Files
talemate/tests/test_graphs.py
veguAI 42a8863e65 0.36.0 (#255)
Major Features

- API key encryption at rest using Fernet (OS keyring with file fallback)
- Prompt Manager: unified UI with template groups, priority ordering, override tracking, response extractors
- Scene context history review panel with token budgets and best-fit mode
- Multiple concurrent director chats with auto-generated titles
- Granular scene state reset dialog
- Time passage insert/edit/delete in scene view
- Image analysis via OpenAI-compatible and Talemate Client backends
- Volatile context placement after scene history for improved prompt caching

Improvements

- Configurable narrator generation length per narration type
- AI Aware conversation mode
- Summarizer: custom instructions, writing style inclusion, short line filtering
- Anthropic: adaptive thinking support, updated model list (opus-4-5/4-6, haiku-4-5)
- Google: gemini-3.1 support
- World editor: generate from topic, quick create state reinforcement, reorganized menus
- Node editor: promote scene modules to global
- Frontend: version mismatch detection, hideable bracket content, required scene name
- TTS: improved pause handling, audio tag support for vocal markers (ElevenLabs v3)
- Writing style template for AI-generated instructions
- Added Kimi.jinja2 LLM prompt template
- Option to disable character names in stopping strings
- Client response length enforcement options
- Graduated token count sliders
- Increased summarizer token threshold max

Bugfixes

- Fix bracket/paren/brace terminators stripped from message ends
- Fix colon in conversation causing content loss
- Fix "Use as reference" navigating to blank page
- Fix avatar regeneration and manual regenerate
- Fix conversation agent ignoring generation length
- Fix duplicate length instructions with reasoning enabled
- Fix trailing newline on message edits
- Fix summarize dialogue sending too much context with layered history
- Fix layered history inspection and construction issues
- Fix empty response handling in summarization
- Fix context ID dot notation with dotted character names
- Fix recursive retry in focal agent
- Fix leading whitespace causing duplicate prepared responses
- Fix summarization not stripping ANALYSIS OF lines
- Fix template group selection/removal in prompt manager
- Fix multiline text in parentheses/brackets parser
- Fix determine_character_name resolution
- Fix character activate/deactivate desyncing creative menu
- Fix character image generation missing context
- Fix LMStudio client not sending token limits
- Fix Recent Scene images on newer Chromium
- Fix sequential reinforcement messages cut off at first linebreak
- Fix reinforcement removal not clearing state
- Fixes #252, #256, #258

Deprecations

- Removed context investigations (replaced by AI-assisted RAG mixin)
- Removed deprecated prompt templates (fix-continuity-errors, fix-exposition, etc.)
- Removed conversation/edit.jinja2, auto break repetition, CLI reset layered history
---------

Co-authored-by: theDTV2 <47825738+theDTV2@users.noreply.github.com>
2026-03-15 12:00:57 +02:00

