Custom Recipe with MongoDB

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1

Hello,

First of all, thanks for developing Prodigy, it's a great tool.

I'm currently trying to use MongoDB as a source for annotations and a place to deposit annotated text. After looking through the docs, it looks like a custom recipe is necessary for storing annotations. I am trying to set up very basic functionality for now. I have a Mongo collection that stores the text to be annotated and a Mongo collection that stores the annotated text. These are referred to in my code as source_collection and dest_collection, respectively. My understanding of a dataset is that it's just a collection of annotated text, and the way we want to implement datasets is up to us.

Here's my simple custom recipe.

@prodigy.recipe(
    'ner-custom',
    dataset=("Dataset to save answers to", "positional", None, str),
)
def custom_recipe(dataset):
    view_id = 'ner_manual'
    mongo_client = CustomMongoClient(MONGO_INSTANCE, PORT, DB_NAME, SOURCE_COLLECTION_NAME, DEST_COLLECTION_NAME)

    def get_inputs_from_mongo():
        for doc in mongo_client.source_collection.find():
            del doc['_id']
            yield doc

    nlp = spacy.blank('en')
    stream = get_inputs_from_mongo()
    stream = add_tokens(nlp, stream)
    
    return {
        'view_id': view_id,
        'db': mongo_client,
        'stream': stream,
        'dataset': dataset,
        'config': {
            'labels': ['ITEM']
        }
    }

Here is my custom MongoDB client.

from pymongo import MongoClient

class CustomMongoClient:

    def __init__(self, mongo_instance, port, db_name, source_collection_name, dest_collection_name):
        self.client = MongoClient(mongo_instance, port)
        self.db = self.client[db_name]
        self.source_collection = self.db[source_collection_name]
        self.dest_collection = self.db[dest_collection_name]

    def get_dataset(self, name, default=None):
        return list(self.dest_collection.find())

    def get_examples(self, ids, by="task_hash"):
        return list(self.dest_collection.find({"task_id": {"$in": ids}}))

    def add_dataset(self, name, meta={}, session=False):
        pass

    def add_examples(self, examples, datasets):
        self.dest_collection.insert_many(examples)

    def get_sessions_examples(self, session_ids=None):
        return self.get_dataset("temp")

As shown above, I've implemented some of the DB functions as outlined in the API. For the dataset functions, I'm basically just pulling everything from my dest_collection. When a dataset is "added", I don't do anything.

When I try to run prodigy ner-custom temp-dataset -F custom_recipe.py, I get an odd error regarding my custom DB class.

15:47:22: CLI: Importing file custom_recipe.py
15:47:22: RECIPE: Calling recipe 'ner-custom'
15:47:22: CONFIG: Using config from global prodigy.json
15:47:22: VALIDATE: Validating components returned by recipe
15:47:22: CONTROLLER: Initialising from recipe
15:47:22: VALIDATE: Creating validator for view ID 'ner_manual'
15:47:22: VALIDATE: Validating Prodigy and recipe config
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/local/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/usr/local/lib/python3.7/site-packages/prodigy/__main__.py", line 61, in <module>
    controller = recipe(*args, use_plac=True)
  File "cython_src/prodigy/core.pyx", line 374, in prodigy.core.recipe.recipe_decorator.recipe_proxy
  File "cython_src/prodigy/core.pyx", line 63, in prodigy.core.Controller.from_components
  File "cython_src/prodigy/core.pyx", line 143, in prodigy.core.Controller.__init__
  File "cython_src/prodigy/core.pyx", line 342, in prodigy.core.Controller.connect_db
TypeError: argument of type 'CustomMongoClient' is not iterable

Do I need to implement all DB methods for the custom DB to work? Or am I doing something wrong here with my setup. I've also tried looking at GitHub - jdagdelen/mondigy: A small component for using Mongodb databases with Prodigy annotation applications., but still not exactly sure what's happening here. Any help is appreciated. Thanks!

2

Hi there!

Prodigy only supports Sqlite, MySQL and Postgres natively. Any other databases will require a custom implementation. This section on our docs gives more details on how you could do that:

I've not used mondigy myself, so I can't comment on it's utility. Alternatively though, you can also just export the MongoDB data into a JSONL file and then use that as input data for Prodigy. Similarily you can also use the db-out recipe to get JSONL data out of Prodigy and then you could use a small Python script to get it into Mongo again. It's a bit of scripting this way, which might be more convenient than writing the database class.

3

Thanks, I'll try that. As for implementing a custom DB class, is it required to have all methods defined?

1 Like
4

I would say that it is recommended. It's possible that you'll only use a subset of methods initially, but especially if you're going to be using it for the long term, you'll likely want to ensure that everything works as expected.

1 Like