API Reference

Learn how to use the W&B Inference API to access foundation models programmatically.

Endpoint

Access the Inference service at:

https://api.inference.wandb.ai/v1

Available methods

The Inference API supports these methods:

Chat completions

Create a chat completion using the /chat/completions endpoint. This endpoint follows the OpenAI format for sending messages and receiving responses.

To create a chat completion, provide:

• The Inference service base URL: https://api.inference.wandb.ai/v1
• Your W&B API key: <your-api-key>
• Your W&B entity and project: <your-team>/<your-project>
• A model ID from the available models

• Bash
• Python

curl https://api.inference.wandb.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <your-api-key>" \
  -H "OpenAI-Project: <your-team>/<your-project>" \
  -d '{
    "model": "<model-id>",
    "messages": [
      { "role": "system", "content": "You are a helpful assistant." },
      { "role": "user", "content": "Tell me a joke." }
    ]
  }'

import openai

client = openai.OpenAI(
    # The custom base URL points to W&B Inference
    base_url='https://api.inference.wandb.ai/v1',

    # Get your API key from https://wandb.ai/authorize
    # Consider setting it in the environment as OPENAI_API_KEY instead for safety
    api_key="<your-api-key>",

    # Team and project are required for usage tracking
    project="<your-team>/<your-project>",
)

# Replace <model-id> with any model ID from the available models list
response = client.chat.completions.create(
    model="<model-id>",
    messages=[
        {"role": "system", "content": "<your-system-prompt>"},
        {"role": "user", "content": "<your-prompt>"}
    ],
)

print(response.choices[0].message.content)

List supported models

Get all available models and their IDs. Use this to select models dynamically or check what’s available.

• Bash
• Python

curl https://api.inference.wandb.ai/v1/models \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <your-api-key>" \
  -H "OpenAI-Project: <your-team>/<your-project>" 

import openai

client = openai.OpenAI(
    base_url="https://api.inference.wandb.ai/v1",
    api_key="<your-api-key>",
    project="<your-team>/<your-project>"
)

response = client.models.list()

for model in response.data:
    print(model.id)

Response format

The API returns responses in OpenAI-compatible format:

{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "created": 1234567890,
  "model": "meta-llama/Llama-3.1-8B-Instruct",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Here's a joke for you..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 50,
    "total_tokens": 75
  }
}

Next steps

• Try the usage examples to see the API in action
• Explore models in the UI