Coze | 3 ways to reduce hallucination for your AI chatbot
TLDRIn the provided transcript, the speaker discusses methods to reduce hallucinations in AI chatbots by enhancing their knowledge base. They demonstrate how to add a structured knowledge base, such as a menu for a restaurant or bakery, using an Excel file with item names, pricing, images, and customer favorites. The speaker also covers the importance of configuring the model's temperature to balance creativity and precision, and setting the minimum matching degree to ensure the bot relies more on the knowledge base for accurate responses. Additionally, they highlight the use of semantic search and the inclusion of image URLs in the knowledge base to provide visual responses. These strategies collectively aim to improve the bot's reliability and user experience.
Takeaways
- 📚 Adding knowledge to your AI chatbot can reduce hallucinations by creating a knowledge base specific to the bot's purpose, such as a menu for a restaurant or bakery.
- 🔍 You can structure knowledge using an Excel file or CSV, which allows for easy uploading and management of data types and descriptions within the knowledge base.
- 📈 The model's temperature controls the randomness of the bot's responses; lowering it increases precision and accuracy, which is particularly useful for customer service bots.
- 🔧 Adjusting the minimum matching degree in the knowledge settings can make the bot refer to the knowledge base more often, providing more accurate answers within the context of a conversation.
- 📈 Using a structured format like Excel for knowledge input ensures that the data is more accurate and reliable for the AI to process.
- 🔗 Including image URLs in the knowledge base allows the bot to retrieve and display images when requested, enhancing the user experience.
- 💡 Using specific prompts like 'output image in this format' along with the image URL in the knowledge base enables the bot to provide visual responses.
- 🛠️ Renaming, updating, and modifying the table structure of the knowledge base after creation provides flexibility in managing the bot's knowledge.
- 📉 Reducing the minimum matching degree can help the bot to draw more from its knowledge base, which can improve the relevance of its responses.
- 🔖 Choosing the right index column, such as 'item name', helps the bot to identify and retrieve specific items of information from the knowledge base.
- 🧩 The bot can use semantic search to find relevant information based on the context of the conversation, which can be optimized by adjusting the knowledge settings.
- 📝 Describing each field in the knowledge base helps the large language model to better understand and utilize the information during conversations.
Q & A
What is one of the easiest ways to reduce hallucinations in an AI chatbot?
-One of the easiest ways to reduce hallucinations in an AI chatbot is to add knowledge to the bot through the interface, creating a new knowledge base that is relevant to the bot's purpose, such as a menu for a restaurant or bakery.
How can you add knowledge to an AI chatbot?
-You can add knowledge to an AI chatbot by creating a new knowledge base, such as a menu, and then adding units to the knowledge base. You can also upload a structured file like an Excel or CSV file that contains relevant information.
What does an Excel file for a knowledge base typically contain?
-An Excel file for a knowledge base typically contains item names, pricing, image URLs, and other relevant details like whether an item is a customer favorite. It serves as a simple database for the bot to reference.
How can you ensure that the AI chatbot uses the uploaded knowledge to answer questions?
-To ensure the AI chatbot uses the uploaded knowledge, you can adjust the model configuration, specifically the temperature setting, to make the bot's responses more precise. Additionally, you can use the automatic call feature with a semantic search and adjust the minimum matching degree to increase the likelihood that the bot will draw from its knowledge base.
What is the role of the temperature setting in an AI chatbot's model configuration?
-The temperature setting in an AI chatbot's model configuration controls the randomness of the bot's responses. A lower temperature setting results in more precise and accurate answers, while a higher temperature allows for more creativity but can lead to hallucinations.
Why is it important to control hallucinations in an AI chatbot?
-Controlling hallucinations in an AI chatbot is important to ensure that it provides accurate and reliable information to users. Uncontrolled hallucinations can lead to incorrect responses that may cause confusion or even financial loss for a business.
How can you upload an Excel file to an AI chatbot's knowledge base?
-To upload an Excel file, you navigate to the knowledge base in the bot's interface, click 'add unit', and then choose to upload the Excel file. The system will guide you through the process of managing and confirming the data within the file.
