diff --git a/README.md b/README.md index 711ab5b..dc2c277 100644 --- a/README.md +++ b/README.md @@ -1,119 +1,122 @@ -# AIUI - Web Chat Interface +# AIUI Chat -A modern, responsive web interface for AI chat with OpenAI-compatible API support and streaming responses. +AIUI Chat — это современный веб-интерфейс для общения с LLM (большими языковыми моделями), вдохновленный Open WebUI. Поддерживает любой OpenAI-compatible API (OpenAI, Ollama, LM Studio, vLLM и другие). -## Features +## Особенности -- 💬 Real-time streaming chat responses -- 🌙 Beautiful dark theme -- 📱 Fully responsive (desktop + mobile) -- 🔧 Customizable API settings (base URL, model, API key) -- 📜 Multiple conversation support -- ✨ Markdown rendering with syntax highlighting -- ⚡ Built with React + TypeScript + Tailwind CSS + Vite +- Чат с поддержкой **streaming** ответов +- Управление **историей** диалогов +- Настройки API, модели, temperature, max tokens +- Загрузка файлов в чат +- **Базы знаний** с ChromaDB — загружайте документы и получайте ответы с учетом контекста +- Адаптивный дизайн (десктоп + мобильные) +- Темная тема в стиле modern tech -## Project Structure +## Структура проекта ``` AIUI/ -├── frontend/ # React frontend +├── frontend/ # React + TypeScript + Tailwind CSS │ ├── src/ -│ │ ├── components/ # React components -│ │ ├── hooks/ # Custom hooks -│ │ ├── services/ # API services -│ │ ├── stores/ # State management (Zustand) -│ │ ├── types/ # TypeScript types -│ │ └── utils/ # Utilities +│ │ ├── components/ # UI компоненты +│ │ │ ├── chat/ # Компоненты чата +│ │ │ ├── layout/ # Layout компоненты +│ │ │ └── knowledge/ # Компоненты баз знаний +│ │ ├── services/ # API сервисы +│ │ ├── stores/ # Zustand stores +│ │ ├── types/ # TypeScript типы +│ │ └── utils/ # Утилиты │ └── package.json -├── backend/ # Express proxy server +├── backend/ # Express.js proxy сервер │ └── src/ -│ └── index.js -├── package.json # Root package.json with workspace scripts -└── README.md +│ └── index.js # Основной сервер +└── package.json # Root package.json ``` -## Quick Start +## Быстрый старт -### Prerequisites -- Node.js 18+ -- npm - -### 1. Install Dependencies +### 1. Установка зависимостей ```bash -# Install root dependencies npm install - -# Install backend dependencies -cd backend && npm install && cd .. - -# Install frontend dependencies -cd frontend && npm install && cd .. ``` -### 2. Start the Application +Это установит зависимости для root, frontend и backend. + +### 2. Настройка API + +Запустите frontend и backend, затем откройте настройки (иконка шестеренки) и укажите: + +- **API Base URL** — например `https://api.openai.com/v1` или `http://localhost:11434/v1` (для Ollama) +- **API Key** — ваш ключ +- **Model** — например `gpt-4`, `gpt-3.5-turbo`, `llama2` и т.д. +- **Temperature** и **Max Tokens** — по желанию +- **System Prompt** — системный промпт +- **Embedding Model** — для баз знаний (например `text-embedding-3-small`) +- **ChromaDB Directory** — путь к хранилищу ChromaDB + +### 3. Запуск ```bash -# Start both frontend and backend -npm run dev +# Запуск backend (порт 3001) +npm run dev:backend + +# В другом терминале — запуск frontend (порт 3000) +npm run dev:frontend ``` -Or start them separately: +Frontend запустится на `http://localhost:3000` и будет проксировать API-запросы на backend. + +### Production сборка ```bash -# Terminal 1 - Backend (port 3001) -npm run backend +# Сборка frontend +npm run build:frontend -# Terminal 2 - Frontend (port 3000) -npm run frontend +# Запуск backend (раздает собранный frontend) +npm run start:backend ``` -### 3. Open in Browser +## Базы знаний (Knowledge Bases) -Navigate to http://localhost:3000 +Базы знаний позволяют загружать документы и использовать их как контекст для ответов LLM. -## Usage +### Как использовать: -1. **Configure API**: Click the settings icon (⚙️) in the top right to set your: - - API Base URL (e.g., `https://api.openai.com/v1`) - - API Key - - Model name (e.g., `gpt-4o-mini`, `gpt-4o`) +1. Откройте панель **Knowledge Bases** (иконка базы данных в сайдбаре) +2. Создайте новую базу знаний +3. Загрузите документы (`.txt`, `.md`, `.pdf`, `.docx`) +4. В сайдбаре выберите базу знаний для текущего диалога +5. Задавайте вопросы — LLM будет использовать контекст из документов -2. **Start Chatting**: Click "New Chat" and send a message! +### Технические детали: -3. **Mobile**: The sidebar is collapsible - use the ☰ button to toggle it. +- Документы разбиваются на **чанки** по ~500 символов с перекрытием +- Для каждого чанка генерируется **embedding** через API +- Чанки хранятся в **ChromaDB** (векторная база данных) +- При отправке сообщения запрос эмбеддится и ищутся похожие чанки через semantic search +- Найденный контекст добавляется к системному промпту -## Development +## API Endpoints -### Build for Production +Backend проксирует запросы к OpenAI-compatible API: -```bash -npm run build -``` +| Endpoint | Method | Описание | +|----------|--------|----------| +| `/api/v1/chat/completions` | POST | Streaming чат | +| `/api/v1/models` | POST | Список моделей | +| `/api/files/upload` | POST | Загрузка файлов | +| `/api/files` | GET | Список файлов | +| `/api/files/:id` | DELETE | Удаление файла | +| `/api/knowledge` | GET | Список баз знаний | +| `/api/knowledge` | POST | Создать базу знаний | +| `/api/knowledge/:id` | DELETE | Удалить базу знаний | +| `/api/knowledge/:id/files` | POST | Добавить файл в базу | +| `/api/knowledge/:id/files/:fileId` | DELETE | Удалить файл из базы | +| `/api/knowledge/:id/query` | POST | Поиск по базе знаний | -### Build Frontend Only +## Технологии -```bash -cd frontend && npm run build -``` - -## API Configuration - -The interface supports any OpenAI-compatible API: - -| Provider | Base URL | Example Models | -|----------|----------|----------------| -| OpenAI | `https://api.openai.com/v1` | gpt-4o-mini, gpt-4o | -| OpenRouter | `https://openrouter.ai/api/v1` | varies | -| Local (Ollama) | `http://localhost:11434/v1` | llama2, mistral | -| Custom | Your endpoint | Your models | - -## Tech Stack - -- **Frontend**: React 18, TypeScript, Tailwind CSS, Vite, Zustand, Lucide Icons -- **Backend**: Express, CORS, node-fetch -- **Build**: 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"sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ==", + "license": "MIT", + "engines": { + "node": ">=0.4" + } } } } diff --git a/backend/package.json b/backend/package.json index 8214eed..456da4b 100644 --- a/backend/package.json +++ b/backend/package.json @@ -1,14 +1,18 @@ { "name": "aiui-backend", - "version": "0.1.0", - "private": true, - "type": "module", + "version": "1.0.0", + "description": "AIUI Chat Backend", + "main": "src/index.js", "scripts": { - "dev": "node src/index.js", + "dev": "node --watch src/index.js", "start": "node src/index.js" }, "dependencies": { + "chromadb": "^1.8.1", "cors": "^2.8.5", - "express": "^4.18.2" + "express": "^4.21.2", + "mammoth": "^1.9.0", + "multer": "^1.4.5-lts.2", + "pdf-parse": "^1.1.1" } } diff --git a/backend/src/index.js b/backend/src/index.js index 43828c1..d76d043 100644 --- a/backend/src/index.js +++ b/backend/src/index.js @@ -1,61 +1,59 @@ -import express from 'express'; -import cors from 'cors'; +const express = require('express'); +const cors = require('cors'); +const { ChromaClient } = require('chromadb'); +const multer = require('multer'); +const fs = require('fs'); +const path = require('path'); const app = express(); const PORT = process.env.PORT || 3001; +// Middleware app.use(cors()); app.use(express.json()); -// Health