Two different prompt agents are used in this product, one is used for SQL generation and the other is used for data insights generation. With the power of openAI, human language can be translated into SQL queries with proper prompt engineering. Built on top of it, stable and flexible database services are available for back-end support. Third, creating data visualization and extracting business insights have been time consuming.Ī data warehouse storing indexed and structured on-chain and off-chain data is provided. There are high technical barriers for using existing data tool platforms. Second, It has been difficult to fetch and process the data for further implementation. In addition, there is limited access to historical data for smart contracts. What is the problem EasyQuery aims to solve?įirst, Web3 data is scattered on various blockchains and platforms lacking connectivity.
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With its ability to extract data insights and facilitate native data utilization in dApps, EasyQuery is the ultimate tool for unlocking the full potential of Web3. By classifying, clustering, and summarizing comments, the app provides a valuable tool for generating new content ideas that will engage and excite their audience, leading to increased views and followers.ĮasyQuery is a revolutionary product that enables users to effortlessly harness the intuitive power of Web3 data query through natural language. In conclusion, this app provides content creators with a streamlined approach to understanding their audience's preferences and interests by analyzing the comments on their posts. This helps content creators to understand the interests and preferences of their audience better and create content that resonates with their viewers. These topics are presented to the content creators, along with suggested content ideas for future posts. Using the analysis of the clustered comments, the app generates a summary of the main themes and extracts the primary topics. By clustering the comments, content creators can quickly analyze and understand the nature of the comments and identify any common themes or topics that resonate with their audience.
These comments are then grouped into three clusters using KMeans. By leveraging the YouTube API, the app can efficiently read through all the comments and classify them according to their sentiment, toxic content, or spam.Īfter classifying the comments, the app creates a word embedding using cohere AI, which helps to identify patterns and group similar comments together. This app is a powerful tool designed to assist content creators who have a substantial following of over 5000 viewers or followers.
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