Mastering Multi-Agents: Tools, Models, and Coordination
- Authors
- Published on
- Published on
In this riveting episode from Sam Witteveen, the team delves into the intricate world of building multi-agents, a topic as complex as navigating a treacherous mountain pass in a high-performance car. With a focus on tools like Alama, Claude, Gemini, Gradio, and OpenAI, they embark on a journey to showcase the capabilities of small agents with different models, akin to pushing a finely-tuned engine to its limits. The importance of setting up a huggingface token in the environment variables is emphasized, much like ensuring a supercar has the right fuel to unleash its full potential on the track.
As they experiment with various models such as Quen, Gemini, and GPT 40 mini, the team experiences a rollercoaster of results when testing code agents and tool calling agents. Just like a seasoned driver tackling unpredictable terrain, they navigate through the challenges posed by different model sizes, with proprietary models like Claude and Gemini Flash emerging as champions in handling code agents. The integration of Gradio UI adds a touch of finesse to their work, enabling them to effortlessly create text-to-image tools using models like Quen 2.5 Coda, akin to seamlessly shifting gears in a high-performance vehicle.
Transitioning towards the creation of tools for multi-agent systems, the team meticulously defines agents and managed agents, showcasing the intricate dance required to ensure seamless collaboration among these digital entities. The demonstration of a multi-agent setup using GPT 40 mini is akin to orchestrating a symphony, with agents working in harmony to tackle complex tasks like multi-hop queries with the precision of a skilled conductor leading a world-class orchestra. The advanced example featuring multiple agents, specifically a research agent and a managed research agent tailored for a blog writing scenario, highlights the versatility and power of multi-agent systems in conquering diverse challenges with the finesse of a high-performance vehicle dominating the racetrack.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Watch How to make Muilt-Agent Apps with smolagents on Youtube
Viewer Reactions for How to make Muilt-Agent Apps with smolagents
Request for a comparison video on agent frameworks for different scenarios and developer experience
Positive feedback on the clear explanation in the video
Request for advanced use cases videos for Pydantic-AI
Inquiry about the capabilities of a framework in editing long documents beyond token limits
Question about a tool returning fixed temperature values and input validation errors
Seeking advice on resolving a ModuleNotFoundError
Comparison between Smolagents framework and Agency Swarm
Question about the usage of multi-agent models in production by companies like OpenAI and Anthropic
Related Articles
Unveiling Gemini 2.5 TTS: Mastering Single and Multi-Speaker Audio Generation
Discover the groundbreaking Gemini 2.5 TTS model unveiled at Google IO, offering single and multi-speaker text to speech capabilities. Control speech style, experiment with different voices, and craft engaging audio experiences with Gemini's native audio out feature.
Google IO 2025: Innovations in Models and Content Creation
Google IO 2025 showcased continuous model releases, including 2.5 Flash and Gemini Diffusion. The event introduced Image Gen 4 and VO3 video models in the innovative product Flow, revolutionizing content creation and filmmaking. Gemini's integration of MCP and AI Studio refresh highlight Google's commitment to technological advancement and user empowerment.
Nvidia Parakeet: Lightning-Fast English Transcriptions for Precise Audio-to-Text Conversion
Explore the latest in speech-to-text technology with Nvidia's Parakeet model. This compact powerhouse offers lightning-fast and accurate English transcriptions, perfect for quick and precise audio-to-text conversion. Available for commercial use on Hugging Face, Parakeet is a game-changer in the world of transcription.
Optimizing AI Interactions: Gemini's Implicit Caching Guide
Gemini team introduces implicit caching, offering 75% token discount based on previous prompts. Learn how it optimizes AI interactions and saves costs effectively. Explore benefits, limitations, and future potential in this insightful guide.