app.py

import streamlit as st
import google.generativeai as genai
import os
from dotenv import load_dotenv
import http.client
import json

load_dotenv()

# Configure the API key
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

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"},
]

model = genai.GenerativeModel('gemini-2.0-flash-exp', tools='code_execution',
                            safety_settings=safety_settings,
                            system_instruction="Tu es un assistant intelligent. ton but est d'assister au mieux que tu peux. tu as été créé par Aenir et tu t'appelles Mariam")

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:
        st.error(f"Erreur lors de la recherche web : {e}")
        return None
    finally:
        conn.close()

def format_search_results(data):
    if not data:
        return "Aucun résultat trouvé"
    
    result = ""
    
    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"
    
    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"
    
    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 role_to_streamlit(role):
    if role == "model":
        return "assistant"
    else:
        return role

# Add chat and settings to session state
if "chat" not in st.session_state:
    st.session_state.chat = model.start_chat(history=[])
if "web_search" not in st.session_state:
    st.session_state.web_search = False

# Display Form Title
st.title("Mariam AI!")

# Settings section
with st.sidebar:
    st.title("Paramètres")
    st.session_state.web_search = st.toggle("Activer la recherche web", value=st.session_state.web_search)

# File upload section
uploaded_file = st.file_uploader("Télécharger un fichier (image/document)", type=['jpg', 'mp4', 'mp3', 'jpeg', 'png', 'pdf', 'txt'])

# Display chat messages
for message in st.session_state.chat.history:
    with st.chat_message(role_to_streamlit(message.role)):
        st.markdown(message.parts[0].text)

# Function to handle file upload with Gemini
def process_uploaded_file(file):
    if file is not None:
        with open(os.path.join("temp", file.name), "wb") as f:
            f.write(file.getbuffer())
        try:
            gemini_file = genai.upload_file(os.path.join("temp", file.name))
            return gemini_file
        except Exception as e:
            st.error(f"Erreur lors du téléchargement du fichier : {e}")
            return None

# Chat input and processing
if prompt := st.chat_input("Hey?"):
    uploaded_gemini_file = None
    if uploaded_file:
        uploaded_gemini_file = process_uploaded_file(uploaded_file)
    
    # Display user message
    st.chat_message("user").markdown(prompt)
    print(prompt)
    print("------------")
    try:
        # Perform web search if enabled
        web_results = None
        if st.session_state.web_search:
            with st.spinner("Recherche web en cours..."):
                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?"""
        
        # Add user message to chat history first
        response_text = ""
        
        # Display assistant message with streaming
        with st.chat_message("assistant"):
            message_placeholder = st.empty()
            
            # Send message to chat with streaming
            if uploaded_gemini_file:
                response = st.session_state.chat.send_message([uploaded_gemini_file, "\n\n", prompt], stream=True)
            else:
                response = st.session_state.chat.send_message(prompt, stream=True)
            
            # Process the streaming response
            for chunk in response:
                if chunk.text:
                    response_text += chunk.text
                    # Update the message placeholder with the accumulated response
                    message_placeholder.markdown(response_text + "▌")
            
            # Remove the cursor and display final response
            message_placeholder.markdown(response_text)
    
    except Exception as e:
        st.error(f"Erreur lors de l'envoi du message : {e}")

# Create temp directory
os.makedirs("temp", exist_ok=True)