2 dépôts
Tools for transmitting and analyzing visual content within agentic workflows.
Distinct from Image Data Visualizers: Distinct from Image Data Visualizers: focuses on input processing for vision-capable models rather than debugging tensor data.
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Supervision is a computer vision toolset for normalizing model outputs, managing datasets, and visualizing annotations. It provides a framework to convert predictions from various classification and detection models into a standardized data format to ensure interoperability across different computer vision pipelines. The library features a post-processor for filtering, counting, and tracking detected objects across image frames and video streams. It includes capabilities for large image tiling to improve the detection of small objects and tools for assigning persistent identities to objects t
Includes utilities to read image files or iterate through video frames for processing pipelines.
Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com
Enables vision-capable models to analyze visual information transmitted via URL or base64 encoding.