vllm - 💡(How to fix) Fix Analyze middleware traces: OWUI sampling profile comparison [1 comments, 1 participants]

Context

4 OWUI sampling profiles are being tested via Roo scheduler tasks on Qwen3.5-35B-A3B (AWQ 4-bit, GPUs 0,1):

Data source

Middleware logs at /logs/chat_completions.jsonl in the vLLM container (~3500 entries, 6MB).

Each entry contains: timestamp, model, prompt_tokens, completion_tokens, ttft_s, e2e_s, temperature, presence_penalty, top_p, top_k, repetition_penalty, tools_count, response_text, reasoning_text, finish_reason, system_prompt_length, last_user_message.

Analysis tasks

1. Extract & classify requests by sampling profile (group by temp+pp+top_p+top_k signature)
2. Repetition metrics per profile:
   • 4-gram / 8-gram repetition rate
   • Type-Token Ratio (TTR)
   • Repeated line ratio
3. Performance metrics per profile:
   • Decode speed (completion_tokens / e2e_s)
   • TTFT distribution
   • Token count distribution
4. Quality assessment (manual sample):
   • Coherence and relevance of responses
   • Language mixing (Chinese in French responses)
   • Code quality for coding tasks
5. Recommendation: which profile(s) to keep for production Roo usage

How to extract logs

docker exec myia_vllm-medium-qwen35-moe bash -c 'cat /logs/chat_completions.jsonl' > middleware_logs.jsonl

Expected output

A report with per-profile metrics and a recommendation for the default Roo sampling config.

🤖 Generated with Claude Code