Managing Fireworks AI

Fireworks AI Management Skill

Manage and analyze Fireworks AI platform resources including models, deployments, and fine-tuning.

API Conventions

Authentication

All API calls use Bearer API key, injected automatically.

Base URL

https://api.fireworks.ai/inference/v1 (inference) and https://api.fireworks.ai/v1 (management)

Core Helper Function

#!/bin/bash

fireworks_api() {
    local method="$1"
    local endpoint="$2"
    local data="${3:-}"

    if [ -n "$data" ]; then
        curl -s -X "$method" \
            -H "Authorization: Bearer $FIREWORKS_API_KEY" \
            -H "Content-Type: application/json" \
            "https://api.fireworks.ai${endpoint}" \
            -d "$data"
    else
        curl -s -X "$method" \
            -H "Authorization: Bearer $FIREWORKS_API_KEY" \
            "https://api.fireworks.ai${endpoint}"
    fi
}

Output Rules

• Target ≤50 lines per script output
• Use jq to extract only needed fields
• Never dump full API responses

Phase 1: Discovery

#!/bin/bash
echo "=== Available Models ==="
fireworks_api GET "/inference/v1/models" \
    | jq -r '.data[] | "\(.id)\t\(.context_length // "N/A")"' \
    | head -25

echo ""
echo "=== Account Info ==="
fireworks_api GET "/v1/accounts/me" \
    | jq '{id: .id, name: .name, tier: .tier}'

echo ""
echo "=== Fine-Tuning Jobs ==="
fireworks_api GET "/v1/accounts/me/fineTuningJobs" \
    | jq -r '.jobs[] | "\(.id[0:16])\t\(.model[0:30])\t\(.status)\t\(.createdAt[0:10])"' \
    | column -t | head -10

echo ""
echo "=== Deployments ==="
fireworks_api GET "/v1/accounts/me/deployedModels" \
    | jq -r '.deployedModels[] | "\(.id[0:16])\t\(.model[0:30])\t\(.state)\t\(.createdAt[0:10])"' \
    | head -10

Phase 2: Analysis

Usage & Health

#!/bin/bash
echo "=== API Health Check ==="
RESULT=$(fireworks_api POST "/inference/v1/chat/completions" '{"model": "accounts/fireworks/models/llama-v3p1-8b-instruct", "messages": [{"role": "user", "content": "test"}], "max_tokens": 1}')
echo "$RESULT" | jq '{model: .model, usage: .usage}' 2>/dev/null || echo "Error: $(echo $RESULT | jq -r '.error.message // "unknown"')"

echo ""
echo "=== Model Categories ==="
fireworks_api GET "/inference/v1/models" \
    | jq -r '[.data[] | .owned_by // "fireworks"] | group_by(.) | map({(.[0]): length}) | add'

Fine-Tuning & Deployment Health

#!/bin/bash
echo "=== Fine-Tuning Status Summary ==="
fireworks_api GET "/v1/accounts/me/fineTuningJobs" \
    | jq -r '.jobs[] | .status' | sort | uniq -c | sort -rn

echo ""
echo "=== Active Deployments ==="
fireworks_api GET "/v1/accounts/me/deployedModels" \
    | jq -r '.deployedModels[] | select(.state == "DEPLOYED") | "\(.id[0:16])\t\(.model[0:30])\t\(.state)\t\(.replicas // 1) replicas"' \
    | head -10

echo ""
echo "=== Custom Models ==="
fireworks_api GET "/v1/accounts/me/models" \
    | jq -r '.models[] | "\(.id[0:20])\t\(.displayName // .id)\t\(.createdAt[0:10])"' \
    | head -10

Output Format

=== Fireworks AI Account: <name> | Tier: <tier> ===

--- Models ---
Available: <n>  Custom: <n>

--- Fine-Tuning ---
Active: <n>  Completed: <n>  Failed: <n>

--- Deployments ---
Active: <n>  Total Replicas: <n>

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

Common Pitfalls

• Model IDs: Use full path format (e.g., accounts/fireworks/models/llama-v3p1-8b-instruct)
• Two API bases: Inference endpoints use /inference/v1, management uses /v1
• OpenAI-compatible: Inference API follows OpenAI chat/completions format
• Rate limits: Vary by tier; check response headers