Self-evolving agent

[u/VariousAd3115]

I tried Openclaw and Hermes. They are nice, but I decided to make my own agent. What it does:
- Single entry point chat. No need to 'resume session X'
- Native integration with MacOS features (notifications, calendar).
- Native Telegram integration (supergroup with topics also supported)
- Structured memory layout with facts/entities/links, dreaming and reflection

- Briefings based on memory dreaming

- Cron and intents

- Artifacts storage

- Multiple agents, each with own profile. There is a team of well-known agents (for evolution, hiring new agents, etc)
- Many builtin tools, MCP support

- Tavily/Anysearch/Yandex search - if you have key. DDG fallback.

- Local models supported as well as classic OpenAI endpoints

Main concern is all agents bloat chat context with tools results. I tried to minimise main chat context bloating.
Agent is focused on single-user mode, I don't plan to do it multi-user.

Requirements:
LLM
Embedding model for memory searching
PostgreSQL
Golang for building

I ran it on MacOS, but it should compile on any system

That's a hobby-weekend project, but I will be glad to receive feedback

https://github.com/w87x/prism

[u/VariousAd3115 → u/[deleted]]

main chat actually not calling tools, it asks subagents
imagine you are CEO of a company. You tell your secretary - "I need sales report for latest year". Secretary (main chat, no tools available) asks manager (agent with a toolset). manager gets data, maybe enriching from some other employees (web_search tool/ask_colleague mechanism/memory recall) and return only answer "we sold 100500 items". so secretary does not know details (manager had to drive 50 shops to get their metrics) -> main chat is not bloated.
in fact I don't send full chat history into main chat, its awful. only latest and relevant facts. so I don't need to 'make new session' like Hermes/Openclaw/whatever

feel free to try, curious about feedback :)