refactor: replace litellm with native openai + anthropic SDKs
- Remove litellm dependency entirely (supply chain risk mitigation) - Add AnthropicProvider (native SDK) and OpenAICompatProvider (unified) - Merge CustomProvider into OpenAICompatProvider, delete custom_provider.py - Add ProviderSpec.backend field for declarative provider routing - Remove _resolve_model, find_gateway, find_by_model (dead heuristics) - Pass resolved spec directly into provider — zero internal lookups - Stub out litellm-dependent model database (cli/models.py) - Add anthropic>=0.45.0 to dependencies, remove litellm - 593 tests passed, net -1034 lines
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Xubin Ren
Xubin Ren
@@ -1,161 +1,122 @@
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"""Regression tests for PR #2026 — litellm_kwargs injection from ProviderSpec.
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"""Tests for OpenAICompatProvider spec-driven behavior.
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Validates that:
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- OpenRouter uses litellm_prefix (NOT custom_llm_provider) to avoid LiteLLM double-prefixing.
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- The litellm_kwargs mechanism works correctly for providers that declare it.
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- Non-gateway providers are unaffected.
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- OpenRouter (no strip) keeps model names intact.
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- AiHubMix (strip_model_prefix=True) strips provider prefixes.
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- Standard providers pass model names through as-is.
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"""
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from __future__ import annotations
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from types import SimpleNamespace
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from typing import Any
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from unittest.mock import AsyncMock, patch
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import pytest
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from nanobot.providers.litellm_provider import LiteLLMProvider
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from nanobot.providers.openai_compat_provider import OpenAICompatProvider
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from nanobot.providers.registry import find_by_name
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def _fake_response(content: str = "ok") -> SimpleNamespace:
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"""Build a minimal acompletion-shaped response object."""
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def _fake_chat_response(content: str = "ok") -> SimpleNamespace:
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"""Build a minimal OpenAI chat completion response."""
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message = SimpleNamespace(
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content=content,
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tool_calls=None,
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reasoning_content=None,
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thinking_blocks=None,
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)
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choice = SimpleNamespace(message=message, finish_reason="stop")
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usage = SimpleNamespace(prompt_tokens=10, completion_tokens=5, total_tokens=15)
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return SimpleNamespace(choices=[choice], usage=usage)
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def test_openrouter_spec_uses_prefix_not_custom_llm_provider() -> None:
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"""OpenRouter must rely on litellm_prefix, not custom_llm_provider kwarg.
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LiteLLM internally adds a provider/ prefix when custom_llm_provider is set,
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which double-prefixes models (openrouter/anthropic/model) and breaks the API.
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"""
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def test_openrouter_spec_is_gateway() -> None:
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spec = find_by_name("openrouter")
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assert spec is not None
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assert spec.litellm_prefix == "openrouter"
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assert "custom_llm_provider" not in spec.litellm_kwargs, (
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"custom_llm_provider causes LiteLLM to double-prefix the model name"
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)
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assert spec.is_gateway is True
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assert spec.default_api_base == "https://openrouter.ai/api/v1"
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@pytest.mark.asyncio
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async def test_openrouter_prefixes_model_correctly() -> None:
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"""OpenRouter should prefix model as openrouter/vendor/model for LiteLLM routing."""
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mock_acompletion = AsyncMock(return_value=_fake_response())
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async def test_openrouter_keeps_model_name_intact() -> None:
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"""OpenRouter gateway keeps the full model name (gateway does its own routing)."""
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mock_create = AsyncMock(return_value=_fake_chat_response())
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spec = find_by_name("openrouter")
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with patch("nanobot.providers.litellm_provider.acompletion", mock_acompletion):
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provider = LiteLLMProvider(
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with patch("nanobot.providers.openai_compat_provider.AsyncOpenAI") as MockClient:
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client_instance = MockClient.return_value
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client_instance.chat.completions.create = mock_create
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provider = OpenAICompatProvider(
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api_key="sk-or-test-key",
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api_base="https://openrouter.ai/api/v1",
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default_model="anthropic/claude-sonnet-4-5",
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provider_name="openrouter",
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spec=spec,
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)
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await provider.chat(
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messages=[{"role": "user", "content": "hello"}],
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model="anthropic/claude-sonnet-4-5",
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)
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call_kwargs = mock_acompletion.call_args.kwargs
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assert call_kwargs["model"] == "openrouter/anthropic/claude-sonnet-4-5", (
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"LiteLLM needs openrouter/ prefix to detect the provider and strip it before API call"
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)
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assert "custom_llm_provider" not in call_kwargs
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call_kwargs = mock_create.call_args.kwargs
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assert call_kwargs["model"] == "anthropic/claude-sonnet-4-5"
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@pytest.mark.asyncio
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async def test_non_gateway_provider_no_extra_kwargs() -> None:
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"""Standard (non-gateway) providers must NOT inject any litellm_kwargs."""
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mock_acompletion = AsyncMock(return_value=_fake_response())
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async def test_aihubmix_strips_model_prefix() -> None:
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"""AiHubMix strips the provider prefix (strip_model_prefix=True)."""
