from __future__ import annotations from curl_cffi.requests import AsyncSession from ..typing import Any, TypedDict from .base_provider import AsyncProvider class Vercel(AsyncProvider): url = "https://sdk.vercel.ai" working = False supports_gpt_35_turbo = True model = "replicate:replicate/llama-2-70b-chat" @classmethod async def create_async( cls, model: str, messages: list[dict[str, str]], proxy: str = None, **kwargs ) -> str: return class ModelInfo(TypedDict): id: str default_params: dict[str, Any] model_info: dict[str, ModelInfo] = { "anthropic:claude-instant-v1": { "id": "anthropic:claude-instant-v1", "default_params": { "temperature": 1, "maxTokens": 200, "topP": 1, "topK": 1, "presencePenalty": 1, "frequencyPenalty": 1, "stopSequences": ["\n\nHuman:"], }, }, "anthropic:claude-v1": { "id": "anthropic:claude-v1", "default_params": { "temperature": 1, "maxTokens": 200, "topP": 1, "topK": 1, "presencePenalty": 1, "frequencyPenalty": 1, "stopSequences": ["\n\nHuman:"], }, }, "anthropic:claude-v2": { "id": "anthropic:claude-v2", "default_params": { "temperature": 1, "maxTokens": 200, "topP": 1, "topK": 1, "presencePenalty": 1, "frequencyPenalty": 1, "stopSequences": ["\n\nHuman:"], }, }, "replicate:a16z-infra/llama7b-v2-chat": { "id": "replicate:a16z-infra/llama7b-v2-chat", "default_params": { "temperature": 0.75, "maxTokens": 500, "topP": 1, "repetitionPenalty": 1, }, }, "replicate:a16z-infra/llama13b-v2-chat": { "id": "replicate:a16z-infra/llama13b-v2-chat", "default_params": { "temperature": 0.75, "maxTokens": 500, "topP": 1, "repetitionPenalty": 1, }, }, "replicate:replicate/llama-2-70b-chat": { "id": "replicate:replicate/llama-2-70b-chat", "default_params": { "temperature": 0.75, "maxTokens": 1000, "topP": 1, "repetitionPenalty": 1, }, }, "huggingface:bigscience/bloom": { "id": "huggingface:bigscience/bloom", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 0.95, "topK": 4, "repetitionPenalty": 1.03, }, }, "huggingface:google/flan-t5-xxl": { "id": "huggingface:google/flan-t5-xxl", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 0.95, "topK": 4, "repetitionPenalty": 1.03, }, }, "huggingface:EleutherAI/gpt-neox-20b": { "id": "huggingface:EleutherAI/gpt-neox-20b", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 0.95, "topK": 4, "repetitionPenalty": 1.03, "stopSequences": [], }, }, "huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5": { "id": "huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", "default_params": {"maxTokens": 200, "typicalP": 0.2, "repetitionPenalty": 1}, }, "huggingface:OpenAssistant/oasst-sft-1-pythia-12b": { "id": "huggingface:OpenAssistant/oasst-sft-1-pythia-12b", "default_params": {"maxTokens": 200, "typicalP": 0.2, "repetitionPenalty": 1}, }, "huggingface:bigcode/santacoder": { "id": "huggingface:bigcode/santacoder", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 0.95, "topK": 4, "repetitionPenalty": 1.03, }, }, "cohere:command-light-nightly": { "id": "cohere:command-light-nightly", "default_params": { "temperature": 0.9, "maxTokens": 200, "topP": 1, "topK": 0, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "cohere:command-nightly": { "id": "cohere:command-nightly", "default_params": { "temperature": 0.9, "maxTokens": 200, "topP": 1, "topK": 0, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:gpt-4": { "id": "openai:gpt-4", "default_params": { "temperature": 0.7, "maxTokens": 500, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:gpt-4-0613": { "id": "openai:gpt-4-0613", "default_params": { "temperature": 0.7, "maxTokens": 500, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:code-davinci-002": { "id": "openai:code-davinci-002", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:gpt-3.5-turbo": { "id": "openai:gpt-3.5-turbo", "default_params": { "temperature": 0.7, "maxTokens": 500, "topP": 1, "topK": 1, "presencePenalty": 1, "frequencyPenalty": 1, "stopSequences": [], }, }, "openai:gpt-3.5-turbo-16k": { "id": "openai:gpt-3.5-turbo-16k", "default_params": { "temperature": 0.7, "maxTokens": 500, "topP": 1, "topK": 1, "presencePenalty": 1, "frequencyPenalty": 1, "stopSequences": [], }, }, "openai:gpt-3.5-turbo-16k-0613": { "id": "openai:gpt-3.5-turbo-16k-0613", "default_params": { "temperature": 0.7, "maxTokens": 500, "topP": 1, "topK": 1, "presencePenalty": 1, "frequencyPenalty": 1, "stopSequences": [], }, }, "openai:text-ada-001": { "id": "openai:text-ada-001", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:text-babbage-001": { "id": "openai:text-babbage-001", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:text-curie-001": { "id": "openai:text-curie-001", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:text-davinci-002": { "id": "openai:text-davinci-002", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, "openai:text-davinci-003": { "id": "openai:text-davinci-003", "default_params": { "temperature": 0.5, "maxTokens": 200, "topP": 1, "presencePenalty": 0, "frequencyPenalty": 0, "stopSequences": [], }, }, }