feat(rag): pass chat history with prior thinking to the LLM

Phase 74 (TODO.md L4): a follow-up question now reaches the model WITH
the conversation so far — every prior user/brain turn and the prior
thinking blocks on brain turns (preserve-thinking) — while
POST /api/chat stays stateless (A10): the client provides the history
in the request body and the server stores nothing new.

Server (task 01):
- ChatRequest.history: optional list[HistoryTurn] (who: user|brain,
  text, optional thinking) — absent/empty keeps the request
  byte-identical to pre-phase-74 (the two-message [system, user]
  request; the kill-switch semantics are pinned in the integration
  suite).
- app.rag.prompts.history_to_messages: pure mapper — walks the turns
  newest-first against the settings budgets (history_max_turns=40 /
  history_max_chars=24000, BOR_HISTORY_MAX_TURNS /
  BOR_HISTORY_MAX_CHARS); a capped turn is dropped WHOLE (never cut
  mid-answer); the kept window is returned oldest-first; brain turns
  carry their thinking as reasoning_content (A4) only when
  non-empty.
- Both branches feed it: the deflected path splices it between the
  system prompt and the current user message (the phase-71 recovery
  still rebuilds from messages[1:]), the grounded agent receives
  run_agent(..., history=hist); llm.py's message params widen to
  list[dict[str, Any]] (string-only messages stay byte-identical on
  the wire — the SDK passes message dicts through verbatim).
- The per-turn log line (PLAN §9) gains history_msgs=N after
  kb_chars=N.
- Pins: tests/unit/test_history.py (mapper: mapping, reasoning
  gating, both budgets, drop-whole, ordering, empty default),
  tests/unit/test_config.py (the two settings + env overrides),
  tests/unit/test_agent.py (the history splice + the default),
  tests/integration/test_chat_api.py (deflected AND grounded forward
  the history incl. reasoning_content, no-history byte-identity, 422
  pins, the log field).

Client (task 02):
- runTurn — the single funnel for fresh send / phase-49 retry /
  phase-53 stale-regen — sends history = the conversation record
  minus the current question, with thinking only on brain records
  that streamed one (undefined drops the key from the JSON, the
  record's convention); the question is never duplicated into the
  history.

Wire proof (task 03):
- The mock's echo my history marker (HISTORY_TRIGGER) answers with
  the deterministic history echo — history: N prior messages; last
  answer tail: <last 24 chars>; thinking: yes|no — checked BEFORE
  the DEFLECT_MODE branch (like TABLE_TRIGGER), so it fires on both
  turn branches whatever the gate says; the module docstring records
  the user/assistant-only history invariant that keeps every
  existing (tool-result-classified) marker flow unaffected.
- tests/e2e/test_llm_history.py (isolated): a grounded follow-up and
  a deflected follow-up both receive history: 2 prior messages +
  thinking: yes + the byte-exact tail of turn 1's answer (derived
  from the persisted bor.chat.v1 record — the same array the client
  maps into the body); a cold start receives history: 0 prior
  messages / last answer tail: none / thinking: no.
- Regressions green in isolation: chat_rag, chat_history (phase 50),
  agent_document_tools, harness_aligned_tools, stop_generation,
  retry_answer, response_to_docs.

