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brain-of-reese/tests/unit/test_schemas.py
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phase: 164_chat_error_honesty
All gates green. Report:

- **Verified (phase 164, all 4 tasks already in `complete/`)**: `HistoryTurn`/`ChatMessage`/`ChatThinkingSegment` caps → 600 000, `history`/saved-messages lists → 500, new `SavedChatCreate/Update` total-8 000 000-char validator; exported `errorDetailText` at the two previously unguarded chat paths (pre-stream `!res.ok` + SSE `error` frame); `FAILED_REQUEST_TEXT` + `bubbleText` threading + phase-114 banner hint; dedicated E2E `tests/e2e/test_chat_error_honesty.py`.
- **Final-pass additions**: `tests/integration/test_chat_api.py::test_history_rejects_one_char_over_the_text_cap` (endpoint-level >600k → 422 with the pydantic list-of-objects `msg` — the criterion's upper half was only unit-pinned); README env rows for `BOR_APP_VERSION` + `BOR_SESSION_COOKIE`; restored `test_document_viewer.py`'s tracked screenshot artifact dirtied by the E2E run (via read-only `git show`, no index/history touched).
- **Tests/lint (exact commands)**: `uv run pytest --cov=app --cov-report=term-missing` → **3837 passed**, `app/` coverage **99%** (>90%); `uv run pytest tests/e2e/test_chat_error_honesty.py -v --no-cov` → **4 passed in isolation**; per-file loop over **all 148** E2E files (`uv run pytest tests/e2e/<f> -q --no-cov`) → **148 × exit 0**, incl. `test_failed_turn_retry`, `test_chat_save_payload_limits`, `test_edit_and_resend`, `test_llm_history`, `test_smoke`; `uv run ruff check .` → All checks passed; `uv run pyright` → 0 errors.
- **Completion criteria**: pre-stream 422 shows the distinct line + verbatim `msg`, `[object Object]` unrepresentable + no `input` in DOM — **met** (unit totality/source pins + E2E asserts 1–2); 525k history accepted (200 settles) / >600k → 422 / saved chat 201 + 8M bound — **met**; transport + SSE-frame settles keep `FAILED_TURN_TEXT`, stop/abort untouched, §7.4 re-enables — **met**; budget trim, `message` 4000, the 7 guarded detail-readers and all SSE shapes byte-identical (diff touches only caps + the two chat paths) — **met**; README/AGENTS full review + proxy deploy note — **met**; commit/`complete/` move = pipeline gate.
- **Docs**: README reviewed in full (env tables cross-checked programmatically: 74 `BOR_*` rows vs `Settings` defaults — no mismatches; every `.env.example` var documented; referenced scripts/pages/endpoints/`query_log` columns exist) — found & fixed the 2 undocumented real knobs above; the phase's payload-limits section, failed-turn copy and `client_max_body_size ≥ 16 MB` deploy note verified accurate. `AGENTS.md` verified consistent (rules, gitignore list, quick-reference commands, referenced paths all correct) — no changes needed.
- **Deviations**: `ChatThinkingSegment.text` raised 32 000 → 600 000 too (not itemized in A1, but its own docstring mirrors `HistoryTurn.thinking`; without it a long-thinking turn 422s its own auto-save — same mirror invariant). No live-infra changes made (the proxy limit lives in the separate deployment repo; README note only).
- **Next pending phase**: none — `164_chat_error_honesty` was the only entry in `todo/`.
2026-10-07 18:00:12 -04:00

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"""Unit: schema boundary caps for the saved-chat surface (phase 83, task 01).
The first schema-boundary suite: every A1 cap in ``app/schemas.py`` is
pinned at BOTH boundaries — a value exactly at the cap validates and one
past it raises a pydantic ``ValidationError`` naming the offending field
(the 422-shaped boundary response, house style, phase 56 precedent).
Plus the regression pin: a realistic ``bor.chat.v1`` payload validates
cleanly and round-trips ``model_dump()`` (the stored-shape contract —
the caps added value bounds only, no key/shape change).
Phase 164 (task 01, locked A1) re-cuts the long-answer chain —
``HistoryTurn.text``/``.thinking``, ``ChatMessage.text``/``.thinking``
and the thinking-segment cap to 600 000 (a FULL-cap answer at
``BOR_MAX_OUTPUT_TOKENS=131_072``, ≈ 524 300 chars), the history list
to 500 and the saved-messages list to 500, and adds the ONE new bound:
the ``SavedChatCreate``/``SavedChatUpdate`` total-character budget
(8 000 000) that keeps the anonymous SEC-05 surface bounded now that a
single message may hold a full-length answer. The chat-path caps are
pinned here too (``HistoryTurn`` + ``ChatRequest.history``) — same
boundaries as the saved-chat mirror, and the 422 ``detail`` SHAPE a cap
rejection produces is pinned as the server-side half of the phase-164
serializer contract (a LIST OF OBJECTS — the live ``[object Object]``
report).
"""
from __future__ import annotations
import pytest
from pydantic import ValidationError
from app.schemas import (
SAVED_CHAT_TOTAL_CHARS_BUDGET,
ChatMessage,
ChatRequest,
ChatSegment,
ChatThinkingSegment,
ChatToolSegment,
HistoryTurn,
SavedChatCreate,
SavedChatUpdate,
SourceRef,
ToolCall,
)
# --- boundary constants (phase 83, A1 — mirror sources in app/schemas.py) ---
#: Phase 164 (locked A1): 32 000 → 600 000. ONE constant for the whole
#: mirror — ``HistoryTurn.text``/``.thinking`` (the chat path),
#: ``ChatMessage.text``/``.thinking`` and the ``segments`` thinking
#: entry: the identical-boundary test IS the proof the phase-83 mirror
#: invariant survived the raise (raise one side and these pins fail).
