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@@ -1,94 +1,139 @@
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"snippet": "...nal infection or intraabdominal abscess - Lymphatic spread - *Burkholderia pseudomallei* (causing melioidosis), endemic in..."
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"Benign Neoplasms",
"Adrenal Cyst"
],
"authors": [
{
"key": "c3463c5c-31d3-4489-bbfe-6b895abdb86d",
"value": "Mitchell Tublin, MD"
}
],
"pageKeywords": "Genitourinary, Diagnosis, Adrenal, Benign Neoplasms, Adrenal Cyst",
"reasons": [
"Content"
],
"snippet": "...om preexisting vascular malformation or obstructed, ectatic lymphatic channels - Thin rim calcification typical - Epitheli..."
},
{
"path": "docs_md/articles/hydrocephalus_e9481739-278e-4682-ab1e-4326a77c3d0c.md",
"title": "Hydrocephalus",
"docid": "e9481739-278e-4682-ab1e-4326a77c3d0c",
"breadcrumbs": [
"Pediatrics",
"Diagnosis",
"Pediatric Neuroradiology",
"Brain",
"Anatomy-Based Diagnoses",
"Ventricles and Cisterns",
"Hydrocephalus"
],
"authors": [
{
"key": "838e1722-2479-4fbd-a5fe-d965980a1a2c",
"value": "Blaise V. Jones, MD"
}
],
"pageKeywords": "Pediatrics, Diagnosis, Pediatric Neuroradiology, Brain, Anatomy-Based Diagnoses, Ventricles and Cisterns, Hydrocephalus",
"reasons": [
"Content"
],
"snippet": "...Extracellular, extravascular fluid in brain is managed by glymphatic system - CSF circulates from within ventricles → subarachnoid space →..."
},
{
"path": "docs_md/articles/inner-ear-lesion-adult_e5bbf757-d77a-4546-a848-d1a1a64cb230.md",
"title": "Inner Ear Lesion, Adult",
"docid": "e5bbf757-d77a-4546-a848-d1a1a64cb230",
"breadcrumbs": [ "breadcrumbs": [
"Head and Neck", "Head and Neck",
"Differential Diagnosis", "Differential Diagnosis",
"Temporal Bone", "Temporal Bone",
"Anatomically Based Differentials", "Anatomically Based Differentials",
"Facial Nerve Lesion, Temporal Bone" "Inner Ear Lesion, Adult"
], ],
"authors": [ "authors": [
{ {
"key": "eef2f839-5706-47b9-89c3-60d8315b2b3a", "key": "d19354f3-7ff2-495a-ad3f-064122e45602",
"value": "Nicholas A. Koontz, MD" "value": "Bernadette L. Koch, MD"
} }
], ],
"pageKeywords": "Head and Neck, Differential Diagnosis, Temporal Bone, Anatomically Based Differentials, Facial Nerve Lesion, Temporal Bone", "pageKeywords": "Head and Neck, Differential Diagnosis, Temporal Bone, Anatomically Based Differentials, Inner Ear Lesion, Adult",
"reasons": [ "reasons": [
"Breadcrumbs", "Content"
"Keywords",
"Title"
], ],
"snippet": "" "snippet": "...ochlear turns - Usually with enlarged endolymphatic sac/duct - Literature suggests dysplastic osseous spiral lamin..."
},
{
"path": "docs_md/articles/ventricles-and-cisterns-overview_ad860c4f-fe9a-4469-8eca-a7ccd5cff70f.md",
"title": "Ventricles and Cisterns Overview",
"docid": "ad860c4f-fe9a-4469-8eca-a7ccd5cff70f",
"breadcrumbs": [
"Brain",
"Diagnosis",
"Anatomy-Based Diagnoses",
"Ventricles and Cisterns",
"Ventricles and Cisterns Overview"
],
"authors": [
{
"key": "a25c450b-3d34-4f64-bba3-cc0834813df6",
"value": "Miral D. Jhaveri, MD, MBA"
}
],
"pageKeywords": "Brain, Diagnosis, Anatomy-Based Diagnoses, Ventricles and Cisterns, Ventricles and Cisterns Overview",
"reasons": [
"Content"
],
"snippet": "...lli along the superior sagittal sinus. CSF also drains into lymphatic vessels around the cranial cavity and spinal canal. - **Updated model of CSF and..."