.agents/phases/complete/74_llm_chat_history/01_server_history_ingestion.md

@@ -0,0 +1,48 @@
+# Task 01 — Server: optional client-provided history, trimmed + mapped (incl. `reasoning_content`)
+
+**Phase:** `74_llm_chat_history` · **Source:** `TODO.md:4` — "Chat history isn't being passed to the LLM. When the LLM responds and you ask a follow-up question the previous question/answer isn't passed to the model. Since my models support preserve thinking, make sure to pass previous thinking blocks as well."
+**Story:** n/a (TODO-derived)
+
+## Objective
+`POST /api/chat` accepts an optional `history` (the client's prior turns) and feeds it to the model on BOTH turn branches — the deflected path and the grounded agent — with prior thinking blocks preserved via the endpoint's existing `reasoning_content` wire convention; oversized histories are trimmed oldest-first by configurable caps.
+
+## Work
+1. `app/config.py` — two new `Settings` fields (existing docstring style, `BOR_`-overridable):
+   - `history_max_turns: int = 40` (`BOR_HISTORY_MAX_TURNS`) — newest history turns kept.
+   - `history_max_chars: int = 24000` (`BOR_HISTORY_MAX_CHARS`) — total kept history chars (text + thinking).
+2. `app/schemas.py` — next to `ChatRequest`:
+   - `class HistoryTurn(BaseModel)`: `who: Literal["user", "brain"]`, `text: str = Field(min_length=1, max_length=4000)`, `thinking: str | None = Field(default=None, max_length=32000)`.
+   - `ChatRequest.history: list[HistoryTurn] = Field(default_factory=list, max_length=100)` — schema-level hard ceiling (DoS sanity); the config budgets below do the real trimming.
+3. `app/rag/prompts.py` — new pure helper (unit-testable, no I/O):
+   ```python
+   def history_to_messages(history: Sequence[HistoryTurn], settings: Settings) -> list[dict[str, Any]]
+   ```
+   - Maps newest-first until BOTH budgets are hit (turn count ≤ `history_max_turns`; cumulative chars — `len(text) + len(thinking or "")` — ≤ `history_max_chars`), then returns the kept turns in chronological (oldest→newest) order.
+   - A budget-exceeding turn is DROPPED WHOLE — never cut mid-answer.
+   - `who="user"` → `{"role": "user", "content": text}`.
+   - `who="brain"` → `{"role": "assistant", "content": text}` plus `"reasoning_content": thinking` ONLY when `thinking` is non-empty (the preserve-thinking wire convention `app/rag/llm.py` already reads on the response side — `delta.reasoning_content`).
+4. `app/api/chat.py`:
+   - After `settings = get_settings()` in `stream()`: `hist = history_to_messages(request.history, settings)` (once per turn; the deflected recovery below reuses it via `messages`).
+   - Deflected branch: build `messages = [{"role": "system", "content": plan.system_prompt}, *hist, {"role": "user", "content": request.message}]` (replaces the two-entry list at ~L381). The phase-71 recovery already rebuilds from `messages[1:]` — unchanged.
+   - Grounded branch: pass `history=hist` into the `run_agent(...)` call (~L414).
+   - Per-turn log line (PLAN §9, the `logger.info` at ~L636): add `history_msgs={len(hist)}` to the existing line (append it near the other context-size fields, e.g. after `kb_chars`).
+5. `app/rag/agent.py` — `run_agent(..., history: Sequence[dict[str, Any]] = (), ...)`: build `messages = [{"role": "system", "content": system_prompt}, *history, {"role": "user", "content": user_message}]` (~L863). Everything downstream (tool rounds, phase-71 recovery rebuilding from `messages`, retry restarts) already operates on `messages` — unchanged.
+6. `app/rag/llm.py` — widen the message parameter type of `chat`, `chat_stream`, and `chat_stream_retried` from `list[dict[str, str]]` to `list[dict[str, Any]]` (an assistant message may now carry `reasoning_content`; the openai SDK passes message dicts through to the request body verbatim, so no transport change — string-only messages stay byte-identical on the wire).
+7. Tests:
+   - `tests/unit/` (extend the existing prompts/chat test files, e.g. `tests/unit/test_chat_gate.py` or a new `tests/unit/test_history.py`): `history_to_messages` — empty default → `[]`; user/brain mapping; `reasoning_content` present only when thinking non-empty; turn-cap trim (newest kept, oldest dropped whole); char-cap trim (text+thinking accounted, drop-whole semantics); chronological order of the result.
+   - `tests/unit/test_config.py`: the two new settings + `BOR_` env overrides (existing pattern).
+   - `tests/unit/test_agent.py`: `run_agent` with a non-empty `history` places it between system and the current user message (mock `LLMClient` capturing the sent messages); default `history=()` keeps the two-message request.
+   - `tests/integration/test_chat_api.py`: `POST /api/chat` with `history` — deflected turn (off-topic message) and grounded turn (on-topic message) both forward the prior turns to the mock LLM client (assert on the captured request messages, including `reasoning_content`); a request without `history` sends exactly `[system, user]` (byte-identical behavior pin); schema rejection: `who="alien"` → 422; `history` > 100 entries → 422; the per-turn log line carries `history_msgs=N` (caplog).
+   - - ASSUMPTION A2 (owner-confirmed 2026-09-08): `/api/chat` stays STATELESS per owner-locked A10 — the history is client-provided in the request body; the server stores nothing new (no `saved_chats`/`query_log` change beyond the log field).
+   - - ASSUMPTION A3 (owner-confirmed 2026-09-08): history is sent for BOTH grounded and deflected turns; caps = newest 40 turns / 24 000 chars (new `BOR_HISTORY_MAX_TURNS` / `BOR_HISTORY_MAX_CHARS`); a capped-out turn is dropped whole, never truncated.
+   - - ASSUMPTION A4 (owner-confirmed 2026-09-08): prior thinking travels as `reasoning_content` on the assistant message (the convention `app/rag/llm.py` already documents for the response side), only when non-empty — this is what makes the owner's preserve-thinking models keep the reasoning chain.
+
+## Testing & Quality
+- Unit/integration as listed in Work item 7 — every branch of the mapper and both API branches is covered.
+- Coverage: **>90%** on `app/` for this task's new/modified code (the mapper is pure — easy to pin).
+
+## Completion Criteria
+- [ ] `history_to_messages` unit tests green (mapping, `reasoning_content` gating, both budgets, drop-whole, ordering).
+- [ ] Integration: deflected AND grounded turns forward history to the mock LLM; no-`history` requests are unchanged; 422 pins; log line gains `history_msgs=N`.
+- [ ] `uv run pytest` green; `uv run pytest --cov=app --cov-report=term-missing` >90%; `uv run ruff check . && uv run pyright` clean.
+- [ ] No commit in this task (task 03 commits the phase) — but `uv run .agents/validate.sh`-equivalent gates must pass.

