import json
import os
import sys
from datetime import datetime
from src.evaluation.perplexity_eval import evaluate_perplexity, create_perplexity_result
from src.envs import EVAL_RESULTS_PATH, API, RESULTS_REPO

def run_dynamic_perplexity_eval(model_name, revision="main", precision="float16"):
    """
    Run perplexity evaluation and save results.
    """
    try:
        sys.stderr.write(f"Starting dynamic evaluation for {model_name}\n")
        sys.stderr.flush()
        
        # Run evaluation
        sys.stderr.write("Running perplexity evaluation...\n")
        sys.stderr.flush()
        perplexity_score = evaluate_perplexity(model_name, revision)
        sys.stderr.write(f"Perplexity evaluation completed: {perplexity_score}\n")
        sys.stderr.flush()
        
        # Create result structure
        result = create_perplexity_result(model_name, revision, precision, perplexity_score)
        sys.stderr.write(f"Created result structure: {result}\n")
        sys.stderr.flush()
        
        # Save result file
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        result_filename = f"results_{model_name.replace('/', '_')}_{timestamp}.json"
        
        # Create directory structure
        org, model = model_name.split("/") if "/" in model_name else ("", model_name)
        result_dir = os.path.join(EVAL_RESULTS_PATH, org) if org else EVAL_RESULTS_PATH
        os.makedirs(result_dir, exist_ok=True)
        
        result_path = os.path.join(result_dir, result_filename)
        sys.stderr.write(f"Saving result to: {result_path}\n")
        sys.stderr.flush()
        
        with open(result_path, "w") as f:
            json.dump(result, f, indent=2)
        
        sys.stderr.write("Result file saved locally\n")
        sys.stderr.flush()
        
        # Upload to Hugging Face dataset
        try:
            sys.stderr.write(f"Uploading to HF dataset: {RESULTS_REPO}\n")
            sys.stderr.flush()
            
            API.upload_file(
                path_or_fileobj=result_path,
                path_in_repo=result_path.split("eval-results/")[1],
                repo_id=RESULTS_REPO,
                repo_type="dataset",
                commit_message=f"Add perplexity results for {model_name}",
            )
            sys.stderr.write("Upload completed successfully\n")
            sys.stderr.flush()
        except Exception as upload_error:
            sys.stderr.write(f"Upload failed: {upload_error}\n")
            sys.stderr.flush()
            # Don't fail the whole process if upload fails
        
        return True, perplexity_score
        
    except Exception as e:
        import traceback
        sys.stderr.write(f"Error in run_dynamic_perplexity_eval: {e}\n")
        sys.stderr.write(f"Traceback: {traceback.format_exc()}\n")
        sys.stderr.flush()
        return False, str(e)