~ | fixed Vercel Provider

pull/1663/head
abc 4 months ago
parent 9d17588fcb
commit 06c448daab

@ -1,6 +1,6 @@
from __future__ import annotations
import json, base64, requests, random, uuid
import json, base64, requests, random, os
try:
import execjs
@ -13,12 +13,13 @@ from .base_provider import AbstractProvider
from ..errors import MissingRequirementsError
class Vercel(AbstractProvider):
url = 'https://sdk.vercel.ai'
working = False
url = 'https://chat.vercel.ai'
working = True
supports_message_history = True
supports_gpt_35_turbo = True
supports_stream = True
supports_gpt_35_turbo = True
supports_stream = True
supports_gpt_4 = False
@staticmethod
def create_completion(
model: str,
@ -29,43 +30,34 @@ class Vercel(AbstractProvider):
) -> CreateResult:
if not has_requirements:
raise MissingRequirementsError('Install "PyExecJS" package')
if not model:
model = "gpt-3.5-turbo"
elif model not in model_info:
raise ValueError(f"Vercel does not support {model}")
headers = {
'authority': 'sdk.vercel.ai',
'authority': 'chat.vercel.ai',
'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',
'cache-control': 'no-cache',
'content-type': 'application/json',
'custom-encoding': get_anti_bot_token(),
'origin': 'https://sdk.vercel.ai',
'origin': 'https://chat.vercel.ai',
'pragma': 'no-cache',
'referer': 'https://sdk.vercel.ai/',
'sec-ch-ua': '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
'referer': 'https://chat.vercel.ai/',
'sec-ch-ua': '"Chromium";v="122", "Not(A:Brand";v="24", "Google Chrome";v="122"',
'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': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36',
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36',
}
json_data = {
'model' : model_info[model]['id'],
'messages' : messages,
'playgroundId': str(uuid.uuid4()),
'chatIndex' : 0,
**model_info[model]['default_params'],
**kwargs
'messages': messages,
'id' : f'{os.urandom(3).hex()}a',
}
max_retries = kwargs.get('max_retries', 20)
max_retries = kwargs.get('max_retries', 6)
for _ in range(max_retries):
response = requests.post('https://sdk.vercel.ai/api/generate',
response = requests.post('https://chat.vercel.ai/api/chat',
headers=headers, json=json_data, stream=True, proxies={"https": proxy})
try:
response.raise_for_status()
@ -74,8 +66,7 @@ class Vercel(AbstractProvider):
for token in response.iter_content(chunk_size=None):
yield token.decode()
break
def get_anti_bot_token() -> str:
headers = {
'authority': 'sdk.vercel.ai',
@ -93,7 +84,7 @@ def get_anti_bot_token() -> str:
'user-agent': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36',
}
response = requests.get('https://sdk.vercel.ai/openai.jpeg',
response = requests.get('https://chat.vercel.ai/openai.jpeg',
headers=headers).text
raw_data = json.loads(base64.b64decode(response,
@ -101,292 +92,10 @@ def get_anti_bot_token() -> str:
js_script = '''const globalThis={marker:"mark"};String.prototype.fontcolor=function(){return `<font>${this}</font>`};
return (%s)(%s)''' % (raw_data['c'], raw_data['a'])
sec_list = [execjs.compile(js_script).call('')[0], [], "sentinel"]
raw_token = json.dumps({'r': execjs.compile(js_script).call(''), 't': raw_data['t']},
raw_token = json.dumps({'r': sec_list, 't': raw_data['t']},
separators = (",", ":"))
return base64.b64encode(raw_token.encode('utf-16le')).decode()
class ModelInfo(TypedDict):
id: str
default_params: dict[str, Any]
model_info: dict[str, ModelInfo] = {
# 'claude-instant-v1': {
# 'id': 'anthropic:claude-instant-v1',
# 'default_params': {
# 'temperature': 1,
# 'maximumLength': 1024,
# 'topP': 1,
# 'topK': 1,
# 'presencePenalty': 1,
# 'frequencyPenalty': 1,
# 'stopSequences': ['\n\nHuman:'],
# },
# },
# 'claude-v1': {
# 'id': 'anthropic:claude-v1',
# 'default_params': {
# 'temperature': 1,
# 'maximumLength': 1024,
# 'topP': 1,
# 'topK': 1,
# 'presencePenalty': 1,
# 'frequencyPenalty': 1,
# 'stopSequences': ['\n\nHuman:'],
# },
# },
# 'claude-v2': {
# 'id': 'anthropic:claude-v2',
# 'default_params': {
# 'temperature': 1,
# 'maximumLength': 1024,
# 'topP': 1,
# 'topK': 1,
# 'presencePenalty': 1,
# 'frequencyPenalty': 1,
# 'stopSequences': ['\n\nHuman:'],
# },
# },
'replicate/llama70b-v2-chat': {
'id': 'replicate:replicate/llama-2-70b-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'a16z-infra/llama7b-v2-chat': {
'id': 'replicate:a16z-infra/llama7b-v2-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'a16z-infra/llama13b-v2-chat': {
'id': 'replicate:a16z-infra/llama13b-v2-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'replicate/llama-2-70b-chat': {
'id': 'replicate:replicate/llama-2-70b-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'bigscience/bloom': {
'id': 'huggingface:bigscience/bloom',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'google/flan-t5-xxl': {