},
{
"path": "docs_md/articles/takayasu-arteritis_d35eb6f3-bfd3-4121-8781-325a93ccc197.md",
"title": "Takayasu Arteritis",
"docid": "d35eb6f3-bfd3-4121-8781-325a93ccc197",
"breadcrumbs": [
"Cardiac",
"Diagnosis",
"Aorta",
"Takayasu Arteritis"
],
"authors": [
{
"key": "ee6ece9d-ad74-458c-a8df-11628ae7f879",
"value": "Arzu Canan, MD"
},
{
"key": "3d1e4c57-c1cf-4c89-b0f0-5d82b29a31e1",
"value": "Suhny Abbara, MD, FACR, MSCCT, FNASCI"
}
],
"pageKeywords": "Cardiac, Diagnosis, Aorta, Takayasu Arteritis",
"reasons": [
"Content"
],
"snippet": ".../ANATOMY:551f4b47-fac1-44f9-b800-09ce766fedd9 ### Vessels, Lymphatic System, and Nerves, Abdominal Gastrointestinal/ANATOMY:0c38fd49-88e7-4272-960f-b..."
},
{
"path": "docs_md/articles/peritoneal-spaces-and-structures_9c50ad6a-e96b-44a1-93d1-a4e7de5212c2.md",
"title": "Peritoneal Spaces and Structures",
"docid": "9c50ad6a-e96b-44a1-93d1-a4e7de5212c2",
"breadcrumbs": [
"Ultrasound",
"Anatomy",
"Abdomen",
"Peritoneal Spaces and Structures"
],
"authors": [
{
"key": "07469ec4-05aa-4d65-a788-08b4d64048af",
"value": "Jade Wong-You-Cheong, MBChB, MRCP, FRCR, FSRU, FSAR"
}
],
"pageKeywords": "Ultrasound, Anatomy, Abdomen, Peritoneal Spaces and Structures",
"reasons": [
"Content"
],
"snippet": "...to right; contains superior mesenteric vessels, nerves, and lymphatics - Transverse mesocolon crosses almost horizontally in front of pancreas, du..."
},
{
"path": "docs_md/articles/cpa-iac-lipoma_37ef2fb6-7d7e-48dc-b786-16ed4475b26e.md",
"title": "CPA-IAC Lipoma",
"docid": "37ef2fb6-7d7e-48dc-b786-16ed4475b26e",
"breadcrumbs": [
"Head and Neck",
"Diagnosis",
"CPA-IAC",
"Congenital Lesions",
"CPA-IAC Lipoma"
],
"authors": [
{
"key": "318f80ab-6abb-4067-a809-2ebdaa5a30c9",
"value": "Kalen Riley, MD, MBA"
},
{
"key": "e0282a62-994d-4550-a127-1eb773b1e920",
"value": "Blair A. Winegar, MD"
},
{
"key": "94f835c8-fa13-4e8a-995b-53048e6b0605",
"value": "Philip R. Chapman, MD"
}
],
"pageKeywords": "Head and Neck, Diagnosis, CPA-IAC, Congenital Lesions, CPA-IAC Lipoma",
"reasons": [
"Content"
],
"snippet": "...ant CPA-IAC lipoma with inner ear second fatty focus in endolymphatic duct-sac.\\n\\nThree axial CT (#1-3) and 3 axial MR (#4-6) images reveal an obviou..."
},
{
"path": "docs_md/articles/cystic-cpa-mass_6c60db6d-8093-4df5-8cbb-c6f6570ae167.md",
"title": "Cystic CPA Mass",
"docid": "6c60db6d-8093-4df5-8cbb-c6f6570ae167",
"breadcrumbs": [
"Head and Neck",
"Differential Diagnosis",
"CPA-IAC and Posterior Fossa",
"Generic Imaging Patterns",
"Cystic CPA Mass"
],
"authors": [
{
"key": "07a2c087-6202-49e7-870b-7aa162d18f06",
"value": "Bronwyn E. Hamilton, MD"
}
],
"pageKeywords": "Head and Neck, Differential Diagnosis, CPA-IAC and Posterior Fossa, Generic Imaging Patterns, Cystic CPA Mass",
"reasons": [
"Content"
],
"snippet": "...chnoid, & neurenteric cysts; neurocysticercosis & large endolymphatic sac anomaly - Many solid CPA tumors may have either intramural cysts,..."
