Release v0.8.4: AI配置中心与图库专注模式优化

Author: ChanMo

docs/release_notes.md

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+# Release Notes
+
+## v0.8.4 (2026-02-20)
+- 新增 AI Prompt 配置能力：支持在设置页自定义 system/user prompt、temperature、tags_limit，并支持重置默认值。
+- 新增 LLM 运行时配置：支持在设置页配置 `base_url`、`model_name`，并展示 API Key 是否已配置。
+- 图片详情页支持“仅本次覆盖生成”高级参数；元数据返回 `prompt_source` 与 `llm_source` 便于追踪来源。
+- Gallery 弹层新增单击图片专注模式：仅隐藏左下角 AI 标题/标签覆层，保留右下角工具按钮可操作。
+- 新增 `tests/test_prompt_config.py`，覆盖 prompt/llm 配置 API 与元数据来源优先级。

package-lock.json

@@ -1,6 +1,6 @@
 {
   "name": "tiklocal",
-  "version": "0.1.6",
+  "version": "0.8.4",
   "description": "A local media server that combines the features of TikTok and Pinterest",
   "scripts": {
     "build-css": "tailwindcss -i ./tiklocal/static/input.css -o ./tiklocal/static/output.css --watch",

package.json

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "TikLocal"
-version = "0.8.3"
+version = "0.8.4"
 description = "A local media server that combines the features of TikTok and Pinterest"
 authors = ["ChanMo <chan.mo@outlook.com>"]
 readme = "README.md"

