2.0 (the // "License"); you may not use th...
milvus/internal/util/importutilv2/binlog/reader_test.go/0
{ "file_path": "milvus/internal/util/importutilv2/binlog/reader_test.go", "repo_id": "milvus", "token_count": 6203 }
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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_modeling_utils.py/0
{ "file_path": "accelerate/tests/test_modeling_utils.py", "repo_id": "accelerate", "token_count": 12826 }
16
[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 = ["ArizePhoenixQueryEnginePack"] contains_example = true import_path = "llama_index.packs.ar...
llama_index/llama-index-packs/llama-index-packs-arize-phoenix-query-engine/pyproject.toml/0
{ "file_path": "llama_index/llama-index-packs/llama-index-packs-arize-phoenix-query-engine/pyproject.toml", "repo_id": "llama_index", "token_count": 721 }
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export const timeout = <T>(prom: Promise<T>, time: number): Promise<T> => { let timer: NodeJS.Timeout; return Promise.race([prom, new Promise<T>((_r, rej) => (timer = setTimeout(rej, time)))]).finally( () => clearTimeout(timer) ); };
chat-ui/src/lib/utils/timeout.ts/0
{ "file_path": "chat-ui/src/lib/utils/timeout.ts", "repo_id": "chat-ui", "token_count": 87 }
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.main { display: flex; flex-direction: column; justify-content: space-between; align-items: center; padding: 6rem; min-height: 100vh; } .description { display: inherit; justify-content: inherit; align-items: inherit; font-size: 0.85rem; max-width: var(--max-width); width: 100%; z-index: 2; ...
langchainjs/environment_tests/test-exports-vercel/src/styles/Home.module.css/0
{ "file_path": "langchainjs/environment_tests/test-exports-vercel/src/styles/Home.module.css", "repo_id": "langchainjs", "token_count": 1973 }
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from typing import Any, Mapping, Optional from llama_index.readers.airbyte_cdk.base import AirbyteCDKReader, RecordHandler class AirbyteTypeformReader(AirbyteCDKReader): """AirbyteTypeformReader reader. Retrieve documents from Typeform Args: config: The config object for the typeform source. ...
llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-typeform/llama_index/readers/airbyte_typeform/base.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-typeform/llama_index/readers/airbyte_typeform/base.py", "repo_id": "llama_index", "token_count": 281 }
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<jupyter_start><jupyter_text>GithubThe `Github` toolkit contains tools that enable an LLM agent to interact with a github repository. The tool is a wrapper for the [PyGitHub](https://github.com/PyGithub/PyGithub) library. Quickstart1. Install the pygithub library2. Create a Github app3. Set your environmental variable...
langchain/docs/docs/integrations/toolkits/github.ipynb/0
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"""Node postprocessor tests.""" from importlib.util import find_spec from pathlib import Path from typing import Dict, cast import pytest from llama_index.core.postprocessor.node import ( KeywordNodePostprocessor, PrevNextNodePostprocessor, ) from llama_index.core.postprocessor.node_recency import ( Embed...
llama_index/llama-index-core/tests/postprocessor/test_base.py/0
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# MangaDex Loader This loader fetches information from the MangaDex API, by manga title. ## Usage ```python from llama_index import download_loader MangaDexReader = download_loader("MangaDexReader") loader = MangaDexReader() documents = loader.load_data( titles=["manga title 1", "manga title 2"], lang="en" ) `...
llama_index/llama-index-integrations/readers/llama-index-readers-mangadex/README.md/0
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<jupyter_start><jupyter_text>Semantic ChunkingSplits the text based on semantic similarity.Taken from Greg Kamradt's wonderful notebook:https://github.com/FullStackRetrieval-com/RetrievalTutorials/blob/main/5_Levels_Of_Text_Splitting.ipynbAll credit to him.At a high level, this splits into sentences, then groups into g...
langchain/docs/docs/modules/data_connection/document_transformers/semantic-chunker.ipynb/0
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# coding=utf-8 # Copyright 2024 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...
