Complete Coze tutorial: Building an AI chatbot from scratch
TLDRThis comprehensive tutorial walks you through the process of building a powerful AI chatbot using the Co platform. The session begins with an introduction to the Co bot store, where community-created bots are available for inspiration. The guide then explains how to create a bot from scratch, starting with naming and integrating large language models like GPT 4 for understanding context. The process continues with designing the bot's persona, adding skills, and customizing responses using natural language prompts. The tutorial highlights the use of plugins, knowledge bases, and card bindings to enhance the bot's functionality and provide structured responses. It also covers the use of variables for personalization and memory functions, as well as the creation of workflows for multi-step processes. The session concludes with instructions on publishing the bot to various chat applications and the Co bot store, emphasizing the platform's ease of use and the extensive support available through documentation, Discord, and YouTube tutorials.
Takeaways
- 🤖 **Building AI Chatbots**: The tutorial covers how to build powerful AI chatbots using Co, a platform that integrates with large language models like GPT-4.
- 🏪 **Cobot Store**: Co features a bot store filled with community-created bots for various purposes, including learning, productivity, and entertainment.
- 📚 **Knowledge Bases**: Co allows users to create knowledge bases by uploading various file types, which can enhance the bot's ability to provide informed responses.
- 🔧 **Workflows**: Users can set up workflows to manage multi-step processes, combining different skills and plugins for more complex tasks.
- 📈 **Optimization**: Co provides an 'optimize prompt' feature that assists in refining the bot's persona and capabilities without requiring expertise in prompt engineering.
- 📱 **Chat Application Integration**: Bots built on Co can be published and used on popular chat applications like Discord and Telegram directly from the platform.
- 📸 **Plugins and APIs**: The platform offers a variety of plugins and connects to APIs like GitHub and Yelp to extend the bot's functionality.
- 💬 **Conversational UI**: Co features a conversational UI that allows for easy testing and modification of the bot before it's published.
- 🧠 **Memory Functions**: Bots can utilize variables and databases to remember user preferences and provide personalized responses.
- 🔗 **Card Bindings**: Co's card bindings feature enables structured responses that include both text and images, enhancing the user experience.
- 🌐 **Publishing Options**: After development, bots can be published to the Co bot store or directly to various chat platforms, making them accessible to a wider audience.
Q & A
What is the main purpose of the Co Bot Store?
-The Co Bot Store serves as a platform where community members can share and explore AI chatbots they've created. It features a variety of bots designed for different purposes such as learning, productivity, writing assistance, and more.
How can one get inspired to create their own AI chatbot?
-One can get inspired by exploring the Co Bot Store, where they can see different types of bots created by the community, such as learning characters, productivity bots, and writing assistance bots. This can spark ideas for the kinds of bots they can build and the use cases of AI chatbots.
What are some key features that Co provides for building AI chatbots?
-Co provides features like knowledge bases, which can ingest data from various sources like PDFs, Excel sheets, APIs, and websites. It also offers workflows for multi-step processes, the ability to publish to popular chat applications directly from the interface, and access to GPT models for free.
How does Co differ from other AI bot builders like the GPT Builder from Open AI?
-While the GPT Builder is great for creating AI bots, Co offers additional features that may not be available in the GPT Builder. These include knowledge bases, workflows, the ability to publish to various chat applications, and access to different GPT models for free.
What is the process of creating a chatbot in Co?
-To create a chatbot in Co, you start by naming your bot and describing its purpose. You then use the workspace to design your bot's persona, discuss the features you want it to have, and write a persona prompt. Co helps optimize the prompt and structure it in a way that is clear for the AI to understand.
How can one test their chatbot before publishing it?
-You can test your chatbot within the Co platform's chat interface without publishing it. Simply write a message or question as you would when using the bot, and observe how it responds based on the persona and skills you've programmed.
What are plugins and how do they enhance the functionality of an AI chatbot?
-Plugins are extensions that allow an AI chatbot to access and utilize information from various services across the web, such as Google web search, Trip Advisor, and Yelp. They enhance the bot's functionality by enabling it to fetch real-time data and provide more personalized and relevant responses.
How does the knowledge base feature in Co help reduce 'hallucinations' in AI chatbots?
-The knowledge base feature allows the AI chatbot to reference and use content stored in different files and websites, providing more context for answering questions. By lowering the minimum matching degree and adjusting the model temperature, the bot is more likely to retrieve accurate information from the knowledge base, reducing the chances of generating incorrect or 'hallucinated' responses.
What is the role of workflows in creating a more structured response from an AI chatbot?
-Workflows help combine different skills like plugins, knowledge bases, and variables to create a multi-step process. This process allows for a more structured and predictable response, enabling the bot to orchestrate between different nodes or skills to generate a stable and refined answer.
How can triggers be used to make an AI chatbot more proactive?
-Triggers can be set based on variables, databases, or events to make the AI chatbot send messages or perform actions at specific times or under certain conditions. For example, a trigger can be used to send a daily news summary or remind a user to take medicine at a set time.
What are the benefits of using multi-agent mode in Co?
-Multi-agent mode allows for the creation of a team of bots, each specializing in different skills. These bots can work together to complete tasks more efficiently, providing a more streamlined experience for the user. It's particularly useful for complex tasks that require multiple skills or for creating a personal assistant with various functionalities.
