Tune LLM API infra, add benchmark/eval scripts, document in docs/AGENTS.md - #4
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Tune LLM API infra, add benchmark/eval scripts, document in docs/AGENTS.md#4elimelt wants to merge 1 commit into
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…TS.md Caddyfile (llm.elimelt.com): - Raise rate limit 20 -> 100 req/min per IP - Exempt internal origins (*.elimelt.com, localhost:5173) from rate limiting - Restructure CORS/preflight and blocked-endpoint handling into handle blocks docker-compose.yml (ollama): - OLLAMA_ORIGINS=* (Ollama's own Origin check returned 403; policy is enforced by Caddy at the edge instead) - OLLAMA_NUM_PARALLEL=4 (concurrency benchmarks plateau at ~4 on CPU) - OLLAMA_MAX_QUEUE=20 for backpressure - Memory limit 50G (26B models OOM-killed the container at 6G) infra/scripts: - bench_ollama.py: TTFT/decode/prompt benchmark; distinguishes first token (incl. thinking) from first content, runs thinking models in both modes - bench_ollama_concurrency.py, bench_ollama_prefill.py - eval_tts_rewrite.py, eval_tts_prompts.py: quality evals for the notes -> TTS rewrite task docs/AGENTS.md: operational notes (model lineup rationale, thinking-model gotchas, benchmark results, CORS/rate-limit behavior) Model lineup changes (server-side, recorded here for history): pulled gemma4:e4b, gemma4:26b, gpt-oss:20b, qwen2.5-coder:7b; removed gemma3:27b and llama3.2:3b as Pareto-dominated.
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Summary
Infrastructure tuning, benchmarking tooling, and operational docs for the LLM API at
llm.elimelt.com(Ollama behind Caddy).Changes
Caddyfile
https://*.elimelt.com,http://localhost:5173) exempted from rate limitinghandleblocksdocker-compose.yml (ollama)
OLLAMA_ORIGINS=*— Ollama's built-in Origin validation was returning 403; origin policy is enforced by Caddy at the edge insteadOLLAMA_NUM_PARALLEL=4— concurrency benchmarks showed CPU-bound throughput plateaus at ~4OLLAMA_MAX_QUEUE=20— backpressure instead of unbounded queueingNew scripts (
infra/scripts/)bench_ollama.py— TTFT/decode/prompt benchmark; distinguishes first token (incl. thinking) from first content, and runs thinking-capable models (gemma4, gpt-oss) in both modesbench_ollama_concurrency.py,bench_ollama_prefill.pyeval_tts_rewrite.py,eval_tts_prompts.py— quality evals for the notes→TTS rewrite taskDocs
docs/AGENTS.md— model lineup rationale, thinking-model gotchas, benchmark results, CORS/rate-limit behaviorServer-side model changes (not in repo, recorded for history)
Pulled
gemma4:e4b,gemma4:26b,gpt-oss:20b,qwen2.5-coder:7b; removedgemma3:27bandllama3.2:3bas Pareto-dominated. Final lineup benchmarks (warm, medians of 3):gemma2:2bgemma4:e4b(think: false)gemma4:26b(think: false)gpt-oss:20b(think: "low")qwen2.5-coder:7bVerification
https://llm.elimelt.com/v1/chat/completionslocalhost:5173and*.elimelt.com