Upload 18 files

frontend/src/components/ChatInterface.jsx

@@ -1,6 +1,6 @@
 import React, { useState, useRef, useEffect } from 'react';
-import axios from 'axios';
 import ReactMarkdown from 'react-markdown';
+import { InferenceClient } from "@huggingface/inference";
 import Avatar from './Avatar.jsx';
 import '../App.css';
 
@@ -8,8 +8,10 @@ const ChatInterface = ({ messages = [], setMessages = () => {}, onMessageSent =
   const [inputMessage, setInputMessage] = useState('');
   const [isLoading, setIsLoading] = useState(false);
   const messagesEndRef = useRef(null);
-  const textareaRef = useRef(null); 
-
+  const textareaRef = useRef(null);
+  
+  // Initialisation du client Hugging Face (idéalement dans un .env)
+  const hfClient = new InferenceClient(process.env.REACT_APP_HF_TOKEN || "votre_token_ici");
 
   const isMarkdown = (text) => /[#*_>`-]/.test(text);
 
@@ -17,7 +19,6 @@ const ChatInterface = ({ messages = [], setMessages = () => {}, onMessageSent =
     messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
   };
 
-
   useEffect(() => {
     scrollToBottom();
   }, [messages]);
@@ -28,11 +29,27 @@ const ChatInterface = ({ messages = [], setMessages = () => {}, onMessageSent =
       
       onMessageSent(message);
       
-      const response = await axios.post('https://15af0837fca124cf6d.gradio.live/gradio_api/run/predict', {
-        data: [message, null],
-        fn_index: 0
+      // Appel au modèle Mistral via Hugging Face
+      const chatCompletion = await hfClient.chatCompletion({
+        provider: "together",  // Vous pouvez aussi utiliser "novita" ou d'autres providers
+        model: "mistralai/Mistral-7B-Instruct-v0.3",
+        messages: [
+          {
+            role: "system",
+            content: "Tu es un assistant médical expert spécialisé uniquement dans la schizophrénie. Réponds uniquement aux questions concernant la schizophrénie. Si la question concerne un autre sujet médical, refuse poliment de répondre."
+          },
+          {
+            role: "user",
+            content: message
+          }
+        ],
+        max_tokens: 512,
+        temperature: 0.7,
       });
-      const botResponse = response.data.data[0];
+      
+      // Extraction de la réponse
+      const botResponse = chatCompletion.choices[0].message.content;
+      
       setMessages(prev => [
         ...prev,
         { sender: 'user', text: message },
@@ -50,6 +67,8 @@ const ChatInterface = ({ messages = [], setMessages = () => {}, onMessageSent =
     }
   };
 
+  
+
   const handleSubmit = (e) => {
     e.preventDefault();
     if (inputMessage.trim() === '') return;