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Paul Gauthier 2023-06-30 13:44:58 -07:00
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docs/benchmarks.md
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@ -70,7 +70,7 @@ The goal is to read the instructions, implement the provided functions/class ske
and pass all the unit tests. The benchmark measures what percentage of
the 133 exercises are completed successfully, with all the associated unit tests passing.
To run the test, aider sends GPT the Exercism instructions followed by:
To complete an exercise, aider sends GPT the Exercism instructions followed by:
```
Use the above instructions to modify the supplied files: {file_list}
@ -90,7 +90,7 @@ Fix the code in {file_list} to resolve the errors.
GPT gets this second chance to fix the implementation because
many of the unit tests check for specifics that are not
clearly called out in the instructions.
called out in the instructions.
For example, many tests want to see
[specific phrases in ValueErrors](https://github.com/exercism/python/blob/f6caa44faa8fb7d0de9a54ddb5c6183e027429c6/exercises/practice/queen-attack/queen_attack_test.py#L31)
raised by
@ -190,7 +190,7 @@ format requests original/updated edits to be returned using the function call AP
}
```
## ChatGPT function calls
## GPT-3.5 hallucinates function calls?
GPT-3.5 was very prone to ignoring the JSON Schema that specified valid functions,
and would often return a completely invalid `function_call` fragment with `name="python"`.