# import gradio as gr # import requests # import os # def function(Textbox,Textbox2): # target = os.environ.get("target") # target2 = os.environ.get("target2") # model = os.environ.get("model") # hrc = os.environ.get("hrc") # content = os.environ.get("content") # if Textbox2 == target: # payload = { # "model": "gpt-3.5-turbo", # "messages": [{"role": "system", "content": content},{"role": "user", "content": Textbox}], # "temperature" : 1.0, # "top_p":1.0, # "n" : 1, # "stream": False, # "presence_penalty":0, # "frequency_penalty":0, # } # headers = { # "Content-Type": "application/json", # "Authorization": f"Bearer {target2}" # } # response = requests.post(hrc, headers=headers, json=payload, stream=False) # response = response.json() # return response["choices"][0]["message"]["content"] # else: # return "Failed" # inputs = [ # gr.inputs.Textbox(label="Textbox",type="text"), # gr.inputs.Textbox(label="Textbox2",type="password") # ] # iface = gr.Interface(fn=function, inputs=inputs, outputs="text") # iface.launch() # import gradio as gr # import requests # import openai # import os # def function(Textbox,Textbox3): # target = os.environ.get("target") # target2 = os.environ.get("target2") # openai.api_key = target2 # content = os.environ.get("content") # # model = os.environ.get("model") # # hrc = os.environ.get("hrc") # if Textbox3 == target: # messages = [ # {"role": "system", "content": content}, # ] # messages.append( # {"role": "user", "content": Textbox}, # ) # chat = openai.ChatCompletion.create( # model="gpt-3.5-turbo", messages=messages # ) # reply = chat.choices[0].message.content # messages.append({"role": "assistant", "content": reply}) # return reply # else: # return "Failed" # inputs = [ # gr.inputs.Textbox(label="Textbox",type="text"), # # gr.inputs.Textbox(label="Textbox2",type="text"), # gr.inputs.Textbox(label="Textbox3",type="password") # ] # iface = gr.Interface(fn=function, inputs=inputs, outputs="text") # iface.launch() from time import sleep from io import BytesIO from PIL import Image import gradio as gr import numpy as np import replicate import traceback import requests import openai import random import base64 import os import urllib.request from pydub import AudioSegment def function(Textbox, Textbox2, Textbox3, Dropdown): target = os.environ.get("target") target2 = os.environ.get("target2") os.environ["REPLICATE_API_TOKEN"] # openai.api_key = target2 # openai.api_base = os.environ.get("base") content = os.environ.get("content") link1 = os.environ.get("link1") path = os.environ.get("path") link2 = os.environ.get("link2") if "/web" in Textbox.lower() or "web" in Textbox.lower(): try: prompt = Textbox.replace("/web", "") except: prompt = Textbox.replace("web", "") headers = { "authority": link1, "method": "POST", "path": path, "scheme": "https", "accept": "application/json, text/plain, */*", "accept-encoding": "gzip, deflate, br", "accept-language": "en-US,en;q=0.9", "content-length": "88", "content-type": "application/json", "origin": link2, "referer": f"{link2}/", "sec-ch-ua": '"Google Chrome";v="111", "Not(A:Brand";v="8", "Chromium";v="111"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "sec-fetch-dest": "empty", "sec-fetch-mode": "cors", "sec-fetch-site": "same-site", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36" } href = os.environ.get("href") response = requests.post(href, json={ "Body": prompt, "From": f"4b7cec35-d15b-422d-838f-b25583bde426{random.randint(1,100)}" }, headers=headers) data = response.json() data = data["message"] trigger = os.environ.get("trigger") if trigger in data: data = data.replace(trigger, "John") return data else: return data else: def download_image(url): try: