managing-banana-dev

name	managing-banana-dev
description	Use when working with Banana Dev — banana.dev ML inference platform management covering model inventory, deployment status, API call history, GPU allocation, scaling configuration, build logs, and latency metrics. Use for comprehensive Banana.dev model deployment assessment and inference performance analysis.
connection_type	banana-dev
preload	false

Banana.dev Management

Analyze Banana.dev model deployments, inference calls, GPU usage, and build status.

Phase 1: Discovery

#!/bin/bash
TOKEN="${BANANA_API_KEY}"
BASE="https://api.banana.dev/v1"
AUTH=(-H "Authorization: Bearer ${TOKEN}" -H "Content-Type: application/json")

echo "=== Models Inventory ==="
curl -s "${BASE}/models" "${AUTH[@]}" \
  | jq -r '.models[] | "\(.name)\t\(.model_key[0:12])\t\(.status)\t\(.gpu_type)\t\(.created_at[0:10])"' \
  | column -t | head -20

echo ""
echo "=== Deployments ==="
curl -s "${BASE}/deployments" "${AUTH[@]}" \
  | jq -r '.deployments[] | "\(.model_name)\t\(.version[0:8])\t\(.status)\t\(.gpu)\t\(.replicas)\t\(.updated_at[0:19])"' \
  | column -t | head -20

echo ""
echo "=== GPU Allocation ==="
curl -s "${BASE}/models" "${AUTH[@]}" \
  | jq -r '.models[] | "\(.name)\t\(.gpu_type)\t\(.min_replicas)-\(.max_replicas) replicas\t\(.cold_start_timeout)s cold start"' \
  | column -t | head -15

echo ""
echo "=== Build History ==="
curl -s "${BASE}/builds?limit=10" "${AUTH[@]}" \
  | jq -r '.builds[] | "\(.model_name)\t\(.build_id[0:8])\t\(.status)\t\(.duration_s // "N/A")s\t\(.created_at[0:19])"' \
  | column -t | head -15

Phase 2: Analysis

#!/bin/bash
TOKEN="${BANANA_API_KEY}"
BASE="https://api.banana.dev/v1"
AUTH=(-H "Authorization: Bearer ${TOKEN}" -H "Content-Type: application/json")

echo "=== Inference Call History ==="
curl -s "${BASE}/calls?limit=20" "${AUTH[@]}" \
  | jq -r '.calls[] | "\(.model_name)\t\(.call_id[0:8])\t\(.status)\t\(.duration_ms)ms\t\(.created_at[0:19])"' \
  | column -t | head -20

echo ""
echo "=== Call Status Summary ==="
curl -s "${BASE}/calls?limit=100" "${AUTH[@]}" \
  | jq -r '.calls | group_by(.status) | .[] | "\(.[0].status): \(length) calls"'

echo ""
echo "=== Latency Metrics ==="
curl -s "${BASE}/calls?limit=50" "${AUTH[@]}" \
  | jq '[.calls[] | select(.duration_ms != null) | .duration_ms] | if length > 0 then {avg_ms: (add/length | round), min_ms: min, max_ms: max, count: length} else {status: "no data"} end'

echo ""
echo "=== Scaling Events ==="
curl -s "${BASE}/scaling-events?limit=10" "${AUTH[@]}" \
  | jq -r '.events[]? | "\(.model_name)\t\(.from_replicas)->\(.to_replicas)\t\(.reason)\t\(.created_at[0:19])"' \
  | column -t | head -10

echo 
 
curl -s   \
  | jq -r  \
  | column -t |  -10

 
 
 
 

Output Format

BANANA.DEV ANALYSIS
=====================
Model            GPU      Replicas   Status    Avg Latency  Calls (24h)
──────────────────────────────────────────────────────────────────────────
sd-inference     A100     1-3        active    1,250ms      340
whisper-large    T4       1-2        active    3,400ms      120
llm-server       A100     2-5        active    850ms        890

Models: 3 active | GPUs: A100(2) T4(1) | Builds: 5 (4 ok, 1 failed)
Calls (24h): 1,350 total (1,320 success, 30 failed)
Avg Latency: 1,833ms | Cold Starts: 12

Safety Rules

• Read-only: Only use GET endpoints against the Banana.dev API
• Never deploy, scale, or delete models without confirmation
• API keys: Never output API key or model key values
• Rate limits: Respect API rate limits to avoid throttling

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative