Search Results for "code source ping" - Page 20
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Showing 1400 open source projects for "code source ping"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Axolotl
Go ahead and axolotl questions
Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training. -
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Composio
Composio equip's your AI agents & LLMs
Empower your AI agents with Composio - a platform for managing and integrating tools with LLMs & AI agents using Function Calling. Equip your agent with high-quality tools & integrations without worrying about authentication, accuracy, and reliability in a single line of code. -
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ProxyAI
The leading open-source AI copilot for JetBrains
ProxyAI is an open-source AI-powered coding assistant designed primarily for JetBrains IDEs, offering a highly customizable alternative to tools like GitHub Copilot while maintaining flexibility across multiple AI providers and deployment environments. It allows developers to connect to a wide range of language models, including cloud-based services and locally hosted models, enabling both online and fully offline workflows depending on user preferences. -
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Bedrock Chat
AWS-native chatbot using Bedrock
...Implementations like Bedrock Chat often integrate with model hosting platforms or APIs that provide access to generative AI systems. The mirror hosted on SourceForge exists primarily to ensure long-term accessibility of the source code and provide alternative download options for developers. Chat platforms of this type frequently include tools for maintaining conversation history, managing prompts, and connecting to multiple model providers. By combining a chat interface with backend AI services, these systems allow users to explore generative AI capabilities in a structured environment. -
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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II Agent
A new open-source framework to build and deploy intelligent agents
II-Agent is an open-source intelligent assistant framework designed to automate complex workflows across multiple domains using large language models and external tools. The platform allows users to interact with multiple AI models within a single environment while connecting those models to external services and knowledge sources. Through a unified interface, users can switch between models, access specialized tools, and execute tasks that require information retrieval, code execution, or file analysis. ... -
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ML.NET
Open source and cross-platform machine learning framework for .NET
With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that... -
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Cofounder
AI tool that generates full-stack web apps with generative UI systems
...Cofounder also provides a dashboard and local API environment that helps manage project generation, iteration, and interaction with the system. Generated projects are stored locally and can be launched using standard development commands, allowing developers to run and modify the code that the system produces. Cofounder relies on configurable nodes and sequences that define how AI operations are executed. -
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Bot Framework Web Chat
A highly-customizable web-based client for Azure Bot Services
This repository contains code for the Bot Framework Web Chat component. The Bot Framework Web Chat component is a highly-customizable web-based client for the Bot Framework V4 SDK. The Bot Framework SDK v4 enables developers to model conversation and build sophisticated bot applications. This repo is part of the Microsoft Bot Framework, a comprehensive framework for building enterprise-grade conversational AI experiences. -
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MiniMind-O
A 0.1B Omni model trained from scratch
MiniMind-O is an educational open-source project for building a small end-to-end Omni model from scratch. It extends the MiniMind family by exploring a model that can handle text, audio, and image inputs while producing text and streaming speech outputs. The project is designed to make multimodal AI training more accessible by keeping the model size small enough for ordinary personal hardware. -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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A.I.G
Full-stack AI Red Teaming platform
AI-Infra-Guard is a powerful open-source security platform from Tencent’s Zhuque Lab designed to assess the safety and resilience of AI infrastructures, codebases, and components through automated scanning and evaluation tools. It brings together AI infrastructure vulnerability scanning, MCP server risk analysis, and jailbreak evaluation into a unified workflow so that enterprises and individuals can identify critical security issues without relying on external services. Users can deploy it... -
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Semantic Router
Superfast AI decision making and processing of multi-modal data
Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited. Semantic Router enables... -
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Harmonist
Portable AI agent orchestration with mechanical protocol enforcement
Harmonist is a portable multi-agent orchestration framework for AI coding assistants such as Cursor, Claude Code, Copilot, Windsurf, and Aider. It is designed to make agent workflows more reliable by enforcing protocol rules mechanically instead of trusting prompts alone. The framework includes a catalog of specialized agents, validated memory behavior, supply-chain checks, and hooks that gate code-changing turns. If required reviewers do not run, memory is not updated, or shipped files fail... -
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Wondel.ai Skills
Agent skills for Claude Code and other agentskills-compatible agents
Wondel.ai Skills is a repository that provides modular capability packages for AI agents, particularly those operating within Claude Code and similar ecosystems. Each skill represents a structured set of instructions, workflows, and tools that enable agents to perform specific tasks with expertise. These skills can cover a wide range of domains, including development, automation, and problem-solving, allowing agents to extend their capabilities dynamically. The system emphasizes modularity,... -
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pg-aiguide
MCP server and Claude plugin for Postgres skills and documentation
pg-aiguide is a tool designed to enhance AI-assisted development with PostgreSQL by providing structured knowledge and skills directly to coding agents. It acts as a bridge between database documentation and AI tools, enabling more accurate generation of SQL queries and database interactions. The system integrates with Claude Code through an MCP server, allowing agents to access curated PostgreSQL knowledge in real time. It focuses on improving developer productivity by reducing errors and... -
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Harness
A meta-skill that designs domain-specific agent teams
Harness is a meta-skill framework designed to automate the creation and orchestration of domain-specific AI agent teams within Claude Code environments. Instead of manually defining agents and their behaviors, it generates specialized agents, assigns them roles, and produces the skills they need to execute tasks effectively. The system focuses on scaling agent-based workflows by dynamically assembling teams tailored to specific problems. It enables structured collaboration between agents,... -
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Context Mode
Context window optimization for AI coding agents
Context Mode is a development approach and tooling concept that enhances how AI-assisted coding environments manage and inject context into language model interactions. It focuses on improving the relevance and accuracy of AI-generated outputs by controlling what information is provided to the model at each step. The project explores structured context management, enabling developers to define how files, code snippets, and metadata are included in prompts. It is particularly useful for large... -
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Godot MCP
MCP server for interfacing with Godot game engine
Godot MCP is a Model Context Protocol server that enables AI assistants to directly interact with the Godot game engine, allowing programmatic control over game development workflows through natural language or agent-driven commands. It acts as a bridge between AI systems and the Godot editor, providing capabilities such as launching projects, running games in debug mode, and capturing runtime output for analysis. The tool is particularly valuable for AI-assisted game development, as it... -
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FormCreate
The easy-to-use Vue low-code visual AI form designer
FormCreate is a low-code visual form builder built on Vue that enables developers to create complex, dynamic forms through a drag-and-drop interface rather than manual coding. It is part of the broader form-create ecosystem and leverages JSON-based schema generation to dynamically render forms, handle validation, and manage data collection workflows. The tool is designed to significantly reduce development time by allowing users to visually assemble forms while automatically generating the... -
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dots.ocr
Multilingual Document Layout Parsing in a Single Vision-Language Model
dots.ocr is a cutting-edge multilingual document parsing system built on a unified vision-language model that combines layout detection, text recognition, and structural understanding into a single architecture. Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective... -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric... -
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Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics
Machine Learning Foundations repository contains the code, notebooks, and teaching materials used in Jon Krohn’s Machine Learning Foundations curriculum. The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. The... -
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SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before... -
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Agentic Coding Flywheel Setup
System tool for beginners wanting agentic engineering capabilities
Agentic Coding Flywheel Setup (ACFS) is a comprehensive environment bootstrap project that configures a full stack of tools for autonomous AI-assisted coding workflows. With a single shell installer, ACFS transforms a fresh compute environment into a ready-to-use development setup that includes modern shells, language runtimes, AI coding agents (like Claude Code, Codex CLI, and Gemini CLI), and a coordinated toolchain for orchestration and safety. The system is designed for developers who... -
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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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handson-ml
Teaching you the fundamentals of Machine Learning in python
handson-ml hosts the notebooks for the first edition of the same hands-on ML book, reflecting the tooling and idioms of its time while teaching durable concepts. It walks through supervised and unsupervised learning with scikit-learn, then introduces deep learning using the earlier TensorFlow 1 graph-execution style. The examples underscore fundamentals like bias-variance trade-offs, regularization, and proper validation, grounding learners before they move to deep nets. Even though the deep...
