predict lang fix2

app.py

@@ -1,21 +1,37 @@
 import gradio as gr
 from huggingface_hub import hf_hub_download
 import fasttext
+import re
 
 REPO = "NbAiLab/nb-nbnn-lid"
 FILE = "nb-nbnn-lid.ftz"
+
 MODEL_PATH = hf_hub_download(repo_id=REPO, filename=FILE)
 ft = fasttext.load_model(MODEL_PATH)
-MAP = {"__label__nob": "nb", "__label__nno": "nn"}
 
-def classify(text):
-    if not text or not text.strip():
+MAP = {"__label__nob": "nb", "__label__nno": "nn"}  # Bokmål / Nynorsk
+
+def _clean(text: str) -> str:
+    # fastText expects ONE line: strip, collapse whitespace, remove newlines
+    text = text or ""
+    text = re.sub(r"[\r\n\t]+", " ", text).strip()
+    # optional: shrink multiple spaces
+    text = re.sub(r"\s{2,}", " ", text)
+    return text
+
+def classify(text: str) -> str:
+    t = _clean(text)
+    if not t:
         return ""
-    label, score = ft.predict(text.strip())
+    label, score = ft.predict(t)  # single text → top-1 label
     return MAP.get(label[0], "nb")
 
-demo = gr.Interface(fn=classify, inputs="text", outputs="text",
-                    title="Bokmål / Nynorsk classifier")
+demo = gr.Interface(
+    fn=classify,
+    inputs=gr.Textbox(label="Text"),
+    outputs=gr.Textbox(label="Label (nb or nn)"),
+    title="Bokmål / Nynorsk classifier"
+)
 
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -1,3 +1,4 @@
 gradio
 huggingface_hub
-fasttext-wheel
+fasttext-wheel==0.9.2
+numpy<2.0