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-rw-r--r--g4f/Provider/Vercel.py66
1 files changed, 2 insertions, 64 deletions
diff --git a/g4f/Provider/Vercel.py b/g4f/Provider/Vercel.py
index 79bcf3f4..43f7d741 100644
--- a/g4f/Provider/Vercel.py
+++ b/g4f/Provider/Vercel.py
@@ -9,7 +9,7 @@ from .base_provider import AsyncProvider
class Vercel(AsyncProvider):
url = "https://sdk.vercel.ai"
- working = True
+ working = False
supports_gpt_35_turbo = True
model = "replicate:replicate/llama-2-70b-chat"
@@ -21,74 +21,12 @@ class Vercel(AsyncProvider):
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 `<font>${{this}}</font>`
- }}
- 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()
-
+ 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",