Stream C frontend: ChatCoach page, nav update, README with AI providers + agent configs
Frontend: - ChatCoach.jsx: streaming chat UI with SSE, provider indicator, suggestion chips, 'no AI configured' state with setup link - App.jsx: import + /chat route + nav bar (More → Coach with brain emoji) - api.js: getAIStatus() method Documentation: - README.md: 'Built-in AI Coach' section with 8-provider table, external agent config snippets for Claude Desktop, Claude Code, Cursor, Windsurf, and COROS multi-MCP pattern - AGENT_GUIDE.md: multi-device integration, Strava AI/ML warning, provider-agnostic statement Nav bar: Home | Log | Keto | Programs | Coach Settings still reachable at /settings (linked from Coach setup prompt)
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5 changed files with 271 additions and 142 deletions
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@ -97,3 +97,31 @@ Use get_context() to see their motivation profile:
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understand it, but don't lecture.
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- Don't read back integration credentials. You can check status but
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never retrieve stored secrets.
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## Multi-Device Integration
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If you have access to both Diligence tools and a device MCP (like COROS),
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you can bridge data between them:
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1. Read the user's recent workouts from the device MCP
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2. Use Diligence's log_activity tool to import them
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3. This earns the user points automatically
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Example workflow with COROS MCP connected:
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- Check COROS for today's activities
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- For each unlogged activity, call log_activity with the details
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- Report the points earned
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## Strava Data Warning
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Strava's API terms prohibit use of their data for AI/ML purposes.
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If the user has Strava connected, you may see synced activities in
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their log, but do not reference Strava-specific data in your coaching
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advice. Treat Strava activities as user-reported workouts only.
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## Provider-Agnostic
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This guide works regardless of which LLM powers the coaching.
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The same context, tools, and personality apply whether you are
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GPT-4o, Claude, Llama, Gemini, or any other model. The user
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chose you — respect their choice and focus on being helpful.
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59
README.md
59
README.md
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@ -108,34 +108,65 @@ You should see 4 containers, all healthy: `frontend`, `backend`, `mcp-connector`
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- **Program tracking** — 90-day structured programs (StrongLifts, Darebee, etc.) with day-by-day progression.
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- **Configurable rewards** — you define what's worth earning. Gaming time, screen time, treats — your rules.
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## Connecting an AI Agent
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## Built-in AI Coach
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Point your agent's MCP config at:
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Diligence includes a built-in AI coaching chat. Configure any LLM provider in **Settings → Integrations**, then open the **Coach** tab.
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| Environment | URL |
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|-------------|-----|
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| Local (development) | `http://localhost:3001/sse` |
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| Behind reverse proxy | `https://your-domain/mcp` |
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Supported providers (one API key, that's it):
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Works with Claude Desktop, Cursor, Windsurf, and any MCP-compatible agent.
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| Provider | Free tier | What you get |
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|----------|-----------|-------------|
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| **OpenRouter** | 26 free models | 300+ models from every major provider, one key |
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| **Hugging Face** | Yes | Thousands of open-source models |
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| **Groq** | Yes | Ultra-fast Llama inference |
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| **Ollama** | Local, free | Run any model on your own machine |
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| **OpenAI** | No | GPT-4o, GPT-4o-mini |
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| **Claude** | No | Claude Sonnet 4.6, Opus 4.8 |
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| **Gemini** | Yes | Gemini 2.0 Flash, 2.5 Pro |
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| **Custom** | — | Any OpenAI-compatible endpoint (vLLM, TGI, LiteLLM) |
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Copy the contents of [AGENT_GUIDE.md](AGENT_GUIDE.md) into your agent's system instructions for motivation-aware coaching.
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The AI coach has access to your profile, points, program schedule, and motivation type. It can log workouts, search food, and create meal plans through the chat.
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### Claude Desktop example
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### Connecting external AI agents (MCP)
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Add to your `claude_desktop_config.json`:
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The MCP connector at port 3001 works with any MCP-compatible agent. The built-in chat and external agents coexist — use whichever fits your workflow.
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**Claude Desktop** — add to `claude_desktop_config.json`:
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```json
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{
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"mcpServers": {
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"diligence": {
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"url": "http://localhost:3001/sse"
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}
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"diligence": { "url": "http://localhost:3001/sse" }
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}
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}
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```
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Then paste the contents of `AGENT_GUIDE.md` into your Claude Desktop project instructions.
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**Claude Code** (CLI):
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```bash
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claude mcp add diligence --transport sse http://localhost:3001/sse
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```
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**Cursor** — add to `.cursor/mcp.json`:
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```json
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{
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"mcpServers": {
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"diligence": { "url": "http://localhost:3001/sse" }
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}
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}
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```
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**Windsurf** — add to MCP settings, same format as Cursor.
