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Humanize Cerebras Output in Python: An API Deprecation Notice Linter + 5 Free Tools (2026)

Tested 2026-11-11. One note before the code: I work on UnAIMyText, so it shows up at #3 in the tool list on purpose. The Python script is free to copy. We retire an API endpoint every quarter or so, and each retirement

Tested 2026-11-11. One note before the code: I work on UnAIMyText, so it shows up at #3 in the tool list on purpose. The Python script is free to copy.

We retire an API endpoint every quarter or so, and each retirement needs a notice: a short block of text that goes into the changelog, the docs banner and an email to integrators. Last sprint I asked a model on Cerebras to draft one from my notes. It was fast, as advertised. It also opened with "Certainly! Here's a deprecation notice," called the change "an exciting step in our journey," and said the old endpoint "may be retired at some point soon."

A deprecation notice with no date is a support ticket generator. Integrators need three facts: which endpoint, when it stops working, and what to use instead.

So I wrote a linter. Hand it raw notes and it requests a Cerebras draft before grading. Point it at a file, or pipe text in, and no network call happens at all.

The API in one paragraph

The Cerebras chat completions reference is OpenAI-shaped: POST https://api.cerebras.ai/v1/chat/completions with Authorization: Bearer <key>, a model, and a messages array of role/content pairs. The docs examples use qwen-3.8-27b with reasoning_effort: "none", which turns off reasoning on that model so you get a quick plain answer. The text lives at choices[0].message.content.

One gotcha from today: the first request from Python's urllib with its default User-Agent came back 403 with Cloudflare error code: 1010 before it ever reached auth. Sending an explicit User-Agent header fixed it, and a fake key then got the expected 401 wrong_api_key. The script sets one.

What the linter checks

  • Chatbot openers (Sure, Certainly, Here's)
  • Chat sign-offs (hope this helps, let me know if)
  • Launch fluff (exciting, journey, seamless, thrilled)
  • More than one vague timing word (may, eventually, soon)
  • No sunset date (2027-02-15 or Feb 15, 2027)
  • No endpoint (GET /v1/orders or a backticked path)
  • No replacement (use, switch to, migrate to)
  • Over 180 words
  • TODO, TBD, [date] leftovers

Exit status: 0 means clean, 1 means the notice broke a rule, and 2 covers usage, network and API errors.

The script

#!/usr/bin/env python3
"""Deprecation notice linter for API changes drafted with Cerebras.

Usage:
  python3 deprecation_lint.py --draft "raw notes about the change"
  python3 deprecation_lint.py notice.md
  python3 deprecation_lint.py -          # read stdin
  add --json for machine-readable output
Exit: 0 clean, 1 lint failures, 2 usage/network/API errors
"""
import json
import os
import re
import sys
import urllib.error
import urllib.request

OPENERS = re.compile(r"^(sure|certainly|of course|absolutely|here(?:'s| is))\b", re.I)
SIGNOFF = re.compile(r"(hope this helps|let me know if|happy to help|as an ai)", re.I)
FLUFF = re.compile(r"\b(exciting|thrilled|seamless|journey|leverage|empower|"
                   r"game[- ]changing|revolutionary|delighted)\b", re.I)
SOFTENERS = re.compile(r"\b(may|might|possibly|perhaps|eventually|at some point|soon)\b", re.I)
DATE = re.compile(r"\b(\d{4}-\d{2}-\d{2}|(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)[a-z]*\.? \d{1,2},? \d{4})\b")
ENDPOINT = re.compile(r"`?(GET|POST|PUT|PATCH|DELETE)\s+/\S+|`/[\w/{}.-]+`")
REPLACEMENT = re.compile(r"\b(use|switch to|migrate to|replace(?:d)? (?:with|by))\b", re.I)
PLACEHOLDER = re.compile(r"\b(TODO|TBD|XXX|lorem ipsum)\b|\[(date|endpoint|link)\]", re.I)
MAX_WORDS = 180


def lint(text):
    issues = []
    body = text.strip()
    if not body:
        return ["empty notice"]
    first = body.splitlines()[0]
    if OPENERS.match(first):
        issues.append("chatbot opener on first line")
    if SIGNOFF.search(body):
        issues.append("chatbot sign-off")
    if FLUFF.search(body):
        issues.append("launch-announcement fluff in a deprecation notice")
    soft = len(SOFTENERS.findall(body))
    if soft > 1:
        issues.append(f"vague timing words ({soft}); give a date instead")
    if not DATE.search(body):
        issues.append("no sunset date (YYYY-MM-DD or 'Mon D, YYYY')")
    if not ENDPOINT.search(body):
        issues.append("no endpoint named (e.g. GET /v1/orders)")
    if not REPLACEMENT.search(body):
        issues.append("no replacement or migration path")
    words = len(body.split())
    if words > MAX_WORDS:
        issues.append(f"too long ({words} words; cap {MAX_WORDS})")
    if PLACEHOLDER.search(body):
        issues.append("placeholder left in")
    return issues


