Search Results for "php-simple-html-dom-parser" - Page 3
Sort By:
Showing 296 open source projects for "php-simple-html-dom-parser"
View related business solutions-
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
-
Awardco Employee RecognitionEverything you love about Amazon is now available for rewards and recognition. Awardco has partnered with Amazon Business to bring millions of reward choices, lower vendor fees and dollar-for-dollar recognition spend to your organization. More choice, more capability, and less spend - all in one simple platform.
-
1
Real-Time Voice Cloning
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Real-Time Voice Cloning is an influential deep-learning repository that demonstrates how to clone a voice from just a few seconds of audio and then generate arbitrary speech in that voice in near real time. It implements the SV2TTS pipeline (“Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis”) in three stages: a speaker encoder, a synthesizer, and a vocoder. In the first stage, short audio clips are converted into a fixed-dimensional speaker embedding that... -
2
DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
3
FramePack
Lets make video diffusion practical
...The repository demonstrates both packing and unpacking steps, making it straightforward to integrate into preprocessing pipelines. It’s useful for diffusion and generative models that learn from sequential image datasets, as well as classical pipelines that batch many related frames. With a simple API and examples, it invites experimentation on tradeoffs between compression, fidelity, and speed. -
4
x-transformers
A simple but complete full-attention transformer
A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. -
Build innovative business apps powered by process automationManage your business as a unified system of interacting processes. Use BPMN 2.0 for low-code process modeling by business people. Follow your strategic goals with process architecture that always corresponds to the structure of an actual business.
-
5
Interpretable machine learning
Book about interpretable machine learning
...This book will give an overview over techniques that can be used to make black boxes as transparent as possible and explain decisions. In the first chapter algorithms that produce simple, interpretable models are introduced together with instructions how to interpret the output. The later chapters focus on analyzing complex models and their decisions. In an ideal future, machines will be able to explain their decisions and make a transition into an algorithmic age more human. -
6
Vanna
Chat with your SQL database
Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users. -
7
DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation.
-
8
mcpo
A simple, secure MCP-to-OpenAPI proxy server
...This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI documentation that shows end-to-end integration. It supports running multiple tools and makes them discoverable to clients that expect Swagger/JSON schemas. In practice, mcpo shortens the path from a local MCP tool to a shareable, network-accessible microservice. -
9
Hiera
A fast, powerful, and simple hierarchical vision transformer
Hiera is a hierarchical vision transformer designed to be fast, simple, and strong across image and video recognition tasks. The core idea is to use straightforward hierarchical attention with a minimal set of architectural “bells and whistles,” achieving competitive or superior accuracy while being markedly faster at inference and often faster to train. The repository provides installation options (from source or Torch Hub), a model zoo with pre-trained checkpoints, and code for evaluation and fine-tuning on standard benchmarks. ... -
Parasoft: Automated Testing to Deliver Superior Quality SoftwareParasoft helps organizations continuously deliver high-quality software with its AI-powered software testing platform and automated test solutions. Supporting the embedded, enterprise, and IoT markets, Parasoft’s proven technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to web UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. Bringing all this together, Parasoft’s award-winning reporting and analytics dashboard provides a centralized view of quality, enabling organizations to deliver with confidence and succeed in today’s most strategic ecosystems and development initiatives—security, safety-critical, Agile, DevOps, and continuous testing.
