Add complete Mail Fine-Tuning Web-App for macOS Apple Silicon
Implemented a full-stack web application for fine-tuning LLMs on email data, optimized for Apple Silicon (M4 Pro with 24GB RAM). Features: - Mail import with drag & drop support (.mbox, .eml, .txt) - Automated mail cleaning and preprocessing - Interactive labeling interface with keyboard shortcuts - Training data export to JSONL format - MLX-based LoRA fine-tuning with live updates - Model evaluation and comparison interface - Server-Sent Events for real-time training progress - Dark theme UI optimized for extended use Technical Stack: - Backend: FastAPI with SQLite database - Frontend: Vanilla HTML/CSS/JavaScript (no external dependencies) - ML Framework: MLX for Apple Silicon optimization - Models: Support for Mistral 7B and Llama 3 8B via MLX Components: - data_manager.py: SQLite operations for mail storage and labeling - mail_parser.py: Parser for multiple mail formats with cleaning - training.py: MLX training wrapper with LoRA support - inference.py: Model loading and inference for evaluation - main.py: FastAPI backend with REST API and SSE - Frontend: Complete UI with all features Documentation: - Comprehensive README with installation and usage guide - Quick-start guide for rapid setup - Example mails for testing - Troubleshooting and best practices Ready for local deployment and fine-tuning workflows.
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Claude
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<!DOCTYPE html>
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<html lang="de">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Mail Fine-Tuning App</title>
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<link rel="stylesheet" href="style.css">
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</head>
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<body>
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<div class="app-container">
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<!-- Sidebar Navigation -->
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<nav class="sidebar">
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<h1>Mail Fine-Tuning</h1>
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<ul class="nav-menu">
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<li><a href="#" data-view="import" class="nav-link active">📥 Mail Import</a></li>
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<li><a href="#" data-view="labeling" class="nav-link">🏷️ Labeling</a></li>
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<li><a href="#" data-view="export" class="nav-link">📊 Export & Stats</a></li>
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<li><a href="#" data-view="models" class="nav-link">🤖 Modelle</a></li>
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<li><a href="#" data-view="training" class="nav-link">🎯 Training</a></li>
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<li><a href="#" data-view="evaluation" class="nav-link">🧪 Evaluation</a></li>
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</ul>
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</nav>
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<!-- Main Content -->
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<main class="main-content">
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<!-- Import View -->
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<div id="import-view" class="view active">
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<h2>Mail Import</h2>
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<div class="upload-section">
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<div class="dropzone" id="dropzone">
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<p>📂 Dateien hier ablegen oder klicken</p>
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<p class="hint">Unterstützt: .eml, .mbox, .txt</p>
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<input type="file" id="file-input" multiple accept=".eml,.mbox,.txt" hidden>
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</div>
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</div>
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<div class="mail-list-section">
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<div class="section-header">
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<h3>Importierte Mails (<span id="mail-count">0</span>)</h3>
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<button id="refresh-mails" class="btn btn-secondary">🔄 Aktualisieren</button>
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</div>
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<div id="mail-list" class="mail-list">
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<!-- Mails werden hier eingefügt -->
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</div>
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</div>
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</div>
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<!-- Labeling View -->
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<div id="labeling-view" class="view">
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<div class="section-header">
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<h2>Mail Labeling</h2>
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<div class="filter-controls">
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<select id="status-filter">
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<option value="">Alle anzeigen</option>
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<option value="unlabeled" selected>Nur Unlabeled</option>
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<option value="labeled">Nur Labeled</option>
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<option value="skip">Übersprungen</option>
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</select>
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</div>
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</div>
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<div class="progress-bar">
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<div class="progress-fill" id="labeling-progress"></div>
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<span class="progress-text" id="progress-text">0 / 0 gelabelt</span>
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</div>
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<div class="keyboard-hints">
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Shortcuts: <kbd>N</kbd> Nächste | <kbd>S</kbd> Speichern | <kbd>K</kbd> Skip
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</div>
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<div id="labeling-container">
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<!-- Labeling Interface wird hier geladen -->
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</div>
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</div>
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<!-- Export View -->
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<div id="export-view" class="view">
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<h2>Daten Export & Statistiken</h2>
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<div class="stats-grid" id="stats-grid">
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<!-- Stats werden hier eingefügt -->
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</div>
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<div class="export-section">
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<h3>Training-Daten exportieren</h3>
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<div class="export-controls">
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<label>
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Train/Val Split:
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<input type="number" id="train-split" value="90" min="50" max="95" step="5">%
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</label>
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<button id="export-jsonl" class="btn btn-primary">📦 JSONL generieren</button>
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</div>
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<div id="export-result"></div>
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</div>
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</div>
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<!-- Models View -->
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<div id="models-view" class="view">
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<h2>Modell-Verwaltung</h2>
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<div class="model-section">
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<h3>Verfügbare Modelle</h3>
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<div id="models-list" class="models-list">
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<!-- Modelle werden hier geladen -->
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</div>
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<div class="model-download">
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<h3>Modell herunterladen</h3>
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<p class="info-text">
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Modelle müssen manuell heruntergeladen werden. Empfohlen:
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</p>
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<ul>
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<li>mlx-community/Mistral-7B-Instruct-v0.3-4bit</li>