What is the significance of choosing the correct index for a knowledge base?
-Choosing the correct index, such as the item name, is significant because it helps the bot identify each item uniquely within the knowledge base. This ensures that the bot can accurately retrieve and provide information about specific items when asked.
How can you make sure the AI chatbot provides image responses from the knowledge base?
-To enable the AI chatbot to provide image responses, include the image URLs in the Excel file and ensure there is a prompt in the bot's settings that instructs it to output images in a specific format.
What are the three tips mentioned to make an AI chatbot more reliable and reduce hallucinations?
-The three tips are: 1) Use knowledge, preferably structured in an Excel sheet, 2) Change the model's temperature to lower for more precise answers, and 3) Adjust the knowledge settings to lower the minimum matching degree, increasing the chance that the model draws from its knowledge to answer questions.
Why is it recommended to use an Excel sheet for knowledge rather than a document or URL?
-An Excel sheet is recommended because it is more structured, allowing for more accurate and precise information to be added to the knowledge base. This structure helps the AI chatbot to provide more reliable and accurate responses.
How can adjusting the minimum matching degree help in reducing hallucinations in an AI chatbot?
-By lowering the minimum matching degree, the bot is more likely to reference the knowledge base when answering questions within the context of a semantic search. This reduces the chance of the bot providing unrelated or hallucinated responses.
Outlines
📚 Adding Knowledge to a Bot
This paragraph explains how to add knowledge to a bot to reduce hallucinations. It covers creating a new knowledge base, uploading an Excel file with menu items, pricing, images, and customer favorites. The process of managing the CSV file, checking data types, and choosing an index column is also described. The paragraph concludes with how the bot can use the knowledge base to answer questions and the importance of configuring the model to prevent the bot from going off-topic.
🔍 Improving Bot Reliability and Reducing Hallucinations
This paragraph discusses three tips to make a chatbot more reliable and reduce hallucinations. First, use structured Excel format for knowledge instead of documents or URLs. Second, lower the model's temperature to make answers more precise. Third, adjust the knowledge settings by lowering the minimum matching degree to increase the likelihood of the bot drawing from its knowledge to answer questions. The paragraph also provides an example of how the bot can retrieve specific images from the knowledge base when prompted. The key takeaway is that while AI chatbots aren't perfect, these strategies can significantly improve the user experience and bot performance.
Mindmap
Keywords
💡Hallucination
💡Knowledge Base
💡Excel File
💡CSV File
💡Data Types
💡Model Configuration
💡Temperature
💡Semantic Search
💡Minimum Matching Degree
💡Vector Store/Database
💡Image Retrieval
Highlights
Adding knowledge to your AI chatbot can reduce hallucinations.
Creating a knowledge base for your bot, such as a menu for a restaurant or bakery, can improve accuracy.
You can add units to the knowledge base and upload structured data like an Excel file.
Excel files should include item names, pricing, images, and customer favorites for a comprehensive database.
Ensure data types and descriptions are correctly set for each field in the knowledge base.
Choosing an index, such as item name, helps the bot identify each item uniquely.
Model configuration allows you to select different AI models and adjust the temperature for randomness control.
Lowering the temperature setting increases the precision of the bot's responses.
Using semantic search in knowledge settings can help the bot retrieve relevant information.
Adjusting the minimum matching degree can increase the likelihood of the bot using knowledge to answer questions.
The bot can retrieve and display images from the knowledge base if the prompt is correctly set up.
Using structured formats like Excel increases the accuracy and reliability of the bot's responses.
Three tips for reducing hallucinations in AI chatbots include using knowledge, adjusting model temperature, and modifying the minimum matching degree.
Properly configuring the bot can prevent it from going off-topic and ensure it provides accurate information.
AI chatbots can be improved to deliver the expected user experience and operational standards.
Managing the bot's knowledge base and settings is crucial for maintaining control over its responses.
The bot can provide specific instructions and follow them if properly programmed.
Optimizing the bot's prompts and settings can lead to a more reliable and user-friendly AI experience.