Outlines
🤖 Introduction to AI Chatbot Creation on Co So Co
The video begins with an introduction to creating powerful AI chatbots using Co So Co, a platform that allows developers to build AI bots on top of large language models like GPT 4. The presenter, playing the role of a developer or user, is guided by Joshua through the process. They discuss the Co bot store, which contains community-built bots for various purposes such as learning, writing assistance, and image generation. The store serves as an inspiration for bot creators and offers pre-built bots for different needs, emphasizing the platform's aim to accelerate bot development.
🚀 Starting the Chatbot Creation Process
The presenter outlines the process of starting to create a chatbot, specifically one designed to help plan a trip to Japan. They discuss the ease of getting started with Co and the potential for adding complexities to the bot. The video demonstrates naming the bot 'Plan a Trip Bot' and integrating a large language model. It also covers customizing the bot's profile image and delving into the Co workspace, where the bot's persona and features are designed using natural language prompts. The platform's ability to optimize prompts and utilize markdown format for better AI comprehension is highlighted.
🔍 Choosing the Right Large Language Model
The video emphasizes the importance of selecting the appropriate large language model based on the bot's use case. It mentions that not every situation requires the most powerful model, such as GPT 4, and that customization options like temperature and response length are available. The presenter also assures that testing the chatbot is straightforward and demonstrates how the bot can use its predefined skills to generate responses, even at this early stage.
📚 Enhancing the Bot with Plugins and APIs
The presenter discusses the use of plugins and APIs to enhance the bot's capabilities. They explain how plugins like Google web search, GPT, and DALL-E 3 can be added to the bot to integrate various functionalities. The video also covers adding Trip Advisor and Yelp plugins to the bot to enable it to recommend places to stay and eat. The presenter shows how to use these plugins within the bot's prompt to specify when to use certain functions, emphasizing the ease of use without requiring coding knowledge.
🖼 Structuring Responses with Card Bindings
The video introduces card bindings, a feature that structures bot responses using data from APIs. The presenter demonstrates how to use card bindings to format recommendations in a visually appealing way, with options for including titles, descriptions, and images. They highlight the customization available through card bindings and the ability to link directly to relevant pages, enhancing user interaction.
🧳 Personalizing the Travel Bot with Variables
The presenter explores the use of variables to personalize the travel bot based on user preferences. They discuss how variables can store trip preferences and how the bot can utilize these variables to provide more customized responses. The video also covers how the bot can remember user properties or preferences for future interactions, offering a more personalized experience.
📝 Utilizing Knowledge Bases for Contextual Responses
The video explains how knowledge bases can be used to give the bot more context when answering questions. The presenter demonstrates how to create a knowledge base using various file types and websites, and how this can be applied to the bot for more informed responses. They also discuss the automatic call feature, which allows further customization of the knowledge base and its responses.
🤖 Publishing and Sharing Your Bot
The video concludes with instructions on how to publish the completed bot for wider use. It covers publishing to the Co bot store, as well as other popular chat applications like Discord and Telegram. The presenter also discusses the benefits of sharing the bot on the Co Discord server and the potential for increased exposure in the recommended section of the bot store.
Mindmap
Keywords
💡AI chatbot
💡Co Bot Store
💡Large Language Models (LLMs)
💡Plugins
💡Workflows
💡Knowledge Bases
💡Persona Prompts
💡Variables
💡Triggers
💡Multi-Agent Mode
💡Publishing
Highlights
Coco provides a platform to build AI chatbots on top of large language models like GPT 4.
The Co Bot Store is a community-driven space filled with bots created by users for various purposes, including learning, productivity, and entertainment.
Bots can be used for personal assistance, AI friends, games, or consultation services.
Public configurations allow users to view how a bot was made, including its persona prompt and plugins.
Coco offers features like knowledge bases, workflows, and the ability to publish bots on popular chat applications directly from the interface.
Coco gives access to GPT models for free, allowing users to build bots without incurring monthly costs.
The platform includes a persona creation process where users can define their bot's character, skills, and constraints using natural language.
Coco's workspace offers tools to optimize prompts and structure them in a way that AI can better understand and utilize.
Users can select from various large language models and customize their bot's response behavior, such as temperature and response length.
The platform enables testing of the chatbot within the workspace before publishing it to ensure it meets the desired functionality.
Plugins can be added to the bot to integrate external services like Google web search, DALL-E for image generation, and APIs like Trip Advisor and Yelp.
Coco supports the creation of custom plugins by users, enhancing the bot's capabilities with external APIs.
Card bindings feature allows for structured responses that include both text and images, making the bot's output more user-friendly.
Variables can be used to set trip preferences and personalize the bot's responses based on user interactions.
Knowledge bases enable bots to reference content from various sources, providing more context and reducing 'hallucinations' where AI generates inaccurate information.
Workflows allow for multi-step processes, combining different skills and features to create a more structured and predictable bot response.
Triggers can be set up to have the bot send messages at specific times or based on events, like receiving an email.
Databases in Coco act like a structured conversational Excel sheet, allowing users to store and query data with natural language.
Long-term memory and filebox features help bots remember past interactions and store files like photos for future reference.
Text-to-voice feature allows the bot to read out responses in selected languages, although it's currently supported in only certain chat applications.
Single and multi-user modes in databases cater to individual or shared data management needs, respectively.
Multi-agent mode allows combining different bots with specialized skills to work together on tasks.
Bots can be published to the Co Bot Store or directly to various chat applications like Discord, Telegram, and others for wider accessibility.
