New: Add automatic translation

app.py

@@ -24,6 +24,8 @@ from safetensors.torch import load_file      # Sicheres & schnelles Laden von We
 # UI / Serving
 import gradio as gr               # Web-UI für Demo/Spaces
 
+import deepl
+
 # Projektspezifische Module
 from lib.bert_regressor import BertMultiHeadRegressor
 from lib.bert_regressor_utils import (
@@ -44,6 +46,7 @@ REPO_ID    = "ziem-io/deberta_flavour_regressor_multi_head"
 # (optional) falls das Model-Repo privat ist:
 HF_TOKEN = os.getenv("HF_TOKEN")  # in Space-Secrets hinterlegen
 MODEL_FILE = os.getenv("MODEL_FILE")  # in Space-Secrets hinterlegen
+DEEPL_API_KEY = os.getenv("DEEPL_API_KEY")  # in Space-Secrets hinterlegen
 
 ##################################################################################
 
@@ -80,11 +83,18 @@ def is_eng(text: str, min_chars: int = 6, threshold: float = 0.1):
     lang, prob = ID.classify(t)  # prob ∈ [0,1]
     return (lang == "en" and prob >= threshold), float(prob)
 
+def translate_en(text: str, target_lang: str = "EN-GB"):
+    deepl_client = deepl.Translator(DEEPL_API_KEY)
+    translated_text = deepl_client.translate_text(text, target_lang=target_lang)
+    return translated_text
+
 ### Do actual prediction #########################################################
 @spaces.GPU(duration=10)  # Sekunden GPU-Zeit pro Call
 def predict(review: str):
 
     review = (review or "").strip()
+    is_translated = False
+    html_out = ""
 
     # Abort if no text if given
     if not review:
@@ -96,11 +106,9 @@ def predict(review: str):
 
     # Abort if text is not english
     if not review_is_eng:
-        # immer zwei Outputs zurückgeben
-        return "Currently, only English reviews are supported.", {
-            "is_eng": review_is_eng,
-            "prob": review_lang_prob
-        }
+        review = translate_en(review)
+        html_out += "<b>Your text has been automatically translated.</b>"
+        is_translated = True
     
     prediction_flavours = {}
     prediction_flavours_list = [0, 0, 0, 0, 0, 0, 0, 0]
@@ -111,9 +119,7 @@ def predict(review: str):
     prediction_flavours_list = list(prediction_flavours.values())
     t_end_flavours = time.time()
 
-    #html_out = f"<b>{html.escape(review)}</b>"
-
-    html_out = build_svg_with_values(prediction_flavours_list)
+    html_out += build_svg_with_values(prediction_flavours_list)
 
     json_out = {
         "results": [{
@@ -127,6 +133,7 @@ def predict(review: str):
         "review": review,
         "model": MODEL_FILE,
         "device": device,
+        "is_translated": is_translated,
         "duration": round((t_end_flavours - t_start_flavours), 3),
     }
 
@@ -163,7 +170,7 @@ with gr.Blocks(css=custom_css) as demo:
     with gr.Row():  # alles nebeneinander
         with gr.Column(scale=1):  # linke Seite: Input
             review_box = gr.Textbox(
-                label="Whisky Review (English only)",
+                label="Whisky Review",
                 lines=8,
                 placeholder="Enter whisky review",
                 value=random_text(),

requirements.txt

@@ -8,4 +8,5 @@ sentencepiece
 tiktoken
 accelerate>=0.30
 spaces
-langid
+langid
+deepl