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://sdk.vercel.ai/api/generate', 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 `${this}`}; 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, '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': [], }, }, }