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Our Software Architecture diagram looks as follows:
As part of this project, we implemented three API funcitonalities.
We have a CRON Job (Scraping Job) that is deployed on Cloud Scheduler which is periodically executed to scrape top trending instagram tags and captions. This data is then stored in MongoDb which would be later used to write to Redis Db. We also have another CRON job (Redis Job) that continously checks for an update in MongoDb. Once the scraping job updates our instagram tags and captions, this Redis Cron Job shall update the Redis Cache with the top trending instagram tags thus making it real time. Since these CRON Jobs are async tasks, we are using GCP queues. The scraping job makes sure the suggested hash tags are real time and up-to-date.
Upon choosing the particular hashtag, top 15 trending hash tags of real time will be displayed.
We sorted trending hashtags by categories to speed up your research.
Our AI based model suggests recommended hash tags for your image using popular and state-of-the-art ALS model. We trained our model using the scraped Instagram data. Please check the references folder for more information about the model.
Upon uploading the image and clicking on submit, a request shall be sent to the REST server and the hash tags are displayed for that image as follows:
Our AI based model suggests recommended hash tags for your image using popular and state-of-the-art ML model. We trained our model using the scraped Instagram data. Please check the references folder for more information about the model.
Upon uploading the image and clicking on submit, a request shall be sent to the REST server and the captions are displayed for that image as follows:
NOTE: