feat(local-agent-v2): step 4 — journey produces structured AgentConfig JSON

Replace freeform prompt_template output with validated AgentConfig JSON:
- agent_setup.py: new system prompt (journey_system_v2), AGENT_CONFIG_START/END
  markers, _extract_agent_config() with Pydantic validation, updated handlers
  returning agent_config key; import AgentConfig from schemas
- tests/test_journey_v2.py: 6 unit tests + 5 parametrized LLM eval cases
  following test_agent_runner_v2.py pattern; _run_journey uses
  set_client_executor/clear_client_executor mirroring device_ws
- tests/fixtures/journey_v2/: cases.yaml + email_action.html + email_info.html
- tests/conftest.py: add --journey-dir CLI option; remove S3/plugin fixtures
  (cleanup from microservices migration, already present in working tree)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Roberto Musso
2026-04-08 00:23:58 +02:00
parent c6c4578f9a
commit d8add7e8cb
6 changed files with 607 additions and 190 deletions

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tests/test_journey_v2.py Normal file
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"""Tests for Local Agent V2 journey setup (Step 4).
Covers the chatbot journey that produces a structured AgentConfig JSON
instead of a freeform prompt_template string.
Unit tests (no LLM)
--------------------
4.6a _extract_agent_config: valid JSON → returns serialised config
4.6b _extract_agent_config: invalid JSON → returns None
4.6c _extract_agent_config: markers absent → returns None
4.6d _extract_agent_config: only START marker → returns None
4.6e Session not found → done=True, agent_config=None
4.6f Nudge uses AGENT_CONFIG_START/END markers (not old PROMPT_TEMPLATE)
Eval tests (real LLM + Langfuse scoring)
-----------------------------------------
Cases are defined in tests/fixtures/journey_v2/cases.yaml.
Email HTML files live in tests/fixtures/journey_v2/data/.
Use --journey-dir to point at a custom folder (same structure required).
Run:
pytest tests/test_journey_v2.py -v
pytest tests/test_journey_v2.py -v -k "4_6" # unit only
pytest tests/test_journey_v2.py -v -k "eval" # LLM evals only
pytest tests/test_journey_v2.py -v --journey-dir /p # custom fixtures
"""
from __future__ import annotations
import uuid
from contextlib import nullcontext
from pathlib import Path
from typing import Any
from unittest.mock import patch
import pytest
import yaml
from app.api.routes.agent_setup import (
_CONFIG_END,
_CONFIG_START,
_MAX_TURNS,
_extract_agent_config,
_sessions,
handle_journey_message,
handle_journey_start,
)
from app.core.langfuse_client import get_langfuse
from app.core.ws_context import clear_client_executor, set_client_executor
from app.schemas import AgentConfig
from tests.conftest import TEST_USER_IDS
# ── Constants ─────────────────────────────────────────────────────────────
_USER_ID = TEST_USER_IDS["power"]
_DEFAULT_FIXTURE_DIR = Path(__file__).parent / "fixtures" / "journey_v2"
# ── Fixture loading ───────────────────────────────────────────────────────
def _fixtures_dir(config) -> Path:
override = config.getoption("--journey-dir")
return Path(override) if override else _DEFAULT_FIXTURE_DIR
def _load_cases(config) -> list[dict]:
return yaml.safe_load(
(_fixtures_dir(config) / "cases.yaml").read_text(encoding="utf-8")
)
def _read_data_file(filename: str, fixtures_dir: Path) -> str:
return (fixtures_dir / "data" / filename).read_text(encoding="utf-8")
# ── pytest_generate_tests ─────────────────────────────────────────────────
def pytest_generate_tests(metafunc):
if "journey_case" not in metafunc.fixturenames:
return
cases = _load_cases(metafunc.config)
metafunc.parametrize("journey_case", cases, ids=[c["id"] for c in cases])
# ── Executor builder ──────────────────────────────────────────────────────
def _make_fs_executor(directory_files: list[dict], fixtures_dir: Path):
"""Return an async callback that simulates filesystem tool responses.
Matches the signature expected by ``set_client_executor`` / ``execute_on_client``:
receives the full ``payload`` dict and returns a result dict.
``directory_files`` is a list of ``{path, content_file}`` dicts;
``content_file`` is relative to ``fixtures_dir/data/``.
