This client provides an interface to interact with the Relevance API. It includes functions to run various steps, insert and retrieve data, and upload temporary files.

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Functions

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Insert data

Python
insert_data(dataset_id: str, data: List[Dict[str, Any]])

Inserts data into a Relevance dataset.

Arguments

  • dataset_id: The ID of the dataset to insert into.
  • data: A list of dictionaries containing the data to insert.

Returns

  • The response from the API as a JSON object.

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Retrieve data

Python
retrieve_data(dataset_id: str, page_size: int = None, include_fields: List[str] = None)

Retrieves data from a Relevance dataset.

Arguments

  • dataset_id: The ID of the dataset to retrieve from.
  • page_size: The number of results to return per page (optional).
  • include_fields: A list of fields to include in the response (optional).

Returns

  • The response from the API as a JSON object.

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Retrieve All Data

Python
retrieve_all(dataset_id: str, page_size: int = 1000, include_fields: List[str] = None) -> List[Dict[str, Any]]:

Retrieves all data from a Relevance dataset, paginated to handle large datasets.

Arguments

  • dataset_id: The ID of the dataset to retrieve from.
  • page_size: The number of results to return per page. Defaults to 1000 (optional).
  • include_fields: A list of fields to include in the response. Defaults to None (optional).

Returns

  • A list of dictionaries containing the retrieved data. Each dictionary represents a document from the dataset.

Example

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Upload a temporary file

Python
insert_temp_file(file_path_or_bytes: str, ext: str = None)

Uploads a temporary file to Relevance.

Arguments

  • file_path_or_bytes: The path to the file or the file contents as bytes.
  • ext: The file extension (optional).

Returns

  • A dictionary containing the download URL of the uploaded file.

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Prompt completion

Python
prompt_completion(prompt: str, model: int = None)

Runs the prompt_completion step with the given prompt and model.

Arguments

  • prompt: The prompt to complete.
  • model: The model to use for completion (optional).

Returns

  • The response from the API as a JSON object.

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Run a step

Python
run_step(step_name: str, params: Dict[str, Any])

Runs a Relevance step with the given name and parameters.

Arguments

  • step_name: The name of the step to run.
  • params: A dictionary of parameters to pass to the step.

Returns

  • The response from the API as a JSON object.

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Usage Examples

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Insert data

Python
data = [{"field1": "value1", "field2": "value2"}, {"field1": "value3", "field2": "value4"}]
response = insert_data("my_dataset", data)

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Retrieve data

Python
response = retrieve_data("my_dataset", page_size=10, include_fields=["field1", "field2"])

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Retrieve all

Python
response = retrieve_all("my_dataset", page_size=500, include_fields=["field1", "field2"])

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Upload a temporary file

Note: Make sure to replace the region variable with your actual region.

Python
file_path = "path/to/file.txt"
response = insert_temp_file(file_path)

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Prompt completion

Python
response = prompt_completion("My prompt", model="openai-gpt35")

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Run a step

Python
response = run_step("my_step", {"param1": "value1", "param2": "value2"})