File size: 8,815 Bytes
a2877a1 237554a 04301d9 8798e5f a2877a1 237554a 921357f 237554a 8ff3919 921357f 237554a 1b5b80c a2877a1 8798e5f dd57cad e7ab1a5 dd57cad e7ab1a5 dd57cad e7ab1a5 dd57cad e7ab1a5 dd57cad 8798e5f 237554a a2877a1 237554a a2877a1 237554a a2877a1 921357f 237554a a2877a1 1b5b80c 237554a 1b5b80c a2877a1 921357f a2877a1 237554a a2877a1 237554a a2877a1 237554a a2877a1 237554a a2877a1 237554a a2877a1 237554a a2877a1 237554a ad8bcc2 237554a ad8bcc2 237554a ad8bcc2 237554a ad8bcc2 237554a ad8bcc2 237554a a2877a1 237554a a2877a1 237554a a2877a1 237554a a2877a1 237554a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 |
# 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]
|