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<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>AI Knowledge Base Server</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
    <style>
        .gradient-bg {
            background: linear-gradient(135deg, #6e8efb, #a777e3);
        }
        .knowledge-card {
            transition: all 0.3s ease;
            border-left: 4px solid #6e8efb;
        }
        .knowledge-card:hover {
            transform: translateY(-5px);
            box-shadow: 0 10px 20px rgba(0,0,0,0.1);
        }
        .file-upload {
            border: 2px dashed #a777e3;
            transition: all 0.3s ease;
        }
        .file-upload:hover {
            background-color: rgba(167, 119, 227, 0.1);
        }
        .sidebar {
            transition: all 0.3s ease;
        }
        .sidebar-item:hover {
            background-color: rgba(255,255,255,0.1);
        }
        .pulse-animation {
            animation: pulse 2s infinite;
        }
        @keyframes pulse {
            0% { box-shadow: 0 0 0 0 rgba(110, 142, 251, 0.7); }
            70% { box-shadow: 0 0 0 10px rgba(110, 142, 251, 0); }
            100% { box-shadow: 0 0 0 0 rgba(110, 142, 251, 0); }
        }
    </style>
</head>
<body class="bg-gray-100 font-sans">
    <!-- Flask Server Implementation (would normally be in separate files) -->
    <script type="text/python">
        from flask import Flask, request, jsonify, send_from_directory
        import os
        import uuid
        from werkzeug.utils import secure_filename
        import json
        from datetime import datetime
        import threading
        import hashlib

        app = Flask(__name__)
        app.config['UPLOAD_FOLDER'] = 'knowledge_base'
        app.config['MAX_CONTENT_LENGTH'] = 100 * 1024 * 1024  # 100MB limit
        app.config['ALLOWED_EXTENSIONS'] = {'txt', 'pdf', 'py', 'js', 'html', 'css', 'json', 'md', 'csv', 'ipynb'}

        # Create knowledge base directory if it doesn't exist
        if not os.path.exists(app.config['UPLOAD_FOLDER']):
            os.makedirs(app.config['UPLOAD_FOLDER'])
            os.makedirs(os.path.join(app.config['UPLOAD_FOLDER'], 'metadata'))
            os.makedirs(os.path.join(app.config['UPLOAD_FOLDER'], 'embeddings'))

        # Knowledge Base Index
        KNOWLEDGE_INDEX = os.path.join(app.config['UPLOAD_FOLDER'], 'knowledge_index.json')
        if not os.path.exists(KNOWLEDGE_INDEX):
            with open(KNOWLEDGE_INDEX, 'w') as f:
                json.dump({"files": {}, "categories": {}, "tags": {}}, f)

        def allowed_file(filename):
            return '.' in filename and \
                   filename.rsplit('.', 1)[1].lower() in app.config['ALLOWED_EXTENSIONS']

        def update_knowledge_index(file_data):
            with open(KNOWLEDGE_INDEX, 'r+') as f:
                index = json.load(f)
                index['files'][file_data['id']] = file_data
                
                # Update categories
                for category in file_data.get('categories', []):
                    if category not in index['categories']:
                        index['categories'][category] = []
                    if file_data['id'] not in index['categories'][category]:
                        index['categories'][category].append(file_data['id'])
                
                # Update tags
                for tag in file_data.get('tags', []):
                    if tag not in index['tags']:
                        index['tags'][tag] = []
                    if file_data['id'] not in index['tags'][tag]:
                        index['tags'][tag].append(file_data['id'])
                
                f.seek(0)
                json.dump(index, f, indent=2)
                f.truncate()

        def generate_embeddings(filepath):
            # This would be replaced with actual embedding generation
            # For demo purposes, we'll just create a placeholder
            embedding_id = str(uuid.uuid4())
            embedding_path = os.path.join(app.config['UPLOAD_FOLDER'], 'embeddings', f"{embedding_id}.json")
            
