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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+pdf_index.faiss filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+from sentence_transformers import SentenceTransformer
+import faiss
+import numpy as np
+import os
+
+# 1. تحميل النموذج والفهرس
+model = SentenceTransformer('distiluse-base-multilingual-cased-v2')
+index = faiss.read_index("pdf_index.faiss")
+
+# 2. تحميل النصوص
+with open("chunks.txt", "r", encoding="utf-8") as f:
+    chunks = f.read().split("\n---\n")
+
+# 3. وظيفة البحث
+def answer_question(question):
+    # توليد التضمين
+    question_embedding = model.encode([question])
+    
+    # البحث في الفهرس
+    distances, indices = index.search(question_embedding, 3)
+    
+    # استخراج أفضل نتيجة
+    best_answer = chunks[indices[0][0]]
+    
+    return best_answer[:1000]  # تحديد طول الإجابة
+
+# 4. واجهة Gradio
+with gr.Blocks() as demo:
+    gr.Markdown("## نظام الأسئلة والأجوبة الذكي من PDF")
+    question = gr.Textbox(label="اطرح سؤالك")
+    answer = gr.Textbox(label="الإجابة", lines=5)
+    submit = gr.Button("إرسال")
+    
+    submit.click(answer_question, inputs=question, outputs=answer)
+
+demo.launch()

pdf_index.faiss

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0649089db69891b683491fdb44420e30d5e8d5fd5c0d3bac4d8d71565b42df7e
+size 2359341

requirements.txt

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+transformers
+sentence-transformers
+faiss-cpu
+gradio