Introduction
Composable agents. Flexible task flows. One lightweight framework.
What is Chainless?
Chainless is a lightweight, modular framework to build task-oriented AI agents and orchestrate them in intelligent flows.
It allows you to define agents, tools, and tasks in a composable and scalable way — ideal for both personal projects and production-grade pipelines.
How Chainless Works
Component | Description | Key Features |
---|---|---|
Agent | A self-contained unit powered by an LLM and optional tools | - Tool invocation - Custom start hooks - System prompts - Stateless or memory-driven design |
Tool | A callable Python function with metadata | - Reusable - Easily registered - Simple input/output schema |
TaskFlow | Composable flow engine that connects agents together | - Sequential/Parallel execution - Input mapping - Output routing |
Custom Start | Override how an agent processes data | - Direct LLM calls - Prompt chaining - Arbitrary preprocessing logic |
Core Features
Modular Agents
Design lightweight agents that use tools or reason directly. Compose complex logic without over-engineering.
Composable TaskFlows
Connect agents in flexible sequences or parallel blocks. Build entire pipelines by just describing the data flow.
Native Python Tools
Define your own tools with pure Python. Chainless automatically wraps them with metadata for agent usage.
Custom Execution Hooks
Fully control how an agent executes. Inject prompts, chain models, or pre/post-process using decorators.
Zero-Bloat, Server-Free
Keep it local. Chainless doesn’t force you into a runtime. No cloud service, no lock-in — just Python.
LLM Agnostic
Bring your own model — from OpenAI, Groq, DeepSeek, Ollama or others. Chainless is fully compatible.