Agent Logging provides a unified logging framework for AI agent frameworks and custom workflows. It intercepts and records each stage of an agent’s execution—prompt generation, tool invocation, LLM response, and final output—along with timestamps and metadata. Logs can be exported in JSON, CSV, or sent to monitoring services. The library supports customizable log levels, hooks for integration with observability platforms, and visualization tools to trace decision paths. With Agent Logging, teams gain insights into agent behavior, spot performance bottlenecks, and maintain transparent records for auditing.

Rhippo revolutionizes the way teams collaborate with their LLM chatbots. By creating a 'brain' that injects relevant context into your prompts and maintains an updating knowledge database, it ensures that only important project information is shared. The setup is swift, taking less than 10 minutes, and includes integrations with Slack and Google Drive for seamless communication. Rhippo promises improved responses with state-of-the-art embedding models, guaranteeing data transparency through Google Drive.