Code - Python
Python Helper Functions
Code - Python
Python Helper Functions
Natively Supported Helper Functions
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.
Functions
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.
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.
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
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.
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.
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.
Usage Examples
Insert data
Python
data = [{"field1": "value1", "field2": "value2"}, {"field1": "value3", "field2": "value4"}]
response = insert_data("my_dataset", data)
Retrieve data
Python
response = retrieve_data("my_dataset", page_size=10, include_fields=["field1", "field2"])
Retrieve all
Python
response = retrieve_all("my_dataset", page_size=500, include_fields=["field1", "field2"])
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)
Prompt completion
Python
response = prompt_completion("My prompt", model="openai-gpt35")
Run a step
Python
response = run_step("my_step", {"param1": "value1", "param2": "value2"})
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