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hermes-agent/tests/hermes_cli/test_azure_detect.py

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feat(azure-foundry): auto-detect transport, models, context length The azure-foundry wizard now probes the endpoint before asking the user to pick anything by hand: 1. URL path sniff — endpoints ending in /anthropic are Azure Foundry Claude routes and skip to anthropic_messages. 2. GET <base>/models probe — if the endpoint returns an OpenAI-shaped model list, we switch to chat_completions and prefill the picker with the returned deployment/model IDs. 3. Anthropic Messages probe — fallback for endpoints that don't expose /models but do speak the Anthropic Messages shape. 4. Manual fallback — private endpoints / custom routes still work; the user picks API mode + types a deployment name. Context length for the selected model is resolved through the existing agent.model_metadata.get_model_context_length chain (models.dev, provider metadata, hardcoded family fallbacks) and stored in model.context_length when a non-default value is found. Also refactors runtime_provider so Azure Foundry resolution is reused between the explicit-credentials path and the default top-level path — previously the /v1 strip for Anthropic-style Azure only ran when the caller passed explicit_* args, which meant config-driven sessions hit a double-/v1 URL. New module hermes_cli/azure_detect.py with 19 unit tests covering: - path sniff, model ID extraction, probe fallbacks - HTTP error handling (URLError, HTTPError) - context-length lookup passthrough - DEFAULT_FALLBACK_CONTEXT rejection New runtime tests cover: - OpenAI-style Azure Foundry - Anthropic-style Azure Foundry with /v1 stripping - Missing base_url / API key raising AuthError Rationale: Microsoft confirms there's no pure-API-key endpoint to list Azure deployments (that requires ARM management auth). The v1 Azure OpenAI endpoint does expose /models with the resource's available model catalog, which is good enough for picker prefill in the common case. Users on private/gated endpoints fall through to manual entry.
2026-04-25 18:38:38 -07:00
"""Tests for hermes_cli.azure_detect — transport & model auto-detection."""
from __future__ import annotations
import json
from unittest.mock import MagicMock, patch
import pytest
from hermes_cli import azure_detect
# ----------------------------------------------------------------------
# Helpers
# ----------------------------------------------------------------------
class _FakeHTTPResponse:
"""Minimal stand-in for urllib.request.urlopen's context manager."""
def __init__(self, status: int, body: bytes):
self.status = status
self._body = body
def __enter__(self):
return self
def __exit__(self, exc_type, exc, tb):
return False
def read(self) -> bytes:
return self._body
def _openai_models_body(*ids: str) -> bytes:
return json.dumps({
"object": "list",
"data": [{"id": i, "object": "model"} for i in ids],
}).encode()
def _anthropic_error_body(msg: str = "model not found") -> bytes:
return json.dumps({
"type": "error",
"error": {"type": "invalid_request_error", "message": msg},
}).encode()
# ----------------------------------------------------------------------
# _looks_like_anthropic_path
# ----------------------------------------------------------------------
@pytest.mark.parametrize("url, expected", [
("https://foo.services.ai.azure.com/anthropic", True),
("https://foo.services.ai.azure.com/anthropic/", True),
("https://foo.services.ai.azure.com/anthropic/v1", True),
("https://foo.openai.azure.com/openai/v1", False),
("https://foo.openai.azure.com/", False),
("https://openrouter.ai/api/v1", False),
])
def test_looks_like_anthropic_path(url, expected):
assert azure_detect._looks_like_anthropic_path(url) is expected
# ----------------------------------------------------------------------
# _extract_model_ids
# ----------------------------------------------------------------------
def test_extract_model_ids_openai_shape():
body = {
"object": "list",
"data": [
{"id": "gpt-4.1-mini", "object": "model"},
{"id": "claude-sonnet-4-6", "object": "model"},
],
}
assert azure_detect._extract_model_ids(body) == ["gpt-4.1-mini", "claude-sonnet-4-6"]
def test_extract_model_ids_bad_shape_returns_empty():
assert azure_detect._extract_model_ids({}) == []
assert azure_detect._extract_model_ids({"data": "not-a-list"}) == []
assert azure_detect._extract_model_ids({"data": [{"no-id": True}]}) == []
# ----------------------------------------------------------------------
# detect() integration
# ----------------------------------------------------------------------
def test_detect_anthropic_path_wins_without_http():
"""URL path sniff short-circuits — no HTTP call happens."""
with patch.object(azure_detect, "_http_get_json") as fake_get, \
patch.object(azure_detect, "_probe_anthropic_messages") as fake_probe:
result = azure_detect.detect(
"https://foo.services.ai.azure.com/anthropic", "key-abc",
)
assert result.api_mode == "anthropic_messages"
assert result.is_anthropic is True
assert "path" in result.reason.lower()
fake_get.assert_not_called()
fake_probe.assert_not_called()
def test_detect_openai_models_probe_success():
"""/models probe returning a model list → chat_completions."""
