AI Conversation History Management

This workflow is designed for:

• Content Creators: Those who need to manage and summarize conversations effectively.
• Customer Support Teams: To streamline responses and utilize AI tools for enhanced service.
• Researchers: Individuals looking for efficient ways to gather information from various sources.
• Developers: Those integrating AI capabilities into applications for better user interaction.

This workflow addresses:

• Inefficiency in Information Retrieval: Automates the process of gathering and summarizing information from various sources, including OpenAI and Wikipedia.
• Memory Limitations: Utilizes a memory buffer to retain the last 20 messages, ensuring context is maintained during conversations.
• Manual Triggering: Allows for user-initiated interactions, providing flexibility in when to engage the AI.

The workflow process includes:

1. Manual Chat Trigger: Starts the workflow when a user sends a chat message.
2. AI Agent Processing: The message is sent to the AI agent which determines the best course of action based on the input.
3. Utilizing Tools: The AI agent can leverage tools like SerpAPI and Wikipedia for additional information.
4. Language Model Interaction: The AI uses the Chat OpenAI model to generate responses based on the user input and gathered data.
5. Memory Management: The Window Buffer Memory retains the last 20 messages to ensure continuity in conversation.
6. Sticky Notes: Important notes are created to summarize conversation history and tools available to the agent.