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mock_create = AsyncMock(return_value=_fake_chat_response())
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spec = find_by_name("aihubmix")
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with patch("nanobot.providers.litellm_provider.acompletion", mock_acompletion):
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provider = LiteLLMProvider(
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api_key="sk-ant-test-key",
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default_model="claude-sonnet-4-5",
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)
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await provider.chat(
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messages=[{"role": "user", "content": "hello"}],
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model="claude-sonnet-4-5",
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)
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with patch("nanobot.providers.openai_compat_provider.AsyncOpenAI") as MockClient:
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client_instance = MockClient.return_value
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client_instance.chat.completions.create = mock_create
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call_kwargs = mock_acompletion.call_args.kwargs
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assert "custom_llm_provider" not in call_kwargs, (
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"Standard Anthropic provider should NOT inject custom_llm_provider"
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)
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@pytest.mark.asyncio
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async def test_gateway_without_litellm_kwargs_injects_nothing_extra() -> None:
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"""Gateways without litellm_kwargs (e.g. AiHubMix) must not add extra keys."""
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mock_acompletion = AsyncMock(return_value=_fake_response())
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with patch("nanobot.providers.litellm_provider.acompletion", mock_acompletion):
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provider = LiteLLMProvider(
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provider = OpenAICompatProvider(
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api_key="sk-aihub-test-key",
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api_base="https://aihubmix.com/v1",
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default_model="claude-sonnet-4-5",
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provider_name="aihubmix",
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)
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await provider.chat(
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messages=[{"role": "user", "content": "hello"}],
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model="claude-sonnet-4-5",
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)
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call_kwargs = mock_acompletion.call_args.kwargs
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assert "custom_llm_provider" not in call_kwargs
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@pytest.mark.asyncio
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async def test_openrouter_autodetect_by_key_prefix() -> None:
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"""OpenRouter should be auto-detected by sk-or- key prefix even without explicit provider_name."""
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mock_acompletion = AsyncMock(return_value=_fake_response())
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with patch("nanobot.providers.litellm_provider.acompletion", mock_acompletion):
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provider = LiteLLMProvider(
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api_key="sk-or-auto-detect-key",
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default_model="anthropic/claude-sonnet-4-5",
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spec=spec,
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)
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await provider.chat(
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messages=[{"role": "user", "content": "hello"}],
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model="anthropic/claude-sonnet-4-5",
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)
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call_kwargs = mock_acompletion.call_args.kwargs
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assert call_kwargs["model"] == "openrouter/anthropic/claude-sonnet-4-5", (
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"Auto-detected OpenRouter should prefix model for LiteLLM routing"
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)
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call_kwargs = mock_create.call_args.kwargs
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assert call_kwargs["model"] == "claude-sonnet-4-5"
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@pytest.mark.asyncio
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async def test_openrouter_native_model_id_gets_double_prefixed() -> None:
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"""Models like openrouter/free must be double-prefixed so LiteLLM strips one layer.
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async def test_standard_provider_passes_model_through() -> None:
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"""Standard provider (e.g. deepseek) passes model name through as-is."""
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mock_create = AsyncMock(return_value=_fake_chat_response())
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spec = find_by_name("deepseek")
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openrouter/free is an actual OpenRouter model ID. LiteLLM strips the first
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openrouter/ for routing, so we must send openrouter/openrouter/free to ensure
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the API receives openrouter/free.
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"""
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mock_acompletion = AsyncMock(return_value=_fake_response())
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with patch("nanobot.providers.openai_compat_provider.AsyncOpenAI") as MockClient:
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client_instance = MockClient.return_value
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client_instance.chat.completions.create = mock_create
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with patch("nanobot.providers.litellm_provider.acompletion", mock_acompletion):
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provider = LiteLLMProvider(
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api_key="sk-or-test-key",
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api_base="https://openrouter.ai/api/v1",
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default_model="openrouter/free",
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provider_name="openrouter",
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provider = OpenAICompatProvider(
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api_key="sk-deepseek-test-key",
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default_model="deepseek-chat",
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spec=spec,
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)
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await provider.chat(
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messages=[{"role": "user", "content": "hello"}],
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model="openrouter/free",
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model="deepseek-chat",
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)
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call_kwargs = mock_acompletion.call_args.kwargs
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assert call_kwargs["model"] == "openrouter/openrouter/free", (
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"openrouter/free must become openrouter/openrouter/free — "
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"LiteLLM strips one layer so the API receives openrouter/free"
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)
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call_kwargs = mock_create.call_args.kwargs
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assert call_kwargs["model"] == "deepseek-chat"
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def test_openai_model_passthrough() -> None:
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"""OpenAI models pass through unchanged."""
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spec = find_by_name("openai")
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with patch("nanobot.providers.openai_compat_provider.AsyncOpenAI"):
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provider = OpenAICompatProvider(
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api_key="sk-test-key",
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default_model="gpt-4o",
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spec=spec,
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)
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assert provider.get_default_model() == "gpt-4o"
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