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from urllib . parse import quote
from tls_client import Session
from time import time
from datetime import datetime
client = Session ( client_identifier = ' chrome110 ' )
client . headers = {
' authority ' : ' www.phind.com ' ,
' accept ' : ' */* ' ,
' 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 ' ,
' content-type ' : ' application/json ' ,
' origin ' : ' https://www.phind.com ' ,
' referer ' : ' https://www.phind.com/search ' ,
' sec-ch-ua ' : ' " Chromium " ;v= " 110 " , " Google Chrome " ;v= " 110 " , " Not:A-Brand " ;v= " 99 " ' ,
' sec-ch-ua-mobile ' : ' ?0 ' ,
' sec-ch-ua-platform ' : ' " macOS " ' ,
' sec-fetch-dest ' : ' empty ' ,
' sec-fetch-mode ' : ' cors ' ,
' sec-fetch-site ' : ' same-origin ' ,
' user-agent ' : ' Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 ' ,
}
class PhindResponse :
class Completion :
class Choices :
def __init__ ( self , choice : dict ) - > None :
self . text = choice [ ' text ' ]
self . content = self . text . encode ( )
self . index = choice [ ' index ' ]
self . logprobs = choice [ ' logprobs ' ]
self . finish_reason = choice [ ' finish_reason ' ]
def __repr__ ( self ) - > str :
return f ''' <__main__.APIResponse.Completion.Choices( \n text = { self . text . encode ( ) } , \n index = { self . index } , \n logprobs = { self . logprobs } , \n finish_reason = { self . finish_reason } )object at 0x1337> '''
def __init__ ( self , choices : dict ) - > None :
self . choices = [ self . Choices ( choice ) for choice in choices ]
class Usage :
def __init__ ( self , usage_dict : dict ) - > None :
self . prompt_tokens = usage_dict [ ' prompt_tokens ' ]
self . completion_tokens = usage_dict [ ' completion_tokens ' ]
self . total_tokens = usage_dict [ ' total_tokens ' ]
def __repr__ ( self ) :
return f ''' <__main__.APIResponse.Usage( \n prompt_tokens = { self . prompt_tokens } , \n completion_tokens = { self . completion_tokens } , \n total_tokens = { self . total_tokens } )object at 0x1337> '''
def __init__ ( self , response_dict : dict ) - > None :
self . response_dict = response_dict
self . id = response_dict [ ' id ' ]
self . object = response_dict [ ' object ' ]
self . created = response_dict [ ' created ' ]
self . model = response_dict [ ' model ' ]
self . completion = self . Completion ( response_dict [ ' choices ' ] )
self . usage = self . Usage ( response_dict [ ' usage ' ] )
def json ( self ) - > dict :
return self . response_dict
class Search :
def create ( prompt : str , actualSearch : bool = True , language : str = ' en ' ) - > dict : # None = no search
if not actualSearch :
return {
' _type ' : ' SearchResponse ' ,
' queryContext ' : {
' originalQuery ' : prompt
} ,
' webPages ' : {
' webSearchUrl ' : f ' https://www.bing.com/search?q= { quote ( prompt ) } ' ,
' totalEstimatedMatches ' : 0 ,
' value ' : [ ]
} ,
' rankingResponse ' : {
' mainline ' : {
' items ' : [ ]
}
}
}
return client . post ( ' https://www.phind.com/api/bing/search ' , json = {
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' q ' : prompt ,
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' userRankList ' : { } ,
' browserLanguage ' : language } ) . json ( ) [ ' rawBingResults ' ]
class Completion :
def create (
model = ' gpt-4 ' ,
prompt : str = ' ' ,
results : dict = None ,
creative : bool = False ,
detailed : bool = False ,
codeContext : str = ' ' ,
language : str = ' en ' ) - > PhindResponse :
if results is None :
results = Search . create ( prompt , actualSearch = True )
if len ( codeContext ) > 2999 :
raise ValueError ( ' codeContext must be less than 3000 characters ' )
models = {
' gpt-4 ' : ' expert ' ,
' gpt-3.5-turbo ' : ' intermediate ' ,
' gpt-3.5 ' : ' intermediate ' ,
}
json_data = {
' question ' : prompt ,
' bingResults ' : results , #response.json()['rawBingResults'],
' codeContext ' : codeContext ,
' options ' : {
' skill ' : models [ model ] ,
' date ' : datetime . now ( ) . strftime ( " %d / % m/ % Y " ) ,
' language ' : language ,
' detailed ' : detailed ,
' creative ' : creative
}
}
completion = ' '
response = client . post ( ' https://www.phind.com/api/infer/answer ' , json = json_data , timeout_seconds = 200 )
for line in response . text . split ( ' \r \n \r \n ' ) :
completion + = ( line . replace ( ' data: ' , ' ' ) )
return PhindResponse ( {
' id ' : f ' cmpl-1337- { int ( time ( ) ) } ' ,
' object ' : ' text_completion ' ,
' created ' : int ( time ( ) ) ,
' model ' : models [ model ] ,
' choices ' : [ {
' text ' : completion ,
' index ' : 0 ,
' logprobs ' : None ,
' finish_reason ' : ' stop '
} ] ,
' usage ' : {
' prompt_tokens ' : len ( prompt ) ,
' completion_tokens ' : len ( completion ) ,
' total_tokens ' : len ( prompt ) + len ( completion )
}
} )