#: 600 000 ≈ a full-cap answer at ``BOR_MAX_OUTPUT_TOKENS=131_072``
#: (≈ 524 300 chars at ~4 chars/token) with margin.
TEXT_CAP = 600_000
SOURCES_CAP = 20
SUGGESTIONS_CAP = 50
CHIP_CAP = 200
TOOLS_CAP = 50
SOURCE_CAP = 120 # documents.source String(120)
PATH_CAP = 1000 # documents.path String(1000)
TITLE_CAP = 500 # documents.title String(500)
NAME_CAP = 100 # ToolCall.name
ARGUMENT_CAP = 2000 # ToolCall.argument
MESSAGES_CAP = 500 # SavedChatCreate/Update.messages (phase 164: was 200)
HISTORY_CAP = 500 # ChatRequest.history (phase 164: was 100)
QUESTION_CAP = 4_000 # ChatRequest.message — the cap the composer mirrors (phase 104)
#: The phase-164 anonymous-surface bound, imported from the source (not
#: restated) so the schema and the suite cannot drift apart.
TOTAL_BUDGET = SAVED_CHAT_TOTAL_CHARS_BUDGET
#: A realistic full-cap answer length (131 072 output tokens at ~4
#: chars/token) — the payload the whole chain must now carry.
FULL_CAP_ANSWER = 524_300
def _source_ref() -> dict:
return {"source": "Homelab", "path": "kubernetes.md", "title": "K8s"}
def _tool_call() -> dict:
# Phase 95 (task 02): the truncation record rides the same entry —
# the CURRENT full shape (additive fields, defaults for a plain read).
# Phase 139 (task 02): the read's requested range joins the same
# entry (additive — None for a plain read, the phase-95 pattern).
return {
"name": "read",
"argument": "Homelab/kubernetes.md",
"truncated": False,
"chars_shown": None,
"chars_total": None,
"offset": None,
"limit": None,
}
def _user_message(text: str = "How did I install k3s?") -> ChatMessage:
return ChatMessage.model_validate({"who": "user", "text": text})
def _failed_loc(exc: ValidationError, *loc: object) -> None:
"""Assert the first ``ValidationError`` names exactly the given
field path (``loc`` tuple, e.g. ``("text",)`` or
``("messages", 0, "text")``) — the 422 must point at the offender."""
assert exc.errors()[0]["loc"] == tuple(loc), exc.errors()
# ---------------------------------------------------------------------------
# ChatMessage.text / .thinking
# ---------------------------------------------------------------------------
def test_chat_message_text_at_cap_validates() -> None:
msg = _user_message("a" * TEXT_CAP)
assert len(msg.text) == TEXT_CAP
def test_chat_message_text_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
_user_message("a" * (TEXT_CAP + 1))
_failed_loc(exc.value, "text")
def test_chat_message_thinking_at_cap_validates() -> None:
msg = ChatMessage.model_validate({"who": "brain", "text": "ok", "thinking": "t" * TEXT_CAP})
assert len(msg.thinking or "") == TEXT_CAP
def test_chat_message_thinking_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "thinking": "t" * (TEXT_CAP + 1)}
)
_failed_loc(exc.value, "thinking")
def test_chat_message_thinking_none_still_valid() -> None:
assert _user_message().thinking is None
assert ChatMessage.model_validate(
{"who": "brain", "text": "ok", "thinking": None}
).thinking is None
# ---------------------------------------------------------------------------
# ChatMessage.sources / .suggestions / .tools
# ---------------------------------------------------------------------------
def test_chat_message_sources_at_cap_validates() -> None:
msg = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "sources": [_source_ref() for _ in range(SOURCES_CAP)]}
)
assert len(msg.sources or []) == SOURCES_CAP
def test_chat_message_sources_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"sources": [_source_ref() for _ in range(SOURCES_CAP + 1)],
}
)
_failed_loc(exc.value, "sources")
def test_chat_message_suggestions_at_cap_validates() -> None:
msg = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "suggestions": [f"chip {i}" for i in range(SUGGESTIONS_CAP)]}
)
assert len(msg.suggestions or []) == SUGGESTIONS_CAP
def test_chat_message_suggestions_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"suggestions": [f"chip {i}" for i in range(SUGGESTIONS_CAP + 1)],
}
)
_failed_loc(exc.value, "suggestions")
def test_chat_message_suggestion_chip_at_cap_validates() -> None:
msg = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "suggestions": ["c" * CHIP_CAP]}
)
assert msg.suggestions is not None
assert len(msg.suggestions[0]) == CHIP_CAP
def test_chat_message_suggestion_chip_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "suggestions": ["c" * (CHIP_CAP + 1)]}
)
# the offender is the ITEM (the list itself is well under max_items).
_failed_loc(exc.value, "suggestions", 0)
def test_chat_message_tools_at_cap_validates() -> None:
msg = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "tools": [_tool_call() for _ in range(TOOLS_CAP)]}
)
assert len(msg.tools or []) == TOOLS_CAP
def test_chat_message_tools_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "tools": [_tool_call() for _ in range(TOOLS_CAP + 1)]}
)
_failed_loc(exc.value, "tools")
# ---------------------------------------------------------------------------
# ChatRequest.message (the 4,000-char question cap — phase 104, A3)
# ---------------------------------------------------------------------------
def test_chat_request_message_at_cap_validates() -> None:
"""EXACTLY 4,000 chars passes — the cap admits "a code example of a
few dozen lines" (owner A3) and the composer's maxlength + counter
mirror this exact boundary (the 4,000/4,000 E2E submit must not
422)."""
