Add job run logs, OpenRouter model picker, and discipline grouping.

- Job logs: each job's stdout/stderr is teed into outputs/<id>/job.log
  (survives restarts) and served at GET /jobs/{id}/log as text/plain, so
  full run logs can be shared for debugging and refinement.
- Model picker: GET /models proxies OpenRouter's public model list with
  per-1M-token pricing (1h cache, 502 on failure); the UI shows a model
  dropdown with costs when OpenRouter compute is selected, and the pick
  overrides vision+text models for that job (Classic and Agent modes).
- Conflicts in the report view are grouped by discipline pair
  (collapsible sections, severity-ordered within groups) instead of one
  flat severity-only list.

tests/api/test_job_log.py

@@ -0,0 +1,77 @@
+import threading
+
+import pytest
+from fastapi.testclient import TestClient
+
+import backend.jobs as jobs
+from backend.main import app
+
+
+class _SyncThread:
+    """Drop-in threading.Thread replacement that runs the target inline."""
+
+    def __init__(self, target=None, args=(), kwargs=None, **_ignored):
+        self._target = target
+        self._args = args
+        self._kwargs = kwargs or {}
+
+    def start(self):
+        self._target(*self._args, **self._kwargs)
+
+
+@pytest.fixture
+def job_env(monkeypatch, tmp_path):
+    monkeypatch.setattr("backend.config.OUTPUT_DIR", str(tmp_path))
+    monkeypatch.setattr(threading, "Thread", _SyncThread)
+    monkeypatch.setattr("backend.jobs.send_conflict_report", lambda *a, **k: True)
+    pdf = tmp_path / "set.pdf"
+    pdf.write_bytes(b"%PDF-1.4\n")
+    yield tmp_path
+    jobs._jobs.clear()
+
+
+def test_job_log_captures_pipeline_output(job_env, monkeypatch):
+    def fake_runner(pdf_path, **kwargs):
+        print("STAGE banner: fake wave ran")
+        return {"source": "set.pdf", "summary": {"conflicts_found": 0}}
+
+    monkeypatch.setattr("backend.jobs.run_pipeline", fake_runner)
+    job_id = jobs.create_job(str(job_env / "set.pdf"), "set.pdf", pipeline_mode="classic")
+
+    log_path = job_env / job_id / "job.log"
+    assert log_path.is_file()
+    content = log_path.read_text()
+    assert "STAGE banner: fake wave ran" in content
+    assert job_id in content  # header line
+
+
+def test_job_log_endpoint_serves_log_and_404s(job_env, monkeypatch):
+    monkeypatch.setattr(
+        "backend.jobs.run_pipeline",
+        lambda pdf_path, **kw: {"source": "s", "summary": {}},
+    )
+    job_id = jobs.create_job(str(job_env / "set.pdf"), "set.pdf", pipeline_mode="classic")
+
+    client = TestClient(app)
+    ok = client.get(f"/jobs/{job_id}/log")
+    assert ok.status_code == 200
+    assert ok.headers["content-type"].startswith("text/plain")
+    assert "Job " + job_id in ok.text
+    assert client.get("/jobs/nope/log").status_code == 404
+
+
+def test_model_override_set_and_cleared_around_run(job_env, monkeypatch):
+    from backend import llm
+
+    seen = {}
+
+    def fake_runner(pdf_path, **kwargs):
+        seen["override"] = llm._model_override
+        return {"source": "set.pdf", "summary": {}}
+
+    monkeypatch.setattr("backend.jobs.run_pipeline", fake_runner)
+    jobs.create_job(str(job_env / "set.pdf"), "set.pdf",
+                    pipeline_mode="classic", model="openai/gpt-4o")
+
+    assert seen["override"] == "openai/gpt-4o"
+    assert llm._model_override is None  # cleared after the run

tests/api/test_models_api.py

@@ -0,0 +1,64 @@
+from fastapi.testclient import TestClient
+
+import backend.models as models
+from backend import config
+from backend.main import app
+
+_PAYLOAD = {
+    "data": [
+        {
+            "id": "openai/gpt-4o",
+            "name": "GPT-4o",
+            "pricing": {"prompt": "0.0000025", "completion": "0.00001"},
+            "context_length": 128000,
+        },
+        {
+            "id": "google/gemini-2.5-pro",
+            "name": "Gemini 2.5 Pro",
+            "pricing": {"prompt": "0.00000125", "completion": "0.00001"},
+            "context_length": 1000000,
+        },
+    ]
+}
+
+
+def _reset_cache():
+    models._cache["models"] = None
+    models._cache["at"] = 0.0
+
+
+def test_models_endpoint_normalizes_pricing(monkeypatch):
+    _reset_cache()
+    monkeypatch.setattr(models, "_fetch_openrouter_models", lambda: _PAYLOAD["data"])
+    client = TestClient(app)
+    response = client.get("/models")
+    assert response.status_code == 200
+    body = response.json()
+    assert body["default"] == config.MODEL
+    assert body["default_text"] == config.TEXT_MODEL
+    by_id = {m["id"]: m for m in body["models"]}
+    assert by_id["openai/gpt-4o"]["prompt_usd_per_mtok"] == 2.5
+    assert by_id["openai/gpt-4o"]["completion_usd_per_mtok"] == 10.0
+    assert by_id["openai/gpt-4o"]["context_length"] == 128000
+
+
+def test_models_endpoint_caches(monkeypatch):
+    _reset_cache()
+    calls = []
+
+    def fake_fetch():
+        calls.append(1)
+        return _PAYLOAD["data"]
+
+    monkeypatch.setattr(models, "_fetch_openrouter_models", fake_fetch)
+    client = TestClient(app)
+    assert client.get("/models").status_code == 200
+    assert client.get("/models").status_code == 200
+    assert len(calls) == 1
+
+
+def test_models_endpoint_502_on_fetch_failure(monkeypatch):
+    _reset_cache()
+    monkeypatch.setattr(models, "_fetch_openrouter_models", lambda: None)
+    client = TestClient(app)
+    assert client.get("/models").status_code == 502

tests/test_llm_model_override.py

@@ -0,0 +1,26 @@
+from backend import config
+from backend.llm import _resolve_backend, set_model_override
+
+
+def test_override_wins_for_vision_and_text():
+    set_model_override("openai/gpt-4o")
+    try:
+        assert _resolve_backend(has_images=True, model_override=None)["model"] == "openai/gpt-4o"
+        assert _resolve_backend(has_images=False, model_override=None)["model"] == "openai/gpt-4o"
+    finally:
+        set_model_override(None)
+
+
+def test_override_beats_per_call_model_arg():
+    set_model_override("openai/gpt-4o")
+    try:
+        # Agents pass their AGENT_*_MODEL per call; the user's job pick wins.
+        assert _resolve_backend(has_images=False, model_override="other/model")["model"] == "openai/gpt-4o"
+    finally:
+        set_model_override(None)
+
+
+def test_no_override_keeps_defaults():
+    set_model_override(None)
+    assert _resolve_backend(has_images=True, model_override=None)["model"] == config.MODEL
+    assert _resolve_backend(has_images=False, model_override=None)["model"] == config.TEXT_MODEL