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app.py

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+import os
+import streamlit as st
+from langchain_community.vectorstores import FAISS
+from langchain_community.embeddings import HuggingFaceEmbeddings
+
+from langchain_huggingface import HuggingFaceEndpoint
+
+from langchain.prompts import PromptTemplate
+from langchain.schema.runnable import RunnablePassthrough
+from langchain.chains import LLMChain
+
+from huggingface_hub import login
+login(token=st.secrets["HF_TOKEN"])
+
+from langchain_community.document_loaders import TextLoader
+from langchain_text_splitters import CharacterTextSplitter
+from langchain_community.document_loaders import PyPDFLoader
+from langchain.chains import RetrievalQA
+from langchain.prompts import PromptTemplate
+from langchain.embeddings.huggingface import HuggingFaceEmbeddings
+
+db = FAISS.load_local("faiss_index", HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L12-v2'),allow_dangerous_deserialization=True)
+
+
+
+retriever = db.as_retriever(
+    search_type="mmr",
+    search_kwargs={'k': 1}
+)
+
+
+prompt_template = """
+### [INST]
+Instruction: You are a Q&A assistant. Your goal is to answer questions as accurately as possible based on the instructions and context provided without using prior knowledge.You answer in FRENCH
+        Analyse carefully the context and provide a direct answer based on the context. If the user said Bonjour or Hello  your only answer will be  Hi! comment puis-je vous aider?
+Answer in french only
+        
+{context}
+Vous devez répondre aux questions en français.
+
+### QUESTION:
+{question}
+[/INST]
+Answer in french only
+ Vous devez répondre aux questions en français.
+
+ """
+
+repo_id = "mistralai/Mistral-7B-Instruct-v0.3"
+
+mistral_llm = HuggingFaceEndpoint(
+    repo_id=repo_id, max_length=2048, temperature=0.05, huggingfacehub_api_token=st.secrets["HF_TOKEN"]
+)
+
+# Create prompt from prompt template
+prompt = PromptTemplate(
+    input_variables=["question"],
+    template=prompt_template,
+)
+
+# Create llm chain
+llm_chain = LLMChain(llm=mistral_llm, prompt=prompt)
+
+
+retriever.search_kwargs = {'k':1}
+qa = RetrievalQA.from_chain_type(
+    llm=mistral_llm,
+    chain_type="stuff",
+    retriever=retriever,
+    chain_type_kwargs={"prompt": prompt},
+)
+
+import streamlit as st
+
+# Streamlit interface with improved aesthetics
+st.set_page_config(page_title="Alter-IA Chat", page_icon="🤖")
+
+# Define function to handle user input and display chatbot response
+def chatbot_response(user_input):
+    response = qa.run(user_input)
+    return response
+
+
+# Create columns for logos
+col1, col2, col3 = st.columns([2, 3, 2])
+
+with col1:
+    st.image("Design 3_22.png", width=150, use_column_width=True)  # Adjust image path and size as needed
+
+with col3:
+    st.image("Altereo logo 2023 original - eau et territoires durables.png", width=150, use_column_width=True)  # Adjust image path and size as needed
+# Streamlit components
+# Ajouter un peu de CSS pour centrer le texte
+# Ajouter un peu de CSS pour centrer le texte et le colorer en orange foncé
+st.markdown("""
+    <style>
+    .centered-text {
+        text-align: center;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+# Utiliser la classe CSS pour centrer et colorer le texte
+st.markdown('<h3 class="centered-text">🤖 AlteriaChat 🤖 </h3>', unsafe_allow_html=True)
+st.markdown("""
+    <style>
+    .centered-orange-text {
+        text-align: center;
+        color: darkorange;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+# Centrer le texte principal
+# Centrer et colorer en orange foncé le texte spécifique
+st.markdown('<p class="centered-orange-text">"Votre Réponse à Chaque Défi Méthodologique "</p>', unsafe_allow_html=True)
+# Input and button for user interaction
+user_input = st.text_input("You:", "")
+submit_button = st.button("Ask 📨")
+
+# Handle user input
+if submit_button:
+    if user_input.strip() != "":
+        bot_response = chatbot_response(user_input)
+        st.markdown("### Bot:")
+        st.text_area("", value=bot_response, height=600)
+    else:
+        st.warning("⚠️ Please enter a message.")
+
+# Motivational quote at the bottom
+st.markdown("---")
+st.markdown("La collaboration est la clé du succès. Chaque question trouve sa réponse, chaque défi devient une opportunité.")
+

requirements (1).txt

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+langchain_huggingface
+sentence_transformers
+scipy
+langchain
+ctransformers
+tensorflow 
+transformers
+faiss-cpu
+pypdf 
+streamlit
+langchain-community
+torch
+datasets 
+sentencepiece