req = ChatRequest.model_validate({"message": "a" * QUESTION_CAP})
assert len(req.message) == QUESTION_CAP
def test_chat_request_message_one_over_cap_rejects() -> None:
"""4,001 chars is the 422 the UI now prevents blind: the server cap
stays the backstop (pre-existing, untouched — this phase only pins
it at the boundary, phase-83 pattern), naming ``message`` in the
error loc."""
with pytest.raises(ValidationError) as exc:
ChatRequest.model_validate({"message": "a" * (QUESTION_CAP + 1)})
_failed_loc(exc.value, "message")
# ---------------------------------------------------------------------------
# HistoryTurn + ChatRequest.history — the CHAT path of the long-answer
# chain (phase 164, task 01, locked A1). The live 422 this phase fixes:
# a >32k-char brain answer rode back as ``history`` on the NEXT turn and
# rejected it, so the follow-up of any long answer died with
# "[object Object]". Same boundaries as the saved-chat mirror above.
# ---------------------------------------------------------------------------
def test_history_turn_text_at_cap_validates() -> None:
"""600 000 chars — a full-cap answer (≈ 524 300 at
``BOR_MAX_OUTPUT_TOKENS=131_072``) flows back as ``history``:
the exact request shape the browser sends on the turn AFTER a long
answer."""
turn = HistoryTurn(who="brain", text="a" * TEXT_CAP)
assert len(turn.text) == TEXT_CAP
# And the realistic full-cap answer, not just the boundary value.
assert len(HistoryTurn(who="brain", text="a" * FULL_CAP_ANSWER).text) == FULL_CAP_ANSWER
def test_history_turn_text_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
HistoryTurn(who="brain", text="a" * (TEXT_CAP + 1))
_failed_loc(exc.value, "text")
def test_history_turn_thinking_at_cap_validates() -> None:
turn = HistoryTurn(who="brain", text="ok", thinking="t" * TEXT_CAP)
assert len(turn.thinking or "") == TEXT_CAP
def test_history_turn_thinking_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
HistoryTurn(who="brain", text="ok", thinking="t" * (TEXT_CAP + 1))
_failed_loc(exc.value, "thinking")
def test_history_turn_caps_match_the_saved_chat_mirror() -> None:
"""The phase-83 mirror invariant, verified by identical boundaries
(not by comment): a payload at the cap validates on BOTH models and
one past it fails on BOTH — ``HistoryTurn`` (the chat path) and
``ChatMessage`` (the saved-chat path). Raise one side in
``app/schemas.py`` and this pin fails."""
for length, rejected in ((TEXT_CAP, False), (TEXT_CAP + 1, True)):
payload = {"who": "brain", "text": "a" * length, "thinking": "t" * length}
for model in (HistoryTurn, ChatMessage):
if rejected:
with pytest.raises(ValidationError):
model.model_validate(payload)
else:
model.model_validate(payload)
def test_chat_request_history_at_cap_validates() -> None:
"""500 turns pass — the client sends the WHOLE ``bor.chat.v1``
record minus the current question, so the ceiling is a DoS sanity
bound only (the config budgets trim for real, locked A4)."""
req = ChatRequest.model_validate(
{"message": "hi", "history": [{"who": "user", "text": f"q{i}"} for i in range(HISTORY_CAP)]}
)
assert len(req.history) == HISTORY_CAP
def test_chat_request_history_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ChatRequest.model_validate(
{
"message": "hi",
"history": [
{"who": "user", "text": f"q{i}"} for i in range(HISTORY_CAP + 1)
],
}
)
_failed_loc(exc.value, "history")
def test_cap_rejection_detail_is_a_list_of_objects() -> None:
"""The server-side half of the phase-164 contract (task 02's input):
a cap rejection is the pydantic 422 ``detail`` — a LIST OF OBJECTS
(``loc``/``msg``/``type``), never a plain string. This is exactly the
shape the client turned into ``[object Object]``; the serializer must
read ``msg`` and never the ``input`` (which carries the whole
conversation)."""
with pytest.raises(ValidationError) as exc:
HistoryTurn(who="brain", text="a" * (TEXT_CAP + 1))
detail = exc.value.errors()
assert isinstance(detail, list) and len(detail) == 1
(entry,) = detail
assert entry["loc"] == ("text",)
assert entry["type"] == "string_too_long"
# The message the UI shows verbatim in the failed-turn note.
assert entry["msg"] == f"String should have at most {TEXT_CAP} characters"
