managing-together-ai

name	managing-together-ai
description	Use when working with Together Ai — together AI inference platform management covering models, fine-tuning jobs, usage analytics, and billing. Use when monitoring API usage and costs, analyzing model performance, reviewing fine-tuning status, checking available models, or troubleshooting Together AI API issues.
connection_type	together-ai
preload	false

Together AI Management Skill

Manage and analyze Together AI platform resources including models, fine-tuning, and usage.

API Conventions

Authentication

All API calls use Bearer API key, injected automatically.

Base URL

https://api.together.xyz/v1

Core Helper Function

#!/bin/bash

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

    if [ -n "$data" ]; then
        curl -s -X "$method" \
            -H "Authorization: Bearer $TOGETHER_API_KEY" \
            -H "Content-Type: application/json" \
            "https://api.together.xyz/v1${endpoint}" \
            -d "$data"
    else
        curl -s -X "$method" \
            -H "Authorization: Bearer $TOGETHER_API_KEY" \
            "https://api.together.xyz/v1${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 (chat) ==="
together_api GET "/models" \
    | jq -r '.[] | select(.type == "chat") | "\(.id)\t\(.context_length // "N/A")\t\(.pricing.input // "N/A")"' \
    | head -20

echo ""
echo "=== Available Models (language) ==="
together_api GET "/models" \
    | jq -r '.[] | select(.type == "language") | .id' | head -10

echo ""
echo "=== Fine-Tuning Jobs ==="
together_api GET "/fine-tunes" \
    | jq -r '.data[] | "\(.id[0:16])\t\(.model)\t\(.status)\t\(.created_at[0:10])"' \
    | column -t | head -10

echo ""
echo "=== Uploaded Files ==="
together_api GET "/files" \
    | jq -r '.data[] | "\(.id[0:16])\t\(.filename[0:30])\t\(.purpose)\t\(.bytes) bytes"' \
    | column -t | head -10

Phase 2: Analysis

Usage & Billing

#!/bin/bash
echo "=== Account Balance ==="
together_api GET "/billing/balance" \
    | jq '{balance: .balance, currency: .currency}'

echo ""
echo "=== Model Count by Type ==="
together_api GET "/models" \
    | jq -r '[.[] | .type] | group_by(.) | map({(.[0]): length}) | add'

echo ""
echo "=== API Health Check ==="
RESULT=$(together_api POST "/chat/completions" '{"model": "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo", "messages": [{"role": "user", "content": "test"}], "max_tokens": 1}')
echo "$RESULT" | jq '{model: .model, usage: .usage}' 2>/dev/null || echo "Error: $(echo $RESULT | jq -r '.error.message // "unknown"')"

Fine-Tuning Health

#!/bin/bash
echo "=== Fine-Tuning Status Summary ==="
together_api GET "/fine-tunes" \
    | jq -r '.data[] | .status' | sort | uniq -c | sort -rn

echo ""
echo "=== Recent Fine-Tuning Jobs ==="
together_api GET "/fine-tunes" \
    | jq -r '.data[] | "\(.id[0:16])\t\(.model)\t\(.status)\t\(.training_type // "full")\t\(.n_epochs) epochs"' \
    | column -t | head -10

echo ""
echo "=== Custom Models ==="
together_api GET "/models" \
    | jq -r '.[] | select(.type == "custom") | "\(.id)\t\(.created_at[0:10] // "N/A")"' | head -10

Output Format

=== Together AI Account ===
Balance: $<amount>

--- Models ---
Chat: <n>  Language: <n>  Embedding: <n>  Image: <n>

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

--- API Health ---
Status: <healthy|degraded>

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

Common Pitfalls

• Model IDs: Use full organization/model format (e.g., meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo)
• Rate limits: Vary by plan; check response headers for current limits
• OpenAI-compatible: API follows OpenAI format for chat/completions endpoints
• Fine-tuning: Supports LoRA and full fine-tuning; specify in job config