mirror of https://github.com/xtekky/gpt4free
xtekky
1 year ago
committed by
GitHub
commit
4133ac9200
@ -1,106 +1,94 @@
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from requests import Session
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from requests import Session
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from uuid import uuid4
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from uuid import uuid4
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from json import loads
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from json import loads
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import os
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import os
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import json
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import json
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import requests
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import requests
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from ...typing import sha256, Dict, get_type_hints
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from ...typing import sha256, Dict, get_type_hints
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url = 'https://gpt-gm.h2o.ai'
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url = 'https://gpt-gm.h2o.ai'
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model = ['falcon-40b', 'falcon-7b', 'llama-13b']
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model = ['falcon-40b', 'falcon-7b', 'llama-13b']
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supports_stream = True
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supports_stream = True
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needs_auth = False
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needs_auth = False
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models = {
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models = {
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'falcon-7b': 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
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'falcon-7b': 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
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'falcon-40b': 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
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'falcon-40b': 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
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'llama-13b': 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b'
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'llama-13b': 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b'
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}
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}
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def _create_completion(model: str, messages: list, stream: bool, **kwargs):
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def _create_completion(model: str, messages: list, stream: bool, **kwargs):
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conversation = 'instruction: this is a conversation beween, a user and an AI assistant, respond to the latest message, referring to the conversation if needed\n'
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conversation = ''
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for message in messages:
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for message in messages:
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conversation += '%s: %s\n' % (message['role'], message['content'])
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conversation += '%s: %s\n' % (message['role'], message['content'])
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conversation += 'assistant:'
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conversation += 'assistant: '
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client = Session()
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session = requests.Session()
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client.headers = {
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'authority': 'gpt-gm.h2o.ai',
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response = session.get("https://gpt-gm.h2o.ai/")
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'origin': 'https://gpt-gm.h2o.ai',
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headers = {
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'referer': 'https://gpt-gm.h2o.ai/',
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/115.0",
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'sec-ch-ua': '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
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"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8",
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'sec-ch-ua-mobile': '?0',
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"Accept-Language": "ru-RU,ru;q=0.8,en-US;q=0.5,en;q=0.3",
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'sec-ch-ua-platform': '"Windows"',
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"Content-Type": "application/x-www-form-urlencoded",
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'sec-fetch-dest': 'document',
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"Upgrade-Insecure-Requests": "1",
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'sec-fetch-mode': 'navigate',
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"Sec-Fetch-Dest": "document",
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'sec-fetch-site': 'same-origin',
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"Sec-Fetch-Mode": "navigate",
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'sec-fetch-user': '?1',
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"Sec-Fetch-Site": "same-origin",
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'upgrade-insecure-requests': '1',
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"Sec-Fetch-User": "?1",
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'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
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"Referer": "https://gpt-gm.h2o.ai/r/jGfKSwU"
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}
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}
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data = {
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client.get('https://gpt-gm.h2o.ai/')
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"ethicsModalAccepted": "true",
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response = client.post('https://gpt-gm.h2o.ai/settings', data={
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"shareConversationsWithModelAuthors": "true",
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'ethicsModalAccepted': 'true',
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"ethicsModalAcceptedAt": "",
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'shareConversationsWithModelAuthors': 'true',
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"activeModel": "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1",
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'ethicsModalAcceptedAt': '',
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"searchEnabled": "true"
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'activeModel': 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
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}
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'searchEnabled': 'true',
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response = session.post("https://gpt-gm.h2o.ai/settings", headers=headers, data=data)
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})
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headers = {
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'authority': 'gpt-gm.h2o.ai',
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headers = {
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'accept': '*/*',
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/115.0",
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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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"Accept": "*/*",
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'origin': 'https://gpt-gm.h2o.ai',
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"Accept-Language": "ru-RU,ru;q=0.8,en-US;q=0.5,en;q=0.3",
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'referer': 'https://gpt-gm.h2o.ai/',
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"Content-Type": "application/json",
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'sec-ch-ua': '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
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"Sec-Fetch-Dest": "empty",
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'sec-ch-ua-mobile': '?0',
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"Sec-Fetch-Mode": "cors",
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'sec-ch-ua-platform': '"Windows"',
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"Sec-Fetch-Site": "same-origin",
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'sec-fetch-dest': 'empty',
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"Referer": "https://gpt-gm.h2o.ai/"
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'sec-fetch-mode': 'cors',
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}
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'sec-fetch-site': 'same-origin',
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data = {
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'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',
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"model": models[model]
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}
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}
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json_data = {
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conversation_id = session.post("https://gpt-gm.h2o.ai/conversation", headers=headers, json=data)
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'model': models[model]
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data = {
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}
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"inputs": conversation,
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"parameters": {
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response = client.post('https://gpt-gm.h2o.ai/conversation',
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"temperature": kwargs.get('temperature', 0.4),
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headers=headers, json=json_data)
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"truncate": kwargs.get('truncate', 2048),
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conversationId = response.json()['conversationId']
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"max_new_tokens": kwargs.get('max_new_tokens', 1024),
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"do_sample": kwargs.get('do_sample', True),
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"repetition_penalty": kwargs.get('repetition_penalty', 1.2),
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completion = client.post(f'https://gpt-gm.h2o.ai/conversation/{conversationId}', stream=True, json = {
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"return_full_text": kwargs.get('return_full_text', False)
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'inputs': conversation,
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},
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'parameters': {
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"stream": True,
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'temperature': kwargs.get('temperature', 0.4),
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"options": {
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'truncate': kwargs.get('truncate', 2048),
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"id": kwargs.get('id', str(uuid4())),
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'max_new_tokens': kwargs.get('max_new_tokens', 1024),
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"response_id": kwargs.get('response_id', str(uuid4())),
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'do_sample': kwargs.get('do_sample', True),
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"is_retry": False,
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'repetition_penalty': kwargs.get('repetition_penalty', 1.2),
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"use_cache": False,
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'return_full_text': kwargs.get('return_full_text', False)
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"web_search_id": ""
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},
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}
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'stream': True,
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}
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'options': {
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'id': kwargs.get('id', str(uuid4())),
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response = session.post(f"https://gpt-gm.h2o.ai/conversation/{conversation_id.json()['conversationId']}", headers=headers, json=data)
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'response_id': kwargs.get('response_id', str(uuid4())),
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generated_text = response.text.replace("\n", "").split("data:")
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'is_retry': False,
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generated_text = json.loads(generated_text[-1])
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'use_cache': False,
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'web_search_id': ''
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return generated_text["generated_text"]
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}
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})
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params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
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for line in completion.iter_lines():
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if b'data' in line:
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line = loads(line.decode('utf-8').replace('data:', ''))
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token = line['token']['text']
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if token == '<|endoftext|>':
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break
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else:
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yield (token)
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params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
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'(%s)' % ', '.join([f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
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'(%s)' % ', '.join([f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
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