Sticky Note Conversation Enhancement Workflow

Target Audience

• Developers: Those looking to automate chat interactions and integrate AI capabilities into their applications.
• Businesses: Organizations that want to enhance customer support through automated responses using AI tools.
• Researchers: Individuals interested in leveraging Wikipedia and weather data for information retrieval and analysis.
• Educators: Teachers and trainers who wish to create interactive learning experiences through chat-based interfaces.

Problem Solved

This workflow addresses the need for an automated conversational agent that can provide real-time information from multiple sources, such as Wikipedia and weather data, while maintaining a history of interactions. It allows users to query specific information and receive accurate responses without manual intervention, thus saving time and improving efficiency.

Workflow Steps

1. Manual Trigger: The workflow starts when a user sends a new chat message.
2. AI Agent Processing: The message is processed by the AI Agent, which utilizes a system message to define its role and capabilities.
3. Memory Buffer: The conversation history is stored in a buffer memory to maintain context for ongoing interactions.
4. Tool Utilization: The AI Agent can access various tools:
   • Wikipedia Tool: For retrieving general information.
   • Weather HTTP Request: For fetching current weather data based on provided latitude and longitude.
5. Response Generation: The AI Agent generates a response using the information from the tools and the conversation history.
6. Output: The final response is sent back to the user, providing them with the requested information.