Production Pipelines

Pipelines, for MLOps, efficiently integrate your data with streamlined processing and make inference with your pre-built models.

Generate Dataset From Scalar/Vector Values

Our production pipelines works strictly with your dataset in CSV or JSON files. This API is exposed to ease the generation of dataset from single values or vector of values to be used for prediction.

Generate dataset API

POST https://autogon.ai/api/v1/models/generate

To prepare a single value for prediction, pass the single value. To prepare for multiple values, pass them in an array. To prepare multi-dimensional values, pass them in nested arrays.

Path Parameters

Name	Type	Description
data*	Various	Value(s) to be generated for prediction.

200: OK URL to CSV for prediction use

"To make an HTTP request in Python, you can use the built-in `requests` module. Here is an example:\n\n```python\nimport requests\n\nresponse = requests.get('https://www.example.com')\nprint(response.text)\n```\n\nThis code sends a GET request to `https://www.example.com` and prints the response content. You can also send other types of requests (POST, PUT, DELETE, etc.) by changing the method in the `requests` function. For example:\n\n```python\nimport requests\n\npayload = {'key1': 'value1', 'key2': 'value2'}\nresponse = requests.post('https://www.example.com/post', data=payload)\nprint(response.text)\n```\n\nThis code sends a POST request to `https://www.example.com/post` with a payload of `{'key1': 'value1', 'key2': 'value2'}` and prints the response content."

Make Predictions

Perform quick and fully-managed model inference

POST https://autogon.ai/api/v1/models/production/

Request Body

Name	Type	Description
test_data*	string	Dataset to be predicted
flow_id	String	Pipeline identifier to use for inference

200: OK Inference results