'id': 'huggingface:google/flan-t5-xxl',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'EleutherAI/gpt-neox-20b': {
'id': 'huggingface:EleutherAI/gpt-neox-20b',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
'stopSequences': [],
},
},
'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5': {
'id': 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
'default_params': {
'maximumLength': 1024,
'typicalP': 0.2,
'repetitionPenalty': 1,
},
},
'OpenAssistant/oasst-sft-1-pythia-12b': {
'id': 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
'default_params': {
'maximumLength': 1024,
'typicalP': 0.2,
'repetitionPenalty': 1,
},
},
'bigcode/santacoder': {
'id': 'huggingface:bigcode/santacoder',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'command-light-nightly': {
'id': 'cohere:command-light-nightly',
'default_params': {
'temperature': 0.9,
'maximumLength': 1024,
'topP': 1,
'topK': 0,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'command-nightly': {
'id': 'cohere:command-nightly',
'default_params': {
'temperature': 0.9,
'maximumLength': 1024,
'topP': 1,
'topK': 0,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
# 'gpt-4': {
# 'id': 'openai:gpt-4',
# 'default_params': {
# 'temperature': 0.7,
# 'maximumLength': 8192,
# 'topP': 1,
# 'presencePenalty': 0,
# 'frequencyPenalty': 0,
# 'stopSequences': [],
# },
# },
# 'gpt-4-0613': {
# 'id': 'openai:gpt-4-0613',
# 'default_params': {
# 'temperature': 0.7,
# 'maximumLength': 8192,
# 'topP': 1,
# 'presencePenalty': 0,
# 'frequencyPenalty': 0,
# 'stopSequences': [],
# },
# },
'code-davinci-002': {
'id': 'openai:code-davinci-002',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'gpt-3.5-turbo': {
'id': 'openai:gpt-3.5-turbo',
'default_params': {
'temperature': 0.7,
'maximumLength': 4096,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'gpt-3.5-turbo-16k': {
'id': 'openai:gpt-3.5-turbo-16k',
'default_params': {
'temperature': 0.7,
'maximumLength': 16280,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'gpt-3.5-turbo-16k-0613': {
'id': 'openai:gpt-3.5-turbo-16k-0613',
'default_params': {
'temperature': 0.7,
'maximumLength': 16280,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'text-ada-001': {
'id': 'openai:text-ada-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-babbage-001': {
'id': 'openai:text-babbage-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-curie-001': {
'id': 'openai:text-curie-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-davinci-002': {
'id': 'openai:text-davinci-002',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-davinci-003': {
'id': 'openai:text-davinci-003',
'default_params': {
'temperature': 0.5,
'maximumLength': 4097,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
}
return base64.b64encode(raw_token.encode('utf-8')).decode()

@ -0,0 +1,392 @@
from __future__ import annotations
import json, base64, requests, random, uuid
try:
import execjs
has_requirements = True
except ImportError:
has_requirements = False
from ...typing import Messages, TypedDict, CreateResult, Any
from ..base_provider import AbstractProvider
from ...errors import MissingRequirementsError
class Vercel(AbstractProvider):
url = 'https://sdk.vercel.ai'
working = False
supports_message_history = True
supports_gpt_35_turbo = True
supports_stream = True
@staticmethod
def create_completion(
model: str,
messages: Messages,
stream: bool,
proxy: str = None,
**kwargs
) -> CreateResult:
if not has_requirements:
raise MissingRequirementsError('Install "PyExecJS" package')
if not model:
model = "gpt-3.5-turbo"
elif model not in model_info:
raise ValueError(f"Vercel does not support {model}")
headers = {
'authority': 'sdk.vercel.ai',
'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',
'cache-control': 'no-cache',
'content-type': 'application/json',
'custom-encoding': get_anti_bot_token(),
'origin': 'https://sdk.vercel.ai',
'pragma': 'no-cache',
'referer': 'https://sdk.vercel.ai/',
'sec-ch-ua': '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
'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': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36',
}
json_data = {
'model' : model_info[model]['id'],
'messages' : messages,
'playgroundId': str(uuid.uuid4()),
'chatIndex' : 0,
**model_info[model]['default_params'],
**kwargs
}
max_retries = kwargs.get('max_retries', 20)
for _ in range(max_retries):
response = requests.post('https://chat.vercel.ai/api/chat',
headers=headers, json=json_data, stream=True, proxies={"https": proxy})
try:
response.raise_for_status()
except:
continue
for token in response.iter_content(chunk_size=None):
yield token.decode()
break
def get_anti_bot_token() -> str:
headers = {
'authority': 'sdk.vercel.ai',
'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',
