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aigc-home/calliope-backend/tests/test_workflow_import_confirm.py
T
总工andmultica-agent e6f761f8c8 feat(workflows): 五类用途识别与导入确认闭环 (HEL-636)
- 判型器 classify_usage:按输出节点(sink 检测)与被消费图片槽判定
  文生图/图生图/文生视频/图生视频/参考图生视频,不依赖文件名/模型名/
  固定节点 ID;歧义(单散装图+视频、同图双输出)与无输出给中文说明
- 参考图组泛化:任意 <group>.<prefix>N 连续编号且均接图源的输入成组
  (MiniMaxH3 特判仅剩标签美化);patcher 支持通用组回填
- workflows 表新增 usage/usage_source,幂等迁移回填;判不出的存量行
  停用待确认;kind 语义收窄为输出媒体,历史无损
- 导入改两步向导:分析→预览(判定依据/输出节点/媒体槽角色可改/
  参数预览/警告)→确认保存;usage_source=user 的纠正不被重分析覆盖
- 生成页按 usage 过滤;待确认工作流不进生成页且提交被拒
- 新增 test_usage_classifier / test_workflow_import_confirm;
  两个旧测试夹具补输出节点以匹配新守卫

Co-authored-by: multica-agent <github@multica.ai>
2026-09-29 12:13:33 +08:00

236 lines
9.2 KiB
Python

"""HEL-636: the two-step import closes the loop — analyze → confirm → save,
user corrections stick (reanalyze never overwrites them), pending workflows
cannot generate, and legacy rows migrate losslessly."""
from __future__ import annotations
import json
from pathlib import Path
from calliope.config import settings
from calliope.db import get_db, migrate_db
FIXTURES = Path(__file__).parent / "fixtures" / "comfy_native"
def _load(name: str) -> dict:
return json.loads((FIXTURES / name).read_text(encoding="utf-8"))
AMBIGUOUS = {
"1": {"class_type": "PrimitiveStringMultiline", "inputs": {"value": "p"}},
"5": {"class_type": "LoadImage", "inputs": {"image": "x.png"}},
"7": {
"class_type": "SomeVideoSampler",
"inputs": {"prompt": ["1", 0], "image": ["5", 0]},
},
"9": {"class_type": "SaveVideo", "inputs": {"images": ["7", 0]}},
}
def test_analyze_returns_usage_evidence_and_problem(client):
wf = _load("qwen_image_t2i_API.json")
r = client.post("/api/workflows/analyze", json={"workflow_json": wf})
assert r.status_code == 200
body = r.json()
assert body["usage"] == "text2image"
assert body["usage_ambiguous"] is False and body["needs_mapping"] is False
assert any(o["kind"] == "image" for o in body["usage_evidence"]["outputs"])
assert body["usable_usage"] == [
"text2image", "image2image", "text2video", "image2video", "ref2video",
]
r = client.post("/api/workflows/analyze", json={"workflow_json": AMBIGUOUS})
body = r.json()
assert body["usage"] is None and body["usage_ambiguous"] is True
assert "首帧还是参考图" in body["usage_problem"]
assert body["usage_evidence"]["image_slots"][0]["nodeId"] == "5"
bare = {"1": {"class_type": "Note", "inputs": {}}}
r = client.post("/api/workflows/analyze", json={"workflow_json": bare})
body = r.json()
assert "未在图中找到输出节点" in body["usage_problem"]
def test_create_stores_auto_usage_and_kind(client):
r = client.post(
"/api/workflows",
json={"name": "自动·文生图", "workflow_json": _load("qwen_image_t2i_API.json")},
)
assert r.status_code == 200, r.text
wf = r.json()
assert wf["usage"] == "text2image" and wf["usage_source"] == "auto"
assert wf["kind"] == "image" and wf["is_enabled"] is True
r = client.post(
"/api/workflows",
json={"name": "自动·参考生视频", "workflow_json": _load("h3_ref2va_05_API.json")},
)
wf = r.json()
assert wf["usage"] == "ref2video" and wf["kind"] == "video"
def test_ambiguous_import_stays_pending_and_cannot_generate(client):
r = client.post("/api/workflows", json={"name": "歧义", "workflow_json": AMBIGUOUS})
assert r.status_code == 200
wf = r.json()
assert wf["usage"] is None and wf["is_enabled"] is False
gen = client.post(
"/api/playground/generate",
json={"workflow_id": wf["id"], "input_values": {"1": "x"}},
)
assert gen.status_code == 400
assert "已停用" in gen.json()["detail"]
assert client.get("/api/playground/jobs").json() == []
def test_confirm_page_correction_roundtrip(client):
"""analyze → user picks usage + fixes the slot role → create carries both."""
analyzed = client.post("/api/workflows/analyze", json={"workflow_json": AMBIGUOUS}).json()
assert analyzed["usage"] is None
slot = analyzed["usage_evidence"]["image_slots"][0]
schema = [
{**i, "role": "first_frame", "manual": True} if i["nodeId"] == slot["nodeId"] else i
for i in analyzed["inputs"]
]
r = client.post(
"/api/workflows",
json={
"name": "确认·图生视频",
"workflow_json": AMBIGUOUS,
"usage": "image2video",
"usage_source": "user",
"input_schema": schema,
},
)
assert r.status_code == 200, r.text
wf = r.json()
assert wf["usage"] == "image2video" and wf["usage_source"] == "user"
assert wf["kind"] == "video" and wf["is_enabled"] is True
# the manual role sticks on read (and through re-derivation)
entry = next(i for i in wf["input_schema"] if i["nodeId"] == slot["nodeId"])
assert entry["role"] == "first_frame"
# reanalyze refreshes the auto schema but never the user's usage
r = client.post(f"/api/workflows/{wf['id']}/reanalyze")
assert r.status_code == 200
fresh = r.json()
assert fresh["usage"] == "image2video" and fresh["usage_source"] == "user"
entry = next(i for i in fresh["input_schema"] if i["nodeId"] == slot["nodeId"])
assert entry["role"] == "first_frame" and entry.get("manual") is True
def test_patch_usage_confirms_pending_workflow(client):
r = client.post("/api/workflows", json={"name": "待确认", "workflow_json": AMBIGUOUS})
wid = r.json()["id"]
assert r.json()["is_enabled"] is False
r = client.patch(f"/api/workflows/{wid}", json={"usage": "ref2video"})
assert r.status_code == 200
wf = r.json()
assert wf["usage"] == "ref2video" and wf["usage_source"] == "user"
assert wf["kind"] == "video" and wf["is_enabled"] is True
listed = next(w for w in client.get("/api/workflows").json() if w["id"] == wid)
assert listed["usage"] == "ref2video"
def test_reanalyze_upgrades_auto_usage_only(client):
r = client.post(
"/api/workflows",
json={"name": "重分析", "workflow_json": _load("qwen_image_t2i_API.json")},
)
wid = r.json()["id"]
r = client.patch(f"/api/workflows/{wid}", json={"usage": "image2image", "usage_source": "user"})
assert r.json()["usage"] == "image2image"
r = client.post(f"/api/workflows/{wid}/reanalyze")
assert r.json()["usage"] == "image2image" # user decision survives
assert r.json()["usage_source"] == "user"
def test_legacy_kind_only_callers_still_work(client):
"""Old clients post kind without usage — determinate graphs classify, the
row is enabled and generation proceeds as before."""
r = client.post(
"/api/workflows",
json={"name": "旧调用", "kind": "image", "workflow_json": _load("qwen_image_t2i_API.json")},
)
assert r.status_code == 200
wf = r.json()
assert wf["usage"] == "text2image" and wf["is_enabled"] is True
def test_migration_backfills_usage_and_keeps_history(client):
"""A8: pre-HEL-636 rows (direct SQL, no usage) settle on re-migration;
determinate ones gain usage, ambiguous ones are parked disabled, and
existing jobs/history stay readable with their original kind."""
pid = client.post("/api/projects", json={"title": "存量项目", "idea": "x"}).json()["id"]
conn = get_db(settings.db_path)
try:
conn.execute(
"INSERT INTO workflows (name, kind, workflow_json, input_schema,"
" output_schema, is_enabled) VALUES (?, 'image', ?, '[]', '[]', 1)",
("存量·文生图", json.dumps(_load("qwen_image_t2i_API.json"))),
)
conn.execute(
"INSERT INTO workflows (name, kind, workflow_json, input_schema,"
" output_schema, is_enabled) VALUES (?, 'video', ?, '[]', '[]', 1)",
("存量·歧义", json.dumps(AMBIGUOUS)),
)
conn.execute(
"INSERT INTO jobs (project_id, kind, workflow_id, status, payload_json,"
" output_paths_json) VALUES (?, 'image', NULL, 'done', '{}', ?)",
(pid, json.dumps(["/old/result.png"])),
)
conn.commit()
finally:
conn.close()
import asyncio
asyncio.run(migrate_db(settings.db_path)) # idempotent re-run
wfs = {w["name"]: w for w in client.get("/api/workflows").json()}
assert wfs["存量·文生图"]["usage"] == "text2image"
assert wfs["存量·文生图"]["is_enabled"] is True
assert wfs["存量·歧义"]["usage"] is None
assert wfs["存量·歧义"]["is_enabled"] is False
assert wfs["存量·歧义"]["kind"] == "video" # old kind semantics untouched
jobs = client.get(f"/api/jobs?project_id={pid}").json()
assert any(
j["status"] == "done" and j["kind"] == "image" and j["output_paths"] == ["/old/result.png"]
for j in jobs
)
# a third run changes nothing (idempotent)
asyncio.run(migrate_db(settings.db_path))
wfs2 = {w["name"]: w for w in client.get("/api/workflows").json()}
assert wfs2["存量·文生图"]["usage"] == "text2image"
assert wfs2["存量·歧义"]["usage"] is None
def test_broken_qwen_import_stays_blocked_but_recorded(client):
"""The damaged Qwen export classifies fine (image2image); its structural
lint errors still refuse generation — a broken file case, not a usage case."""
wf_json = _load("qwen21_edit_sage_API.json")
r = client.post(
"/api/workflows/analyze", json={"workflow_json": wf_json}
)
assert r.json()["usage"] == "image2image"
r = client.post(
"/api/workflows", json={"name": "损坏·Qwen", "kind": "image", "workflow_json": wf_json}
)
assert r.status_code == 200
wf = r.json()
assert wf["usage"] == "image2image" and wf["is_enabled"] is True
assert any(w["level"] == "error" for w in wf["warnings"])
gen = client.post(
"/api/playground/generate",
json={"workflow_id": wf["id"], "input_values": {"4@prompt": "x"}},
)
assert gen.status_code == 400 and "重新导出" in gen.json()["detail"]