- .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>
- Deleted the `.env.example` file as it is no longer needed; all configurations are now centralized in `backend/.env`.
- Updated `docker-compose.yml` and `docker-compose.dev.yml` to reflect changes in environment variable handling, ensuring that the application reads from `backend/.env` exclusively.
- Adjusted the nginx configuration to improve API request handling and ensure proper proxying for frontend interactions.
These changes streamline the environment setup process and enhance the overall configuration management for local and production deployments.
Talha Ahmed
ahmed.mujtaba