},
{
"path": "docs_md/articles/cranial-meninges_3210cf7d-5be6-4741-a11d-dd7f8c1bc286.md",
"title": "Cranial Meninges",
"docid": "3210cf7d-5be6-4741-a11d-dd7f8c1bc286",
"breadcrumbs": [
"Brain",
"Anatomy",
"Scalp, Skull, and Meninges",
"Cranial Meninges"
],
"authors": [
{
"key": "5cff4116-3654-4b3a-bb75-5ebe0b8c9850",
"value": "Anne G. Osborn, MD, FACR"
}
],
"pageKeywords": "Brain, Anatomy, Scalp, Skull, and Meninges, Cranial Meninges",
"reasons": [
"Content"
],
"snippet": "...along penetrating arteries - Key part of brain \"glymphatic\" system ## GROSS ANATOMY - ### Overview - Brain encased by 3 meninge..."
} }
] ]
tools/search_md.py
+147 -107
View File
@@ -249,11 +249,33 @@ def match_author(authors: List[Dict[str, Any]], q: str) -> bool:
return False return False
def run_search(root: str, qkey: str, qval: str, mode: str = 'exact', targets: List[str] = None) -> List[Dict[str, Any]]: def run_search(root: str, qkey: str, qval: str, mode: str = 'exact', targets: List[str] = None, or_queries: List[Dict[str, Any]] = None) -> List[Dict[str, Any]]:
out = [] out = []
# Helper to test if a string/list/dict matches under the chosen mode # Normalize queries list
def value_matches(query: str, target_val: Any) -> bool: if not or_queries:
or_queries = [{
'qkey': qkey,
'qval': qval,
'mode': mode,
'targets': targets
}]
normalized_specs = []
for spec in or_queries:
qk = spec.get('qkey') or 'global'
qv = spec.get('qval') or ''
m = spec.get('mode') or 'exact'
t = spec.get('targets')
normalized_specs.append({
'qkey': qk,
'qval': qv,
'mode': m,
'targets': t
})
# Helper to test if a string/list/dict matches under a specific mode
def value_matches(query: str, target_val: Any, mode_val: str) -> bool:
if target_val is None: if target_val is None:
return False return False
@@ -261,15 +283,15 @@ def run_search(root: str, qkey: str, qval: str, mode: str = 'exact', targets: Li
for item in target_val: for item in target_val:
if isinstance(item, dict): if isinstance(item, dict):
for k, v in item.items(): for k, v in item.items():
if value_matches(query, v): if value_matches(query, v, mode_val):
return True return True
else: else:
if value_matches(query, item): if value_matches(query, item, mode_val):
return True return True
return False return False
elif isinstance(target_val, dict): elif isinstance(target_val, dict):
for k, v in target_val.items(): for k, v in target_val.items():
if value_matches(query, v): if value_matches(query, v, mode_val):
return True return True
return False return False
@@ -277,9 +299,9 @@ def run_search(root: str, qkey: str, qval: str, mode: str = 'exact', targets: Li
if not s_val: if not s_val:
return False return False
if mode == 'stemming': if mode_val == 'stemming':
return match_stemming(query, s_val) return match_stemming(query, s_val)
elif mode == 'fuzzy': elif mode_val == 'fuzzy':
return match_fuzzy(query, s_val) return match_fuzzy(query, s_val)
else: else:
# Exact substring or wildcard match # Exact substring or wildcard match
@@ -303,108 +325,126 @@ def run_search(root: str, qkey: str, qval: str, mode: str = 'exact', targets: Li
reasons = [] reasons = []
snippet = "" snippet = ""
# Normalise query key. If none or global/all/empty, search all for spec in normalized_specs:
k_lower = (qkey or '').strip().lower() qk = spec['qkey']
if not k_lower or k_lower in ('global', 'all', 'any'): qv = spec['qval']
# Determine which targets to test m = spec['mode']
if targets: t = spec['targets']
target_set = {t.lower() for t in targets}
else:
target_set = {'title', 'docid', 'breadcrumbs', 'authors', 'keywords', 'category', 'type', 'content'}
# Single search box mode / global search: if not qv:
# 1. Title continue # skip empty queries
if 'title' in target_set:
for f in ['title', 'enhancedTitle', 'pageTitle']: spec_matched = False
