LiteLLM Health Check Client

LiteLLM Health Check Client

A health check tool for testing all configured models on a LiteLLM proxy. Tests each model with completion/embedding requests and reports health status, errors, and response times.

Features

• YAML Config Support: Reads models from YAML config file OR fetches from proxy API
• Smart Mode Detection: Detects embedding vs chat models from config or model name
• Concurrent Testing: Tests all models concurrently using asyncio
• Containerized: Docker image for easy deployment
• Parallel Execution: Supports parallel execution for stress testing
• Configurable: Customizable timeouts (default 120s) and test prompts

Quick Start

As a Python Script

Option 1: Fetch models from proxy API

export LITELLM_BASE_URL="https://litellm.example.com"
export LITELLM_API_KEY="your-api-key"
python scripts/health_check/health_check_client.py

Option 2: Use YAML config file

export LITELLM_BASE_URL="https://litellm.example.com"
export LITELLM_API_KEY="your-api-key"
export LITELLM_MODELS_YAML="/path/to/config.yaml"
python scripts/health_check/health_check_client.py

Option 3: Use custom authentication header

export LITELLM_BASE_URL="https://litellm.example.com"
export LITELLM_API_KEY="your-api-key"
export LITELLM_CUSTOM_AUTH_HEADER="x-custom-auth-header"
python scripts/health_check/health_check_client.py

As a Docker Container

1. Build the Docker image:

docker build -f docker/Dockerfile.health_check -t litellm/litellm-health-check:latest .

2. Run a single health check:

docker run --rm \
  -e LITELLM_BASE_URL="https://litellm.example.com" \
  -e LITELLM_API_KEY="your-api-key" \
  litellm/litellm-health-check:latest

3. Run with custom authentication header:

docker run --rm \
  -e LITELLM_BASE_URL="https://litellm.example.com" \
  -e LITELLM_API_KEY="your-api-key" \
  -e LITELLM_CUSTOM_AUTH_HEADER="x-custom-auth-header" \
  litellm/litellm-health-check:latest

Parallel Execution (Stress Testing)

Run multiple health check containers in parallel:

PowerShell:

$env:LITELLM_BASE_URL="https://litellm.example.com"
$env:LITELLM_API_KEY="your-api-key"
.\scripts\health_check\run_parallel_health_checks.ps1 16

Bash/Shell:

export LITELLM_BASE_URL="https://litellm.example.com"
export LITELLM_API_KEY="your-api-key"
./scripts/health_check/run_parallel_health_checks.sh 16

With Custom Auth Header:

$env:LITELLM_BASE_URL="https://litellm.example.com"
$env:LITELLM_API_KEY="your-api-key"
$env:LITELLM_CUSTOM_AUTH_HEADER="x-custom-auth-header"
.\scripts\health_check\run_parallel_health_checks.ps1 16

With Custom Docker Image:

$env:LITELLM_BASE_URL="https://litellm.example.com"
$env:LITELLM_API_KEY="your-api-key"
$env:LITELLM_CUSTOM_AUTH_HEADER="x-custom-auth-header"
.\scripts\health_check\run_parallel_health_checks.ps1 -NumParallelJobs 16 -ImageName "your-registry/your-image:tag"

Bash with Custom Image:

export LITELLM_BASE_URL="https://litellm.example.com"
export LITELLM_API_KEY="your-api-key"
export LITELLM_CUSTOM_AUTH_HEADER="x-custom-auth-header"
./scripts/health_check/run_parallel_health_checks.sh 16 "your-registry/your-image:tag"

Configuration

Environment Variables

• LITELLM_BASE_URL (required): Base URL of the LiteLLM proxy
  • Example: https://litellm.example.com
• LITELLM_API_KEY (required): API key for authentication
• LITELLM_CUSTOM_AUTH_HEADER (optional): Custom header name for authentication
  • Use this when your LiteLLM proxy uses a custom authentication header instead of the standard Authorization header
  • Example: x-custom-auth-header (the API key will be sent as Bearer <api_key> in this header)
• LITELLM_MODELS_YAML (optional): Path to YAML config file with model_list
  • If provided, reads models from YAML instead of fetching from API
  • Example: /path/to/config.yaml
• LITELLM_TIMEOUT (optional): Request timeout in seconds (default: 120)
• LITELLM_COMPLETION_PROMPT (optional): Test prompt for chat/completion models (default: ~100k characters)
• LITELLM_EMBEDDING_TEXT (optional): Test text for embedding models (default: ~100k characters)
• LITELLM_JSON_OUTPUT (optional): Output results as JSON (default: false)

Parallel Script Parameters

PowerShell (run_parallel_health_checks.ps1):

