Files
hermes-webui/tests/test_webui_state_db_context_reconciliation.py

277 lines
10 KiB
Python

import queue
import sqlite3
from collections import OrderedDict
from pathlib import Path
import pytest
pytestmark = pytest.mark.requires_agent_modules
def _make_state_db(path: Path, sid: str, rows):
conn = sqlite3.connect(path)
conn.execute(
"CREATE TABLE sessions (id TEXT PRIMARY KEY, source TEXT, title TEXT, model TEXT, started_at REAL, message_count INTEGER)"
)
conn.execute(
"CREATE TABLE messages (id INTEGER PRIMARY KEY AUTOINCREMENT, session_id TEXT, role TEXT, content TEXT, timestamp REAL)"
)
conn.execute(
"INSERT INTO sessions (id, source, title, model, started_at, message_count) VALUES (?, ?, ?, ?, ?, ?)",
(sid, "webui", "Context Reconcile", "test-model", 1000.0, len(rows)),
)
for row in rows:
conn.execute(
"INSERT INTO messages (session_id, role, content, timestamp) VALUES (?, ?, ?, ?)",
(sid, row["role"], row["content"], row.get("timestamp", 1000.0)),
)
conn.commit()
conn.close()
def test_next_webui_turn_context_includes_state_db_external_messages(monkeypatch, tmp_path):
import api.config as config
import api.models as models
import api.profiles as profiles
import api.streaming as streaming
from api.models import Session
session_dir = tmp_path / "sessions"
session_dir.mkdir()
index_file = session_dir / "_index.json"
monkeypatch.setattr(models, "SESSION_DIR", session_dir)
monkeypatch.setattr(models, "SESSION_INDEX_FILE", index_file)
monkeypatch.setattr(models, "SESSIONS", OrderedDict(), raising=False)
monkeypatch.setattr(config, "SESSION_DIR", session_dir, raising=False)
monkeypatch.setattr(config, "SESSION_INDEX_FILE", index_file, raising=False)
monkeypatch.setattr(streaming, "SESSION_DIR", session_dir, raising=False)
monkeypatch.setattr(profiles, "get_active_hermes_home", lambda: tmp_path, raising=False)
monkeypatch.setattr(models, "_active_state_db_path", lambda: tmp_path / "state.db", raising=False)
config.STREAMS.clear()
config.CANCEL_FLAGS.clear()
config.AGENT_INSTANCES.clear()
config.SESSION_AGENT_LOCKS.clear()
sid = "webui_context_reconcile_001"
sidecar_messages = [
{"role": "user", "content": "old user", "timestamp": 1000.0},
{"role": "assistant", "content": "old assistant", "timestamp": 1001.0},
]
session = Session(
session_id=sid,
title="Context Reconcile",
workspace=str(tmp_path),
model="test-model",
messages=list(sidecar_messages),
context_messages=list(sidecar_messages),
)
session.active_stream_id = "stream-context-reconcile"
session.pending_user_message = "new webui turn"
session.pending_started_at = 1004.0
session.save(touch_updated_at=False)
models.SESSIONS[sid] = session
_make_state_db(
tmp_path / "state.db",
sid,
[
{"role": "user", "content": "old user", "timestamp": 1000.0},
{"role": "assistant", "content": "old assistant", "timestamp": 1001.0},
{"role": "user", "content": "external gateway user", "timestamp": 1002.0},
{"role": "assistant", "content": "external gateway assistant", "timestamp": 1003.0},
],
)
captured = {}
class FakeAgent:
def __init__(self, **kwargs):
self.session_id = sid
self.context_compressor = None
self.ephemeral_system_prompt = None
def run_conversation(self, **kwargs):
captured["conversation_history"] = kwargs.get("conversation_history")
history = kwargs.get("conversation_history") or []
return {
"completed": True,
"final_response": "ok",
"messages": history + [
{"role": "user", "content": kwargs.get("persist_user_message", "")},
{"role": "assistant", "content": "ok"},
],
}
monkeypatch.setattr(streaming, "_get_ai_agent", lambda: FakeAgent)
monkeypatch.setattr(streaming, "resolve_model_provider", lambda *args, **kwargs: ("test-model", None, None))
monkeypatch.setattr(streaming, "get_config", lambda: {})
monkeypatch.setattr(config, "get_config", lambda: {})
monkeypatch.setattr(config, "_resolve_cli_toolsets", lambda *args, **kwargs: [])
stream_id = "stream-context-reconcile"
config.STREAMS[stream_id] = queue.Queue()
try:
streaming._run_agent_streaming(
session_id=sid,
msg_text="new webui turn",
model="test-model",
workspace=str(tmp_path),
stream_id=stream_id,
attachments=[],
)
finally:
config.STREAMS.pop(stream_id, None)
history_contents = [m.get("content") for m in captured.get("conversation_history") or []]
assert history_contents == [
"old user",
"old assistant",
"external gateway user",
"external gateway assistant",
]
reloaded = models.Session.load(sid)
saved_contents = [m.get("content") for m in (reloaded.messages if reloaded else [])]
assert saved_contents == [
"old user",
"old assistant",
"external gateway user",
"external gateway assistant",
"new webui turn",
"ok",
]
assert saved_contents.count("old user") == 1
assert saved_contents.count("external gateway user") == 1
def test_state_db_delta_after_context_allows_recovered_turn_prefix():
from api.models import state_db_delta_after_context
sidecar_context = [
{
"role": "user",
"content": "alright gateway restarted, lets give it a live test...",
"_recovered": True,
},
{
"role": "assistant",
"content": (
"**Response interrupted.**\n\n"
"The live response stream stopped before this turn finished. "
"The user message above was preserved, but no agent output was recovered."
