Update app.py

app.py

@@ -74,111 +74,111 @@
 # iface = gr.Interface(fn=function1, inputs="text", outputs=[gr.Audio(label="Audio",type="numpy")])
 # iface.launch()
 
+import gradio as gr
+import requests
+import urllib.request
+from pydub import AudioSegment
+import numpy as np
+import os
+import sys
+import wave
+import io
+import base64
+import azure.cognitiveservices.speech as speechsdk
+
+speech_key = os.environ.get("test3")
+service_region = os.environ.get("test4")
+
+speech_config = speechsdk.SpeechConfig(subscription=speech_key, region=service_region)
+# Note: the voice setting will not overwrite the voice element in input SSML.
+speech_config.speech_synthesis_voice_name = os.environ.get("test5")
+
+def function1(prompt):
+    response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={
+      "data": [
+        prompt,
+    ]}).json()
+    message = response["data"][0]
+    speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config)
+    result = speech_synthesizer.speak_text_async(message).get()
+    if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
+        audio_stream = io.BytesIO(result.audio_data)
+    
+        # Create a wave file object and write the audio data to it
+        with wave.open("audio.wav", 'wb') as wave_file:
+            wave_file.setnchannels(1)
+            wave_file.setsampwidth(2)
+            wave_file.setframerate(16000)
+            wave_file.writeframesraw(audio_stream.getvalue())
+        
+        # Use ffmpeg to convert the wave file to an mp3 file
+        filename = "output.mp3"
+        
+        if os.path.exists(filename):
+            os.remove(filename)
+        else:
+            pass
+        command = f"ffmpeg -i audio.wav -y -codec:a libmp3lame -qscale:a 2 {filename}"
+        os.system(command)
+        return "output.mp3"
+
+iface = gr.Interface(fn=function1, inputs="text", outputs=[gr.Audio(label="Audio",type="numpy")])
+iface.launch()
+
 # import gradio as gr
 # import requests
-# import urllib.request
-# from pydub import AudioSegment
-# import numpy as np
+# import json
 # import os
-# import sys
-# import wave
-# import io
-# import base64
-# import azure.cognitiveservices.speech as speechsdk
-
-# speech_key = os.environ.get("test3")
-# service_region = os.environ.get("test4")
 
-# speech_config = speechsdk.SpeechConfig(subscription=speech_key, region=service_region)
-# # Note: the voice setting will not overwrite the voice element in input SSML.
-# speech_config.speech_synthesis_voice_name = os.environ.get("test5")
-
-# def function1(prompt):
+# def function2(prompt):
 #     response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={
 #       "data": [
 #         prompt,
 #     ]}).json()
 #     message = response["data"][0]
-#     speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config)
-#     result = speech_synthesizer.speak_text_async(message).get()
-#     if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
-#         audio_stream = io.BytesIO(result.audio_data)
-    
-#         # Create a wave file object and write the audio data to it
-#         with wave.open("audio.wav", 'wb') as wave_file:
-#             wave_file.setnchannels(1)
-#             wave_file.setsampwidth(2)
-#             wave_file.setframerate(16000)
-#             wave_file.writeframesraw(audio_stream.getvalue())
-        
-#         # Use ffmpeg to convert the wave file to an mp3 file
-#         filename = "output.mp3"
-        
-#         if os.path.exists(filename):
-#             os.remove(filename)
-#         else:
-#             pass
-#         command = f"ffmpeg -i audio.wav -y -codec:a libmp3lame -qscale:a 2 {filename}"
-#         os.system(command)
-#         return "output.mp3"
 
-# iface = gr.Interface(fn=function1, inputs="text", outputs=[gr.Audio(label="Audio",type="numpy")])
-# iface.launch()
+#     url = "https://api.dynapictures.com/designs/7c4aba1d73"
+#     test6 = os.environ.get("test6")
+#     headers = {
+#         "Authorization": f"Bearer {test6}",
+#         "Content-Type": "application/json"
+#     }
 
-import gradio as gr
-import requests
-import json
-import os
+#     payload = {
+#       "format": "jpeg",
+#       "metadata": "some text",
+#       "params": [
+#         {
+#           "name": "bubble",
+#           "imageUrl": "https://dynapictures.com/b/rest/public/media/0ceb636a01/images/568b337221.png"
+#         },
+#         {
+#           "name": "quotes",
+#           "imageUrl": "https://dynapictures.com/b/rest/public/media/0ceb636a01/images/779f8b9041.png"
+#         },
+#         {
+#           "name": "text",
+#           "text": message
+#         },
+#         {
+#           "name": "avatar",
+#           "imageUrl": "https://dynapictures.com/b/rest/public/media/0ceb636a01/images/2f7ddd7b55.jpg"
+#         },
+#         {
+#           "name": "name",
+#           "text": "JohnAI"
+#         },
+#         {
+#           "name": "title",
+#           "text": "Automated"
+#         }
+#       ]
+#     }
 
-def function2(prompt):
-    response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={
-      "data": [
-        prompt,
-    ]}).json()
-    message = response["data"][0]
+#     response = requests.post(url, headers=headers, data=json.dumps(payload))
+#     response = response.json()
+#     response = response["imageUrl"]
+#     return response
 
-    url = "https://api.dynapictures.com/designs/7c4aba1d73"
-    test6 = os.environ.get("test6")
-    headers = {
-        "Authorization": f"Bearer {test6}",
-        "Content-Type": "application/json"
-    }
-
-    payload = {
-      "format": "jpeg",
-      "metadata": "some text",
-      "params": [
-        {
-          "name": "bubble",
-          "imageUrl": "https://dynapictures.com/b/rest/public/media/0ceb636a01/images/568b337221.png"
-        },
-        {
-          "name": "quotes",
-          "imageUrl": "https://dynapictures.com/b/rest/public/media/0ceb636a01/images/779f8b9041.png"
-        },
-        {
-          "name": "text",
-          "text": message
-        },
-        {
-          "name": "avatar",
-          "imageUrl": "https://dynapictures.com/b/rest/public/media/0ceb636a01/images/2f7ddd7b55.jpg"
-        },
-        {
-          "name": "name",
-          "text": "JohnAI"
-        },
-        {
-          "name": "title",
-          "text": "Automated"
-        }
-      ]
-    }
-
-    response = requests.post(url, headers=headers, data=json.dumps(payload))
-    response = response.json()
-    response = response["imageUrl"]
-    return response
-
-iface = gr.Interface(fn=function2, inputs="text", outputs="text")
-iface.launch()
+# iface = gr.Interface(fn=function2, inputs="text", outputs="text")
+# iface.launch()