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Agent Zero

2.1k members • Free

3 contributions to Agent Zero
🆕 v0.9.3 Release! 🥳
👉Agents can now have individual system extensions and tools 👉 LLM providers are now configurable 👉 Memory improved by AI 📺 Video tomorrow! Full changelog below👇 - Faster startup/restart - Subordinate agents can have dedicated prompts, tools and system extensions - Streamable HTTP MCP server support - Memory loading enhanced by AI filter - Memory AI consolidation when saving memories - Auto memory system configuration in settings - LLM providers available are set by providers.yaml configuration file - venice.ai LLM provider supported - Initial agent message for user + as example for LLM - Docker build support for local images - File browser fix
1 like • Aug '25
excellent, thank you very much for the effort.
First Ever Agent Zero Community Call – Kicks Off Tomorrow @ 9AM CST
Click Here to watch the Announcement video Like, comment and share this post so we pack out this call to help everyone level up using Agent Zero! "A rising tide lifts all boats" Let's go!!!
First Ever Agent Zero Community Call – Kicks Off Tomorrow @ 9AM CST
2 likes • Jul '25
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1 like • Jul '25
Excellent Excellent event, I joined late but loved seeing everyone have a space to speak, very collaborative. Open like 👍agent zero.
Agent Zero is a real team member
What I would like to make my Agent Zero do, I need help to set up this scenario. One detail is that each sub-agent can use a different Model. Recommended Final Structure of the /a0/agents/ Directory /a0/agents/ ├── shared_utils/ # Shared functions/utilities (templates, helpers, integrations) │ ├── message_template.json │ ├── mongo_integration.txt │ └── README.md ├── orchestrator_agent_zero/ # Main orchestrator (defines central prompts and decision logic) │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── architect/ # Specialist agent for solution architecture │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── integration_engineer/ # Agent for technical integrations (e.g., APIs, middlewares) │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── rap_cap_java_json_developer/ # Specialist agent for CAP/RAP and Java/JSON development │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── tech_lead_expert/ # Tech Lead/Senior agent for technical review and guidance │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── analyst/ # Functional and requirements analyst agent │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── critic/ # Critical agent for QA, review, and quality control │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── debugger/ # Agent for debugging and error resolution │ ├── system_prompt.txt │ ├── user_prompt.txt │ └── README.md ├── orchestration_scripts/ # Central multi-agent orchestration scripts (router, launcher, manager) │ ├── orchestrator.py │ ├── agent_launcher.py │ ├── task_router.py │ ├── communication_manager.py │ ├── logger.py │ ├── shared_utils.py │ └── test_multi_agent_flow.py ├── persistence/ # Abstraction for database integration (MongoDB, etc.) │ └── (relevant scripts/configs) ├── tests/ # Automated unit and multi-agent integration tests ├── ci_cd/ # Continuous integration and delivery pipelines ├── healthcheck.py # Script for system health monitoring and healthcheck
Agent Zero is a real team member
1 like • Jul '25
@Jan Tomášek , I have a suggestion to leave here since you are working with multi-agent systems. One limitation I see at this moment is that when working with subagents, I always encounter a restriction with the TPM limit at the end of the multi-agent action. Basically, if I set up agents (BPO, Tech Leader, and Architect) to analyze and refine a business requirement to later break it down into epics, features, stories, and tests, I always run into errors due to the compression process without losing context. At a certain point, it hits the limit of 31,000 TPM of the ChatGPT API 4.1. It would be necessary to have, for example, a multi-chat scheme or to improve the summary, with compression checkpoints, etc. The secret would be not to lose context because the stories, for example, need to be completely aligned with the epic; the test writing must be in the context of each story, and so on. In this type of work, the zero agent distinguishes itself from everything I've tested, but it still has those limitations. If you want, I can share a structure to understand where they are going with the zero agent.
0 likes • Jul '25
@Jan Tomášek Yes, it's true, but the problem is that the message is always long and always exceeds 30k. I would need to be able to compress it or just send summaries. The problem is that I haven't been able to summarize it yet because of the context. I could use another model like nano or mini but then I lose quality of stories or test for stories.It's been a challenge 🫠
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César Ferreira
2
10points to level up
@cesar-ferreira-9385
I am an enthusiast

Active 35d ago
Joined Jul 21, 2025
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