),
"_error": True,
"type": "interrupted",
},
]
state_messages = [
{
"role": "user",
"content": "alright gateway restarted, lets give it a live test...",
"timestamp": 1.0,
},
{"role": "assistant", "content": "old assistant", "timestamp": 2.0},
{"role": "user", "content": "new prompt", "timestamp": 3.0},
]
delta = state_db_delta_after_context(sidecar_context, state_messages)
assert [m.get("content") for m in delta] == ["old assistant", "new prompt"]
def test_state_db_delta_after_context_does_not_promote_unrelated_prefix_as_recovered():
from api.models import state_db_delta_after_context
sidecar_context = [
{"role": "user", "content": "hi", "_recovered": True},
{"role": "user", "content": "hello"},
]
state_messages = [
{"role": "user", "content": "hello", "timestamp": 1.0},
{"role": "assistant", "content": "response", "timestamp": 2.0},
]
delta = state_db_delta_after_context(sidecar_context, state_messages)
assert [m.get("content") for m in delta] == ["hello", "response"]
def test_webui_streaming_normalizes_trailing_prefill_user_before_current_turn(monkeypatch, tmp_path):
import api.config as config
import api.models as models
import api.streaming as streaming
from api.models import new_session
session_dir = tmp_path / "sessions"
session_dir.mkdir()
index_file = session_dir / "_index.json"
monkeypatch.setattr(models, "SESSION_DIR", session_dir)
monkeypatch.setattr(models, "SESSION_INDEX_FILE", index_file)
monkeypatch.setattr(models, "SESSIONS", OrderedDict(), raising=False)
monkeypatch.setattr(config, "SESSION_DIR", session_dir, raising=False)
monkeypatch.setattr(config, "SESSION_INDEX_FILE", index_file, raising=False)
monkeypatch.setattr(streaming, "SESSION_DIR", session_dir, raising=False)
monkeypatch.setattr(models, "_active_state_db_path", lambda: tmp_path / "state.db", raising=False)
config.STREAMS.clear()
config.CANCEL_FLAGS.clear()
captured = {}
class FakeAgent:
def __init__(self, prefill_messages=None, **kwargs):
captured["prefill_messages"] = kwargs.get("prefill_messages")
if prefill_messages is not None:
captured["prefill_messages"] = prefill_messages
self.context_compressor = None
self.ephemeral_system_prompt = None
def run_conversation(self, **kwargs):
return {
"completed": True,
"final_response": "ok",
"messages": [
{"role": "user", "content": kwargs.get("persist_user_message", "")},
{"role": "assistant", "content": "ok"},
],
}
monkeypatch.setattr(streaming, "_get_ai_agent", lambda: FakeAgent)
monkeypatch.setattr(streaming, "resolve_model_provider", lambda *args, **kwargs: ("test-model", None, None))
monkeypatch.setattr(streaming, "get_config", lambda: {})
monkeypatch.setattr(config, "get_config", lambda: {})
monkeypatch.setattr(config, "_resolve_cli_toolsets", lambda *args, **kwargs: [])
monkeypatch.setattr(streaming, "_load_webui_prefill_context", lambda cfg: {
"status": "loaded",
"source": "test",
"label": "test",
"message_count": 2,
"messages": [
{"role": "assistant", "content": "prefill summary"},
{"role": "user", "content": "webui session context"},
],
})
s = new_session(workspace=str(tmp_path))
stream_id = "stream-prefill-boundary-normalization"
s.active_stream_id = stream_id
s.pending_user_message = "new webui turn"
s.pending_started_at = 0.0
s.save(touch_updated_at=False)
models.SESSIONS[s.session_id] = s
config.STREAMS[stream_id] = queue.Queue()
try:
streaming._run_agent_streaming(
session_id=s.session_id,
msg_text="new webui turn",
model="test-model",
workspace=str(tmp_path),
stream_id=stream_id,
attachments=[],
)
finally:
config.STREAMS.pop(stream_id, None)
prefill = captured.get("prefill_messages") or []
assert prefill == [{"role": "assistant", "content": "prefill summary"}]