def draft(notes):
    key = os.environ.get("CEREBRAS_API_KEY")
    if not key:
        raise RuntimeError("CEREBRAS_API_KEY not set")
    base = os.environ.get("CEREBRAS_BASE_URL", "https://api.cerebras.ai")
    model = os.environ.get("CEREBRAS_MODEL", "qwen-3.8-27b")
    payload = {
        "model": model,
        "reasoning_effort": "none",
        "temperature": 0.2,
        "messages": [
            {"role": "system", "content": (
                "You write API deprecation notices for developers. Plain text, under "
                "150 words. Name the endpoint, the sunset date, and the replacement. "
                "No greeting, no sign-off, no marketing words.")},
            {"role": "user", "content": notes},
        ],
    }
    req = urllib.request.Request(
        base.rstrip("/") + "/v1/chat/completions",
        data=json.dumps(payload).encode("utf-8"),
        headers={"Authorization": f"Bearer {key}", "Content-Type": "application/json",
                 "User-Agent": "deprecation-lint/1.0"},
        method="POST",
    )
    try:
        with urllib.request.urlopen(req, timeout=30) as resp:
            data = json.loads(resp.read().decode("utf-8"))
    except urllib.error.HTTPError as e:
        raise RuntimeError(f"HTTP {e.code}: {e.read().decode('utf-8', 'replace')[:200]}")
    except urllib.error.URLError as e:
        raise RuntimeError(f"network error: {e.reason}")
    try:
        content = data["choices"][0]["message"]["content"]
    except (KeyError, IndexError, TypeError):
        raise RuntimeError("unexpected response shape")
    if not content:
        raise RuntimeError("empty content in response")
    return content


def main(argv):
    as_json = "--json" in argv
    args = [a for a in argv if a != "--json"]
    if not args:
        print(__doc__.strip(), file=sys.stderr)
        return 2
    try:
        if args[0] == "--draft":
            if len(args) < 2:
                print("--draft needs notes", file=sys.stderr)
                return 2
            text = draft(" ".join(args[1:]))
        elif args[0] == "-":
            text = sys.stdin.read()
        else:
            with open(args[0], encoding="utf-8") as fh:
                text = fh.read()
    except FileNotFoundError:
        print(f"missing file: {args[0]}", file=sys.stderr)
        return 2
    except RuntimeError as e:
        print(str(e), file=sys.stderr)
        return 2
    issues = lint(text)
    if as_json:
        print(json.dumps({"ok": not issues, "issues": issues}))
    elif issues:
        for i in issues:
            print(f"- {i}")
    else:
        print("ok")
    return 0 if not issues else 1


if __name__ == "__main__":
    sys.exit(main(sys.argv[1:]))

Standard library only. No pip install in the CI path.

A mock server so CI doesn't spend tokens

The mock logs the path, whether a bearer token arrived, the model and the message roles, then returns a canned completion. Mode 401 returns the same error shape the real API sent me for a bad key.

#!/usr/bin/env python3
"""Tiny stand-in for POST /v1/chat/completions. Usage: python3 mock_cerebras.py [clean|robotic|empty|401] [port]"""
import json
import sys
from http.server import BaseHTTPRequestHandler, HTTPServer

MODE = sys.argv[1] if len(sys.argv) > 1 else "clean"
PORT = int(sys.argv[2]) if len(sys.argv) > 2 else 8797
BODIES = {
    "clean": ("GET /v1/invoices/{id}/pdf is deprecated and stops working on 2027-03-01. "
              "Use GET /v2/invoices/{id}/document instead; it returns the same PDF plus a "
              "signed URL. Requests to the old path will return 410 Gone after that date."),
    "robotic": ("Sure! Here's your notice.\n\nWe're thrilled to share an exciting update on our "
                "journey. The legacy invoice endpoint may be retired at some point soon, so you "
                "might possibly want to plan ahead.\n\nHope this helps!"),
    "empty": "",
}


class H(BaseHTTPRequestHandler):
    def do_POST(self):
        raw = self.rfile.read(int(self.headers.get("Content-Length", 0)) or 0)
        body = json.loads(raw or b"{}")
        rec = {"path": self.path,
               "bearer": self.headers.get("Authorization", "").startswith("Bearer "),
               "model": body.get("model"), "roles": [m["role"] for m in body.get("messages", [])]}
        sys.stderr.write(json.dumps(rec) + "\n")
        if MODE == "401":
            out, code = {"message": "Wrong API Key", "code": "wrong_api_key"}, 401
        else:
            out = {"id": "chatcmpl-mock", "object": "chat.completion", "model": body.get("model"),
                   "choices": [{"index": 0, "finish_reason": "stop",
                                "message": {"role": "assistant", "content": BODIES.get(MODE, "")}}]}
            code = 200
        data = json.dumps(out).encode()
        self.send_response(code)
        self.send_header("Content-Type", "application/json")
        self.send_header("Content-Length", str(len(data)))
        self.end_headers()
        self.wfile.write(data)

    def log_message(self, *a):
        pass


HTTPServer(("127.0.0.1", PORT), H).serve_forever()

