Search Results for "backend"
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Showing 19 open source projects for "backend"
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InsForge
InsForge is the backend built for AI-assisted development
InsForge is an open-source backend development platform designed specifically for AI-assisted or agent-driven application development, positioning itself as an agent-native alternative to tools like Supabase by exposing backend primitives (auth, database, storage, serverless functions, and AI integrations) in a way that intelligent agents can understand, reason about, and act upon directly. -
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Dify
One API for plugins and datasets, one interface for prompt engineering
Dify is an easy-to-use LLMOps platform designed to empower more people to create sustainable, AI-native applications. With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement. Out-of-the-box web sites supporting form mode and chat conversation mode A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort Visual data analysis, log review, and annotation for applications -
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Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
gemini-fullstack-langgraph-quickstart is a fullstack reference application from Google DeepMind’s Gemini team that demonstrates how to build a research-augmented conversational AI system using LangGraph and Google Gemini models. The project features a React (Vite) frontend and a LangGraph/FastAPI backend designed to work together seamlessly for real-time research and reasoning tasks. The backend agent dynamically generates search queries based on user input, retrieves information via the Google Search API, and performs reflective reasoning to identify knowledge gaps. It then iteratively refines its search until it produces a comprehensive, well-cited answer synthesized by the Gemini model. ... -
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CopilotKit
Build in-app AI chatbots, and AI-powered Text areas
...Plug-and-play, fully customizable, copilot infrastructure. Build in-app AI chatbots that can "see" the current app state + take action inside your app. The AI chatbot can talk to your app frontend & backend, and to 3rd party services (Salesforce, Dropbox, etc.) via plugins. Autocompletion + AI editing + generate from scratch. Indexed on your users' content. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Autoskills
One command. Your entire AI skill stack. Installed
...Once the stack is identified, it automatically installs a curated set of AI skills tailored to those technologies, significantly reducing setup time for AI-assisted development environments. The system is designed to work across a wide range of ecosystems, including frontend, backend, mobile, cloud, and AI tooling stacks. It also supports integration with environments like Claude Code by generating structured summaries of installed skills. By removing the need for manual configuration, it streamlines the onboarding process for AI-assisted workflows. Overall, autoskills functions as an intelligent automation layer that bridges project context with AI tooling capabilities. -
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Suna
Suna - Open Source Generalist AI Agent
...It serves as a digital companion for research, data analysis, and everyday challenges, integrating tools like browser automation, file management, web crawling, command-line execution, website deployment, and API integration. Suna's architecture comprises a FastAPI-based backend, a Next.js/React frontend, an agent Docker environment, and a Supabase database for state management. This modular design allows for seamless interaction and task execution through simple conversations. -
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Nimbalyst
Run multiple Codex and Claude Code AI sessions
Crystal is an open-source project focused on building a lightweight and flexible system for managing structured data, workflows, or automation pipelines, typically oriented toward developer productivity and extensible backend tooling. It is designed with modularity in mind, allowing developers to define reusable components and compose them into larger workflows that can adapt to different use cases. The project emphasizes simplicity and clarity, making it easier to understand and extend compared to heavier enterprise frameworks. Crystal often leverages modern programming practices and clean architecture principles to ensure maintainability and scalability as projects grow. ... -
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eve
The Framework for Building Agents
eve is Vercel’s open-source framework for building, running, and scaling durable backend AI agents. It uses a filesystem-first model where an agent is defined as a directory of files, making the project structure itself the agent contract. The framework is designed to include production concerns from the start instead of leaving developers to assemble durability, sandboxing, approvals, and deployment separately. Eve supports durable execution, sandboxed compute, human-in-the-loop approvals, subagents, long-running work, and Vercel-native deployment. ... -
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Mysti
AI coding dream team of agents for VS Code
...The experience is organized around “personas” that change how the assistant approaches a task, such as architecture, debugging, security review, performance tuning, or refactoring, which helps structure the AI’s behavior for different goals. It also supports a brainstorm-style workflow where using more than one backend can produce competing solutions and then synthesize a best answer. Mysti is designed for speed and convenience with quick actions, toolbar persona switching, and a saved conversation history so work is not lost between sessions. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Microsoft Agent Skills
Skills, MCP servers, Custom Agents, Agents.md for SDKs
