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author | abc <98614666+xtekky@users.noreply.github.com> | 2023-09-23 02:31:46 +0200 |
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committer | abc <98614666+xtekky@users.noreply.github.com> | 2023-09-23 02:31:46 +0200 |
commit | d4acc23c0b2259222438a184dd17dd02c1db2f91 (patch) | |
tree | afcd8157a1f37447d918e8afc8f5cccc7d2d88ec /g4f/Provider | |
parent | ~ | update models list (diff) | |
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Diffstat (limited to '')
-rw-r--r-- | g4f/Provider/Vercel.py | 534 |
1 files changed, 307 insertions, 227 deletions
diff --git a/g4f/Provider/Vercel.py b/g4f/Provider/Vercel.py index 9835cdc0..b3241b70 100644 --- a/g4f/Provider/Vercel.py +++ b/g4f/Provider/Vercel.py @@ -1,289 +1,369 @@ -from __future__ import annotations -from curl_cffi.requests import AsyncSession +from __future__ import annotations -from ..typing import Any, TypedDict -from .base_provider import AsyncProvider +import json, base64, requests, execjs, random, uuid +from ..typing import Any, TypedDict, CreateResult +from .base_provider import BaseProvider +from abc import abstractmethod -class Vercel(AsyncProvider): - url = "https://sdk.vercel.ai" - working = False + +class Vercel(BaseProvider): + url = 'https://sdk.vercel.ai' + working = True supports_gpt_35_turbo = True - model = "replicate:replicate/llama-2-70b-chat" + supports_stream = True - @classmethod - async def create_async( - cls, + @staticmethod + @abstractmethod + def create_completion( model: str, messages: list[dict[str, str]], - proxy: str = None, - **kwargs - ) -> str: - return + stream: bool, **kwargs ) -> CreateResult: + + 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' : AntiBotToken(), + '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' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.%s.%s Safari/537.36' % ( + random.randint(99, 999), + random.randint(99, 999) + ) + } + + json_data = { + 'model' : model_info[model]['id'], + 'messages' : messages, + 'playgroundId': str(uuid.uuid4()), + 'chatIndex' : 0} | model_info[model]['default_params'] + + + server_error = True + while server_error: + response = requests.post('https://sdk.vercel.ai/api/generate', + headers=headers, json=json_data, stream=True) + + for token in response.iter_content(chunk_size=2046): + if token != b'Internal Server Error': + server_error = False + yield (token.decode()) + +def AntiBotToken() -> 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' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.%s.%s Safari/537.36' % ( + random.randint(99, 999), + random.randint(99, 999) + ) + } + + 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] = { - "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:"], + '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:'], }, }, - "anthropic:claude-v1": { - "id": "anthropic:claude-v1", - "default_params": { - "temperature": 1, - "maxTokens": 200, - "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:'], }, }, - "anthropic:claude-v2": { - "id": "anthropic:claude-v2", - "default_params": { - "temperature": 1, - "maxTokens": 200, - "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:a16z-infra/llama7b-v2-chat": { - "id": "replicate:a16z-infra/llama7b-v2-chat", - "default_params": { - "temperature": 0.75, - "maxTokens": 500, - "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, }, }, - "replicate:a16z-infra/llama13b-v2-chat": { - "id": "replicate:a16z-infra/llama13b-v2-chat", - "default_params": { - "temperature": 0.75, - "maxTokens": 500, - "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:replicate/llama-2-70b-chat": { - "id": "replicate:replicate/llama-2-70b-chat", - "default_params": { - "temperature": 0.75, - "maxTokens": 1000, - "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, }, }, - "huggingface:bigscience/bloom": { - "id": "huggingface:bigscience/bloom", - "default_params": { - "temperature": 0.5, - "maxTokens": 200, - "topP": 0.95, - "topK": 4, - "repetitionPenalty": 1.03, + 'bigscience/bloom': { + 'id': 'huggingface:bigscience/bloom', + 'default_params': { + 'temperature': 0.5, + 'maximumLength': 1024, + '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, + '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, }, }, - "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": [], + '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': [], }, }, - "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}, + '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, + }, }, - "huggingface:OpenAssistant/oasst-sft-1-pythia-12b": { - "id": "huggingface:OpenAssistant/oasst-sft-1-pythia-12b", - "default_params": {"maxTokens": 200, "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, + }, }, - "huggingface:bigcode/santacoder": { - "id": "huggingface:bigcode/santacoder", - "default_params": { - "temperature": 0.5, - "maxTokens": 200, - "topP": 0.95, - "topK": 4, - "repetitionPenalty": 1.03, + 'bigcode/santacoder': { + 'id': 'huggingface:bigcode/santacoder', + 'default_params': { + 'temperature': 0.5, + 'maximumLength': 1024, + '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": [], + 'command-light-nightly': { + 'id': 'cohere:command-light-nightly', + 'default_params': { + 'temperature': 0.9, + 'maximumLength': 1024, + 'topP': 1, + 'topK': 0, + 'presencePenalty': 0, + 'frequencyPenalty': 0, + 'stopSequences': [], }, }, - 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