PHPMem v2.0.1

Version
1.6.45
Uptime
8 days 3 hours 33 minutes 55 seconds

Memory

Total
512MB
Used
7,68MB (1.5%)
Free
504,32MB

Keys

Current
5 910
Total (since start)
11 098
Evictions
0
Reclaimed
326
Expired Unfetched
0
Evicted Unfetched
0

Connections

Current
3 / 1 024 max
Total
76 689
Rejected
0
llm:8e9e6d04940df7e05964eeab95985a744de6657c2977211ca20bacbccd1f91af
TTL 5 days 18 hours 6 minutes 55 seconds Size 1,22KB Export
Edit
{
    "action": "tool_call",
    "reasoning": "I've reviewed the evidence and found several interesting patterns, but I need to explore one more angle that could be truly counterintuitive: the relationship between LLM model choice and actual cost efficiency. The data shows claude-sonnet-4-5 has 111 usage instances with much higher total costs ($4.97) compared to claude-haiku-4-5 (also 111 instances, $0.14), but I want to see if there's a counterintuitive pattern in cost-per-token or effectiveness that would surprise someone. Let me check the cost efficiency metrics across models.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT model_name, SUM(calls) as total_calls, SUM(input_tokens) as total_input, SUM(output_tokens) as total_output, SUM(cost_usd) as total_cost, SUM(cost_usd) / NULLIF(SUM(input_tokens + output_tokens), 0) as cost_per_token, SUM(output_tokens) / NULLIF(SUM(calls), 0) as avg_output_per_call FROM raw.analysis_run_llm_usage GROUP BY model_name ORDER BY total_calls DESC",
        "purpose": "Calculate cost efficiency metrics per model to identify counterintuitive patterns in LLM usage economics",
        "source": "raw"
    }
}