detoxify-pub

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Utiric commited on Mar 13

Commit

176df74

1 Parent(s): 17d94c7

Added models, edited homepage and edited usage

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Files changed (1) hide show

app.py +110 -65

app.py CHANGED Viewed

@@ -1,95 +1,140 @@
 from flask import Flask, request, jsonify, render_template_string
 from detoxify import Detoxify
 import os
-# Flask uygulamasını başlat
 app = Flask(__name__)
-# Detoxify Multilingual modelini yükle
-model = Detoxify('multilingual')
-# API anahtarını environment variable'dan al
 API_KEY = os.getenv('API_KEY')
-# Test arayüzü için HTML şablonu
 HTML_TEMPLATE = '''
 <!DOCTYPE html>
 <html lang="en">
 <head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>Detoxify API Test</title>
 </head>
-<body>
-    <h1>Detoxify Multilingual API Test</h1>
-    <form id="testForm">
-        <label for="api_key">API Key:</label>
-        <input type="text" id="api_key" name="api_key" required><br><br>
-        <label for="text">Analiz Edilecek Metin:</label>
-        <input type="text" id="text" name="text" required><br><br>
-        <button type="submit">Analiz Et</button>
     </form>
-    <div id="results"></div>
-    <script>
-        document.getElementById('testForm').addEventListener('submit', function(event) {
-            event.preventDefault();
-            const apiKey = document.getElementById('api_key').value;
-            const text = document.getElementById('text').value;
-            fetch('/predict', {
-                method: 'POST',
-                headers: {
-                    'Content-Type': 'application/json'
-                },
-                body: JSON.stringify({api_key: apiKey, texts: [text]})
-            })
-            .then(response => response.json())
-            .then(data => {
-                const resultsDiv = document.getElementById('results');
-                if (data.error) {
-                    resultsDiv.innerHTML = `<p style="color:red;">Hata: ${data.error}</p>`;
-                } else {
-                    let html = '<h2>Sonuçlar:</h2>';
-                    for (const [key, value] of Object.entries(data)) {
-                        html += `<p>${key}: ${value[0].toFixed(5)}</p>`;
-                    }
-                    resultsDiv.innerHTML = html;
-                }
-            })
-            .catch(error => {
-                console.error('Hata:', error);
-            });
         });
-    </script>
 </body>
 </html>
 '''
-# Ana sayfa route'u
-@app.route('/')
-def home():
-    return render_template_string(HTML_TEMPLATE)
-# API endpoint'i
-@app.route('/predict', methods=['POST'])
-def predict():
-    # İstekten JSON verisini al
     data = request.get_json()
     api_key = data.get('api_key')
     texts = data.get('texts')
-    # API anahtarını kontrol et
     if api_key != API_KEY:
         return jsonify({"error": "Geçersiz API anahtarı"}), 401
-    # Girişin geçerli olduğunu kontrol et
     if not texts or not isinstance(texts, list):
         return jsonify({"error": "Geçersiz giriş, metin listesi bekleniyor"}), 400
-    # Detoxify modeliyle tahmin yap
-    results = model.predict(texts)
-    return jsonify(results)
-# Sunucuyu çalıştır (HuggingFace Spaces'de bu satır otomatik işlenir)
 if __name__ == '__main__':
     port = int(os.getenv('PORT', 7860))
-    app.run(host='0.0.0.0', port=port, debug=True)

