echoChain

echoChain is an innovative tool designed to analyze the degradation of answers as they undergo multiple rewrites by language models. This repository provides a robust framework for measuring how the quality of a generated answer changes through iterative processing cycles, offering insights into the reliability and accuracy of AI-generated text.

Key Features

• Model Feedback Loop: Examine how models alter responses over repeated iterations to assess their stability and coherence.
• Dry-Run Capability: Utilize the dry-run command to simulate the process without executing changes, making it easier to test configurations safely.
• Live Cycle Execution: Carry out a single live cycle analysis to understand immediate effects in real-time.
• Result Analysis: Summarize completed runs for a comprehensive review of the outcomes, enabling a clearer understanding of degradation metrics.

Example Usage

To demonstrate its functionality, the following commands illustrate common operations with echoChain:

Run a dry run with a configuration file:

echochain run --config examples/echochain.toml --dry-run

Execute a live cycle with a specific input:

echochain run --start "Redis uses epoll for I/O" --max-cycles 1 --yes

Analyze the results of a specific run:

echochain analyze runs/RUN_ID

For additional details on flags, configuration options, output files, and exit codes, refer to the usage guide.

Further Resources

• Access the documentation for comprehensive guidelines.
• Review the methodology to understand the analytical techniques utilized in echoChain.
• Explore the contributing guidelines for information on how to contribute to the project.
• Check out an example configuration for quick setup.