Alternatives
Products that do what Dhenara Agent DSL– Framework for Complex Agents with Free Observability does
Dhenara Agent DSL (DAD), an open-source framework for building, running, and managing AI agents! GitHub: https://github.com/dhenara/dhenara-agent Documentation: https://docs.dhenara.com/dhenara-agent/introduction Key Features: - Agent Lifecycle Management: Create, run, resume, and manage agents - Run Controls: Resume execution from any point to save on API costs - Built-in Observability: OpenTelemetry tracing with Jaeger and Zipkin support - Event System: Fine-grained flow control - Open Development: Build using standard tools (Git, VS Code) - No…
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Hello HN! The day has finally come to stop adding features and start sharing what I've been building the last 5-6 months. It's a bit of CrewAI, OpenDevon, LangFuse/Cloud all in one, providing devs who prefer TypeScript an integrated framework thats provides a lot out of the box to start experimenting and building agents with. It started after peeking at the LangChain docs a few times and never liking the example code. I began experimenting with automating a simple Jira request from the engineering team to add an index to one of our Google Spanner databases (for context I'm the…
2024 · github.com
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Hi HN, Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents. At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full privacy and no external data sharing. What makes it different • Fast & lightweight — Agents instantiate in ~3μs and use ~6.6 KiB of memory on average (tested on M4 MacBook Pro). • Runtime architecture — Async, stateless, horizontally scalable runtime built on FastAPI. • Integrated…
Oct 2025 · agno.link
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Agentpanel is an observability platform for optimizing the control flow, performance, token usage, and correctness of LLM/AI agents! Built-in @rustlang, the first release of Agent Panel currently features an AI gateway that provides seamless access to 100+ LLMs across 20+ platforms, including OpenAI GPT-4o, Gemini 1.5 Pro latest, AnthropicAI Claude 3.5, MistralAI, Cohere, Groq,Perplexity AI, and more.
2024 · github.com
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I’ve been experimenting with infrastructure for multi-agent systems. I built a small project called AgentLog. The core idea is very simple, topics are just append-only JSONL files. Agents publish events over HTTP and subscribe to streams using SSE. The system is intentionally single-node and minimal for now. Future ideas I’m exploring: - replayable agent workflows - tracing reasoning across agents - visualizing event timelines - distributed/federated agent logs Curious if others building agent systems have run into similar needs.
Mar 2026 · github.com
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2023 · github.com
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Hi HN, This is Andrei from askmanu and I'm super happy to share a new framework I've been working on: acorn. It takes all the best parts of DSPy, langchaing, instructor, etc and wraps it in a beautiful and easy to use API. Very easy to define model I/O, branches, define callbacks for every step, etc See the getting started docs here: https://github.com/askmanu/acorn/blob/main/docs/getting-star... Try out the different demos here: https://huggingface.co/spaces/askmanu/acorn
Feb 2026 · github.com
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I’ve been working on a temporal database for agents that combines graphs, tables, and compute. While building it, I ended up needing an agent framework that could handle both simple tool-use tasks and more graph-based execution, so I pulled that out into a separate project, Agent Forge. Agent Forge uses a two-tier execution model: * a heuristic router decides whether a request is simple or complex * simple requests go through a lightweight agent loop with a single system prompt and tool-calling loop * more complex requests can use memory retrieval, reflection constraints, tree search, and…
Mar 2026 · github.com
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Hey HN! I am super excited (and slightly nervous) to introduce AgentServe! AgentServe is a framework to make hosting scalable AI agents as easy as possible. With 4 lines of code AS wraps your agent (any framework) in a FastAPI and connects it to a Task Queue (celery or redis). Why Should You Care? Standardized Communication Pattern: AgentServe proposes that all agents should communicate with each other and the outside world with “Tasks” that can be submitted in a sync or async way. This simple API wil enable Framework Agnostic: No favorites. OpenAI, LangChain, LlamaIndex, CrewAI are all…
2024 · github.com
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I’ve been working on a multi-agent academic research lab, and I wanted to share it here today primarily to give a massive shoutout to the developers behind ZeroClaw. When designing the architecture for this, I needed an autonomous agent runtime that was lightweight, entirely agnostic, and highly secure for local execution. ZeroClaw’s pure Rust implementation provided exactly the zero-overhead foundation the project required. Because they solved the core runtime execution so elegantly, I was able to spend my time building the higher-level orchestration on top of it—like the retrieval graph…
Mar 2026 · rainlabteam.vercel.app
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AgentRQ is a (optionally) human-in-the-loop, self learning closed loop task manager for agents. Agents can create and schedule tasks for themself and work on them on their own schedule. In high level it comes with one supervisor MCP that controls workspaces(worker agents) and unlimited number of isolated workspace MCPs (self learning agents). Each workspace/agent has a mission/persona for the agent. And self-learning-loop note. I am using it about 6 weeks in production, and completed more than 500 tasks. I just released the opensource version(as is in production) under Apache 2.0…
Apr 2026 · github.com
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I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.
27d ago · pacslate.com
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