claude-agent-service/tests/test_conversational.py
Viktor Barzin eccf0dd407
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conversational: trim per-turn context to cut brain TTFT ~1.3s
The no-tools conversational agent was dragging the full project context (this
repo's CLAUDE.md, the MCP server configs, local settings) plus the dynamic
system-prompt sections into every voice turn — ~45k input tokens -> ~3.4s
time-to-first-token (measured against the live pod, 2026-06-21).

Add --setting-sources user + --exclude-dynamic-system-prompt-sections to both
the gateway (json) and realtime (stream-json) conversational argvs: context
drops to ~23k and TTFT to ~2.1s (~1.3s/turn faster) with no change to the
reply. Helps the portal-assistant v1 gateway AND the v2 realtime agent (both
run the same turn). The /execute agent path is untouched.

Investigation ruled out the assumed culprits: CLI startup is only ~0.5s, and a
warm prompt cache does NOT lower TTFT (turn 2 read all 45k from cache yet TTFT
was unchanged) — the cost was the context size, not the spawn.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-21 18:00:21 +00:00

256 lines
9.8 KiB
Python

"""Tests for the conversational (no-tools, multi-turn) brain endpoint.
This is the portal-assistant "Brain": a lean path that drives the Claude CLI with
a no-tools conversational agent and per-conversation `--resume`, used by the voice
gateway. Unlike /v1/chat/completions it does NOT clone a workspace or run a
tool-enabled agent (see portal-assistant ADR-0002).
"""
import json
from unittest.mock import AsyncMock, patch
import pytest
from httpx import ASGITransport, AsyncClient
from app import conversational
from app.main import app
# --------------------------------------------------------------------------- #
# argv builder
# --------------------------------------------------------------------------- #
def test_conversational_argv_new_session():
argv = conversational_argv_call(resume=False)
assert argv[0] == "claude"
assert "-p" in argv
assert argv[argv.index("--agent") + 1] == "conversational"
# a new conversation opens with --session-id, never --resume
assert argv[argv.index("--session-id") + 1] == "sess-1"
assert "--resume" not in argv
# SECURITY: a public-facing endpoint must NOT skip tool permissions
assert "--dangerously-skip-permissions" not in argv
assert argv[argv.index("--model") + 1] == "sonnet"
assert argv[argv.index("--output-format") + 1] == "json"
# latency: trims project CLAUDE.md/MCP + dynamic system-prompt sections off
# the no-tools voice turn (~45k -> ~23k input tokens, ~1.3s faster TTFT)
assert argv[argv.index("--setting-sources") + 1] == "user"
assert "--exclude-dynamic-system-prompt-sections" in argv
assert argv[-1] == "Hi there"
def test_conversational_argv_resume_continues_session():
argv = conversational_argv_call(resume=True)
# a follow-up turn resumes the existing claude session
assert argv[argv.index("--resume") + 1] == "sess-1"
assert "--session-id" not in argv
def conversational_argv_call(resume: bool):
from app.conversational import conversational_argv
return conversational_argv(
session_id="sess-1", message="Hi there", model="sonnet", resume=resume
)
# --------------------------------------------------------------------------- #
# endpoint
# --------------------------------------------------------------------------- #
class _AsyncLineIter:
"""Async iterator over a list of byte lines — mimics `proc.stdout`."""
def __init__(self, lines: list[bytes]):
self._lines = list(lines)
self._i = 0
def __aiter__(self):
return self
async def __anext__(self):
if self._i >= len(self._lines):
raise StopAsyncIteration
line = self._lines[self._i]
self._i += 1
return line
def _mock_subprocess_returning(output: bytes, returncode: int = 0):
proc = AsyncMock()
lines = [chunk + b"\n" for chunk in output.split(b"\n") if chunk]
proc.stdout = _AsyncLineIter(lines)
proc.stderr = AsyncMock()
proc.stderr.read = AsyncMock(return_value=b"")
proc.wait = AsyncMock(return_value=returncode)
proc.returncode = returncode
return proc
@pytest.fixture(autouse=True)
def _reset_sessions():
conversational.reset_started()
yield
conversational.reset_started()
@pytest.fixture
def auth_header():
return {"Authorization": "Bearer test-token"}
@pytest.mark.asyncio
async def test_conversational_happy_path(auth_header):
"""A message in → the assistant's reply out, keyed to the session."""
cli_output = json.dumps({
"type": "result",
"is_error": False,
"result": "Здравейте! Как мога да помогна?",
"session_id": "sess-1",
}).encode()
mock_proc = _mock_subprocess_returning(cli_output, returncode=0)
with patch("app.conversational.asyncio.create_subprocess_exec", return_value=mock_proc):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.post(
"/v1/conversational",
json={"session_id": "sess-1", "message": "Здравей"},
headers=auth_header,
)
assert response.status_code == 200, response.text
body = response.json()
assert body["session_id"] == "sess-1"
assert body["reply"] == "Здравейте! Как мога да помогна?"
@pytest.mark.asyncio
async def test_conversational_resumes_on_second_turn(auth_header):
"""First turn opens the session (--session-id); a second turn on the same
session id resumes it (--resume) — this is what makes it a conversation."""
calls: list[tuple] = []
def fake_spawn(*args, **kwargs):
calls.append(args)
out = json.dumps({"type": "result", "is_error": False, "result": "ok"}).encode()
return _mock_subprocess_returning(out, returncode=0)
with patch("app.conversational.asyncio.create_subprocess_exec", side_effect=fake_spawn):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
for _ in range(2):
r = await client.post(
"/v1/conversational",
json={"session_id": "sess-X", "message": "hi"},
headers=auth_header,
)
assert r.status_code == 200, r.text
assert "--session-id" in calls[0] and "--resume" not in calls[0]
assert "--resume" in calls[1] and "--session-id" not in calls[1]
@pytest.mark.asyncio
async def test_conversational_requires_auth():
"""No bearer token → 401, same as the other endpoints."""
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
r = await client.post(
"/v1/conversational",
json={"session_id": "s", "message": "hi"},
)
assert r.status_code == 401
@pytest.mark.asyncio
async def test_conversational_returns_503_on_failure(auth_header):
"""A non-zero claude exit surfaces as 503 execution-failed."""
mock_proc = _mock_subprocess_returning(b"", returncode=7)
mock_proc.stderr.read = AsyncMock(return_value=b"boom")
with patch("app.conversational.asyncio.create_subprocess_exec", return_value=mock_proc):
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as client:
r = await client.post(
"/v1/conversational",
json={"session_id": "s", "message": "x"},
headers=auth_header,
)
assert r.status_code == 503
assert r.json()["error"] == "execution failed"
# --------------------------------------------------------------------------- #
# streaming helpers (OpenAI-compatible token relay for the realtime voice agent)
# --------------------------------------------------------------------------- #
from collections import namedtuple # noqa: E402
_Msg = namedtuple("_Msg", "role content")
def test_stream_argv_uses_stream_json_and_is_stateless():
argv = conversational.stream_argv("hello", "sonnet")
assert argv[:2] == ["claude", "-p"]
assert "--agent" in argv and "conversational" in argv
assert "stream-json" in argv
assert "--include-partial-messages" in argv
assert "--verbose" in argv
assert "--model" in argv and "sonnet" in argv
# latency: same lean-context trim as the gateway path
assert argv[argv.index("--setting-sources") + 1] == "user"
assert "--exclude-dynamic-system-prompt-sections" in argv
assert argv[-1] == "hello"
# stateless + no tools
assert "--resume" not in argv and "--session-id" not in argv
assert "--dangerously-skip-permissions" not in argv
def test_delta_text_extracts_content_block_delta():
line = json.dumps({
"type": "stream_event",
"event": {"type": "content_block_delta",
"delta": {"type": "text_delta", "text": "Слон"}},
})
assert conversational.delta_text(line) == "Слон"
def test_delta_text_ignores_non_text_events():
for ev in [
{"type": "system"},
{"type": "stream_event", "event": {"type": "message_start"}},
{"type": "stream_event", "event": {"type": "content_block_delta",
"delta": {"type": "input_json_delta", "partial_json": "{"}}},
{"type": "result"},
]:
assert conversational.delta_text(json.dumps(ev)) is None
assert conversational.delta_text("") is None
assert conversational.delta_text("not json") is None
def test_openai_chunk_valid_sse_and_keeps_cyrillic():
s = conversational.openai_chunk("chatcmpl-x", "sonnet", 123, content="две")
assert s.startswith("data: ") and s.endswith("\n\n")
payload = json.loads(s[len("data: "):].strip())
assert payload["object"] == "chat.completion.chunk"
assert payload["choices"][0]["delta"]["content"] == "две"
assert payload["choices"][0]["finish_reason"] is None
assert "две" in s # not unicode-escaped
def test_openai_chunk_role_and_finish():
role = conversational.openai_chunk("id", "m", 1, role="assistant")
assert json.loads(role[6:].strip())["choices"][0]["delta"] == {"role": "assistant"}
stop = conversational.openai_chunk("id", "m", 1, finish_reason="stop")
c = json.loads(stop[6:].strip())["choices"][0]
assert c["finish_reason"] == "stop" and c["delta"] == {}
def test_synthesise_chat_prompt_keeps_assistant_turns():
msgs = [
_Msg("system", "Be brief."),
_Msg("user", "Здравей"),
_Msg("assistant", "Здравей! Как си?"),
_Msg("user", "Добре, ти?"),
]
p = conversational.synthesise_chat_prompt(msgs)
assert "Be brief." in p
assert "User: Здравей" in p
assert "Assistant: Здравей! Как си?" in p
assert p.strip().endswith("User: Добре, ти?")