Coze | How to use Workflows
TLDRIn this informative video, the creator guides viewers on how to enhance their AI chatbot's capabilities using workflows. The focus is on building a multi-step task for an NBA bot that provides up-to-date statistics, scores, and information on past and real-time games. The video explains the concept of nodes, which are the building blocks of workflows, and how they connect to form a cohesive process. The creator demonstrates adding a custom plugin to connect to an NBA API for accurate data retrieval. By incorporating a code node for data parsing and a large language model node for generating user-friendly responses, the workflow ensures that the bot can provide tailored and accurate information. The video concludes with a comparison between the bot's performance with and without the workflow, highlighting the significant improvement in the quality and accuracy of the bot's responses when utilizing workflows.
Takeaways
- 🤖 Utilize workflows to enable your AI chatbot to complete multi-step tasks more effectively.
- 🏀 The example demonstrates creating an NBA bot to provide real-time game statistics and scores.
- 📈 Workflows enhance the bot's ability to fetch and deliver accurate and tailored information to the user.
- 🔍 Workflows consist of nodes that connect to form a sequence of steps to achieve a specific outcome.
- 📝 Nodes can include starting points for user input, end points for output, and various processing steps in between.
- 🧠 Large language model nodes can generate responses based on input, aiding in understanding and formatting data.
- 💡 Prompt nodes allow for specifying answers more precisely, while code nodes process inputs and generate return values.
- 📚 Knowledge nodes tap into created knowledge bases to match information based on user queries.
- 🔗 Plugins can be used as nodes, enabling the integration of external services like Reddit, Google Search, and custom APIs.
- 📅 The NBA bot workflow uses a custom plugin to connect to an NBA API, retrieving past and real-time game data.
- 🔍 Code nodes are used to parse and truncate data, focusing on the specific information required for the task.
- 📝 The final output is formatted through a large language model node, making the information legible and user-friendly.
Q & A
What is the main purpose of using workflows with an AI chatbot?
-The main purpose of using workflows with an AI chatbot is to enable the bot to complete multi-step tasks and provide tailored responses to specific user needs, enhancing its functionality and accuracy.
How do workflows enhance the bot's ability to provide information?
-Workflows enhance the bot's ability to provide information by allowing the setup of multi-step tasks that connect various nodes, such as input, processing, and output nodes, to fetch and deliver accurate and uniform data to the user.
What is a node in the context of workflows?
-A node in the context of workflows is a basic unit that represents a step in a process. Nodes connect to one another to achieve an end result, with each node performing a specific function towards generating the desired output.
How does the large language model node function within a workflow?
-The large language model node functions within a workflow by generating a response based on the input provided to it. It can process information from previous nodes and use it to create a more coherent and user-friendly output.
What is the role of the code node in a workflow?
-The code node in a workflow allows for the processing of input variables and generates a return value. It is used to manipulate data, extract specific information, and prepare it for further use in the workflow, although it requires some coding knowledge.
How do plugins fit into the workflow system?
-Plugins can be used as nodes within the workflow system, providing additional functionality and enabling the bot to connect to various external services or databases. They can fetch specific data or perform actions that contribute to the completion of the workflow's task.
Why is it beneficial to create a custom plugin for a specific task?
-Creating a custom plugin for a specific task is beneficial because it allows the user to connect directly to the desired data source or service, such as an API, to fetch the exact data needed. This leads to more accurate and relevant responses from the bot.
How does the knowledge node assist in a workflow?
-The knowledge node assists in a workflow by utilizing created knowledge bases to match information based on user inputs. It helps in providing responses that are informed by the data stored in the knowledge bases, making the bot's answers more informed and relevant.
What is the significance of the if condition and variable nodes in a workflow?
-The if condition and variable nodes are significant in a workflow as they introduce logic and data handling capabilities. The if condition node allows for decision-making based on certain conditions, while the variable node helps in reading and writing values, enabling the storage and passing of information as needed.
How does the end node format the final output for the user?
-The end node formats the final output by taking the processed information from previous nodes and presenting it in a way that is defined by the user within the workflow. It can include direct answer content, which is customized based on the inputs and the desired presentation format.
What is the impact of adding a workflow to an AI chatbot's functionality?
