Comparisons / AutoGen vs Flue
AutoGen vs Flue: Which Agent Framework to Use?
AutoGen vs Flue, head to head
AutoGen and Flue both let you build an agent, but they sit in different parts of the stack and they assume different things about who's writing the code.
AutoGen by Microsoft models agents as ConversableAgents that chat with each other.
Flue is a declarative TypeScript agent framework from Fred K.
Underneath, both wrap the same thing: a model call, a tool dispatch, a loop. The decision is about which abstraction your team wants to think in day to day, and which ecosystem you're willing to inherit along with it. There's an honest, framework-free version of the same pattern in about 60 lines of Python in the lesson at the bottom of this page — useful as a baseline regardless of which framework wins.
Pick AutoGen if
Pick AutoGen if autoGen excels at complex multi-agent workflows where agents need to debate or collaborate. For single-agent use cases or simple tool-calling agents, the plain Python version is significantly simpler. The tradeoffs in its intro should match how your team already thinks about agents; Flue will feel like translation if they don't.
Pick Flue if
Pick Flue if flue is the natural choice when the deploy target is Cloudflare and you want a TypeScript-first, declarative agent framework tuned for Durable Objects. Its cross-runtime story (Cloudflare + Node + CI) is genuinely useful if agents run in more than one place. For a single-agent loop that doesn't need persistence, plain TypeScript is simpler. The tradeoffs in its intro should match how your team already thinks about agents; AutoGen will feel like translation if they don't.
By the numbers
By the numbers
AutoGen
56.7k
8.5k
Python
CC-BY-4.0
2023-08-18
Microsoft Research
Flue
2.4k
140
TypeScript
MIT
2026-05-01
Fred K. Schott + Astro team (at Cloudflare)
Cloudflare
Cloudflare Durable Objects; also deploys to Node, GitHub Actions, GitLab CI
Yes
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | AutoGen | Flue |
|---|---|---|
| Agent | `ConversableAgent` with `system_message`, `llm_config` | `createAgent({ model, instructions, tools })` — declarative config, framework runs the loop |
| Tools | `register_for_llm()` and `register_for_execution()` | Registered with valibot schemas: `{ name, description, schema, execute }` |
| Conversation | Two-agent chat with `initiate_chat()`, message history | — |
| Multi-Agent | `GroupChat` with `GroupChatManager`, speaker selection | — |
| Nested Chats | `register_nested_chats()` for sub-task handling | — |
| Termination | `is_termination_msg` callback, `max_consecutive_auto_reply` | — |
| State | — | Durable Streams — replayable, checkpointed event log stored in Cloudflare Durable Objects |
| Deployment | — | One config controls deploys to Cloudflare, Node, GitHub Actions, or GitLab CI |
| Runtime | — | The Pi harness — same runtime as OpenClaw, so agents share tooling with that ecosystem |
| Cloudflare-native | — | Durable Objects give per-agent persistence and locking without an external DB |
Or build your own in 60 lines
Both AutoGen and Flue implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.
No framework. No dependencies. No opinions. Just the code.
Build it from scratch →