# The raw input DOES ride the error object server-side — which is why
# the client serializer only ever reads ``msg``.
assert entry["input"].startswith("aaaa")
# ---------------------------------------------------------------------------
# SourceRef (documents column-length mirrors)
# ---------------------------------------------------------------------------
def test_source_ref_source_at_cap_validates() -> None:
ref = SourceRef.model_validate(
{"source": "s" * SOURCE_CAP, "path": "a.md", "title": "A"}
)
assert len(ref.source) == SOURCE_CAP
def test_source_ref_source_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
SourceRef.model_validate({"source": "s" * (SOURCE_CAP + 1), "path": "a.md", "title": "A"})
_failed_loc(exc.value, "source")
def test_source_ref_path_at_cap_validates() -> None:
ref = SourceRef.model_validate(
{"source": "Homelab", "path": "p" * PATH_CAP, "title": "A"}
)
assert len(ref.path) == PATH_CAP
def test_source_ref_path_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
SourceRef.model_validate(
{"source": "Homelab", "path": "p" * (PATH_CAP + 1), "title": "A"}
)
_failed_loc(exc.value, "path")
def test_source_ref_title_at_cap_validates() -> None:
ref = SourceRef.model_validate(
{"source": "Homelab", "path": "a.md", "title": "t" * TITLE_CAP}
)
assert len(ref.title) == TITLE_CAP
def test_source_ref_title_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
SourceRef.model_validate(
{"source": "Homelab", "path": "a.md", "title": "t" * (TITLE_CAP + 1)}
)
_failed_loc(exc.value, "title")
# ---------------------------------------------------------------------------
# ToolCall
# ---------------------------------------------------------------------------
def test_tool_call_name_at_cap_validates() -> None:
call = ToolCall.model_validate({"name": "n" * NAME_CAP, "argument": None})
assert len(call.name) == NAME_CAP
def test_tool_call_name_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ToolCall.model_validate({"name": "n" * (NAME_CAP + 1), "argument": None})
_failed_loc(exc.value, "name")
def test_tool_call_argument_at_cap_validates() -> None:
call = ToolCall.model_validate({"name": "read", "argument": "a" * ARGUMENT_CAP})
assert len(call.argument or "") == ARGUMENT_CAP
def test_tool_call_argument_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
ToolCall.model_validate({"name": "read", "argument": "a" * (ARGUMENT_CAP + 1)})
_failed_loc(exc.value, "argument")
def test_tool_call_argument_none_still_valid() -> None:
assert ToolCall.model_validate({"name": "ls", "argument": None}).argument is None
assert ToolCall.model_validate({"name": "ls"}).argument is None
# ---------------------------------------------------------------------------
# SavedChatCreate / SavedChatUpdate .messages
# ---------------------------------------------------------------------------
def _minimal_messages(n: int) -> list[dict]:
return [{"who": "user" if i % 2 == 0 else "brain", "text": f"m{i}"} for i in range(n)]
def test_saved_chat_create_messages_at_cap_validates() -> None:
payload = SavedChatCreate.model_validate(
{"title": "big", "messages": _minimal_messages(MESSAGES_CAP)}
)
assert len(payload.messages) == MESSAGES_CAP
def test_saved_chat_create_messages_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
SavedChatCreate.model_validate(
{"title": "bigger", "messages": _minimal_messages(MESSAGES_CAP + 1)}
)
_failed_loc(exc.value, "messages")
def test_saved_chat_update_messages_at_cap_validates() -> None:
payload = SavedChatUpdate.model_validate({"messages": _minimal_messages(MESSAGES_CAP)})
assert len(payload.messages) == MESSAGES_CAP
def test_saved_chat_update_messages_one_over_cap_rejects() -> None:
with pytest.raises(ValidationError) as exc:
SavedChatUpdate.model_validate({"messages": _minimal_messages(MESSAGES_CAP + 1)})
_failed_loc(exc.value, "messages")
# ---------------------------------------------------------------------------
# The phase-164 total-character budget (locked A1) — the ONE new bound on
# the anonymous saved-chat surface. The per-message caps went to 600 000,
# so the LIST is bounded by total characters instead of by an item count
# that a full-cap answer would blow through: 8 000 000 keeps the worst
# case at the order the phase-83 SEC-05 audit accepted (200 × 64k
# ≈ 12.8 MB) while fitting ~15 full-cap answers.
# ---------------------------------------------------------------------------
def _full_cap_messages(count: int, *, size: int = FULL_CAP_ANSWER) -> list[dict]:
"""``count`` brain answers at the realistic full-cap length."""
return [{"who": "brain", "text": "a" * size} for _ in range(count)]
def test_saved_chat_within_total_budget_of_full_cap_answers_validates() -> None:
"""~15 full-cap answers (15 × 524 300 = 7 864 500 chars, the biggest
whole-count fit under 8 000 000) validate — the budget is a sanity
bound, not a practical limit on a real conversation."""
fits = TOTAL_BUDGET // FULL_CAP_ANSWER
assert fits == 15
payload = SavedChatCreate.model_validate({"messages": _full_cap_messages(fits)})
assert len(payload.messages) == fits
def test_saved_chat_over_total_budget_rejects_with_the_budget_message() -> None:
"""One full-cap answer past the fit → ValidationError whose ``msg``
NAMES the budget (the 422 the anonymous caller sees), on BOTH the
create and the update model — the same validator on both bodies."""
over = _full_cap_messages(TOTAL_BUDGET // FULL_CAP_ANSWER + 1)
for model in (SavedChatCreate, SavedChatUpdate):
with pytest.raises(ValidationError) as exc:
model.model_validate({"messages": over})
(error,) = exc.value.errors()
assert error["loc"] == () # a model-level validator, not a field
assert "8,000,000-character budget" in error["msg"]
def test_saved_chat_one_full_cap_answer_plus_normal_turns_validates() -> None:
"""The realistic case the live report blocked: a saved chat carrying
ONE 525k-char brain answer alongside ordinary turns."""
