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Fireworks AI

Introduction​

Fireworks AI offers a rapid, cost-effective, and adaptable solution for generative artificial intelligence, enabling product developers to execute, refine, and distribute LLMs efficiently.

Deploying your model​

Fireworks offers the capability to deploy various Chat Models(LLM) under its umbrella.

Chat Model​

Refer to their documentation to understand the latest offerings, with feature and cost comparisons.

Usage with MAAP​

To use Fireworks model with MAAP framework, you would need to feed below values.

  • Config File :​

    Provided below are the values required to be added in config.yaml file in embedding section.

    llms:
        class_name: Fireworks
        model_name: <check_references_below>
        max_tokens: <integer_value>
        temperature: <integer_value>

  • Environment Variable :​

    Below value(s) are to be added in .env file, present at builder/partnerproduct/.

    FIREWORKS_API_KEY : <check_references_below>

Embedding Model​

You can follow the same steps as above to deploy the embedding model as well. The process is documented here.

Usage with MAAP​

To use Azure OpenAI embedding with MAAP framework, you would need to feed below values.

  • Config File :​

    Provided below are the values required to be added in config.yaml file in embedding section. The class_name should be appropriate to the embedding model being used.

    embedding:
        class_name: Fireworks
        model_name: <check_references_below>

  • Environment Variable :​

    Below value(s) are to be added in .env file, present at builder/partnerproduct/.

    FIREWORKS_API_KEY = <check_references_below>

References​

Provided below are the instructions on how to procure the right values for building your MAAP framework.

  • Model Name​

    You can pick any model from the updated list given in Fireworks documentation.

  • API Key​

    You will need to sign up and retrieve a Fireworks API Key.