khoj/src/main.py

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from typing import Optional
from fastapi import FastAPI
from search_type import asymmetric
from processor.org_mode.org_to_jsonl import org_to_jsonl
from utils.helpers import is_none_or_empty
import argparse
import pathlib
import uvicorn
app = FastAPI()
@app.get('/search')
def search(q: str, n: Optional[int] = 5, t: Optional[str] = 'notes'):
if q is None or q == '':
print(f'No query param (q) passed in API call to initiate search')
return {}
user_query = q
results_count = n
if t == 'notes':
# query notes
hits = asymmetric.query_notes(
user_query,
corpus_embeddings,
entries,
bi_encoder,
cross_encoder,
top_k)
# collate and return results
return asymmetric.collate_results(hits, entries, results_count)
else:
return {}
@app.get('/regenerate')
def regenerate():
# Extract Entries, Generate Embeddings
extracted_entries, computed_embeddings, _, _, _ = asymmetric.setup(args.input_files, args.input_filter, args.compressed_jsonl, args.embeddings, regenerate=True, verbose=args.verbose)
# Now Update State
# update state variables after regeneration complete
# minimize time the application is in inconsistent, partially updated state
global corpus_embeddings
global entries
entries = extracted_entries
corpus_embeddings = computed_embeddings
return {'status': 'ok', 'message': 'regeneration completed'}
if __name__ == '__main__':
# Setup Argument Parser
parser = argparse.ArgumentParser(description="Expose API for Semantic Search")
parser.add_argument('--input-files', '-i', nargs='*', help="List of org-mode files to process")
parser.add_argument('--input-filter', type=str, default=None, help="Regex filter for org-mode files to process")
parser.add_argument('--compressed-jsonl', '-j', type=pathlib.Path, default=pathlib.Path(".notes.jsonl.gz"), help="Compressed JSONL formatted notes file to compute embeddings from")
parser.add_argument('--embeddings', '-e', type=pathlib.Path, default=pathlib.Path(".notes_embeddings.pt"), help="File to save/load model embeddings to/from")
parser.add_argument('--regenerate', action='store_true', default=False, help="Regenerate embeddings from org-mode files. Default: false")
parser.add_argument('--verbose', action='count', default=0, help="Show verbose conversion logs. Default: 0")
args = parser.parse_args()
entries, corpus_embeddings, bi_encoder, cross_encoder, top_k = asymmetric.setup(args.input_files, args.input_filter, args.compressed_jsonl, args.embeddings, args.regenerate, args.verbose)
# Start Application Server
uvicorn.run(app)