Upload app.py

app.py

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+import gradio as gr
+from langchain_community.vectorstores import Chroma
+from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain.chains import RetrievalQA
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.document_loaders import PyPDFLoader
+import os
+import shutil
+
+CHROMA_PATH = "chroma_db"
+EMBED_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
+
+def load_and_prepare_file(file_path):
+    # تنظيف المجلد القديم
+    if os.path.exists(CHROMA_PATH):
+        shutil.rmtree(CHROMA_PATH)
+
+    # تحميل وتقطيع النص
+    loader = PyPDFLoader(file_path)
+    pages = loader.load_and_split()
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
+    chunks = text_splitter.split_documents(pages)
+
+    # إنشاء قاعدة بيانات المتجهات
+    embedding_function = HuggingFaceEmbeddings(model_name=EMBED_MODEL)
+    vectordb = Chroma.from_documents(chunks, embedding_function, persist_directory=CHROMA_PATH)
+    vectordb.persist()
+    return "✅ تم تجهيز الملف بنجاح، يمكنك الآن طرح الأسئلة."
+
+def answer_question(question):
+    embedding_function = HuggingFaceEmbeddings(model_name=EMBED_MODEL)
+    vectordb = Chroma(persist_directory=CHROMA_PATH, embedding_function=embedding_function)
+    retriever = vectordb.as_retriever()
+    qa = RetrievalQA.from_chain_type(llm="gpt2", retriever=retriever)
+    result = qa.run(question)
+    return result
+
+with gr.Blocks() as demo:
+    gr.Markdown("### 📚 Smart PDF Assistant - مساعد PDF الذكي")
+
+    file_input = gr.File(label="📄 ارفع ملف PDF", type="filepath")
+    upload_output = gr.Textbox(label="نتيجة الرفع")
+    upload_button = gr.Button("تحميل ومعالجة الملف")
+
+    question_input = gr.Textbox(label="✍️ اكتب سؤالك هنا")
+    answer_output = gr.Textbox(label="🔎 الإجابة")
+
+    upload_button.click(load_and_prepare_file, inputs=file_input, outputs=upload_output)
+    question_input.submit(answer_question, inputs=question_input, outputs=answer_output)
+
+demo.launch()