Production-ready Python framework for AI agents with built-in guardrails, audit logging, cost tracking, and hybrid RAG. Supports OpenAI, Anthropic, Gemini, Ollama. By NichevLabs.
README
┌─┐┌─┐┬ ┌─┐┌─┐┌┬┐┌─┐┌─┐┬ ┌─┐
└─┐├┤ │ ├┤ │ │ │ ││ ││ └─┐
└─┘└─┘┴─┘└─┘└─┘ ┴ └─┘└─┘┴─┘└─┘
An open-source project from NichevLabs.
Multi-agent orchestration in plain Python. Build agent graphs, compose pipelines with |, deploy with one command. No DSL, no compile step, no paid debugger. Works with OpenAI, Anthropic, Gemini, and Ollama.
# 1. Single agent — 5 lines
agent = Agent(tools=[search, calculate], provider=OpenAIProvider())
result = agent.run("What is 15 * 7?")
# 2. Multi-agent graph — 1 line
result = AgentGraph.chain(planner, writer, reviewer).run("Write a blog post")
# 3. Deploy — 1 command
# selectools serve agent.yaml
A feature release landing the post-1.0 backlog: scheduled agents, composable reasoning, two new session backends, an injection guardrail, and the rest of the v1.1 candidate set. All additive (@beta); no breaking changes.
AgentScheduler runs an agent on a cron("0 9 * * *") or every(minutes=5) schedule. Async loop that sleeps until the next due job, per-job max_runs / `on