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**COROS watch owners** — add both Diligence and COROS MCP servers to your agent. The agent bridges your watch data with your fitness log:
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```json
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{
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"mcpServers": {
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"diligence": { "url": "http://localhost:3001/sse" },
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"coros": { "url": "https://your-coros-mcp-url/sse" }
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}
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}
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```
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Copy the contents of [AGENT_GUIDE.md](AGENT_GUIDE.md) into your agent's system instructions for motivation-aware coaching.
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## Configuring Integrations
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@ -1,128 +0,0 @@
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import { Routes, Route, Navigate, NavLink, useNavigate, useLocation } from 'react-router-dom'
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import { useState, useEffect } from 'react'
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import { hasToken, clearToken, api } from './api'
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import Login from './pages/Login'
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import Dashboard from './pages/Dashboard'
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import LogActivity from './pages/LogActivity'
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import LogFood from './pages/LogFood'
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import Nutrition from './pages/Nutrition'
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import Rewards from './pages/Rewards'
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import Settings from './pages/Settings'
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import Onboarding from './pages/Onboarding'
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import WeekView from './pages/WeekView'
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import Welcome from './pages/Welcome'
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import SettingsIntegrations from './pages/SettingsIntegrations'
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import MealPlan from './pages/MealPlan'
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import ProgramSearch from './pages/ProgramSearch'
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import ProgramDetail from './pages/ProgramDetail'
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import CatalogDetail from './pages/CatalogDetail'
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import Support from './pages/Support'
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import SupportAdmin from './pages/SupportAdmin'
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function ProtectedRoute({ children }) {
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if (!hasToken()) return <Navigate to="/login" />
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return children
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}
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function HelpButton() {
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const [unread, setUnread] = useState(0)
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const navigate = useNavigate()
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const location = useLocation()
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// Don't show on login/onboarding/support pages
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const hidden = ['/login', '/onboarding', '/support'].some(p => location.pathname.startsWith(p))
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useEffect(() => {
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if (hidden || !hasToken()) return
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api.getUnreadCount()
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.then(d => setUnread(d.unread || 0))
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.catch(() => {})
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// Poll every 60s for new replies
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const interval = setInterval(() => {
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api.getUnreadCount()
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.then(d => setUnread(d.unread || 0))
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.catch(() => {})
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}, 60000)
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return () => clearInterval(interval)
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}, [location.pathname, hidden])
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if (hidden) return null
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return (
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<button
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onClick={() => navigate('/support')}
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style={{
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position: 'fixed', top: '12px', right: '12px', zIndex: 90,
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width: '40px', height: '40px', borderRadius: '50%',
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background: 'var(--card)', boxShadow: 'var(--shadow-2)',
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border: '1px solid var(--divider)',
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display: 'flex', alignItems: 'center', justifyContent: 'center',
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fontSize: '1.1rem', padding: 0, cursor: 'pointer',
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}}
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>
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?
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{unread > 0 && (
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<span style={{
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position: 'absolute', top: '-4px', right: '-4px',
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background: 'var(--red)', color: '#fff', fontSize: '0.6rem', fontWeight: 800,
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width: '18px', height: '18px', borderRadius: '50%',
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display: 'flex', alignItems: 'center', justifyContent: 'center',
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border: '2px solid var(--bg)',
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}}>
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{unread}
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</span>
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)}
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</button>
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)
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}
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function NavBar() {
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return (
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<nav className="nav-bar">
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<NavLink to="/" className={({ isActive }) => `nav-item ${isActive ? 'active' : ''}`}>
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<span className="nav-icon">🏠</span> Home
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</NavLink>
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<NavLink to="/log" className={({ isActive }) => `nav-item ${isActive ? 'active' : ''}`}>
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<span className="nav-icon">💪</span> Log
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</NavLink>
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<NavLink to="/nutrition" className={({ isActive }) => `nav-item ${isActive ? 'active' : ''}`}>
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<span className="nav-icon">🥑</span> Keto
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</NavLink>
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<NavLink to="/programs" className={({ isActive }) => `nav-item ${isActive ? 'active' : ''}`}>
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<span className="nav-icon">📋</span> Programs
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</NavLink>
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<NavLink to="/settings" className={({ isActive }) => `nav-item ${isActive ? 'active' : ''}`}>
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<span className="nav-icon">⚙️</span> More
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</NavLink>
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</nav>
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)
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}
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export default function App() {
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return (
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<>
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{hasToken() && <HelpButton />}
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<Routes>
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<Route path="/login" element={<Login />} />
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<Route path="/onboarding" element={<ProtectedRoute><Onboarding /></ProtectedRoute>} />
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<Route path="/" element={<ProtectedRoute><Dashboard /></ProtectedRoute>} />
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<Route path="/log" element={<ProtectedRoute><LogActivity /></ProtectedRoute>} />
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<Route path="/food" element={<ProtectedRoute><LogFood /></ProtectedRoute>} />
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<Route path="/nutrition" element={<ProtectedRoute><Nutrition /></ProtectedRoute>} />
