Upload api_env.py

api_env.py

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+from flask import Flask, request, send_file, jsonify
+from gevent.pywsgi import WSGIServer
+from functools import wraps
+from art import tprint
+import edge_tts
+import asyncio
+import tempfile
+import os
+
+app = Flask(__name__)
+
+# Use environment variables for API_KEY and PORT
+API_KEY = os.environ.get('API_KEY')
+PORT = int(os.environ.get('PORT', 5000))
+
+tprint("OPEN SPEECH")
+print(f"OpenSource TTS API Compatible with OpenAI API")
+print(f" ")
+print(f"   ---------------------------------------------------------------- ")
+print(f" * Serving OpenVoice API")
+print(f" * Server running on http://localhost:{PORT}")
+print(f" * Voice Endpoint Generated: http://localhost:{PORT}/v1/audio/speech")
+print(f" ")
+print("Press CTRL+C to quit")
+
+def require_api_key(f):
+    @wraps(f)
+    def decorated_function(*args, **kwargs):
+        auth_header = request.headers.get('Authorization')
+        if not auth_header or not auth_header.startswith('Bearer '):
+            return jsonify({"error": "Missing or invalid API key"}), 401
+        token = auth_header.split('Bearer ')[1]
+        if token != API_KEY:
+            return jsonify({"error": "Invalid API key"}), 401
+        return f(*args, **kwargs)
+    return decorated_function
+
+@app.route('/v1/audio/speech', methods=['POST'])
+@require_api_key
+def text_to_speech():
+    data = request.json
+    if not data or 'input' not in data:
+        return jsonify({"error": "Missing 'input' in request body"}), 400
+
+    text = data['input']
+    model = data.get('model', 'tts-1') # We will ignore this input
+    voice = data.get('voice', 'en-US-AriaNeural')
+
+    # Map OpenAI voices to edge-tts voices (this is a simple mapping, you might want to expand it)
+    voice_mapping = {
+        'alloy': 'en-US-AriaNeural',
+        'echo': 'en-US-GuyNeural',
+        'fable': 'en-GB-SoniaNeural',
+        'onyx': 'en-US-ChristopherNeural',
+        'nova': 'en-AU-NatashaNeural',
+        'shimmer': 'en-US-JennyNeural'
+    }
+
+    edge_tts_voice = voice_mapping.get(voice, voice)
+
+    output_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
+
+    async def generate_speech():
+        communicate = edge_tts.Communicate(text, edge_tts_voice)
+        await communicate.save(output_file.name)
+
+    asyncio.run(generate_speech())
+
+    return send_file(output_file.name, mimetype="audio/mpeg", as_attachment=True, download_name="speech.mp3")
+
+@app.route('/v1/models', methods=['GET'])
+@require_api_key
+def list_models():
+    # For simplicity, we're returning a fixed list of "models"
+    models = [
+        {"id": "tts-1", "name": "Text-to-speech v1"},
+        {"id": "tts-1-hd", "name": "Text-to-speech v1 HD"}
+    ]
+    return jsonify({"data": models})
+
+@app.route('/v1/voices', methods=['GET'])
+@require_api_key
+def list_voices():
+    voices = edge_tts.list_voices()
+    # Transform the voice data to match OpenAI's format
+    formatted_voices = [{"name": v['ShortName'], "language": v['Locale']} for v in voices]
+    return jsonify({"voices": formatted_voices})
+
+if __name__ == '__main__':
+    if not API_KEY:
+        print("Warning: API_KEY environment variable is not set.")
+    http_server = WSGIServer(('0.0.0.0', PORT), app)
+    http_server.serve_forever()