AI-gent Workflows

secai is a Golang framework for Reasoning AI Workflows, implemented using a unique state machine which thrives in complexity. It's a solid foundation for complex, proactive, and long-lived AI Agents with deep and structured memory. Each bot ships with embedded devtools and several UIs. The execution flow is graph-based, which allows for precise behavior modeling of agents, including interruptions, concurrency, and fault tolerance.

It's a sophisticated replacement for frameworks like LangGraph and offers deeply relational consensus of state.

Diagram

Dev Tools

Log

Schema

States

Dashboard

Browse SQL

Browse Files

AI-gent Cook (PWA / TUI / REPL)

User Demo: AI-gent Cook

This demo presents data collection, gen AI, offers, stories, workflows, dynamic short-term memory, planning with a DAG, story navigation, progress, and clockmoji.

Platform Demo: AI-gent Research

This tech demo will show a "deepresearch" AI Agent as seen throughout the platform: SVG diagram, TUI debugger, Grafana, Jaeger, REPL, SQL, IDE, Bash scripts, and Prompt dumps.

secai is on GitHub

Almost all the code is Free and Open Source, which guarantees free updates in the future.

multi-prompt agency
- a single agent / bot is built of several AI prompts
- each state can have a prompt bound to it, with dedicated history and documents
atomic consensus with relations and negotiation
- eg states excluding each other can't be active simultaneously
dedicated DSL layer for bot schema
- suitable for non-coding authors
structured prompt input/output via JSON schemas
declarative flow definitions for non-linear flows
cancellation support (interrupts)
choice menu (list of offers)
prompt history
- embedded SQLite
- JSONL log
- "latest prompt" files
proactive stories with actors
- stories have actions and progress
LLM-sourced story switching (orienting)
- on prompts and timeouts
dynamic flow graph for the memory
- LLM creates an actionable state-machine
TUIs and WebAssembly PWAs for user interfaces

secai differs from other AI agents / workflows frameworks in the way it treats AI prompts. Most frameworks call each prompt an "agent", while secai treats prompts as simple DB queries with IoC (Inversion of Control). Tool usage happens manually through typesafe params / results. This approach increases determinism, safety, and overfall control. This multi-prompt workflow forms an actual bot / agent. This does not mean agents can't be composed into larger groups, which happens through stateful dialog, state piping, and aRPC. The underlying workflow engine asyncmachine-go doesn't depend on AI at all.

The flow graph, unlike in regular workflows, is not path-based - each node (state) can be activated anytime (same as calling a function), and the edges between nodes are meant to resolve the state consensus. It's a directed multigraph of states with a negotiation phase.