if value_matches(qval, fm.get(f)): spec_reasons = []
matched = True spec_snippet = ""
reasons.append('Title')
break k_lower = (qk or '').strip().lower()
# 2. DocID if not k_lower or k_lower in ('global', 'all', 'any'):
if 'docid' in target_set: # Determine which targets to test
if value_matches(qval, fm.get('docid')): if t:
matched = True target_set = {x.lower() for x in t}
reasons.append('DocID')
# 3. Breadcrumbs
if 'breadcrumbs' in target_set:
bcs = fm.get('breadcrumbs') or []
if isinstance(bcs, list) and bcs and isinstance(bcs[0], dict):
bcs_list = [d.get('name') or d.get('slug') or '' for d in bcs]
else: else:
bcs_list = bcs target_set = {'title', 'docid', 'breadcrumbs', 'authors', 'keywords', 'category', 'type', 'content'}
if '>' in qval:
query_parts = [p.strip() for p in qval.split('>') if p.strip()] # 1. Title
if match_breadcrumbs(bcs_list, query_parts): if 'title' in target_set:
matched = True for f in ['title', 'enhancedTitle', 'pageTitle']:
reasons.append('Breadcrumbs') if value_matches(qv, fm.get(f), m):
else: spec_matched = True
if value_matches(qval, bcs_list): spec_reasons.append('Title')
matched = True break
reasons.append('Breadcrumbs') # 2. DocID
# 4. Authors if 'docid' in target_set:
if 'authors' in target_set: if value_matches(qv, fm.get('docid'), m):
if value_matches(qval, fm.get('authors')): spec_matched = True
matched = True spec_reasons.append('DocID')
reasons.append('Authors') # 3. Breadcrumbs
# 5. PageKeywords if 'breadcrumbs' in target_set:
if 'keywords' in target_set or 'pagekeywords' in target_set: bcs = fm.get('breadcrumbs') or []
if value_matches(qval, fm.get('pageKeywords')): if isinstance(bcs, list) and bcs and isinstance(bcs[0], dict):
matched = True bcs_list = [d.get('name') or d.get('slug') or '' for d in bcs]
reasons.append('Keywords') else:
# 6. Category bcs_list = bcs
if 'category' in target_set: if '>' in qv:
if value_matches(qval, fm.get('category')): query_parts = [p.strip() for p in qv.split('>') if p.strip()]
matched = True if match_breadcrumbs(bcs_list, query_parts):
reasons.append('Category') spec_matched = True
# 7. Type spec_reasons.append('Breadcrumbs')
if 'type' in target_set: else:
if value_matches(qval, fm.get('type')): if value_matches(qv, bcs_list, m):
matched = True spec_matched = True
reasons.append('Type') spec_reasons.append('Breadcrumbs')
# 8. Content # 4. Authors
if 'content' in target_set: if 'authors' in target_set:
if value_matches(qval, content): if value_matches(qv, fm.get('authors'), m):
matched = True spec_matched = True
reasons.append('Content') spec_reasons.append('Authors')
snippet = get_content_snippet(content, qval) # 5. PageKeywords
else: if 'keywords' in target_set or 'pagekeywords' in target_set:
# Specific key search if value_matches(qv, fm.get('pageKeywords'), m):
if k_lower == 'breadcrumbs': spec_matched = True
bcs = fm.get('breadcrumbs') or [] spec_reasons.append('Keywords')
if bcs and isinstance(bcs, list) and bcs and isinstance(bcs[0], dict): # 6. Category
bcs_list = [d.get('name') or d.get('slug') or '' for d in bcs] if 'category' in target_set:
else: if value_matches(qv, fm.get('category'), m):
bcs_list = bcs spec_matched = True
if '>' in qval: spec_reasons.append('Category')
query_parts = [p.strip() for p in qval.split('>') if p.strip()] # 7. Type
matched = match_breadcrumbs(bcs_list, query_parts) if 'type' in target_set:
else: if value_matches(qv, fm.get('type'), m):
matched = value_matches(qval, bcs_list) spec_matched = True
if matched: spec_reasons.append('Type')
reasons.append('Breadcrumbs') # 8. Content
elif k_lower == 'authors': if 'content' in target_set:
matched = value_matches(qval, fm.get('authors')) if value_matches(qv, content, m):
if matched: spec_matched = True