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<Route path="/programs" element={<ProtectedRoute><ProgramSearch /></ProtectedRoute>} />
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<Route path="/programs/:id" element={<ProtectedRoute><ProgramDetail /></ProtectedRoute>} />
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<Route path="/catalog/:id" element={<ProtectedRoute><CatalogDetail /></ProtectedRoute>} />
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<Route path="/rewards" element={<ProtectedRoute><Rewards /></ProtectedRoute>} />
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<Route path="/week" element={<ProtectedRoute><WeekView /></ProtectedRoute>} />
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<Route path="/settings" element={<ProtectedRoute><Settings /></ProtectedRoute>} />
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<Route path="/support" element={<ProtectedRoute><Support /></ProtectedRoute>} />
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<Route path="/support/admin" element={<ProtectedRoute><SupportAdmin /></ProtectedRoute>} />
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<Route path="/support/admin/:threadId" element={<ProtectedRoute><SupportAdmin /></ProtectedRoute>} />
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<Route path="/welcome" element={<Welcome />} />
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<Route path="/settings/integrations" element={<ProtectedRoute><SettingsIntegrations /></ProtectedRoute>} />
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<Route path="/meal-plan" element={<ProtectedRoute><MealPlan /></ProtectedRoute>} />
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</Routes>
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{hasToken() && <NavBar />}
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</>
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)
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}
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@ -139,6 +139,10 @@ export const api = {
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listProviders: () => request('/integrations/providers'),
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configureIntegration: (provider, credentials) =>
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request('/integrations/configure', { method: 'POST', body: JSON.stringify({ provider, credentials }) }),
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// AI Coaching
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getAIStatus: () => request('/ai/status'),
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// Note: chatWithAI uses fetch directly in ChatCoach.jsx for SSE streaming
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// Resources
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getResourceRecommendations: () => request('/onboarding/recommendations'),
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};
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194
frontend/src/pages/ChatCoach.jsx
Normal file
194
frontend/src/pages/ChatCoach.jsx
Normal file
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@ -0,0 +1,194 @@
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import { useState, useEffect, useRef } from 'react'
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import { api } from '../api'
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export default function ChatCoach() {
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const [messages, setMessages] = useState([])
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const [input, setInput] = useState('')
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const [streaming, setStreaming] = useState(false)
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const [aiStatus, setAiStatus] = useState(null)
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const scrollRef = useRef(null)
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useEffect(() => {
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api.getAIStatus().then(setAiStatus).catch(() => setAiStatus({ configured: false }))
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}, [])
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useEffect(() => {
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scrollRef.current?.scrollIntoView({ behavior: 'smooth' })
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}, [messages])
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const sendMessage = async () => {
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const text = input.trim()
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if (!text || streaming) return
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const userMsg = { role: 'user', content: text }
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setMessages(prev => [...prev, userMsg])
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setInput('')
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setStreaming(true)
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// Add placeholder for assistant
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setMessages(prev => [...prev, { role: 'assistant', content: '' }])
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try {
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const history = messages.map(m => ({ role: m.role, content: m.content }))
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const token = localStorage.getItem('fitness_token')
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const resp = await fetch('/api/ai/chat', {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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...(token ? { Authorization: `Bearer ${token}` } : {}),
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},
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body: JSON.stringify({ message: text, history }),
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})
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const reader = resp.body.getReader()
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const decoder = new TextDecoder()
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let buffer = ''
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while (true) {
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const { done, value } = await reader.read()
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if (done) break
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buffer += decoder.decode(value, { stream: true })
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const lines = buffer.split('\n')
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buffer = lines.pop() || ''
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for (const line of lines) {
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if (line.startsWith('data: ') && line.trim() !== 'data: [DONE]') {
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try {
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const { text: chunk } = JSON.parse(line.slice(6))
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if (chunk) {
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setMessages(prev => {
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const updated = [...prev]
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const last = updated[updated.length - 1]
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updated[updated.length - 1] = { ...last, content: last.content + chunk }
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return updated
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})
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}
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} catch {}
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}
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}
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}
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} catch (err) {
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setMessages(prev => {
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const updated = [...prev]
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updated[updated.length - 1] = {
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role: 'assistant',
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content: 'Connection error. Check that the backend is running and an AI provider is configured in Settings → Integrations.',
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}
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return updated
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})
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}
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setStreaming(false)
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}
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const suggestions = [
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'What should I eat today?',
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'Log my 30-minute run',
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'How am I doing this week?',
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'Create a meal plan for me',
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]
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if (aiStatus && !aiStatus.configured) {
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return (
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<div className="page">
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<h1 className="page-title">AI Coach</h1>
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<div className="card" style={{ textAlign: 'center', padding: '32px 20px' }}>
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<div style={{ fontSize: '2rem', marginBottom: '12px' }}>🤖</div>
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<h3 style={{ marginBottom: '8px' }}>No AI provider connected</h3>
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<p style={{ color: 'var(--text-2)', fontSize: '0.9rem', marginBottom: '16px' }}>
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Connect OpenAI, OpenRouter, Claude, Ollama, or any other provider to start chatting with your AI fitness coach.