            # Simulate embedding generation
            with open(filepath, 'r') as f:
                content = f.read()
                # Simple hash as a placeholder for real embeddings
                embedding = hashlib.sha256(content.encode()).hexdigest()
            
            with open(embedding_path, 'w') as f:
                json.dump({
                    "id": embedding_id,
                    "file_id": os.path.basename(filepath),
                    "embedding": embedding,
                    "created_at": datetime.now().isoformat()
                }, f)
            
            return embedding_id

        @app.route('/api/upload', methods=['POST'])
        def upload_file():
            if 'file' not in request.files:
                return jsonify({"error": "No file part"}), 400
            
            file = request.files['file']
            if file.filename == '':
                return jsonify({"error": "No selected file"}), 400
            
            if file and allowed_file(file.filename):
                filename = secure_filename(file.filename)
                file_id = str(uuid.uuid4())
                filepath = os.path.join(app.config['UPLOAD_FOLDER'], file_id)
                file.save(filepath)
                
                # Extract metadata from form
                metadata = {
                    "id": file_id,
                    "original_filename": filename,
                    "uploaded_at": datetime.now().isoformat(),
                    "categories": request.form.get('categories', '').split(','),
                    "tags": request.form.get('tags', '').split(','),
                    "description": request.form.get('description', ''),
                    "file_type": filename.rsplit('.', 1)[1].lower(),
                    "size": os.path.getsize(filepath)
                }
                
                # Save metadata
                metadata_path = os.path.join(app.config['UPLOAD_FOLDER'], 'metadata', f"{file_id}.json")
                with open(metadata_path, 'w') as f:
                    json.dump(metadata, f)
                
                # Update knowledge index
                update_knowledge_index(metadata)
                
                # Generate embeddings in background
                threading.Thread(target=generate_embeddings, args=(filepath,)).start()
                
                return jsonify({
                    "message": "File uploaded successfully",
                    "file_id": file_id,
                    "metadata": metadata
                }), 201
            
            return jsonify({"error": "File type not allowed"}), 400

        @app.route('/api/knowledge', methods=['GET'])
        def get_knowledge():
            with open(KNOWLEDGE_INDEX, 'r') as f:
                index = json.load(f)
                return jsonify(index), 200

        @app.route('/api/search', methods=['GET'])
        def search_knowledge():
            query = request.args.get('q', '')
            category = request.args.get('category', '')
            tag = request.args.get('tag', '')
            
            with open(KNOWLEDGE_INDEX, 'r') as f:
                index = json.load(f)
                
                results = []
                for file_id, file_data in index['files'].items():
                    # Simple search - in a real implementation, this would use embeddings
                    matches = (
                        query.lower() in file_data['original_filename'].lower() or
                        query.lower() in file_data.get('description', '').lower() or
                        any(query.lower() in tag.lower() for tag in file_data.get('tags', []))
                    )
                    
                    category_match = not category or category in file_data.get('categories', [])
                    tag_match = not tag or tag in file_data.get('tags', [])
                    
                    if matches and category_match and tag_match:
                        results.append(file_data)
                
                return jsonify({"results": results}), 200

        @app.route('/api/train', methods=['POST'])
        def train_model():
            # This endpoint would interface with your AI models
            model_name = request.json.get('model', 'deepseek-v3.1')
            file_ids = request.json.get('file_ids', [])
            
            # In a real implementation, this would:
            # 1. Load the specified model
            # 2. Retrieve the requested files
            # 3. Fine-tune the model with the knowledge
            # 4. Save the improved model
            
            return jsonify({
                "message": f"Model {model_name} training initiated with {len(file_ids)} files",
                "status": "queued",
                "training_id": str(uuid.uuid4())
            }), 202

        if __name__ == '__main__':
            app.run(host='0.0.0.0', port=5000, debug=True)
    </script>

