mirror of
https://github.com/dograh-hq/dograh.git
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432 lines
14 KiB
Python
432 lines
14 KiB
Python
"""End-to-end tests for the Node TS validator bridge.
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Exercises the real `node` subprocess — slow-ish but the whole point is
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that code → JSON and JSON → code round-trip losslessly.
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"""
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from __future__ import annotations
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import shutil
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from types import NoneType
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from typing import Any, get_args
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import pytest
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from api.mcp_server.ts_bridge import TsBridgeError, generate_code, parse_code
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from api.services.workflow.dto import EdgeDataDTO
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from api.services.workflow.node_specs import (
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NodeSpec,
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PropertySpec,
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PropertyType,
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all_specs,
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)
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pytestmark = pytest.mark.skipif(
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shutil.which("node") is None, reason="node binary not available"
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)
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def _minimal_workflow() -> dict:
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"""Start → End, one edge. Stored shape matches ReactFlowDTO."""
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return {
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"nodes": [
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{
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"id": "1",
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"type": "startCall",
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"position": {"x": 0, "y": 0},
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"data": {
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"name": "Greeting",
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"prompt": "Greet warmly.",
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"greeting_type": "text",
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"greeting": "Hi {{first_name}}!",
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"allow_interrupt": True,
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},
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},
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{
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"id": "2",
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"type": "endCall",
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"position": {"x": 200, "y": 0},
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"data": {"name": "Done", "prompt": "Say goodbye."},
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},
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],
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"edges": [
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{
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"id": "1-2",
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"source": "1",
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"target": "2",
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"data": {"label": "done", "condition": "conversation complete"},
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},
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],
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"viewport": {"x": 0, "y": 0, "zoom": 1},
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}
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def _normalize(wf: dict) -> dict:
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"""Strip cosmetics before comparing a round-tripped workflow.
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Node IDs are regenerated deterministically by the parser
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(1, 2, 3, ...) so the inputs already match if constructed that way.
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Position is preserved. Edge ids follow `source-target`.
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"""
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return {
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"nodes": [
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{
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"id": n["id"],
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"type": n["type"],
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"position": n["position"],
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"data": n["data"],
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}
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for n in wf["nodes"]
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],
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"edges": [
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{
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"id": e["id"],
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"source": e["source"],
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"target": e["target"],
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"data": e["data"],
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}
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for e in wf["edges"]
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],
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}
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def _strip_optional(annotation: Any) -> Any:
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args = tuple(arg for arg in get_args(annotation) if arg is not NoneType)
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if len(args) == 1:
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return args[0]
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return annotation
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def _pick_option_value(prop: PropertySpec) -> Any:
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assert prop.options, f"{prop.name} has no options"
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default = prop.default
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for option in prop.options:
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if option.value != default:
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return option.value
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return prop.options[0].value
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def _sample_number(prop: PropertySpec) -> int | float:
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candidates: list[int | float] = [1, 2, 3, 0.5, 4.5, 10]
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for candidate in candidates:
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if prop.min_value is not None and candidate < prop.min_value:
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continue
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if prop.max_value is not None and candidate > prop.max_value:
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continue
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if prop.default is not None and candidate == prop.default:
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continue
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return candidate
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raise AssertionError(f"No valid sample number found for {prop.name}")
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def _sample_property_value(prop: PropertySpec, *, path: str) -> Any:
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slug = path.replace(".", "_")
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if prop.type == PropertyType.string:
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return f"{slug}_value"
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if prop.type == PropertyType.mention_textarea:
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return f"{slug} prompt with {{name}}"
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if prop.type == PropertyType.url:
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return f"https://example.com/{slug}"
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if prop.type == PropertyType.recording_ref:
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return f"recording_{slug}"
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if prop.type == PropertyType.credential_ref:
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return f"credential_{slug}"
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if prop.type == PropertyType.number:
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return _sample_number(prop)
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if prop.type == PropertyType.boolean:
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return not prop.default if isinstance(prop.default, bool) else True
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if prop.type == PropertyType.options:
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return _pick_option_value(prop)
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if prop.type == PropertyType.multi_options:
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return [_pick_option_value(prop)]
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if prop.type == PropertyType.tool_refs:
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return [f"tool_{slug}"]
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if prop.type == PropertyType.document_refs:
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return [f"document_{slug}"]
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if prop.type == PropertyType.json:
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return {"kind": slug, "enabled": True}
