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SPADE (System for Prompt Analysis and Delta-Based Evaluation)

This is the code for the paper SPADE: Auto-Generated Assertions for Large Language Model Pipelines.

The SPADE pipeline has the following steps:

1. Decomposing a list of prompts and an example into a set of prompt deltas, assertion concepts, and candidate assertions. This is in candidate_gen.py.

2. Generating a set of candidate assertions for each prompt delta. This is also in candidate_gen.py (uses a helper function in assertion_gen.py).

3. Generates synthetic data and evaluates the assertions (execute_assertions.py). The user should label the synthetic data responses as correct or incorrect.

4. Evaluates subsumption of the assertions (check_subsumes.py).

5. Runs the assertion selection algorithm (`optimizer.py``).

All the experiments live in paper_experiments/ and have a notebook for each experiment. To run any of the experiments (leveraging cached data so you don't need to run any LLMs), run the pipeline.ipynb notebook in the root directory, using the correct experiment name.