llm-model-deprecation

Track and check deprecation status of LLM provider models (OpenAI, Anthropic, Gemini, etc.). Use it to warn when your app uses deprecated or retired models and to get replacement suggestions.

Install

pip install llm-model-deprecation

Optional: URL loading via requests (otherwise stdlib urllib is used):

pip install "llm-model-deprecation[fetch]"

Library usage

Data is loaded from the default registry (online with built-in fallback). No config needed.

from llm_deprecation import DeprecationChecker, DeprecationStatus

checker = DeprecationChecker()

# Check by model id (searches all providers)
checker.is_deprecated("gpt-3.5-turbo-0301")   # True
checker.is_retired("gpt-3.5-turbo-0301")     # True
checker.status("gpt-4")                       # DeprecationStatus.ACTIVE

# With provider for exact match
checker.get("claude-2.0", provider="anthropic")
# -> ModelInfo(provider='anthropic', model_id='claude-2.0', status=..., replacement='...', ...)

# List deprecated models
for m in checker.list_deprecated(provider="openai"):
    print(m.model_id, m.status.value, m.replacement)

Status values

• active — Currently supported, no deprecation.
• legacy — Still supported; prefer newer models.
• deprecated — Will be retired; migrate before sunset date.
• retired — No longer available.

Add or override models in code

from datetime import date
from llm_deprecation import DeprecationChecker
from llm_deprecation.models import ModelInfo, DeprecationStatus

checker = DeprecationChecker()
checker.register(ModelInfo(
    provider="openai",
    model_id="gpt-4-old",
    status=DeprecationStatus.DEPRECATED,
    sunset_date=date(2026, 1, 1),
    replacement="gpt-4o",
))

CLI

Scan a project for deprecated or retired model references (CI, cron, or local):

llm-deprecation scan
llm-deprecation scan /path/to/project
llm-deprecation scan --fail-on-deprecated   # exit 1 if any found (for CI)

Example output:

Scanning project...
⚠ openai:gpt-3.5-turbo → deprecated soon
⚠ anthropic:claude-instant → retired

The scanner looks in common code and config files (.py, .json, .yaml, .env, .ts, etc.).

GitHub Action

Run the same check in GitHub Actions:

- name: Check LLM deprecations
  uses: techdevsynergy/llm-model-deprecation@v1
  with:
    fail-on-deprecated: true

Options: path (project root to scan), fail-on-deprecated, version (pin package version).

Data source

Registry is loaded from the default URL (llm-deprecation-data); if unreachable (e.g. offline), the built-in registry in the library is used.

Links

• OpenAI API deprecations
• Anthropic model deprecations
• deprecations.info

License

MIT