189 lines
5.6 KiB
Python

import os
import json
import pytest
import enum
import pydantic
import talemate.game.engine.nodes.load_definitions # noqa: F401
import talemate.agents.director # noqa: F401
from talemate.context import ActiveScene
from talemate.game.engine.nodes.core import (
Graph,
GraphState,
)
import structlog
from talemate.game.engine.nodes.layout import load_graph_from_file
from talemate.game.engine.nodes.registry import import_talemate_node_definitions
from conftest import MockClientContext, MockScene, bootstrap_scene
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
TEST_GRAPH_DIR = os.path.join(BASE_DIR, "data", "graphs")
RESULTS_DIR = os.path.join(BASE_DIR, "data", "graphs", "results")
UPDATE_RESULTS = False
log = structlog.get_logger("talemate.test_graphs")
# This runs once for the entire test session
@pytest.fixture(scope="session", autouse=True)
def load_node_definitions():
import_talemate_node_definitions()
def load_test_graph(name) -> Graph:
path = os.path.join(TEST_GRAPH_DIR, f"{name}.json")
graph, _ = load_graph_from_file(path)
return graph
@pytest.fixture
def mock_scene():
scene = MockScene()
bootstrap_scene(scene)
return scene
@pytest.fixture
def mock_scene_with_assets():
scene = MockScene()
bootstrap_scene(scene)
# Load test assets from the test scene file
test_scene_path = os.path.join(
BASE_DIR, "data", "scenes", "talemate-laboratory", "talemate-lab.json"
)
with open(test_scene_path, "r") as f:
test_scene_data = json.load(f)
# Override scenes_dir to point to test data directory
test_scenes_dir = os.path.join(BASE_DIR, "data", "scenes")
scene.scenes_dir = lambda: test_scenes_dir
scene.project_name = "talemate-laboratory"
# Create library.json file with assets from the scene file
if "assets" in test_scene_data and "assets" in test_scene_data["assets"]:
assets_dict = test_scene_data["assets"]["assets"]
# Ensure assets directory exists
assets_dir = os.path.join(test_scenes_dir, "talemate-laboratory", "assets")
os.makedirs(assets_dir, exist_ok=True)
# Create library.json file
library_path = os.path.join(assets_dir, "library.json")
with open(library_path, "w") as f:
json.dump({"assets": assets_dict}, f, indent=2)
return scene
def serialize_state(obj):
"""Custom JSON serializer for Pydantic models"""
if isinstance(obj, pydantic.BaseModel):
return obj.model_dump()
raise TypeError(f"Object of type {type(obj)} is not JSON serializable")
def normalize_state(data):
"""Convert Pydantic models to dicts for comparison"""
if isinstance(data, pydantic.BaseModel):
return data.model_dump()
elif isinstance(data, enum.Enum):
return data.value
elif isinstance(data, dict):
return {k: normalize_state(v) for k, v in data.items()}
elif isinstance(data, list):
return [normalize_state(item) for item in data]
return data
def make_assert_fn(name: str, write_results: bool = False):
async def assert_fn(state: GraphState):
if write_results or not os.path.exists(
os.path.join(RESULTS_DIR, f"{name}.json")
):
with open(os.path.join(RESULTS_DIR, f"{name}.json"), "w") as f:
json.dump(state.shared, f, indent=4, default=serialize_state)
else:
with open(os.path.join(RESULTS_DIR, f"{name}.json"), "r") as f:
expected = json.load(f)
# Normalize state.shared to convert Pydantic models to dicts for comparison
normalized_shared = normalize_state(state.shared)
assert normalized_shared == expected
return assert_fn
def make_graph_test(name: str, write_results: bool = False):
async def test_graph(scene):
assert_fn = make_assert_fn(name, write_results)
def error_handler(state, error: Exception):
raise error
with ActiveScene(scene):
graph = load_test_graph(name)
assert graph is not None
graph.callbacks.append(assert_fn)
graph.error_handlers.append(error_handler)
await graph.execute()
return test_graph
@pytest.mark.asyncio
async def test_graph_core(mock_scene):
fn = make_graph_test("test-harness-core", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_data(mock_scene):
fn = make_graph_test("test-harness-data", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_scene(mock_scene):
fn = make_graph_test("test-harness-scene", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_functions(mock_scene):
fn = make_graph_test("test-harness-functions", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_agents(mock_scene):
fn = make_graph_test("test-harness-agents", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_prompt(mock_scene):
fn = make_graph_test("test-harness-prompt", False)
async with MockClientContext() as client_reponses:
client_reponses.append("The sum of 1 and 5 is 6.")
client_reponses.append('```json\n{\n "result": 6\n}\n```')
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_collectors(mock_scene):
fn = make_graph_test("test-harness-collectors", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_context_ids(mock_scene):
fn = make_graph_test("test-harness-context-ids", False)
await fn(mock_scene)
@pytest.mark.asyncio
async def test_graph_assets(mock_scene_with_assets):
fn = make_graph_test("test-harness-assets", False)
await fn(mock_scene_with_assets)