with urllib.request.urlopen(url) as response: image_data = response.read() image = Image.open(BytesIO(image_data)) image_array = np.array(image) return image_array except urllib.error.URLError as e: print('URL Error:', str(e)) except IOError as e: print('IO Error:', str(e)) if Textbox3 == target: if Dropdown == "Option1": Textbox2 = Textbox2.replace("[", "").replace("]", "").replace("'", "") Textbox2 = Textbox2.split(",") Textbox2_edited = [x.strip() for x in Textbox2] Textbox2_edited = list(Textbox2_edited) Textbox2_edited.append(Textbox) data = { "messages": [ {"role": "system", "content": content} ] } for i in Textbox2_edited: data["messages"].append( {"role": "user", "content": i} ) try: sleep(0.8) # chat = openai.ChatCompletion.create( # model="gpt-3.5-turbo", messages=messages # ) response = requests.post(target2, json=data) reply = response.content.decode("utf-8") # reply = reply.replace(" ", "%20") # image_array = download_image(f"https://api.placid.app/u/pydav4ibo?quote[text]={reply}") data["messages"].append({"role": "assistant", "content": reply}) return reply except Exception as e: print(traceback.format_exc()) return "Please Wait!" elif Dropdown == "Option2": Textbox2 = Textbox2.replace("[", "").replace("]", "").replace("'", "") Textbox2 = Textbox2.split(",") Textbox2_edited = [x.strip() for x in Textbox2] Textbox2_edited = list(Textbox2_edited) Textbox2_edited.append(Textbox) data = { "messages": [ {"role": "system", "content": content} ] } for i in Textbox2_edited: data["messages"].append( {"role": "user", "content": i} ) try: sleep(0.8) # chat = openai.ChatCompletion.create( # model="gpt-3.5-turbo", messages=messages # ) response = requests.post(target2, json=data) reply = response.content.decode("utf-8") # reply = reply.replace(" ", "%20") # image_array = download_image(f"https://api.placid.app/u/pydav4ibo?quote[text]={reply}") data["messages"].append({"role": "assistant", "content": reply}) output = replicate.run( "suno-ai/bark:b76242b40d67c76ab6742e987628a2a9ac019e11d56ab96c4e91ce03b79b2787", input={ "prompt": reply, "history_prompt": "en_speaker_5" } ) output = output["audio_out"] audio_data = base64.b64decode(output) return audio data # Save the audio to an MP3 file # mp3_path = "output.mp3" # with open(mp3_path, "wb") as f: # f.write(audio_data) # # Return the path to the MP3 file # return mp3_path except Exception as e: print(traceback.format_exc()) return "Please Wait!" else: return "Failed" inputs = [ gr.inputs.Textbox(label="Textbox", type="text"), gr.inputs.Textbox(label="Textbox2", type="text"), gr.inputs.Textbox(label="Textbox3", type="password"), gr.inputs.Dropdown(["Option1", "Option2"], label="Dropdown") ] # outputs = gr.outputs.Image(type="numpy") outputs = gr.outputs.Audio(type="filepath") iface = gr.Interface(fn=function, inputs=inputs, outputs=outputs) iface.launch() # from time import sleep # import gradio as gr # import traceback # import requests # import openai # import random # import base64 # import os # def function(Textbox,Textbox2, Textbox3): # target = os.environ.get("target") # target2 = os.environ.get("target2") # content = os.environ.get("content") # content2 = os.environ.get("content2") # auth_key = os.environ.get("auth_key") # link1 = os.environ.get("link1") # path = os.environ.get("path") # link2 = os.environ.get("link2") # if "/web" in Textbox.lower() or "web" in Textbox.lower(): # try: # prompt = Textbox.replace("/web","") # except: # prompt = Textbox.replace("web","") # headers = { # "authority": link1, # "method": "POST", # "path": path, # "scheme": "https", # "accept": "application/json, text/plain, */*", # "accept-encoding": "gzip, deflate, br", # "accept-language": "en-US,en;q=0.9", # "content-length": "88", # "content-type": "application/json", # "origin": link2, # "referer": f"{link2}/", # "sec-ch-ua": '"Google