• -NumParallelJobs (optional): Number of parallel containers to run (default: 16)
• -ImageName (optional): Docker image to use (default: litellm/litellm-health-check:latest)
• -ContainerRuntime (optional): Container runtime to use (default: docker)

Bash (run_parallel_health_checks.sh):

• [num_parallel_jobs] (optional): Number of parallel containers to run (default: 16)
• [image_name] (optional): Docker image to use (default: litellm/litellm-health-check:latest)
• [container_runtime] (optional): Container runtime to use (default: docker)

Output

Standard Output (Human-Readable)

Example output format:

============================================================
Starting health check queries

---- gpt-4o ----
✅ Success. Response:
This is a test

---- text-embedding-3-small ----
✅ Success. Generated embedding vector with 1536 dimensions.

---- gpt-5-codex ----
❌ ERROR: HTTP 503: Service unavailable

============================================================
Health Check Summary
============================================================
Total models: 47
Healthy: 45
Unhealthy: 2
============================================================

Exit code: 0 if all models are healthy, 1 if any models are unhealthy.

JSON Output

When LITELLM_JSON_OUTPUT=true, outputs JSON:

{
  "gpt-4o": {
    "model": "gpt-4o",
    "healthy": true,
    "error": null,
    "response_time_ms": 245.67,
    "mode": "chat",
    "response_text": "This is a test"
  },
  "text-embedding-3-small": {
    "model": "text-embedding-3-small",
    "healthy": true,
    "error": null,
    "response_time_ms": 123.45,
    "mode": "embedding",
    "dimensions": 1536
  }
}

How It Works

1. Model Discovery:
   • If LITELLM_MODELS_YAML is set: Reads models from YAML config file
   • Otherwise: Queries /v1/models (OpenAI-compatible) or /model/info to get all configured models
2. Mode Detection:
   • Checks mode field from YAML config, or falls back to model name patterns (embedding, embed, text-embedding)
3. Concurrent Testing:
   • Chat models: POST /v1/chat/completions with configurable prompt (default: "Say this is a test")
   • Embedding models: POST /v1/embeddings with configurable text (default: "This is a test for vectorization.")
4. Reporting: Health status, errors, response times, and response details are reported

Use Cases

1. Regular Health Monitoring

Run as a cron job or scheduled task:

# Cron job: Run every 5 minutes
*/5 * * * * /path/to/health_check.sh

2. Load/Stress Testing

Run multiple health checks in parallel:

PowerShell:

# Using default image
.\scripts\health_check\run_parallel_health_checks.ps1 16

# Using custom image
.\scripts\health_check\run_parallel_health_checks.ps1 -NumParallelJobs 16 -ImageName "your-registry/your-image:tag"

Bash:

# Using default image
./scripts/health_check/run_parallel_health_checks.sh 16

# Using custom image
./scripts/health_check/run_parallel_health_checks.sh 16 "your-registry/your-image:tag"

3. CI/CD Integration

Add to your deployment pipeline:

# GitHub Actions example
- name: Health Check
  run: |
    docker run --rm \
      -e LITELLM_BASE_URL="${{ secrets.LITELLM_BASE_URL }}" \
      -e LITELLM_API_KEY="${{ secrets.LITELLM_API_KEY }}" \
      litellm/litellm-health-check:latest

4. Kubernetes Deployment

Deploy as a CronJob:

apiVersion: batch/v1
kind: CronJob
metadata:
  name: litellm-health-check
spec:
  schedule: "*/5 * * * *"  # Every 5 minutes
  jobTemplate:
    spec:
      template:
        spec:
          containers:
          - name: health-check
            image: litellm/litellm-health-check:latest
            env:
            - name: LITELLM_BASE_URL
              value: "https://litellm.example.com"
            - name: LITELLM_API_KEY
              valueFrom:
                secretKeyRef:
                  name: litellm-secrets
                  key: api-key
          restartPolicy: OnFailure

Troubleshooting

No Models Found

• Verify LITELLM_BASE_URL is correct
• Check that the API key has permissions to list models
• Ensure the proxy is running and accessible
• If using YAML, verify LITELLM_MODELS_YAML path is correct

Timeout Errors

• Increase LITELLM_TIMEOUT for slower models (default is 120s)
• Check network connectivity to the proxy
• Verify proxy isn't overloaded

Authentication Errors

• Verify LITELLM_API_KEY is correct
• Check API key has not expired
• Ensure the key has necessary permissions

Dependencies

• Python 3.11+
• httpx (for async HTTP requests)
• pyyaml (for YAML config file support)
• Docker or Podman (for containerized execution)
• PowerShell (for parallel execution script on Windows)

License

Same as LiteLLM project.