Coze | How to use Workflows

The video transcript outlines how to create a multi-step workflow for an AI chatbot to perform specific tasks. It uses the example of an NBA bot that provides up-to-date statistics and scores for NBA games. The process involves setting up nodes, including a starting node for user input, an end node for output, and various other nodes for logic and data processing. The video demonstrates how to connect these nodes, use a custom plugin to fetch data from an NBA API, and refine the data using a code node. Finally, it shows how to utilize a large language model to generate a user-friendly response and format the final output through an end node. The workflow significantly improves the bot's ability to provide accurate and tailored information compared to a bot without a workflow.

Takeaways

• 🤖 Use workflows to customize your AI chatbot for multi-step tasks tailored to your specific needs.
• 🏀 The example demonstrates creating an NBA bot to provide real-time game statistics and scores.
• 📈 Workflows enhance the bot's ability to provide accurate and uniform data to the user.
• 🔍 Nodes are the basic units of a workflow, representing steps that connect to each other to achieve the desired outcome.
• 📚 Knowledge nodes use knowledge bases to match information based on user inputs.
• 💡 The large language model node generates responses based on input, aiding in creating more human-like bot interactions.
• 📅 The 'date' is used as a starting input to query the NBA API for specific game data.
• 🔌 Plugins can be used as nodes to connect to various APIs, such as an NBA API for game statistics.
• 👩‍💻 A code node is used to process input variables and generate return values, requiring some coding knowledge.
• 🔗 The workflow connects nodes from the start (user input) to the end (output), passing information through each step.
• 📝 Customizing the end node allows for formatting the final response to the user in a preferred manner.
• 🚀 Workflows enable the bot to provide a higher quality of answer by processing and tailoring information through multiple steps.

Q & A

What is the primary purpose of using workflows with an AI chatbot?

The primary purpose of using workflows with an AI chatbot is to enable the bot to complete multi-step tasks tailored towards specific user needs, providing more accurate and uniform responses.

How do workflows enhance the functionality of an AI chatbot?

Workflows enhance an AI chatbot's functionality by allowing it to process complex, multi-step tasks through a series of interconnected nodes, which can include inputs, outputs, decision-making logic, and data processing.

What is a node in the context of workflows?

A node in workflows is the basic unit that makes up a workflow. Nodes represent individual steps or actions that, when connected, guide the workflow towards achieving the desired end result.

How does the large language model node contribute to the workflow?

The large language model node contributes to the workflow by generating responses based on the input provided to it. It can take complex, structured data and transform it into a more readable and understandable format for the user.

Why is coding knowledge beneficial when working with workflows?

Coding knowledge is beneficial when working with workflows because it allows for the creation of custom plugins and APIs, which can provide specific data or functionalities. It also aids in understanding and manipulating data within code nodes for tailored responses.

What is the role of the code node in a workflow?

The code node in a workflow plays a crucial role in processing input variables and generating return values. It allows for the manipulation and parsing of data to extract specific information needed for the workflow's output.

How do plugins function within a workflow?

Plugins function within a workflow as nodes that can connect to external services or databases, such as an NBA API, to retrieve or send data. They can be used to gather information needed for the workflow to produce accurate and relevant outputs.

What is the significance of the starting node in a workflow?

The starting node in a workflow is significant as it is the entry point where the user's input or question is received. It sets the workflow in motion and is the initial step in the multi-step task.

How does the end node in a workflow differ from other nodes?

The end node in a workflow differs from other nodes as it is responsible for producing the final output and returning the value that the user is looking for. It signifies the completion of the workflow process.

What is the importance of the knowledge nodes in a workflow?

Knowledge nodes are important in a workflow as they utilize created knowledge bases to match and retrieve information based on user inputs. They help in providing context-aware and accurate responses.

How can the if condition and variable nodes assist in a workflow?

The if condition and variable nodes assist in a workflow by introducing logic and memory. The if condition node allows for decision-making based on certain conditions, while variable nodes enable the reading and writing of values for storage and later use within the workflow.

What is the final step in implementing a workflow?

The final step in implementing a workflow is to publish the workflow and integrate it into the AI chatbot. This allows the bot to use the workflow to process user queries and provide tailored, accurate responses.

Outlines

00:00

🤖 Customizing AI Chatbots with Workflows

The video introduces the concept of using workflows to enhance an AI chatbot's capabilities. The speaker discusses how to create a multi-step task for the bot to complete, specifically for an NBA bot that provides the latest information, statistics, and scores of NBA games. The workflow is designed to replace the need for external sources like ESPN. The speaker explains the importance of nodes within a workflow, which represent steps to reach the desired outcome. The video also emphasizes the difference between a bot's functionality with and without a workflow.

05:02

🔌 Utilizing Plugins and Workflows for Data Retrieval

The speaker delves into the use of plugins for the NBA bot, highlighting the creation of a custom plugin that connects to an NBA API to fetch real-time and historical game data. The process involves naming inputs, connecting nodes, and using a code node to parse and extract relevant information from the API payload. The speaker demonstrates how to format the output to pass on to the next node in the workflow, emphasizing the power of the code node in customizing the bot's response.