Chrome";v="111", "Not(A:Brand";v="8", "Chromium";v="111"', # "sec-ch-ua-mobile": "?0", # "sec-ch-ua-platform": '"Windows"', # "sec-fetch-dest": "empty", # "sec-fetch-mode": "cors", # "sec-fetch-site": "same-site", # "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36" # } # href = os.environ.get("href") # response = requests.post(href,json={ # "Body":prompt, # "From":f"4b7cec35-d15b-422d-838f-b25583bde426{random.randint(1,100)}" # },headers=headers) # data = response.json() # data = data["message"] # trigger = os.environ.get("trigger") # if trigger in data: # data = data.replace(trigger,"John") # return data # else: # return data # else: # # model = os.environ.get("model") # # hrc = os.environ.get("hrc") # if Textbox3 == target: # Textbox2 = Textbox2.replace("[", "").replace("]", "").replace("'", "") # Textbox2 = Textbox2.split(",") # Textbox2_edited = [x.strip() for x in Textbox2] # Textbox2_edited = list(Textbox2_edited) # Textbox2_edited.append(Textbox) # messages = [ # {"role": "system", "content": content2}, # ] # for i in Textbox2_edited: # messages.append( # {"role": "user", "content": i} # ) # try: # # sleep(0.8) # # headers = { # # "Authorization": f"Bearer {auth_key}" # # } # response = requests.post(target2, json={ # "messages": messages # }).json() # # reply = response['choices'][0]['message']['content'] # reply = response["content"] # messages.append({"role": "assistant", "content": reply}) # return reply # except Exception as e: # print(traceback.format_exc()) # return "Please Wait!" # else: # return "Failed" # inputs = [ # gr.inputs.Textbox(label="Textbox",type="text"), # gr.inputs.Textbox(label="Textbox2",type="text"), # gr.inputs.Textbox(label="Textbox3",type="password") # ] # iface = gr.Interface(fn=function, inputs=inputs, outputs="text") # iface.launch() # from time import sleep # import gradio as gr # import traceback # import requests # import openai # import random # import base64 # import json # import os # def function(Textbox,Textbox2, Textbox3, Textbox4): # target = os.environ.get("target") # target2 = os.environ.get("target2") # content = os.environ.get("content") # content2 = os.environ.get("content2") # auth_key = os.environ.get("auth_key") # link1 = os.environ.get("link1") # path = os.environ.get("path") # link2 = os.environ.get("link2") # if "/web" in Textbox.lower() or "web" in Textbox.lower(): # try: # prompt = Textbox.replace("/web","") # except: # prompt = Textbox.replace("web","") # headers = { # "authority": link1, # "method": "POST", # "path": path, # "scheme": "https", # "accept": "application/json, text/plain, */*", # "accept-encoding": "gzip, deflate, br", # "accept-language": "en-US,en;q=0.9", # "content-length": "88", # "content-type": "application/json", # "origin": link2, # "referer": f"{link2}/", # "sec-ch-ua": '"Google Chrome";v="111", "Not(A:Brand";v="8", "Chromium";v="111"', # "sec-ch-ua-mobile": "?0", # "sec-ch-ua-platform": '"Windows"', # "sec-fetch-dest": "empty", # "sec-fetch-mode": "cors", # "sec-fetch-site": "same-site", # "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36" # } # href = os.environ.get("href") # response = requests.post(href,json={ # "Body":prompt, # "From":f"4b7cec35-d15b-422d-838f-b25583bde426{random.randint(1,100)}" # },headers=headers) # data = response.json() # data = data["message"] # trigger = os.environ.get("trigger") # if trigger in data: # data = data.replace(trigger,"John") # return data # else: # return data # else: # # model = os.environ.get("model") # # hrc = os.environ.get("hrc") # if