phase: 114_embed_question_length

All verification passes complete — the phase was already fully implemented in the working tree, and every gate is green. No defects found; no code changes were needed.

**Final verification pass — Phase 114 (embed question length):**
- Verified truncation: `chat.py:459` embeds `request.message[:settings.embed_question_max_chars]` (default 1200, `BOR_EMBED_QUESTION_MAX_CHARS`, `>0` validator); full question still reaches the LLM prompt/log.
- Verified error mapping: `EmbeddingInputTooLargeError(EmbeddingError)` (byte-identical message) caught **before** `EmbeddingError` → no retry, terminal frame `detail="Question too long — trim it and re-ask."` + reachability-fine hint; `ChatErrorEvent.hint` additive.
- Verified frontend chain: frame `hint` → `err.hint` → `setUiState(error, …, {hint})` → `showErrorBanner(…, {retryable: true})` — hint replaces default `ERROR_HINT`, phase-111 `#banner-retry` button revealed. 4,000-char clamp untouched (A2).
- `uv run pytest tests/unit/test_embed_question_length.py -v --no-cov` → 21 passed
- `uv run pytest tests/e2e/test_embed_question_length.py -v --no-cov` (isolation, DB up) → 1 passed (4,000-char question → done, no banner)
- Regression: `test_llm_retry.py` 4 passed · `test_oneshot_llm_retry.py` 2 passed · `test_chip_sizing_question_cap.py` 6 passed
- `uv run pytest --cov=app --cov-report=term-missing` → 2444 passed, TOTAL **99%** (>90% gate)
- `uv run ruff check .` → All checks passed; `uv run pyright` → 0 errors, 0 warnings

**Completion criteria:** (1) 4,000-char question embeds prefix + full prompt ✅ · (2) too-large → accurate frame + hint + Retry button ✅ · (3) reachability failure byte-identical (retries + old copy) ✅ · (4) all gates green ✅ · (5) commit/phase-move → left to the harness per instructions (no `git add`/`commit` run).
**Deviations:** none. **Next pending phase:** `115_doc_draft_discard`.

app/config.py

@@ -156,6 +156,18 @@ class Settings(BaseSettings):
     chunk_target_chars: int = 2_000
     chunk_overlap_chars: int = 200
     embed_batch_size: int = 16
+    #: Char budget for the chat turn's question embed (phase 114, TODO L6;
+    #: LOCKED A1): the embed step embeds at most this many chars of the
+    #: question — the default 1200 is the chunker's ``HARD_MAX_CHARS``
+    #: budget (``app/rag/chunker.py``: worst-case ~1.4 chars/token, so it
+    #: stays under the endpoint's ~1024-token per-request input cap). Only
+    #: the embedding is bounded: the FULL question still reaches the LLM
+    #: prompt (prompt build untouched), and a question at or under the
+    #: budget embeds byte-identically to the pre-phase path. A model with a
+    #: larger/smaller cap is accommodated by env, no code change (A1).
+    #: ``0``/negative is a typo — the validator fails loudly at startup
+    #: (the ``agent_max_rounds`` pattern).
+    embed_question_max_chars: int = 1200
     #: Total char budget for the ``<tuning>`` section of the system prompt
     #: (phase 15, steering notes). The newest-fitting notes are kept and the
     #: overflow is replaced by the ``[…truncated…]`` marker.
@@ -415,6 +427,15 @@ class Settings(BaseSettings):
             raise ValueError("read_max_chars must be >= 0 (chars)")
         return v
 
+    @field_validator("embed_question_max_chars")
+    @classmethod
+    def _embed_question_max_chars_positive(cls, v: int) -> int:
+        """``0``/negative would embed an empty/absent prefix — fail loud at
+        startup (the ``agent_max_rounds`` pattern, phase 114)."""
+        if v <= 0:
+            raise ValueError("embed_question_max_chars must be > 0 (chars)")
+        return v
+
     @field_validator("llm_retries")
     @classmethod
     def _llm_retries_non_negative(cls, v: int) -> int: