The simplest OpenAI-compatible LLM proxy you will ever need.™️

FAAAH allows you to reuse your AI Agent subscription as a generic OpenAI-compatible local server.

FAAAH is dependency-free, implemented as a plain-text file protocol
(UNIX-philosophy certified):

  • Instead of sending your prompts to cloud LLM APIs, send them to FAAAH,
    which reads OpenAI-compatible requests and dumps them into a folder as
    .txtfiles.
  • Then, tell your existing AI coding agent (Claude Code, opencode, etc) to
    read the files and write responses to other .txtfiles.
  • FAAAH then packages the responses into OpenAI-compatible JSON, and returns them to your app.

Because you already pay for an AI coding assistant. Stop paying for API keys
just for your weekend side projects! faaah!

demo-9mb.mp4

It is my understanding that local, non-commercial use of this tool doesn't break the existing ToS of any AI agent provider.

But if any lawyer disagrees, kindly send me a message. I would then introduce you to a friend of mine: Miss Barbra Streisand.

Be cautious about using FAAAH to process massive datasets. Some providers
(you know which ones) might do some Kafkaesque interpretations of their
ambiguous ToS, and deploy Orwellian telemetry to detect infractions (hasn't
happened to me yet, YOLO!)

  • Zero Dependencies:Uses Python's- http.server. That's it.
  • 308 lines of code:Have you seen the- bloatof other tools in this space? Yuck.
  • Unix Philosophy:Everything is a file. Do one thing well. Keep it KISS, ya YAGNI.
  • Universal Compatibility:If a tool supports the- de-factoOpenAI API format (GraphRAG, LangChain, LlamaIndex, LiteLLM, the- openaiSDK), it supports FAAAH.
  • Agent Agnostic:Due to the agent entrypoint being- a prompt, it's not tied to any specific agent provider/version. Future-proof.
  • Human-in-the-loop Fallback:If the AI agent gets stuck or hits usage limits, you can literally open the current response file (say- response-0004.txt), type the answer yourself (or copy-paste the request to your favorite web chatbot), and hit save. FAAAH will succeed.

Install with uv:

```

from inside this repo

uv tool install . # installs the faaah command on PATH
```
Or straight from the git repository:

`uv tool install git+https://github.com/sebastiancarlos/faaah` faaah # listens on 127.0.0.1:8000, queue ~/.cache/faaah/queue faaah --port 8080 # override port faaah --queue /tmp/q # override queue directory
The agent prompt is printed on startup. To grab it again:

faaah --agent-messagePaste it into your coding agent, which then starts a FAAAH coordinator
loop:

  • Call faaah --watchto obtain the next request (blocks until one exists).
  • Delegate the request to a worker subagent (to prevent accumulating context).
  • Repeat. If a worker leaves no response file, faaah --watchsimply returns the same path again, so the coordinator retries it.

Note: FAAAH uses subagents to prevent exhaustion of context on multiple
requests. Thereby, your AI Agents must support creation of subagents on
request by prompt.

You can use curl, for example:

curl http://127.0.0.1:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -H "Authorization: Bearer anything" \ -d '{ "model": "faaah", "messages": [{"role": "user", "content": "Write a haiku."}] }'
Or any OpenAI-API shaped client:

from openai import OpenAI client = OpenAI(base_url="http://127.0.0.1:8000/v1", api_key="anything") response = client.chat.completions.create( model="faaah", # this field is ignored anyway messages=[{"role": "user", "content": "Write a haiku."}], timeout=None, # agents can be slow ).choices[0].message.content print(response)
A dependency-free example lives in examples/chat.py.

For an advanced usage, GraphRAG fully driven through FAAAH, see
graphrag-faaah.

usage: faaah [-h] [--host HOST] [--port PORT] [--queue QUEUE] [--timeout TIMEOUT] [--agent-message] [--watch] Filesystem As An AI Handler: an OpenAI-compatible proxy backed by an AI agent working over text files. options: -h, --help show this help message and exit --host HOST Address to bind (default: 127.0.0.1). --port PORT Port to listen on (default: 8000). --queue QUEUE Directory where prompt/response files live (default: ~/.cache/faaah/queue). --timeout TIMEOUT Abort each call after N seconds. 0 (default) waits forever. --agent-message Print ONLY the agent prompt and exit (it's also printed on launch). --watch Block until a pending prompt exists, print its path.
The protocol relies on files on the queue directory (~/.cache/faaah/queue by
default).

Each request produces a prompt-<id>.txt file, where the first one's ID will be
00001 and increase monotonically.

FAAAH then expects the agent (or anything really) to generate a corresponding
response-<id>.txt.

The subagent workers are prompted to write a first pass as
response-<id>.txt.draft, which they may revise, before renaming it to the
final response-<id>.txt they consider final.

| File | Who writes | Meaning |
|---|---|---|
| prompt-<id>.txt | server | an incoming request for the agent |
| response-<id>.txt.draft | agent | an in-progress, editable draft |
| response-<id>.txt | agent | the answer |

Retry is automatic: a prompt with no response file is simply re-offered by
faaah --watch to the coordinator until one appears.

MIT