097faaca1e
simple fix used builtin map func instead of a list comprehension, incorrect usage of comprehensions.
291 lines
11 KiB
Python
291 lines
11 KiB
Python
from urllib.parse import quote
|
|
from time import time
|
|
from datetime import datetime
|
|
from queue import Queue, Empty
|
|
from threading import Thread
|
|
from re import findall
|
|
|
|
from curl_cffi.requests import post
|
|
|
|
cf_clearance = ''
|
|
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'
|
|
|
|
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 = list(map(self.Choices, 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 user_agent == '':
|
|
raise ValueError('user_agent must be set, refer to documentation')
|
|
if cf_clearance == '' :
|
|
raise ValueError('cf_clearance must be set, refer to documentation')
|
|
|
|
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': []
|
|
}
|
|
}
|
|
}
|
|
|
|
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',
|
|
'cookie': f'cf_clearance={cf_clearance}',
|
|
'origin': 'https://www.phind.com',
|
|
'referer': 'https://www.phind.com/search?q=hi&c=&source=searchbox&init=true',
|
|
'sec-ch-ua': '"Chromium";v="112", "Google Chrome";v="112", "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': user_agent
|
|
}
|
|
|
|
return post('https://www.phind.com/api/bing/search', headers = headers, json = {
|
|
'q': prompt,
|
|
'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 user_agent == '' :
|
|
raise ValueError('user_agent must be set, refer to documentation')
|
|
|
|
if cf_clearance == '' :
|
|
raise ValueError('cf_clearance must be set, refer to documentation')
|
|
|
|
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
|
|
}
|
|
}
|
|
|
|
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',
|
|
'cookie': f'cf_clearance={cf_clearance}',
|
|
'origin': 'https://www.phind.com',
|
|
'referer': 'https://www.phind.com/search?q=hi&c=&source=searchbox&init=true',
|
|
'sec-ch-ua': '"Chromium";v="112", "Google Chrome";v="112", "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': user_agent
|
|
}
|
|
|
|
completion = ''
|
|
response = post('https://www.phind.com/api/infer/answer', headers = headers, json = json_data, timeout=99999, impersonate='chrome110')
|
|
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)
|
|
}
|
|
})
|
|
|
|
|
|
class StreamingCompletion:
|
|
message_queue = Queue()
|
|
stream_completed = False
|
|
|
|
def request(model, prompt, results, creative, detailed, codeContext, language) -> None:
|
|
|
|
models = {
|
|
'gpt-4' : 'expert',
|
|
'gpt-3.5-turbo' : 'intermediate',
|
|
'gpt-3.5': 'intermediate',
|
|
}
|
|
|
|
json_data = {
|
|
'question' : prompt,
|
|
'bingResults' : results,
|
|
'codeContext' : codeContext,
|
|
'options': {
|
|
'skill' : models[model],
|
|
'date' : datetime.now().strftime("%d/%m/%Y"),
|
|
'language': language,
|
|
'detailed': detailed,
|
|
'creative': creative
|
|
}
|
|
}
|
|
|
|
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',
|
|
'cookie': f'cf_clearance={cf_clearance}',
|
|
'origin': 'https://www.phind.com',
|
|
'referer': 'https://www.phind.com/search?q=hi&c=&source=searchbox&init=true',
|
|
'sec-ch-ua': '"Chromium";v="112", "Google Chrome";v="112", "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': user_agent
|
|
}
|
|
|
|
response = post('https://www.phind.com/api/infer/answer',
|
|
headers = headers, json = json_data, timeout=99999, impersonate='chrome110', content_callback=StreamingCompletion.handle_stream_response)
|
|
|
|
|
|
StreamingCompletion.stream_completed = True
|
|
|
|
@staticmethod
|
|
def create(
|
|
model : str = 'gpt-4',
|
|
prompt : str = '',
|
|
results : dict = None,
|
|
creative : bool = False,
|
|
detailed : bool = False,
|
|
codeContext : str = '',
|
|
language : str = 'en'):
|
|
|
|
if user_agent == '':
|
|
raise ValueError('user_agent must be set, refer to documentation')
|
|
if cf_clearance == '' :
|
|
raise ValueError('cf_clearance must be set, refer to documentation')
|
|
|
|
if results is None:
|
|
results = Search.create(prompt, actualSearch = True)
|
|
|
|
if len(codeContext) > 2999:
|
|
raise ValueError('codeContext must be less than 3000 characters')
|
|
|
|
Thread(target = StreamingCompletion.request, args = [
|
|
model, prompt, results, creative, detailed, codeContext, language]).start()
|
|
|
|
while StreamingCompletion.stream_completed != True or not StreamingCompletion.message_queue.empty():
|
|
try:
|
|
chunk = StreamingCompletion.message_queue.get(timeout=0)
|
|
|
|
if chunk == b'data: \r\ndata: \r\ndata: \r\n\r\n':
|
|
chunk = b'data: \n\n\r\n\r\n'
|
|
|
|
chunk = chunk.decode()
|
|
|
|
chunk = chunk.replace('data: \r\n\r\ndata: ', 'data: \n')
|
|
chunk = chunk.replace('\r\ndata: \r\ndata: \r\n\r\n', '\n\n\r\n\r\n')
|
|
chunk = chunk.replace('data: ', '').replace('\r\n\r\n', '')
|
|
|
|
yield PhindResponse({
|
|
'id' : f'cmpl-1337-{int(time())}',
|
|
'object' : 'text_completion',
|
|
'created': int(time()),
|
|
'model' : model,
|
|
'choices': [{
|
|
'text' : chunk,
|
|
'index' : 0,
|
|
'logprobs' : None,
|
|
'finish_reason' : 'stop'
|
|
}],
|
|
'usage': {
|
|
'prompt_tokens' : len(prompt),
|
|
'completion_tokens' : len(chunk),
|
|
'total_tokens' : len(prompt) + len(chunk)
|
|
}
|
|
})
|
|
|
|
except Empty:
|
|
pass
|
|
|
|
@staticmethod
|
|
def handle_stream_response(response):
|
|
StreamingCompletion.message_queue.put(response)
|