def _fake_get(url, api_key, timeout=6.0):
assert "key-abc" == api_key
return 200, json.loads(_openai_models_body("gpt-5.4", "claude-opus-4-6"))
with patch.object(azure_detect, "_http_get_json", side_effect=_fake_get):
result = azure_detect.detect(
"https://my.openai.azure.com/openai/v1", "key-abc",
)
assert result.api_mode == "chat_completions"
assert result.models_probe_ok is True
assert result.models == ["gpt-5.4", "claude-opus-4-6"]
assert "/models" in result.reason
def test_detect_openai_models_probe_empty_list_still_counts():
"""Endpoint returned OpenAI shape but no models → still chat_completions."""
def _fake_get(url, api_key, timeout=6.0):
return 200, {"object": "list", "data": []}
with patch.object(azure_detect, "_http_get_json", side_effect=_fake_get):
result = azure_detect.detect(
"https://my.openai.azure.com/openai/v1", "key-abc",
)
assert result.api_mode == "chat_completions"
assert result.models == []
assert result.models_probe_ok is True
def test_detect_falls_back_to_anthropic_probe():
"""/models fails but Anthropic Messages probe succeeds."""
def _fake_get(url, api_key, timeout=6.0):
return 401, None # /models forbidden
with patch.object(azure_detect, "_http_get_json", side_effect=_fake_get), \
patch.object(azure_detect, "_probe_anthropic_messages", return_value=True):
result = azure_detect.detect(
"https://my.services.ai.azure.com/v1", "key-abc",
)
assert result.api_mode == "anthropic_messages"
assert result.is_anthropic is True
def test_detect_all_probes_fail_returns_none():
"""Every probe fails → api_mode is None and caller falls back to manual."""
with patch.object(azure_detect, "_http_get_json", return_value=(500, None)), \
patch.object(azure_detect, "_probe_anthropic_messages", return_value=False):
result = azure_detect.detect(
"https://some-private.example.com/", "key-abc",
)
assert result.api_mode is None
assert result.models == []
assert "manual" in result.reason.lower()
# ----------------------------------------------------------------------
# _probe_openai_models URL list (Azure vs v1 api-version)
# ----------------------------------------------------------------------
def test_probe_openai_models_tries_multiple_api_versions():
"""First call (no api-version) fails, api-version fallback succeeds."""
calls = []
def _fake_get(url, api_key, timeout=6.0):
calls.append(url)
if "api-version" not in url:
return 404, None
return 200, json.loads(_openai_models_body("gpt-4.1"))
with patch.object(azure_detect, "_http_get_json", side_effect=_fake_get):
ok, models = azure_detect._probe_openai_models(
"https://my.openai.azure.com/openai/v1", "k",
)
assert ok is True
assert models == ["gpt-4.1"]
# Should have tried without api-version first, then with at least one
assert any("api-version" not in u for u in calls)
assert any("api-version" in u for u in calls)
# ----------------------------------------------------------------------
# _http_get_json error handling
# ----------------------------------------------------------------------
def test_http_get_json_on_urlerror_returns_zero_none():
"""Network failure returns (0, None), never raises."""
import urllib.error
with patch("hermes_cli.azure_detect.urllib_request.urlopen",
side_effect=urllib.error.URLError("dns fail")):
status, body = azure_detect._http_get_json("https://bad.example/", "k")
assert status == 0
assert body is None
def test_http_get_json_on_http_error_returns_code_none():
"""HTTP 4xx/5xx returns (code, None)."""
import urllib.error
err = urllib.error.HTTPError("https://x/", 403, "Forbidden", {}, None)
with patch("hermes_cli.azure_detect.urllib_request.urlopen", side_effect=err):
status, body = azure_detect._http_get_json("https://x/", "k")
assert status == 403
assert body is None
# ----------------------------------------------------------------------
# lookup_context_length
# ----------------------------------------------------------------------
def test_lookup_context_length_returns_known():
"""When model_metadata returns a non-fallback value, we pass it through."""
fake = MagicMock(return_value=400000)
with patch("agent.model_metadata.get_model_context_length", fake), \
patch("agent.model_metadata.DEFAULT_FALLBACK_CONTEXT", 128000):
n = azure_detect.lookup_context_length(
"gpt-5.4", "https://x.openai.azure.com/openai/v1", "k",
)
assert n == 400000
def test_lookup_context_length_returns_none_on_fallback():
"""When resolver falls through to DEFAULT_FALLBACK_CONTEXT, we return None."""
with patch("agent.model_metadata.get_model_context_length", return_value=128000), \
patch("agent.model_metadata.DEFAULT_FALLBACK_CONTEXT", 128000):
n = azure_detect.lookup_context_length(
"totally-unknown-model", "https://x.openai.azure.com/openai/v1", "k",
)
assert n is None
def test_lookup_context_length_swallows_exceptions():
"""Resolver raising must not crash the wizard."""
with patch("agent.model_metadata.get_model_context_length",
side_effect=RuntimeError("boom")):
assert azure_detect.lookup_context_length("m", "https://x/", "k") is None