    <!-- Frontend UI -->
    <div class="flex h-screen overflow-hidden">
        <!-- Sidebar -->
        <div class="sidebar w-64 bg-gray-900 text-white flex flex-col">
            <div class="p-4 border-b border-gray-700">
                <h1 class="text-2xl font-bold flex items-center">
                    <i class="fas fa-brain mr-2 text-purple-400"></i>
                    AI Knowledge Base
                </h1>
                <p class="text-gray-400 text-sm mt-1">Your centralized intelligence hub</p>
            </div>
            
            <div class="flex-1 overflow-y-auto">
                <div class="p-4">
                    <h2 class="text-lg font-semibold text-gray-300 mb-2 flex items-center">
                        <i class="fas fa-folder-open mr-2 text-blue-400"></i>
                        Categories
                    </h2>
                    <ul id="categories-list" class="space-y-1">
                        <li class="sidebar-item px-3 py-2 rounded cursor-pointer bg-gray-800">
                            <i class="fas fa-code mr-2 text-green-400"></i>
                            Code Frameworks
                        </li>
                        <li class="sidebar-item px-3 py-2 rounded cursor-pointer">
                            <i class="fas fa-file-alt mr-2 text-yellow-400"></i>
                            Documentation
                        </li>
                        <li class="sidebar-item px-3 py-2 rounded cursor-pointer">
                            <i class="fas fa-chart-line mr-2 text-red-400"></i>
                            Analytics
                        </li>
                        <li class="sidebar-item px-3 py-2 rounded cursor-pointer">
                            <i class="fas fa-project-diagram mr-2 text-purple-400"></i>
                            Projects
                        </li>
                    </ul>
                </div>
                
                <div class="p-4 border-t border-gray-700">
                    <h2 class="text-lg font-semibold text-gray-300 mb-2 flex items-center">
                        <i class="fas fa-tags mr-2 text-blue-400"></i>
                        Popular Tags
                    </h2>
                    <div id="tags-list" class="flex flex-wrap gap-2">
                        <span class="sidebar-item px-2 py-1 rounded-full text-xs bg-gray-800 cursor-pointer">
                            #python
                        </span>
                        <span class="sidebar-item px-2 py-1 rounded-full text-xs bg-gray-800 cursor-pointer">
                            #ai
                        </span>
                        <span class="sidebar-item px-2 py-1 rounded-full text-xs bg-gray-800 cursor-pointer">
                            #flask
                        </span>
                        <span class="sidebar-item px-2 py-1 rounded-full text-xs bg-gray-800 cursor-pointer">
                            #machinelearning
                        </span>
                    </div>
                </div>
                
                <div class="p-4 border-t border-gray-700">
                    <h2 class="text-lg font-semibold text-gray-300 mb-2 flex items-center">
                        <i class="fas fa-cog mr-2 text-blue-400"></i>
                        AI Models
                    </h2>
                    <ul class="space-y-2">
                        <li class="sidebar-item px-3 py-2 rounded cursor-pointer flex items-center justify-between">
                            <div>
                                <i class="fas fa-robot mr-2 text-green-400"></i>
                                DeepSeek V3.1
                            </div>
                            <span class="text-xs bg-green-500 text-white px-2 py-1 rounded-full">Active</span>
                        </li>
                        <li class="sidebar-item px-3 py-2 rounded cursor-pointer flex items-center">
                            <i class="fas fa-robot mr-2 text-blue-400"></i>
                            Local LLM
                        </li>
                    </ul>
                </div>
            </div>
            
            <div class="p-4 border-t border-gray-700">
                <button id="upload-btn" class="w-full gradient-bg text-white py-2 px-4 rounded-lg font-medium flex items-center justify-center">
                    <i class="fas fa-cloud-upload-alt mr-2"></i>
                    Upload Knowledge
                </button>
            </div>
        </div>
        