pyproject.toml

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+import pytest
+
+from tiklocal.app import create_app
+from tiklocal.services.metadata import PromptConfigStore
+
+
+def _build_prompt_payload(enabled: bool = True, tags_limit: int = 5, temperature: float = 0.6):
+    return {
+        "enabled": enabled,
+        "system_prompt": "你是一个测试助手，只能输出 JSON。",
+        "user_prompt": "请给出标题和 {tags_limit} 个标签。",
+        "temperature": temperature,
+        "tags_limit": tags_limit,
+    }
+
+
+@pytest.fixture
+def client(tmp_path, monkeypatch):
+    media_root = tmp_path / "media"
+    media_root.mkdir(parents=True, exist_ok=True)
+    (media_root / "photo.jpg").write_bytes(b"fake-image")
+
+    data_root = tmp_path / "tiklocal-data"
+    monkeypatch.setenv("MEDIA_ROOT", str(media_root))
+    monkeypatch.setenv("TIKLOCAL_INSTANCE", str(data_root))
+    monkeypatch.setenv("OPENAI_API_KEY", "test-key")
+    monkeypatch.setenv("TIKLOCAL_LLM_MODEL", "test-model")
+
+    calls = []
+
+    def fake_generate(self, image_path, tags_limit=5, prompt_config=None):  # noqa: ARG001
+        calls.append({"tags_limit": tags_limit, "prompt_config": prompt_config or {}})
+        return {
+            "title": "测试标题",
+            "tags": ["测试"],
+            "model": self.model,
+            "provider": "openai",
+            "base_url": self.base_url or "",
+            "prompt_version": 2,
+            "prompt_hash": "deadbeef",
+        }
+
+    monkeypatch.setattr("tiklocal.services.metadata.CaptionService.generate", fake_generate)
+
+    app = create_app({"TESTING": True, "MEDIA_ROOT": media_root})
+    return app.test_client(), calls
+
+
+def test_prompt_config_store_roundtrip(tmp_path):
+    store_path = tmp_path / "prompt_config.json"
+    store = PromptConfigStore(store_path)
+
+    assert store.get() is None
+
+    saved = store.set(_build_prompt_payload())
+    assert saved["enabled"] is True
+    assert "updated_at" in saved
+
+    loaded = store.get()
+    assert loaded is not None
+    assert loaded["system_prompt"] == "你是一个测试助手，只能输出 JSON。"
+    assert loaded["tags_limit"] == 5
+
+    store.reset()
+    assert store.get() is None
+
+
+def test_prompt_config_api_crud(client):
+    test_client, _ = client
+
+    res = test_client.get("/api/ai/prompt-config")
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["active_profile"] == "default"
+
+    save_payload = _build_prompt_payload(enabled=True, tags_limit=7, temperature=0.8)
+    res = test_client.post("/api/ai/prompt-config", json=save_payload)
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["active_profile"] == "custom"
+    assert data["data"]["custom"]["tags_limit"] == 7
+    assert data["data"]["custom"]["enabled"] is True
+
+    res = test_client.post("/api/ai/prompt-config/reset")
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["active_profile"] == "default"
+    assert data["data"]["custom"] is None
+
+
+def test_prompt_config_api_validation(client):
+    test_client, _ = client
+    payload = _build_prompt_payload(temperature=2.5)
+
+    res = test_client.post("/api/ai/prompt-config", json=payload)
+    data = res.get_json()
+    assert res.status_code == 400
+    assert data["success"] is False
+    assert "temperature" in data["error"]
+
+
+def test_metadata_prompt_source_priority(client):
+    test_client, calls = client
+
+    custom_payload = _build_prompt_payload(enabled=True, tags_limit=7, temperature=0.7)
+    res = test_client.post("/api/ai/prompt-config", json=custom_payload)
+    assert res.status_code == 200
+
+    res = test_client.post(
+        "/api/image/metadata",
+        json={"uri": "photo.jpg", "force": True},
+    )
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["prompt_source"] == "custom"
+    assert calls[-1]["prompt_config"]["tags_limit"] == 7
+
+    override = {
+        "system_prompt": "仅本次覆盖",
+        "user_prompt": "请输出 1 到 {tags_limit} 个标签",
+        "temperature": 0.3,
+        "tags_limit": 3,
+    }
+    res = test_client.post(
+        "/api/image/metadata",
+        json={"uri": "photo.jpg", "force": True, "prompt_override": override},
+    )
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["prompt_source"] == "override"
+    assert calls[-1]["prompt_config"]["tags_limit"] == 3
+
+
+def test_llm_config_api_crud(client):
+    test_client, _ = client
+
+    res = test_client.get("/api/ai/llm-config")
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert "effective" in data["data"]
+    assert "has_api_key" in data["data"]
+
+    payload = {
+        "model_name": "gpt-test-custom",
+        "base_url": "https://example.com/v1",
+    }
+    res = test_client.post("/api/ai/llm-config", json=payload)
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["effective"]["model_name"] == "gpt-test-custom"
+    assert data["data"]["effective"]["base_url"] == "https://example.com/v1"
+    assert data["data"]["active_profile"] == "custom"
+
+    res = test_client.post("/api/ai/llm-config/reset")
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["active_profile"] == "default"
+
+
+def test_llm_config_api_validation(client):
+    test_client, _ = client
+    res = test_client.post(
+        "/api/ai/llm-config",
+        json={"model_name": "gpt-test", "base_url": "ftp://invalid-url"},
+    )
+    data = res.get_json()
+    assert res.status_code == 400
+    assert data["success"] is False
+    assert "base_url" in data["error"]
+
+
+def test_metadata_uses_custom_llm_settings(client):
+    test_client, _ = client
+
+    res = test_client.post(
+        "/api/ai/llm-config",
+        json={"model_name": "gpt-override", "base_url": "https://custom.example/v1"},
+    )
+    assert res.status_code == 200
+
+    res = test_client.post("/api/image/metadata", json={"uri": "photo.jpg", "force": True})
+    data = res.get_json()
+    assert res.status_code == 200
+    assert data["success"] is True
+    assert data["data"]["model"] == "gpt-override"
+    assert data["data"]["base_url"] == "https://custom.example/v1"
+    assert data["data"]["llm_source"] == "custom"