backend integration with front

index.js

@@ -8,7 +8,8 @@ import {
   ModalBuilder, 
   TextInputBuilder, 
   TextInputStyle, 
-  ActionRowBuilder 
+  ActionRowBuilder,
+  MessageFlags 
 } from "discord.js";
 
 const client = new Client({
@@ -19,6 +20,8 @@ const client = new Client({
 	],
 });
 
+const API_URL = process.env.API_URL || "http://127.0.0.1:8000";
+
 client.once(Events.ClientReady, async () => {
 	console.log(`Bot ready: ${client.user.tag}`);
 
@@ -26,7 +29,7 @@ client.once(Events.ClientReady, async () => {
 		await client.application.commands.set([
 			{
 				name: "detect",
-				description: "Otwiera okienko do wklejenia linku lub tekstu",
+				description: "Otwiera okienko do wklejenia linku lub tekstu do analizy",
 			},
 		]);
 		console.log("Pomyślnie zarejestrowano komendę /detect");
@@ -35,21 +38,63 @@ client.once(Events.ClientReady, async () => {
 	}
 });
 
+function preparePayload(input) {
+	const trimmed = input.trim();
+	const isUrl = trimmed.startsWith("http://") || trimmed.startsWith("https://");
+
+	if (isUrl) {
+		const lowerUrl = trimmed.toLowerCase();
+		
+		if (lowerUrl.endsWith(".png") || lowerUrl.endsWith(".jpg") || lowerUrl.endsWith(".jpeg") || lowerUrl.endsWith(".webp") || lowerUrl.endsWith(".gif")) {
+			return { 
+				type: "image", 
+				payload: { 
+					image_url: trimmed,
+					content_type: "image"
+				} 
+			};
+		} else if (lowerUrl.endsWith(".mp4") || lowerUrl.endsWith(".webm") || lowerUrl.endsWith(".mov") || lowerUrl.endsWith(".avi")) {
+			return { 
+				type: "video", 
+				payload: { 
+					video_url: trimmed,
+					content_type: "video"
+				} 
+			};
+		} else {
+			return { 
+				type: "file", 
+				payload: { 
+					file_url: trimmed,
+					content_type: "file" 
+				} 
+			};
+		}
+	}
+
+	return { 
+		type: "text", 
+		payload: { 
+			text: trimmed,
+			content_type: "text"
+		} 
+	};
+}
+
 client.on(Events.InteractionCreate, async (interaction) => {
-	
 	if (interaction.isChatInputCommand()) {
 		if (interaction.commandName === "detect") {
-			
 			const modal = new ModalBuilder()
 				.setCustomId("detectModal")
-				.setTitle("Detektor linków/tekstu");
+				.setTitle("Detektor Deepfake");
 
 			const textInput = new TextInputBuilder()
 				.setCustomId("detectInput")
-				.setLabel("Wklej tutaj link lub tekst do przetworzenia:")
-				.setStyle(TextInputStyle.Paragraph) 
+				.setLabel("Wklej tutaj tekst lub link (obraz/wideo):")
+				.setStyle(TextInputStyle.Paragraph)
 				.setPlaceholder("Wklej zawartość...")
 				.setRequired(true);
+
 			const actionRow = new ActionRowBuilder().addComponents(textInput);
 			modal.addComponents(actionRow);
 
@@ -61,12 +106,61 @@ client.on(Events.InteractionCreate, async (interaction) => {
 		if (interaction.customId === "detectModal") {
 			const userContent = interaction.fields.getTextInputValue("detectInput");
 
-			await interaction.reply({
-				content: `ziemniak`,
-				ephemeral: true, 
-			});
+			await interaction.deferReply({ flags: [MessageFlags.Ephemeral] });
+
+			try {
+				const { type, payload } = preparePayload(userContent);
+				
+				console.log(`Wysyłanie zapytania typu: ${type} do API...`);
+
+				const response = await fetch(`${API_URL}/analyze`, {
+					method: "POST",
+					headers: {
+						"Content-Type": "application/json",
+					},
+					body: JSON.stringify(payload),
+				});
+
+				if (!response.ok) {
+					const errorData = await response.json().catch(() => ({}));
+					console.error("Szczegóły błędu z FastAPI:", JSON.stringify(errorData, null, 2));
+					
+					let errorMsg = `Błąd serwera API (Status ${response.status})`;
+					if (errorData.detail) {
+						if (Array.isArray(errorData.detail)) {
+							errorMsg = errorData.detail
+								.map(err => `• Pole \`${err.loc.join(".")}\`: ${err.msg}`)
+								.join("\n");
+						} else {
+							errorMsg = errorData.detail;
+						}
+					}
+					throw new Error(errorMsg);
+				}
+
+				const data = await response.json();
+
+				const statusEmoji = data.is_deepfake ? "⚠️ **Wykryto potencjalny Deepfake!**" : "✅ **Zawartość wydaje się oryginalna**";
+				const confidencePercent = (data.confidence * 100).toFixed(2);
+				const timeSec = data.analysis_time.toFixed(3);
+
+				const replyMessage = 
+					`### Wyniki Analizy (${data.content_type.toUpperCase()})\n` +
+					`${statusEmoji}\n\n` +
+					`* **Pewność modelu:** \`${confidencePercent}%\`\n` +
+					`* **Użyty model:** \`${data.model_used}\`\n` +
+					`* **Czas przetwarzania:** \`${timeSec} sekund\`\n`;
+
+				await interaction.editReply({
+					content: replyMessage,
+				});
 
-			console.log(`Użytkownik wkleił: ${userContent}`);
+			} catch (error) {
+				console.error("Błąd podczas analizy:", error);
+				await interaction.editReply({
+					content: `❌ Nie udało się przeprowadzić analizy.\n\n**Szczegóły błędu:**\n${error.message}`,
+				});
+			}
 		}
 	}
 });