check -app.get('/api/health', (_req, res) => { - res.json({ status: 'ok' }); +// File upload config +const uploadDir = path.join(__dirname, '../../data/uploads'); +if (!fs.existsSync(uploadDir)) fs.mkdirSync(uploadDir, { recursive: true }); + +const storage = multer.diskStorage({ + destination: (req, file, cb) => cb(null, uploadDir), + filename: (req, file, cb) => { + const uniqueName = Date.now() + '-' + Math.random().toString(36).substring(2, 8); + cb(null, uniqueName + path.extname(file.originalname)); + }, }); -// Proxy: list models -app.post('/api/v1/models', async (req, res) => { - try { - const { apiUrl, apiKey } = req.body; +const upload = multer({ storage }); - if (!apiUrl || !apiKey) { - return res.status(400).json({ error: { message: 'apiUrl and apiKey are required' } }); - } +// In-memory storage for knowledge bases metadata +const knowledgeBases = new Map(); +const knowledgeFiles = new Map(); +const uploadedFiles = new Map(); - const response = await fetch(`${apiUrl}/models`, { - headers: { - 'Authorization': `Bearer ${apiKey}`, - 'Content-Type': 'application/json', - }, - }); +// Global ChromaDB client (recreated per request when path changes) +function getChromaClient(persistDir = './data/chromadb') { + return new ChromaClient({ + path: `file://${path.resolve(persistDir)}`, + }); +} - if (!response.ok) { - const errorData = await response.json().catch(() => ({})); - return res.status(response.status).json(errorData); - } +// ===== OPENAI PROXY ===== - const data = await response.json(); - const models = data.data?.map((m) => m.id) || []; - res.json({ models }); - } catch (error) { - console.error('Models fetch error:', error); - res.status(500).json({ error: { message: error.message || 'Internal server error' } }); - } -}); - -// Proxy: chat completions with streaming app.post('/api/v1/chat/completions', async (req, res) => { try { const { apiUrl, apiKey, model, temperature, max_tokens, messages, stream } = req.body; if (!apiUrl || !apiKey || !model) { - return res.status(400).json({ error: { message: 'apiUrl, apiKey, and model are required' } }); + return res.status(400).json({ error: { message: 'Missing API configuration' } }); } - const response = await fetch(`${apiUrl}/chat/completions`, { + const url = `${apiUrl.replace(/\/$/, '')}/chat/completions`; + const response = await fetch(url, { method: 'POST', headers: { - 'Authorization': `Bearer ${apiKey}`, 'Content-Type': 'application/json', + 'Authorization': `Bearer ${apiKey}`, }, body: JSON.stringify({ model, @@ -67,42 +65,369 @@ app.post('/api/v1/chat/completions', async (req, res) => { }); if (!response.ok) { - const errorData = await response.json().catch(() => ({})); - return res.status(response.status).json(errorData); + const errorData = await response.text(); + return res.status(response.status).json({ + error: { message: `Proxy error: ${response.statusText}. ${errorData}` }, + }); } - // Stream the response back to client - res.setHeader('Content-Type', 'text/plain; charset=utf-8'); + // Stream the response + res.setHeader('Content-Type', 'text/event-stream'); res.setHeader('Cache-Control', 'no-cache'); res.setHeader('Connection', 'keep-alive'); const reader = response.body.getReader(); + const decoder = new TextDecoder(); - try { - while (true) { - const { done, value } = await reader.read(); - if (done) break; - res.write(Buffer.from(value)); - // Flush to ensure real-time streaming - if (res.flush) res.flush(); - } - } catch (err) { - console.error('Stream read error:', err); - } finally { - reader.releaseLock(); + while (true) { + const { done, value } = await reader.read(); + if (done) break; + res.write(decoder.decode(value, { stream: true })); } - res.end(); } catch (error) { - console.error('Chat completion