Use absolute file path to open files in org-to-jsonl.py, asymmetric.py

Exit script if neither org_files, org_file_filter is present

processor/org-mode/org-to-jsonl.py

@@ -12,7 +12,7 @@ import gzip
 # Define Functions
 def dump_jsonl(jsonl_data, output_path, verbose=0):
     "Write List of JSON objects to JSON line file"
-    with open(output_path, 'w', encoding='utf-8') as f:
+    with open(get_absolute_path(output_path), 'w', encoding='utf-8') as f:
         f.write(jsonl_data)
 
     if verbose > 0:
@@ -30,7 +30,7 @@ def compress_jsonl_data(jsonl_data, output_path, verbose=0):
 def load_jsonl(input_path, verbose=0):
     "Read List of JSON objects from JSON line file"
     data = []
-    with open(input_path, 'r', encoding='utf-8') as f:
+    with open(get_absolute_path(input_path), 'r', encoding='utf-8') as f:
         for line in f:
             data.append(json.loads(line.rstrip('\n|\r')))
 
@@ -105,7 +105,7 @@ def get_absolute_path(filepath):
 
 
 if __name__ == '__main__':
-    # Setup argument parser
+    # Setup Argument Parser
     parser = argparse.ArgumentParser(description="Map Org-Mode notes into (compressed) JSONL format")
     parser.add_argument('--jsonl-file', '-o', type=pathlib.Path, required=True, help="Output file for JSONL formatted notes")
     parser.add_argument('--org-files', '-i', nargs='*', help="List of org-mode files to process")
@@ -116,6 +116,7 @@ if __name__ == '__main__':
 
     if is_none_or_empty(args.org_files) and is_none_or_empty(args.org_file_filter):
         print("At least one of org-files or org-file-filter is required to be specified")
+        exit(1)
 
     # Get Org Files to Process
     org_files = get_org_files(args.org_files, args.org_file_filter)

search_types/asymmetric.py

@@ -23,7 +23,7 @@ def initialize_model():
 def extract_entries(notesfile, verbose=False):
     "Load entries from compressed jsonl"
     entries = []
-    with gzip.open(str(notesfile.expanduser()), 'rt', encoding='utf8') as jsonl:
+    with gzip.open(get_absolute_path(notesfile), 'rt', encoding='utf8') as jsonl:
         for line in jsonl:
             note = json.loads(line.strip())
 
@@ -44,13 +44,13 @@ def compute_embeddings(entries, bi_encoder, embeddings_file, verbose=False):
     "Compute (and Save) Embeddings or Load Pre-Computed Embeddings"
     # Load pre-computed embeddings from file if exists
     if embeddings_file.exists():
-        corpus_embeddings = torch.load(str(embeddings_file.expanduser()))
+        corpus_embeddings = torch.load(get_absolute_path(embeddings_file))
         if verbose:
             print(f"Loaded embeddings from {embeddings_file}")
 
     else:  # Else compute the corpus_embeddings from scratch, which can take a while
         corpus_embeddings = bi_encoder.encode(entries, convert_to_tensor=True, show_progress_bar=True)
-        torch.save(corpus_embeddings, str(embeddings_file.expanduser()))
+        torch.save(corpus_embeddings, get_absolute_path(embeddings_file))
         if verbose:
             print(f"Computed embeddings and save them to {embeddings_file}")
 
@@ -140,6 +140,10 @@ def collate_results(hits, entries, count=5, verbose=False):
         in hits[0:count]]
 
 
+def get_absolute_path(filepath):
+    return str(pathlib.Path(filepath).expanduser().absolute())
+
+
 if __name__ == '__main__':
     # Setup Argument Parser
     parser = argparse.ArgumentParser(description="Map Org-Mode notes into JSONL format")