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Showing 207 open source projects for "result"
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Douyin TikTok Download API
Douyin TikTok Download API
Use the official interface to capture Douyin|TikTok data, support API calls, Web portals, and batch analysis. Fast, asynchronous, free, open source, ad-free, long-term maintenance. This project is based on PyWebIO , FastAPI , HTTPX , a fast and asynchronous Douyin / TikTok data crawling tool, and realizes online batch parsing and downloading of watermark-free videos or atlases through the web, data crawling API, and iOS shortcut instructions for watermark-free download and other functions.... -
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autoresearch-mlx
Apple Silicon (MLX) port of Karpathy's autoresearch
autoresearch-mlx is an Apple Silicon–optimized implementation of the autoresearch framework that enables autonomous AI research loops to run natively on MLX without requiring PyTorch or CUDA dependencies. It maintains the core autoresearch structure, where an AI agent iteratively edits a training script, executes experiments under a fixed time budget, and evaluates results based on a defined metric such as validation bits per byte. The system is tailored for Apple hardware, leveraging... -
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react2shell-scanner
High Fidelity Detection Mechanism for RSC/Next.js RCE
react2shell-scanner is a security-oriented tool that bridges modern JavaScript (React) applications and shell scripting by auditing web front-ends for exposed interfaces that could be manipulated or controlled through command execution. It scans React codebases, identifies places where user input interacts with shell-executable contexts, and flags risky patterns that might lead to command injection, unvalidated arguments, or unsafe bindings between UI controls and underlying system actions.... -
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Sacred
Sacred is a tool to help you configure, andorganize IDSIA experiments
...You get a powerful command-line interface for each experiment that you can use to change parameters and run different variants. Observers that log all kinds of information about your experiment, its dependencies, the configuration you used, the machine it is run on, and of course the result. These can be saved to a MongoDB, for easy access later. -
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Wemake Django Template
Bleeding edge django template focused on code quality and security
...The main idea of this project is to provide a fully configured template for django projects, where code quality, testing, documentation, security, and scalability are number one priorities. This template is a result of implementing our processes, it should not be considered as an independent part. When developing this template we had several goals in mind. Development environment should be bootstrapped easily, so we use docker-compose for that. Development should be consistent, so we use strict quality and style checks. Development, testing, and production should have the same environment, so again we develop, test, and run our apps in docker containers. ... -
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django-import-export
Django application and library for importing and exporting data
...By default all records will be imported, even if no changes are detected. This can be changed setting the skip_unchanged option. Also, the report_skipped option controls whether skipped records appear in the import Result object, and if using the admin whether skipped records will show in the import preview page. Not all data can be easily extracted from an object/model attribute. In order to turn complicated data model into a (generally simpler) processed data structure on export, dehydrate_<fieldname> method should be defined. -
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Mercury
Convert Python notebook to web app and share with non-technical users
...Mercury is a perfect tool to convert Python notebook to interactive web application and share with non-programmers. You define interactive widgets for your notebook with the YAML header. Your users can change the widgets values, execute the notebook and save result (as PDF or html file). You can hide your code to not scare your (non-coding) collaborators. Easily deploy to any server. Mercury is dual-licensed. Looking for dedicated support, a commercial-friendly license, and more features? The Mercury Pro is for you. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). ... -
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screenshot-to-code
Drop in a screenshot and convert it to clean code
...A web interface lets you upload images, tune options, and preview generated results, while a backend service orchestrates the model calls and post-processing. The tool focuses on practical developer outputs—semantic markup, reusable components, and readable classes—so the result is a starting point you can refine, not a throwaway demo. It also supports multi-model backends and local-first options to balance cost, speed, and privacy. Teams use it for rapid prototyping, migrating static mockups to codebases, and exploring design alternatives without hand-coding every pixel from scratch. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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openbench
Provider-agnostic, open-source evaluation infrastructure
openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves. With a simple CLI interface (e.g. bench eval... -
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OpenHarness
Open Agent Harness with a built-in personal agent, Ohmo
OpenHarness is an open-source framework developed to support large-scale machine learning workflows, particularly in the context of training, evaluating, and benchmarking AI models. It provides a structured environment for orchestrating experiments, managing datasets, and standardizing evaluation processes across different models. The project focuses on reproducibility and scalability, allowing researchers and engineers to run consistent experiments while tracking results effectively. It... -
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Claude Agent SDK for Python
Python SDK for Claude Agent
Claude Agent SDK (Python) is the official Python counterpart to the TypeScript Agent SDK from Anthropic, designed to let Python developers build powerful autonomous AI agents with Claude Code under the hood. The SDK wraps the core functionality of Claude Code and exposes high-level asynchronous and synchronous interfaces to query prompts, manage sessions, and orchestrate tool use — so you can build agents that understand code, make edits, run bash commands, interact with files, and handle... -
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Engram
A New Axis of Sparsity for Large Language Models
