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module pixeltable.functions.together

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

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udf chat_completions()

chat_completions(
    messages: Json,
    *,
    model: String,
    model_kwargs: Json | None = None
) -> Json
Generate chat completions based on a given prompt using a specified model. Equivalent to the Together AI chat/completions API endpoint. For additional details, see: https://docs.together.ai/reference/chat-completions-1 Request throttling: Applies the rate limit set in the config (section together.rate_limits, key chat). If no rate limit is configured, uses a default of 600 RPM. Requirements:
  • pip install together
Parameters:
  • messages (Json): A list of messages comprising the conversation so far.
  • model (String): The name of the model to query.
  • model_kwargs (Json | None): Additional keyword arguments for the Together chat/completions API. For details on the available parameters, see: https://docs.together.ai/reference/chat-completions-1
Returns:
  • Json: A dictionary containing the response and other metadata.
Examples: Add a computed column that applies the model mistralai/Mixtral-8x7B-v0.1 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='mistralai/Mixtral-8x7B-v0.1'))

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udf completions()

completions(
    prompt: String,
    *,
    model: String,
    model_kwargs: Json | None = None
) -> Json
Generate completions based on a given prompt using a specified model. Equivalent to the Together AI completions API endpoint. For additional details, see: https://docs.together.ai/reference/completions-1 Request throttling: Applies the rate limit set in the config (section together.rate_limits, key chat). If no rate limit is configured, uses a default of 600 RPM. Requirements:
  • pip install together
Parameters:
  • prompt (String): A string providing context for the model to complete.
  • model (String): The name of the model to query.
  • model_kwargs (Json | None): Additional keyword arguments for the Together completions API. For details on the available parameters, see: https://docs.together.ai/reference/completions-1
Returns:
  • Json: A dictionary containing the response and other metadata.
Examples: Add a computed column that applies the model mistralai/Mixtral-8x7B-v0.1 to an existing Pixeltable column tbl.prompt of the table tbl: 
tbl.add_computed_column(response=completions(tbl.prompt, model='mistralai/Mixtral-8x7B-v0.1'))

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udf embeddings()

embeddings(input: String, *, model: String) -> Array[(None,), Float]
Query an embedding model for a given string of text. Equivalent to the Together AI embeddings API endpoint. For additional details, see: https://docs.together.ai/reference/embeddings-2 Request throttling: Applies the rate limit set in the config (section together.rate_limits, key embeddings). If no rate limit is configured, uses a default of 600 RPM. Requirements:
  • pip install together
Parameters:
  • input (String): A string providing the text for the model to embed.
  • model (String): The name of the embedding model to use.
Returns:
  • Array[(None,), Float]: An array representing the application of the given embedding to input.
Examples: Add a computed column that applies the model togethercomputer/m2-bert-80M-8k-retrieval to an existing Pixeltable column tbl.text of the table tbl: 
tbl.add_computed_column(response=embeddings(tbl.text, model='togethercomputer/m2-bert-80M-8k-retrieval'))

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udf image_generations()

image_generations(
    prompt: String,
    *,
    model: String,
    model_kwargs: Json | None = None
) -> Image
Generate images based on a given prompt using a specified model. Equivalent to the Together AI images/generations API endpoint. For additional details, see: https://docs.together.ai/reference/post_images-generations Request throttling: Applies the rate limit set in the config (section together.rate_limits, key images). If no rate limit is configured, uses a default of 600 RPM. Requirements:
  • pip install together
Parameters:
  • prompt (String): A description of the desired images.
  • model (String): The model to use for image generation.
  • model_kwargs (Json | None): Additional keyword args for the Together images/generations API. For details on the available parameters, see: https://docs.together.ai/reference/post_images-generations
Returns:
  • Image: The generated image.
Examples: Add a computed column that applies the model stabilityai/stable-diffusion-xl-base-1.0 to an existing Pixeltable column tbl.prompt of the table tbl: 
tbl.add_computed_column(
    response=image_generations(tbl.prompt, model='stabilityai/stable-diffusion-xl-base-1.0')
)