import os
import json
from datetime import datetime, timezone

# Use local relative paths to avoid optional dependencies during generation
EVAL_RESULTS_PATH = "eval-results"
EVAL_REQUESTS_PATH = "eval-queue"

# Leaderboard data provided by user
MODELS = [
    {"name": "Intern-S1", "type": "Open", "scores": [15.74, 38.09, 28.79, 29.02, 28.87]},
    {"name": "Intern-S1-mini", "type": "Open", "scores": [11.06, 36.04, 16.97, 12.42, 16.84]},
    {"name": "Qwen3-VL-235B-A22B", "type": "Open", "scores": [11.97, 39.28, 28.41, 30.30, 31.62]},
    {"name": "Qwen3-Max", "type": "Open", "scores": [15.38, 39.83, 33.21, 33.62, 37.80]},
    {"name": "Qwen3-8B", "type": "Open", "scores": [8.18, 35.78, 18.45, 9.96, 23.37]},
    {"name": "Llama-4-Scout", "type": "Open", "scores": [7.86, 29.72, 20.37, 21.66, 25.77]},
    {"name": "GPT-4o", "type": "Closed", "scores": [7.86, 35.95, 26.94, 31.31, 32.30]},
    {"name": "GPT-4.1", "type": "Closed", "scores": [11.32, 36.49, 34.32, 36.63, 38.49]},
    {"name": "GPT-5", "type": "Closed", "scores": [14.47, 55.40, 29.89, 16.31, 38.14]},
    {"name": "GPT-5.1", "type": "Closed", "scores": [11.64, 47.12, 31.00, 22.77, 34.02]},
    {"name": "o3", "type": "Closed", "scores": [12.89, 46.07, 31.73, 30.04, 32.65]},
    {"name": "o4-mini", "type": "Closed", "scores": [11.95, 40.78, 35.79, 28.86, 33.33]},
    {"name": "Gemini-2.5-Flash", "type": "Closed", "scores": [10.69, 39.13, 21.03, 18.55, 34.36]},
    {"name": "Gemini-2.5-Pro", "type": "Closed", "scores": [15.09, 39.95, 22.51, 22.05, 41.24]},
    {"name": "Gemini-3-Pro", "type": "Closed", "scores": [18.48, 39.68, 36.64, 32.45, 41.92]},
    {"name": "Claude-Opus-4.1", "type": "Closed", "scores": [12.93, 40.29, 34.69, 25.38, 38.83]},
    {"name": "Claude-Sonnet-4.5", "type": "Closed", "scores": [13.84, 43.20, 35.79, 30.15, 37.80]},
    {"name": "Grok-4", "type": "Closed", "scores": [13.31, 37.12, 33.71, 29.01, 30.24]},
]

# Task keys must match Tasks Enum in src/about.py
TASK_KEYS = [
    "deep_research",
    "idea_generation",
    "dry_experiment",
    "wet_experiment",
    "experimental_reasoning",
]

# Convert percentages to decimals expected by read_evals (it multiplies by 100)
def pct_to_decimal(p):
    return round(p / 100.0, 6)

def ensure_dir(p):
    os.makedirs(p, exist_ok=True)

def write_result_json(org, model, scores):
    model_full = f"{org}/{model}"
    # Place each model's JSON in its own subfolder under eval-results
    model_dir = os.path.join(EVAL_RESULTS_PATH, org, model)
    ensure_dir(model_dir)

    # Minimal config expected by read_evals.py
    cfg = {
        "model_dtype": "float16",
        "model_name": model_full,
        "model_sha": "",
    }

    # Build results mapping
    results = {}
    for key, score in zip(TASK_KEYS, scores):
        results[key] = {"acc": pct_to_decimal(score)}

    payload = {
        "config": cfg,
        "results": results,
    }

    # Filename pattern is flexible; read_evals walks directories and reads all JSONs
    ts = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
    out_path = os.path.join(model_dir, f"results_{ts}.json")
    with open(out_path, "w", encoding="utf-8") as f:
        json.dump(payload, f, ensure_ascii=False, indent=2)
    return out_path

def write_request_json(org, model, model_type):
    # Ensure request file lives under eval-queue/{org}/
    org_dir = os.path.join(EVAL_REQUESTS_PATH, org)
    ensure_dir(org_dir)

    model_full = f"{org}/{model}"
    now = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")

    # Model type label must be parsable by ModelType.from_str
    type_label = "🔓 : Open" if model_type == "Open" else "🔒 : Closed"

    entry = {
        "model": model_full,
        "base_model": "",
        "revision": "main",
        "precision": "float16",
        "weight_type": "Original",
        "status": "FINISHED",
        "submitted_time": now,
        "model_type": type_label,
        "likes": 0,
        "params": 0,
        "license": "?",
        "private": False,
    }

    # File naming convention similar to submit.py
    out_path = os.path.join(org_dir, f"{model}_eval_request_False_float16_Original.json")
    with open(out_path, "w", encoding="utf-8") as f:
        json.dump(entry, f, ensure_ascii=False, indent=2)
    return out_path

def main():
    org = "sgi-bench"
    ensure_dir(EVAL_RESULTS_PATH)
    ensure_dir(EVAL_REQUESTS_PATH)

    result_paths = []
    request_paths = []

    for m in MODELS:
        res_path = write_result_json(org, m["name"], m["scores"])
        req_path = write_request_json(org, m["name"], m["type"])
        result_paths.append(res_path)
        request_paths.append(req_path)

    print("Generated result JSONs:")
    for p in result_paths:
        print("  -", p)
    print("Generated request JSONs:")
    for p in request_paths:
        print("  -", p)

if __name__ == "__main__":
    main()