vercel.py•4.25 kB
from __future__ import annotations as _annotations
import os
from typing import overload
import httpx
from pydantic_ai import ModelProfile
from pydantic_ai.exceptions import UserError
from pydantic_ai.models import cached_async_http_client
from pydantic_ai.profiles.amazon import amazon_model_profile
from pydantic_ai.profiles.anthropic import anthropic_model_profile
from pydantic_ai.profiles.cohere import cohere_model_profile
from pydantic_ai.profiles.deepseek import deepseek_model_profile
from pydantic_ai.profiles.google import google_model_profile
from pydantic_ai.profiles.grok import grok_model_profile
from pydantic_ai.profiles.mistral import mistral_model_profile
from pydantic_ai.profiles.openai import OpenAIJsonSchemaTransformer, OpenAIModelProfile, openai_model_profile
from pydantic_ai.providers import Provider
try:
from openai import AsyncOpenAI
except ImportError as _import_error: # pragma: no cover
raise ImportError(
'Please install the `openai` package to use the Vercel provider, '
'you can use the `openai` optional group — `pip install "pydantic-ai-slim[openai]"`'
) from _import_error
class VercelProvider(Provider[AsyncOpenAI]):
"""Provider for Vercel AI Gateway API."""
@property
def name(self) -> str:
return 'vercel'
@property
def base_url(self) -> str:
return 'https://ai-gateway.vercel.sh/v1'
@property
def client(self) -> AsyncOpenAI:
return self._client
def model_profile(self, model_name: str) -> ModelProfile | None:
provider_to_profile = {
'anthropic': anthropic_model_profile,
'bedrock': amazon_model_profile,
'cohere': cohere_model_profile,
'deepseek': deepseek_model_profile,
'mistral': mistral_model_profile,
'openai': openai_model_profile,
'vertex': google_model_profile,
'xai': grok_model_profile,
}
profile = None
try:
provider, model_name = model_name.split('/', 1)
except ValueError:
raise UserError(f"Model name must be in 'provider/model' format, got: {model_name!r}")
if provider in provider_to_profile:
profile = provider_to_profile[provider](model_name)
# As VercelProvider is always used with OpenAIChatModel, which used to unconditionally use OpenAIJsonSchemaTransformer,
# we need to maintain that behavior unless json_schema_transformer is set explicitly
return OpenAIModelProfile(
json_schema_transformer=OpenAIJsonSchemaTransformer,
).update(profile)
@overload
def __init__(self) -> None: ...
@overload
def __init__(self, *, api_key: str) -> None: ...
@overload
def __init__(self, *, api_key: str, http_client: httpx.AsyncClient) -> None: ...
@overload
def __init__(self, *, openai_client: AsyncOpenAI | None = None) -> None: ...
def __init__(
self,
*,
api_key: str | None = None,
openai_client: AsyncOpenAI | None = None,
http_client: httpx.AsyncClient | None = None,
) -> None:
# Support Vercel AI Gateway's standard environment variables
api_key = api_key or os.getenv('VERCEL_AI_GATEWAY_API_KEY') or os.getenv('VERCEL_OIDC_TOKEN')
if not api_key and openai_client is None:
raise UserError(
'Set the `VERCEL_AI_GATEWAY_API_KEY` or `VERCEL_OIDC_TOKEN` environment variable '
'or pass the API key via `VercelProvider(api_key=...)` to use the Vercel provider.'
)
default_headers = {'http-referer': 'https://ai.pydantic.dev/', 'x-title': 'pydantic-ai'}
if openai_client is not None:
self._client = openai_client
elif http_client is not None:
self._client = AsyncOpenAI(
base_url=self.base_url, api_key=api_key, http_client=http_client, default_headers=default_headers
)
else:
http_client = cached_async_http_client(provider='vercel')
self._client = AsyncOpenAI(
base_url=self.base_url, api_key=api_key, http_client=http_client, default_headers=default_headers
)