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detoxify

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Utiric commited on 7 days ago

Commit

c7133b5

1 Parent(s): 176df74

Edited usage

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Files changed (1) hide show

app.py +23 -24

app.py CHANGED Viewed

@@ -1,7 +1,7 @@
 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__)
@@ -11,27 +11,23 @@ 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">
@@ -52,14 +48,16 @@ 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 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');
@@ -88,19 +86,26 @@ HTML_TEMPLATE = '''
 </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":
@@ -109,7 +114,6 @@ def moderations():
             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))]
@@ -119,7 +123,6 @@ def moderations():
     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"
@@ -131,10 +134,6 @@ def moderations():
     }
     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)

 from flask import Flask, request, jsonify, render_template_string
 import os
 import torch
+from detoxify import Detoxify
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 app = Flask(__name__)
 koala_model = AutoModelForSequenceClassification.from_pretrained("KoalaAI/Text-Moderation")
 koala_tokenizer = AutoTokenizer.from_pretrained("KoalaAI/Text-Moderation")
+# API key from environment variable
 API_KEY = os.getenv('API_KEY')
+# Modern HTML interface with Tailwind CSS
 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 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 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="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">
   <script>
     document.getElementById('testForm').addEventListener('submit', async function(event) {
       event.preventDefault();
       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',
+              'Authorization': 'Bearer YOUR_API_KEY'  // Replace YOUR_API_KEY with your actual API key
+          },
+          body: JSON.stringify({ model: model, texts: [text] })
         });
         const data = await response.json();
         const resultsDiv = document.getElementById('results');
 </html>
 '''
+@app.route('/')
+def home():
+    return render_template_string(HTML_TEMPLATE)
 @app.route('/v1/moderations', methods=['POST'])
 def moderations():
+    # Retrieve API key from Authorization header in Bearer format
+    auth_header = request.headers.get('Authorization')
+    if not auth_header or not auth_header.startswith("Bearer "):
+        return jsonify({"error": "Unauthorized"}), 401
+    provided_api_key = auth_header.split(" ")[1]
+    if provided_api_key != API_KEY:
+        return jsonify({"error": "Unauthorized"}), 401
     data = request.get_json()
     texts = data.get('texts')
     model_choice = data.get('model', 'unitaryai/detoxify-multilingual')
     if not texts or not isinstance(texts, list):
+        return jsonify({"error": "Invalid input, expected a list of texts"}), 400
     results = []
     if model_choice == "koalaai/text-moderation":
             outputs = koala_model(**inputs)
             logits = outputs.logits
             probabilities = torch.softmax(logits, dim=-1).squeeze().tolist()
             if isinstance(probabilities, float):
                 probabilities = [probabilities]
             labels = [koala_model.config.id2label[idx] for idx in range(len(probabilities))]
     else:
         for text in texts:
             pred = detoxify_model.predict([text])
             prediction = {k: v[0] for k, v in pred.items()}
             results.append({"input": text, "predictions": prediction})
         response_model = "unitaryai/detoxify-multilingual"
     }
     return jsonify(response_data)
 if __name__ == '__main__':
     port = int(os.getenv('PORT', 7860))
     app.run(host='0.0.0.0', port=port, debug=True)