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Runtime error
| import logging | |
| import uvicorn | |
| from fastapi import FastAPI, Response, status | |
| from transformers import ( | |
| AutoModelForSequenceClassification, | |
| AutoTokenizer, | |
| pipeline | |
| ) | |
| logging.basicConfig(level=logging.INFO) | |
| app = FastAPI(docs_url="/") | |
| model_name_or_path = "Stratos97/biobert-base-cased-PubMed-Mesh" | |
| model = AutoModelForSequenceClassification.from_pretrained(model_name_or_path) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name_or_path) | |
| pipe = pipeline(task="text-classification", model=model, tokenizer=tokenizer, top_k=None) | |
| async def get_health(): | |
| return {"message": "OK"} | |
| async def data(input_data: dict, response: Response): | |
| try: | |
| # Get the input article (text) | |
| article = input_data["text"] | |
| # Classify the given article | |
| scores = pipe(article)[0] | |
| # Construct the response | |
| results = { | |
| f"article": article, | |
| "scores": {r['label']: r['score'] for r in scores} | |
| } | |
| except Exception as e: | |
| logging.error("Something went wrong ", e) | |
| response.status_code = status.HTTP_500_INTERNAL_SERVER_ERROR | |
| return {"STATUS": "Error", "RESPONSE": {}} | |
| return {"STATUS": "OK", "RESPONSE": results} | |
| if __name__ == "__main__": | |
| uvicorn.run("api:app", reload=True, port=6000, host="0.0.0.0") | |