10:04

📈 Parsing Data and Enhancing Readability with the Large Language Model

The video continues by illustrating how to use a large language model node to make the output data more readable for the user. The speaker connects the code node to the language model node, passing the parsed game information through a prompt designed to guide the model's output. The speaker then customizes the end node to format the final response, including the game results, date, and game count, to present it in a user-friendly manner. The workflow is tested with a sample query to demonstrate its effectiveness.

15:04

📝 Workflow Implementation and Comparison

The final paragraph focuses on the practical implementation of the workflow within the bot and compares its performance to the bot's functionality without the workflow. The speaker demonstrates how the bot's response is significantly more accurate and tailored when the workflow is integrated. The video concludes by emphasizing the power of workflows in customizing the bot's responses and invites viewers to explore further resources and join the community for more insights.

Keywords

💡Workflows

Workflows are a series of connected steps or tasks that are automated to accomplish a specific goal. In the context of the video, workflows are used to enable a chatbot to complete multi-step tasks, such as retrieving and presenting NBA game scores, in a structured and automated manner. The video demonstrates how workflows can enhance a bot's capabilities by guiding it through a sequence of actions to deliver accurate and tailored information to the user.

💡AI Chatbot

An AI chatbot is an artificial intelligence application designed to engage in conversation with humans. It uses natural language processing to understand and respond to user inputs. In the video, the AI chatbot is being customized to serve as a personal assistant for NBA game information, demonstrating the integration of workflows to improve its functionality.

💡Knowledge Bases

Knowledge bases are structured collections of information that an AI system can use to enhance its understanding and responses. They provide the AI with a source of facts and data to draw upon. In the video, knowledge bases are used to give the AI chatbot intelligence and context for delivering accurate NBA game statistics and scores.

💡Plugins

Plugins are additional software components that can be added to a program to extend its functionality. In the video, the creator mentions using plugins to connect the chatbot to various services like Reddit, Microsoft Outlook, and Google Search. Additionally, a custom plugin is created to connect to an NBA API, which is crucial for fetching real-time game data.

💡Nodes

In the context of workflows, nodes represent individual steps or actions within the workflow process. Each node performs a specific function, and nodes are connected to create a sequence of operations. The video explains how nodes such as the 'large language model node' and 'code node' are used to process information and generate responses within the NBA bot's workflow.

💡Large Language Model

A large language model is an AI system that is trained on a vast amount of text data and can generate human-like language. It is used in the video to process inputs and generate responses based on the information passed through the workflow. The model helps in making the bot's responses more natural and understandable to users.

💡Code Node

A code node within a workflow allows for the execution of custom code to manipulate data, perform calculations, or handle logic. In the video, the code node is used to parse and process the raw data received from the NBA API, extracting only the relevant information needed to answer the user's query about game scores.

💡API (Application Programming Interface)

An API is a set of rules and protocols that allows different software applications to communicate and interact with each other. In the video, the creator uses an API to fetch real-time and historical NBA game data, which is then processed through the workflow to provide the user with the desired information.

💡Multi-Step Task

A multi-step task is a process that requires multiple stages or steps to reach completion. The video focuses on using workflows to automate multi-step tasks for an AI chatbot, ensuring that the bot can provide comprehensive and accurate responses to queries about NBA game scores across different dates.

💡Customization

Customization refers to the process of adapting or tailoring a product or service to meet specific needs or preferences. In the video, the AI chatbot is customized using workflows to serve as a personalized NBA game information assistant, demonstrating how workflows can be used to make the bot's responses more relevant and useful to the user.

💡Data Parsing

Data parsing involves extracting and organizing data from a raw or unstructured format into a structured one that can be easily understood and used. In the video, data parsing is done through the code node to take the large payload of NBA game data and convert it into a more manageable and relevant format for the chatbot's responses.

Highlights

Workflows are introduced as a way to customize AI chatbots for specific tasks.

The video demonstrates creating an NBA bot to provide real-time game statistics and scores.

Workflows enable bots to complete multi-step tasks with greater accuracy.

Nodes are the basic units of a workflow, representing steps that connect to produce a result.

The starting node is where the user input or question is placed in the workflow.

The end node produces the output and returns the value that the user is looking for.

Large language model nodes generate responses based on input, which can be further specified with prompts.

Code nodes process input variables and generate return values, requiring coding knowledge.

Knowledge nodes use knowledge bases to match information based on user inputs.

If condition nodes and variable nodes are used for logic and data storage within workflows.

Plugins can be used as nodes to extend functionality, such as connecting to APIs.

Custom plugins can be created to connect to specific APIs for tailored data retrieval.

The NBA Daily data node uses a custom plugin to fetch real-time NBA game data.

Code nodes are used to parse and truncate data to extract only the necessary information.

Large language model nodes take the parsed data and make it readable for the user.

The end node formats the final result, presenting it to the user in a customized manner.

Workflows can significantly improve the quality and accuracy of a bot's responses.

Adding a workflow to a bot allows for a tailored and more accurate response to user queries.

The power of workflows lies in their ability to format and present information as desired by the user.