+ This starts a paid Apify search of LinkedIn for people matching
+ this job's title, technical requirements and experience level, {locationLabel} —
+ up to 25 profiles per run (roughly $0.20). Repeating the same search continues
+ deeper into the results, so each run surfaces new people; anyone already found
+ is refreshed, not duplicated.
+
+
+ )}
+
+ )
+}
diff --git a/scripts/smoke_structured_output.py b/scripts/smoke_structured_output.py
new file mode 100644
index 0000000..bbaaea0
--- /dev/null
+++ b/scripts/smoke_structured_output.py
@@ -0,0 +1,108 @@
+"""Live smoke test for the request shape. Makes two real API calls.
+
+Run this once before trusting the service against a new model or SDK version:
+
+ python scripts/smoke_structured_output.py
+
+It proves the three things unit tests cannot:
+
+1. The schema derived from ``ATSScore`` is accepted by structured outputs, and the
+ configured model supports both it and the requested reasoning effort.
+2. ``output_parsed`` comes back as a valid ``ATSScore``.
+3. The shared job-description prefix is actually cached -- the second call reports
+ ``usage.input_tokens_details.cached_tokens > 0``.
+
+Needs OPENAI_API_KEY in the environment or .env, and spends a few cents.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import sys
+from pathlib import Path
+
+# Running a script directly puts scripts/ on sys.path[0], not the repo root. This
+# environment has another project on the path via an editable-install .pth file, and
+# it also ships a top-level `app` package -- without this line `import app` silently
+# resolves to that one instead.
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
+
+from openai import AsyncOpenAI
+
+from app.core.config import get_settings, supports_reasoning
+from app.core.logging import configure_logging
+from app.services.llm import OpenAIScorer
+
+# OpenAI only caches prompts at or above 1024 tokens, so a short job description will
+# report zero cached tokens no matter how stable the prefix is. This one clears it.
+JOB_DESCRIPTION = (
+ "Senior backend engineer.\n\n"
+ "Required: Python 3.12, FastAPI, asyncio, Docker, PostgreSQL, REST API design, "
+ "and demonstrated ownership of production services.\n"
+ "Preferred: AWS, Kubernetes, Terraform, observability tooling.\n\n"
+) + ("Responsibilities include designing, shipping, and operating backend services. " * 200)
+
+RESUME_A = (
+ "Ada Lovelace\nBackend engineer, 6 years.\n"
+ "Built FastAPI services on Python 3.12 with asyncio and PostgreSQL. "
+ "Owned Docker-based deploys and on-call for a payments API."
+)
+RESUME_B = (
+ "Grace Hopper\nData engineer, 3 years.\n"
+ "Primarily ETL in Python with pandas and Airflow. Familiar with REST APIs. "
+ "No production service ownership listed."
+)
+
+
+async def main() -> int:
+ settings = get_settings()
+ configure_logging(level=settings.log_level, fmt=settings.log_format)
+ print(
+ f"model={settings.openai_model} "
+ f"effort={settings.openai_effort if supports_reasoning(settings.openai_model) else 'n/a'} "
+ f"max_output_tokens={settings.openai_max_output_tokens}"
+ )
+
+ client = AsyncOpenAI(
+ api_key=settings.openai_api_key or None,
+ timeout=settings.openai_timeout_seconds,
+ max_retries=settings.openai_max_retries,
+ )
+ scorer = OpenAIScorer(
+ client,
+ model=settings.openai_model,
+ max_output_tokens=settings.openai_max_output_tokens,
+ effort=settings.openai_effort,
+ enable_cache=settings.openai_enable_prompt_cache,
+ )
+
+ try:
+ # Sequential on purpose: a cache entry is only readable once the first
+ # response exists, which is exactly what score_batch's priming step does.
+ first = await scorer.score(JOB_DESCRIPTION, RESUME_A)
+ print(
+ f"call 1 ok: score={first.match_score} name={first.candidate_name!r} "
+ f"title={first.job_title!r} years={first.years_experience} "
+ f"critique={first.summary_critique!r}"
+ )
+
+ second = await scorer.score(JOB_DESCRIPTION, RESUME_B)
+ print(
+ f"call 2 ok: score={second.match_score} name={second.candidate_name!r} "
+ f"title={second.job_title!r} years={second.years_experience} "
+ f"critique={second.summary_critique!r}"
+ )
+ finally:
+ await client.close()
+
+ print(
+ "\nSchema accepted and both responses parsed. "
+ "Check the 'candidate_scored_upstream' log lines above: call 2 should show a "
+ "non-zero cached_tokens. If it is zero, either the prompt is under the 1024-token "
+ "caching minimum or the job-description prefix is not byte-stable across calls."
+ )
+ return 0
+
+
+if __name__ == "__main__":
+ sys.exit(asyncio.run(main()))
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py
new file mode 100644
index 0000000..e69de29