'cache-control': 'no-cache',
'pragma': 'no-cache',
'referer': 'https://sdk.vercel.ai/',
'sec-ch-ua': '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
'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': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36',
}
response = requests.get('https://sdk.vercel.ai/openai.jpeg',
headers=headers).text
raw_data = json.loads(base64.b64decode(response,
validate=True))
js_script = '''const globalThis={marker:"mark"};String.prototype.fontcolor=function(){return `<font>${this}</font>`};
return (%s)(%s)''' % (raw_data['c'], raw_data['a'])
raw_token = json.dumps({'r': execjs.compile(js_script).call(''), 't': raw_data['t']},
separators = (",", ":"))
return base64.b64encode(raw_token.encode('utf-16le')).decode()
class ModelInfo(TypedDict):
id: str
default_params: dict[str, Any]
model_info: dict[str, ModelInfo] = {
# 'claude-instant-v1': {
# 'id': 'anthropic:claude-instant-v1',
# 'default_params': {
# 'temperature': 1,
# 'maximumLength': 1024,
# 'topP': 1,
# 'topK': 1,
# 'presencePenalty': 1,
# 'frequencyPenalty': 1,
# 'stopSequences': ['\n\nHuman:'],
# },
# },
# 'claude-v1': {
# 'id': 'anthropic:claude-v1',
# 'default_params': {
# 'temperature': 1,
# 'maximumLength': 1024,
# 'topP': 1,
# 'topK': 1,
# 'presencePenalty': 1,
# 'frequencyPenalty': 1,
# 'stopSequences': ['\n\nHuman:'],
# },
# },
# 'claude-v2': {
# 'id': 'anthropic:claude-v2',
# 'default_params': {
# 'temperature': 1,
# 'maximumLength': 1024,
# 'topP': 1,
# 'topK': 1,
# 'presencePenalty': 1,
# 'frequencyPenalty': 1,
# 'stopSequences': ['\n\nHuman:'],
# },
# },
'replicate/llama70b-v2-chat': {
'id': 'replicate:replicate/llama-2-70b-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'a16z-infra/llama7b-v2-chat': {
'id': 'replicate:a16z-infra/llama7b-v2-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'a16z-infra/llama13b-v2-chat': {
'id': 'replicate:a16z-infra/llama13b-v2-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'replicate/llama-2-70b-chat': {
'id': 'replicate:replicate/llama-2-70b-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'bigscience/bloom': {
'id': 'huggingface:bigscience/bloom',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'google/flan-t5-xxl': {
'id': 'huggingface:google/flan-t5-xxl',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'EleutherAI/gpt-neox-20b': {
'id': 'huggingface:EleutherAI/gpt-neox-20b',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
'stopSequences': [],
},
},
'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5': {
'id': 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
'default_params': {
'maximumLength': 1024,
'typicalP': 0.2,
'repetitionPenalty': 1,
},
},
'OpenAssistant/oasst-sft-1-pythia-12b': {
'id': 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
'default_params': {
'maximumLength': 1024,
'typicalP': 0.2,
'repetitionPenalty': 1,
},
},
'bigcode/santacoder': {
'id': 'huggingface:bigcode/santacoder',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'command-light-nightly': {
'id': 'cohere:command-light-nightly',
'default_params': {
'temperature': 0.9,
'maximumLength': 1024,
'topP': 1,
'topK': 0,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'command-nightly': {
'id': 'cohere:command-nightly',
'default_params': {
'temperature': 0.9,
'maximumLength': 1024,
'topP': 1,
'topK': 0,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
# 'gpt-4': {
# 'id': 'openai:gpt-4',
# 'default_params': {
# 'temperature': 0.7,
# 'maximumLength': 8192,
# 'topP': 1,
# 'presencePenalty': 0,
# 'frequencyPenalty': 0,
# 'stopSequences': [],
# },
# },
# 'gpt-4-0613': {
# 'id': 'openai:gpt-4-0613',
# 'default_params': {
# 'temperature': 0.7,
# 'maximumLength': 8192,
# 'topP': 1,
# 'presencePenalty': 0,
# 'frequencyPenalty': 0,
# 'stopSequences': [],
# },
# },
'code-davinci-002': {
'id': 'openai:code-davinci-002',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'gpt-3.5-turbo': {
'id': 'openai:gpt-3.5-turbo',
'default_params': {
'temperature': 0.7,
'maximumLength': 4096,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'gpt-3.5-turbo-16k': {
'id': 'openai:gpt-3.5-turbo-16k',
'default_params': {
'temperature': 0.7,
'maximumLength': 16280,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'gpt-3.5-turbo-16k-0613': {
'id': 'openai:gpt-3.5-turbo-16k-0613',
'default_params': {
'temperature': 0.7,
'maximumLength': 16280,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'text-ada-001': {
'id': 'openai:text-ada-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-babbage-001': {
'id': 'openai:text-babbage-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-curie-001': {
'id': 'openai:text-curie-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
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