from __future__ import annotations import json from ..typing import AsyncResult, Messages from .base_provider import AsyncGeneratorProvider, ProviderModelMixin, AuthFileMixin from ..requests import StreamSession, get_args_from_nodriver, raise_for_status, merge_cookies from ..requests import DEFAULT_HEADERS, has_nodriver, has_curl_cffi from ..providers.response import FinishReason, Usage from ..errors import ResponseStatusError, ModelNotFoundError from .. import debug from .helper import render_messages def clean_name(name: str) -> str: return name.split("/")[-1].replace( "-instruct", "").replace( "-17b-16e", "").replace( "-chat", "").replace( "-fp8", "").replace( "-fast", "").replace( "-int8", "").replace( "-awq", "").replace( "-qvq", "").replace( "-r1", "").replace( "meta-llama-", "llama-").replace( "-it", "").replace( "qwen-", "qwen").replace( "qwen", "qwen-") # models = [] # model_aliases = {clean_name(m.get("name")): m.get("name") for m in models} # open(__file__, "a").write(f"""# Generated by g4f.models.cloudflare.py # model_aliases = {model_aliases} # """) class Cloudflare(AsyncGeneratorProvider, ProviderModelMixin, AuthFileMixin): label = "Cloudflare AI" url = "https://playground.ai.cloudflare.com" working = False use_nodriver = True active_by_default = True api_endpoint = "https://playground.ai.cloudflare.com/api/inference" models_url = "https://playground.ai.cloudflare.com/api/models" supports_stream = True supports_system_message = True supports_message_history = True default_model = 'llama-3.3-70b' model_aliases = { 'deepseek-coder-6.7b-base': '@hf/thebloke/deepseek-coder-6.7b-base-awq', 'deepseek-coder-6.7b': '@hf/thebloke/deepseek-coder-6.7b-instruct-awq', 'deepseek-math-7b': '@cf/deepseek-ai/deepseek-math-7b-instruct', 'deepseek-distill-qwen-32b': '@cf/deepseek-ai/deepseek-r1-distill-qwen-32b', 'discolm-german-7b-v1': '@cf/thebloke/discolm-german-7b-v1-awq', 'falcon-7b': '@cf/tiiuae/falcon-7b-instruct', 'gemma-3-12b': '@cf/google/gemma-3-12b-it', 'gemma-7b': '@hf/google/gemma-7b-it', 'hermes-2-pro-mistral-7b': '@hf/nousresearch/hermes-2-pro-mistral-7b', 'llama-2-13b': '@hf/thebloke/llama-2-13b-chat-awq', 'llama-2-7b-fp16': '@cf/meta/llama-2-7b-chat-fp16', 'llama-2-7b': '@cf/meta/llama-2-7b-chat-int8', 'llama-3-8b': '@hf/meta-llama/meta-llama-3-8b-instruct', 'llama-3.1-8b': '@cf/meta/llama-3.1-8b-instruct-fp8', 'llama-3.2-11b-vision': '@cf/meta/llama-3.2-11b-vision-instruct', 'llama-3.2-1b': '@cf/meta/llama-3.2-1b-instruct', 'llama-3.2-3b': '@cf/meta/llama-3.2-3b-instruct', 'llama-3.3-70b': '@cf/meta/llama-3.3-70b-instruct-fp8-fast', 'llama-4-scout': '@cf/meta/llama-4-scout-17b-16e-instruct', 'llama-guard-3-8b': '@cf/meta/llama-guard-3-8b', 'llamaguard-7b': '@hf/thebloke/llamaguard-7b-awq', 'mistral-7b-v0.1': '@hf/thebloke/mistral-7b-instruct-v0.1-awq', 'mistral-7b-v0.2': '@hf/mistral/mistral-7b-instruct-v0.2', 'mistral-small-3.1-24b': '@cf/mistralai/mistral-small-3.1-24b-instruct', 'neural-7b-v3-1': '@hf/thebloke/neural-chat-7b-v3-1-awq', 'openchat-3.5-0106': '@cf/openchat/openchat-3.5-0106', 'openhermes-2.5-mistral-7b': '@hf/thebloke/openhermes-2.5-mistral-7b-awq', 'phi-2': '@cf/microsoft/phi-2', 'qwen1.5-0.5b': '@cf/qwen/qwen1.5-0.5b-chat', 'qwen-1.5-1.8b': '@cf/qwen/qwen1.5-1.8b-chat', 'qwen-1.5-14b': '@cf/qwen/qwen1.5-14b-chat-awq', 'qwen-1.5-7b': '@cf/qwen/qwen1.5-7b-chat-awq', 'qwen-2.5-coder-32b': '@cf/qwen/qwen2.5-coder-32b-instruct', 'qwq-32b': '@cf/qwen/qwq-32b', 'sqlcoder-7b-2': '@cf/defog/sqlcoder-7b-2', 'starling-lm-7b-beta': '@hf/nexusflow/starling-lm-7b-beta', 'tinyllama-1.1b-v1.0': '@cf/tinyllama/tinyllama-1.1b-chat-v1.0', 'una-cybertron-7b-v2-bf16': '@cf/fblgit/una-cybertron-7b-v2-bf16', 'zephyr-7b-beta': '@hf/thebloke/zephyr-7b-beta-awq' } models = list(model_aliases.keys()) _args: dict = None @classmethod async def create_async_generator( cls, model: str, messages: Messages, proxy: str = None, max_tokens: int = 2048, **kwargs ) -> AsyncResult: cache_file = cls.get_cache_file() if cls._args is None: headers = DEFAULT_HEADERS.copy() headers["referer"] = f"{cls.url}" headers["origin"] = cls.url if cache_file.exists(): with cache_file.open("r") as f: cls._args = json.load(f) elif has_nodriver: try: cls._args = await get_args_from_nodriver(cls.url, proxy=proxy) except (RuntimeError, FileNotFoundError) as e: debug.log(f"Cloudflare: Nodriver is not available:", e) cls._args = {"headers": headers, "cookies": {}, "impersonate": "chrome"} else: cls._args = {"headers": headers, "cookies": {}, "impersonate": "chrome"} try: model = cls.get_model(model) except ModelNotFoundError: pass data = { "messages": [{ **message, "parts": [{"type":"text", "text": message["content"]}]} for message in render_messages(messages)], "lora": None, "model": model, "max_tokens": max_tokens, "stream": True, "system_message":"You are a helpful assistant", "tools":[] } async with StreamSession(**cls._args) as session: async with session.post( cls.api_endpoint, json=data, ) as response: cls._args["cookies"] = merge_cookies(cls._args["cookies"] , response) try: await raise_for_status(response) except ResponseStatusError: cls._args = None if cache_file.exists(): cache_file.unlink() raise async for line in response.iter_lines(): if line.startswith(b'0:'): yield json.loads(line[2:]) elif line.startswith(b'e:'): finish = json.loads(line[2:]) yield Usage(**finish.get("usage")) yield FinishReason(finish.get("finishReason")) with cache_file.open("w") as f: json.dump(cls._args, f)