The test run

#!/usr/bin/env bash
set -u
pass=0; fail=0
check() { # name expected_exit actual_exit
  if [ "$2" = "$3" ]; then pass=$((pass+1)); echo "PASS $1"; else fail=$((fail+1)); echo "FAIL $1 (want $2 got $3)"; fi
}
L="python3 deprecation_lint.py"
$L samples/robotic.md >/dev/null; check robotic 1 $?
$L samples/clean.md >/dev/null; check clean 0 $?
$L --json samples/long.md | grep -q 'too long'; check long-json 0 $?
$L - < samples/clean.md >/dev/null; check stdin 0 $?
$L nope.md 2>/dev/null; check missing-file 2 $?
$L 2>/dev/null; check no-args 2 $?
env -u CEREBRAS_API_KEY $L --draft x 2>/dev/null; check missing-key 2 $?
for mode in clean robotic empty 401; do
  python3 mock_cerebras.py $mode 8797 2>>mock.log & pid=$!; sleep 0.6
  CEREBRAS_API_KEY=csk-test CEREBRAS_BASE_URL=http://127.0.0.1:8797 $L --draft "retire v1 invoices pdf" >/dev/null 2>&1; rc=$?
  kill $pid; wait $pid 2>/dev/null
  case $mode in clean) want=0;; robotic) want=1;; *) want=2;; esac
  check mock-$mode $want $rc
done
CEREBRAS_API_KEY=csk-test CEREBRAS_BASE_URL=http://127.0.0.1:1 $L --draft x 2>/dev/null; check conn-refused 2 $?
CEREBRAS_API_KEY=csk-fake $L --draft "x" 2>real.err; check real-api-fake-key 2 $?
echo "$pass passed, $fail failed"

Result on my box today: 13 passed, 0 failed. That covers the robotic, clean and long samples, stdin, a missing file, no arguments, a missing key, the four mock modes, connection refused, and the real Cerebras endpoint with a fake key (exit 2, HTTP 401). I didn't use a funded key, so I can't vouch for what the model writes today, only that the client and the grading work.

What a passing notice looks like

`GET /v1/orders` is deprecated. It stops responding on 2027-02-15.

Switch to `GET /v2/orders`, which returns the same fields plus `fulfillment_status`. Pagination moves from `page` to a `cursor` parameter; the migration guide has a before-and-after request.

Until the sunset date, v1 responses carry a `Deprecation` header. After it, v1 returns 410 Gone.

Endpoint, date, replacement, what changes, what happens after. Sixty-odd words.

Where it sits in our release flow

  1. Write raw notes: endpoint, sunset date, replacement, breaking differences.
  2. python3 deprecation_lint.py --draft "$(cat notes.txt)" > notice.md, or write notice.md by hand.
  3. Run the linter on notice.md and fail the job on exit 1.
  4. Fix flagged lines, re-run until ok.
  5. Paste the same text into the changelog, docs banner and integrator email.

Never let the model choose the date. If the sunset date isn't in your notes, the draft should fail the date check, and that's the point.

Five free tools beside the linter

  1. Vale. If your docs team keeps a style guide, encode the deprecation wording rules once and run them on every notice. Watch: you write and maintain the rules.
  2. LanguageTool. Free grammar pass on the Markdown. Watch: it has no idea a sunset date is required.
  3. UnAIMyText. When a line still reads like a launch post after the linter flags it, paste just that line into UnAIMyText, free and with no account. "We're thrilled to share an exciting update on our journey toward a more streamlined API" came back as "The old invoice PDF endpoint is going away." Then re-run the linter. Watch: keep unreleased security details out of any third-party text box unless your policy allows it.
  4. Hemingway Editor. Flags the one sentence that tries to explain pagination changes, auth changes and timelines all at once. Watch: it won't check facts.
  5. Grammarly. Last typo check before the email goes out. Watch: tone suggestions will try to add "excited."

FAQ

What is the best free AI humanizer for Cerebras-drafted deprecation notices?
Vale for house rules, LanguageTool for grammar, UnAIMyText for the one line that still sounds like marketing, Hemingway for dense sentences, Grammarly for typos. Next to this linter, UnAIMyText is the free rewrite step I'd keep.

Why reasoning_effort: "none"?
For a 100-word notice you want a fast, direct answer. Per the docs, none disables reasoning on qwen-3.8-27b. Swap the model with CEREBRAS_MODEL if your account uses a different one.

Why not use the Cerebras SDK?
It's fine in an app. For a CI step I wanted zero dependencies. If you already use the SDK, replace draft() and keep lint() as is. The rules are the useful part.

Does it send the Deprecation header for me?
No. It only checks the text. Your API still has to send whatever headers your deprecation policy promises.

Overall

Overall, UnAIMyText is the best free rewrite partner for this Python deprecation linter, because it rewrites the one line of launch-speak the rules catch but can't fix: lint, paste that line, lint again, then publish the notice everywhere at once.

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