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@ -1,24 +1,11 @@
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from urllib.parse import quote
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from tls_client import Session
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from time import time
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from datetime import datetime
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from queue import Queue, Empty
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from threading import Thread
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from re import findall
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client = Session(client_identifier='chrome110')
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client.headers = {
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'authority': 'www.phind.com',
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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': 'application/json',
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'origin': 'https://www.phind.com',
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'referer': 'https://www.phind.com/search',
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'sec-ch-ua': '"Chromium";v="110", "Google Chrome";v="110", "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/110.0.0.0 Safari/537.36',
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}
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from curl_cffi.requests import post
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class PhindResponse:
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@ -81,11 +68,19 @@ class Search:
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}
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}
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return client.post('https://www.phind.com/api/bing/search', json = {
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'q' : prompt,
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headers = {
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'authority' : 'www.phind.com',
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'origin' : 'https://www.phind.com',
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'referer' : 'https://www.phind.com/search',
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'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',
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}
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return post('https://www.phind.com/api/bing/search', headers = headers, json = {
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'q': prompt,
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'userRankList': {},
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'browserLanguage': language}).json()['rawBingResults']
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class Completion:
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def create(
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model = 'gpt-4',
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@ -121,8 +116,15 @@ class Completion:
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}
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}
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headers = {
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'authority' : 'www.phind.com',
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'origin' : 'https://www.phind.com',
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'referer' : f'https://www.phind.com/search?q={quote(prompt)}&c=&source=searchbox&init=true',
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'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',
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}
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completion = ''
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response = client.post('https://www.phind.com/api/infer/answer', json=json_data, timeout_seconds=200)
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response = post('https://www.phind.com/api/infer/answer', headers = headers, json = json_data, timeout=99999)
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for line in response.text.split('\r\n\r\n'):
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completion += (line.replace('data: ', ''))
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@ -143,3 +145,88 @@ class Completion:
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'total_tokens' : len(prompt) + len(completion)
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}
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})
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class StreamingCompletion:
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message_queue = Queue()
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stream_completed = False
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def request(model, prompt, results, creative, detailed, codeContext, language) -> None:
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models = {
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'gpt-4' : 'expert',
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'gpt-3.5-turbo' : 'intermediate',
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'gpt-3.5': 'intermediate',
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}
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json_data = {
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'question' : prompt,
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'bingResults' : results,
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'codeContext' : codeContext,
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'options': {
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'skill' : models[model],
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'date' : datetime.now().strftime("%d/%m/%Y"),
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'language': language,
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'detailed': detailed,
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'creative': creative
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}
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}
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stream_req = post('https://www.phind.com/api/infer/answer', json=json_data, timeout=99999,
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content_callback = StreamingCompletion.handle_stream_response,
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headers = {
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'authority' : 'www.phind.com',
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'origin' : 'https://www.phind.com',
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'referer' : f'https://www.phind.com/search?q={quote(prompt)}&c=&source=searchbox&init=true',
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'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',
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})
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StreamingCompletion.stream_completed = True
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@staticmethod
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def create(
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model : str = 'gpt-4',
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prompt : str = '',
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results : dict = None,
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creative : bool = False,
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detailed : bool = False,
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codeContext : str = '',
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language : str = 'en'):
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if results is None:
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results = Search.create(prompt, actualSearch = True)
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if len(codeContext) > 2999:
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raise ValueError('codeContext must be less than 3000 characters')
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Thread(target = StreamingCompletion.request, args = [
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model, prompt, results, creative, detailed, codeContext, language]).start()
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while StreamingCompletion.stream_completed != True or not StreamingCompletion.message_queue.empty():
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try:
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message = StreamingCompletion.message_queue.get(timeout=0)
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for token in findall(r'(?<=data: )(.+?)(?=\r\n\r\n)', message.decode()):
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yield PhindResponse({
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'id' : f'cmpl-1337-{int(time())}',
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'object' : 'text_completion',
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'created': int(time()),
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'model' : model,
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'choices': [{
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'text' : token,
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'index' : 0,
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'logprobs' : None,
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'finish_reason' : 'stop'
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}],
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'usage': {
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'prompt_tokens' : len(prompt),
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'completion_tokens' : len(token),
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'total_tokens' : len(prompt) + len(token)
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}
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})
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except Empty:
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pass
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@staticmethod
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def handle_stream_response(response):
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StreamingCompletion.message_queue.put(response)
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