Search Results for "api" - Page 10
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Showing 1193 open source projects for "api"
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agentgateway
Next Generation Agentic Proxy for AI Agents and MCP servers
Agentgateway is an open-source “data plane” built specifically for agentic AI connectivity, focusing on how agents talk to other agents and to tools across different frameworks and environments. It presents itself as a complete connectivity solution that adds drop-in security, observability, and governance to agent-to-agent and agent-to-tool communication without requiring you to rebuild your agent stack. The project supports interoperable protocols designed for this ecosystem, including... -
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Forge Code
AI enabled pair programmer for Claude, GPT, O Series, Grok, Deepseek
...Rather than requiring a separate UI or web-based IDE, Forge respects the developer’s existing habits and setups, and keeps all operations local, ensuring your code doesn’t get sent to unknown external services — a strong point for privacy and security. It supports many model providers (e.g. GPT, Claude, Grok, and others) via API keys. -
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DocStrange
Extract and convert data from any document, images, pdfs, word doc
...It is built for developers who need high-quality parsing from scans, photos, PDFs, office files, and other document sources while preserving privacy and control over the processing flow. One of its key differentiators is deployment flexibility: it offers a cloud API for managed usage as well as a fully private offline mode that runs locally on a GPU. The platform also supports synchronous extraction, streaming responses, and asynchronous processing for larger documents, which makes it adaptable to both interactive workflows and heavier back-end pipelines. -
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Meta-World
Collections of robotics environments
...It also offers meta-learning benchmarks (ML1, ML10, ML45) that evaluate few-shot adaptation to new goals or entirely new tasks. The environments adhere to the Gymnasium API, which makes them easy to plug into existing RL pipelines, and they support both synchronous and asynchronous vectorized execution for running many environments in parallel. Installation is done via pip, with official support for Python versions 3.8 through 3.11 on Linux and macOS, and the project is licensed under MIT to encourage broad academic and industry use. -
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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OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
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SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image... -
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AutoBE
AI Vibe Coding Agent of TS backend server
AutoBE is an AI backend builder that turns natural-language requirements into a working TypeScript backend application. It analyzes what the user wants, creates specifications, designs database structure, defines API documentation, writes end-to-end tests, and generates implementation logic. The project is aimed at moving from prototype to production more quickly while keeping generated code buildable and verifiable. It uses an agentic workflow supported by compiler-friendly checks and test generation, which helps reduce the risk of incomplete AI output. ... -
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Context Hub
Makes coding agents get smarter with every task
...It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls, or workarounds across future sessions. Feedback can be sent back to maintainers so shared documentation improves over time. Context Hub is especially useful for teams that use AI coding assistants and want more reliable API usage, fewer hallucinated calls, and a transparent source of agent-readable context. -
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ds4.c
DeepSeek 4 Flash local inference engine for Metal
...Built as a native low-level implementation, it focuses on performance, reduced abstraction overhead, and direct integration with Apple GPU acceleration through Metal compute graphs. The project also supports streaming inference behavior and local API serving for integration with external tools and AI applications. Overall, ds4 represents a minimalist high-performance approach to running large language models locally without relying on heavyweight inference frameworks. -
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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OpenMed
Open source healthcare AI
...The project includes a curated registry of more than a dozen medical NER models focused on areas such as diseases, drugs, anatomy, genes, and protected health information, and it is built to support both research and deployment scenarios. OpenMed can be used in three main ways: as a simple Python API for scripts and notebooks, as a Docker-friendly FastAPI service for backend integration, and as a batch-processing system for multi-document workflows. -
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Cognita
Open source RAG framework for building scalable modular AI apps
Cognita is an open source framework designed to help developers build, organize, and deploy Retrieval-Augmented Generation (RAG) applications in a structured and production-ready way. It addresses the gap between quick experimentation in notebooks and the complexity of deploying scalable AI systems by introducing a modular and API-driven architecture. Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize each stage of the RAG pipeline independently. It includes both a backend service and a frontend interface, enabling users to upload documents, experiment with configurations, and perform question-answering tasks interactively. ... -
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skfolio
Python library for portfolio optimization built on top of scikit-learn
...The project provides a unified machine learning-style framework for building, validating, and comparing portfolio allocation strategies using financial data. By following the familiar scikit-learn API design, the library allows quantitative researchers and developers to apply techniques such as model selection, cross-validation, and hyperparameter tuning to portfolio construction workflows. It supports a wide range of allocation methods, from classical mean-variance optimization to modern techniques that rely on clustering, factor models, and risk-based allocations. ... -
