Comparisons / Flue vs Haystack
Flue vs Haystack: Which Agent Framework to Use?
Flue vs Haystack, head to head
Flue and Haystack 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.
Flue is a declarative TypeScript agent framework from Fred K.
Haystack by deepset is a framework for building NLP and LLM pipelines.
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 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; Haystack will feel like translation if they don't.
Pick Haystack if
Pick Haystack if haystack earns its complexity when you're building RAG pipelines with multiple retrieval stages, document processing, and production deployment needs. But for straightforward agents with a few tools, the plain Python version is simpler to write and debug. The tradeoffs in its intro should match how your team already thinks about agents; Flue will feel like translation if they don't.
By the numbers
By the numbers
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
Haystack
24.7k
2.7k
Python
Apache-2.0
2019-11-14
deepset
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | Flue | Haystack |
|---|---|---|
| Agent | `createAgent({ model, instructions, tools })` — declarative config, framework runs the loop | `Agent` component with `ChatGenerator`, tool definitions, and message routing |
| Tools | Registered with valibot schemas: `{ name, description, schema, execute }` | `Tool` dataclass with function reference, name, description, parameters schema |
| 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 | Pipeline YAML serialization, `Hayhooks` REST server |
| 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 | — |
| Pipeline Architecture | — | `Pipeline()` with `add_component()` and `connect()` — a directed graph of typed components |
| RAG / Retrieval | — | `DocumentStore` + `Retriever` + `PromptBuilder` + `Generator` wired in a `Pipeline` |
| Memory | — | `ChatMessageStore` with `ConversationMemory` component in pipeline |
Or build your own in 60 lines
Both Flue and Haystack 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 →