Mixing FAQ sets and knowledge base documents in your Voiceflow agent to generate better responses.

Summary

In this video, Nico from Voice FL demonstrates how to effectively combine a knowledge base and a FAQ set to deliver the most accurate responses. He showcases the potential issue of using similar questions in both systems and how they might yield incorrect answers. The solution involves using separate agents for the knowledge base and FAQ set, ensuring that specific answers from the FAQ are supplemented with context from the knowledge base for enhanced accuracy. Nico also explains how to integrate these systems using API calls and provides a step-by-step guide for setting up and querying both sources.

Takeaways

• 😀 The video demonstrates how to integrate a knowledge base and a fiq set in separate agents to generate accurate responses.
• 🔍 The main issue discussed is the challenge of using fiq and a knowledge base in the same agent, which can lead to incorrect answers due to the reliance on fiq.
• 🛠️ The video provides a practical demonstration using fiq API and KB query to illustrate the problem of incorrect answers when the question closely matches the fiq set.
• 📚 It suggests adding documents to the knowledge base to improve the accuracy of responses, such as importing a pricing page.
• 🔑 The importance of using different API keys for the main agent with the knowledge base and the separate agent with the fiq set is highlighted.
• 🤖 The video shows how to query the fiq using the fiq agent's API key and then use the knowledge base from the main agent to refine the answer.
• 📝 It explains the process of capturing chunks from the KB and fiq responses, and using them to generate a more accurate answer.
• 🔄 The script emphasizes the strategy of using the fiq answer as a starting point and then cross-referencing it with the knowledge base for verification.
• 📈 The video concludes by showing how using a separate knowledge base and fiq set can reduce the likelihood of hallucination and improve response accuracy.
• 💡 An additional test is conducted to demonstrate the effectiveness of the method by adding new information to the fiq and successfully generating an accurate response.
• 👋 The presenter signs off by summarizing the benefits of using both fiq and knowledge base features for better response generation in chatbots.

Q & A

What is the main issue highlighted in the video when using FIQ and a knowledge base in the same agent?

The main issue is that when a question closely matches an entry in the FIQ set, the agent might prioritize the FIQ answer, even if it's incorrect, over the correct information in the knowledge base.

How can the issue of incorrect FIQ answers be addressed?

The issue can be addressed by using separate agents: one agent dedicated to FIQ and another to the knowledge base. This allows for checking both sources and generating a more accurate answer.

What is an FIQ set, as mentioned in the video?

An FIQ (Frequently Inquired Questions) set is a collection of specific question-answer pairs that an agent can reference to provide quick and precise responses.

Why did the speaker choose to trigger the issue with similar prompts during the demo?

The speaker used similar prompts intentionally to demonstrate how the agent might incorrectly rely on the FIQ set when the question matches closely with an FIQ entry.

What happens if you remove the FIQ set and then query the knowledge base?

If the FIQ set is removed, the agent correctly uses the information from the knowledge base to answer the query.

How does the video suggest handling multiple sources for generating an answer?

The video suggests fetching answers from both the FIQ set and the knowledge base, reviewing both contexts, and then generating the most accurate response.

What is the purpose of using two different API keys in the solution?

Two different API keys are used to separate the FIQ set and the knowledge base, ensuring that the agent queries each one independently.

What is the role of the 'chunks' mentioned in the video?

Chunks refer to segments of information retrieved from the knowledge base, which are then used alongside FIQ answers to generate a more accurate response.

How does the solution reduce the likelihood of generating inaccurate answers?

By combining FIQ answers with context from the knowledge base and selecting the most accurate response, the solution reduces the likelihood of hallucinations and incorrect answers.

What can you do if only the knowledge base provides information and no FIQ set is available?

If only the knowledge base provides information, the agent will rely solely on the knowledge base to generate the answer.