| # import gradio as gr | |
| # import requests | |
| # import os | |
| # def function1(prompt): | |
| # response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={ | |
| # "data": [ | |
| # prompt, | |
| # ]}).json() | |
| # message = response["data"][0] | |
| # url = 'https://api.elevenlabs.io/v1/text-to-speech/pNInz6obpgDQGcFmaJgB' | |
| # headers = { | |
| # 'accept': 'audio/mpeg', | |
| # 'xi-api-key': os.environ.get("test2"), | |
| # 'Content-Type': 'application/json' | |
| # } | |
| # data = { | |
| # "text": message, | |
| # "voice_settings": { | |
| # "stability": 0, | |
| # "similarity_boost": 0 | |
| # } | |
| # } | |
| # response = requests.post(url, headers=headers, json=data) | |
| # if response.status_code == 200: | |
| # file_path = 'test.mp3' | |
| # if os.path.isfile(file_path): | |
| # os.remove(file_path) | |
| # with open(file_path, 'wb') as f: | |
| # f.write(response.content) | |
| # return "test.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 os | |
| # def function1(prompt): | |
| # response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={ | |
| # "data": [ | |
| # prompt, | |
| # ]}).json() | |
| # data = response["data"][0] | |
| # response = requests.post("https://matthijs-speecht5-tts-demo.hf.space/run/predict", json={ | |
| # "data": [ | |
| # data, | |
| # "KSP (male)", | |
| # ] | |
| # }).json() | |
| # data = response["data"][0]["name"] | |
| # data = "https://matthijs-speecht5-tts-demo.hf.space/file="+data | |
| # file_name, headers = urllib.request.urlretrieve(data, "speech.mp3") | |
| # # code = random.randint(1,1000) | |
| # # generated_file = f"output{code}" | |
| # filename = "output.mp3" | |
| # if os.path.exists(filename): | |
| # os.remove(filename) | |
| # else: | |
| # pass | |
| # command = f"ffmpeg -i {file_name} -vn -ar 44100 -ac 2 -b:a 192k output.mp3" | |
| # os.system(command) | |
| # return "output.mp3" | |
| # iface = gr.Interface(fn=function1, inputs="text", outputs=[gr.Audio(label="Audio",type="numpy")]) | |
| # iface.launch() | |
| import requests | |
| import base64 | |
| import os | |
| import gradio as gr | |
| def function(prompt): | |
| target = os.environ.get("target") | |
| response = requests.post(target, json={ ###################################### WORKING API###################################### | |
| "prompt": [ | |
| prompt, | |
| ]}) | |
| data = response | |
| data = str(data.content,"utf-8") | |
| result = base64.b64encode(data.encode('utf-8')) | |
| result2 = result.decode('utf-8') | |
| return result2 | |
| iface = gr.Interface(fn=function, inputs="text", outputs="text") | |
| iface.launch() | |
| # import gradio as gr | |
| # import requests | |
| # import base64 | |
| # import time | |
| # import os | |
| # import re | |
| # def function(prompt): | |
| # url = os.environ.get("test7") | |
| # referrer = os.environ.get("test13") | |
| # headers = { | |
| # "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36 Edge/16.16299", | |
| # "Accept": "application/json", | |
| # "Accept-Language": "en-US,en;q=0.5", | |
| # "Referer": referrer, | |
| # "Connection": "keep-alive", | |
| # "TE": "Trailers", | |
| # "Flag-Real-Time-Data": "true" | |
| # } | |
| # data = { | |
| # "input": prompt | |
| # } | |
| # response = requests.post(url, headers=headers, json=data) | |
| # response = response.json() | |
| # output = response["output"] | |
| # trigger1 = os.environ.get("test9") | |
| # trigger2 = os.environ.get("test10") | |
| # set1 = os.environ.get("test11") | |
| # set2 = os.environ.get("test12") | |
| # if trigger1 in output and trigger2 in output: | |
| # output = re.sub(trigger2, set1, output) | |
| # output = re.sub(trigger1, set2, output) | |
| # result = base64.b64encode(output.encode('utf-8')) | |
| # result2 = result.decode('utf-8') | |
| # return output | |
| # iface = gr.Interface(fn=function, inputs="text", outputs="text") | |
| # 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 json | |
| # import os | |
| # def function2(prompt): | |
| # response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={ | |
| # "data": [ | |
| # prompt, | |
| # ]}).json() | |
| # message = response["data"][0] | |
| # 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() |