        <!-- Main Content -->
        <div class="flex-1 flex flex-col overflow-hidden">
            <!-- Header -->
            <header class="bg-white shadow-sm z-10">
                <div class="flex items-center justify-between px-6 py-4">
                    <div class="flex items-center">
                        <div class="relative w-64">
                            <input type="text" placeholder="Search knowledge base..." 
                                   class="w-full pl-10 pr-4 py-2 rounded-lg border border-gray-300 focus:outline-none focus:ring-2 focus:ring-purple-500 focus:border-transparent">
                            <i class="fas fa-search absolute left-3 top-3 text-gray-400"></i>
                        </div>
                    </div>
                    
                    <div class="flex items-center space-x-4">
                        <button class="pulse-animation gradient-bg text-white py-2 px-4 rounded-lg font-medium flex items-center">
                            <i class="fas fa-bolt mr-2"></i>
                            Train AI Model
                        </button>
                        <div class="h-8 w-8 rounded-full bg-purple-500 flex items-center justify-center text-white font-bold">
                            <i class="fas fa-user"></i>
                        </div>
                    </div>
                </div>
            </header>
            
            <!-- Content -->
            <main class="flex-1 overflow-y-auto p-6 bg-gray-50">
                <div class="mb-6 flex justify-between items-center">
                    <h2 class="text-2xl font-bold text-gray-800">Knowledge Repository</h2>
                    <div class="flex space-x-2">
                        <button class="bg-white border border-gray-300 px-3 py-1 rounded-lg text-sm flex items-center">
                            <i class="fas fa-filter mr-2 text-gray-500"></i>
                            Filter
                        </button>
                        <button class="bg-white border border-gray-300 px-3 py-1 rounded-lg text-sm flex items-center">
                            <i class="fas fa-sort mr-2 text-gray-500"></i>
                            Sort
                        </button>
                    </div>
                </div>
                
                <!-- Stats Cards -->
                <div class="grid grid-cols-1 md:grid-cols-4 gap-4 mb-6">
                    <div class="bg-white rounded-lg shadow p-4">
                        <div class="flex items-center justify-between">
                            <div>
                                <p class="text-gray-500 text-sm">Total Files</p>
                                <h3 class="text-2xl font-bold">1,248</h3>
                            </div>
                            <div class="p-3 rounded-full bg-blue-100 text-blue-500">
                                <i class="fas fa-file-alt"></i>
                            </div>
                        </div>
                    </div>
                    <div class="bg-white rounded-lg shadow p-4">
                        <div class="flex items-center justify-between">
                            <div>
                                <p class="text-gray-500 text-sm">AI Models</p>
                                <h3 class="text-2xl font-bold">5</h3>
                            </div>
                            <div class="p-3 rounded-full bg-purple-100 text-purple-500">
                                <i class="fas fa-robot"></i>
                            </div>
                        </div>
                    </div>
                    <div class="bg-white rounded-lg shadow p-4">
                        <div class="flex items-center justify-between">
                            <div>
                                <p class="text-gray-500 text-sm">Knowledge Used</p>
                                <h3 class="text-2xl font-bold">87%</h3>
                            </div>
                            <div class="p-3 rounded-full bg-green-100 text-green-500">
                                <i class="fas fa-chart-pie"></i>
                            </div>
                        </div>
                    </div>
                    <div class="bg-white rounded-lg shadow p-4">
                        <div class="flex items-center justify-between">
                            <div>
                                <p class="text-gray-500 text-sm">Last Training</p>
                                <h3 class="text-2xl font-bold">2h ago</h3>
                            </div>
                            <div class="p-3 rounded-full bg-yellow-100 text-yellow-500">
                                <i class="fas fa-bolt"></i>
                            </div>
                        </div>
                    </div>
                </div>
                
                <!-- Knowledge Items -->
                <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4">
                    <!-- Sample knowledge cards -->
                    <div class="knowledge-card bg-white rounded-lg shadow p-4">
                        <div class="flex items-start justify-between mb-3">
                            <div class="flex items-center">
                                <div class="p-2 rounded-lg bg-blue-100 text-blue-500 mr-3">
                                    <i class="fas fa-code"></i>
                                </div>
                                <div>
                                    <h4 class="font-bold">Custom AI Framework</h4>
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