Langchain
The agent engineering platform
Haystack es un proyecto de agentes de IA de código abierto de deepset-ai (deepset-ai/haystack en GitHub). Tiene 26.646 estrellas en GitHub y 3.227 bifurcaciones, se publica bajo la licencia Apache-2.0 y se actualizó por última vez en GitHub el 2 de octubre de 2026.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and…
Application frameworks, agent runtimes, or voice stacks — choose by whether you are building apps, automations, or realtime voice.
Python or TypeScript packages install with one command; most include quickstart templates.
Give the agent functions it can call and a memory layer so it stays coherent across sessions.
Launch the agent, watch its tool calls and reasoning traces, and iterate on prompts and tools.
Agents act on the world: APIs, databases, browsers, and shell commands.
Crews and graphs of specialized agents collaborating on complex tasks.
Short and long-term memory so agents improve across sessions.
Traces of every decision and tool call — essential for debugging.
Low-latency stacks for conversational voice agents.
Swap underlying LLMs without rewriting your agent logic.
Download the source and move into the project folder.
git clone https://github.com/deepset-ai/haystack.git
cd haystackIsolate dependencies so nothing clashes with your other projects.
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activateInstall the requirements, then follow the README's launch command (it varies per project).
pip install -r requirements.txtFrameworks build your own; some repos here ship ready-made agents you can run directly.
Tool-calling quality matters more than raw size — strong mid-size models work well.
It is an open-source project at deepset-ai/haystack with 3,227 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Sandbox tool access, confirm destructive actions, and review traces — treat agents like junior employees with supervision.
Self-hosted frameworks are free; you pay only for model inference (local or API).
A quickstart template in the framework's docs — most get a first agent running in minutes.
The agent engineering platform
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work…
A programming framework for agentic AI
Langroid: a principled Python framework for building LLM multi-agent applications (from CMU/UW researchers)
A harness-oriented framework for production-grade agent applications.
Enterprise-grade AI agent framework with multi-provider LLM management, secure knowledge bases and high-precision RAG, visual workflow orchestration, and mul…
Los demás proyectos de Agentes de IA con más estrellas del catálogo de LibreAI: la lista realista de alternativas si Haystack no es lo que buscas.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Proyectos de Agentes de IA cercanos en el catálogo, los más próximos en estrellas a Haystack: sigue explorando a ambos lados.
A fully local Manus-style autonomous agent: browses, codes and speaks — no APIs, no subscription
An Open Phone Agent Model & Framework. Unlocking the AI Phone for Everyone
TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill,…
The open protocol that lets AI agents talk to each other.
The fast, Pythonic way to build MCP servers and clients.
Test prompts, agents and RAGs — LLM evals, red teaming and model comparisons from the CLI
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.