From 73ec30a3f0fffcd9aa87ec68b4856c44724e4f99 Mon Sep 17 00:00:00 2001 From: Tekky <98614666+xtekky@users.noreply.github.com> Date: Sun, 17 Sep 2023 22:51:22 +0100 Subject: ~ --- g4f/Provider/Vercel.py | 353 ------------------------------------------------- 1 file changed, 353 deletions(-) delete mode 100644 g4f/Provider/Vercel.py diff --git a/g4f/Provider/Vercel.py b/g4f/Provider/Vercel.py deleted file mode 100644 index 79bcf3f4..00000000 --- a/g4f/Provider/Vercel.py +++ /dev/null @@ -1,353 +0,0 @@ -from __future__ import annotations - -import base64, json, uuid, quickjs, random -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 = True - 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: - if model in ["gpt-3.5-turbo", "gpt-4"]: - model = "openai:" + model - model = model if model else cls.model - proxies = None - if proxy: - if "://" not in proxy: - proxy = "http://" + proxy - proxies = {"http": proxy, "https": proxy} - headers = { - "User-Agent": "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.{rand1}.{rand2} Safari/537.36".format( - rand1=random.randint(0,9999), - rand2=random.randint(0,9999) - ), - "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8", - "Accept-Encoding": "gzip, deflate, br", - "Accept-Language": "en-US,en;q=0.5", - "TE": "trailers", - } - async with AsyncSession(headers=headers, proxies=proxies, impersonate="chrome107") as session: - response = await session.get(cls.url + "/openai.jpeg") - response.raise_for_status() - custom_encoding = _get_custom_encoding(response.text) - headers = { - "Content-Type": "application/json", - "Custom-Encoding": custom_encoding, - } - data = _create_payload(model, messages) - response = await session.post(cls.url + "/api/generate", json=data, headers=headers) - response.raise_for_status() - return response.text - - -def _create_payload(model: str, messages: list[dict[str, str]]) -> dict[str, Any]: - if model not in model_info: - raise ValueError(f'Model are not supported: {model}') - default_params = model_info[model]["default_params"] - return { - "messages": messages, - "playgroundId": str(uuid.uuid4()), - "chatIndex": 0, - "model": model - } | default_params - -# based on https://github.com/ading2210/vercel-llm-api -def _get_custom_encoding(text: str) -> str: - data = json.loads(base64.b64decode(text, validate=True)) - script = """ - String.prototype.fontcolor = function() {{ - return `${{this}}` - }} - var globalThis = {{marker: "mark"}}; - ({script})({key}) - """.format( - script=data["c"], key=data["a"] - ) - context = quickjs.Context() # type: ignore - token_data = json.loads(context.eval(script).json()) # type: ignore - token_data[2] = "mark" - token = {"r": token_data, "t": data["t"]} - token_str = json.dumps(token, separators=(",", ":")).encode("utf-16le") - return base64.b64encode(token_str).decode() - - -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": { - 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