📚 Cloud Tables is a cloud infrastructure that combines the functionality of PHP and WordPress data tables to provide seamless integration with other applications and frameworks.
🔗 By adding the Cloud Tables API as a dependency in Flowise, developers can store values online and access and manipulate the tables in various languages, including Node.js.
💻 Custom tools and Open AI agent can be used to store and sort data in different data sets within Cloud Tables, allowing for embedding the tables in other applications and extending functionality.
📊 Two data sets are created: one for alarm data and one for order data.
🔑 There are two pre-configured API Keys with different permissions.
🔗 To add dependencies to Flowise, yarn is used and certain steps need to be followed.
📚 To add the Cloudtables API library to our project, we clone the Flowise repository and navigate to the components directory.
⚙️ After installing the library, we configure Flowise by uncommenting instructions in the dot end file and assigning our library to Tool_function_external_depth.
🚀 With the installation and configuration complete, we can start Flowise by typing 'npx flowwise start' and it will listen to Port tree towers.
🔑 Setting up the open AI key for Flowise and connecting it to the Cloudtables-API.
💡 Creating a flow in Flowise for storing stock price alarms in the Cloud table.
📝 Implementing the JavaScript function to require the newly added dependency and create an API.
📊 Understanding the importance of the data set ID and data point IDs when storing properties in the alarm data set.
💾 Storing data in the cloud and retrieving the result from cloud tables.
🔒 Exploring the security measures and permissions required to access the cloud tables node.js API.
💡 Creating custom flows in Flowise and adding properties for stock order data.
📊 Using JavaScript function to add properties to a dataset in Flowise.
💻 Connecting to Cloudtables API and storing data in different datasets.
🤖 Using Chat GPT to answer questions and store information in Cloudtables.
💡 The video discusses the use of chat GPT to add alarms and orders for trading purposes.
🔍 It highlights the importance of checking and managing data in cloud tables.
🛠️ The example demonstrates how to improve the chatbot by adding error handling and automation.
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