PHPMem v2.0.1

Version
1.6.45
Uptime
15 days 12 hours 52 minutes 29 seconds

Memory

Total
512MB
Used
9,60MB (1.88%)
Free
502,40MB

Keys

Current
11 840
Total (since start)
35 066
Evictions
0
Reclaimed
733
Expired Unfetched
0
Evicted Unfetched
0

Connections

Current
13 / 1 024 max
Total
173 990
Rejected
0
llm:332f7dbbee06dc8788faa060d3e56f4ad6af21418ac6b2dada65c6b8d906946d
TTL 5 days 13 hours 10 minutes 59 seconds Size 1,39KB Export
Edit
{
    "action": "tool_call",
    "reasoning": "I can see from the evidence that the dataset has two distinct structures: 1) A daily summary section (rows with Day values like 'Thu', 'Fri', etc.) showing aggregate call metrics, and 2) Individual call records (rows with Call ID like 'CY-2847') showing per-call details. The unnamed columns (_unnamed_7, _unnamed_8, _unnamed_9) appear to contain the individual call data headers and values. To find correlations, I need to query the numeric columns and compute correlation coefficients. I'll focus on the individual call records which have measurable numeric fields like Duration (s) and Sentiment Score.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT CORR(CAST(REPLACE(_unnamed_7, ' ', '') AS DOUBLE), CAST(_unnamed_8 AS DOUBLE)) as duration_sentiment_corr, CORR(CASE WHEN _unnamed_9 = 'Positive' THEN 1 WHEN _unnamed_9 = 'Neutral' THEN 0 ELSE -1 END, CAST(_unnamed_8 AS DOUBLE)) as sentiment_label_score_corr, COUNT(*) as call_records FROM raw.callyeah_analytics_2026_07_23 WHERE Day LIKE 'CY-%' AND _unnamed_7 NOT IN ('Duration (s)', '') AND _unnamed_8 NOT IN ('Sentiment Score', '')",
        "purpose": "Calculate correlations between duration and sentiment score, and between sentiment label and sentiment score for individual call records",
        "source": "raw"
    }
}