scribemi 1.2.0

Library to manage MI files in Scribe's platform

Scribe Private Documents (MI) SDK

A Python library designed to facilitate accessing Scribe's Private Documents (MI) API.

This library requires a version of Python 3 that supports typings.

Installation

pip install ScribeMi

Usage

Construct client

The constructor expects an environment object:

env = {
  API_URL: 'API_URL',
  IDENTITY_POOL_ID: 'IDENTITY_POOL_ID',
  USER_POOL_ID: 'USER_POOL_ID',
  CLIENT_ID: 'CLIENT_ID',
  REGION: 'REGION',
};

The API_URL is "mi.scribelabs.ai/v1".

The REGION is "eu-west-2".

Contact Scribe to obtain other details required for authentication.

from ScribeMi import MI

client = MI({
    'API_URL': 'mi.scribelabs.ai/v1',
    'REGION': 'eu-west-2',
    'IDENTITY_POOL_ID': 'Contact Scribe for authentication details',
    'USER_POOL_ID': 'Contact Scribe for authentication details',
    'CLIENT_ID': 'Contact Scribe for authentication details',
})

Authenticate

Authentication is handled by Scribe's Auth library, without the need for you to call that library directly.

# Authenticate with username / password
client.authenticate({ 'username': 'myUsername', 'password': 'myPassword' })

# OR with refresh token
client.authenticate({ 'refresh_token': 'myRefreshToken' })

The MI client will try to automatically re-authenticate with your refresh token, if you try to make an API call after credentials have expired.

Submit a document for processing

jobid = client.submit_task('path/to/file.pdf', {
    'filetype': 'pdf',
    'filename': 'example-co-2023-q1.pdf',
    'companyname': 'Example Co Ltd'
})

The filetype parameter is required: it should match the file's extension / MIME type.

Other parameters are optional:

• filename is recommended: it should be the name of the uploaded file. It appears in API responses and the web UI.
• companyname can optionally be included for company Financials data: it should be the legal name of the company this document describes, so that documents relating to the same company can be collated.

The returned jobid can be used to find information about the task status via getTask, or via the web UI.

View tasks

Fetch details of an individual task:

task = client.get_task(jobid)
print(task.status)

Or list all tasks:

tasks = client.list_tasks()

Export output models

After documents have been processed by Scribe, the task status (which can be seen via get_task / list_tasks) is "SUCCESS". At this point, you can export the model:

task = client.get_task(jobid)

# Use fetchModel
model = client.fetch_model(task)

# Alternatively, fetch the model directly from its URL
return task.modelUrl

In either case, note that the model is accessed via a pre-signed URL, which is only valid for a limited time after calling get_task / list_tasks.

Collate fund data

When using Scribe to process fund data, multiple models can be consolidated for export in a single file:

tasks = client.list_tasks()
tasks_to_collate = [task for task in tasks if task['originalFilename'].startswith('Fund_1')]

collated_model = client.consolidate_tasks(tasks_to_collate)

Delete tasks / cancel processing

task = client.get_task(jobid)

client.delete_task(task)

Deletion is irreversible.

After a successful deletion, the file, any output model, and any other file derived from the input are deleted permanently from Scribe's servers.

See also

Documentation for the underlying REST API may also be useful, although we recommend accessing the API via this library or our Node SDK.

• REST API documentation

• Node SDK