reasons.append('Authors') spec_reasons.append('Content')
elif k_lower == 'pagekeywords': spec_snippet = get_content_snippet(content, qv)
matched = value_matches(qval, fm.get('pageKeywords'))
if matched:
reasons.append('Keywords')
elif k_lower == 'content':
matched = value_matches(qval, content)
if matched:
reasons.append('Content')
snippet = get_content_snippet(content, qval)
elif k_lower in ('title', 'enhancedtitle', 'pagetitle'):
for f in ['title', 'enhancedTitle', 'pageTitle']:
if value_matches(qval, fm.get(f)):
matched = True
reasons.append('Title')
break
else: else:
matched = value_matches(qval, fm.get(qkey)) # Specific key search
if matched: if k_lower == 'breadcrumbs':
reasons.append(qkey.capitalize()) bcs = fm.get('breadcrumbs') or []
if bcs and isinstance(bcs, list) and bcs and isinstance(bcs[0], dict):
bcs_list = [d.get('name') or d.get('slug') or '' for d in bcs]
else:
bcs_list = bcs
if '>' in qv:
query_parts = [p.strip() for p in qv.split('>') if p.strip()]
spec_matched = match_breadcrumbs(bcs_list, query_parts)
else:
spec_matched = value_matches(qv, bcs_list, m)
if spec_matched:
spec_reasons.append('Breadcrumbs')
elif k_lower == 'authors':
spec_matched = value_matches(qv, fm.get('authors'), m)
if spec_matched:
spec_reasons.append('Authors')
elif k_lower == 'pagekeywords':
spec_matched = value_matches(qv, fm.get('pageKeywords'), m)
if spec_matched:
spec_reasons.append('Keywords')
elif k_lower == 'content':
spec_matched = value_matches(qv, content, m)
if spec_matched:
spec_reasons.append('Content')
spec_snippet = get_content_snippet(content, qv)
elif k_lower in ('title', 'enhancedtitle', 'pagetitle'):
for f in ['title', 'enhancedTitle', 'pageTitle']:
if value_matches(qv, fm.get(f), m):
spec_matched = True
spec_reasons.append('Title')
break
else:
spec_matched = value_matches(qv, fm.get(qk), m)
if spec_matched:
spec_reasons.append(qk.capitalize())
if spec_matched:
matched = True
spec_reasons_clean = [str(x) for x in spec_reasons]
reasons.extend(spec_reasons_clean)
if spec_snippet and not snippet:
snippet = spec_snippet
if matched: if matched:
out.append({ out.append({
tools/search_md_gui.py
+97 -40
View File
@@ -169,41 +169,82 @@ def search_page() -> None: # build UI
with ui.row().classes('gap-2'): with ui.row().classes('gap-2'):
ui.button('Open Output Dir', icon='folder', on_click=lambda: open_output_dir(), color='secondary').props('outline') ui.button('Open Output Dir', icon='folder', on_click=lambda: open_output_dir(), color='secondary').props('outline')
# Main Search Box Card # Main Search card
with ui.card().classes('w-full p-6 shadow-xl'): queries = [
with ui.row().classes('w-full items-center gap-4'): {
# Single search box 'qval': '',
qval_input = ui.input( 'mode': 'exact',
label='Search Query', 'targets': ['Title', 'Content', 'Breadcrumbs', 'Keywords', 'Category', 'Type']
placeholder='Type search terms...' }
).classes('flex-grow').props('outlined label-slot') ]
qval_input.add_slot('append', '<q-icon name="search" />')
with ui.card().classes('w-full p-6 shadow-xl gap-4'):
# Match mode select query_blocks_container = ui.column().classes('w-full gap-4')
mode_select = ui.select(
options={'exact': 'Exact Match', 'fuzzy': 'Fuzzy Match', 'stemming': 'Stemming (Related Words)'}, def render_query_blocks():
value='exact', query_blocks_container.clear()
label='Match Mode' with query_blocks_container:
).classes('w-56').props('outlined') for idx, q in enumerate(queries):
with ui.row().classes('w-full items-center gap-4 border border-slate-800 p-4 rounded-lg bg-slate-900/40 relative'):
# Targets select label_text = "Query 1 (Primary)" if idx == 0 else f"OR Query {idx + 1}"
targets_select = ui.select( ui.label(label_text).classes('text-blue-400 font-semibold w-36')
options={
'Title': 'Title', # Bind value and update on change