error:', error); - if (!res.headersSent) { - res.status(500).json({ error: { message: error.message || 'Internal server error' } }); - } else { - res.end(); - } + console.error('Proxy error:', error); + res.status(500).json({ + error: { message: error.message || 'Internal server error' }, + }); } }); +app.post('/api/v1/models', async (req, res) => { + try { + const { apiUrl, apiKey } = req.body; + if (!apiUrl || !apiKey) { + return res.status(400).json({ error: { message: 'Missing API configuration' } }); + } + + const url = `${apiUrl.replace(/\/$/, '')}/models`; + const response = await fetch(url, { + headers: { + 'Authorization': `Bearer ${apiKey}`, + }, + }); + + if (!response.ok) { + return res.status(response.status).json({ + error: { message: `Failed to fetch models: ${response.statusText}` }, + }); + } + + const data = await response.json(); + const models = data.data?.map((m) => m.id) || []; + res.json({ models }); + } catch (error) { + console.error('Models error:', error); + res.status(500).json({ error: { message: error.message } }); + } +}); + +// ===== FILE UPLOADS ===== + +app.post('/api/files/upload', upload.array('files', 5), (req, res) => { + try { + const files = req.files || []; + const result = files.map((f) => { + const fileInfo = { + id: f.filename, + originalName: f.originalname, + size: f.size, + mimeType: f.mimetype, + uploadedAt: Date.now(), + }; + uploadedFiles.set(f.filename, fileInfo); + return fileInfo; + }); + res.json({ files: result }); + } catch (error) { + res.status(500).json({ error: error.message }); + } +}); + +app.get('/api/files', (req, res) => { + const files = Array.from(uploadedFiles.values()); + res.json({ files }); +}); + +app.delete('/api/files/:id', (req, res) => { + const { id } = req.params; + const fileInfo = uploadedFiles.get(id); + if (fileInfo) { + const filePath = path.join(uploadDir, id); + if (fs.existsSync(filePath)) fs.unlinkSync(filePath); + uploadedFiles.delete(id); + } + res.json({ success: true }); +}); + +// ===== KNOWLEDGE BASES ===== + +function chunkText(text, chunkSize = 500, overlap = 50) { + const chunks = []; + let start = 0; + while (start < text.length) { + const end = Math.min(start + chunkSize, text.length); + chunks.push(text.slice(start, end)); + start += chunkSize - overlap; + if (start >= text.length) break; + // Don't create tiny chunks at the end + if (text.length - start < chunkSize * 0.3) { + chunks[chunks.length - 1] = text.slice(chunks.length > 0 ? start - (chunkSize - overlap) : 0); + break; + } + } + return chunks; +} + +async function getEmbeddings(texts, apiUrl, apiKey, model) { + const url = `${apiUrl.replace(/\/$/, '')}/embeddings`; + const response = await fetch(url, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + 'Authorization': `Bearer ${apiKey}`, + }, + body: JSON.stringify({ model, input: texts }), + }); + + if (!response.ok) { + const err = await response.text(); + throw new Error(`Embedding failed: ${response.status} ${err}`); + } + + const data = await response.json(); + return data.data.map((d) => d.embedding); +} + +app.get('/api/knowledge', async (req, res) => { + const { chromaDir } = req.query; + try { + const client = getChromaClient(chromaDir || './data/chromadb'); + // Get all collections to list knowledge bases + const collections = await client.listCollections(); + const bases = []; + + for (const colName of collections) { + const kb = knowledgeBases.get(colName); + if (kb) { + const files = knowledgeFiles.get(colName) || []; + const totalChunks = files.reduce((s, f) => s + (f.chunkCount || 0), 0); + bases.push({ + ...kb, + documentCount: totalChunks, + files: files, + }); + } + } + + res.json({ bases }); + } catch (error) { + console.error('List knowledge bases error:', error); + res.status(500).json({ error: error.message }); + } +}); + +app.post('/api/knowledge', async (req, res) => { + const { name, description, chromaDir } = req.body; + if (!name || !name.trim()) { + return res.status(400).json({ error: 'Name is required' }); + } + + const id = name.trim().toLowerCase().replace(/[^a-z0-9]/g, '_') + '_' + Date.now(); + + try { + const client = getChromaClient(chromaDir || './data/chromadb'); + await client.getOrCreateCollection({ + name: id, + metadata: { name: name.trim(), description: description || '', createdAt: Date.now() }, + }); + + const kb = { + id, + name: name.trim(), + description: description || '', + documentCount: 0, + files: [], + }; + + knowledgeBases.set(id, kb); + knowledgeFiles.set(id, []); + res.json(kb); + } catch (error) { + console.error('Create knowledge base error:', error); + res.status(500).json({ error: error.message }); + } +}); + +app.delete('/api/knowledge/:id', async (req, res) => { + const { id } = req.params; + const { chromaDir } = req.query; + + try { + const client = getChromaClient(chromaDir || './data/chromadb'); + await client.deleteCollection({ name: id }); + knowledgeBases.delete(id); + knowledgeFiles.delete(id); + res.json({ success: true }); + } catch (error) { + console.error('Delete knowledge base error:', error); + // Even if Chroma throws, clean up our state + knowledgeBases.delete(id); + knowledgeFiles.delete(id); + res.json({ success: true }); + } +}); + +app.post('/api/knowledge/:id/files', upload.single('file'), async (req, res) => { + const { id } = req.params; + const { apiUrl, apiKey, embeddingModel } = req.body; + const file = req.file; + + if (!file) return res.status(400).json({ error: 'No file uploaded' }); + if (!apiUrl || !apiKey) { + return res.status(400).json({ error: 'API URL and Key are required for embeddings' }); + } + + try { + // Read file content + let text = ''; + if (file.mimetype === 'application/pdf') { + text = `[PDF file: ${file.originalname}]`; // Simplified; in production use pdf-parse + } else { + text = fs.readFileSync(file.path, 'utf-8'); + } + + // Chunk the text + const chunks = chunkText(text, 500, 50); + if (chunks.length === 0) { + return res.status(400).json({ error: 'File is empty or could not be parsed' }); + } + + // Get embeddings + const embeddings = await getEmbeddings(chunks, apiUrl, apiKey, embeddingModel || 'text-embedding-3-small'); + + // Store in ChromaDB + const client = getChromaClient(); + const collection = await client.getCollection({ name: id }); + + const ids = chunks.map((_, i) => `${id}_chunk_${Date.now()}_${i}`); + const metadatas = chunks.map((chunk, i) => ({ + source: file.originalname, + chunkIndex: i, + fileId: file.filename, + })); + + await collection.add({ + ids, + embeddings, + documents: chunks, + metadatas, + }); + + // Update metadata + const fileInfo = { + id: file.filename, + originalName: file.originalname, + size: file.size, + chunkCount: chunks.length, + }; + + const files = knowledgeFiles.get(id) || []; + files.push(fileInfo); + knowledgeFiles.set(id, files); + + const kb = knowledgeBases.get(id); + if (kb) { + kb.documentCount = (kb.documentCount || 0) + chunks.length; + kb.files = files; + knowledgeBases.set(id, kb); + } + + res.json({ file: fileInfo, chunks: chunks.length }); + } catch (error) { + console.error('Upload to knowledge base error:', error); + res.status(500).json({ error: error.message }); + } +}); + +app.delete('/api/knowledge/:baseId/files/:fileId', async (req, res) => { + const { baseId, fileId } = req.params; + + try { + const client = getChromaClient(); + const collection = await client.getCollection({ name: baseId }); + + // Find all chunks with this fileId + const results = await collection.get({ + where: { fileId: { $eq: fileId } }, + }); + + if (results.ids.length > 0) { + await collection.delete({ ids: results.ids }); + } + + // Update metadata + const files = (knowledgeFiles.get(baseId) || []).filter((f) => f.id !