The client side python apis for making integration with recvani serveers
This contains the client side api for use with recvani server. Recvani is collabrative learning platform for any bussiness where a user and item interact. So client can send score for user interactions and ask for recommendation for user. And all these things in real time.
Check us out at https://www.recvani.com
- Ease to integration:
Integrating is as simple as integrating a database.
- Real time system:
User interaction are taken care within milliseconds for recommendation
- Can Scale very easily:
It can easily support upto millions of users.
- Low on cost:
Cost for deploying will be much less than your inhouse machine learning cost.
- Support categorization:
Client can easily ask for specific category of item for a user.
We can directly install python client using pip
pip install recvani
Client need model name, client key and model key for connecting to recvani server. You can get these by contacting us.
Setting up connection is quite easy.
from recvani.rv_client import rv_client #Don't forget to replace these by the keys you will get. client = rv_client(CLIENT_KEY, MODEL_NAME, MODEL_KEY)
Send Single Interaction
from recvani.rv_requests import simple_interaction import time USER = "USER1" # unique id for user ITEM = "ITEM1" # item id (item can be news id, video id, product id etc.) SCORE = 1.0 # score client want to give for interaction. Should be devised intelligently ITIME = int(time.time()) # time for the interaction in seconds interaction = simple_interaction(USER, ITEM, SCORE, ITIME) result = client.send(interaction) #result will 1 on sucess otherwise exception will be thrown. Better to catch it.
Send Batch Interactions
from recvani.rv_requests import batch_interaction, simple_interaction import time bi =  bi.append(simple_interaction("USER1", "ITEM1", 0.0, int(time.time()))) bi.append(simple_interaction("USER2", "ITEM1", 1.0, int(time.time()))) bi.append(simple_interaction("USER1", "ITEM2", 0.0, int(time.time()))) bis = batch_interaction(bi) result = client.send(bis)
We can attach tags and expiry time for every item
Send expiry time
from recvani.rv_requests import exp_request import time EXP_TIME = time.time() + 30*24*3600 # The time you want to expire the item. rexp = exp_request("ITEM1", EXP_TIME) result = client.send(rexp)
from recvani.rv_requests import tag_request TAGS = ["TAG1", "TAG2"] trequest = tag_request("STORY1", TAGS) result = client.send(trequest)
Send in bulk
from recvani.rv_requests import batch_param, item_param import time param1 = item_param("ITEM1", int(time.time()) + 365*24*3600, ["TAG1"]) param2 = item_param("ITEM2", None, ["TAG2"]) param3 = item_param("ITEM3", exp_time = int(time.time()) + 365*24*3600) bparam = batch_param([param1, param2, param3]) result = client.send(bparam)
We can get the final recommendation for the user. We can filter history and send you items for particular tag.
from recvani.rv_requests import rec_request USER = "USER1" # USER ID COUNT = 10 # Count of Recommended item to fetch TAGS =  # Tags of item, Empty for overall HISTORY = False # Will not serve already serverd item. rc = rec_request("USER1", 1, , True) result = client.send(rc) # Result will be list of items
rc = rec_request("USER1", 10, [["TAG1"]], True) result = client.send(rc) # Will give 10 stories with "TAG1" attached to it
Tags can be used to make complex queries. For Example
TAGS = [["TAG1", "TAG2"], ["TAG4"]]
The inner lists provide intersection and outer lists provide union. The tags above will return all time which are either marked "TAG4" or have both "TAG1" and "TAG2" attached to it.
For any help feel free to contact email@example.com
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