Overcoming the Challenges of Building Agentic AI

Join Daniele Bernardi, CEO of Toolhouse AI and Dan Loman, Data and AI Practitioner at Groq for a technical webinar on the challenges of building agentic AI. They'll provide a high level overview of agentic architecture, highlight the current challenges of building agents (including building tools, prompting, and latency), explain how you can overcome them with Toolhouse AI and Groq, and share a demo.
Using Toolhouse for Tool Use with Groq API:
github.com/gro...
Groq API Cookbook:
github.com/gro...
To get access and the $150 worth of credits
join.toolhouse.ai
Toolhouse generates an API directly in the onboarding experience. Users can generate new API Keys here:
app.toolhouse....
Direct link to install Code Interpreter:
app.toolhouse....

[@sirishkumar-m5z]

Building agentic AI can be complex. Explore alternative tools to overcome challenges and optimize your development process. #AIAgents #Innovation

[@rajaakhil588]

This is really great, but I believe it would be much more effective if there were an in-built option to select the most probable tools for the current situation and keep only those in context.
Rationale:
In my current application, I have around 15 tools, and sending all of them to the LLM for each call is not optimal. This approach quickly hits the token limit imposed by Groq within just a few seconds of running a conversational AI.

[@iamdaniele]

We're releasing functionality to exactly overcome the issues you describe. This functionality will allow the LLM to work with just a subset of all your installed tools, based on the task at hand. For example, if you are building a financial analyst app with two steps (retrieval and forecasting), you can feed just a the retrieval tools to the first step and just the forecasting tools to the second. This functionality is coming very soon - make sure to sign up and check out Toolhouse in the next coming days for an update!