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# loader.py
import os
import json
from typing import List, Dict, Any

from huggingface_hub import hf_hub_download, HfApi
DATASET_REPO_ID = "Heng2004/lao-science-qa-store" 
DATASET_FILENAME = "manual_qa.jsonl"

import qa_store

# Base paths (make them relative to this file)
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
DATA_DIR = os.path.join(BASE_DIR, "data")

CURRICULUM_PATH = os.path.join(DATA_DIR, "M_1_U_1.jsonl")
MANUAL_QA_PATH = os.path.join(DATA_DIR, "manual_qa.jsonl")

GLOSSARY_PATH = os.path.join(DATA_DIR, "glossary.jsonl")


def sync_upload_manual_qa() -> str:
    """
    Upload the local manual_qa.jsonl back to the Hugging Face Dataset repo.
    Returns a status message string to display in the UI.
    """
    if not DATASET_REPO_ID or "YOUR_USERNAME" in DATASET_REPO_ID:
        return "⚠️ Upload Skipped (Repo ID not set)"

    print(f"[INFO] Uploading {DATASET_FILENAME} to {DATASET_REPO_ID}...")
    try:
        from huggingface_hub import HfApi
        
        api = HfApi()
        
        api.upload_file(
            path_or_fileobj=MANUAL_QA_PATH,
            path_in_repo=DATASET_FILENAME,
            repo_id=DATASET_REPO_ID,
            repo_type="dataset",
            commit_message="Teacher Panel: Updated Q&A data"
        )
        print("[INFO] Upload success!")
        return "☁️ Cloud Upload Success"
        
    except Exception as e:
        print(f"[ERROR] Could not upload manual_qa.jsonl: {e}")
        return f"⚠️ Cloud Upload Failed: {e}"
        
def sync_download_manual_qa() -> None:
    """
    Download the latest manual_qa.jsonl from the Hugging Face Dataset repo
    at startup so we don't lose previous teacher edits.
    """
    if not DATASET_REPO_ID or "YOUR_USERNAME" in DATASET_REPO_ID:
        print("[WARN] DATASET_REPO_ID is not set. Skipping download.")
        return

    print(f"[INFO] Downloading {DATASET_FILENAME} from {DATASET_REPO_ID}...")
    try:
        from huggingface_hub import hf_hub_download
        
        # Download file to a temporary path first
        downloaded_path = hf_hub_download(
            repo_id=DATASET_REPO_ID,
            filename=DATASET_FILENAME,
            repo_type="dataset",
            token=os.environ.get("HF_TOKEN") # Uses the Space's system token
        )
        
        # Copy it to our local data folder
        import shutil
        target_path = MANUAL_QA_PATH
        shutil.copy(downloaded_path, target_path)
        print("[INFO] Download success!")
        
    except Exception as e:
        print(f"[WARN] Could not download manual_qa.jsonl: {e}")
        print("[INFO] Starting with empty or local manual_qa.jsonl instead.")

def load_curriculum() -> None:
    """
    Load official textbook JSONL into qa_store.ENTRIES and AUTO_QA_KNOWLEDGE.
    """
    qa_store.ENTRIES.clear()
    qa_store.AUTO_QA_KNOWLEDGE.clear()

    if not os.path.exists(CURRICULUM_PATH):
        print(f"[WARN] Curriculum file not found: {CURRICULUM_PATH}")
        qa_store.RAW_KNOWLEDGE = "ຍັງບໍ່ມີຂໍ້ມູນປະຫວັດສາດຖືກໂຫຼດ."
        return


    with open(CURRICULUM_PATH, "r", encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            try:
                obj: Dict[str, Any] = json.loads(line)
            except json.JSONDecodeError:
                print("[WARN] Skipping invalid JSON line in curriculum file.")
                continue


            if "text" not in obj:
                continue

            qa_store.ENTRIES.append(obj)

            for pair in obj.get("qa", []):
                q = (pair.get("q") or "").strip()
                a = (pair.get("a") or "").strip()
                if not q or not a:
                    continue
                norm_q = qa_store.normalize_question(q)
                qa_store.AUTO_QA_KNOWLEDGE.append(
                    {
                        "norm_q": norm_q,
                        "q": q,
                        "a": a,
                        "source": "auto",
                        "id": obj.get("id", ""),
                    }
                )

    if qa_store.ENTRIES:
        qa_store.RAW_KNOWLEDGE = "\n\n".join(e["text"] for e in qa_store.ENTRIES)
    else:
        qa_store.RAW_KNOWLEDGE = "ຍັງບໍ່ມີຂໍ້ມູນປະຫວັດສາດທີ່ອ່ານໄດ້."