payload = SavedChatCreate.model_validate(
{
"messages": [
{"who": "user", "text": "Write me the whole runbook."},
{"who": "brain", "text": "a" * 525_000},
{"who": "user", "text": "And the rollback?"},
{"who": "brain", "text": "Short rollback."},
]
}
)
assert len(payload.messages) == 4
def test_saved_chat_total_budget_counts_thinking() -> None:
"""``thinking`` counts against the budget exactly like ``text`` (the
history budget's own accounting, mirrored): 15 turns of 280 000 text
+ 280 000 thinking = 8 400 000 REJECTS even though the text alone is
only 4 200 000 — a text-only accounting would have waved it
through."""
turns = 15
size = 280_000
assert turns * size <= TOTAL_BUDGET < turns * (size * 2)
heavy = [
{"who": "brain", "text": "a" * size, "thinking": "t" * size}
for _ in range(turns)
]
with pytest.raises(ValidationError) as exc:
SavedChatCreate.model_validate({"messages": heavy})
assert "8,000,000-character budget" in exc.value.errors()[0]["msg"]
# One turn fewer fits (14 × 560 000 = 7 840 000).
assert len(SavedChatCreate.model_validate({"messages": heavy[:-1]}).messages) == 14
def test_saved_chat_at_exactly_the_total_budget_validates() -> None:
"""The boundary is INCLUSIVE: exactly 8 000 000 characters across the
messages passes (13 at the 600 000 cap + one of 200 000), one
character more rejects."""
def _conversation(last_size: int) -> list[dict]:
return [{"who": "brain", "text": "a" * TEXT_CAP} for _ in range(13)] + [
{"who": "brain", "text": "b" * last_size}
]
at = SavedChatCreate.model_validate({"messages": _conversation(200_000)})
assert sum(len(m.text) for m in at.messages) == TOTAL_BUDGET
with pytest.raises(ValidationError) as exc:
SavedChatCreate.model_validate({"messages": _conversation(200_001)})
assert "8,000,000-character budget" in exc.value.errors()[0]["msg"]
# ---------------------------------------------------------------------------
# JSON-shape regression: same KEYS as before, value bounds only
# ---------------------------------------------------------------------------
def test_extra_keys_still_forbidden() -> None:
"""``extra="forbid"`` is untouched — a stray key is still a 422-shaped
rejection (the accepted/rejected KEYS did not change with phase 83)."""
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate({"who": "user", "text": "hi", "html": "<b>x</b>"})
_failed_loc(exc.value, "html")
def test_minimal_message_still_validates() -> None:
"""Optional keys may be ABSENT exactly as pre-phase-83."""
msg = ChatMessage.model_validate({"who": "user", "text": "hi"})
assert (
msg.sources,
msg.related,
msg.deflected,
msg.suggestions,
msg.thinking,
msg.tools,
msg.stopped,
msg.failed,
msg.error,
) == (
None,
None,
None,
None,
None,
None,
None,
None,
None,
)
# ---------------------------------------------------------------------------
# Realistic-payload round-trip (the stored-shape contract)
# ---------------------------------------------------------------------------
def test_realistic_bor_chat_v1_payload_round_trips() -> None:
"""A full ``bor.chat.v1``-shaped record (4–8 messages mixing
user/brain, one brain message with ``thinking`` + ``tools`` +
``sources``, one with ``suggestions`` + ``stopped``) validates
cleanly and ``model_dump()`` of the messages equals the input dict —
``None``-keys preserved (the phase-50/51 byte-identical stored shape;
the caps added value bounds only, no key/shape change)."""
messages: list[dict] = [
{
"who": "user",
"text": "How did I install k3s on the new node?",
"sources": None,
"related": None,
"deflected": None,
"suggestions": None,
"thinking": None,
"tools": None,
"stopped": None,
"failed": None,
"error": None,
"budget_exhausted": None,
},
{
"who": "brain",
"text": "Your k3s cluster runs on three nodes — here's how it happened.",
"sources": [
{"source": "Homelab", "path": "kubernetes.md", "title": "Kubernetes Cluster"},
{"source": "Deployments", "path": "k3s-install.md", "title": "k3s Install Notes"},
