Search Results for "delphi source code" - Page 6

Showing 2405 open source projects for "delphi source code"

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  • 1
    ex-skill

    ex-skill

    Distill your ex into an AI Skill

    ex-skill is an experimental AI tooling project that allows users to transform personal memories, particularly past relationships, into interactive AI “skills” that replicate the communication style, personality, and behavioral patterns of a specific individual. The system works by ingesting various forms of personal data such as chat logs, social media content, photos, and user-provided descriptions, then structuring this information into a layered representation that combines memory and...
    Downloads: 20 This Week
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  • 2
    py2many

    py2many

    Transpiler of Python to many other languages

    ...We can fix that by transpiring a subset of the language into a more performant, statically typed language. A second benefit is security. Writing security-sensitive code in a low-level language like C is error-prone and could lead to privilege escalation. Specialized languages such as wuffs exist to address this use case. py2many can be a more general-purpose solution to the problem where you can verify the source via unit tests before you transpile. Swift and Kotlin dominate the mobile app development workflow. ...
    Downloads: 4 This Week
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  • 3
    DVC

    DVC

    Data Version Control | Git for Data & Models

    DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets,...
    Downloads: 4 This Week
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  • 4
    CodiumAI PR-Agent

    CodiumAI PR-Agent

    AI-Powered tool for automated pull request analysis

    CodiumAI PR-Agent is an open-source tool aiming to help developers review pull requests faster and more efficiently. It automatically analyzes the pull request and can provide several types of commands. See the Usage Guide for instructions how to run the different tools from CLI, online usage, Or by automatically triggering them when a new PR is opened. You can try GPT-4 powered PR-Agent, on your public GitHub repository, instantly. Just mention @CodiumAI-Agent and add the desired command in...
    Downloads: 4 This Week
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  • 5
    ChatDBG

    ChatDBG

    ChatDBG - AI-assisted debugging. Uses AI to answer 'why'

    ChatDBG is an AI-assisted debugging tool that integrates large language models into standard debuggers like pdb, lldb, and gdb. It allows developers to engage in a dialog with the debugger, asking open-ended questions about their program's behavior, and provides error diagnoses and suggested fixes.
    Downloads: 5 This Week
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  • 6
    LLMStack

    LLMStack

    No-code multi-agent framework to build LLM Agents, workflows

    LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise.
    Downloads: 3 This Week
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  • 7
    Label Sleuth

    Label Sleuth

    Open source no-code system for text annotation and building of text

    An open-source no-code system for text annotation and building text classifiers. No AI knowledge needed. From task definition to working model in just a few hours! While domain experts label their data, Label Sleuth automatically trains in the background-appropriate machine learning models. To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeled next.
    Downloads: 4 This Week
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  • 8
    CosyVoice

    CosyVoice

    Multi-lingual large voice generation model, providing inference

    CosyVoice is a multilingual large voice generation model that offers a full-stack solution for training, inference, and deployment of high-quality TTS systems. The model supports multiple languages, including Chinese, English, Japanese, Korean, and a range of Chinese dialects such as Cantonese, Sichuanese, Shanghainese, Tianjinese, and Wuhanese. It is designed for zero-shot voice cloning and cross-lingual or mix-lingual scenarios, so a single reference voice can be used to synthesize speech...
    Downloads: 8 This Week
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  • 9
    Read the Docs

    Read the Docs

    The source code that powers readthedocs.org

    Read the Docs is a platform that automates building, versioning, and hosting documentation from source repositories. Supporting Sphinx, MkDocs, Jupyter Book, and more, it integrates with GitHub, GitLab, and Bitbucket to trigger automatic builds upon updates. Both open-source projects and private documentation can be hosted, with previews, search, audits, and analytics, enabling seamless “Docs as Code” workflows.
    Downloads: 4 This Week
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  • 10
    sparkmagic

    sparkmagic

    Jupyter magics and kernels for working with remote Spark clusters

    Sparkmagic is a set of tools for interactively working with remote Spark clusters in Jupyter notebooks. Sparkmagic interacts with remote Spark clusters through a REST server. Automatic visualization of SQL queries in the PySpark, Spark and SparkR kernels; use an easy visual interface to interactively construct visualizations, no code required. Ability to capture the output of SQL queries as Pandas dataframes to interact with other Python libraries (e.g. matplotlib). Send local files or...
    Downloads: 4 This Week
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  • 11
    Ludwig AI

    Ludwig AI

    Low-code framework for building custom LLMs, neural networks

    Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),...
    Downloads: 16 This Week
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  • 12

