Make tune trial budget resumable

src/aituner/cli.py

@@ -126,6 +126,8 @@ def cmd_study_tune(args: argparse.Namespace) -> int:
     executed: list[dict[str, object]] = []
     for idx in range(max_trials):
         state = store.load_state(study.study_id)
+        if state.next_trial_index > max_trials:
+            break
         window, requests = load_trace_requests(study, study_spec_path=spec_path)
         window_summary = summarize_window(requests, window)
         harness_context = (
@@ -169,7 +171,10 @@ def cmd_study_tune(args: argparse.Namespace) -> int:
                 ensure_ascii=False,
             )
         elif proposal_files:
-            proposal_source = proposal_files[idx]
+            proposal_index = state.next_trial_index - 1
+            if proposal_index >= len(proposal_files):
+                break
+            proposal_source = proposal_files[proposal_index]
             proposal_text = proposal_source.read_text(encoding="utf-8")
             proposal_name = proposal_source.stem
         else:

src/aituner/llm.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import json
+import time
 from pathlib import Path
 from typing import Any
 
@@ -604,7 +605,8 @@ def call_llm_for_proposal(
     if policy.endpoint is None:
         raise RuntimeError("study.llm.endpoint is not configured")
     last_error: Exception | None = None
-    for attempt in range(2):
+    max_attempts = 4
+    for attempt in range(max_attempts):
         try:
             if policy.endpoint.stream:
                 text = stream_text_completion(
@@ -636,6 +638,7 @@ def call_llm_for_proposal(
             last_error = RuntimeError("LLM response content is empty")
         except Exception as exc:  # noqa: BLE001
             last_error = exc
-        if attempt == 0:
+        if attempt < max_attempts - 1:
+            time.sleep(min(30.0, 2.0 * (2**attempt)))
             continue
     raise RuntimeError(f"LLM proposal failed after retry: {last_error}") from last_error

tests/test_core_flow.py

@@ -2919,7 +2919,7 @@ class CoreFlowTests(unittest.TestCase):
                             "--store-root",
                             str(store_root),
                             "--max-trials",
-                            "1",
+                            "5",
                         ]
                     )
 
@@ -2997,6 +2997,53 @@ class CoreFlowTests(unittest.TestCase):
             self.assertEqual(state.trials[0].config_patch, {"env_patch": {}, "flag_patch": {}})
             self.assertEqual(state.trials[1].config_patch["flag_patch"], {"max-num-seqs": 64})
 
+    def test_cli_tune_max_trials_is_total_budget_on_resume(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp:
+            tmp_path = Path(tmp)
+            study_path = _write_study_assets(tmp_path)
+            payload = json.loads(study_path.read_text(encoding="utf-8"))
+            payload["llm"]["endpoint"] = {
+                "provider": "custom",
+                "base_url": "http://llm.example/v1",
+                "wire_api": "chat.completions",
+                "model": "test-model",
+                "api_key_env": "OPENAI_API_KEY",
+            }
+            study_path.write_text(json.dumps(payload), encoding="utf-8")
+            store_root = tmp_path / "store"
+            study = load_study_spec(study_path)
+            store = StudyStore(store_root)
+            store.init_study(spec_path=study_path, study=study)
+            state = StudyState(
+                study_id=study.study_id,
+                next_trial_index=3,
+                trials=[
+                    TrialSummary(trial_id="trial-0001", status="completed"),
+                    TrialSummary(trial_id="trial-0002", status="completed"),
+                ],
+            )
+            store.save_state(state)
+
+            with mock.patch("aituner.cli.call_llm_for_proposal") as llm_mock:
+                with mock.patch("aituner.cli.run_trial") as run_trial_mock:
+                    exit_code = cli_main(
+                        [
+                            "study",
+                            "tune",
+                            "--spec",
+                            str(study_path),
+                            "--store-root",
+                            str(store_root),
+                            "--max-trials",
+                            "2",
+                        ]
+                    )
+
+            self.assertEqual(exit_code, 0)
+            llm_mock.assert_not_called()
+            run_trial_mock.assert_not_called()
+            self.assertEqual(store.load_state(study.study_id).next_trial_index, 3)
+
     def test_load_compare_spec_requires_window_selection(self) -> None:
         with tempfile.TemporaryDirectory() as tmp:
             tmp_path = Path(tmp)