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</p>
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<a href="/settings/integrations" className="btn-primary" style={{
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display: 'inline-block', padding: '12px 24px', borderRadius: 'var(--r)',
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background: 'var(--accent)', color: 'var(--text-inv)', textDecoration: 'none',
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fontWeight: 600, fontSize: '0.88rem',
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}}>
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Configure AI Provider
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</a>
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</div>
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</div>
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)
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}
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return (
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<div className="page" style={{ display: 'flex', flexDirection: 'column', paddingBottom: '96px' }}>
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<div style={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', marginBottom: '12px' }}>
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<h1 className="page-title" style={{ marginBottom: 0 }}>AI Coach</h1>
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{aiStatus?.provider && (
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<span style={{
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fontFamily: 'var(--font-mono)', fontSize: '0.7rem', color: 'var(--text-3)',
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background: 'var(--accent-bg)', padding: '4px 10px', borderRadius: 'var(--r-full)',
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}}>
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{aiStatus.provider} · {aiStatus.model}
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</span>
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)}
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</div>
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<div style={{ flex: 1, overflowY: 'auto', marginBottom: '12px' }}>
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{messages.length === 0 && (
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<div style={{ textAlign: 'center', padding: '24px 0' }}>
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<p style={{ color: 'var(--text-3)', fontSize: '0.9rem', marginBottom: '16px' }}>
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Ask me anything about your fitness, nutrition, or program.
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</p>
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<div style={{ display: 'flex', flexWrap: 'wrap', gap: '8px', justifyContent: 'center' }}>
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{suggestions.map(s => (
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<button key={s} className="btn-outline btn-sm" onClick={() => { setInput(s); }}
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style={{ fontSize: '0.8rem' }}>
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{s}
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</button>
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))}
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</div>
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</div>
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)}
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{messages.map((msg, i) => (
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<div key={i} style={{
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display: 'flex',
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justifyContent: msg.role === 'user' ? 'flex-end' : 'flex-start',
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marginBottom: '10px',
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}}>
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<div style={{
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maxWidth: '85%',
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padding: '10px 14px',
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borderRadius: msg.role === 'user'
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? 'var(--r-lg) var(--r-lg) var(--r-sm) var(--r-lg)'
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: 'var(--r-lg) var(--r-lg) var(--r-lg) var(--r-sm)',
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background: msg.role === 'user' ? 'var(--accent)' : 'var(--card)',
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color: msg.role === 'user' ? 'var(--text-inv)' : 'var(--text)',
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border: msg.role === 'user' ? 'none' : '1px solid var(--card-border)',
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fontSize: '0.9rem',
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lineHeight: '1.5',
|
||||
whiteSpace: 'pre-wrap',
|
||||
}}>
|
||||
{msg.content || (streaming && i === messages.length - 1 ? '...' : '')}
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
<div ref={scrollRef} />
|
||||
</div>
|
||||
|
||||
<div style={{
|
||||
display: 'flex', gap: '8px',
|
||||
position: 'sticky', bottom: '72px',
|
||||
background: 'var(--bg)', padding: '8px 0',
|
||||
}}>
|
||||
<input
|
||||
value={input}
|
||||
onChange={e => setInput(e.target.value)}
|
||||
onKeyDown={e => e.key === 'Enter' && !e.shiftKey && sendMessage()}
|
||||
placeholder={streaming ? 'Thinking...' : 'Ask your AI coach...'}
|
||||
disabled={streaming}
|
||||
style={{ flex: 1 }}
|
||||
/>
|
||||
<button
|
||||
onClick={sendMessage}
|
||||
disabled={streaming || !input.trim()}
|
||||
className="btn-primary"
|
||||
style={{ padding: '12px 18px', minWidth: 'auto' }}
|
||||
>
|
||||
{streaming ? '···' : '→'}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue