mirror of
https://github.com/langgenius/dify.git
synced 2026-10-04 13:47:55 +08:00
90 lines
3.6 KiB
Python
90 lines
3.6 KiB
Python
"""M2 Localizer: detect language, translate only catalog/template strings, cache."""
|
|
|
|
from core.dify_builder.models import ConversationItem
|
|
from services.dify_builder.agent.localize import Localizer
|
|
|
|
|
|
class _FakeModel:
|
|
"""Records calls; returns canned detection / translation payloads."""
|
|
def __init__(self):
|
|
self.translate_calls = 0
|
|
|
|
# detect_language uses invoke_text; translate uses invoke_json — patched below.
|
|
|
|
|
|
def _localizer(monkeypatch, *, detect="zh-Hans", table=None):
|
|
table = table or {}
|
|
from services.dify_builder.agent import localize as mod
|
|
|
|
def fake_invoke_text(model, *, system, user, **kw): # noqa: ARG001
|
|
return detect
|
|
|
|
def fake_invoke_json(model, *, system, user, **kw): # noqa: ARG001
|
|
model.translate_calls += 1
|
|
# translate every requested source string via the table (default: prefix)
|
|
import json
|
|
srcs = json.loads(user)["strings"] if user.strip().startswith("{") else []
|
|
return {s: table.get(s, f"<{s}>") for s in srcs}
|
|
|
|
monkeypatch.setattr(mod.llm, "invoke_text", fake_invoke_text)
|
|
monkeypatch.setattr(mod.llm, "invoke_json", fake_invoke_json)
|
|
fake = _FakeModel()
|
|
return Localizer(lambda: fake), fake
|
|
|
|
|
|
def test_detect_language(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch, detect="ja")
|
|
assert loc.detect_language("こんにちは") == "ja"
|
|
|
|
|
|
def test_detect_language_english_fallback_on_empty(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch)
|
|
assert loc.detect_language("") == "en"
|
|
|
|
|
|
def test_detect_language_clean_code_passes(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch, detect="ja")
|
|
assert loc.detect_language("hello") == "ja"
|
|
|
|
|
|
def test_detect_language_rejects_non_code_reply(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch, detect="The language is Japanese.")
|
|
assert loc.detect_language("hello") == "en"
|
|
|
|
|
|
def test_localize_translates_catalog_string(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch, table={"Test run": "测试运行"})
|
|
items = [ConversationItem(kind="test_result", payload={"title": "Test run", "tone": "success"})]
|
|
out = loc.localize_items(items, "zh-Hans")
|
|
assert out[0].payload["title"] == "测试运行"
|
|
assert out[0].payload["tone"] == "success" # enum untouched
|
|
|
|
|
|
def test_localize_leaves_non_catalog_prose_untouched(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch)
|
|
items = [ConversationItem(kind="assistant_turn", payload={"reply_text": "这是我为你生成的计划"})]
|
|
out = loc.localize_items(items, "zh-Hans")
|
|
assert out[0].payload["reply_text"] == "这是我为你生成的计划" # LLM prose, not in catalog
|
|
|
|
|
|
def test_localize_template_reinserts_dynamic_part(monkeypatch):
|
|
loc, _ = _localizer(monkeypatch, table={"Workflow built ({count} nodes)": "已构建工作流（{count} 个节点）"})
|
|
items = [ConversationItem(kind="summary", payload={"items": ["Workflow built (3 nodes)"]})]
|
|
out = loc.localize_items(items, "zh-Hans")
|
|
assert out[0].payload["items"][0] == "已构建工作流（3 个节点）"
|
|
|
|
|
|
def test_localize_english_is_noop(monkeypatch):
|
|
loc, fake = _localizer(monkeypatch)
|
|
items = [ConversationItem(kind="test_result", payload={"title": "Test run"})]
|
|
out = loc.localize_items(items, "en")
|
|
assert out[0].payload["title"] == "Test run"
|
|
assert fake.translate_calls == 0
|
|
|
|
|
|
def test_localize_caches_translations(monkeypatch):
|
|
loc, fake = _localizer(monkeypatch, table={"Review": "评审"})
|
|
for _ in range(3):
|
|
loc.localize_items([ConversationItem(kind="summary", payload={"title": "Review"})], "zh-Hans")
|
|
assert fake.translate_calls == 1 # translated once, cached thereafter
|