Multi Modal Researcher
A Multi Modal Researcher is an AI agent built on Google’s Gemini 2.5 models and orchestrated through the LangGraph framework. The system is designed to conduct comprehensive investigations by processing and analyzing multiple data types simultaneously, including text, images, and other modalities. This multi-modal capability enables the agent to extract insights from complex information sources that would be difficult to analyze through text alone.
Architecture and Components
The agent leverages Gemini 2.5’s native multi-modal capabilities to understand and reason across different input types. LangGraph provides the orchestration layer, managing the workflow and state transitions as the agent progresses through its investigation phases. This combination allows the system to maintain context and coordinate complex reasoning tasks across multiple steps.
Investigation Capabilities
The Multi Modal Researcher performs systematic investigations by integrating information from diverse sources. By processing multiple modalities, it can cross-reference visual information with textual data, identify patterns across different data types, and generate comprehensive outputs that reflect this integrated analysis. The framework supports iterative investigation cycles where findings can be refined and validated through multiple passes of analysis.