together-deploy-integration
Together AI deploy integration for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together deploy integration".
Best use case
together-deploy-integration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Together AI deploy integration for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together deploy integration".
Teams using together-deploy-integration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/together-deploy-integration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How together-deploy-integration Compares
| Feature / Agent | together-deploy-integration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Together AI deploy integration for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together deploy integration".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Together AI Deploy Integration
## Overview
Deploy a containerized Together AI inference integration service with Docker. This skill covers building a production image that connects to Together's OpenAI-compatible API for running completions, embeddings, and image generation across 100+ open-source models. Includes environment configuration for model selection and batch processing, health checks that verify API key validity and model availability, and rolling update strategies for zero-downtime deployments serving real-time inference requests.
## Docker Configuration
```dockerfile
FROM python:3.12-slim AS builder
WORKDIR /app
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
FROM python:3.12-slim
RUN groupadd -r app && useradd -r -g app app
WORKDIR /app
COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages
COPY --from=builder /usr/local/bin /usr/local/bin
COPY src/ ./src/
USER app
EXPOSE 8000
HEALTHCHECK --interval=30s --timeout=5s --retries=3 \
CMD curl -f http://localhost:8000/health || exit 1
CMD ["python", "src/server.py"]
```
## Environment Variables
```bash
export TOGETHER_API_KEY="tog_xxxxxxxxxxxx"
export TOGETHER_BASE_URL="https://api.together.xyz/v1"
export TOGETHER_DEFAULT_MODEL="meta-llama/Llama-3.1-8B-Instruct"
export TOGETHER_MAX_TOKENS="2048"
export LOG_LEVEL="info"
export PORT="8000"
```
## Health Check Endpoint
```typescript
import express from 'express';
const app = express();
app.get('/health', async (req, res) => {
try {
const response = await fetch(`${process.env.TOGETHER_BASE_URL}/models`, {
headers: { 'Authorization': `Bearer ${process.env.TOGETHER_API_KEY}` },
});
if (!response.ok) throw new Error(`Together API returned ${response.status}`);
res.json({ status: 'healthy', service: 'together-integration', model: process.env.TOGETHER_DEFAULT_MODEL, timestamp: new Date().toISOString() });
} catch (error) {
res.status(503).json({ status: 'unhealthy', error: (error as Error).message });
}
});
```
## Deployment Steps
### Step 1: Build
```bash
docker build -t together-integration:latest .
```
### Step 2: Run
```bash
docker run -d --name together-integration \
-p 8000:8000 \
-e TOGETHER_API_KEY -e TOGETHER_BASE_URL -e TOGETHER_DEFAULT_MODEL \
together-integration:latest
```
### Step 3: Verify
```bash
curl -s http://localhost:8000/health | jq .
```
### Step 4: Rolling Update
```bash
docker build -t together-integration:v2 . && \
docker stop together-integration && \
docker rm together-integration && \
docker run -d --name together-integration -p 8000:8000 \
-e TOGETHER_API_KEY -e TOGETHER_BASE_URL -e TOGETHER_DEFAULT_MODEL \
together-integration:v2
```
## Error Handling
| Issue | Cause | Fix |
|-------|-------|-----|
| `401 Unauthorized` | Invalid API key | Regenerate key at api.together.xyz/settings |
| `Model not found` | Wrong model ID string | List models with `GET /v1/models` or check docs |
| `429 Rate Limited` | Exceeding requests per minute | Implement backoff; use batch inference for 50% cost savings |
| `500 Server Error` | Model overloaded or unavailable | Retry with exponential backoff; try alternate model |
| Slow inference | Model cold start on first request | Use a smaller model or keep-alive with periodic requests |
## Resources
- [Together AI Docs](https://docs.together.ai/)
- [API Reference](https://docs.together.ai/reference/chat-completions-1)
- [Model List](https://docs.together.ai/docs/inference-models)
## Next Steps
See `together-webhooks-events`.Related Skills
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