],
# Phase 113 related-doc tier — an ACCEPTED key (the phase-113
# omission of this field made extra="forbid" 422 every
# done-time auto-save carrying it, so grounded turns' brain
# messages never persisted — the A2 quiet failure swallowed
# the 422). Round-trips like sources.
"related": [
{"source": "Homelab", "path": "traefik.md", "title": "Traefik Notes"}
],
"deflected": False,
"suggestions": None,
"thinking": "The kubernetes doc covers the cluster layout…",
"tools": [
# Phase 95 (task 02): the current full shape — one
# truncated read (the marker record) + a plain ls.
# Phase 139 (task 02): the truncated read is a RANGE
# read — the requested offset/limit ride the same entry
# so a save → restore re-renders the "(lines 42–71)"
# suffix; the ls carries no range (None, as serialized).
{
"name": "read",
"argument": "Homelab/kubernetes.md",
"truncated": True,
"chars_shown": 128_000,
"chars_total": 204_000,
"offset": 42,
"limit": 30,
},
{
"name": "ls",
"argument": None,
"truncated": False,
"chars_shown": None,
"chars_total": None,
"offset": None,
"limit": None,
},
],
"stopped": None,
"failed": None,
"error": None,
"budget_exhausted": None,
},
{
"who": "user",
"text": "And what ports does Traefik expose?",
"sources": None,
"related": None,
"deflected": None,
"suggestions": None,
"thinking": None,
"tools": None,
"stopped": None,
"failed": None,
"error": None,
"budget_exhausted": None,
},
{
"who": "brain",
"text": "Traefik exposes 80/443 on every node.",
"sources": None,
"related": None,
"deflected": None,
"suggestions": ["What is the Traefik dashboard password?"],
"thinking": None,
"tools": None,
"stopped": True, # the owner stopped the generation mid-answer
"failed": None,
"error": None,
"budget_exhausted": None,
},
]
payload = SavedChatCreate.model_validate({"title": "k3s install", "messages": messages})
dumped = payload.model_dump()
# the stored shape is byte-identical: every message dict — None-keys
# and all — round-trips unchanged (and the top-level record keeps its
# ``share`` default). The phase-160 additive ``budget_exhausted``
# marker joins as an explicit null (the phase-120 ``failed`` /
# phase-48 ``stopped`` style — ``None`` flows as null, the
# phase-50 byte-identical contract covers the new key).
assert dumped["messages"] == messages
assert dumped["share"] is False
def test_realistic_payload_round_trips_through_update_model() -> None:
"""Same record re-Saved through ``SavedChatUpdate`` (the re-Save
upsert surface) — identical stored shape."""
msg = {
"who": "brain",
"text": "answer",
"sources": [_source_ref()],
"related": None,
"deflected": None,
"suggestions": ["follow-up?"],
"thinking": "scratchpad",
"tools": [_tool_call()],
"stopped": None,
"failed": None,
"error": None,
"budget_exhausted": None,
}
payload = SavedChatUpdate.model_validate({"messages": [msg]})
# Identical stored shape (the phase-160 additive ``budget_exhausted``
# marker rides as an explicit null — the phase-120/48 style).
assert payload.model_dump()["messages"] == [msg]
# ---------------------------------------------------------------------------
# Phase 95 (task 02): ToolCall truncation fields + ChatToolResultEvent
# ---------------------------------------------------------------------------
def test_tool_call_round_trips_with_truncation_fields() -> None:
"""The CURRENT full shape (phase 95 task 02 + phase 139 task 02):
a truncated read's record (``truncated: True`` + the two non-negative
counts + the additive range fields, absent for a plain read) validates
and round-trips ``model_dump()`` unchanged — the save payload carries
it with zero other change (the UI re-renders the marker — and, for a
range read, the "(lines N–M)" suffix — from it)."""
raw = {
"name": "read",
"argument": "Homelab/big.md",
"truncated": True,
"chars_shown": 128_000,
"chars_total": 204_000,
"offset": None,
"limit": None,
}
call = ToolCall.model_validate(raw)
assert call.truncated is True
assert call.chars_shown == 128_000
assert call.chars_total == 204_000
assert call.offset is None and call.limit is None
assert call.model_dump() == raw
def test_tool_call_range_fields_round_trip() -> None:
"""Phase 139 (task 02): a RANGE read's record (``offset`` +
``limit``, the phase-131 wire fields) validates and round-trips
``model_dump()`` unchanged — the saved chat's ``tools`` JSONB keeps
the range, so the chat page's restore path and the shared page
re-render the "(lines N–M)" suffix from the stored row. Only ONE of
the two is also a real shape (the model may pass a start without a
count — the UI's "(from line N)" line)."""
both = ToolCall.model_validate(
{"name": "read", "argument": "Homelab/big.md", "offset": 42, "limit": 30}
)
assert (both.offset, both.limit) == (42, 30)
assert both.model_dump() == {
"name": "read",
"argument": "Homelab/big.md",
"truncated": False,
"chars_shown": None,
"chars_total": None,
"offset": 42,
"limit": 30,
}
offset_only = ToolCall.model_validate(
{"name": "read", "argument": "Homelab/big.md", "offset": 7}
)
assert (offset_only.offset, offset_only.limit) == (7, None)
limit_only = ToolCall.model_validate(
{"name": "read", "argument": "Homelab/big.md", "limit": 20}
)
assert (limit_only.offset, limit_only.limit) == (None, 20)
def test_tool_call_range_fields_reject_zero_or_negative() -> None:
"""Phase 139 (task 02) bounds (the phase-83 philosophy, the UI's
guard mirrored): a line number is >= 1 (the server's
``_whole_line_number`` bound — 0 / negative are not real ranges, and
the UI never legitimately sends them; the bool exclusion lives on
the SSE-side guard, where frames are minted)."""
for bad_offset, bad_limit in ((0, None), (None, 0), (-3, None), (None, -1)):
with pytest.raises(ValidationError):
ToolCall.model_validate(
{
"name": "read",
"argument": "x",
"offset": bad_offset,
"limit": bad_limit,
}
)
def test_tool_call_old_shape_validates_with_defaults() -> None:
"""Backward-compat (the phase-50 rule): a saved chat written BEFORE
phase 95 — tool records without the truncation fields — validates
UNCHANGED: ``truncated`` defaults to False (the marker is absent),
the counts to None. No migration (``ChatMessage.tools`` is JSON);
only the dump gains the additive keys with their defaults."""
old_shape = {"name": "read", "argument": "Homelab/kubernetes.md"}
call = ToolCall.model_validate(old_shape)
assert call.truncated is False
assert call.chars_shown is None
assert call.chars_total is None
dumped = call.model_dump()
assert dumped["name"] == "read" and dumped["argument"] == "Homelab/kubernetes.md"
assert dumped["truncated"] is False
assert dumped["chars_shown"] is None and dumped["chars_total"] is None
def test_tool_call_old_shape_message_still_round_trips_as_record() -> None:
"""The record-level backward-compat: a pre-phase-95 brain message
(old-shape ``tools``) validates inside ``ChatMessage`` and dumps back
as a VALID record of the same shape (the frontend renders it without
the marker — ``truncated`` falsy)."""
old_message = {
"who": "brain",
"text": "You've got this!",
"sources": None,
"deflected": False,
"suggestions": None,
"thinking": None,
"tools": [
{"name": "read", "argument": "Homelab/kubernetes.md"},
{"name": "read_document", "argument": "Homelab/legacy.md"},
],
"stopped": None,
}
msg = ChatMessage.model_validate(old_message)
assert all(t.truncated is False for t in (msg.tools or []))
# Re-validating the dump is a no-op (lossless record round-trip).
ChatMessage.model_validate(msg.model_dump())
def test_tool_call_counts_reject_negative() -> None:
"""Phase 83 bounds philosophy: the counts are non-negative
(``ge=0``) — a negative count is not a real record."""
with pytest.raises(ValidationError):
ToolCall.model_validate(
{
"name": "read",
"argument": "x",
"truncated": True,
"chars_shown": -1,
"chars_total": 5,
}
)
with pytest.raises(ValidationError):
ToolCall.model_validate(
{
"name": "read",
"argument": "x",
"truncated": True,
"chars_shown": 5,
"chars_total": -1,
}
)
def test_chat_tool_result_event_shape() -> None:
"""The A15 extension's wire shape (phase 95 task 02): the seventh,
OPTIONAL SSE event type — ``{type, name, argument, truncated,
chars_shown, chars_total}`` — with the pinned field order, the
``tool_result`` default, ``truncated`` defaulting True (the emission
trigger), and the non-negative counts."""
from app.schemas import ChatToolResultEvent
ev = ChatToolResultEvent(
name="read",
argument="docs/big.md",
truncated=True,
chars_shown=128_000,
chars_total=204_000,
)
dumped = ev.model_dump()
assert list(dumped) == [
"type",
"name",
"argument",
"truncated",
"chars_shown",
"chars_total",
]
assert dumped == {
"type": "tool_result",
"name": "read",
"argument": "docs/big.md",
"truncated": True,
"chars_shown": 128_000,
"chars_total": 204_000,
}
# The emission trigger defaults: the pump always builds the frame from
# a piece, so a frame that ever exists carries the truncation truth.
minimal = ChatToolResultEvent(
name="read", argument=None, chars_shown=0, chars_total=0
).model_dump()
assert minimal["truncated"] is True
def test_chat_tool_result_event_counts_reject_negative() -> None:
"""The frame's counts are non-negative (``ge=0``), like the record's."""
from app.schemas import ChatToolResultEvent
with pytest.raises(ValidationError):
ChatToolResultEvent(name="read", argument="x", chars_shown=-1, chars_total=5)
with pytest.raises(ValidationError):
ChatToolResultEvent(name="read", argument="x", chars_shown=5, chars_total=-1)
# ---------------------------------------------------------------------------
# Phase 158 (task 01): the ChatMessage.segments field — the turn's
# chronological run order (D4/D6, owner direction 2026-10-04): the
# discriminated thinking/tool union (ChatSegment), capped phase-83-style
# (mirrored, not weakened — ToolCall is the shape source), OMITTED when
# absent (the phase-50 byte-identical round-trip contract — ABSENT,
# never null), the extra="forbid" boundary intact around the new key.
# ---------------------------------------------------------------------------
def test_segments_absent_by_default_and_omitted_in_dump() -> None:
"""A record WITHOUT ``segments`` (every pre-phase shape, every
no-thinking/no-tools turn) validates with ``None`` and dumps
WITHOUT the key — ABSENT, never ``null`` (the phase-50 round-trip
contract; the wrap serializer does the dropping on every surface).
The dump stays byte-identical to the pre-phase shape."""
msg = ChatMessage.model_validate({"who": "brain", "text": "ok"})
assert msg.segments is None
dumped = msg.model_dump()
assert "segments" not in dumped
# Byte-identical to the pre-phase stored shape: every bor.chat.v1
# optional key present (null) — the phase-160 additive
# ``budget_exhausted`` marker included (the phase-120 ``failed`` /
# phase-48 ``stopped`` style — explicit null where absent) — and
# the three serializer-popped keys (image / answer_image /
# segments) absent.
assert dumped == {
"who": "brain",
"text": "ok",
"sources": None,
"related": None,
"deflected": None,
"suggestions": None,
"thinking": None,
"tools": None,
"stopped": None,
"failed": None,
"error": None,
"budget_exhausted": None,
}
# An explicit empty list is a different thing: [] is a value, so it
# round-trips as [] (present, empty — the pop is None-gated only).
empty = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": []}
).model_dump()
assert empty["segments"] == []
def test_segments_thinking_entry_round_trips_and_caps() -> None:
"""The thinking entry: ``min_length=1`` (the zero-char run the
client never stores) + ``max_length=600_000`` (HistoryTurn's cap,
phase 83) — at the cap validates, one past raises naming the
offender; a missing ``text`` too."""
