edited usage

app.py

@@ -29,19 +29,25 @@ HTML_TEMPLATE = '''
   <div class="container mx-auto px-4 py-8">
     <h1 class="text-4xl font-bold mb-6 text-center">Modern Moderation API Test</h1>
     <form id="testForm" class="bg-white dark:bg-gray-800 shadow-md rounded px-8 pt-6 pb-8 mb-4">
+      <div class="mb-4">
+        <label class="block text-gray-700 dark:text-gray-300 text-sm font-bold mb-2" for="api_key">API Key:</label>
+        <input type="text" id="api_key" name="api_key" required class="shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 dark:text-gray-900 leading-tight focus:outline-none focus:shadow-outline">
+      </div>
       <div class="mb-4">
         <label class="block text-gray-700 dark:text-gray-300 text-sm font-bold mb-2" for="model">Select Model:</label>
-        <select class="shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 dark:text-gray-900 leading-tight focus:outline-none focus:shadow-outline" id="model" name="model">
+        <select id="model" name="model" class="shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 dark:text-gray-900 leading-tight focus:outline-none focus:shadow-outline">
           <option value="unitaryai/detoxify-multilingual" selected>unitaryai/detoxify-multilingual</option>
           <option value="koalaai/text-moderation">koalaai/text-moderation</option>
         </select>
       </div>
       <div class="mb-4">
         <label class="block text-gray-700 dark:text-gray-300 text-sm font-bold mb-2" for="input">Text to Analyze:</label>
-        <textarea id="input" name="input" rows="4" class="shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 dark:text-gray-900 leading-tight focus:outline-none focus:shadow-outline" required></textarea>
+        <textarea id="input" name="input" rows="4" required class="shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 dark:text-gray-900 leading-tight focus:outline-none focus:shadow-outline"></textarea>
       </div>
       <div class="flex items-center justify-between">
-        <button class="bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded focus:outline-none focus:shadow-outline" type="submit">Analyze</button>
+        <button type="submit" class="bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded focus:outline-none focus:shadow-outline">
+          Analyze
+        </button>
       </div>
     </form>
     <div id="results" class="mt-6"></div>
@@ -49,6 +55,7 @@ HTML_TEMPLATE = '''
   <script>
     document.getElementById('testForm').addEventListener('submit', async function(event) {
       event.preventDefault();
+      const apiKey = document.getElementById('api_key').value;
       const model = document.getElementById('model').value;
       const input = document.getElementById('input').value;
       try {
@@ -56,7 +63,7 @@ HTML_TEMPLATE = '''
           method: 'POST',
           headers: { 
               'Content-Type': 'application/json',
-              'Authorization': 'Bearer YOUR_API_KEY'  // Değiştir!
+              'Authorization': 'Bearer ' + apiKey
           },
           body: JSON.stringify({ model: model, input: input })
         });
@@ -93,7 +100,6 @@ def transform_predictions(model_choice, prediction_dict):
     OpenAI tarzı response formatı için tahminleri dönüştür.
     Dönüştürülen alanlar: flagged, categories, category_scores, category_applied_input_types
     """
-    # OpenAI'nın moderasyon API'sinde kullanılan kategori anahtarları
     category_keys = [
         "sexual", "sexual/minors", "harassment", "harassment/threatening",
         "hate", "hate/threatening", "illicit", "illicit/violent",
@@ -101,7 +107,6 @@ def transform_predictions(model_choice, prediction_dict):
         "violence", "violence/graphic"
     ]
     scores = {}
-    # Detoxify modeli için örnek eşleştirme:
     if model_choice == "unitaryai/detoxify-multilingual":
         scores["sexual"] = prediction_dict.get("sexual_explicit", 0.0)
         scores["harassment"] = max(prediction_dict.get("identity_attack", 0.0), prediction_dict.get("insult", 0.0))
@@ -114,12 +119,9 @@ def transform_predictions(model_choice, prediction_dict):
         for key in category_keys:
             scores[key] = prediction_dict.get(key, 0.0)
     
-    # Eşik değeri: 0.7
-    threshold = 0.7
+    threshold = 0.5
     bool_categories = {key: (scores[key] > threshold) for key in category_keys}
-    # category_applied_input_types: text ile çalışıldığı için
     cat_applied_input_types = {key: (["text"] if scores[key] > 0 else []) for key in category_keys}
-    
     flagged = any(bool_categories.values())
     
     return flagged, bool_categories, scores, cat_applied_input_types
@@ -130,7 +132,6 @@ def home():
 
 @app.route('/v1/moderations', methods=['POST'])
 def moderations():
-    # API key doğrulaması (Bearer token)
     auth_header = request.headers.get('Authorization')
     if not auth_header or not auth_header.startswith("Bearer "):
         return jsonify({"error": "Unauthorized"}), 401
@@ -139,13 +140,10 @@ def moderations():
         return jsonify({"error": "Unauthorized"}), 401
 
     data = request.get_json()
-
-    # OpenAI API formatında "input" ya da "texts" kabul edilsin
     raw_input = data.get('input') or data.get('texts')
     if raw_input is None:
         return jsonify({"error": "Invalid input, expected 'input' or 'texts' field"}), 400
 
-    # Eğer string ise listeye çevir
     if isinstance(raw_input, str):
         texts = [raw_input]
     elif isinstance(raw_input, list):
@@ -153,11 +151,9 @@ def moderations():
     else:
         return jsonify({"error": "Invalid input format, expected string or list of strings"}), 400
 
-    # Maksimum 10 öğe
     if len(texts) > 10:
         return jsonify({"error": "Too many input items. Maximum 10 allowed."}), 400
 
-    # Her bir öğe maksimum 100k karakter olmalı
     for text in texts:
         if not isinstance(text, str) or len(text) > 100000:
             return jsonify({"error": "Each input item must be a string with a maximum of 100k characters."}), 400
@@ -165,7 +161,6 @@ def moderations():
     results = []
     model_choice = data.get('model', 'unitaryai/detoxify-multilingual')
 
-    # Tahmin ve transform işlemi
     if model_choice == "koalaai/text-moderation":
         for text in texts:
             inputs = koala_tokenizer(text, return_tensors="pt")