Update app.py

app.py

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+from llama_index.core import Settings, VectorStoreIndex, StorageContext, load_index_from_storage
+from llama_index.core.embeddings import BaseEmbedding
+from llama_index.llms.mistralai import MistralAI
+from llama_index.core.node_parser import SentenceSplitter
+from llama_index.core import SimpleDirectoryReader
+from llama_index.core import PromptTemplate
+# from pydantic import PrivateAttr
+# import requests
+from typing import List, Optional, Union
+# from llama_index.core.embeddings.utils import BaseEmbedding  
+from llama_index.embeddings.huggingface import HuggingFaceInferenceAPIEmbedding
+# from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+import streamlit as st
+import pickle
+
+
+mistral_api_key = os.getenv("mistral_api_key")
+
+class QASystem:
+    def __init__(self, 
+                 mistral_api_key: str = mistral_api_key,
+                 data_dir: str = "./data",
+                 storage_dir: str = "./index_llama_136_multilingual-e5-large",
+                 model_temperature: float = 0.002):
+        self.data_dir = data_dir
+        self.storage_dir = storage_dir
+        
+        # Initialize embedding model with API
+        # api_key = 
+        self.embedding_model = HuggingFaceInferenceAPIEmbedding(
+                                    model_name="intfloat/multilingual-e5-large",
+                                    )
+        # self.embedding_model = HuggingFaceEmbedding(model_name="intfloat/multilingual-e5-large",trust_remote_code=True)
+        
+        self.llm = MistralAI(
+            model="mistral-large-latest", 
+            api_key=mistral_api_key, 
+            temperature=model_temperature,
+            max_tokens=1024
+        )
+        self._configure_settings()
+
+        # self.create_index()
+
+        self.index = self.load_index()  # Define index here 
+        
+    def _configure_settings(self):
+        Settings.llm = self.llm
+        Settings.embed_model = self.embedding_model
+
+    def create_index(self):
+        print("creating index")
+        documents = SimpleDirectoryReader(self.data_dir).load_data()
+        node_parser = SentenceSplitter(chunk_size=206, chunk_overlap=0)
+        nodes = node_parser.get_nodes_from_documents(documents, show_progress=True)
+        
+        sentence_index = VectorStoreIndex(nodes, show_progress=True)
+        sentence_index.storage_context.persist(self.storage_dir)
+
+        # # Save the index to a pickle file  
+        # with open(f"{self.storage_dir}/index.pkl", "wb") as f:  
+        #     pickle.dump(sentence_index, f) 
+        
+        return sentence_index
+    
+    def load_index(self):
+        # with open(f'{self.storage_dir}/index.pkl', 'rb') as f:  
+        #     sentence_index = pickle.load(f)
+
+        storage_context = StorageContext.from_defaults(persist_dir=self.storage_dir)
+        return load_index_from_storage(storage_context, embed_model=self.embedding_model)
+    
+    def create_query_engine(self):
+        template = """
+        استخدم المعلومات التالية للإجابة على السؤال في النهاية. إذا لم تكن تعرف الإجابة، فقل فقط أنك لا تعرف، لا تحاول اختلاق إجابة.