def load_glossary() -> None:
    """Load glossary entries into qa_store.GLOSSARY."""
    qa_store.GLOSSARY.clear()

    if not os.path.exists(GLOSSARY_PATH):
        print(f"[WARN] Glossary file not found: {GLOSSARY_PATH}")
        return

    with open(GLOSSARY_PATH, "r", encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            try:
                obj = json.loads(line)
            except json.JSONDecodeError:
                print("[WARN] Skipping invalid glossary JSON line")
                continue
            qa_store.GLOSSARY.append(obj)

    print(f"[INFO] Loaded {len(qa_store.GLOSSARY)} glossary terms.")


def load_manual_qa() -> None:
    """
    Load manual_qa.jsonl into qa_store.MANUAL_QA_LIST and MANUAL_QA_INDEX.
    """
    qa_store.MANUAL_QA_LIST.clear()
    qa_store.MANUAL_QA_INDEX.clear()
    max_num = 0

    if not os.path.exists(MANUAL_QA_PATH):
        print(f"[WARN] Manual QA file not found: {MANUAL_QA_PATH}")
        qa_store.NEXT_MANUAL_ID = 1
        return


    with open(MANUAL_QA_PATH, "r", encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            try:
                obj = json.loads(line)
            except json.JSONDecodeError:
                print("[WARN] Skipping invalid JSON line in manual QA file.")
                continue


            q = (obj.get("q") or "").strip()
            a = (obj.get("a") or "").strip()
            if not q or not a:
                continue

            entry_id = str(obj.get("id") or "")
            if not entry_id:
                max_num += 1
                entry_id = f"manual_{max_num:04d}"

            # track biggest number in id
            import re as _re

            m = _re.search(r"(\d+)$", entry_id)
            if m:
                max_num = max(max_num, int(m.group(1)))

            norm_q = qa_store.normalize_question(q)
            entry = {
                "id": entry_id,
                "q": q,
                "a": a,
                "norm_q": norm_q,
            }
            qa_store.MANUAL_QA_LIST.append(entry)
            qa_store.MANUAL_QA_INDEX[norm_q] = entry

    qa_store.NEXT_MANUAL_ID = max_num + 1 if max_num > 0 else 1


# loader.py

def generate_new_manual_id() -> str:
    """
    Generate the smallest free manual_XXXX ID based on the
    current MANUAL_QA_LIST (so gaps like 11 after delete
    are reused).
    """
    import re as _re

    used_nums = set()

    # collect all numbers that are already used in IDs
    for e in qa_store.MANUAL_QA_LIST:
        raw_id = str(e.get("id") or "")
        m = _re.search(r"(\d+)$", raw_id)
        if m:
            used_nums.add(int(m.group(1)))

    # find the smallest positive integer that is not used
    i = 1
    while i in used_nums:
        i += 1

    # keep the global counter roughly in sync (optional)
    qa_store.NEXT_MANUAL_ID = i + 1

    return f"manual_{i:04d}"



def save_manual_qa_file() -> None:
    """
    Persist MANUAL_QA_LIST to data/manual_qa.jsonl.
    """
    os.makedirs(os.path.dirname(MANUAL_QA_PATH), exist_ok=True)
    with open(MANUAL_QA_PATH, "w", encoding="utf-8") as f:
        for e in qa_store.MANUAL_QA_LIST:
            obj = {"id": e["id"], "q": e["q"], "a": e["a"]}
            f.write(json.dumps(obj, ensure_ascii=False) + "\n")


def rebuild_combined_qa() -> None:
    """
    Combine auto and manual QA into QA_INDEX & ALL_QA_KNOWLEDGE.
    Manual answers override auto ones if same normalized question.
    """
    qa_store.QA_INDEX.clear()
    qa_store.ALL_QA_KNOWLEDGE.clear()

    # auto first
    for item in qa_store.AUTO_QA_KNOWLEDGE:
        norm_q = item["norm_q"]
        qa_store.QA_INDEX[norm_q] = item["a"]
        qa_store.ALL_QA_KNOWLEDGE.append(item)

    # manual overrides
    for e in qa_store.MANUAL_QA_LIST:
        item = {
            "norm_q": e["norm_q"],
            "q": e["q"],
            "a": e["a"],
            "source": "manual",
            "id": e["id"],
        }
        qa_store.QA_INDEX[item["norm_q"]] = item["a"]
        qa_store.ALL_QA_KNOWLEDGE.append(item)


def manual_qa_table_data() -> List[List[str]]:
    """
    Table rows for Teacher Panel.
    """
    return [[e["id"], e["q"], e["a"]] for e in qa_store.MANUAL_QA_LIST]