'Content': 'Content', qval_input = ui.input(
'Breadcrumbs': 'Breadcrumbs', label='Search Query',
'Authors': 'Authors', placeholder='Type search terms...',
'Keywords': 'Keywords', value=q['qval'],
'Category': 'Category', on_change=lambda e, q=q: q.update({'qval': e.value})
'Type': 'Type' ).classes('flex-grow').props('outlined dense').on('keydown.enter', lambda: asyncio.create_task(run_search_handler()))
},
value=['Title', 'Content', 'Breadcrumbs', 'Keywords', 'Category', 'Type'], mode_select = ui.select(
label='Search Targets', options={'exact': 'Exact Match', 'fuzzy': 'Fuzzy Match', 'stemming': 'Stemming (Related Words)'},
multiple=True value=q['mode'],
).classes('w-80').props('outlined use-chips') label='Match Mode',
on_change=lambda e, q=q: q.update({'mode': e.value})
# Search button ).classes('w-48').props('outlined dense')
search_btn = ui.button('Search', icon='search', on_click=lambda: asyncio.create_task(run_search_handler())).classes('bg-blue-600 hover:bg-blue-700 text-white font-semibold py-4 px-8 rounded-lg shadow-md transition-all duration-300')
targets_select = ui.select(
options={
'Title': 'Title',
'Content': 'Content',
'Breadcrumbs': 'Breadcrumbs',
'Authors': 'Authors',
'Keywords': 'Keywords',
'Category': 'Category',
'Type': 'Type'
},
value=q['targets'],
label='Search Targets',
multiple=True,
on_change=lambda e, q=q: q.update({'targets': e.value})
).classes('w-72').props('outlined dense use-chips')
if idx > 0:
ui.button(
icon='delete',
on_click=lambda _, idx=idx: remove_query_block(idx)
).classes('text-red-400 hover:text-red-500').props('flat round dense')
def add_query_block():
queries.append({
'qval': '',
'mode': 'exact',
'targets': ['Title', 'Content', 'Breadcrumbs', 'Keywords', 'Category', 'Type']
})
render_query_blocks()
def remove_query_block(idx: int):
if 0 < idx < len(queries):
queries.pop(idx)
render_query_blocks()
# Render initial query blocks
render_query_blocks()
with ui.row().classes('w-full justify-between items-center gap-4 mt-2'):
ui.button('Add OR Query', icon='add', on_click=add_query_block).classes('text-blue-400 border border-blue-800').props('outline dense')
search_btn = ui.button('Search', icon='search', on_click=lambda: asyncio.create_task(run_search_handler())).classes('bg-blue-600 hover:bg-blue-700 text-white font-semibold py-3 px-8 rounded-lg shadow-md transition-all duration-300')
# Advanced Criteria Expansion Box # Advanced Criteria Expansion Box
with ui.expansion('Advanced Configurations', icon='settings').classes('w-full text-slate-300 border border-slate-800 rounded-lg p-2'): with ui.expansion('Advanced Configurations', icon='settings').classes('w-full text-slate-300 border border-slate-800 rounded-lg p-2'):
@@ -283,7 +324,12 @@ def search_page() -> None: # build UI
''') ''')
async def run_search_handler(): async def run_search_handler():
if not qval_input.value: has_query = False
for q in queries:
if q['qval'].strip():
has_query = True
break
if not has_query:
ui.notify('Please enter a search query', color='warning') ui.notify('Please enter a search query', color='warning')
return return
@@ -291,13 +337,24 @@ def search_page() -> None: # build UI
search_btn.set_enabled(False) search_btn.set_enabled(False)
try: try:
or_queries_param = []
for q in queries:
if q['qval'].strip():
or_queries_param.append({
'qkey': key_select.value,
'qval': q['qval'],
'mode': q['mode'],
'targets': [t.lower() for t in q['targets']]
})
results = await anyio.to_thread.run_sync( results = await anyio.to_thread.run_sync(
search_md.run_search, search_md.run_search,
root_input.value, root_input.value,
key_select.value, 'global',
qval_input.value, '',
mode_select.value, 'exact',
targets_select.value None,
or_queries_param
) )
table.rows = results table.rows = results