Features: 1) Add support for .sat suffix fields in search query with phrase_prefix match; 2) Incorporate lenient fuzzy match and prefix match into a combined query logic; 3) Enhance function_score with additional filtering for better query relevance.
Fixes: 1) Handle missing or empty query input with a more explicit check; 2) Resolve potential response errors by catching `NotFoundError` exceptions in search execution. Extra: Refactor code structure to improve readability and modularity, including better slug generation logic and streamlined image URL handling.
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1 changed files with 105 additions and 93 deletions
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@ -30,114 +30,126 @@ SMART_FIELDS = [
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"title.ngram^3",
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"title.phonetic",
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"title.auto^4",
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"name.sat^6",
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"title.sat^4",
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]
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def process_query(query: str = "", request: Request | None = None):
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"""
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Perform a lenient, typo‑tolerant, multi‑index search.
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* Full‑text with fuzziness for spelling mistakes
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* `bool_prefix` for edge‑ngram autocomplete / “icontains”
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"""
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if not query:
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if not (query := query.strip()):
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raise ValueError(_("no search term provided."))
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query = query.strip()
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try:
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q = Q(
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"bool",
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should=[
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Q(
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"multi_match",
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query=query,
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fields=SMART_FIELDS,
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fuzziness="AUTO",
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operator="and",
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),
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Q(
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"multi_match",
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query=query,
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fields=[f for f in SMART_FIELDS if f.endswith(".auto")],
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type="bool_prefix",
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),
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],
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minimum_should_match=1,
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)
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sat_match = Q(
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"multi_match",
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query=query,
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type="phrase_prefix",
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fields=[f for f in SMART_FIELDS if ".sat" in f],
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)
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functions = [
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{
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"gauss": {
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"sales_rank": {
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"origin": 100,
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"scale": 500,
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"offset": 0,
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"decay": 0.3,
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}
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},
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"weight": 3,
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},
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]
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fuzzy_match = Q(
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"multi_match",
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query=query,
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fields=SMART_FIELDS,
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fuzziness="AUTO",
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operator="and",
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)
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boosted = Q(
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"function_score",
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query=q,
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boost_mode="sum",
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score_mode="sum",
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functions=functions,
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)
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prefix_match = Q(
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"multi_match",
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query=query,
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fields=[f for f in SMART_FIELDS if f.endswith(".auto")],
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type="bool_prefix",
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)
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search = (
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Search(index=["products", "categories", "brands", "posts"])
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.query(boosted)
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.extra(size=100)
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)
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response = search.execute()
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combined = Q(
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"bool",
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should=[sat_match, fuzzy_match, prefix_match],
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minimum_should_match=1,
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)
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results: dict = {"products": [], "categories": [], "brands": [], "posts": []}
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for hit in response.hits:
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obj_uuid = getattr(hit, "uuid", None) or hit.meta.id
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obj_name = (
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getattr(hit, "name", None) or getattr(hit, "title", None) or "N/A"
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)
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obj_slug = ""
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raw_slug = getattr(hit, "slug", None)
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if raw_slug:
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obj_slug = raw_slug
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elif hit.meta.index == "brands":
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obj_slug = slugify(obj_name)
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elif hit.meta.index == "categories":
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obj_slug = slugify(f"{obj_name}")
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image_url = None
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idx = hit.meta.index
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if idx == "products" and request:
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prod = get_object_or_404(Product, uuid=obj_uuid)
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first = prod.images.order_by("priority").first()
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if first and first.image:
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image_url = request.build_absolute_uri(first.image.url)
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elif idx == "brands" and request:
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brand = get_object_or_404(Brand, uuid=obj_uuid)
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if brand.small_logo:
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image_url = request.build_absolute_uri(brand.small_logo.url)
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elif idx == "categories" and request:
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cat = get_object_or_404(Category, uuid=obj_uuid)
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if cat.image:
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image_url = request.build_absolute_uri(cat.image.url)
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results[idx].append(
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{
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"uuid": str(obj_uuid),
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"name": obj_name,
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"slug": obj_slug,
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"image": image_url,
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functions = [
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{
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"filter": Q("prefix", **{"name.raw": query.lower()}),
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"weight": 5,
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},
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{
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"gauss": {
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"sales_rank": {
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"origin": 100,
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"scale": 500,
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"offset": 0,
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"decay": 0.3,
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}
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)
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},
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"weight": 3,
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},
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]
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return results
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boosted = Q(
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"function_score",
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query=combined,
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boost_mode="sum",
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score_mode="sum",
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functions=functions,
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)
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search = (
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Search(index=["products", "categories", "brands", "posts"])
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.query(boosted)
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.extra(size=100)
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)
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try:
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response = search.execute()
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except NotFoundError:
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raise Http404
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results = {"products": [], "categories": [], "brands": [], "posts": []}
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for hit in response.hits:
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obj_uuid = getattr(hit, "uuid", None) or hit.meta.id
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obj_name = getattr(hit, "name", None) or getattr(hit, "title", None) or "N/A"
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raw_slug = getattr(hit, "slug", None) or ""
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obj_slug = (
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raw_slug or slugify(obj_name)
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if hit.meta.index in {"brands", "categories"}
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else raw_slug
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)
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image_url = None
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idx = hit.meta.index
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if request:
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if idx == "products":
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prod = get_object_or_404(Product, uuid=obj_uuid)
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first = prod.images.order_by("priority").first()
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image_url = (
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request.build_absolute_uri(first.image.url)
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if first and first.image
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else None
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)
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if idx == "brands":
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brand = get_object_or_404(Brand, uuid=obj_uuid)
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image_url = (
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request.build_absolute_uri(brand.small_logo.url)
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if brand.small_logo
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else None
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)
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if idx == "categories":
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cat = get_object_or_404(Category, uuid=obj_uuid)
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image_url = (
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request.build_absolute_uri(cat.image.url) if cat.image else None
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)
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results[idx].append(
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{
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"uuid": str(obj_uuid),
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"name": obj_name,
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"slug": obj_slug,
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"image": image_url,
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}
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)
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return results
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LANGUAGE_ANALYZER_MAP = {
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"ar": "arabic",
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