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Pixeltable UDFs that wrap various endpoints from the Fireworks AI API. In order to use them, you must first pip install fireworks-ai and configure your Fireworks AI credentials, as described in the Working with Fireworks tutorial. View source on GitHub

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udf chat_completions()

chat_completions(
    messages: Json,
    *,
    model: String,
    model_kwargs: Json | None = None
) -> Json
Creates a model response for the given chat conversation. Equivalent to the Fireworks AI chat/completions API endpoint. For additional details, see: https://docs.fireworks.ai/api-reference/post-chatcompletions Request throttling: Applies the rate limit set in the config (section fireworks, key rate_limit). If no rate limit is configured, uses a default of 600 RPM. Requirements:
  • pip install fireworks-ai
Parameters:
  • messages (Json): A list of messages comprising the conversation so far.
  • model (String): The name of the model to use.
  • model_kwargs (Json | None): Additional keyword args for the Fireworks chat_completions API. For details on the available parameters, see: https://docs.fireworks.ai/api-reference/post-chatcompletions
Returns:
  • Json: A dictionary containing the response and other metadata.
Example: Add a computed column that applies the model accounts/fireworks/models/mixtral-8x22b-instruct to an existing Pixeltable column tbl.prompt of the table tbl: 
messages = [{'role': 'user', 'content': tbl.prompt}]
tbl.add_computed_column(response=chat_completions(messages, model='accounts/fireworks/models/mixtral-8x22b-instruct'))