Free-Tier AI Commit Messages: A MonkeyCode Build Log

Free-Tier AI Commit Messages: A MonkeyCode Build Log

Most code generation tools ask for a credit card before you can even test a realistic workflow. MonkeyCode's open-source platform takes a different approach: free model tokens and a free server tier for small apps. For a weekend project, that's enough to build something genuinely useful — a tool that reads your staged Git diff and suggests a commit message.

Disclosure: This article was prepared as part of MonkeyCode's product outreach.

This build log covers the full stack: a FastAPI service that calls the model API, a local CLI that sends diffs, and deployment onto MonkeyCode's free hosting. The result is a practical pattern you can reuse with any API provider.

Why a commit-message generator?

Commit messages are a low-stakes, high-frequency task. They are also easy to brute-force with an LLM because the input is a diff and the output is a short sentence. The model only sees the diff you give it, so there is no hidden context to trust — addressing the "AI remembers everything" concern from a recent DEV discussion.

The project also gives you a safe way to play with free-tier limits without risking anything important. If the API is down or the generated message is bad, you lose a few seconds, not a deployment.

Architecture overview

• Local CLI: captures git diff --cached and POSTs it to your server.
• Free server: runs a small FastAPI app that forwards the diff to MonkeyCode's model API.
• Model API: returns a commit message, which the server relays back to the CLI.

The two-part design matters because it keeps your API key off your laptop and lets you reuse the same endpoint from multiple machines.

Step 1: Get API access

Create an account and grab an API key from MonkeyCode's dashboard. The free tier currently includes 10,000,000 tokens and a free server slot — enough for hundreds of small requests.

Verify current quotas and endpoint details in the official docs, since free tiers change over time.

Step 2: Write the FastAPI service

Here's a minimal server that accepts a diff and returns a suggested commit message. Replace MONKEYCODE_API_URL and MODEL_ID with the values from the current documentation (I'm using placeholders because these vary by region and billing plan):

# server.py
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import requests
import os

app = FastAPI()

class DiffRequest(BaseModel):
    diff: str

@app.post("/generate")
async def generate(req: DiffRequest):
    api_key = os.getenv("MONKEYCODE_API_KEY")
    if not api_key:
        raise HTTPException(status_code=500, detail="API key not configured")

    url = os.getenv("MONKEYCODE_API_URL")  # e.g., https://api.monkeycode.ai/v1/chat/completions
    headers = {"Authorization": f"Bearer {api_key}"}
    payload = {
        "model": os.getenv("MONKEYCODE_MODEL", "placeholder-model"),
        "messages": [
            {"role": "system", "content": "You are an expert at writing concise, conventional Git commit messages."},
            {"role": "user", "content": f"Write a commit message for this diff: {req.diff}"}
        ]
    }

    try:
        resp = requests.post(url, json=payload, headers=headers, timeout=30)
        resp.raise_for_status()
        data = resp.json()
        return {"message": data["choices"][0]["message"]["content"].strip()}
    except Exception as e:
        raise HTTPException(status_code=502, detail=str(e))

Run locally with uvicorn server:app --reload if you want to test before deploying.

Step 3: Deploy to MonkeyCode's free server

MonkeyCode's free server accepts standard containerized services. After you commit the server.py and a minimal requirements.txt, use their CLI or dashboard to deploy. For example, their CLI often looks like:

mc deploy --app my-commit-bot

I'm not going to copy every command because the precise workflow depends on your registry and region. The good news: the free server is intended for small personal projects, so you don't need to tune a Dockerfile or configure autoscaling.

Set the environment variables MONKEYCODE_API_KEY, MONKEYCODE_API_URL, and MONKEYCODE_MODEL in the dashboard after deployment.

Step 4: Build the local CLI

The CLI is a 20-line Python script that collects the staged diff and calls your server:

# commit-msg.py
import subprocess, sys, requests

def get_diff():
    result = subprocess.run(["git", "diff", "--cached"], capture_output=True, text=True)
    return result.stdout

def ask_server(diff):
    url = sys.argv[1] if len(sys.argv) > 1 else "https://your-app.onmck.dev/generate"
    response = requests.post(url, json={"diff": diff}, timeout=30)
    response.raise_for_status()
    return response.json()["message"]

if __name__ == "__main__":
    diff = get_diff()
    if not diff.strip():
        print("No staged changes. Run git add first.")
        sys.exit(1)

    message = ask_server(diff)
    print("Suggested commit message:")
    print(message)

Make it executable and run:

chmod +x commit-msg.py
./commit-msg.py https://your-app.onmck.dev/generate

What I learned about free tiers

• Token limits go faster than you think. Each diff can be anywhere from 500 to 3,000 tokens when you include context. At 1,000 tokens per call, 10M tokens gives you ~10,000 requests — generous for personal use, but not for a team.
• Latency varies. Free server instances may go to sleep. The first request after a pause can take 5–10 seconds extra. That's fine for interactive use, not for CI.
• Error handling is essential. The API can return malformed JSON or rate-limit you. Always wrap the call in try/except and fall back to a manual message.

Who should not use this approach

• Teams that generate dozens of messages per hour during code review.
• Projects where commit messages must follow a strict internal format beyond convention.
• Anyone who needs guaranteed uptime for a mission-critical pipeline.

For those cases, a paid plan with a service-level agreement makes more sense. But for a side project or a personal productivity boost, the free tier gets the job done.

Try it this weekend

The full pattern — local CLI, serverless API, free model — can be cloned and running in under an hour. If you want a zero-cost AI assistant that writes your commit messages, give MonkeyCode's free tier a shot. The code above is a solid starting point, and you can extend it to add emoji suggestions, multiple language styles, or even a pre-commit hook.