at_cap = ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"segments": [{"kind": "thinking", "text": "t" * TEXT_CAP}],
}
)
assert at_cap.segments == [
ChatThinkingSegment(kind="thinking", text="t" * TEXT_CAP)
]
assert at_cap.model_dump()["segments"] == [
{"kind": "thinking", "text": "t" * TEXT_CAP}
]
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"segments": [{"kind": "thinking", "text": "t" * (TEXT_CAP + 1)}],
}
)
# Pydantic 2.13 names the union variant in the loc — the 422 still
# points at the offender (segments[0].text).
_failed_loc(exc.value, "segments", 0, "thinking", "text")
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": [{"kind": "thinking", "text": ""}]}
)
_failed_loc(exc.value, "segments", 0, "thinking", "text")
with pytest.raises(ValidationError):
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": [{"kind": "thinking"}]}
)
def test_segments_tool_entry_mirrors_toolcall_shape() -> None:
"""The tool entry is the EXACT ToolCall field set (mirrored, not
weakened — phase-37 pair + phase-95 truncation stamp + phase-139
range + phase-146 scoped path): a full entry round-trips
byte-for-byte; a NON-scoped entry dumps WITHOUT ``path`` (ABSENT,
never ``null`` — the ToolCall omission rule mirrored, so a
``segments`` entry and the matching ``tools`` entry of the same
record stay the same data); a scoped one keeps it."""
full = {
"kind": "tool",
"name": "read",
"argument": "Homelab/kubernetes.md",
"truncated": True,
"chars_shown": 128_000,
"chars_total": 204_000,
"offset": 42,
"limit": 30,
"path": "search_docs/reese-notes.md",
}
msg = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": [full]}
)
assert msg.model_dump()["segments"] == [full]
# Round-trip: the dump re-validates and dumps back to itself.
again = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": msg.model_dump()["segments"]}
)
assert again.model_dump() == msg.model_dump()
unscoped = {
"kind": "tool",
"name": "ls",
"argument": None,
"truncated": False,
"chars_shown": None,
"chars_total": None,
"offset": None,
"limit": None,
}
dumped = ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": [unscoped]}
).model_dump()["segments"][0]
assert "path" not in dumped # ABSENT, never null
assert dumped == {
"kind": "tool",
"name": "ls",
"argument": None,
"truncated": False,
"chars_shown": None,
"chars_total": None,
"offset": None,
"limit": None,
}
def test_segments_caps_mirrored_not_weakened() -> None:
"""The ToolCall caps bind on the segment (mirrored, not
weakened): ``name`` ≤ 100, ``argument`` ≤ 2 000, ``path`` ≤ 2 000,
``offset``/``limit`` ≥ 1, the list ≤ 50 (the phase-83 voice — the
``tools`` cap)."""
bad: list[dict] = [
{"kind": "tool", "name": "n" * (NAME_CAP + 1), "argument": None},
{"kind": "tool", "name": "grep", "argument": "a" * (ARGUMENT_CAP + 1)},
{"kind": "tool", "name": "grep", "argument": "x", "path": "p" * (ARGUMENT_CAP + 1)},
{"kind": "tool", "name": "read", "offset": 0},
{"kind": "tool", "name": "read", "limit": 0},
{"kind": "tool", "name": "read", "chars_shown": -1},
]
for entry in bad:
with pytest.raises(ValidationError):
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": [entry]}
)
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"segments": [{"kind": "thinking", "text": "x"}] * (TOOLS_CAP + 1),
}
)
_failed_loc(exc.value, "segments")
def test_unknown_segment_kind_rejected() -> None:
"""The discriminator (``kind`` = ``"thinking"`` | ``"tool"``): an
unknown ``kind`` is a ValidationError naming the offending entry —
nothing outside the union crosses the boundary."""
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"segments": [{"kind": "bogus", "text": "x"}],
}
)
assert exc.value.errors()[0]["loc"][:2] == ("segments", 0), exc.value.errors()
# A thinking variant without its ``text`` and a tool variant without
# its ``name`` are both rejected (the required fields are real).
with pytest.raises(ValidationError):
ChatMessage.model_validate(
{"who": "brain", "text": "ok", "segments": [{"kind": "tool"}]}
)
def test_extra_top_level_key_still_forbidden_with_segments() -> None:
"""The ``extra="forbid"`` boundary is INTACT around the new key:
a record with a well-formed ``segments`` AND a stray top-level key
is still rejected — adding the field changed nothing about which
keys are accepted (the phase-83 voice)."""
with pytest.raises(ValidationError) as exc:
ChatMessage.model_validate(
{
"who": "brain",
"text": "ok",
"html": "<b>x</b>",
"segments": [{"kind": "thinking", "text": "x"}],
}
)
_failed_loc(exc.value, "html")
def test_segments_alias_is_the_discriminated_union() -> None:
"""``ChatSegment`` is the Annotated discriminated alias (the
``_Chip`` precedent, phase 83): the JSON shape is a flat object —
the discriminator rides as a field, no wrapper."""
from pydantic import TypeAdapter
adapter = TypeAdapter(ChatSegment)
thinking = adapter.validate_python({"kind": "thinking", "text": "x"})
assert isinstance(thinking, ChatThinkingSegment)
tool = adapter.validate_python({"kind": "tool", "name": "ls"})
assert isinstance(tool, ChatToolSegment)