feat: i18n / translations

gliner_api/frontend.py

@@ -7,13 +7,17 @@
 from stamina import retry_context
 
 from gliner_api.config import Config, get_config
+from gliner_api.translations import Translations
 
 config: Config = get_config()
 client: AsyncClient = AsyncClient(
     base_url=f"http://localhost:{config.port}",
     headers={"Authorization": f"Bearer {config.api_key}"} if config.api_key is not None else None,
 )
 
+languages: dict[str, dict[str, str]] = Translations().model_dump()["languages"]
+i18n: gr.I18n = gr.I18n(**languages)
+
 
 async def call_invoke(
     text: str,
@@ -92,45 +96,45 @@ async def call_invoke(
     fn=call_invoke,
     inputs=[
         gr.Textbox(
-            label="Input Text",
-            placeholder="Enter text...\nYou can also paste longer texts here.",
+            label=i18n("input_label"),
+            placeholder=i18n("input_placeholder"),
             lines=3,
             max_lines=15,
             value="Steve Jobs founded Apple Inc. in Cupertino, CA on April 1, 1976.",
-            info="Text to analyze for named entities.",
+            info=i18n("input_info"),
         ),
         gr.Slider(
-            label="Threshold",
+            label=i18n("slider_label"),
             minimum=0.0,
             maximum=1.0,
             step=0.05,
             value=config.default_threshold,
-            info="Minimum confidence score for entities to be included in the response.",
+            info=i18n("slider_info"),
         ),
         gr.Dropdown(
-            label="Entity Types",
+            label=i18n("dropdown_label"),
             choices=config.default_entities,
             multiselect=True,
             value=config.default_entities,
             allow_custom_value=True,
-            info="Select entity types to detect. Add custom entity types as needed.",
+            info=i18n("dropdown_info"),
         ),
         gr.CheckboxGroup(
-            label="Additional Options (Advanced)",
+            label=i18n("options_label"),
             choices=[
-                ("Enable deep NER mode", "deep_ner"),
-                ("Enable multi-label classification", "multi_label"),
+                (i18n("options_deep_ner"), "deep_ner"),
+                (i18n("options_multi_label"), "multi_label"),
             ],
             value=[],
-            info="Deep NER: hierarchical entity detection for nested entities. Multi-label: entities can belong to multiple types.",
+            info=i18n("options_info"),
         ),
     ],
     outputs=[
         gr.HighlightedText(
-            label="Detected Entities",
+            label=i18n("outputs_highlighted_text"),
         ),
-        gr.Label(label="Inference Time"),
-        gr.JSON(label="Raw Response Body"),
+        gr.Label(label=i18n("outputs_label")),
+        gr.JSON(label=i18n("outputs_json")),
     ],
     title="GLiNER API - Frontend",
     description=description,
@@ -176,5 +180,4 @@ async def call_invoke(
     api_name=False,
     flagging_mode="never",
     theme=gr_themes.Base(primary_hue="teal"),
-    submit_btn="Detect Entities",
 )

gliner_api/translations.py

@@ -0,0 +1,58 @@
+from pydantic import BaseModel, Field
+from pydantic_settings import (
+    BaseSettings,
+    JsonConfigSettingsSource,
+    PydanticBaseSettingsSource,
+    SettingsConfigDict,
+)
+
+
+class Translations(BaseSettings):
+    languages: dict[str, "Language"] = Field(
+        default_factory=dict,
+    )
+
+    model_config = SettingsConfigDict(
+        json_file="translations.json",
+        json_file_encoding="utf-8",
+    )
+
+    @classmethod
+    def settings_customise_sources(
+        cls,
+        settings_cls: type[BaseSettings],
+        init_settings: PydanticBaseSettingsSource,
+        env_settings: PydanticBaseSettingsSource,
+        dotenv_settings: PydanticBaseSettingsSource,
+        file_secret_settings: PydanticBaseSettingsSource,
+    ) -> tuple[PydanticBaseSettingsSource, ...]:
+        return (
+            init_settings,
+            JsonConfigSettingsSource(settings_cls),
+        )
+
+
+class Language(BaseModel):
+    # TextInput properties
+    input_label: str
+    input_info: str
+    input_placeholder: str
+
+    # ThresholdSlider properties
+    slider_label: str
+    slider_info: str
+
+    # EntityDropdown properties
+    dropdown_label: str
+    dropdown_info: str
+
+    # OptionsCheckboxGroup properties
+    options_label: str
+    options_info: str
+    options_deep_ner: str
+    options_multi_label: str
+
+    # OutputsLabels properties
+    outputs_highlighted_text: str
+    outputs_label: str
+    outputs_json: str

main.py

@@ -29,14 +29,15 @@ async def close_metrics_server():
         from fastapi.staticfiles import StaticFiles
         from gradio import mount_gradio_app
 
-        from gliner_api.frontend import client, interface
+        from gliner_api.frontend import client, i18n, interface
 
         app.mount("/static", StaticFiles(directory="static"), name="static")
         mount_gradio_app(
             app,
             interface,
             path="",
             show_api=False,
+            i18n=i18n,
         )
 
         @app.on_event("shutdown")

translations.json

@@ -0,0 +1,36 @@
+{
+  "languages": {
+    "de": {
+      "dropdown_info": "Wählen Sie zu erkennende Entitäts-Klassen aus. Fügen Sie bei Bedarf benutzerdefinierte Klassen hinzu.",
+      "dropdown_label": "Entitäts-Klassen",
+      "input_info": "Text, der auf Entitäten analysiert werden soll.",
+      "input_label": "Eingabe",
+      "input_placeholder": "Text eingeben...\nSie können auch längere Texte hier einfügen.",
+      "options_deep_ner": "Deep NER aktivieren",
+      "options_info": "Deep NER: Hierarchische Entitätserkennung für verschachtelte Entitäten.\nMulti-Label: Entitäten können mehreren Klassen angehören.",
+      "options_label": "Zusätzliche Optionen (erweitert)",
+      "options_multi_label": "Multi-Label-Klassifikation aktivieren",
+      "outputs_highlighted_text": "Erkannte Entitäten",
+      "outputs_json": "Ursprüngliche Ausgabe",
+      "outputs_label": "Inferenzzeit",
+      "slider_info": "Mindest-Konfidenzwert für die Einbeziehung erkannter Entitäten in die Ausgabe.",
+      "slider_label": "Konfidenzgrenze"
+    },
+    "en": {
+      "dropdown_info": "Select entity types to detect. Add custom entity types as needed.",
+      "dropdown_label": "Entity Types",
+      "input_info": "Text to analyze for named entities.",
+      "input_label": "Input Text",
+      "input_placeholder": "Enter text...\nYou can also paste longer texts here.",
+      "options_deep_ner": "Enable Deep NER mode",
+      "options_info": "Deep NER: hierarchical entity detection for nested entities.\nMulti-label: entities can belong to multiple types.",
+      "options_label": "Additional Options (Advanced)",
+      "options_multi_label": "Enable multi-label classification",
+      "outputs_highlighted_text": "Detected Entities",
+      "outputs_json": "Raw Response Body",
+      "outputs_label": "Inference Time",
+      "slider_info": "Minimum confidence score for entities to be included in the response.",
+      "slider_label": "Confidence Threshold"
+    }
+  }
+}