Spaces:
Sleeping
Sleeping
New: Add lang check
Browse files
app.py
CHANGED
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@@ -1,6 +1,8 @@
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import gradio as gr
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import fasttext
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import html
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from huggingface_hub import hf_hub_download
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# Projektspezifische Module
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@@ -23,17 +25,44 @@ lid_path = hf_hub_download(
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lid_model = fasttext.load_model(lid_path)
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lang_labels, lang_probs = lid_model.predict(review)
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lang_label = lang_labels[0]
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lang_prob = float(lang_probs[0])
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if not review:
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# immer zwei Outputs zurückgeben
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return "<i>Please enter a review.</i>", {}
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@@ -47,8 +76,10 @@ def predict(review: str, mode: str):
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json_out = {
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"review": review,
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"mode": mode,
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}
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return html_out, json_out
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import gradio as gr
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import fasttext
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import html
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import numpy as np
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import types
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from huggingface_hub import hf_hub_download
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# Projektspezifische Module
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lid_model = fasttext.load_model(lid_path)
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# robustes predict mit NumPy-2-Fix + Fallback, falls fastText nur Labels liefert
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def _predict_np2_compat(self, text, k=1, threshold=0.0, on_unicode_error='strict'):
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out = self.f.predict(text, k, threshold, on_unicode_error)
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# Fälle:
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# 1) (labels, probs)
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# 2) labels-only (einige Builds/SWIG-Versionen)
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if isinstance(out, tuple) and len(out) == 2:
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labels, probs = out
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else:
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labels = out
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# sinnvolle Defaults, falls keine Wahrscheinlichkeiten vorliegen
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if isinstance(labels, (list, tuple)):
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probs = [1.0] * len(labels)
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else:
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labels = [labels]
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probs = [1.0]
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return labels, np.asarray(probs) # np.asarray statt np.array(copy=False)
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# Instanz patchen
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lid_model.predict = types.MethodType(_predict_np2_compat, lid_model)
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### Check if lang is english ##############################################
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def is_eng(review: str):
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lang_labels, lang_probs = lid_model.predict(review)
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lang_label = lang_labels[0]
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lang_prob = float(lang_probs[0])
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return lang_label[1] == "__lang_en__", lang_prob
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### Do actual prediction ##############################################
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def predict(review: str, mode: str):
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review = (review or "").strip()
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review_is_eng, review_is_eng_prob = is_eng(review)
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if not review:
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# immer zwei Outputs zurückgeben
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return "<i>Please enter a review.</i>", {}
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json_out = {
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"review": review,
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"mode": mode,
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"is_en": {
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"is": review_is_eng,
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"prob": review_is_eng_prob
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}
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}
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return html_out, json_out
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