Search Results for "delphi source code" - Page 12
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Showing 1533 open source projects for "delphi source code"
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
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PipesHub
Workplace AI platform for enterprise search and workflow automation
PipesHub AI is an open-source, enterprise-grade workplace AI platform designed to unify search, knowledge management, and workflow automation across distributed organizational systems. It connects to a wide range of enterprise tools such as Google Workspace, Slack, Jira, and Confluence, aggregating data into a centralized knowledge layer that can be queried using natural language. -
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TypedAI
TypeScript AI platform with AI chat, Autonomous agents
TypedAI is an open-source TypeScript platform designed for building and running AI agents, chatbots, and large language model workflows. The framework provides developers with a full-featured environment for designing autonomous agents capable of performing complex tasks such as code analysis, workflow automation, or conversational assistance. Written in TypeScript, the platform emphasizes strong typing and structured development patterns to improve reliability when building AI-driven systems. ... -
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Laravel Boost
Laravel-focused MCP server for augmenting AI powered local development
Boost is a Laravel-first toolkit that supercharges AI-assisted development by giving assistants structured, Laravel-aware context. At its core it runs as an MCP server that exposes a battery of Laravel-specific tools, so an AI agent can explore your app, inspect code and config, and take targeted actions instead of guessing. It ships opinionated, composable guidelines tuned for popular Laravel packages, which helps keep generated code idiomatic and consistent with framework norms. The... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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Tribe AI
Low code tool to rapidly build and coordinate multi-agent teams
Low code tool to rapidly build and coordinate multi-agent teams. Have you heard the saying, 'Two minds are better than one'? That's true for agents too. Tribe leverages on the langgraph framework to let you customize and coordinate teams of agents easily. By splitting up tough tasks among agents who are good at different things, each one can focus on what it does best. This makes solving problems faster and better. -
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a-stock-data
Full-stack China A-Share data toolkit for AI coding assistants
a-stock-data is a self-contained AI agent skill for accessing Chinese A-share market data through direct HTTP data sources. It packages data access logic into a structured skill file so coding assistants can retrieve and analyze stock information without relying on separate third-party wrapper libraries. The project organizes data across multiple layers, including market quotes, research reports, signals, capital flows, news, announcements, macro data, and financial statements. It is... -
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GitMCP
Turn any GitHub repository into an MCP documentation server for AI
GitMCP is an open source remote Model Context Protocol (MCP) server designed to transform GitHub repositories into structured documentation hubs that AI assistants can query directly. It enables developer-focused AI tools to access up-to-date project documentation and source code so that responses are grounded in real repository content rather than outdated training data. -
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agentation
The visual feedback tool for agents
Agentation is a visual annotation and feedback tool designed to make interacting with AI coding agents more intuitive and precise by letting developers visually click on frontend elements in a browser and annotate them with context before sending structured feedback to an agent. Instead of describing UI elements in text — like “the blue button in the sidebar” — users click directly on elements to automatically capture selectors, positions, and contextual metadata that can be consumed by AI... -
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Appsmith
Low code project to build admin panels, internal tools, and dashboards
Low code project to build admin panels, internal tools, and dashboards. Integrates with 15+ databases and any API. Appsmith is an open-source platform to build, deploy, and maintain internal apps. You can build anything from simple CRUD apps, admin panels, dashboards to custom business apps and complicated multi-step workflows. Build your UI with our drag and drop UI builder. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Dyad
Free, local, open-source AI app builder
...All source code remains on your device and integrates seamlessly with your preferred IDE. A natural-language API enables powerful data queries and updates, automating tasks without leaving the chat interface. By running entirely locally, Dyad delivers maximum privacy, minimal latency, and smooth developer experiences free from cloud-based inconsistencies. -
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td
Telegram client, in Go. (MTProto API)
Telegram MTProto API client in Go for users and bots. -
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Gen.jl
A general-purpose probabilistic programming system
...Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code. Users can also hand-code parts of their models that demand better performance. Neural network inference is fast, but can be inaccurate on out-of-distribution data, and requires expensive training. -
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Gemini MCP Tool
MCP server that enables AI assistants to interact with Google Gemini
