Update app.py

app.py

@@ -1,68 +1,150 @@
-import streamlit as st
+from flask import Flask, render_template, request, redirect, url_for, session
+import os
+import json
+import http.client
+import google.generativeai as genai
+from dotenv import load_dotenv
 
-from llama_index.llms.gemini import Gemini
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
-import os 
-from llama_index.embeddings.gemini import GeminiEmbedding
-#os.environ["GOOGLE_API_KEY"] = GOOGLE_API_KEY
+load_dotenv()
 
-st.set_page_config(page_title="Chat with the Streamlit docs, powered by LlamaIndex", page_icon="🦙", layout="centered", initial_sidebar_state="auto", menu_items=None)
-#openai.api_key = st.secrets.openai_key
-st.title("Chat with the Streamlit docs, powered by LlamaIndex 💬🦙")
-st.info("Check out the full tutorial to build this app in our [blog post](https://blog.streamlit.io/build-a-chatbot-with-custom-data-sources-powered-by-llamaindex/)", icon="📃")
+app = Flask(__name__)
+app.secret_key = 'votre-cle-secrete'  # Remplacez par une clé forte
 
-if "messages" not in st.session_state.keys():  # Initialize the chat messages history
-    st.session_state.messages = [
-        {
-            "role": "assistant",
-            "content": "Ask me a question about Streamlit's open-source Python library!",
-        }
-    ]
+# Configure la clé API pour Google Generative AI
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
 
-@st.cache_resource(show_spinner=False)
-def load_data():
-    reader = SimpleDirectoryReader(input_dir="./data", recursive=True)
-    docs = reader.load_data()
-    Settings.llm = Gemini(
-        model="models/gemini-2.0-flash-exp",
-        temperature=1,
-        system_prompt="""You are an expert on 
-        the Streamlit Python library and your 
-        job is to answer technical questions. 
-        Assume that all questions are related 
-        to the Streamlit Python library. Keep 
-        your answers technical and based on 
-        facts – do not hallucinate features.""",
-    )
-    Settings.embed_model = GeminiEmbedding(
-    model="models/embedding-001", embed_batch_size=100
-    )
-    
-    index = VectorStoreIndex.from_documents(docs)
-    return index
+# Paramètres de sécurité
+safety_settings = [
+    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+    {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+    {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+]
+
+# Prompt système pour Mariam
+ss = """
+# Prompt System pour Mariam, IA conçu par youssouf 
+
+## Personnalité Fondamentale
+
+Mariam est une IA chaleureuse, bienveillante et authentique, conçue pour être une présence réconfortante et utile. Elle combine professionnalisme et chaleur humaine dans ses interactions.
 
+...
+"""  # Vous pouvez insérer le prompt complet ici
 
-index = load_data()
+# Création du modèle Gemini
+model = genai.GenerativeModel('gemini-2.0-flash-exp',
+                              tools='code_execution',
+                              safety_settings=safety_settings,
+                              system_instruction=ss)
 
-if "chat_engine" not in st.session_state.keys():  # Initialize the chat engine
-    st.session_state.chat_engine = index.as_chat_engine(
-        chat_mode="condense_question", verbose=True, streaming=True
-    )
+def perform_web_search(query):
+    conn = http.client.HTTPSConnection("google.serper.dev")
+    payload = json.dumps({"q": query})
+    headers = {
+        'X-API-KEY': '9b90a274d9e704ff5b21c0367f9ae1161779b573',
+        'Content-Type': 'application/json'
+    }
+    try:
+        conn.request("POST", "/search", payload, headers)
+        res = conn.getresponse()
+        data = json.loads(res.read().decode("utf-8"))
+        return data
+    except Exception as e:
+        print(f"Erreur lors de la recherche web : {e}")
+        return None
+    finally:
+        conn.close()
 
