Files
turnstone/tests/test_model_probe.py
T
Patrick Buckley 12bd848c68 feat(providers): anthropic-compatible lane for local /v1/messages servers
Add provider id "anthropic-compatible": the existing AnthropicProvider
pointed at Anthropic-compatible local servers (vLLM /v1/messages),
mirroring the openai/openai-compatible split. Registry-only — configured
via the admin Models tab or [models.*] toml, not exposed on the bare
--provider flag, so the CLI/server prod-URL defaults are unreachable for
the lane and real-Anthropic behavior is untouched.

Lane behavior (live-verified against vLLM 0.22.1rc1 + DeepSeek-V4-Flash):
- Capability defaults replace the Claude static table: token_param
  max_tokens, thinking_mode none, web_search/tool_search/vision off,
  reasoning replay on. vLLM rejects Anthropic server-side tool types
  (tools require input_schema) and ignores the thinking request param,
  so neither is sent; thinking blocks still stream back and round-trip
  through the native lane verbatim.
- Reasoning toggles via server_compat extra_body chat_template_kwargs
  (first-class vLLM request field; request-level keys beat server
  defaults). _build_thinking_and_kwargs forwards non-internal
  extra_params as SDK extra_body; thinking_budget_tokens stays internal.
- No temperature force: thinking_mode none skips the Claude-only
  temperature=1.0 requirement.

Admin UI: provider option + URL placeholder (base_url without /v1 — the
SDK appends /v1/messages); the server-compat section shows only the
extra-body field for the lane. thinking_mode round-trips through the
form dropdown for every provider except anthropic-compatible, where it
stays in the raw capabilities JSON — the edit-load lift and save restore
use the same predicate so stored overrides are never silently dropped.

Docs: architecture.md gains the lane subsection incl. verified quirks
(thinking param dropped by vLLM; stop_sequences cut inside thinking and
report end_turn; usage has no cache fields; images need a multimodal
model; mid-conversation system turns are per-model opt-in).

Negative-tested: removing the _INTERNAL_EXTRA_PARAMS exclusion fails
test_internal_keys_not_leaked; the live test drives a streamed turn with
the chat_template_kwargs toggle and asserts no reasoning deltas.
2026-06-11 20:27:29 -07:00