-Adding a workflow to an AI chatbot significantly improves its functionality by allowing it to provide more accurate, tailored, and detailed responses. It enables the bot to handle complex queries by breaking them down into manageable steps, leading to higher user satisfaction.
How does the workflow process differ from a bot operating without a workflow?
-A bot operating without a workflow relies solely on its built-in capabilities and may provide less accurate or less tailored responses. In contrast, a bot with a workflow can process information through a series of connected nodes, each performing a specific task, resulting in more precise and customized answers.
Outlines
🤖 Customizing AI Chatbots with Workflows
The video introduces the concept of using workflows to enhance an AI chatbot's ability to complete multi-step tasks. The speaker demonstrates how to create a workflow for an NBA bot that provides up-to-date statistics and scores for NBA games. The workflow is designed to improve the bot's performance by ensuring it delivers accurate and tailored information to the user. The importance of nodes, which are the building blocks of a workflow, is emphasized, and different types of nodes such as the large language model node, code node, and knowledge nodes are explained. The speaker also discusses the integration of plugins into the workflow to fetch real-time data from an API.
📅 Creating a Workflow for NBA Game Information
The speaker details the process of creating a custom plugin that connects to an NBA API to retrieve game data, including past and real-time games, scores, and statistics. The workflow is then constructed by connecting nodes, starting with a starting node that takes user input, typically a date, and an end node that produces the desired output. The use of a code node to parse and process the API data is highlighted, demonstrating how to extract specific information from the payload. The speaker also shows how to set up inputs and outputs for the next steps in the workflow, including the number of games and game details.
🔍 Refining Data with Code and Language Model Nodes
The video continues with the workflow setup, focusing on how to use a code node to refine the data from the NBA Daily data node. The speaker explains how to truncate the data to include only necessary details such as the profile, box score, home team, away team, and the number of games that occurred on a specific date. A large language model node is then introduced to take the refined data and make it more readable for the user. The speaker also discusses how to format the final output to present the game results, game date, and game count in a customized manner.
📈 Testing and Publishing the Workflow
The speaker demonstrates the workflow in action by testing it with a specific date and showing how the nodes process the input step by step to produce the output. The video emphasizes the difference in data length before and after the code node's processing. The large language model node is shown taking the refined data and using a prompt to create a readable format for the user. The workflow is then published, and the speaker contrasts the bot's response without the workflow to the enhanced response with the workflow. The video concludes with a call to action to learn more about workflows and to join the community for further insights.
Mindmap
Keywords
💡Workflows
💡AI Chatbot
💡Nodes
💡Large Language Model (LLM)
💡Plugins
💡Knowledge Bases
💡Code Node
💡Conditional Logic
💡Variables
💡Tailored Responses
💡Publishing Workflow
Highlights
Workflows are used to customize AI chatbots to complete multi-step tasks tailored to specific needs.
The NBA bot is designed to provide the latest information, statistics, and scores of NBA games for the current season and past seasons.
Workflows enhance the bot's capabilities by allowing it to access real-time game data without the need for external sources like ESPN.
Nodes are the basic units of a workflow, representing steps that connect to one another to achieve an end result.
The starting node is where the user inputs their question, and the end node produces the output.
Large language model nodes generate responses based on input, while prompt nodes allow for more specific answer guidance.
Code nodes process input variables and generate return values, which can be beneficial for users with coding knowledge.
Knowledge nodes use knowledge bases to match information based on user inputs, enhancing the bot's ability to provide accurate responses.
If condition nodes and variable nodes assist with logic and data handling within the workflow.
Plugins can be used as nodes, allowing integration with various services like Reddit, Microsoft Outlook, and Google Search.
Custom plugins can be created to connect to specific APIs, such as an NBA API for game data.
The workflow process involves connecting nodes to create a sequence that processes input and generates a tailored output.
Code blocks within the workflow allow for complex data manipulation and customization of the response.
Large language model nodes take the processed data and format it into a readable and user-friendly response.
The end node formats the final output, presenting the information to the user in a specified manner.
Workflows can significantly improve the quality and accuracy of a bot's responses compared to using only persona prompts.
After implementing a workflow, the bot's response is tailored to the user's query, providing accurate and formatted game results.
Workflows are a powerful feature for customizing bot responses and ensuring the delivery of precise and relevant information.