bzAICallLogging-FM

Analyze and Refine AI Interactions in FileMaker

Free Download GitHub

As AI-powered features become more integrated into FileMaker, understanding how AI interactions function behind the scenes is crucial.

bzAICallLogging-FM extends the bzSemanticSearch-FM demo file by incorporating FileMaker’s AI Call Logging script step, providing a structured way to track AI requests, responses, and token usage. This helps analyze AI interactions and refine cosine similarity for better search accuracy.

Learn more about this functionality in the second blog post from our series on Semantic Search, where we explore how AI Call Logging enhances transparency, security, and workflow optimization in FileMaker.

By capturing and storing AI call logs, developers and businesses can monitor system performance, refine AI-driven workflows, and ensure relevant search results with greater efficiency.

AI Call Logging in Action: Track, Analyze, and Optimize AI Interactions

This screenshot showcases bzAICallLogging-FM in action, capturing AI call logs in FileMaker. The log details token usage, similarity thresholds, and iterative semantic searches, helping developers fine-tune AI-driven queries. By analyzing these logs, users can optimize search accuracy, manage costs, and troubleshoot AI behavior efficiently.

Uses of bzAICallLogging-FM

AI Call Tracking & Analysis

Capture detailed logs of AI requests and responses to gain insight into how FileMaker interacts with AI models, helping to fine-tune workflows and improve AI-driven results.

Dynamic Search Optimization

Use AI call logs to evaluate cosine similarity thresholds and refine semantic search accuracy by adjusting parameters for more relevant search results.

Cost-Efficient AI Token Usage

Monitor token consumption per AI request to optimize performance while managing API costs, ensuring a balance between accuracy and efficiency.

Error Handling & Debugging Insights

Leverage AI logs to identify failed searches, track errors, and iterate on improvements, streamlining troubleshooting and reducing time spent on debugging AI-related processes.

Features

Developer Spotlight

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