Fireworks AI | liteLLM (original) (raw)

info

We support ALL Fireworks AI models, just set fireworks_ai/ as a prefix when sending completion requests

Overview​

This guide explains how to integrate LiteLLM with Fireworks AI. You can connect to Fireworks AI in three main ways:

1. Using Fireworks AI serverless models – Easy connection to Fireworks-managed models.
2. Connecting to a model in your own Fireworks account – Access models that are hosted within your Fireworks account.
3. Connecting via a direct-route deployment – A more flexible, customizable connection to a specific Fireworks instance.

API Key​

# env variable
os.environ['FIREWORKS_AI_API_KEY']

Sample Usage - Serverless Models​

from litellm import completion
import os

os.environ['FIREWORKS_AI_API_KEY'] = ""
response = completion(
    model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct", 
    messages=[
       {"role": "user", "content": "hello from litellm"}
   ],
)
print(response)

Sample Usage - Serverless Models - Streaming​

from litellm import completion
import os

os.environ['FIREWORKS_AI_API_KEY'] = ""
response = completion(
    model="fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct", 
    messages=[
       {"role": "user", "content": "hello from litellm"}
   ],
    stream=True
)

for chunk in response:
    print(chunk)

Sample Usage - Models in Your Own Fireworks Account​

from litellm import completion
import os

os.environ['FIREWORKS_AI_API_KEY'] = ""
response = completion(
    model="fireworks_ai/accounts/fireworks/models/YOUR_MODEL_ID", 
    messages=[
       {"role": "user", "content": "hello from litellm"}
   ],
)
print(response)

Sample Usage - Direct-Route Deployment​

from litellm import completion
import os

os.environ['FIREWORKS_AI_API_KEY'] = "YOUR_DIRECT_API_KEY"
response = completion(
    model="fireworks_ai/accounts/fireworks/models/qwen2p5-coder-7b#accounts/gitlab/deployments/2fb7764c", 
    messages=[
       {"role": "user", "content": "hello from litellm"}
   ],
   api_base="https://gitlab-2fb7764c.direct.fireworks.ai/v1"
)
print(response)

Note: The above is for the chat interface, if you want to use the text completion interface it's model="text-completion-openai/accounts/fireworks/models/qwen2p5-coder-7b#accounts/gitlab/deployments/2fb7764c"

Usage with LiteLLM Proxy​

1. Set Fireworks AI Models on config.yaml​

model_list:
  - model_name: fireworks-llama-v3-70b-instruct
    litellm_params:
      model: fireworks_ai/accounts/fireworks/models/llama-v3-70b-instruct
      api_key: "os.environ/FIREWORKS_AI_API_KEY"

2. Start Proxy​

litellm --config config.yaml

3. Test it​

• Curl Request
• OpenAI v1.0.0+
• Langchain

curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Content-Type: application/json' \
--data ' {
      "model": "fireworks-llama-v3-70b-instruct",
      "messages": [
        {
          "role": "user",
          "content": "what llm are you"
        }
      ]
    }
'

Document Inlining​

LiteLLM supports document inlining for Fireworks AI models. This is useful for models that are not vision models, but still need to parse documents/images/etc.

LiteLLM will add #transform=inline to the url of the image_url, if the model is not a vision model.See Code

• SDK
• PROXY

from litellm import completion
import os

os.environ["FIREWORKS_AI_API_KEY"] = "YOUR_API_KEY"
os.environ["FIREWORKS_AI_API_BASE"] = "https://audio-prod.api.fireworks.ai/v1"

completion = litellm.completion(
    model="fireworks_ai/accounts/fireworks/models/llama-v3p3-70b-instruct",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://storage.googleapis.com/fireworks-public/test/sample_resume.pdf"
                    },
                },
                {
                    "type": "text",
                    "text": "What are the candidate's BA and MBA GPAs?",
                },
            ],
        }
    ],
)
print(completion)

Disable Auto-add​

If you want to disable the auto-add of #transform=inline to the url of the image_url, you can set the auto_add_transform_inline to False in the FireworksAIConfig class.

• SDK
• PROXY

litellm.disable_add_transform_inline_image_block = True

Reasoning Effort​

The reasoning_effort parameter is supported on select Fireworks AI models. Supported models include:

• SDK
• PROXY

from litellm import completion
import os

os.environ["FIREWORKS_AI_API_KEY"] = "YOUR_API_KEY"

response = completion(
    model="fireworks_ai/accounts/fireworks/models/qwen3-8b",
    messages=[
        {"role": "user", "content": "What is the capital of France?"}
    ],
    reasoning_effort="low",
)
print(response)

Supported Models - ALL Fireworks AI Models Supported

info

We support ALL Fireworks AI models, just set fireworks_ai/ as a prefix when sending completion requests

Supported Embedding Models​

info

We support ALL Fireworks AI models, just set fireworks_ai/ as a prefix when sending embedding requests

Audio Transcription​

Quick Start​

• SDK
• PROXY

from litellm import transcription
import os

os.environ["FIREWORKS_AI_API_KEY"] = "YOUR_API_KEY"
os.environ["FIREWORKS_AI_API_BASE"] = "https://audio-prod.api.fireworks.ai/v1"

response = transcription(
    model="fireworks_ai/whisper-v3",
    audio=audio_file,
)

Pass API Key/API Base in .transcription

Rerank​

Quick Start​

• SDK
• PROXY

from litellm import rerank
import os

os.environ["FIREWORKS_AI_API_KEY"] = "YOUR_API_KEY"

query = "What is the capital of France?"
documents = [
    "Paris is the capital and largest city of France, home to the Eiffel Tower and the Louvre Museum.",
    "France is a country in Western Europe known for its wine, cuisine, and rich history.",
    "The weather in Europe varies significantly between northern and southern regions.",
    "Python is a popular programming language used for web development and data science.",
]

response = rerank(
    model="fireworks_ai/fireworks/qwen3-reranker-8b",
    query=query,
    documents=documents,
    top_n=3,
    return_documents=True,
)
print(response)

Pass API Key/API Base in .rerank

Supported Models​