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Trace query response performance and display timings in verbose mode

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This commit is contained in:
Debanjum Singh Solanky
2022-07-26 21:03:53 +04:00
parent d8efcd559f
commit f094c86204
3 changed files with 64 additions and 14 deletions
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49
src/main.py
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@@ -1,5 +1,6 @@
# Standard Packages
import sys, json, yaml, os
import time
from typing import Optional
# External Packages
@@ -66,50 +67,74 @@ def search(q: str, n: Optional[int] = 5, t: Optional[SearchType] = None):
device = torch.device("cuda:0") if torch.cuda.is_available() else torch.device("cpu")
user_query = q
results_count = n
results = {}
if (t == SearchType.Org or t == None) and model.orgmode_search:
# query org-mode notes
hits, entries = text_search.query(user_query, model.orgmode_search, device=device, filters=[explicit_filter, date_filter])
query_start = time.time()
hits, entries = text_search.query(user_query, model.orgmode_search, device=device, filters=[explicit_filter, date_filter], verbose=verbose)
query_end = time.time()
# collate and return results
return text_search.collate_results(hits, entries, results_count)
collate_start = time.time()
results = text_search.collate_results(hits, entries, results_count)
collate_end = time.time()
if (t == SearchType.Music or t == None) and model.music_search:
# query music library
hits, entries = text_search.query(user_query, model.music_search, device=device, filters=[explicit_filter, date_filter])
query_start = time.time()
hits, entries = text_search.query(user_query, model.music_search, device=device, filters=[explicit_filter, date_filter], verbose=verbose)
query_end = time.time()
# collate and return results
return text_search.collate_results(hits, entries, results_count)
collate_start = time.time()
results = text_search.collate_results(hits, entries, results_count)
collate_end = time.time()
if (t == SearchType.Markdown or t == None) and model.orgmode_search:
# query markdown files
hits, entries = text_search.query(user_query, model.markdown_search, device=device, filters=[explicit_filter, date_filter])
query_start = time.time()
hits, entries = text_search.query(user_query, model.markdown_search, device=device, filters=[explicit_filter, date_filter], verbose=verbose)
query_end = time.time()
# collate and return results
return text_search.collate_results(hits, entries, results_count)
collate_start = time.time()
results = text_search.collate_results(hits, entries, results_count)
collate_end = time.time()
if (t == SearchType.Ledger or t == None) and model.ledger_search:
# query transactions
hits, entries = text_search.query(user_query, model.ledger_search, filters=[explicit_filter, date_filter])
query_start = time.time()
hits, entries = text_search.query(user_query, model.ledger_search, filters=[explicit_filter, date_filter], verbose=verbose)
query_end = time.time()
# collate and return results
return text_search.collate_results(hits, entries, results_count)
collate_start = time.time()
results = text_search.collate_results(hits, entries, results_count)
collate_end = time.time()
if (t == SearchType.Image or t == None) and model.image_search:
# query images
hits = image_search.query(user_query, results_count, model.image_search)
query_start = time.time()
hits = image_search.query(user_query, results_count, model.image_search, verbose=verbose)
output_directory = f'{os.getcwd()}/{web_directory}'
query_end = time.time()
# collate and return results
return image_search.collate_results(
collate_start = time.time()
results = image_search.collate_results(
hits,
image_names=model.image_search.image_names,
output_directory=output_directory,
static_files_url='/static',
count=results_count)
collate_end = time.time()
else:
return {}
if verbose > 1:
print(f"Query took {query_end - query_start:.3f} seconds")
print(f"Collating results took {collate_end - collate_start:.3f} seconds")
return results
@app.get('/reload')