Is there an existing integration?

• I have searched the existing integrations.

Use Case

tf-serving (the whole name is tensorflow-serving, the url is https://github.com/tensorflow/serving) is a widely used Deep Model release/publish/inference platform which can provide model-inference function with ideal performace. The ML model generated by several mainly used ML-framework can work on tf-serving， including tensorflow, pytorch, maxnet and so on. (tf-serving, it's also a sub project of the top tensorflow project, I saw #2933 which also mentioned tensorflow, after read it, I think it means the project https://github.com/tensorflow/tensorflow, not including https://github.com/tensorflow/serving, so I think issues/2933 is different with this issue)

After the integration of tf-serving, that provides a query/predict only function, it can work as the usecase below:

register a tf-serving

CREATE PREDICTOR mindsdb.tf_house_price_predictor
PREDICT target
USING
url.predict='http://localhost:8501/v1/models/model_name/predict',
format='tfserving',
dtype_dict={"year": integer, "month": integer, "city_code": integer, "street_code": integer, "target": float};

predict with tf-serving

SELECT hp_tbl.year, hp_tbl.month, hp_tbl.city_code, hp_tbl.street_code, tf_p.target
FROM mindsdb_mysql_proxy.house_price AS hp_tbl
JOIN tf_house_price_predictor AS tf_p
WHERE hp_tbl.year >= 2022 AND hp_tbl.month >= 3

Motivation

tf-serving is a widely used Deep Model release platform which can provide an ideal performance model inference function.
The ML model generated by several mainly used ML-framework can work on tf-serving， including tensorflow, pytorch and so on.

Compare with integrate the tensorflow (https://github.com/tensorflow/tensorflow) framework, integrate tf-serving (https://github.com/tensorflow/serving) first will cost very less time, in fact, tf-serving is a platform for publish/release/inference models.

With mindsdb, people can implement ai features as easy as writing sql, I guess the main audiences of this product could not be the ai-specialists, so a model release platform should be more suitable to implement in the first time. Of crouse, tensorfow (https://github.com/tensorflow/tensorflow) framework is the most popular framework in ai-area, it must be integrated to our mindsdb, but it needs to cost more time, and maybe the using of tf-serving in mindsdb will provide more important experience for integrating tensorflow (https://github.com/tensorflow/tensorflow).

Believe me, to integrate tf-serving, it will be very useful, you will never regret to do such a right decision.

Thank you! ^_^

Implementation

Depend on integrating it as a virtual datasource or only a ml function, there're two ways to implement this funciton:
1 Datasource
Add handler in mindsdb, but only deal with the create and delete and query related sqls, because we only want to support prediction but training. Code path: \mindsdb\integration\handlers\tf_serving_handler

2 ML function
Integrate it in lightwood framework, in path \lightwood\mixer\tf_serving_model.py

Anything else?

In fact, I've read your project code for a few days, your project is very cool, have coverd many kinds of data source and ml-frameworks, here i sincerely to provide a piece of advice, i thought you can design some functions which focusing on providing professional services to some industry， to support its full lifecycle, such as online-shopping, supply-chain-management, etc. Thank you.