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| from subprocess import run | |
| import gradio as gr | |
| from huggingface_hub import snapshot_download | |
| from corporate_emission_reports.inference import extract_emissions | |
| run(["sh", "install-llamacpp.sh"]) | |
| MODEL_PATH = snapshot_download("nopperl/emissions-extraction-lora-merged-GGUF") | |
| def predict(input_method, document_file, document_url): | |
| document_path = document_file if input_method == "File" else document_url | |
| emissions = extract_emissions(document_path, MODEL_PATH, model_name="ggml-model-Q5_K_M.gguf") | |
| return emissions.model_dump_json() | |
| with open("description.md", "r") as f: | |
| description = f.read().strip() | |
| with open("article.md", "r") as f: | |
| article = f.read().strip() | |
| interface = gr.Interface( | |
| predict, | |
| inputs=[gr.Radio(choices=["File", "URL"], value="File"), gr.File(type="filepath", file_types=[".pdf"], file_count="single", label="Report File"), gr.Textbox(label="Report URL")], | |
| outputs=gr.JSON(), | |
| description=description, | |
| examples = [ | |
| ["URL", None, "https://www.deutsche-boerse.com/resource/blob/3373890/1cdeb942b1a02ce3495e25240dfdfe81/data/DBG-Detailed-GRI-index-Deutsche-Bo%CC%88rse-Group-AR-2022.pdf"], | |
| ["URL", None, "https://mpmaterials.com/downloads/MP_MATERIALS_2021_ESG_REPORT_A.pdf"], | |
| ], | |
| article=article, | |
| analytics_enabled=False, | |
| cache_examples=False, | |
| ) | |
| interface.queue().launch() | |