Engram is a high-performance embedding and similarity search library focused on making retrieval-augmented workflows efficient, scalable, and easy to adopt by developers building search, recommendation, or semantic matching systems. It provides utilities to generate embeddings from text or other structured data, index them using efficient approximate nearest neighbor algorithms, and perform real-time similarity queries even on large corpora. Engineered with speed and memory efficiency in... -
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TensorRT Node for ComfyUI
Enables the best performance on NVIDIA RTX Graphics Cards
ComfyUI_TensorRT is an extension that lets ComfyUI run AI inference through NVIDIA’s TensorRT, aiming to get faster, more efficient execution on supported GPUs. It bridges the gap between ComfyUI’s flexible, node-based workflows and TensorRT’s highly optimized engine format. The result is that complex diffusion or image-processing graphs can be accelerated without the user having to rewrite the pipeline. The repo typically includes instructions for converting models to TensorRT engines and for wiring those engines into ComfyUI nodes. This is particularly attractive for power users who run many generations or who host ComfyUI on dedicated hardware and want to squeeze out every bit of GPU performance. ... -
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Swift Numerics
Advanced mathematical types and functions for Swift
...API design follows Swift’s emphasis on value semantics and protocol-oriented programming, enabling compiler optimizations and predictable performance. The modules are factored to keep dependencies minimal and to allow adopters to pull in only what they need. As a result, Swift Numerics underpins higher-level libraries in simulation, signal processing, and machine learning written in pure Swift. -
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VectorVein
No-code AI workflow
...A workflow represents a work task process that includes input, output, and workflow triggering methods. You can arbitrarily define what the input is, what the output is, and how the input is processed and reaches the output result. -
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VCR.py
Automatically mock your HTTP interactions to simplify testing
...When the relevant piece of code is executed again, VCR.py will read the serialized requests and responses from the aforementioned cassette file, and intercept any HTTP requests that it recognizes from the original test run and return the responses that corresponded to those requests. This means that the requests will not actually result in HTTP traffic, which confers several benefits including: -
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Unicorn
The magical reactive component framework for Django
...Skip creating a bunch of serializers and just use Django. Unicorn progressively enhances a normal Django view, so the initial render of components is fast and great for SEO. The end result is that you can focus on writing regular Django templates and Python classes without needing to switch to another language or build unnecessary plumbing. Best of all, the JavaScript portion is a paltry. Unicorn is a reactive component framework that progressively enhances a normal Django view, makes AJAX calls in the background, and dynamically updates the DOM. ... -
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Amazon Braket Default Simulator
An implementation of a quantum simulator that you can run locally
...You must have the Amazon Braket SDK installed to use the local simulator. Follow the instructions in the README for setup. If you want to contribute to the project, be sure to run unit tests and get a successful result before you submit a pull request. The execution times for the performance tests are affected by the other processes running on the system. In order to get stable results, stop other applications when running these tests. -
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HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
...To support training, the team built a scalable data engine that automatically curates large video datasets with camera pose estimation and metric depth prediction. As a result, Voyager delivers state-of-the-art performance on world exploration benchmarks while maintaining photometric, style, and 3D consistency. -
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linkedin2username
Generate probable usernames from LinkedIn company employee lists
linkedin2username is an open source OSINT (Open Source Intelligence) tool designed to generate lists of potential usernames by scraping employee information from a company’s LinkedIn page. It logs into LinkedIn using valid user credentials and collects publicly visible employee names associated with a specified organization. Using these names, it automatically generates multiple possible username formats that organizations commonly use for accounts or email addresses. This process helps... -
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CAG
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
...This strategy allows the model to generate responses using the cached context directly, eliminating the need for repeated retrieval operations during runtime. As a result, the approach can significantly reduce latency and simplify system architecture compared with traditional RAG pipelines. The framework is particularly effective when the knowledge base is limited enough to fit within the extended context window of modern language models. -
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Perfect Pixel
Refine and quantize messy AI pixel art into clean, perfect pixels
...It tackles a common problem with AI pixel art: edges that look pixelated at first glance but are not actually aligned to a coherent pixel grid, which causes shimmer, blur, and uneven block sizes when you zoom in. The tool analyzes an image to infer the intended grid size, then refines and quantizes the artwork so pixels snap into consistent cells and the final result looks crisp and intentional. This makes it useful for game developers, sprite artists, and hobbyists who want to use AI-assisted ideation without shipping “almost pixel art” assets. It is designed to be easy to slot into an existing pipeline, whether you are batch-processing images or cleaning up a few key assets for a project. -
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DomainBed
DomainBed is a suite to test domain generalization algorithms
DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and... -
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EdgeDB
A next-generation graph-relational database
The world's favorite graph-relational database is back for an action-packed sequel. Tune in for a series of lightning talks breaking down what's new and what's next for EdgeDB. EdgeDB is an open-source database designed as a spiritual successor to SQL and the relational paradigm. It aims to solve some hard design problems that make existing databases unnecessarily onerous to use. Powered by the Postgres query engine under the hood, EdgeDB thinks about schema the same way you do: as objects...
