Update app.py

app.py

@@ -1,4 +1,6 @@
-# app.py (بدون camel_tools)
+# -*- coding: utf-8 -*-
+# app.py — CAMeL‑Lab GED→GEC (بدون camel_tools / بدون ged_tags في generate)
+
 import gradio as gr
 import torch
 import torch.nn.functional as F
@@ -6,33 +8,32 @@ from transformers import AutoTokenizer, BertForTokenClassification, MBartForCond
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
-# نماذج CAMeL‑Lab
-GED_MODEL_NAME = "CAMeL-Lab/camelbert-msa-qalb14-ged-13"   # أو qalb15
-GEC_MODEL_NAME = "CAMeL-Lab/arabart-qalb14-gec-ged-13"      # أو qalb15
+# 1) أسماء النماذج (يمكن ترقية qalb14 إلى qalb15 إن رغبت)
+GED_MODEL_NAME = "CAMeL-Lab/camelbert-msa-qalb14-ged-13"
+GEC_MODEL_NAME = "CAMeL-Lab/arabart-qalb14-gec-ged-13"
 
+# 2) تحميل النماذج والمُرمّزات
 ged_tokenizer = AutoTokenizer.from_pretrained(GED_MODEL_NAME)
 ged_model = BertForTokenClassification.from_pretrained(GED_MODEL_NAME).to(DEVICE).eval()
 
 gec_tokenizer = AutoTokenizer.from_pretrained(GEC_MODEL_NAME)
 gec_model = MBartForConditionalGeneration.from_pretrained(GEC_MODEL_NAME).to(DEVICE).eval()
 
+# 3) الدالة الأساسية
 def camel_gec_correct(text: str) -> str:
     if not text or not text.strip():
         return "⚠️ يرجى إدخال نص."
-    # 1) GED مباشرة على النص المُدخل
+
+    # (أ) GED مباشرة على النص
     inputs = ged_tokenizer([text], return_tensors="pt")
     inputs = {k: v.to(DEVICE) for k, v in inputs.items()}
     with torch.no_grad():
         logits = ged_model(**inputs).logits
-        probs = torch.softmax(logits, dim=-1).squeeze()[1:-1]
+        probs = F.softmax(logits, dim=-1).squeeze()[1:-1]  # تجاهل [CLS]/[SEP]
         pred_ids = torch.argmax(probs, -1)
     pred_ged_labels = [ged_model.config.id2label[i.item()] for i in pred_ids]
 
-    # 2) محاذاة وسوم GED مع تقطيع GEC
-    ged_label2ids = getattr(gec_model.config, "ged_label2id", None)
-    if ged_label2ids is None:
-        raise RuntimeError("Model config missing ged_label2id mapping.")
-
+    # (ب) محاذاة وسوم GED مع تقطيع GEC
     tokens, ged_labels = [], []
     for word, label in zip(text.split(), pred_ged_labels):
         w_toks = gec_tokenizer.tokenize(word)
@@ -40,29 +41,33 @@ def camel_gec_correct(text: str) -> str:
             tokens.extend(w_toks)
             ged_labels.extend([label] * len(w_toks))
 
-    input_ids = [gec_tokenizer.bos_token_id] + gec_tokenizer.convert_tokens_to_ids(tokens) + [gec_tokenizer.eos_token_id]
-    label_ids = [ged_label2ids.get("UC", 0)] + [ged_label2ids.get(l, ged_label2ids.get("<pad>", 0)) for l in ged_labels] + [ged_label2ids.get("UC", 0)]
-    attention_mask = [1] * len(input_ids)
+    # (ج) نبني تسلسل الإدخال لـ GEC (بدون ged_tags)
+    input_ids = [gec_tokenizer.bos_token_id] + \
+                gec_tokenizer.convert_tokens_to_ids(tokens) + \
+                [gec_tokenizer.eos_token_id]
 
-   
-with torch.no_grad():
-    generated = gec_model.generate(
-        torch.tensor([input_ids], device=DEVICE),
-        num_beams=5,
-        max_length=max(64, len(input_ids) + 20),
-        num_return_sequences=1,
-    )
-return gec_tokenizer.batch_decode(
-    generated, skip_special_tokens=True, clean_up_tokenization_spaces=False
-)[0]
+    # (د) توليد التصحيح القياسي
+    with torch.no_grad():
+        generated = gec_model.generate(
+            torch.tensor([input_ids], device=DEVICE),
+            num_beams=5,
+            max_length=max(128, len(input_ids) + 32),
+            num_return_sequences=1,
+        )
+    corrected = gec_tokenizer.batch_decode(
+        generated, skip_special_tokens=True, clean_up_tokenization_spaces=False
+    )[0]
+    return corrected
 
-def ui_correct(text): return camel_gec_correct(text)
+# 4) واجهة Gradio
+def ui_correct(text): 
+    return camel_gec_correct(text)
 
-with gr.Blocks(title="CAMeL-Lab Arabic GEC/GED") as demo:
-    gr.Markdown("### تصحيح نحوي عربي (CAMeL-Lab GED→GEC)")
-    inp = gr.Textbox(label="النص", lines=6, placeholder="أدخل النص العربي...")
+with gr.Blocks(title="المصحح النحوي عربي (CAMeL‑Lab GED→GEC)") as demo:
+    gr.Markdown("### تصحيح نحوي عربي باستخدام نماذج CAMeL‑Lab (GED ثم GEC)")
+    inp = gr.Textbox(label="النص", lines=8, placeholder="أدخل النص العربي هنا...")
     btn = gr.Button("تصحيح")
-    out = gr.Textbox(label="النص المصحح")
+    out = gr.Textbox(label="النص المصحح", lines=8)
     btn.click(fn=ui_correct, inputs=inp, outputs=out)
 
 if __name__ == "__main__":