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README.md

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 <img width="1000px" alt="" src="figures/figure_1_the_pipeline_of_ProGraph_benchmark_construction.jpg">
 
 #### The pipeline of LLM4Graph dataset construction and corresponding model enhancement.
-Code datasets. We construct two code datasets in the form of QA pairs. The questions in both datasets are the same, but the answers differ. In the simpler dataset, each answer only contains Python code. Inspired by Chain of Thought (CoT) [55], each answer in the more complex dataset additionally includes relevant APIs and their documents as prefixes. This modification can facilitate open-source models to utilize document information more effectively. We name the above code datasets as Code (QA) and Doc+Code (QA), respectively. Unlike the hand-crafted benchmark, problems in the code datasets are automatically generated and each contains only one key API.
 
 <img width="1000px" alt="" src="figures/figure_2_the_pipeline_of_LLM4Graph_dataset_construction_and_corresponding_model_enhancement.jpg">