#python #agent #agents #ai #anthropic #claudecode #llm #llms #openai

Open SWE is a free, open-source framework to build internal coding agents like those at Stripe, Ramp, and Coinbase. Trigger it via Slack, Linear, or GitHub (@openswe) to research codebases, plan tasks, code, test, review, and auto-open PRs in secure cloud sandboxes—running parallel jobs without your machine's resources. Customize models, tools, and workflows easily. You benefit by automating routine coding, slashing review cycles and production time by 30-50%, freeing you to focus on high-value work while ensuring safe, high-quality changes.

https://github.com/langchain-ai/open-swe

#typescript #agent #agents #ai #background_agents

Open Agents is an open-source tool that lets you build AI coding agents running on Vercel. It separates the agent logic from the sandbox environment, meaning the AI runs outside the virtual machine and controls it through commands like file edits and shell operations. This architecture gives you flexibility—the agent isn't tied to a single request, sandboxes can pause and resume independently, and you can swap AI models or sandbox implementations without rebuilding everything. You get chat-driven coding with file tools, durable multi-step execution, isolated sandboxes, GitHub integration for cloning and creating pull requests, and optional voice input. The benefit is a scalable, modular system you can fork and customize for your own background coding agent needs without managing your laptop.

https://github.com/vercel-labs/open-agents

#go #agents #claude_code #coding

Beads (bd) is a free CLI tool for macOS, Linux, Windows, and FreeBSD that gives AI coding agents persistent, structured memory via a version-controlled Dolt SQL database with graphs for tasks, dependencies, and hierarchies. Install once with `curl` script or brew, then `bd init` in any project—no repo cloning needed. Key commands like `bd ready`, `bd create`, and `bd update` track blockers, claim tasks, and auto-detect ready work in JSON for agents. It prevents conflicts with hash IDs, compacts old tasks, and supports stealth/git-free modes. You benefit by replacing messy plans with clear, long-term task tracking that keeps AI agents focused without losing context, boosting productivity on complex projects.

https://github.com/gastownhall/beads

#jupyter_notebook #agentmemory #agents #ai #ai_developer #artificial_intelligence #generative_ai #kubernetes #kustomize #oracle_database #oracleaidatabase #oraclejet #rag

Oracle AI Developer Hub offers apps, notebooks, guides, workshops, and agent memory tools to build AI apps, agents, and systems using Oracle AI Database and OCI services. Explore ready examples like FitTracker fitness app, RAG agents, and memory-augmented workflows with LangChain or OpenAI. This saves you time by providing complete code, tutorials, and best practices to quickly create production-grade AI solutions without starting from scratch.

https://github.com/oracle-devrel/oracle-ai-developer-hub

#typescript #agentmemory #agents #ai #claude #claudecode #codex #copilot #cursor #genai #harness #hermes #memory #openclaw

# agentmemory `npx @agentmemory/agentmemory`.

https://github.com/rohitg00/agentmemory

#typescript #agents #code_review #doctor #react #skill

React Doctor is a free tool that scans your React codebase with one command (`npx react-doctor@latest .`), giving a 0-100 health score and fixing issues in state, effects, performance, security, accessibility, and dead code. It works with Next.js, Vite, React Native, GitHub Actions, and AI agents like Claude. Customize via config, ignore rules, or use as ESLint/oxlint plugin. This saves you time debugging bad code from agents or teams, boosts app quality, and prevents costly errors. Try the demo at react.doctor.

https://github.com/millionco/react-doctor

#python #agents #llm #rag #skills #video_analytics #video_search #vlm

NVIDIA's Video Search and Summarization blueprint lets you build AI agents for fast video analysis, including real-time intelligence, alerts, natural language search, Q&A, and long-video summaries using vision models and NIM microservices. Deploy easily via Docker or cloud notebooks on supported NVIDIA hardware. This saves you time analyzing huge video volumes for smart monitoring, warehouses, or operations, boosting decisions and efficiency with ready workflows and custom options.

https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization

#jupyter_notebook #agent #agent_framework #agents #ai_agents #deployment #genai #generative_ai #langgraph #llm #llms #mlops #production #python #tutorials

Agents Towards Production is a free open-source guide for building AI agents that work in real products. It gives runnable tutorials on memory, tools, search, deployment, security, monitoring, testing, and user interfaces. You can use it to learn faster, build with less guesswork, and move from a simple prototype to a more reliable, scalable agent system.

https://github.com/NirDiamant/agents-towards-production

#python #agents #ai #ai_agents #ai_engineering #computer_vision #course #deep_learning #from_scratch #generative_ai #llm #machine_learning #mcp #nlp #python #reinforcement_learning #rust #swarm_intelligence #transformers #tutorial #typescript

This is a free MIT learning guide for AI engineering with 428 lessons in 20 phases. It teaches you AI from the math up, then moves into machine learning, deep learning, LLMs, agents, tools, safety, and production. Each lesson helps you build useful code or AI tools, not just read theory. You can start at the right level, follow a clear path, and keep reusable artifacts for real work. The benefit is simple: you learn how AI actually works and gain practical skills you can use to build and ship better AI systems.

https://github.com/rohitg00/ai-engineering-from-scratch

#python #agentic_ai #agentic_workflow #agents #function_calling #llama_cpp #llamafile #llm #ollama #python #self_hosted #tool_calling

Forge is a Python tool that makes self-hosted LLM tool-calling more reliable. It helps local models handle multi-step tasks with guardrails, better context control, and support for Ollama, llama-server, Llamafile, and Anthropic. You can use it as a workflow runner, middleware, or proxy server with OpenAI-style clients. The benefit is fewer broken tool calls, better results on small models, and easier setup for agent apps, chat tools, and long-running sessions.

https://github.com/antoinezambelli/forge