Create model_suggestions.py

model_suggestions.py

@@ -0,0 +1,141 @@
+from nc_py_api import Nextcloud
+import json
+from typing import Dict, List
+import os
+import time
+from datetime import datetime
+import threading
+import arena_config
+import re
+
+# Initialize Nextcloud client
+nc = Nextcloud(
+    nextcloud_url=arena_config.NEXTCLOUD_URL,
+    nc_auth_user=arena_config.NEXTCLOUD_USERNAME,
+    nc_auth_pass=arena_config.NEXTCLOUD_PASSWORD
+)
+
+SUGGESTIONS_FILE = "model_suggestions.json"
+NEXTCLOUD_SUGGESTIONS_PATH = "/gpu_poor_model_suggestions.json"
+
+def validate_model_url(url: str) -> bool:
+    """Validate if the provided URL matches the expected HuggingFace format."""
+    pattern = r'^hf\.co/[\w-]+/[\w\.-]+(?:-GGUF)?:Q[0-9]+(?:_[A-Z0-9_]+)?$'
+    return bool(re.match(pattern, url))
+
+def load_suggestions() -> Dict:
+    """Load suggestions from local file or initialize if not exists."""
+    if os.path.exists(SUGGESTIONS_FILE):
+        with open(SUGGESTIONS_FILE, 'r') as f:
+            return json.load(f)
+    return {
+        "suggestions": {},
+        "last_updated": datetime.now().isoformat()
+    }
+
+def save_suggestions(suggestions: Dict) -> None:
+    """Save suggestions to both local file and Nextcloud."""
+    with open(SUGGESTIONS_FILE, 'w') as f:
+        json.dump(suggestions, f, indent=2)
+    
+    # Upload to Nextcloud
+    try:
+        nc.files.upload(
+            NEXTCLOUD_SUGGESTIONS_PATH,
+            json.dumps(suggestions, indent=2).encode('utf-8')
+        )
+    except Exception as e:
+        print(f"Error uploading to Nextcloud: {e}")
+
+def add_suggestion(model_url: str) -> str:
+    """Add a new model suggestion or update existing one."""
+    if not validate_model_url(model_url):
+        return "❌ Invalid model URL format. Please use the format: hf.co/username/model-name-GGUF:Q4_K_M"
+    
+    suggestions = load_suggestions()
+    
+    if model_url in suggestions["suggestions"]:
+        suggestions["suggestions"][model_url]["count"] += 1
+        suggestions["suggestions"][model_url]["last_suggested"] = datetime.now().isoformat()
+        message = f"✨ Model suggestion updated! This model has been suggested {suggestions['suggestions'][model_url]['count']} times."
+    else:
+        suggestions["suggestions"][model_url] = {
+            "count": 1,
+            "first_suggested": datetime.now().isoformat(),
+            "last_suggested": datetime.now().isoformat()
+        }
+        message = "✅ New model suggestion recorded successfully!"
+    
+    suggestions["last_updated"] = datetime.now().isoformat()
+    save_suggestions(suggestions)
+    
+    return message
+
+def get_suggestions_html() -> str:
+    """Generate HTML table of model suggestions."""
+    suggestions = load_suggestions()
+    
+    # Sort suggestions by count (descending)
+    sorted_suggestions = sorted(
+        suggestions["suggestions"].items(),
+        key=lambda x: x[1]["count"],
+        reverse=True
+    )
+    
+    html = """
+    <style>
+        .suggestions-table {
+            width: 100%;
+            border-collapse: collapse;
+            font-family: Arial, sans-serif;
+        }
+        .suggestions-table th, .suggestions-table td {
+            border: 1px solid #ddd;
+            padding: 8px;
+            text-align: left;
+        }
+        .suggestions-table th {
+            background-color: rgba(255, 255, 255, 0.1);
+            font-weight: bold;
+        }
+        .rank-column {
+            width: 60px;
+            text-align: center;
+        }
+        .count-badge {
+            background-color: rgba(34, 87, 122, 0.7);
+            color: white;
+            padding: 4px 8px;
+            border-radius: 12px;
+            font-size: 0.9em;
+        }
+        .description-column {
+            font-size: 0.9em;
+            color: #888;
+        }
+    </style>
+    <table class='suggestions-table'>
+    <tr>
+        <th class='rank-column'>Rank</th>
+        <th>Model URL</th>
+        <th>Suggestions</th>
+        <th>First Suggested</th>
+        <th>Last Suggested</th>
+    </tr>
+    """
+    
+    for index, (model_url, data) in enumerate(sorted_suggestions, start=1):
+        rank_display = {1: "🥇", 2: "🥈", 3: "🥉"}.get(index, f"{index}")
+        
+        html += f"""
+        <tr>
+            <td class='rank-column'>{rank_display}</td>
+            <td>{model_url}</td>
+            <td><span class="count-badge">{data['count']}</span></td>
+            <td>{data['first_suggested'].split('T')[0]}</td>
+            <td>{data['last_suggested'].split('T')[0]}</td>
+        </tr>
+        """
+    
+    html += "</table>"
+    return html