"""
file_map: dict[str, str] = {
entry["path"]: _read_data_file(entry["content_file"], fixtures_dir)
for entry in directory_files
}
async def _executor(payload: dict) -> dict:
action = payload.get("action", "")
data = payload.get("data") or {}
if action == "list_directory":
return {"entries": [
{"type": "file", "name": p.split("/")[-1], "path": p}
for p in file_map
]}
if action == "read_file_content":
path = data.get("path", "")
return {"content": file_map.get(path, "")}
if action == "get_file_metadata":
path = data.get("path", "")
name = path.split("/")[-1]
ext = "." + name.rsplit(".", 1)[-1] if "." in name else ""
return {"name": name, "extension": ext, "size": 1024,
"createdAt": None, "modifiedAt": None}
return {}
return _executor
# ── Journey runner helper ─────────────────────────────────────────────────
async def _run_journey(user_id: str, case: dict, executor) -> dict[str, Any]:
"""Drive start + all user_messages for a case. Returns the final reply dict.
Mirrors ``device_ws._handle_journey_start/message``: sets the client
executor (so filesystem tools work) before each handler call.
"""
session_id = str(uuid.uuid4())
try:
set_client_executor(executor)
reply = await handle_journey_start(user_id, {
"agent_type": "local",
"directory": case["directory"],
"data_types": case["data_types"],
"session_id": session_id,
})
for msg in case.get("user_messages", []):
if reply.get("done"):
break
set_client_executor(executor)
reply = await handle_journey_message(user_id, {
"session_id": reply["session_id"],
"message": msg,
})
finally:
clear_client_executor()
_sessions.pop(session_id, None)
return reply
# ── Assertion helper ──────────────────────────────────────────────────────
def _evaluate_case(case: dict, reply: dict) -> tuple[float, str]:
"""Return (score, comment) for a journey case given the final reply dict."""
if case.get("expect_question"):
has_q = "?" in reply.get("message", "")
return (1.0 if has_q else 0.0), f"first_reply_has_question={has_q}"
if case.get("expect_done") and not reply.get("done"):
return 0.0, "expected done=True but journey did not complete"
agent_config_raw = reply.get("agent_config")
if case.get("expect_valid_config"):
if not agent_config_raw:
return 0.0, "agent_config is None"
try:
parsed = AgentConfig.model_validate_json(agent_config_raw)
valid = len(parsed.content_types) > 0
return (1.0 if valid else 0.0), f"content_types={len(parsed.content_types)}"
except Exception as exc:
return 0.0, f"parse error: {exc}"
if case.get("expect_content_type_id"):
expected_id = case["expect_content_type_id"]
if not agent_config_raw:
return 0.0, "agent_config is None"
try:
parsed = AgentConfig.model_validate_json(agent_config_raw)
ids = [ct.id for ct in parsed.content_types]
found = expected_id in ids
return (1.0 if found else 0.0), f"content_type_ids={ids}, expected={expected_id}"
except Exception as exc:
return 0.0, f"parse error: {exc}"
if case.get("expect_extraction_contains"):
keyword = case["expect_extraction_contains"].lower()
if not agent_config_raw:
return 0.0, "agent_config is None"
try:
parsed = AgentConfig.model_validate_json(agent_config_raw)
if not parsed.content_types:
return 0.0, "no content_types in config"
prompt = parsed.content_types[0].extraction_prompt.lower()
found = keyword in prompt
return (1.0 if found else 0.0), f"keyword='{keyword}' in extraction_prompt={found}"
except Exception as exc:
return 0.0, f"parse error: {exc}"
if case.get("expect_global_rules"):
if not agent_config_raw:
return 0.0, "agent_config is None"
try:
parsed = AgentConfig.model_validate_json(agent_config_raw)
has_rules = len(parsed.global_rules) > 0
return (1.0 if has_rules else 0.0), f"global_rules={parsed.global_rules}"
except Exception as exc:
return 0.0, f"parse error: {exc}"
return 1.0, "no specific assertion"
# ── Unit tests ────────────────────────────────────────────────────────────
def test_4_6a_extract_valid_json():
"""_extract_agent_config: valid JSON between markers → returns serialised config."""
