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Mixture of Experts
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name: SWE-bench Pro
description: >
SWE-bench Pro is a benchmark for evaluating AI models on real-world software
engineering tasks. It contains 100 problems from various open-source repositories
across multiple programming languages (Go, Python, JavaScript, TypeScript).
Each problem includes a repository, base commit, patch, test patch, and problem
statement.
evaluation_framework: inspect-ai
tasks:
- id: swe-bench-pro
config: default
split: test
field_spec:
input: problem_statement
target: patch
choices:
- repo
- instance_id
- base_commit
- test_patch
- requirements
- interface
- repo_language
- fail_to_pass
- pass_to_pass
- issue_specificity
- issue_categories
- before_repo_set_cmd
- selected_test_files_to_run
- dockerhub_tag
solvers:
- name: system_message
args:
template: |
You are an expert software engineer. Given a problem statement and repository context,
generate the correct patch to fix the issue.
Consider:
1. The repository structure and language
2. The base commit and changes needed
3. Test requirements and validation
- name: generate
scorers:
- name: model_graded_fact
args:
model: openai/o3-mini