How to structure and analyze AI model interaction results with interactive transcript inspection

How to structure and analyze AI model interaction results with interactive transcript inspection

This task can be performed using Bloom

Bloom: instantly evaluate behaviors for safer AI development

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Bloom

Bloom is an open-source framework for automated behavior evaluation of large language models, generating configurable interaction suites from seed configurations. It helps safety researchers probe behaviors like bias or sycophancy, log structured results, and inspect transcripts through an interactive viewer.

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What to expect from an ideal product

  1. Generate organized interaction suites from basic settings to create consistent test scenarios for evaluating AI model behaviors across different conditions
  2. Automatically log all model responses in structured formats that make it easy to spot patterns, track changes, and compare results between different testing runs
  3. Use the built-in interactive viewer to examine individual conversations and transcripts without switching between multiple tools or losing context
  4. Set up custom evaluation criteria that match your specific research needs, whether you're checking for bias, harmful outputs, or inconsistent reasoning
  5. Export and share findings with your team through standardized reports that clearly show which behaviors need attention and how severe the issues are

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