Textbox3 == target: # try: # # sleep(0.8) # # headers = { # # "Authorization": f"Bearer {auth_key}" # # } # response = requests.post(target2, headers={ # "Content-Type": "application/json" # }, data=json.dumps({ # "text": Textbox, # "key": auth_key, # "playerId": Textbox4, # "speak": False # })) # # reply = response['choices'][0]['message']['content'] # response = response.json() # reply = response["output"]["text"] # return reply # except Exception as e: # print(traceback.format_exc()) # return "Please Wait!" # else: # return "Failed" # inputs = [ # gr.inputs.Textbox(label="Textbox",type="text"), # gr.inputs.Textbox(label="Textbox2",type="text"), # gr.inputs.Textbox(label="Textbox3",type="password"), # gr.inputs.Textbox(label="Textbox4",type="text") # ] # iface = gr.Interface(fn=function, inputs=inputs, outputs="text") # iface.launch() # from time import sleep # import gradio as gr # import traceback # import requests # import openai # import random # import base64 # import os # def function(Textbox,Textbox2, Textbox3): # target = os.environ.get("target") # target2 = os.environ.get("target2") # openai.api_key = target2 # content = os.environ.get("content") # content2 = os.environ.get("content2") # link1 = os.environ.get("link1") # path = os.environ.get("path") # link2 = os.environ.get("link2") # if "/web" in Textbox.lower() or "web" in Textbox.lower(): # try: # prompt = Textbox.replace("/web","") # except: # prompt = Textbox.replace("web","") # headers = { # "authority": link1, # "method": "POST", # "path": path, # "scheme": "https", # "accept": "application/json, text/plain, */*", # "accept-encoding": "gzip, deflate, br", # "accept-language": "en-US,en;q=0.9", # "content-length": "88", # "content-type": "application/json", # "origin": link2, # "referer": f"{link2}/", # "sec-ch-ua": '"Google Chrome";v="111", "Not(A:Brand";v="8", "Chromium";v="111"', # "sec-ch-ua-mobile": "?0", # "sec-ch-ua-platform": '"Windows"', # "sec-fetch-dest": "empty", # "sec-fetch-mode": "cors", # "sec-fetch-site": "same-site", # "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36" # } # href = os.environ.get("href") # response = requests.post(href,json={ # "Body":prompt, # "From":f"4b7cec35-d15b-422d-838f-b25583bde426{random.randint(1,100)}" # },headers=headers) # data = response.json() # data = data["message"] # trigger = os.environ.get("trigger") # if trigger in data: # data = data.replace(trigger,"John") # return data # else: # return data # else: # # model = os.environ.get("model") # # hrc = os.environ.get("hrc") # if Textbox3 == target: # Textbox2 = Textbox2.replace("[", "").replace("]", "").replace("'", "") # Textbox2 = Textbox2.split(",") # Textbox2_edited = [x.strip() for x in Textbox2] # Textbox2_edited = list(Textbox2_edited) # Textbox2_edited.append(Textbox) # messages = [ # {"role": "system", "content": content2}, # ] # for i in Textbox2_edited: # messages.append( # {"role": "user", "content": i} # ) # try: # # sleep(1.8) # response = requests.post(target2, json={ # "messages":messages, # "model":"gpt-3.5-turbo-003", # "max_tokens":"null", # "temperature":1, # "presence_penalty":0, # "top_p":1, # "frequency_penalty":0, # "stream":False # }).json() # reply = response['choices'][0]['message']['content'] # messages.append({"role": "assistant", "content": reply}) # return reply # except Exception as e: # print(traceback.format_exc()) # return "Please Wait!" # else: # return "Failed" # inputs = [ # gr.inputs.Textbox(label="Textbox",type="text"), # gr.inputs.Textbox(label="Textbox2",type="text"), # gr.inputs.Textbox(label="Textbox3",type="password") # ] # iface = gr.Interface(fn=function, inputs=inputs, outputs="text") # iface.launch()