+
+        {context_str}
+        السؤال: {query_str}
+        الإجابة بالعربية:
+        """
+        prompt = PromptTemplate(template=template)
+        
+        return self.index.as_query_engine(
+            similarity_top_k=10,
+            streaming=True,
+            text_qa_template=prompt,
+            response_mode="compact", #tree_summarize, simple_summarize, compact
+            embed_model=self.embedding_model
+        )
+    
+    def query(self, question: str):
+        query_engine = self.create_query_engine()
+        response = query_engine.query(question)
+        return  response#.print_response_stream()
+
+
+# Utilisation de singleton pour éviter les réinitialisations multiples  
+@st.cache_resource  
+def get_qa_system():  
+    return QASystem() 
+
+def main():  
+    st.markdown("""  
+    <style>  
+        @import url('https://fonts.googleapis.com/css2?family=Noto+Kufi+Arabic:wght@100;200;300;400;500;600;700;800;900&display=swap');
+
+        /* Application globale de la police */
+        * {
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+        
+        body {  
+            text-align: right;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }  
+        
+        /* Style pour tous les textes */
+        p, div, span, button, input, label, h1, h2, h3, h4, h5, h6 {
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+
+        /* Titre principal avec taille réduite */
+        h1 {
+            font-size: 1.2em !important;
+            margin-bottom: 0.5em !important;
+            text-align: center;
+            padding: 0.3px;
+        }
+
+        .css-1h9b9rq.e1tzin5v0 {
+            direction: rtl; 
+            text-align: right;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }  
+        
+        /* Style pour l'expandeur */
+        .streamlit-expanderContent, div[data-testid="stExpander"] {
+            direction: rtl !important;
+            text-align: right !important;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+        
+        /* Style pour les boutons de l'expandeur */
+        button[kind="secondary"] {
+            direction: rtl !important;
+            text-align: right !important;
+            width: 100% !important;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+            font-weight: 30 !important;
+        }
+        
+        /* Style pour tous les éléments de texte */
+        p, div {
+            direction: rtl !important;
+            text-align: right !important;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+        
+        /* Style pour les bullet points */
+        ul, li {
+            direction: rtl !important;
+            text-align: right !important;
+            margin-right: 20px !important;
+            margin-left: 0 !important;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+        
+        .stTextInput, .stButton {  
+            margin-left: auto;  
+            margin-right: 0;  
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }  
+        
+        .stTextInput {  
+            width: 100% !important;   
+            direction: rtl; 
+            text-align: right;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+        
+        /* Force RTL sur tous les conteneurs */
+        .element-container, .stMarkdown {
+            direction: rtl !important;
+            text-align: right !important;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+        
+        /* Style spécifique pour l'expandeur des sources */
+        .css-1fcdlhc, .css-1629p8f {
+            direction: rtl !important;
+            text-align: right !important;
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+
+        /* Style pour le titre */
+        .stTitle {
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+            font-weight: 700 !important;
+        }
+
+        /* Style pour les boutons */
+        .stButton>button {
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+            font-weight: 500 !important;
+        }
+
+        /* Style pour les champs de texte */
+        .stTextInput>div>div>input {
+            font-family: 'Noto Kufi Arabic', sans-serif !important;
+        }
+    </style>  
+    """, unsafe_allow_html=True)  
+    
+    st.title("هذا تطبيق للاجابة عن الاسئلة المتعلقة بالقانون المغربي ")  
+    st.title("حاليا يضم 136 قانونا")
+    
+    qa_system = get_qa_system()  
+    
+    question = st.text_input("اطرح سؤالك :",placeholder=None)  
+    
+    if st.button("بحث"):  
+        if question:  
+            response_container = st.empty()  
+            def stream_response(token):  
+                if 'current_response' not in st.session_state:  
+                    st.session_state.current_response = ""  
+                st.session_state.current_response += token  
+                response_container.markdown(st.session_state.current_response, unsafe_allow_html=True)  
+            
+            try:  
+                query_engine = qa_system.create_query_engine()  
+                st.session_state.current_response = ""  
+                response = query_engine.query(question)  
+                
+                full_response = ""  
+                for token in response.response_gen:  
+                    full_response += token  
+                    stream_response(token)  
+                
+                if hasattr(response, 'source_nodes'):  
+                    st.markdown("""
+                        <div style="direction: rtl !important; text-align: right !important; font-family: 'Noto Kufi Arabic', sans-serif !important;">
+                            <div class="streamlit-expanderHeader">
+                                المصادر
+                            </div>
+                        </div>
+                    """, unsafe_allow_html=True)
+                    with st.expander(""):  
+                        for node in response.source_nodes:  
+                            st.markdown(f"""
+                                <div style="direction: rtl !important; text-align: right !important; font-family: 'Noto Kufi Arabic', sans-serif !important;">
+                                    <p style="text-align: right !important;">مصادر الجواب : {node.metadata.get('file_name', 'Unknown')}</p>
+                                    <p style="text-align: right !important;">Extrait: {node.text[:]}</p>
+                                </div>
+                            """, unsafe_allow_html=True)
+            except Exception as e:  
+                st.error(f"Une erreur s'est produite : {e}")  
+
+if __name__ == "__main__":  
+    main()