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Serverless is the fastest way to get started with using open models. This quickstart will help you make your first API call in minutes.

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Step 1: Create and export an API key

Before you begin, create an API key in the Fireworks dashboard. Click Create API key and store it in a safe location. Once you have your API key, export it as an environment variable in your terminal:
  • macOS / Linux
  • Windows
export FIREWORKS_API_KEY="your_api_key_here"

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Step 2: Make your first Serverless API call

  • Python
  • JavaScript
  • curl
Fireworks provides an OpenAI compatible endpoint. Install the OpenAI Python SDK:
pip install openai
Then make your first Serverless API call:
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("FIREWORKS_API_KEY"),
    base_url="https://api.fireworks.ai/inference/v1"
)

response = client.chat.completions.create(
    model="accounts/fireworks/models/deepseek-v3p1",
    messages=[{
        "role": "user",
        "content": "Say hello in Spanish",
    }],
)

print(response.choices[0].message.content)
You should see a response like: "¡Hola!"

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Common use cases

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Streaming responses

Stream responses token-by-token for a better user experience:
  • Python
  • JavaScript
  • curl
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("FIREWORKS_API_KEY"),
    base_url="https://api.fireworks.ai/inference/v1"
)

stream = client.chat.completions.create(
    model="accounts/fireworks/models/deepseek-v3p1",
    messages=[{"role": "user", "content": "Tell me a short story"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

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Function calling

Connect your models to external tools and APIs:
  • Python
  • JavaScript
  • curl
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("FIREWORKS_API_KEY"),
    base_url="https://api.fireworks.ai/inference/v1",
)

response = client.chat.completions.create(
    model="accounts/fireworks/models/kimi-k2-instruct-0905",
    messages=[{"role": "user", "content": "What's the weather in Paris?"}],
    tools=[
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get the current weather for a location",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "City name, e.g. San Francisco",
                        }
                    },
                    "required": ["location"],
                },
            },
        }
    ],
)

print(response.choices[0].message.tool_calls)
Learn more about function calling →

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Structured outputs (JSON mode)

Get reliable JSON responses that match your schema:
  • Python
  • JavaScript
  • curl
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("FIREWORKS_API_KEY"),
    base_url="https://api.fireworks.ai/inference/v1",
)

response = client.chat.completions.create(
    model="accounts/fireworks/models/deepseek-v3p1",
    messages=[
        {
            "role": "user",
            "content": "Extract the name and age from: John is 30 years old",
        }
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "person",
            "schema": {
                "type": "object",
                "properties": {"name": {"type": "string"}, "age": {"type": "number"}},
                "required": ["name", "age"],
            },
        },
    },
)

print(response.choices[0].message.content)
Learn more about structured outputs →

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Vision models

Analyze images with vision-language models:
  • Python
  • JavaScript
  • curl
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("FIREWORKS_API_KEY"),
    base_url="https://api.fireworks.ai/inference/v1"
)

response = client.chat.completions.create(
    model="accounts/fireworks/models/qwen2p5-vl-32b-instruct",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's in this image?"},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://storage.googleapis.com/fireworks-public/image_assets/fireworks-ai-wordmark-color-dark.png"
                    },
                },
            ],
        }
    ],
)

print(response.choices[0].message.content)
Learn more about vision models →

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Next steps

Ready to scale to production, explore other modalities, or customize your models?

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API Reference

Complete API documentation
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