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LangServe
Helps developers deploy LangChain runnables and chains as a REST API
...The tool simplifies the process of turning language-model pipelines, chains, and agents into web services that can be accessed by external applications. Instead of manually writing API endpoints, developers can use LangServe to automatically generate a server that exposes LangChain workflows through HTTP interfaces. The framework is built on top of FastAPI and uses Pydantic for request validation and structured data handling. It also includes client libraries that allow developers to interact with deployed chains from Python or JavaScript applications. ... -
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A.I.G
Full-stack AI Red Teaming platform
...Users can deploy it via Docker or scripts to get a modern web UI that guides them through tasks like scanning third-party frameworks for known CVEs and experimenting with prompt security against attack vectors. The tool provides both a visual interface and a comprehensive API, making integration with internal security systems or CI/CD pipelines practical for ongoing risk management. -
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PasteGuard
Masks sensitive data and secrets before they reach AI
PasteGuard is an open-source privacy proxy that protects sensitive information like personal data and API secrets by detecting and masking them before they reach large language model APIs such as OpenAI or Anthropic Claude. It sits between an application and the LLM provider, automatically replacing names, emails, tokens, and other personally identifiable information (PII) with placeholders so that external services never see raw sensitive values, and then optionally unmasking them in the returned output. ... -
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Minigrid
Simple and easily configurable grid world environments
...The design emphasizes speed (agents can run thousands of steps per second), low dependency overhead, and high customizability — making it easy to define new maps, new tasks, or wrappers. It supports the Gymnasium-style environment API so that RL researchers can plug it into their existing frameworks and algorithms with minimal adaptation. Because of its simplicity, it is often used for rapid prototyping, analytic experiments, curriculum learning, or pedagogical tutorials. While it is not a full 3D simulation environment, its strength lies in enabling many environment resets and steps cheaply, which is valuable for algorithmic RL research rather than high-fidelity rendering. -
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Simple MCP
A simple TypeScript library for creating MCP servers
simple-mcp is a TypeScript library designed to facilitate the creation of Model Context Protocol (MCP) servers. It offers a straightforward API, enabling developers to set up MCP servers with minimal code. The library emphasizes type safety through full TypeScript integration and incorporates parameter validation using Zod. It fully implements the MCP, ensuring compatibility with MCP clients. -
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MCP Golang
Write Model Context Protocol servers in few lines of go code
mcp-golang is an unofficial Go implementation of the Model Context Protocol (MCP), allowing developers to write MCP servers and clients with minimal code. It aims to simplify the development process by providing a straightforward API for integrating MCP functionalities into Go applications. Comprehensive documentation is available to assist developers in getting started. -
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PyKEEN
A Python library for learning and evaluating knowledge graph embedding
PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-modal information). PyKEEN is a Python package for reproducible, facile knowledge graph embeddings. PyKEEN has a function pykeen.env() that magically prints relevant version information about PyTorch, CUDA, and your operating system that can be used for debugging. If you’re in a Jupyter Notebook, it will be pretty-printed as an HTML table. -
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cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the cuML Benchmarks Notebook. -
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Skyvern
Automate browser-based workflows with LLMs and Computer Vision
Skyvern uses a combination of computer vision and AI to understand content on a webpage, making it adaptable to any website. Skyvern takes instructions in natural language, allowing it to execute complex objectives with simple commands. Skyvern is an API-first product. Workflows execute in the cloud, allowing it to run hundreds of workflows at the same time. Skyvern's AI decisions come with built-in explanations, providing clear summaries and justifications for every action. Support for proxies, with support for country, state, or even precise zip-code level targeting. Skyvern understands how to solve CAPTCHAs to complete complicated workflows. ... -
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AutoMLPipeline.jl
Package that makes it trivial to create and evaluate machine learning
AutoMLPipeline (AMLP) is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for... -
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OpenAI Realtime Agents
This is a simple demonstration of more advanced, agentic patterns
...It also supports a “Chat-Supervisor” pattern where a lightweight realtime chat agent handles user interactions and delegates more complex reasoning or tool usage to a stronger textual model (e.g. GPT-4). Because realtime agents are still a beta feature, the code and API surface are subject to changes and may evolve. -
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Kitten TTS
State-of-the-art TTS model under 25MB
KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis. -
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Large Language Models (LLMs)
Connect MATLAB to LLM APIs, including OpenAI® Chat Completions
This repository enables MATLAB to connect with large language models (LLMs) such as OpenAI's ChatGPT, DALL-E, Azure OpenAI, and Ollama, integrating their natural language processing and image generation capabilities directly within MATLAB environments. It facilitates creating chatbots, summarizing text, and image generation, among other tasks.