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.

app/schemas.py

@@ -26,9 +26,50 @@ class SuggestionList(BaseModel):
     suggestions: list[str]
 
 
-class ChatRequest(BaseModel):
-    message: str = Field(min_length=1, max_length=4000)
+class HistoryTurn(BaseModel):
+    """One prior chat turn the client sends with ``POST /api/chat``
+    (phase 74, TODO L4).
 
+    The endpoint stays stateless (A10): the client's ``bor.chat.v1``
+    conversation record (minus the question about to be asked) is
+    provided in the request body as ``history`` so a follow-up question
+    reaches the model together with the exchange so far — and, for
+    preserve-thinking models, with the prior brain turns' thinking (the
+    record has carried the ``thinking`` key since phase 17).
+
+    ``thinking`` travels to the model as ``reasoning_content`` on the
+    assistant message (the wire convention :mod:`app.rag.llm` already
+    documents for the response side) — only when non-empty (A4).
+    ``text`` mirrors :attr:`ChatMessage.text`'s answer shape; the
+    thinking cap is looser (scratchpads run longer than answers). These
+    are boundary sanity caps only — the real trimming budget is the
+    settings pair ``history_max_turns`` / ``history_max_chars``
+    (``app.config``, A3: a capped-out turn is dropped whole, never
+    truncated).
+    """
+
+    who: Literal["user", "brain"]
+    text: str = Field(min_length=1, max_length=4000)
+    thinking: str | None = Field(default=None, max_length=32000)
+
+
+class ChatRequest(BaseModel):
+    """``POST /api/chat`` body: the current question plus the optional
+    prior turns (phase 74 — the client-provided history, stateless per
+    A10).
+
+    ``history`` is the client's earlier turns, oldest first (the
+    ``bor.chat.v1`` record minus the current question); the mapper
+    (:func:`app.rag.prompts.history_to_messages`) trims it newest-first
+    against the settings budgets and maps it to model messages. The
+    schema-level ``max_length=100`` is a DoS sanity ceiling only — the
+    config budgets do the real trimming (A3). Absent or empty keeps the
+    request byte-identical to pre-phase-74: the model sees exactly the
+    two-message ``[system, user]`` request.
+    """
+
+    message: str = Field(min_length=1, max_length=4000)
+    history: list[HistoryTurn] = Field(default_factory=list, max_length=100)
 
 class LoginRequest(BaseModel):
     """``POST /api/login`` body (phase 16): the single admin's password.