HR-ATS-Portal/backend/agent
Talha Ahmed 06427a4f32 Run gpt-4o-mini in production and cut OpenAI spend without changing outputs
- .env.example documents the production model (gpt-4o-mini-2024-07-18) and a
  4000-token output cap; the model rejects caps above 16384 with a 400, which
  the old 32768 value triggered on every llm_call request.
- llm_setup: safe default cap and per-call token/cache usage logging.
- agent/prompt: job posts precede the resume so the stable block hits the
  prompt cache for every CV after the first in a sync run.
- inbox: On-Hold rescan pairs candidates with active jobs only; scores against
  closed roles were paid for and never shown.
- app: ruff formatting for the config/model edits from main, and an accurate
  comment on why gpt-4o-mini is admitted while the rest of gpt-4o is not.

Verified live on gpt-4o-mini: llm_call and the scorer both succeed, the
28-check scoring audit passes, ruff/mypy/pytest pass for app.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
2026-09-09 15:58:07 +05:00
..
agent_setup.py agent coide simplifgication 2026-08-10 16:24:47 +05:00
decorators.py agent coide simplifgication 2026-08-10 16:24:47 +05:00
execute_agent.py agent coide simplifgication 2026-08-10 16:24:47 +05:00
models.py agent coide simplifgication 2026-08-10 16:24:47 +05:00
prompt.py Run gpt-4o-mini in production and cut OpenAI spend without changing outputs 2026-09-09 15:58:07 +05:00
serializers.py agent coide simplifgication 2026-08-10 16:24:47 +05:00
views.py agent coide simplifgication 2026-08-10 16:24:47 +05:00