Gemini MCP Tool is a lightweight MCP server that enables AI assistants to interface directly with the Google Gemini CLI, effectively extending the capabilities of one AI system by leveraging another. Its primary purpose is to allow tools like Claude or other MCP-compatible agents to offload complex or large-scale analysis tasks to Gemini, particularly when working with large files or codebases. The system takes advantage of Gemini’s large context window, enabling deeper analysis of extensive... -
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MCPB
One-click local MCP server installation in desktop apps
MCPB (MCP Bundles) defines a packaging format and toolchain for one-click installation of local Model Context Protocol (MCP) servers in desktop apps like Claude for macOS and Windows. An .mcpb file is a zip archive containing your server and a manifest.json that declares capabilities, entry points, permissions, and configuration inputs, much like how .crx packages Chrome extensions or .vsix packages VS Code extensions. The goal is to make local tool servers easy for end users to install,... -
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Feynman
The open source AI research agent
Feynman is a command-line AI research agent designed to automate complex research workflows by orchestrating multiple specialized agents that collaborate to gather, analyze, and synthesize information into structured outputs. It operates as a “Claude Code for research,” allowing users to input natural language queries and receive fully developed, source-grounded research briefs, literature reviews, or experimental analyses. The system is built around a multi-agent architecture that includes roles such as researcher, reviewer, writer, and verifier, each responsible for a specific stage of the research pipeline. ... -
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Ploomber
The fastest way to build data pipelines
Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. ... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
AI-Codereview-Gitlab is an open-source automation tool that integrates large language models into the GitLab development workflow to perform automated code reviews. The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform allows teams to choose the AI engine that best fits their infrastructure and privacy requirements. ... -
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Build with Claude
A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins
Build with Claude is an open-source plugin marketplace and discovery hub for the Claude Code ecosystem that centralizes hundreds of plugins, agents, commands, hooks, skills, and marketplaces to enhance developer workflows with autonomous AI functionality. It serves as a one-stop index where users can browse curated agent modules for tasks like blockchain development, code analysis, DevOps, documentation generation, and much more — all designed to be installed directly into Claude Code using a simple plugin system. ... -
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Bytebot
Bytebot is an AI desktop agent that automates computer tasks
Bytebot is an open-source AI assistant and automation framework built to help developers and teams automate repetitive software development tasks, accelerate coding workflows, and integrate intelligent assistance into everyday tooling. It typically includes capabilities for code generation, refactoring suggestions, automated testing assistance, and integration with source control systems to make commits or generate pull requests guided by natural language prompts. ... -
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Big-AGI
AI suite powered by state-of-the-art models and providing advanced AI
Big-AGI is a comprehensive, open-source AI workspace built to serve as a powerful multi-model interface for developers, researchers, and professionals who want deep control over generative AI workflows and outputs. It unifies access to multiple large language models (LLMs) and AI services through a modern web UI that emphasizes efficient interaction, flexibility, and extensibility, enabling users to conduct multi-model chats, execute code, generate images, and perform voice or text-based tasks all in one place. ... -
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Self-hosted AI Package
Run all your local AI together in one package
Self-hosted AI Package is an open-source Docker Compose-based starter kit that makes it easy to bootstrap a full local AI and low-code development environment with commonly used open tools, empowering developers to run LLMs and AI workflows entirely on their infrastructure. The stack typically includes Ollama for running local large language models, n8n as a low-code workflow automation platform, Supabase for database and vector storage, Open WebUI for interacting with models, Flowise for agent building, and additional services like SearXNG, Neo4j, and Langfuse for search, knowledge graphs, and observability. ... -
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Python Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models for NER
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models. -
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Factory AI
Agent-Native Software Development
...At its core, the system introduces the concept of “Droids,” specialized AI agents that operate across development environments such as the command line, web interfaces, project management tools, and communication platforms, enabling seamless interaction with engineering workflows. Rather than acting as a simple coding assistant, Factory is positioned as a full command center for development, where AI agents can autonomously write code, review pull requests, debug issues, and even coordinate tasks across tools like GitHub, Jira, or Slack. The platform integrates deeply with existing repositories and infrastructure, allowing it to analyze source code, monitor logs, and use contextual data from observability systems to make informed decisions. -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. -
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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.