diffusers/src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.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/pkg/mq/msgstream/mqwrapper/nmq/nmq_id.go/0
{ "file_path": "milvus/pkg/mq/msgstream/mqwrapper/nmq/nmq_id.go", "repo_id": "milvus", "token_count": 712 }
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import * as yaml from "js-yaml"; import { OpenAPIV3, OpenAPIV3_1 } from "openapi-types"; export class OpenAPISpec { constructor(public document: OpenAPIV3_1.Document) {} get baseUrl() { return this.document.servers ? this.document.servers[0].url : undefined; } getPathsStrict() { if (!this.document.pa...
langchainjs/langchain/src/util/openapi.ts/0
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978
-----BEGIN CERTIFICATE----- MIIDizCCAnOgAwIBAgIUNCeQzjvQkinJwUgQ4quG0opHAL4wDQYJKoZIhvcNAQEL BQAwYzELMAkGA1UEBhMCQ04xCzAJBgNVBAgMAkdaMQswCQYDVQQHDAJHWjESMBAG A1UECgwJcm9uZXRoaW5nMRIwEAYDVQQLDAlyb25ldGhpbmcxEjAQBgNVBAMMCWxv Y2FsaG9zdDAeFw0yMjA1MDEwODU3MzRaFw0zMjA0MjgwODU3MzRaMEkxCzAJBgNV BAYTAkNOMRIwEAYDVQQKDAlyb25ldGhp...
milvus/configs/cert/server.pem/0
{ "file_path": "milvus/configs/cert/server.pem", "repo_id": "milvus", "token_count": 953 }
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<jupyter_start><jupyter_text>2Markdown>[2markdown](https://2markdown.com/) service transforms website content into structured markdown files.<jupyter_code># You will need to get your own API key. See https://2markdown.com/login api_key = "" from langchain_community.document_loaders import ToMarkdownLoader loader = ToM...
langchain/docs/docs/integrations/document_loaders/tomarkdown.ipynb/0
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from typing import Tuple import torch def ndgrid(*tensors) -> Tuple[torch.Tensor, ...]: """generate N-D grid in dimension order. The ndgrid function is like meshgrid except that the order of the first two input arguments are switched. That is, the statement [X1,X2,X3] = ndgrid(x1,x2,x3) produc...
pytorch-image-models/timm/layers/grid.py/0
{ "file_path": "pytorch-image-models/timm/layers/grid.py", "repo_id": "pytorch-image-models", "token_count": 565 }
354
flash_att_commit := 3a9bfd076f98746c73362328958dbc68d145fbec flash-attention: # Clone flash attention pip install -U packaging ninja --no-cache-dir git clone https://github.com/HazyResearch/flash-attention.git build-flash-attention: flash-attention cd flash-attention && git fetch && git checkout $(flash_att_c...
text-generation-inference/server/Makefile-flash-att/0
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python_sources()
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-dashvector/llama_index/vector_stores/dashvector/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-dashvector/llama_index/vector_stores/dashvector/BUILD", "repo_id": "llama_index", "token_count": 6 }
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import { test, expect } from "@jest/globals"; import { ChatOpenAI } from "@langchain/openai"; import { AgentAction, AgentFinish } from "@langchain/core/agents"; import { StructuredChatOutputParserWithRetries } from "../structured_chat/outputParser.js"; test("Can parse JSON with text in front of it", async () => { co...
langchainjs/langchain/src/agents/tests/structured_chat_output_parser_with_retries.int.test.ts/0
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--- hide_table_of_contents: true --- import CodeBlock from "@theme/CodeBlock"; # Redis-Backed Chat Memory For longer-term persistence across chat sessions, you can swap out the default in-memory `chatHistory` that backs chat memory classes like `BufferMemory` for a [Redis](https://redis.io/) instance. ## Setup You...
langchainjs/docs/core_docs/docs/integrations/chat_memory/redis.mdx/0
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700
from langchain_community.llms.deepinfra import ( DeepInfra, ) __all__ = [ "DeepInfra", ]
langchain/libs/langchain/langchain/llms/deepinfra.py/0
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510
// Auto-generated by `scripts/create-entrypoints.js`. Do not edit manually. export * as agents from "../agents.js"; export * as caches from "../caches.js"; export * as callbacks__base from "../callbacks/base.js"; export * as callbacks__manager from "../callbacks/manager.js"; export * as callbacks__promises from "../ca...
langchainjs/langchain-core/src/load/import_map.ts/0
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