...In addition to the skills themselves, the repo includes templates for agent configuration (e.g., Agents.md), marketplace setup files, and command utilities to install skills into directories like .github/skills or .claude/skills. It also offers preconfigured MCP servers and custom agent roles covering backend, frontend, infrastructure, planner, and other use cases, helping teams create richer, role-aware AI assistants. -
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Berd
A desktop app for getting work done with any model
Berd is an open-source desktop workspace for working with AI agents on real projects. It is built with Tauri and React and connects to the Goose backend through the Agent Client Protocol. Users can chat with agents, attach files or folders, choose models, and organize work inside projects. It also supports skills, extensions, automations, and provider configuration. Session history helps keep longer-running work continuous and inspectable. The project is designed for engineers, designers, and other builders who want a persistent AI companion with access to local workspace context. -
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Coze Studio
An AI agent development platform with all-in-one visual tools
...It offers no-code/low-code workflows to build, debug, and deploy conversational agents, integrating prompting, RAG-based knowledge bases, plugin systems, and workflow orchestration. Developed in Go (backend) and React/TypeScript (frontend), it uses a containerized microservices architecture suitable for enterprise deployment. -
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OpenAI CS Agents Demo
Demo of a customer service use case implemented with the OpenAI Agents
This repository is a customer service agent demo built using the OpenAI Agents SDK to showcase how to build a production-style conversational assistant for use cases like airline customer support. It consists of two major parts: a Python backend that orchestrates agent logic (tool calls, handoffs, memory, routing) and a Next.js UI for chat interaction and visualizing agent state. The demo covers tasks you’d expect in customer service: changing flights, checking status, answering FAQs, etc. It shows how multiple subagents can be coordinated under a triage agent that decides which specialized agent should handle a given request. ... -
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OpenAI Realtime Agents
This is a simple demonstration of more advanced, agentic patterns
...The SDK offers abstractions such as agent orchestration, event handling, handoffs, state management, and guardrails, tailored to support realtime, conversational systems. The demo includes a Next.js frontend for browser interaction and likely a backend component to orchestrate realtime sessions and agent logic. 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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Antigravity Kit
AI Agent templates with Skills, Agents, and Workflows
Antigravity Kit is an AI agent capability expansion toolkit that provides structured templates, skills, and workflows designed to boost the productivity of AI assistants and autonomous agents in coding environments. It comes with an extensive library of predefined agent personas and domain-specific skills that help in performing targeted tasks such as frontend development, backend engineering, quality assurance, and more. With this kit, developers can rapidly initialize a project scaffold and gain access to specialist agents and command workflows that guide the agent through multi-step tasks and slash-command procedures. The repository follows a clear pattern for defining agents and their behaviors, making it easier to extend with new skills or tailor existing ones to your use case. ... -
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TencentDB Agent Memory
TencentDB Agent Memory delivers fully local long-term memory for AI
TencentDB Agent Memory is a local long-term memory system for AI agents. It uses symbolic short-term memory and layered long-term memory instead of storing everything as flat vector fragments. For active tasks, it offloads heavy logs into external files and keeps a compact Mermaid canvas in the agent context. For personalization, it organizes memory from raw conversations into atoms, scenarios, and persona-level knowledge. The design keeps high-level memory inspectable while preserving a... -
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Lux Desktop
Example client of oagi-python developed with Tauri
Lux Desktop is a cross-platform desktop application that showcases how to build a graphical client on top of the Lux computer-use model using the OAGI Python SDK as its backend. It is implemented with Tauri, combining a TypeScript/React front end with a Rust-powered shell to produce lightweight native executables for macOS and Windows. The project serves as a reference implementation for developers who want to see how Lux-powered agents can be packaged into a user-friendly app, including how to wire up commands, configuration, and UI flows around computer-use automation. ... -
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AgentDock
Build Anything with AI Agents
AgentDock is an open-source framework designed to simplify the development, orchestration, and deployment of AI agents capable of executing complex automated workflows. The platform provides a backend-first architecture that allows developers to create sophisticated agent systems while maintaining flexibility in model providers and infrastructure choices. It consists of two main components: a core framework that handles agent logic and orchestration, and a reference client application that demonstrates how agents can be deployed and interacted with through a web interface. ... -
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CodinIT.dev
Free, local, open-source AI app builder
CodinIT.dev is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5, Claude Sonnet 4.5) or local via Ollama, so you’re never locked in. 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. ...
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