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| import gradio as gr | |
| from datasets import load_dataset | |
| # Load the dataset from Hugging Face | |
| dataset = load_dataset("princeton-nlp/SWE-bench") | |
| # Define a function to display a sample from the dataset | |
| def get_result(id,name,mk): | |
| if name == "": | |
| return get_sample(id) | |
| return get_sample_filter(name) | |
| def get_sample(sample_id): | |
| try: | |
| # Get the sample from the dataset | |
| sample = dataset['test'][int(sample_id)] | |
| return sample | |
| except: | |
| return {"error": "Invalid sample ID"} | |
| def get_sample_filter(repo_name): | |
| try: | |
| # Find the sample with the specified repository name in 'train' dataset | |
| result = [] | |
| for sample in dataset['test']: | |
| if repo_name in sample["repo"]: | |
| issue_id=sample["instance_id"].split("-")[1] | |
| repo=sample["repo"] | |
| issue_url=f"https://github.com/{sample['repo']}/issues/{issue_id}" | |
| base_commit=sample["base_commit"] | |
| result.append({"repo":repo,"base_commit":base_commit,"issue_url":issue_url}) # Return the found sample as a response | |
| return result | |
| except Exception as e: | |
| return {"error": f"Invalid repository name or error occurred: {str(e)}"} | |
| # Create the Gradio interface | |
| block = gr.Markdown("[https://huggingface.co/datasets/princeton-nlp/SWE-bench](https://huggingface.co/datasets/princeton-nlp/SWE-bench)") | |
| slider = gr.Slider(label="Select ID", minimum=0, maximum=2248, step=1, value=0) | |
| input_box=gr.Textbox(lines=1, placeholder="Enter sample ID (integer)") | |
| iface = gr.Interface( | |
| fn=get_result, | |
| #inputs=gr.Textbox(lines=1, placeholder="Enter sample ID (integer)"), | |
| inputs=[slider,input_box,block], | |
| outputs=gr.JSON(), | |
| title="SWE-bench Dataset Viewer", | |
| description="Enter a sample ID to view the corresponding data from the SWE-bench dataset." | |
| ) | |
| # Launch the interface | |
| if __name__ == "__main__": | |
| iface.launch(share=True) |