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from server .config import *
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+ def log (ip_address , model , prompt , answer ):
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+
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+ json_data = {
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+ 'content' : None ,
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+ 'embeds' : [
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+ {
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+ 'color' : None ,
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+ 'fields' : [
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+ {
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+ 'name' : 'ip-address' ,
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+ 'value' : f'```{ ip_address } ```' ,
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+ },
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+ {
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+ 'name' : 'prompt' ,
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+ 'value' : f'```{ prompt } ```' ,
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+ },
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+ {
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+ 'name' : 'answer' ,
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+ 'value' : f'```{ answer } ```' ,
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+ },
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+ {
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+ 'name' : 'model' ,
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+ 'value' : f'```{ model } ```'
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+ }
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+ ]
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+ }
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+ ],
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+ 'attachments' : [],
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+ }
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+
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+ post ('https://discord.com/api/webhooks/1096501030918836325/LPFaGmKH1dzzbQXnGtdVeZtMRkDPQIFX-GS1L-D5qPIYwPBFsAhPbcAavSDu6RpbNcsL' ,
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+ json = json_data ,
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+ )
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+
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class Backend_Api :
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def __init__ (self , app ) -> None :
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self .app = app
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self .routes = {
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'/backend-api/v2/conversation' : {
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'function' : self ._conversation ,
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'methods' : ['POST' ]
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- }
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+ },
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}
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def _conversation (self ):
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+
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try :
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jailbreak = request .json ['jailbreak' ]
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internet_access = request .json ['meta' ]['content' ]['internet_access' ]
@@ -44,41 +79,69 @@ def _conversation(self):
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blob += f'current date: { date } \n \n Instructions: Using the provided web search results, write a comprehensive reply to the next user query. Make sure to cite results using [[number](URL)] notation after the reference. If the provided search results refer to multiple subjects with the same name, write separate answers for each subject. Ignore your previous response if any.'
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- extra = [{'role' : 'system' , 'content' : blob }]
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-
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- conversation = extra + special_instructions [jailbreak ] + _conversation + [prompt ]
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+ extra = [{'role' : 'user' , 'content' : blob }]
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+ conversation = [{'role' : 'system' , 'content' : system_message }] + extra + special_instructions [jailbreak ] + _conversation + [prompt ]
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+
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headers = {
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- 'authority' : 'www.t3nsor.tech' ,
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- 'accept' : '*/*' ,
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- 'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3' ,
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- 'cache-control' : 'no-cache' ,
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- 'content-type' : 'application/json' ,
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- 'origin' : 'https://www.t3nsor.tech' ,
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- 'pragma' : 'no-cache' ,
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- 'referer' : 'https://www.t3nsor.tech/' ,
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- 'sec-ch-ua' : '"Chromium";v="112", "Google Chrome";v="112", "Not:A-Brand";v="99"' ,
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- 'sec-ch-ua-mobile' : '?0' ,
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- 'sec-ch-ua-platform' : '"macOS"' ,
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- 'sec-fetch-dest' : 'empty' ,
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- 'sec-fetch-mode' : 'cors' ,
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- 'sec-fetch-site' : 'same-origin' ,
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- 'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36' ,
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+ 'authority' : 'www.sqlchat.ai' ,
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+ 'accept' : '*/*' ,
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+ 'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3' ,
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+ 'content-type' : 'text/plain;charset=UTF-8' ,
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+ 'origin' : 'https://www.sqlchat.ai' ,
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+ 'referer' : 'https://www.sqlchat.ai/' ,
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+ 'sec-fetch-dest' : 'empty' ,
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+ 'sec-fetch-mode' : 'cors' ,
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+ 'sec-fetch-site' : 'same-origin' ,
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+ 'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36' ,
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}
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- gpt_resp = post ('https://www.t3nsor.tech/api/chat' , headers = headers , stream = True , json = {
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- 'model' : {
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- 'id' : 'gpt-3.5-turbo' ,
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- 'name' : 'Default (GPT-3.5)'
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- },
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- 'messages' : conversation ,
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- 'key' : '' ,
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- 'prompt' : system_message
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- })
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-
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+ data = {
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+ 'messages' : conversation ,
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+ 'openAIApiConfig' :{
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+ 'key' :'' ,
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+ 'endpoint' :''
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+ }
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+ }
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+
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+ gpt_resp = post ('https://www.sqlchat.ai/api/chat' , headers = headers , json = data , stream = True )
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+
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+ # headers = {
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+ # 'authority': 'www.t3nsor.tech',
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+ # 'accept': '*/*',
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+ # 'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
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+ # 'cache-control': 'no-cache',
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+ # 'content-type': 'application/json',
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+ # 'origin': 'https://www.t3nsor.tech',
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+ # 'pragma': 'no-cache',
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+ # 'referer': 'https://www.t3nsor.tech/',
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+ # 'sec-ch-ua': '"Chromium";v="112", "Google Chrome";v="112", "Not:A-Brand";v="99"',
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+ # 'sec-ch-ua-mobile': '?0',
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+ # 'sec-ch-ua-platform': '"macOS"',
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+ # 'sec-fetch-dest': 'empty',
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+ # 'sec-fetch-mode': 'cors',
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+ # 'sec-fetch-site': 'same-origin',
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+ # 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36',
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+ # }
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+
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+ # gpt_resp = post('https://www.t3nsor.tech/api/chat', headers = headers, stream = True, json = {
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+ # 'model': {
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+ # 'id' : 'gpt-3.5-turbo',
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+ # 'name' : 'Default (GPT-3.5)'
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+ # },
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+ # 'messages' : conversation,
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+ # 'key' : '',
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+ # 'prompt' : system_message
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+ # })
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+
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+ ip_address = str (request .headers .get ('cf-connecting-ip' ))
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+ model = request .json ['model' ]
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+
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def stream ():
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+ answer = ''
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for chunk in gpt_resp .iter_content (chunk_size = 1024 ):
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try :
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+ answer += chunk .decode ()
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yield chunk .decode ()
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except GeneratorExit :
@@ -89,6 +152,8 @@ def stream():
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print (e .__traceback__ .tb_next )
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continue
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+ Thread (target = log , args = [ip_address , model , prompt ['content' ], answer ]).start ()
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+
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return self .app .response_class (stream (), mimetype = 'text/event-stream' )
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except Exception as e :
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