 from flask import Flask, request, jsonify, render_template_string
 from detoxify import Detoxify
 import os
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
 app = Flask(__name__)
+# Load models
+detoxify_model = Detoxify('multilingual')
+koala_model = AutoModelForSequenceClassification.from_pretrained("KoalaAI/Text-Moderation")
+koala_tokenizer = AutoTokenizer.from_pretrained("KoalaAI/Text-Moderation")
+# Retrieve the API key from environment variables
 API_KEY = os.getenv('API_KEY')
+# Modern HTML interface with Tailwind CSS (dark/light compatible)
 HTML_TEMPLATE = '''
 <!DOCTYPE html>
 <html lang="en">
 <head>
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <title>Modern Detoxify & Moderation API Test</title>
+  <script src="https://cdn.tailwindcss.com"></script>
 </head>
+<body class="bg-gray-100 dark:bg-gray-900 text-gray-900 dark:text-gray-100">
+  <div class="container mx-auto px-4 py-8">
+    <h1 class="text-4xl font-bold mb-6 text-center">Modern Detoxify & 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 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" type="text" id="api_key" name="api_key" required>
+      </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">
+          <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="text">Text to Analyze:</label>
+        <input 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" type="text" id="text" name="text" required>
+      </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>
+      </div>
     </form>
+    <div id="results" class="mt-6"></div>
+  </div>
+  <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 text = document.getElementById('text').value;
+      try {
+        const response = await fetch('/v1/moderations', {
+          method: 'POST',
+          headers: { 'Content-Type': 'application/json' },
+          body: JSON.stringify({ api_key: apiKey, model: model, texts: [text] })
         });
+        const data = await response.json();
+        const resultsDiv = document.getElementById('results');
+        if (data.error) {
+          resultsDiv.innerHTML = `<p class="text-red-500 font-bold">Error: ${data.error}</p>`;
+        } else {
+          let html = '<h2 class="text-2xl font-bold mb-4">Results:</h2>';
+          data.results.forEach(item => {
+            html += `<div class="mb-4 p-4 bg-gray-200 dark:bg-gray-700 rounded">
+                       <p class="font-semibold">Input: ${item.input}</p>
+                       <ul>`;
+            for (const [key, value] of Object.entries(item.predictions)) {
+              html += `<li>${key}: ${value.toFixed(5)}</li>`;
+            }
+            html += `  </ul>
+                     </div>`;
+          });
+          resultsDiv.innerHTML = html;
+        }
+      } catch (error) {
+        console.error('Error:', error);
+      }
+    });
+  </script>
 </body>
 </html>
 '''
+# OpenAI-style API endpoint (/v1/moderations)
+@app.route('/v1/moderations', methods=['POST'])
+def moderations():
     data = request.get_json()
     api_key = data.get('api_key')
     texts = data.get('texts')
+    model_choice = data.get('model', 'unitaryai/detoxify-multilingual')
     if api_key != API_KEY:
         return jsonify({"error": "Geçersiz API anahtarı"}), 401
     if not texts or not isinstance(texts, list):
         return jsonify({"error": "Geçersiz giriş, metin listesi bekleniyor"}), 400
+    results = []
+    if model_choice == "koalaai/text-moderation":
+        for text in texts:
+            inputs = koala_tokenizer(text, return_tensors="pt")
+            outputs = koala_model(**inputs)
+            logits = outputs.logits
+            probabilities = torch.softmax(logits, dim=-1).squeeze().tolist()
+            # Ensure probabilities is a list
+            if isinstance(probabilities, float):
+                probabilities = [probabilities]
+            labels = [koala_model.config.id2label[idx] for idx in range(len(probabilities))]
+            prediction = {label: prob for label, prob in zip(labels, probabilities)}
+            results.append({"input": text, "predictions": prediction})
+        response_model = "koalaai/text-moderation"
+    else:
+        for text in texts:
+            pred = detoxify_model.predict([text])
+            # Convert Detoxify output (lists) to a simple dict with float values
+            prediction = {k: v[0] for k, v in pred.items()}
+            results.append({"input": text, "predictions": prediction})
+        response_model = "unitaryai/detoxify-multilingual"
+    response_data = {
+        "object": "moderation",
+        "model": response_model,
+        "results": results
+    }
+    return jsonify(response_data)
+@app.route('/')
+def home():
+    return render_template_string(HTML_TEMPLATE)
 if __name__ == '__main__':
     port = int(os.getenv('PORT', 7860))
+    app.run(host='0.0.0.0', port=port, debug=True)