.agents/phases/complete/74_llm_chat_history/02_client_sends_history.md

@@ -0,0 +1,34 @@
+# Task 02 — Client: `runTurn` sends the conversation history (with thinking) in the request body
+
+**Phase:** `74_llm_chat_history` · **Source:** `TODO.md:4` — "Chat history isn't being passed to the LLM. When the LLM responds and you ask a follow-up question the previous question/answer isn't passed to the model. Since my models support preserve thinking, make sure to pass previous thinking blocks as well."
+**Story:** n/a (TODO-derived)
+
+## Objective
+The browser sends the prior conversation on every turn — user turns, brain answers, and the brain turns' `thinking` blocks — as the new `history` field of the `POST /api/chat` body, so follow-up questions are answered WITH the conversation the user has already seen.
+
+## Work
+1. `frontend/assets/app.js` — in `runTurn` (~L1859), the single funnel for ALL turns (fresh send, phase-49 retry via `runTurn(text, { reask: true })`, phase-53 stale-regen — verify the invariant while editing: in every one of those paths the question being sent is the LAST entry of `conversation` at fetch time — a fresh send just pushed it; `retryLastTurn` ~L1798 pops the old brain record and keeps the question as the last entry; `regenerateStaleChat` ~L1617 follows the same pop-then-reask pattern):
+   ```js
+   const history = conversation.slice(0, -1).map((m) => ({
+     who: m.who,
+     text: m.text,
+     thinking: m.who === "brain" ? m.thinking || undefined : undefined,
+   }));
+   ```
+   and send `body: JSON.stringify({ message: text, history })` in the existing `fetch("/api/chat", …)` (~L1905, replacing `{ message: text }`).
+   - `thinking` is only present on brain records that actually streamed one (phase-17+ optional key) — `undefined` drops the key from the JSON (the record's existing convention).
+   - Old/restored records without `thinking` send none — the server maps that to a plain assistant message.
+   - The current question itself is NEVER in `history` (the `slice(0, -1)`) — it is the request's `message`, exactly as the server expects.
+   - No UI change: nothing renders differently; the request body just carries the record the user already sees.
+2. - ASSUMPTION A5 (owner-confirmed 2026-09-08): stopped/partial brain turns (the `stopped: true` records) are included in the history like any other prior answer — the persisted record is the source of truth, and what the user saw is what the model should treat as the prior answer.
+3. Sanity check (no code): the server-side schema (task 01) accepts exactly `{who, text, thinking}` — no other record keys (`sources`, `tools`, `deflected`, `suggestions`) travel in the body; `tools` metadata is display-only and was never part of the LLM wire.
+
+## Testing & Quality
+- No JS unit-test infra in this repo — the wire-level pin is task 03's E2E (the mock sees the exact messages the client sent).
+- Manual smoke while running the dev server: DevTools → Network → the second `/api/chat` request's body carries the first Q/A pair (and `thinking` when the first turn streamed one).
+- `uv run pytest` stays green (frontend-only change).
+
+## Completion Criteria
+- [ ] Every `/api/chat` request carries `history` = the `conversation` record minus the current question, with `thinking` on brain turns that have it (verified in DevTools for a 2-turn conversation).
+- [ ] Retry (phase 49) and stale-regen (phase 53) send the correct history for their re-asked question (the popped/replaced answer is NOT in the history; the question is NOT duplicated).
+- [ ] No UI change; `uv run pytest` green; ruff + pyright clean.