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Evidence case: self-hosted OpenAI-compatible server, client vs server surface (Discussion #26) - #39

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What & why

Adds a runnable evidence case for known-limits section 6, as offered in Discussion #26. It pins one live capture (vLLM 0.27.1 on a T4): the same request three times, one of them a stream without stream_options. Client surface: 70 / 32 on two calls, one call with no usage. Server surface: 3 requests, 105 / 48, and 64 prompt tokens read from the prefix cache. Gap: +35 / +16.

It also pins a second client-surface gap: vLLM sends prompt_tokens_details only with --enable-prompt-tokens-details (off by default), so the cache split is unreported, not 0. And one small refinement: with exactly one absent call the gap is that call's by elimination; with two or more it stays UNPROVABLE.

Evidence

python3 conformance/evidence/selfhosted-openai-compatible-reconcile/run_case.py

Expected: 12 PASS lines, then CONFORMANT. The raw files (full /metrics snapshots, the client's usage per call, the server log) are published unedited at qaisermehdi3-coder/qvunex@1094fd5, with sha256 in expected.json.

Conformance impact

New evidence case only (4 files). No spec, registry or adapter change. CI: a one-step addition to conformance.yml after the unknown-model-pricing case would run it; I left the workflow untouched.

AI-assisted: yes

The runner, the fixture extraction and the README were written with an AI assistant. I did the run live. Every fixture value was checked by script against the raw files, and each check in the runner fails when the rule it guards is removed (10 of 10).

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