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if prop.type == PropertyType.fixed_collection:
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assert prop.properties, f"{prop.name} fixed_collection has no sub-properties"
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return [
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{
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sub_prop.name: _sample_property_value(
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sub_prop, path=f"{path}.{sub_prop.name}"
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)
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for sub_prop in prop.properties
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}
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]
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raise AssertionError(f"Unhandled PropertyType in TS bridge test: {prop.type}")
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def _sample_node_data(spec: NodeSpec) -> dict[str, Any]:
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return {
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prop.name: _sample_property_value(prop, path=f"{spec.name}.{prop.name}")
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for prop in spec.properties
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}
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def _sample_edge_value(field_name: str, annotation: Any) -> Any:
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inner = _strip_optional(annotation)
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if inner is str:
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return f"{field_name}_value"
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if inner is bool:
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return True
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if inner in (int, float):
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return 1
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raise AssertionError(
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f"Unhandled edge field annotation in TS bridge test: {field_name} -> {annotation!r}"
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)
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def _sample_edge_data() -> dict[str, Any]:
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return {
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field_name: _sample_edge_value(field_name, field.annotation)
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for field_name, field in EdgeDataDTO.model_fields.items()
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}
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# ─── generate_code ───────────────────────────────────────────────────────
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@pytest.mark.asyncio
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async def test_generate_emits_imports_and_factories():
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code = await generate_code(_minimal_workflow(), workflow_name="test")
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assert 'import { Workflow } from "@dograh/sdk";' in code
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assert "startCall" in code
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assert "endCall" in code
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assert "wf.addTyped(startCall(" in code
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assert "wf.edge(" in code
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@pytest.mark.asyncio
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async def test_generate_strips_spec_defaults():
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wf = _minimal_workflow()
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code = await generate_code(wf)
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# `add_global_prompt=True` is a spec default for startCall; emitted
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# code should omit it. Keeps the LLM-facing projection tight.
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assert "add_global_prompt" not in code
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@pytest.mark.asyncio
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async def test_generate_omits_position():
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"""Positions are hidden from the LLM — auto-layout post-processing
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(future) reassigns them on save. Keeping them out of the edit
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surface avoids the LLM producing cramped/overlapping layouts."""
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wf = _minimal_workflow()
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code = await generate_code(wf)
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assert "position" not in code
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@pytest.mark.asyncio
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async def test_generate_strips_legacy_ui_state_fields():
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"""Stored workflows from before spec validation carry UI-state fields
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(`invalid`, `selected`, `is_start`, etc.). `get_workflow_code` hides
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those from the LLM so edits don't round-trip the noise."""
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wf = {
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"nodes": [
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{
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"id": "1",
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"type": "startCall",
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"position": {"x": 0, "y": 0},
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"data": {
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"name": "g",
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"prompt": "hi",
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"invalid": False,
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"validationMessage": None,
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"is_start": True,
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"selected": True,
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"dragging": False,
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},
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},
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],
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"edges": [],
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"viewport": {"x": 0, "y": 0, "zoom": 1},
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}
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code = await generate_code(wf)
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for dropped in ("invalid", "validationMessage", "is_start", "selected", "dragging"):
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assert dropped not in code, f"{dropped} should be stripped"
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assert 'prompt: "hi"' in code
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@pytest.mark.asyncio
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async def test_generate_strips_unknown_edge_fields():
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wf = _minimal_workflow()
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wf["edges"][0]["data"]["invalid"] = False
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wf["edges"][0]["data"]["validationMessage"] = None
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code = await generate_code(wf)
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assert "invalid" not in code
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assert "validationMessage" not in code
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@pytest.mark.asyncio
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async def test_generate_preserves_all_edge_dto_fields():
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wf = _minimal_workflow()
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edge_data = _sample_edge_data()
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wf["edges"][0]["data"] = edge_data
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code = await generate_code(wf)
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result = await parse_code(code)
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assert result["ok"] is True, result
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assert result["workflow"]["edges"][0]["data"] == edge_data
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# ─── parse_code ──────────────────────────────────────────────────────────
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@pytest.mark.asyncio
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async def test_parse_accepts_minimal_code():
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code = """import { Workflow } from "@dograh/sdk";
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import { startCall, endCall } from "@dograh/sdk/typed";
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const wf = new Workflow({ name: "min" });
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const a = wf.addTyped(startCall({ name: "g", prompt: "hi" }));
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const b = wf.addTyped(endCall({ name: "d", prompt: "bye" }));
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wf.edge(a, b, { label: "done", condition: "wrapped" });
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"""
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result = await parse_code(code)
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assert result["ok"] is True
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wf = result["workflow"]
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assert len(wf["nodes"]) == 2
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assert len(wf["edges"]) == 1
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assert wf["nodes"][0]["type"] == "startCall"
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assert wf["edges"][0]["source"] == wf["nodes"][0]["id"]
