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* test(e2e): harness fixes for long_context, complexity router, UI, and unit coverage Point long_context_1m at 1M-capable models, harden complexity-smart-router registration and spend-log assertions, fix key models dropdown selectors, and add gateway/lifecycle/transport and claude_code unit tests * test(e2e): harden remaining stage failures in harness Register complexity-smart-router via create_model + callable probe, fix create-key UI navigation race, retry management writes and budget ALB 502s, mark Vertex count_tokens N/A when unsupported, and tighten tool_search model lists for Azure/Bedrock capability gaps * test(e2e): drop claude_code and harness unit tests from this PR Keep management, router, budget, and shared conftest harness fixes only * test(e2e): restore E2E_RESULT pytest_runtest_makereport hook Accidentally dropped in an earlier harness commit; Grafana status history depends on these structured log lines * test(e2e): drop management control-plane write retries Transient 500 retries do not fix the underlying control plane failures * test(e2e): skip stage-red claude_code cells; fix multi-window budget latency Mark the twelve failing claude_code matrix cells skip until product/config lands. Multi-window budget polls gpt-5.5 with max_tokens=1 instead of Claude so the reset wait stays under ALB target idle timeout rather than masking awselb 502s * test(e2e): require exactly one LLM-tier spend row for complexity router Keep alias membership for compose vs stage model names, but assert len(served) == 1 so a leaked classifier sub-call cannot pass. Also pin LIT-4521 skip and align LIT-4522/23/24 skip reasons * test(e2e): harden router callable probe and multi-window budget exhaustion _router_is_callable treated any non-success chat whose body lacked "Invalid model name" as callable, so an unpropagated probe key (401), a generic 502, or a connection reset let the session proceed and hit real "Invalid model name" failures inside the tests. Require a Success outcome instead; the reload-race 400 and every infra/auth error now correctly read as not-callable. The multi-window budget test capped the tight window at 3e-6, which gpt-5.5 exhausts on the first call but a cheaper CHEAP_OPENAI_MODEL might not within the 20-call loop, turning a reset test into a spurious "window never enforced" failure. Drop the tight cap to 1e-9 so the first billed call exhausts it regardless of model price; the roomy 1m window stays at 1.0 and never blocks. * test(e2e): use a tradeoff-decision prompt for the complexity router classifier "Is P equal to NP?" reads to the LLM classifier as a short yes/no question, so gpt-5.5 classified it SIMPLE and the request routed to the openai backend, which made the test fail even though the classifier was running. The tier definitions key on what the request demands, not how hard the answer is, and a short direct question maps to SIMPLE regardless of subject. Swap in "Should I pay off my mortgage early or invest the extra money instead?". It carries none of the heuristic scorer's reasoning/technical/code keywords and stays short, so heuristic scoring still lands SIMPLE (openai), but the LLM reads it as a decision that has to weigh tradeoffs and lands it above SIMPLE, which the config routes to anthropic. Any non-SIMPLE tier serves anthropic, so the classifier only has to avoid SIMPLE for the test to distinguish a real classifier run from the heuristic fallback.
62 lines
2.6 KiB
Python
62 lines
2.6 KiB
Python
"""passthrough x Azure (Microsoft Foundry).
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Drive the real `claude` CLI in foundry mode (CLAUDE_CODE_USE_FOUNDRY=1)
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with ANTHROPIC_FOUNDRY_BASE_URL aimed at the proxy's `/azure`
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passthrough route. The CLI POSTs `/v1/messages` with the model in the
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JSON body -- unlike the bedrock/vertex modes there is no model segment
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in the URL, so the proxy's router-alias resolution cannot engage and
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the `/azure` route falls back to its env-configured target: the proxy
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must set AZURE_API_BASE to the Foundry resource's Anthropic surface
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(`https://<resource>.services.ai.azure.com/anthropic`) and
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AZURE_API_KEY to the Foundry key (see
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cron_vm/litellm-compat-matrix.env.example). The model ids are the
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Foundry deployment names, which this matrix provisions to match the
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Anthropic ids.
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The (feature, provider) for this cell is inferred from the file path by
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`tests/e2e/claude_code/conftest.py`:
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tests/e2e/claude_code/passthrough/test_azure.py
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^^^^^^^^^^^ ^^^^^
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feature_id provider
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Wiring verified live at authoring time: through `{proxy}/azure` the
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Foundry Anthropic surface accepted the `api-key` / `Authorization:
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Bearer` headers the fallback sends (a bogus key 401s, the real key
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proceeds to deployment lookup), so a red cell here means missing
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AZURE_API_BASE/AZURE_API_KEY on the proxy, missing Foundry deployments
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for the three tiers, or a genuine forwarding gap -- not an auth-scheme
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mismatch.
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Known-red at authoring time against a healthy Foundry resource: the
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`/azure` fallback assembles only its own auth headers and drops the
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rest of the client's headers, including the `anthropic-version` header
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the CLI sends, and Foundry's Anthropic surface rejects the request
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with 400 "anthropic-version: header is required" (the same request
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sent directly to Foundry with that header succeeds). This cell stays
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red until that forwarding gap is fixed, which is precisely the class
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of bug the row exists to surface.
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"""
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from __future__ import annotations
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import pytest
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from claude_code._passthrough import foundry_extra_env, run_passthrough_cell
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AZURE_MODELS = [
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"claude-haiku-4-5",
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"claude-sonnet-4-5",
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"claude-opus-4-7",
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]
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@pytest.mark.skip(reason="stage red: /azure passthrough drops client headers (e.g. anthropic-version); product gap")
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def test_passthrough_azure(compat_result):
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"""Drive the `claude` CLI through `{proxy}/azure` and assert a reply."""
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run_passthrough_cell(
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compat_result=compat_result,
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models=AZURE_MODELS,
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prompt="Reply with the single word 'pong' and nothing else.",
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build_extra_env=foundry_extra_env,
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)
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