Expose API endpoint to (re-)generate embeddings from latest notes

- Provides mechanism to update notes from within application
  - Instead of having to pass the same arguments multiple times
    Pass it once (or rely on defaults when possible) and let app keep
    state and location of intermediary files

- Allows user to not have to deal with the internals of the application
  - E.g user doesn't have to specify the jsonl.gz or embeddings file path
    The app will still put those files in a default location
  - The user doesn't have to run the generation from the commandline
    as a separate step

main.py

@@ -1,6 +1,8 @@
 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
@@ -20,7 +22,7 @@ def search(q: str, n: Optional[int] = 5, t: Optional[str] = 'notes'):
     if t == 'notes':
         # query notes
         hits = asymmetric.query_notes(
-            q,
+            user_query,
             corpus_embeddings,
             entries,
             bi_encoder,
@@ -34,22 +36,47 @@ def search(q: str, n: Optional[int] = 5, t: Optional[str] = 'notes'):
         return {}
 
 
+@app.get('/regenerate')
+def regenerate():
+    org_to_jsonl(args.input_files, args.input_filter, args.compressed_jsonl, args.verbose)
+
+    # Extract Entries
+    global entries
+    entries = asymmetric.extract_entries(args.compressed_jsonl, args.verbose)
+
+    # Compute or Load Embeddings
+    global corpus_embeddings
+    corpus_embeddings = asymmetric.compute_embeddings(entries, bi_encoder, args.embeddings, regenerate=True, verbose=args.verbose)
+
+
 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', help="Show verbose conversion logs. Default: 0")
     args = parser.parse_args()
 
+    # Input Validation
+    if is_none_or_empty(args.input_files) and is_none_or_empty(args.input_filter):
+        print("At least one of org-files or org-file-filter is required to be specified")
+        exit(1)
+
     # Initialize Model
     bi_encoder, cross_encoder, top_k = asymmetric.initialize_model()
 
+    # Map notes in Org-Mode files to (compressed) JSONL formatted file
+    if not args.compressed_jsonl.exists() or args.regenerate:
+        org_to_jsonl(args.input_files, args.input_filter, args.compressed_jsonl, args.verbose)
+
     # Extract Entries
     entries = asymmetric.extract_entries(args.compressed_jsonl, args.verbose)
 
     # Compute or Load Embeddings
-    corpus_embeddings = asymmetric.compute_embeddings(entries, bi_encoder, args.embeddings, args.verbose)
+    corpus_embeddings = asymmetric.compute_embeddings(entries, bi_encoder, args.embeddings, regenerate=args.regenerate, verbose=args.verbose)
 
     # Start Application Server
     uvicorn.run(app)