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@pytest.mark.asyncio
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async def test_parse_rejects_function_declaration():
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code = """import { Workflow } from "@dograh/sdk";
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const wf = new Workflow({ name: "x" });
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function evil() { return 1; }
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"""
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result = await parse_code(code)
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assert result["ok"] is False
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assert result["stage"] == "parse"
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assert any("FunctionDeclaration" in e["message"] for e in result["errors"])
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@pytest.mark.asyncio
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async def test_parse_rejects_unknown_field():
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code = """import { Workflow } from "@dograh/sdk";
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import { startCall } from "@dograh/sdk/typed";
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const wf = new Workflow({ name: "x" });
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const a = wf.addTyped(startCall({ name: "g", prompt: "hi", promt: "typo" }));
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"""
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result = await parse_code(code)
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assert result["ok"] is False
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assert result["stage"] == "validate"
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assert any("Unknown field" in e["message"] for e in result["errors"])
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@pytest.mark.asyncio
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async def test_parse_rejects_unknown_variable_in_edge():
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code = """import { Workflow } from "@dograh/sdk";
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import { startCall, endCall } from "@dograh/sdk/typed";
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const wf = new Workflow({ name: "x" });
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const a = wf.addTyped(startCall({ name: "g", prompt: "hi" }));
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wf.edge(a, missing, { label: "done", condition: "c" });
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"""
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result = await parse_code(code)
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assert result["ok"] is False
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assert result["stage"] == "parse"
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assert any("Unknown node variable" in e["message"] for e in result["errors"])
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@pytest.mark.asyncio
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async def test_parse_requires_label_and_condition_on_edge():
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code = """import { Workflow } from "@dograh/sdk";
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import { startCall, endCall } from "@dograh/sdk/typed";
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const wf = new Workflow({ name: "x" });
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const a = wf.addTyped(startCall({ name: "g", prompt: "hi" }));
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const b = wf.addTyped(endCall({ name: "d", prompt: "bye" }));
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wf.edge(a, b, { label: "", condition: "c" });
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"""
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result = await parse_code(code)
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assert result["ok"] is False
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assert result["stage"] == "parse"
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@pytest.mark.asyncio
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async def test_parse_rejects_unknown_edge_field():
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code = """import { Workflow } from "@dograh/sdk";
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import { startCall, endCall } from "@dograh/sdk/typed";
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const wf = new Workflow({ name: "x" });
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const a = wf.addTyped(startCall({ name: "g", prompt: "hi" }));
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const b = wf.addTyped(endCall({ name: "d", prompt: "bye" }));
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wf.edge(a, b, { label: "done", condition: "wrapped", bogus: "x" });
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"""
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result = await parse_code(code)
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assert result["ok"] is False
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assert result["stage"] == "parse"
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assert any("Unknown edge field" in e["message"] for e in result["errors"])
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# ─── Round-trip ──────────────────────────────────────────────────────────
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@pytest.mark.asyncio
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async def test_round_trip_minimal():
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wf = _minimal_workflow()
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code = await generate_code(wf, workflow_name="rt")
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result = await parse_code(code)
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assert result["ok"] is True, result
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# Positions are intentionally not preserved — they'll be reassigned
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# by a downstream auto-layout pass. Parser defaults to {0, 0}.
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for in_node, out_node in zip(wf["nodes"], result["workflow"]["nodes"]):
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assert out_node["type"] == in_node["type"]
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assert out_node["position"] == {"x": 0, "y": 0}
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for k, v in in_node["data"].items():
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assert out_node["data"][k] == v, (
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f"{k}: {out_node['data'].get(k)!r} != {v!r}"
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)
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assert _normalize({"nodes": [], "edges": result["workflow"]["edges"]})["edges"] == [
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{
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"id": "1-2",
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"source": "1",
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"target": "2",
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"data": {"label": "done", "condition": "conversation complete"},
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}
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]
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@pytest.mark.asyncio
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@pytest.mark.parametrize("spec", all_specs(), ids=lambda spec: spec.name)
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async def test_round_trip_preserves_all_node_spec_fields(spec: NodeSpec):
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data = _sample_node_data(spec)
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wf = {
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"nodes": [
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{
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"id": "1",
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"type": spec.name,
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"position": {"x": 0, "y": 0},
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"data": data,
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}
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],
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"edges": [],
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"viewport": {"x": 0, "y": 0, "zoom": 1},
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}
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code = await generate_code(wf, workflow_name=f"{spec.name}_rt")
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result = await parse_code(code)
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assert result["ok"] is True, result
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assert result["workflow"]["nodes"][0]["data"] == data
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@pytest.mark.asyncio
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async def test_generate_fails_on_unknown_type():
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bad = {
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"nodes": [
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{
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"id": "1",
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"type": "doesNotExist",
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"position": {"x": 0, "y": 0},
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"data": {},
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}
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],
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"edges": [],
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"viewport": {"x": 0, "y": 0, "zoom": 1},
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}
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with pytest.raises(TsBridgeError, match="Unknown node type"):
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await generate_code(bad)
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