-if prompt := st.chat_input(
-    "Ask a question"
-):  # Prompt for user input and save to chat history
-    st.session_state.messages.append({"role": "user", "content": prompt})
+def format_search_results(data):
+    if not data:
+        return "Aucun résultat trouvé"
+    
+    result = ""
+    # Knowledge Graph
+    if 'knowledgeGraph' in data:
+        kg = data['knowledgeGraph']
+        result += f"### {kg.get('title', '')}\n"
+        result += f"*{kg.get('type', '')}*\n\n"
+        result += f"{kg.get('description', '')}\n\n"
+    # Organic Results
+    if 'organic' in data:
+        result += "### Résultats principaux:\n"
+        for item in data['organic'][:3]:
+            result += f"- **{item['title']}**\n"
+            result += f"  {item['snippet']}\n"
+            result += f"  [Lien]({item['link']})\n\n"
+    # People Also Ask
+    if 'peopleAlsoAsk' in data:
+        result += "### Questions fréquentes:\n"
+        for item in data['peopleAlsoAsk'][:2]:
+            result += f"- **{item['question']}**\n"
+            result += f"  {item['snippet']}\n\n"
+    return result
+
+def process_uploaded_file(file):
+    if file:
+        upload_dir = 'temp'
+        if not os.path.exists(upload_dir):
+            os.makedirs(upload_dir)
+        filepath = os.path.join(upload_dir, file.filename)
+        file.save(filepath)
+        try:
+            gemini_file = genai.upload_file(filepath)
+            return gemini_file
+        except Exception as e:
+            print(f"Erreur lors du téléchargement du fichier : {e}")
+            return None
+    return None
 
-for message in st.session_state.messages:  # Write message history to UI
-    with st.chat_message(message["role"]):
-        st.write(message["content"])
+# Initialisation de la session pour le chat
+def init_session():
+    if 'chat_history' not in session:
+        session['chat_history'] = []  # Liste de messages {'role': 'user'/'assistant', 'message': ...}
+    if 'web_search' not in session:
+        session['web_search'] = False
+
+@app.route('/', methods=['GET', 'POST'])
+def index():
+    init_session()
+    if request.method == 'POST':
+        # Mise à jour du toggle pour la recherche web
+        session['web_search'] = (request.form.get('toggle_web_search') == 'on')
+        prompt = request.form.get('prompt')
+        uploaded_file = request.files.get('file')
+        uploaded_gemini_file = None
+        if uploaded_file and uploaded_file.filename != '':
+            uploaded_gemini_file = process_uploaded_file(uploaded_file)
+        
+        # Ajout du message utilisateur dans l'historique
+        session['chat_history'].append({'role': 'user', 'message': prompt})
+        
+        # Si la recherche web est activée, on complète le prompt avec les résultats
+        if session.get('web_search'):
+            web_results = perform_web_search(prompt)
+            if web_results:
+                formatted_results = format_search_results(web_results)
+                prompt = f"Question: {prompt}\n\nRésultats de recherche web:\n{formatted_results}\n\nPourrais-tu analyser ces informations et me donner une réponse complète?"
+        
+        try:
+            # Envoi du message à Gemini
+            if uploaded_gemini_file:
+                response = model.send_message([uploaded_gemini_file, "\n\n", prompt])
+            else:
+                response = model.send_message(prompt)
+            assistant_response = response.text
+            # Ajout de la réponse de l'assistant dans l'historique
+            session['chat_history'].append({'role': 'assistant', 'message': assistant_response})
+        except Exception as e:
+            error_msg = f"Erreur lors de l'envoi du message : {e}"
+            session['chat_history'].append({'role': 'assistant', 'message': error_msg})
+        
+        session.modified = True
+        return redirect(url_for('index'))
+    
+    return render_template('index.html',
+                           chat_history=session.get('chat_history'),
+                           web_search=session.get('web_search'))
 
-# If last message is not from assistant, generate a new response
-if st.session_state.messages[-1]["role"] != "assistant":
-    with st.chat_message("assistant"):
-        response_stream = st.session_state.chat_engine.stream_chat(prompt)
-        st.write_stream(response_stream.response_gen)
-        message = {"role": "assistant", "content": response_stream.response}
-        # Add response to message history
-        st.session_state.messages.append(message)
+if __name__ == '__main__':
+    app.run(debug=True)