Visual Workflow AI

With the API Block, you can connect to any endpoint, process the response, and loop through the data to trigger actions. Whether it’s sending alerts, posting tweets, executing trades, or anything else. $FlowAi

Go back to the Chat panel. Since we added a response format, new output options are now available: - Click the dropdown and select the new structured output option (the schema we just created) - Enter a new test message like: "Sarah is a marketing manager from New York who has an MBA from Harvard Business School." - Click "Send" to run the workflow again You should now see structured JSON output with the person's information organized into location, profession, and education fields.

Now let's make our agent return structured data. Click on the Agent block to select it. In the Response Format section: - Click the magic wand icon (✨) next to the schema field - In the prompt that appears, type: "create a schema named person, that contains location, profession, and education" - The AI will generate a JSON schema for you automatically

Now let's test our workflow. Go to the Chat panel on the right side of the screen. In the chat panel: - Click the dropdown and select agent1.content (this will show us the output of our agent) - Enter a test message like: "John is a software engineer from San Francisco who studied Computer Science at Stanford University." - Click "Send" to run the workflow You should see the agent's response analyzing the person described in your text.

Let's enhance our agent with tools for better capabilities. Click on the Agent block to select it. In the Tools section: - Click Add Tool - Select Exa from the available tools - Select Linkup from the available tools - Add your API keys for both tools (this allows the agent to search the web and access additional information)

Open Visual Workflow AI and click "New Workflow" in the dashboard. Name it "Getting Started". When you create a new workflow, it automatically includes a Start block - this is the entry point that receives input from users. For this example, we'll be triggering the workflow via chat, so we don't need to configure anything on the Start block. Now drag an Agent Block onto the canvas from the blocks panel on the left. Configure the Agent Block: - Model: Select "OpenAI GPT-4o" - System Prompt: "You are a people research agent. When given a person's name, use your available search tools to find comprehensive information about them including their location, profession, educational background, and other relevant details." - User Prompt: Drag the connection from the Start block's output into this field (this connects <start.input> to the user prompt)

What We're Building: A people research agent that: 1. Receives a person's name via chat interface 2. Uses an AI agent with advanced search capabilities 3. Searches the web using state-of-the-art LLM-Search tools (Exa and Linkup) 4. Extracts structured information using a response format 5. Returns comprehensive data about the person

What started as Almost Ready for Deployment is now live in production. Wallet management and credit purchase features are now available Pricing updates in real-time based on the current $SOL ➝ $FlowAI rate All revenue goes to the marketing wallet to support future growth and buybacks

Almost Ready for Deployment 👀 - Wallet Management and Credit Purchase modules added - Dynamic pricing based on live $SOL - $FlowAI conversion - Revenue goes to the marketing wallet for future development and buybacks A new era of on-chain, autonomous workflow infrastructure is taking shape.

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