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The generic provider treated any Venice-style model_spec.pricing as authoritative after only a None check, so a native both-zero price served the model free, a negative one credited the caller on every request, and a non-numeric string threw while parsing — the outer catch then dropped the provider's entire catalog. Coerce both native prices through the resolver's _as_float and reject absent / non-numeric / negative / both-zero values, falling through to the shared litellm→OpenRouter→fail-closed chain instead. This extends the same money-safety guard the litellm and OpenRouter rungs already apply to the native source, and keeps one malformed entry from emptying the catalog. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
234 lines
9.4 KiB
Python
234 lines
9.4 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING
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import httpx
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from .base import BaseUpstreamProvider
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from .pricing_resolver import (
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FallbackPricingResolver,
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ResolvedPricing,
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_as_float,
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estimate_context_length,
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)
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if TYPE_CHECKING:
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from ..core.db import UpstreamProviderRow
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from ..payment.models import Model
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from ..core.logging import get_logger
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logger = get_logger(__name__)
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class GenericUpstreamProvider(BaseUpstreamProvider):
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"""Generic upstream provider that can fetch models from any OpenAI-compatible API."""
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provider_type = "generic"
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default_base_url = "http://localhost:8888"
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platform_url = None
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def __init__(
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self,
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base_url: str,
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api_key: str = "",
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provider_fee: float = 1.01,
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upstream_name: str | None = None,
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):
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"""Initialize generic provider.
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Args:
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base_url: Base URL of the upstream API endpoint
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api_key: Optional API key for authentication
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provider_fee: Provider fee multiplier (default 1.01 for 1% fee)
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upstream_name: Optional name for the upstream provider
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"""
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self.upstream_name = upstream_name or "generic"
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super().__init__(
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base_url=base_url,
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api_key=api_key,
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provider_fee=provider_fee,
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)
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@classmethod
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def _build_from_row(
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cls, provider_row: "UpstreamProviderRow"
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) -> "GenericUpstreamProvider":
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return cls(
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base_url=provider_row.base_url,
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api_key=provider_row.api_key,
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provider_fee=provider_row.provider_fee,
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)
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@classmethod
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def get_provider_metadata(cls) -> dict[str, object]:
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return {
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"id": cls.provider_type,
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"name": "Generic",
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"default_base_url": cls.default_base_url,
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"fixed_base_url": False,
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"platform_url": cls.platform_url,
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}
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def _native_pricing(
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self, model_id: str, model_spec: dict
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) -> ResolvedPricing | None:
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"""Read pricing/metadata from Venice's bespoke ``model_spec`` schema.
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Returns ``None`` when the upstream reported no *usable* native price —
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absent, non-numeric, negative, or both-zero — so the caller falls
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through to the shared resolution chain instead of fabricating a number
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or trusting a bogus one. This mirrors the money-safety guards the
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litellm and OpenRouter rungs already apply: a both-zero price would
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serve the model free, a negative one would credit the caller, and a
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non-numeric string would otherwise throw and drop the whole catalog.
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"""
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pricing_info = model_spec.get("pricing", {})
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input_usd = _as_float(pricing_info.get("input", {}).get("usd"))
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output_usd = _as_float(pricing_info.get("output", {}).get("usd"))
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if input_usd is None or output_usd is None:
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return None
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if input_usd < 0 or output_usd < 0 or (input_usd == 0 and output_usd == 0):
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return None
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capabilities = model_spec.get("capabilities", {})
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input_modalities = ["text"]
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if capabilities.get("supportsVision", False):
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input_modalities.append("image")
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return ResolvedPricing(
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prompt=input_usd / 1_000_000,
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completion=output_usd / 1_000_000,
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context_length=model_spec.get("availableContextTokens"),
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source="native",
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input_modalities=input_modalities,
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)
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async def fetch_models(self) -> list[Model]:
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"""Fetch models from upstream API using /models endpoint."""
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from ..payment.models import Architecture, Model, Pricing, TopProvider
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try:
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async with httpx.AsyncClient(timeout=30.0) as client:
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headers = {}
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if self.api_key:
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headers["Authorization"] = f"Bearer {self.api_key}"
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response = await client.get(f"{self.base_url}/models", headers=headers)
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response.raise_for_status()
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data = response.json()
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resolver = FallbackPricingResolver()
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models_list = []
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for model_data in data.get("data", []):
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model_id = model_data.get("id", "")
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if not model_id:
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continue
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model_name = model_data.get("name", model_id)
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created = model_data.get("created", 0)
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owned_by = model_data.get("owned_by", "unknown")
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model_spec = model_data.get("model_spec", {})
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resolved = self._native_pricing(model_id, model_spec)
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if resolved is None:
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resolved = await resolver.resolve(model_id)
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if resolved is None:
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# Fail closed: never invent a price. Import the model
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# disabled with a warning so the operator can price it
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# (the admin UI surfaces disabled remote models).
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logger.warning(
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f"No pricing source resolved for '{model_id}' from "
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f"{self.upstream_name}; importing it disabled",
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extra={"model_id": model_id, "base_url": self.base_url},
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)
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resolved = ResolvedPricing(
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prompt=0.0,
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completion=0.0,
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context_length=None,
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source="unresolved",
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)
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enabled = False
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else:
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enabled = True
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# Prefer the source's own modality string (OpenRouter ships
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# one, e.g. "text+image->text"); otherwise derive it from the
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# captured input/output modalities in the same "in->out" shape
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# rather than flattening vision models to "text->text".
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modality = resolved.modality or (
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f"{'+'.join(resolved.input_modalities)}"
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f"->{'+'.join(resolved.output_modalities)}"
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)
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# A source can carry a price but no context (e.g. a litellm
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# entry missing max_input_tokens); fall back to an id-based
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# estimate so we never persist a zero-length window.
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context_length = resolved.context_length or estimate_context_length(
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model_id
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)
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spec_name = model_spec.get("name", model_name)
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description = f"{spec_name}"
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if owned_by != "unknown":
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description += f" via {owned_by}"
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models_list.append(
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Model(
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id=model_id,
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name=spec_name,
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created=created,
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description=description,
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context_length=context_length,
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architecture=Architecture(
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modality=modality,
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input_modalities=resolved.input_modalities,
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output_modalities=resolved.output_modalities,
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tokenizer=resolved.tokenizer,
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instruct_type=resolved.instruct_type,
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),
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pricing=Pricing(
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prompt=resolved.prompt,
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completion=resolved.completion,
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request=0.0,
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image=0.0,
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web_search=0.0,
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internal_reasoning=0.0,
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input_cache_read=resolved.input_cache_read,
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input_cache_write=resolved.input_cache_write,
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),
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sats_pricing=None,
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per_request_limits=None,
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top_provider=TopProvider(
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context_length=context_length,
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max_completion_tokens=(
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resolved.max_completion_tokens
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if resolved.max_completion_tokens is not None
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else context_length // 2
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),
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is_moderated=bool(resolved.is_moderated),
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),
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enabled=enabled,
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upstream_provider_id=None,
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canonical_slug=None,
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)
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)
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logger.info(
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f"Fetched {len(models_list)} models from {self.upstream_name}",
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extra={"model_count": len(models_list), "base_url": self.base_url},
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)
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return models_list
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except Exception as e:
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logger.error(
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f"Failed to fetch models from {self.upstream_name} API: {e}",
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extra={
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"error": str(e),
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"error_type": type(e).__name__,
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"base_url": self.base_url,
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},
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)
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return []
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