How to Create AI Tools and Agents for Knowledge Q&A in 7 Minutes

Creating a Simple Chat Experience with AI

• The process begins with uploading the desired data into the AI tool's data Tab.

• Once the data is uploaded, a process called vectorization is run to enable contextual search for relevant data.

• After the data is uploaded and processed, a new AI tool is created to perform the Q&A based on the knowledge within the uploaded file.

• The AI tool is configured with the uploaded file as the knowledge base and an input for user questions.

• The tool is named 'Purple SEC IT Q&A', and basic text input is used for the question.

Creating a Simple Chat Experience with AI

Optimizing Knowledge for Effective Prompt Generation

• When setting up a variable in a prompt, it's important to give it a name that reflects its purpose.

• Tool steps involve creating a prompt with a context and a question. The context includes all the knowledge or data sets available for the prompt.

• To handle too much content, the option of 'most relevant data' can be selected, which uses vector search to reduce content size while ensuring relevance.

• Performing a vector search for the question within the knowledge helps to find the most relevant data to include in the prompt.

• Optimizing the accuracy of the prompt while managing the content size is crucial for effective prompt generation.

Optimizing Knowledge for Effective Prompt Generation

Enhancing the Prompt Functionality

• The first step is to analyze the results of the penetration test and search for the answer.

• It's important to incorporate the source file name for the answer, which can be added in the prompt.

• Additional rules like not fabricating an answer if the context doesn't include information and including as much detail as possible should be included.

• These enhancements make the prompt more functional and applicable to various use cases.

Enhancing the Prompt Functionality

Creating a Conversational AI Tool

• Different models can be used for creating a Q&A AI tool, such as GPT-3.5, GPT-3.5 16k, GPT-4, or Claude V2.

• GPT-3.5 16k has four times the amount of context available, while GPT-4 is more expensive but more accurate. Claude V2 allows up to a hundred thousand tokens per prompt for huge amounts of context.

• The AI tool can be shared by creating a template that can be shared into someone else's notebook, generating a read-only shareable link, embedding it into an iframe, or integrating it into other platforms using the API endpoint.

• A conversational approach using AI agent's functionality can be created by starting from scratch and setting up a new agent with customized prompts and personality.

Creating a Conversational AI Tool

Creating an AI-Powered Agent

• To create a functional AI agent, it's important to equip it with the necessary AI tools.

• An example is using the Purple Stickit Q&A tool, which can be integrated into the agent without requiring prompts for every use.

• The Purple Stickit Q&A tool provides comprehensive responses to inquiries and can even elaborate on specific topics, such as the Windshock vulnerability.

• The conversational experience of the AI agent allows for interactive and informative communication with users.

• Users can share and embed the AI agent's responses, enabling them to create custom chatbot experiences based on their data and preferences.

• The process of creating a knowledge-based Q&A system using AI tools is made simple and accessible, providing a versatile solution for various applications.

Creating an AI-Powered Agent

Conclusion:

The process of creating AI tools and agents for Knowledge Q&A is made simple and accessible in this blog. With a focus on optimization and enhancing functionality, it provides a versatile solution for various applications. Start creating your AI-powered knowledge Q&A system today!