config = AgentConfig(
content_types=[],
global_rules=["No project = no entity"],
data_types=["tasks"],
)
text = f"Some preamble\n{_CONFIG_START}\n{config.model_dump_json()}\n{_CONFIG_END}\nTrailing"
result = _extract_agent_config(text)
assert result is not None
parsed = AgentConfig.model_validate_json(result)
assert parsed.global_rules == ["No project = no entity"]
def test_4_6b_extract_invalid_json():
"""_extract_agent_config: malformed JSON between markers → returns None."""
text = f"{_CONFIG_START}\n{{not: valid json\n{_CONFIG_END}"
assert _extract_agent_config(text) is None
def test_4_6c_extract_markers_absent():
"""_extract_agent_config: no markers at all → returns None."""
assert _extract_agent_config("No markers here at all") is None
def test_4_6d_extract_only_start_marker():
"""_extract_agent_config: START without END → returns None."""
assert _extract_agent_config(f"text {_CONFIG_START} no end marker") is None
@pytest.mark.asyncio
async def test_4_6e_session_not_found():
"""4.6e Session not found → done=True, agent_config=None, informative message."""
reply = await handle_journey_message(_USER_ID, {
"session_id": "nonexistent-session-id",
"message": "Hello",
})
assert reply["done"] is True
assert reply["agent_config"] is None
assert "not found" in reply["message"].lower() or "expired" in reply["message"].lower()
@pytest.mark.asyncio
async def test_4_6f_nudge_uses_new_markers():
"""4.6f Nudge injected after max turns uses AGENT_CONFIG markers, not PROMPT_TEMPLATE."""
session_id = str(uuid.uuid4())
captured_histories: list[list[dict]] = []
async def _mock_llm(system_prompt, history, tools, **kwargs) -> str:
captured_histories.append(list(history))
# Return plain text — no markers — to trigger the nudge path.
return "I still need more information from you."
from app.api.routes.agent_setup import JourneySession
fake_session = JourneySession(
session_id=session_id,
user_id=_USER_ID,
agent_type="local",
directory="/test",
data_types=["tasks"],
system_prompt="system",
langfuse_prompt=None,
)
# Fill history to the turn limit so the next message triggers the nudge.
for i in range(_MAX_TURNS):
fake_session.history.append({"role": "user", "content": f"msg {i}"})
fake_session.history.append({"role": "assistant", "content": "ok"})
_sessions[session_id] = fake_session
try:
with patch("app.api.routes.agent_setup._call_llm_with_tools", side_effect=_mock_llm):
await handle_journey_message(_USER_ID, {
"session_id": session_id,
"message": "one more message to trigger nudge",
})
finally:
_sessions.pop(session_id, None)
# Second LLM call receives the nudge appended to history.
assert len(captured_histories) >= 2, "Expected ≥ 2 LLM calls (main reply + nudge)"
nudge_history = captured_histories[1]
user_msgs = " ".join(t["content"] for t in nudge_history if t["role"] == "user")
assert _CONFIG_START in user_msgs, f"Nudge must reference {_CONFIG_START}"
assert _CONFIG_END in user_msgs, f"Nudge must reference {_CONFIG_END}"
assert "PROMPT_TEMPLATE" not in user_msgs, "Old PROMPT_TEMPLATE markers must not appear in nudge"
# ── Eval tests (real LLM + Langfuse) ─────────────────────────────────────
@pytest.mark.asyncio
@pytest.mark.eval
async def test_eval_journey(journey_case, pytestconfig):
"""Parametrized eval test — one invocation per YAML case."""
case: dict = journey_case
fixtures_dir = _fixtures_dir(pytestconfig)
executor = _make_fs_executor(case.get("directory_files", []), fixtures_dir)
lf = get_langfuse()
obs_ctx = lf.start_as_current_observation(
name=f"eval-journey-{case['id']}-{case.get('score_name', 'unknown').replace('.', '-')}",
metadata={"step": "4", "case_id": case["id"]},
) if lf else nullcontext()
with obs_ctx as obs:
reply = await _run_journey(_USER_ID, case, executor)
score, comment = _evaluate_case(case, reply)
if obs is not None:
obs.score(
name=case.get("score_name", f"journey.case_{case['id']}"),
value=score,
comment=comment,
)
if lf:
lf.flush()
assert score == 1.0, f"[{case['id']}] {case.get('description', '')}{comment}"