-
10
aisuite
Simple, unified interface to multiple Generative AI providers
Simple, unified interface to multiple Generative AI providers. aisuite makes it easy for developers to use multiple LLM through a standardized interface. Using an interface similar to OpenAI's, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. -
11
Unsloth
Finetune Llama 3.2, Mistral, Phi & Gemma LLMs 2-5x faster
Unsloth is a framework designed to significantly improve the performance of Llama 3.3, DeepSeek-R1, and other reasoning large language models (LLMs). It optimizes these models to run up to 2x faster while using 70% less memory. Unsloth aims to make finetuning large models more efficient, offering users a simple, resource-efficient solution for customizing LLMs with their datasets. It provides a user-friendly experience through free notebooks and the ability to export finetuned models to various formats. -
12
Bootstrap Your Own Latent (BYOL)
Usable Implementation of "Bootstrap Your Own Latent" self-supervised
Practical implementation of an astoundingly simple method for self-supervised learning that achieves a new state-of-the-art (surpassing SimCLR) without contrastive learning and having to designate negative pairs. This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. -
13
PyTorch Ignite
Library to help with training and evaluating neural networks
...Extensible API for metrics, experiment managers, and other components. The cool thing with handlers is that they offer unparalleled flexibility (compared to, for example, callbacks). Handlers can be any function: e.g. lambda, simple function, class method, etc. Thus, we do not require to inherit from an interface and override its abstract methods which could unnecessarily bulk up your code and its complexity. Extremely simple engine and event system. Out-of-the-box metrics to easily evaluate models. Built-in handlers to compose training pipeline, save artifacts and log parameters and metrics. -
14
Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. ... -
15
API-for-Open-LLM
Openai style api for open large language models
API-for-Open-LLM is a lightweight API server designed for deploying and serving open large language models (LLMs), offering a simple way to integrate LLMs into applications. -
16
Nerve
The Simple Agent Development Kit
Nerve is a developer-friendly Agent Development Kit (ADK) that utilizes YAML and a CLI to define, run, orchestrate, and evaluate LLM-driven agents. It supports declarative setups, tool integration, workflow pipelines, and both MCP client and server roles. Nerve is a simple yet powerful Agent Development Kit (ADK) to build, run, evaluate, and orchestrate LLM-based agents using just YAML and a CLI. It’s designed for technical users who want programmable, auditable, and reproducible automation using large language models. Define agents using a clean YAML format: system prompt, task, tools, and variables — all in one file. -
17
KServe
Standardized Serverless ML Inference Platform on Kubernetes
...It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary Rollouts to your ML deployments. It enables a simple, pluggable, and complete story for Production ML Serving including prediction, pre-processing, post-processing and explainability. KServe is being used across various organizations. -
18
Scrapling
An undetectable, powerful, flexible, high-performance Python library
Scrapling is a Python scraping framework built for the modern web, combining high-performance fetchers with a rapid parsing engine to handle dynamic sites and anti-bot countermeasures. It emphasizes being “undetectable,” flexible, and fast, offering an approachable API for both experienced scrapers and newcomers. The library targets the full scraping pipeline: session handling, fetching, rendering when needed, parsing, and export—while keeping ergonomics front and center. Community posts and... -
19
NVIDIA AgentIQ
The NVIDIA AgentIQ toolkit is an open-source library
...It provides a framework-agnostic platform that integrates seamlessly with various data sources and tools, enabling developers to build composable and reusable agentic workflows. By treating agents, tools, and workflows as simple function calls, AgentIQ facilitates rapid development and optimization of AI-driven applications, enhancing collaboration and efficiency in complex tasks. -
20
Deep Lake
Data Lake for Deep Learning. Build, manage, and query datasets
Deep Lake (formerly known as Activeloop Hub) is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the cloud, and it enables you to store all of your data in one place, ranging from simple annotations to large videos. Deep Lake is used by Google, Waymo, Red Cross, Omdena, Yale, & Oxford. Use one API to upload, download, and stream datasets to/from AWS S3/S3-compatible storage, GCP, Activeloop cloud, or local storage. ... -
21
GluonTS
Probabilistic time series modeling in Python
GluonTS is a Python package for probabilistic time series modeling, focusing on deep learning based models. GluonTS requires Python 3.6 or newer, and the easiest way to install it is via pip. We train a DeepAR-model and make predictions using the simple "airpassengers" dataset. The dataset consists of a single time-series, containing monthly international passengers between the years 1949 and 1960, a total of 144 values (12 years * 12 months). We split the dataset into train and test parts, by removing the last three years (36 months) from the train data. Thus, we will train a model on just the first nine years of data. ... -
22
PPTAgent
PPTAgent: Generating and Evaluating Presentations
PPTAgent is a research system for generating and evaluating slide decks that goes beyond simple text-to-slides. It follows a two-stage, edit-based workflow: first it analyzes reference presentations to infer slide roles and structure, then it drafts an outline and iteratively performs editing actions to produce new slides. The project includes both the generation agent and an evaluation framework, PPTEval, to score content quality, design, and coherence. -
23
ChatGPT Clone
ChatGPT interface with better UI
...The project is useful for prototyping assistants, documentation bots, and internal developer tools without committing to a specific vendor or UI framework. Configuration is kept simple so newcomers can get a working chat in minutes and then dial in features like authentication or multi-model routing. While it illustrates how to hook into third-party LLM endpoints, it is typically positioned as an educational, self-hosted starter that you should operate responsibly and within provider's terms of use. -
24
MCP Agent
Build effective agents using Model Context Protocol
The MCP Agent is a framework that enables the construction of effective AI agents using the Model Context Protocol. It focuses on simple, composable patterns to build production-ready AI agents, facilitating seamless integration with various tools and services to enhance AI capabilities. -
25
TensorLy
Tensor Learning in Python
TensorLy is a Python library that aims at making tensor learning simple and accessible. It allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, PyTorch, JAX, TensorFlow, CuPy or Paddle, and run methods at scale on CPU or GPU.