279 lines
11 KiB
Python

"""Tests for probe_model_endpoint() and lookup_model_capabilities()."""
from __future__ import annotations
from typing import Any
from unittest.mock import MagicMock, patch
import pytest
from turnstone.core.model_registry import probe_model_endpoint
from turnstone.core.providers import list_known_models, lookup_model_capabilities
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _mock_model(
model_id: str,
*,
owned_by: str = "test",
meta: dict[str, Any] | None = None,
**kwargs: Any,
) -> MagicMock:
m = MagicMock()
m.id = model_id
dumped: dict[str, Any] = {"owned_by": owned_by}
if meta is not None:
dumped["meta"] = meta
if kwargs.get("max_model_len") is not None:
dumped["max_model_len"] = kwargs["max_model_len"]
m.model_dump.return_value = dumped
return m
def _mock_client(*models: MagicMock) -> MagicMock:
fast = MagicMock()
fast.models.list.return_value = MagicMock(data=list(models))
client = MagicMock()
client.with_options.return_value = fast
return client
# ---------------------------------------------------------------------------
# probe_model_endpoint
# ---------------------------------------------------------------------------
class TestProbeModelEndpoint:
@patch("turnstone.core.providers.create_client")
def test_probe_success(self, mock_cc: MagicMock) -> None:
m1 = _mock_model("model-a")
m2 = _mock_model("model-b")
mock_cc.return_value = _mock_client(m1, m2)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["reachable"] is True
assert result["available_models"] == ["model-a", "model-b"]
assert result["error"] is None
@patch("turnstone.core.providers.create_client")
def test_target_found(self, mock_cc: MagicMock) -> None:
m1 = _mock_model("gpt-5")
mock_cc.return_value = _mock_client(m1)
result = probe_model_endpoint(
"openai", "http://localhost:8000/v1", "key", target_model="gpt-5"
)
assert result["model_found"] is True
@patch("turnstone.core.providers.create_client")
def test_target_not_found(self, mock_cc: MagicMock) -> None:
m1 = _mock_model("model-a")
mock_cc.return_value = _mock_client(m1)
result = probe_model_endpoint(
"openai", "http://localhost:8000/v1", "key", target_model="gpt-5"
)
assert result["model_found"] is False
assert result["available_models"] == ["model-a"]
@patch("turnstone.core.providers.create_client")
def test_no_target_model_found_is_none(self, mock_cc: MagicMock) -> None:
m1 = _mock_model("model-a")
mock_cc.return_value = _mock_client(m1)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["model_found"] is None
@patch("turnstone.core.providers.create_client")
def test_context_window_llama_cpp(self, mock_cc: MagicMock) -> None:
m = _mock_model("qwen-32b", meta={"n_ctx_train": 131072})
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["context_window"] == 131072
assert result["server_type"] == "llama.cpp"
@patch("turnstone.core.providers.create_client")
def test_server_type_openai(self, mock_cc: MagicMock) -> None:
m = _mock_model("gpt-5")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "https://api.openai.com/v1", "sk-test")
assert result["server_type"] == "openai"
@patch("turnstone.core.providers.create_client")
def test_server_type_sglang(self, mock_cc: MagicMock) -> None:
m = _mock_model("meta-llama/Llama-3", owned_by="sglang")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "http://localhost:30000/v1", "key")
assert result["server_type"] == "sglang"
@patch("turnstone.core.providers.create_client")
def test_vllm_max_model_len(self, mock_cc: MagicMock) -> None:
m = _mock_model("/models/nemotron", max_model_len=262144, owned_by="vllm")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["context_window"] == 262144
assert result["server_type"] == "vllm"
@patch("turnstone.core.providers.create_client")
def test_vllm_max_model_len_preferred_over_meta(self, mock_cc: MagicMock) -> None:
m = _mock_model(
"/models/test",
meta={"n_ctx_train": 8192},
max_model_len=131072,
)
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["context_window"] == 131072
@patch("turnstone.core.providers.create_client")
def test_server_type_vllm(self, mock_cc: MagicMock) -> None:
m = _mock_model("org/model-name")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["server_type"] == "vllm"
@patch("turnstone.core.providers.create_client")
def test_server_type_generic(self, mock_cc: MagicMock) -> None:
m = _mock_model("my-model")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["server_type"] == "openai-compatible"
@patch("turnstone.core.providers.create_client")
def test_anthropic_provider(self, mock_cc: MagicMock) -> None:
m = _mock_model("claude-sonnet-4-6")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint(
"anthropic",
"https://api.anthropic.com",
"sk-ant-test",
target_model="claude-sonnet-4-6",
)
assert result["reachable"] is True
assert result["server_type"] == "anthropic"
assert result["context_window"] == 1000000
@patch("turnstone.core.providers.create_client")
def test_anthropic_compatible_server_type(self, mock_cc: MagicMock) -> None:
m = _mock_model("deepseek-ai/DeepSeek-V4-Flash")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("anthropic-compatible", "http://localhost:8000", "dummy")
assert result["reachable"] is True
assert result["server_type"] == "anthropic-compatible"
assert result["context_window"] is None
@patch("turnstone.core.providers.create_client")
def test_anthropic_compatible_max_model_len(self, mock_cc: MagicMock) -> None:
m = _mock_model("deepseek-ai/DeepSeek-V4-Flash", max_model_len=131072)
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint("anthropic-compatible", "http://localhost:8000", "dummy")
assert result["context_window"] == 131072
assert result["server_type"] == "anthropic-compatible"
@patch("turnstone.core.providers.create_client")
def test_connection_failure(self, mock_cc: MagicMock) -> None:
mock_cc.side_effect = OSError("Connection refused")
result = probe_model_endpoint("openai", "http://bad:1234/v1", "key")
assert result["reachable"] is False
assert "Connection refused" in (result["error"] or "")
@patch("turnstone.core.providers.create_client")
def test_empty_model_list(self, mock_cc: MagicMock) -> None:
mock_cc.return_value = _mock_client() # no models
result = probe_model_endpoint("openai", "http://localhost:8000/v1", "key")
assert result["reachable"] is True
assert result["available_models"] == []
assert "No models found" in (result["error"] or "")
@patch("turnstone.core.providers.create_client")
def test_context_window_openai_static_table(self, mock_cc: MagicMock) -> None:
"""When base_url is api.openai.com and model is known, use static table."""
m = _mock_model("gpt-5")
mock_cc.return_value = _mock_client(m)
result = probe_model_endpoint(
"openai", "https://api.openai.com/v1", "sk-test", target_model="gpt-5"
)
assert result["context_window"] == 400000
# ---------------------------------------------------------------------------
# lookup_model_capabilities
# ---------------------------------------------------------------------------
class TestLookupModelCapabilities:
def test_known_openai_model(self) -> None:
caps = lookup_model_capabilities("openai", "gpt-5")
assert caps is not None
assert caps["context_window"] == 400000
assert caps["supports_temperature"] is False
def test_known_anthropic_model(self) -> None:
caps = lookup_model_capabilities("anthropic", "claude-opus-4-6")
assert caps is not None
assert caps["context_window"] == 1000000
assert caps["thinking_mode"] == "adaptive"
def test_unknown_model_returns_none(self) -> None:
caps = lookup_model_capabilities("openai", "totally-unknown-model")
assert caps is None
def test_tuples_converted_to_lists(self) -> None:
caps = lookup_model_capabilities("openai", "gpt-5")
assert caps is not None
for val in caps.values():
assert not isinstance(val, tuple), f"Found tuple: {val}"
def test_reasoning_effort_values_are_list(self) -> None:
caps = lookup_model_capabilities("openai", "gpt-5")
assert caps is not None
assert isinstance(caps["reasoning_effort_values"], list)
assert "medium" in caps["reasoning_effort_values"]
def test_openai_compatible_returns_none(self) -> None:
caps = lookup_model_capabilities("openai-compatible", "my-local-model")
assert caps is None
def test_invalid_provider_raises(self) -> None:
with pytest.raises(ValueError, match="Unknown provider"):
lookup_model_capabilities("bad-provider", "gpt-5")
# ---------------------------------------------------------------------------
# list_known_models
# ---------------------------------------------------------------------------
class TestListKnownModels:
def test_openai_models(self) -> None:
models = list_known_models("openai")
assert "gpt-5" in models
assert isinstance(models, list)
assert models == sorted(models)
def test_anthropic_models(self) -> None:
models = list_known_models("anthropic")
assert "claude-opus-4-6" in models
def test_openai_compatible_returns_empty(self) -> None:
assert list_known_models("openai-compatible") == []
def test_unknown_provider_returns_empty(self) -> None:
assert list_known_models("bad-provider") == []