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<li>mlx-community/Meta-Llama-3-8B-Instruct-4bit</li>
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</ul>
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<p class="code-example">
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huggingface-cli download [model-name] --local-dir models/[model-name]
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</p>
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</div>
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</div>
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</div>
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<!-- Training View -->
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<div id="training-view" class="view">
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<h2>Training</h2>
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<div class="training-config">
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<h3>Konfiguration</h3>
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<form id="training-form">
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<div class="form-group">
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<label>Modell:</label>
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<select id="training-model" required>
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<option value="">-- Modell wählen --</option>
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</select>
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</div>
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<div class="form-group">
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<label>
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Learning Rate: <span id="lr-value">1e-5</span>
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</label>
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<input type="range" id="learning-rate"
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min="-6" max="-4" step="0.1" value="-5">
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</div>
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<div class="form-group">
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<label>
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Epochs: <span id="epochs-value">3</span>
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</label>
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<input type="range" id="epochs"
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min="1" max="10" value="3">
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</div>
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<div class="form-group">
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<label>Batch Size:</label>
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<select id="batch-size">
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<option value="1">1</option>
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<option value="2">2</option>
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<option value="4" selected>4</option>
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<option value="8">8</option>
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</select>
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</div>
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<div class="form-group">
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<label>LoRA Rank:</label>
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<select id="lora-rank">
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<option value="4">4</option>
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<option value="8" selected>8</option>
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<option value="16">16</option>
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<option value="32">32</option>
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</select>
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</div>
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<div class="form-actions">
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<button type="submit" class="btn btn-primary" id="start-training">
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▶️ Training starten
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</button>
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<button type="button" class="btn btn-danger" id="stop-training" disabled>
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⏹️ Training stoppen
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</button>
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</div>
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</form>
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</div>
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<div class="training-status" id="training-status">
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<!-- Training Status wird hier angezeigt -->
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</div>
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<div class="training-charts">
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<div class="chart-container">
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<h4>Training Loss</h4>
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<canvas id="train-loss-chart"></canvas>
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</div>
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<div class="chart-container">
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<h4>Validation Loss</h4>
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<canvas id="val-loss-chart"></canvas>
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</div>
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</div>
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</div>
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<!-- Evaluation View -->
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<div id="evaluation-view" class="view">
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<h2>Modell Evaluation</h2>
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<div class="eval-controls">
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<h3>Chat Interface</h3>
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<div class="form-group">
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<label>Task Type:</label>
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<select id="eval-task-type">
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<option value="Zusammenfassen">Zusammenfassen</option>
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<option value="Antwort schreiben">Antwort schreiben</option>
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<option value="Kategorisieren">Kategorisieren</option>
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<option value="Action Items">Action Items</option>
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<option value="Custom">Custom</option>
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</select>
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</div>
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<div class="form-group">
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<label>Mail-Text:</label>
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<textarea id="eval-mail-text" rows="6" placeholder="Mail-Text hier eingeben..."></textarea>
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</div>
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<div class="form-group">
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<button id="load-test-prompt" class="btn btn-secondary">📝 Test-Beispiel laden</button>
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<button id="run-comparison" class="btn btn-primary">🔍 Vergleich starten</button>
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</div>
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</div>
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<div class="comparison-results">
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<div class="result-box">
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<h4>Base Model</h4>
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<div id="base-result" class="result-content">
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Noch kein Ergebnis
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</div>
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</div>
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<div class="result-box">
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<h4>Fine-tuned Model</h4>
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<div id="finetuned-result" class="result-content">
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Noch kein Ergebnis
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</div>
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</div>
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</div>
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</div>
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</main>
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</div>
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<!-- Toast Notifications -->
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<div id="toast-container"></div>
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<script src="app.js"></script>
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</body>
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</html>
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