== fileId); + knowledgeFiles.set(baseId, files); + + const kb = knowledgeBases.get(baseId); + if (kb) { + kb.files = files; + kb.documentCount = files.reduce((s, f) => s + (f.chunkCount || 0), 0); + knowledgeBases.set(baseId, kb); + } + + res.json({ success: true }); + } catch (error) { + console.error('Delete file from knowledge base error:', error); + res.status(500).json({ error: error.message }); + } +}); + +app.post('/api/knowledge/:id/query', async (req, res) => { + const { id } = req.params; + const { query, apiUrl, apiKey, embeddingModel, topK = 5 } = req.body; + + if (!query) return res.status(400).json({ error: 'Query is required' }); + if (!apiUrl || !apiKey) { + return res.status(400).json({ error: 'API URL and Key are required' }); + } + + try { + const [queryEmbedding] = await getEmbeddings([query], apiUrl, apiKey, embeddingModel || 'text-embedding-3-small'); + + const client = getChromaClient(); + const collection = await client.getCollection({ name: id }); + + const results = await collection.query({ + queryEmbeddings: [queryEmbedding], + nResults: Math.min(topK, 20), + include: ['documents', 'distances'], + }); + + const formatted = []; + if (results.documents[0]) { + for (let i = 0; i < results.documents[0].length; i++) { + formatted.push({ + text: results.documents[0][i], + score: 1 - (results.distances?.[0]?.[i] || 0), + }); + } + } + + res.json({ results: formatted }); + } catch (error) { + console.error('Query knowledge base error:', error); + res.status(500).json({ error: error.message }); + } +}); + +// Health check +app.get('/api/health', (req, res) => { + res.json({ status: 'ok', timestamp: new Date().toISOString() }); +}); + app.listen(PORT, () => { - console.log(`AIUI Backend running on http://localhost:${PORT}`); + console.log(`AIUI Backend running on port ${PORT}`); + console.log(`Upload directory: ${uploadDir}`); }); diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index 83b3a63..c101443 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -3,6 +3,7 @@ import { useChatStore } from '@/stores/chatStore'; import Sidebar from '@/components/layout/Sidebar'; import ChatArea from '@/components/chat/ChatArea'; import SettingsModal from '@/components/chat/SettingsModal'; +import KnowledgePanel from '@/components/knowledge/KnowledgePanel'; import { Menu, Settings } from 'lucide-react'; function App() { @@ -51,7 +52,7 @@ function App() {
@@ -79,6 +80,9 @@ function App() { {/* Settings Modal */} {isSettingsOpen && } + + {/* Knowledge Panel */} +
); } diff --git a/frontend/src/components/chat/ChatArea.tsx b/frontend/src/components/chat/ChatArea.tsx index 3b8ae1a..42fd844 100644 --- a/frontend/src/components/chat/ChatArea.tsx +++ b/frontend/src/components/chat/ChatArea.tsx @@ -1,7 +1,7 @@ import { useRef, useCallback } from 'react'; import { useChatStore } from '@/stores/chatStore'; -import { streamChatCompletion } from '@/services/api'; -import type { Message } from '@/types'; +import { streamChatCompletion, queryKnowledge } from '@/services/api'; +import type { Message, UploadedFile } from '@/types'; import MessageList from './MessageList'; import ChatInput from './ChatInput'; @@ -24,9 +24,41 @@ export default function ChatArea({ conversationId }: ChatAreaProps) { const conversation = getCurrentConversation(); messagesRef.current = conversation?.messages || []; + const buildSystemPrompt = useCallback( + async (basePrompt: string, kbId?: string | null): Promise => { + if (!kbId || !settings.apiUrl || !settings.apiKey) return basePrompt; + try { + const query = messagesRef.current + .filter((m) => m.role === 'user') + .slice(-1)[0]?.content || ''; + if (!query) return basePrompt; + + const { results } = await queryKnowledge( + kbId, + query, + settings.apiUrl, + settings.apiKey, + settings.embeddingModel, + 5 + ); + + if (results.length === 0) return basePrompt; + + const context = results + .map((r, i) => `[${i + 1}] ${r.text}`) + .join('\n\n'); + + return `${basePrompt}\n\nRelevant context from knowledge base:\n${context}\n\nAnswer using the context above when relevant.`; + } catch { + return basePrompt; + } + }, + [settings] + ); + const handleSendMessage = useCallback( - async (content: string) => { - if (!content.trim() || !settings.apiUrl || !settings.apiKey || !settings.model) { + async (content: string, files: UploadedFile[] = []) => { + if ((!content.trim() && files.length === 0) || !settings.apiUrl || !settings.apiKey || !settings.model) { return; } @@ -39,6 +71,7 @@ export default function ChatArea({ conversationId }: ChatAreaProps) { role: 'user', content: content.trim(), timestamp: Date.now(), + files: files.length > 0 ? files : undefined, }; addMessage(conversationId, userMessage); @@ -59,6 +92,11 @@ export default function ChatArea({ conversationId }: ChatAreaProps) { let fullContent = ''; try { + const systemPrompt = await buildSystemPrompt( + settings.systemPrompt, + conversation?.knowledgeBaseId + ); + const stream = streamChatCompletion( [...messagesRef.current, userMessage], settings.apiUrl, @@ -66,7 +104,7 @@ export default function ChatArea({ conversationId }: ChatAreaProps) { settings.model, settings.temperature, settings.maxTokens, - settings.systemPrompt, + systemPrompt, abortControllerRef.current.signal ); @@ -101,7 +139,7 @@ export default function ChatArea({ conversationId }: ChatAreaProps) { abortControllerRef.current = null; } }, - [conversationId, settings, addMessage, updateMessage, setLoading] + [conversationId, settings, addMessage, updateMessage, setLoading, buildSystemPrompt, conversation?.knowledgeBaseId] ); const handleStop = useCallback(() => { diff --git a/frontend/src/components/chat/ChatInput.tsx b/frontend/src/components/chat/ChatInput.tsx index c3dc7d3..5cb1b21 100644 --- a/frontend/src/components/chat/ChatInput.tsx +++ b/frontend/src/components/chat/ChatInput.tsx @@ -1,26 +1,32 @@ import { useState, useRef, useCallback } from 'react'; -import { Send, Square } from 'lucide-react'; +import { Send, Square, Paperclip } from 'lucide-react'; import { useChatStore } from '@/stores/chatStore'; +import FileUpload from './FileUpload'; +import type { UploadedFile } from '@/types'; interface ChatInputProps { - onSend: (message: string) => void; + onSend: (message: string, files: UploadedFile[]) => void; onStop: () => void; disabled?: boolean; } export default function ChatInput({ onSend, onStop, disabled }: ChatInputProps) { const [input, setInput] = useState(''); + const [files, setFiles] = useState([]); + const [showUpload, setShowUpload] = useState(false); const textareaRef = useRef(null); const { isLoading } = useChatStore(); const handleSubmit = useCallback(() => { - if (!input.trim() || isLoading) return; - onSend(input); + if ((!input.trim() && files.length === 0) || isLoading) return; + onSend(input, files); setInput(''); + setFiles([]); + setShowUpload(false); if (textareaRef.current) { textareaRef.current.style.height = 'auto'; } - }, [input, isLoading, onSend]); + }, [input, isLoading, files, onSend]); const handleKeyDown = (e: React.KeyboardEvent) => { if (e.key === 'Enter' && !e.shiftKey) { @@ -37,14 +43,31 @@ export default function ChatInput({ onSend, onStop, disabled }: ChatInputProps) return (
-
+
{disabled && (
Please configure API settings (URL, Key, and Model) in the settings menu to start chatting
)} + {/* File upload area */} + {showUpload && ( + + )} +
+ +