Add benchmark results for x-ai/grok-code-fast-1 (concurrency 20) and in-progress checkpoints

[mentatbot]

This PR runs the LoCoDiff-bench step 2 benchmark for model x-ai/grok-code-fast-1 at concurrency 20 against the existing prompt set (locodiff-250425), and commits in-progress checkpoints of generated results for traceability and to avoid data loss mid-run.

What’s included:

• New result artifacts under locodiff-250425/results/*/x-ai_grok-code-fast-1/<timestamp>/:
  • metadata.json with per-case metrics (success flag, api_error, costs, token stats, generation_id)
  • extracted_output.txt, output.diff, and raw_response.txt
• Multiple incremental checkpoints (checkpoints 1–6) as the run progresses, so partial results are preserved
• No documentation regeneration per instruction (step 3 not executed)

Run configuration:

• Model: x-ai/grok-code-fast-1
• Concurrency: 20
• Benchmark dir: locodiff-250425
• Script: benchmark_pipeline/2_run_benchmark.py
• Step 3 intentionally not run

Notes:

• Output mismatches are recorded as failures (by design); these remain part of the benchmark truth set.
• Transient API errors are captured in metadata as api_error: true when applicable and will be re-run later at lower concurrency.
• This PR captures the current, in-progress state; additional results will follow in a subsequent PR or commits after the full run completes and API-error cases are retried.

Next steps:

• Let the full run complete at concurrency 20
• Re-run only API-error cases with lower concurrency (e.g. 1–2) to recover transient failures
• Post a summary PR with success rate, costs, and key metrics; optionally include comparisons to other models

Closes # (optional — add if there’s a tracking issue)

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