from fastapi import APIRouter, HTTPException import random from datasets import load_dataset from huggingface_hub import HfApi, dataset_info import os router = APIRouter(tags=["benchmark"]) @router.get("/benchmark-questions/{session_id}") async def get_benchmark_questions(session_id: str): """ Get example questions from the generated benchmark Args: session_id: Session ID for the benchmark Returns: Dictionary with sample questions from the dataset """ try: # Dataset path on Hugging Face dataset_repo_id = f"yourbench/yourbench_{session_id}" # Initialize response response = { "success": False, "questions": [], "dataset_url": f"https://huggingface.co/datasets/{dataset_repo_id}" } # Try to load the dataset questions = [] try: # Try to load single-shot questions directly with the config name single_dataset = load_dataset(dataset_repo_id, 'single_shot_questions') if single_dataset and len(single_dataset['train']) > 0: # Take all questions starting from index 1 (avoiding the first question) start_idx = 1 for idx in range(start_idx, len(single_dataset['train'])): questions.append({ "id": str(idx), "question": single_dataset['train'][idx].get("question", ""), "answer": single_dataset['train'][idx].get("self_answer", "No answer available"), "type": "single_shot" }) print(f"Loaded {len(questions)} single-shot questions") except Exception as e: print(f"Error loading single-shot questions: {str(e)}") # If we couldn't load any questions, the dataset might not exist if len(questions) == 0: # Check if we have a directory for this session locally as fallback session_dir = os.path.join("uploaded_files", session_id) if not os.path.exists(session_dir): raise HTTPException(status_code=404, detail="Dataset not found") # Update the response response["success"] = len(questions) > 0 response["questions"] = questions return response except HTTPException: # Re-raise HTTP exceptions raise except Exception as e: return { "success": False, "error": f"Error retrieving benchmark questions: {str(e)}" }