Multimodal Function Calling with Gemini 3 and Interactions API

2026-02-13 · Source: philschmid.de - RSS feed · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, short

Summary

Google's Multimodal Function Calling, integrated with the Interactions API, enables AI agents to process visual information directly from tool outputs. Unlike standard function calls that return text descriptions, this feature allows tools to return actual image data, which Gemini 3 then processes natively for tasks like describing images, analyzing documents, or making visually informed decisions. The Interactions API provides a unified interface for Gemini models, simplifying state management and tool orchestration for multi-turn agentic workflows. An example demonstrates building a tool to read images from disk, encode them in base64, and return them as part of a `function_result` for Gemini 3 to describe, showcasing a four-step interaction flow from user request to model response.

Key takeaway

For AI engineers building agents that require visual perception, adopting Multimodal Function Calling with the Interactions API can significantly enhance agent capabilities. You should explore integrating tools that return image data directly into your workflows, moving beyond text-only descriptions. This approach enables Gemini 3 to "see" what your tools see, opening up new possibilities for sophisticated visual agents in areas like document processing, UI automation, and image analysis.

Key insights

Multimodal function calling allows AI agents to natively process images returned by tools, enhancing visual understanding.

Principles

• Tools can return raw image data.
• Gemini 3 processes visual content natively.

Method

Define a tool to read image files, implement its execution to base64 encode image data, and integrate it into an agentic loop using the Interactions API for Gemini 3 to process the visual output.

In practice

• Capture UI screenshots for coding agents.
• Analyze browser screenshots for computer use agents.
• Process charts and diagrams from documents.

Topics

• Multimodal Function Calling
• Gemini 3
• Interactions API
• Agentic Workflows
• Tool Orchestration

Best for: AI Engineer, Machine Learning Engineer, Software Engineer

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• Building Smarter Visual Recommendations with Gemini Multimodal Embeddings — Gemini multimodal embeddings offer improved semantic understanding for visual recommendation systems compared to ResNet50 and SigLIP.
• Gemini's busy agentic day at Google I/O — Gemini is evolving into a pervasive, agentic, and multimodal AI engine deeply integrated across Google's product ecosystem.
• Google makes Interactions API the default interface for Gemini models and agents — The Interactions API is Google's new standard for Gemini agents, enabling advanced features and flexible cost/speed options.
• Google Gemini now generates interactive visualizations you can tweak and explore right in the chat — Conversational AI platforms are integrating interactive data visualization directly into chat interfaces.

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Editorial summary, takeaway, and curation by AIssential. Original article published by philschmid.de - RSS feed.