Hooks and Multi-Agent Workflow (Developers)
Hooks is a new functionality added to HAT V2. It enables multiple specialized agents to work together seamlessly and to provide faster, more accurate responses to give the agent the ability to handle more complex tasks and multiple use cases.
Hooks allows the agent to tap into several specialized agents working in the background, helping to produce a more accurate and intelligent response delivered by the agent.
🖇️ How Do Hooks Work?
Pre-hooks: These steps happen before the agents begin working. They are responsible for preparing the input from the user. This can include:
Formatting the input: Making sure the user’s query is in a clean and structured format that the agents can understand.
Extracting metadata: Identifying important details (like keywords or user intent) that will help agents process the request.
Intent analysis: Understanding what the user wants—whether it's information, an action, or a response based on specific context.
Orchestrator: The orchestrator is the central manager that sends the user’s formatted request to the appropriate agents. It makes sure the agents collaborate effectively, and each one works on the part of the query he's best suited for.
Workspace: In the workflow, there are multiple agents with different specializations. For example:
One agent might be great at fetching real-time data (e.g., stock prices, weather).
Another agent might specialize in understanding the user's intent.
A third could focus on generating human-like text for responses. These agents operate independently, but they work together through the orchestrator to respond to the user.
Post-hooks: After the agents have completed their tasks, post-hooks handle the final steps. This could include:
Generating visual content like images or charts if needed.
Notifying other agents about the response, such as sending a reply to the user on Telegram, Discord, or Twitter.
🖇️ How Do Hooks Make Your Agent Better?
Specialization: Each agent in the background can focus on what he does best. For example, one agent could fetch live data, while another processes user intent. This makes your agent smarter and more precise in handling different types of tasks.
Faster Responses: Since agents can work simultaneously (in parallel), the workflow is much faster. Pre-hooks format the input, agents perform their tasks in parallel, and post-hooks finalize the output, all leading to quicker responses for users.
Flexibility: If you need your agent to do something new—like fetching data from a different API or adding a new feature—you can add or modify agents without disrupting the entire system. This makes your agent more adaptable to changing needs.
More Quality Conversations: By using multiple agents with different specializations, your system can give more accurate, detailed, and relevant responses. Instead of one agent doing everything, each one handles a part of the task, which results in more tailored and smarter responses.
Scalability: As your needs grow, you can scale your agent by adding more specialized agents. For example, you could introduce agents for new tools, data sources, or workflows, making it easier to expand your agent’s functionality over time.
Last updated