Update app.py

app.py

@@ -1,31 +1,30 @@
-from fastapi import FastAPI, Query
-from langchain_community.vectorstores import Chroma
-from langchain_community.embeddings import HuggingFaceEmbeddings
-from together import Together
 import os
+import gradio as gr
+from rag_system import RAGSystem  # تأكد أن الملف اسمه rag_system.py وموجود في نفس المجلد
 
-embedding = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
-vectordb = Chroma(persist_directory="chroma_db", embedding_function=embedding)
+# --- تحميل النظام ---
+rag = RAGSystem(
+    vector_db_path="vector_db",  # تأكد أن قاعدة البيانات مضغوطة ومرفوعة ضمن files
+    model_name="meta-llama/Llama-3-8b-chat-hf",
+    embedding_model_name="sentence-transformers/all-mpnet-base-v2"
+)
 
-TOGETHER_API_KEY = os.getenv("TOGETHER_API_KEY", "")
-client = Together(api_key=TOGETHER_API_KEY)
+rag.load_vectorstore()
+rag.load_llm()
+rag.get_prompt_template()
 
-def call_llama(prompt: str):
-    response = client.chat.completions.create(
-        model="meta-llama/Llama-3-8b-chat-hf",
-        messages=[
-            {"role": "system", "content": "You are a helpful assistant."},
-            {"role": "user", "content": prompt}
-        ]
-    )
-    return response.choices[0].message.content
+# --- دالة الاستجابة ---
+def ask_question_interface(question):
+    return rag.ask_question(question)
 
-app = FastAPI()
+# --- واجهة Gradio ---
+demo = gr.Interface(
+    fn=ask_question_interface,
+    inputs=gr.Textbox(label="Ask a question about the ECC Guide"),
+    outputs=gr.Textbox(label="Answer"),
+    title="ECC Cybersecurity Assistant",
+    description="Ask questions based on the Essential Cybersecurity Controls (ECC) Implementation Guide issued by the NCA (Saudi Arabia).",
+)
 
-@app.get("/ask")
-async def ask(q: str = Query(..., description="Your question")):
-    docs = vectordb.similarity_search(q, k=3)
-    context = "\n".join([doc.page_content for doc in docs])
-    final_prompt = f"Use the context below to answer the question.\n\nContext:\n{context}\n\nQuestion: {q}"
-    answer = call_llama(final_prompt)
-    return {"answer": answer}
+if __name__ == "__main__":
+    demo.launch()