Surface provider error bodies and stop one dead sampler losing all metrics

[dan-s-w]

Two failures that were harder to diagnose than they needed to be. Both surfaced while debugging AIEV-275.

1. API error bodies were discarded

raise_for_status() reports only the status line, so a rejected request surfaced as:

perplexity_finance_historical_lookup failed with error 400, message='Bad Request'

That's everything the harness told us. The actual reason was sitting in the response body the whole time — diagnosing it meant re-issuing the request by hand outside the harness.

Non-2xx responses now include the body, capped at 2000 chars. Same request, after this change:

400, message='Bad Request: {"error":{"message":"invalid request body: json:
unknown field \"max_tokens\"","type":"invalid_request","code":400,
"param":"max_tokens"}}', url='https://api.perplexity.ai/v1/agent'

An hour of probing becomes one line in the log. The GET/POST branches were also collapsed, since they only differed in json= vs params=.

2. One fully failed sampler destroyed the whole summary

write_metrics raised ValueError as soon as any sampler had zero successful rows. Six healthy samplers plus one dead one produced no scorecard at all — the healthy results were computed and then thrown away.

It now logs the dead sampler and skips it. If nothing succeeded anywhere, it warns and writes nothing rather than raising on an empty frame.

3. failed_count column

Failures are excluded from the accuracy denominator, so a sampler that errored on half the dataset currently looks identical to one that answered all of it. failed_count sits next to problem_count so that's visible at a glance.

The accuracy calculation itself is unchanged. Whether failures should count against a provider is a methodology question, and this PR deliberately doesn't answer it — it just stops the situation being invisible.

Tests

tests/test_eval_results_analyzer.py — no network. Covers the reported counts, the one-dead-sampler regression, and the everything-failed case.

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