    Python Fire

    Automatically generate CLIs from absolutely any Python object

    Python Fire is a library that automatically generates command line interfaces (CLIs) from absolutely any Python object. It’s a really simple and easy way to create CLI in Python, and can also enable you to explore existing code or turn other people’s code into a CLI. Python Fire lets you call Fire on any Python object: be it functions, classes, objects, modules, lists-- you name it! It will help you develop as well as debug Python code, and make transitioning between Bash and Python a...
    Downloads: 0 This Week
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  • 13
    srsly

    srsly

    Modern high-performance serialization utilities for Python

    This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that's correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle, and YAML. Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings,...
    Downloads: 20 This Week
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  • 14
    UltraRAG

    UltraRAG

    Less Code, Lower Barrier, Faster Deployment

    UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It...
    Downloads: 5 This Week
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  • 15
    Full Stack FastAPI and PostgreSQL

    Full Stack FastAPI and PostgreSQL

    Full stack, modern web application generator

    Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic...
    Downloads: 5 This Week
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  • 16
    theHarvester

    theHarvester

    E-mails, subdomains and names

    theHarvester is a very simple to use, yet powerful and effective tool designed to be used in the early stages of a penetration test or red team engagement. Use it for open source intelligence (OSINT) gathering to help determine a company's external threat landscape on the internet. The tool gathers emails, names, subdomains, IPs and URLs using multiple public data sources.
    Downloads: 47 This Week
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  • 17
    Mito

    Mito

    AI-powered Jupyter spreadsheet that converts workflows into Python

    Mito is an open source set of Jupyter extensions designed to speed up Python workflows and data analysis. It combines a spreadsheet-style interface with AI-assisted coding, allowing users to explore, clean, and transform data without switching tools. Mito includes a context-aware AI assistant that helps generate code, debug errors, and guide workflows directly inside Jupyter.
    Downloads: 1 This Week
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  • 18
    AIDE ML

    AIDE ML

    AI-Driven Exploration in the Space of Code

    AIDE ML is an open-source research framework designed to explore automated machine learning development through agent-based search and code optimization. The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. ...
    Downloads: 1 This Week
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  • 19
    book-to-skill

    book-to-skill

    Turn any technical book PDF into a Claude Code skill

    ...The goal is not simply to summarize a book, but to make its knowledge available during problem solving and implementation. book-to-skill is best suited for developers and researchers who want AI assistants to work from specific long-form source material.
    Downloads: 3 This Week
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  • 20
    pytype

    pytype

    A static type analyzer for Python code

    pytype is a static type analyzer that checks and infers types for Python code without executing it, catching errors at “compile time” and generating actionable diagnostics. It grew alongside Python typing at Google and can understand both inline annotations and unannotated code via powerful inference. The tool consumes stub files (.pyi) for the standard library and third-party packages (from typeshed and its own built-ins), enabling accurate checks even in large, mixed-quality codebases....
    Downloads: 0 This Week
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  • 21
    PyGAD

    PyGAD

    Source code of PyGAD, Python 3 library for building genetic algorithms

    PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function.
    Downloads: 4 This Week
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  • 22
    arxiv_latex_cleaner

    arxiv_latex_cleaner

    arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper

    This tool allows you to easily clean the LaTeX code of your paper to submit to arXiv. From a folder containing all your code, e.g. /path/to/latex/, it creates a new folder /path/to/latex_arXiv/, that is ready to ZIP and upload to arXiv.
    Downloads: 0 This Week
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  • 23
    Vibe-Trading

    Vibe-Trading

    Vibe-Trading: Your Personal Trading Agent

    Vibe-Trading is an AI-powered multi-agent financial workspace that converts natural language inputs into executable trading strategies and market analysis. It allows users to describe investment ideas in plain language, which are then translated into code, backtested, and evaluated across global markets. The platform integrates multiple data sources, including equities, crypto, and derivatives, with automatic fallback mechanisms. It features a swarm-based architecture with prebuilt expert...
    Downloads: 14 This Week
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  • 24
    Microsandbox

    Microsandbox

    Secure local-first microVM sandbox for running untrusted code fast

    Microsandbox is an open source platform designed to securely execute untrusted code in isolated environments using lightweight virtualization techniques. It focuses on combining strong security guarantees with fast startup times by leveraging hardware-level microVM isolation instead of relying solely on traditional containers or full virtual machines. It aims to solve the common tradeoffs between speed, isolation, and control that developers encounter when running untrusted workloads. ...
    Downloads: 5 This Week
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  • 25
    MLE-bench

    MLE-bench

    AI multi-agent framework for automating data-driven R&D workflows

    RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. ...
    Downloads: 5 This Week
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