Add compare to cli

src/beaky/cli.py

@@ -5,6 +5,7 @@ from pydantic import ValidationError
 
 from beaky import _ansi
 from beaky.config import Config
+from beaky.image_classifier.classifier import img_classify
 from beaky.link_classifier.classifier import LinkClassifier
 from beaky.resolvers.resolver import TicketResolver, TicketVerdict
 from beaky.scanner.scanner import Links
@@ -36,7 +37,7 @@ def main() -> None:
     parser = argparse.ArgumentParser(prog="beaky")
     parser.add_argument("--config", help="Path to config file.", default="config/application.yml")
     parser.add_argument("--id", type=int, help="Resolve a single ticket by id (only used with resolve mode).")
-    parser.add_argument("mode", choices=["screenshotter", "parser", "class", "resolve"], help="Mode of operation.")
+    parser.add_argument("mode", choices=["screenshotter", "parser", "class", "resolve", "compare"], help="Mode of operation.")
 
     args = parser.parse_args()
     config = load_config(args.config)
@@ -72,6 +73,19 @@ def main() -> None:
                 for k, v in vars(bet).items():
                     print(f"    {k}: {v}")
 
+    if args.mode == "compare":
+        linkclassifier = LinkClassifier()
+        links = [l for l in data.links if l.id == args.id] if args.id is not None else data.links
+        if args.id is not None and not links:
+            print(f"ERROR: ticket id {args.id} not found")
+            return
+        for link in links:
+            linkClass = linkclassifier.classify(link)
+            imgClass =  img_classify(["./data/screenshots/{link.id}.png"], ticket_id=link.id)
+
+            print(linkClass)
+            print(imgClass)
+
     if args.mode == "resolve":
         classifier = LinkClassifier()
         resolver = TicketResolver(config.resolver)

src/beaky/image_classifier/classifier.py

@@ -132,20 +132,16 @@ def classify(text: str) -> Bet:
     return UnknownTicket(ticketType=BetType.UNKNOWN, raw_text=text, **base_args)
 
 
-def img_classify(path: str, ticket_id: int) -> Ticket:
+def img_classify(paths: list[str], ticket_id: int) -> Ticket:
     """Given a path to an image and a date, return a list of Tickets that are
     relevant to that image and date."""
     # Define valid image extensions to ignore system files or text documents
     ticket = Ticket(id=ticket_id, bets=[])
     valid_extensions = {".png", ".jpg", ".jpeg", ".bmp", ".tiff", ".webp"}
-    path_obj = Path(path)
-
-    if not path_obj.is_dir():
-        print(f"Error: The path '{path}' is not a valid directory.")
-        return ticket
 
     # Iterate through all files in the folder
-    for file_path in path_obj.iterdir():
+    for file in paths:
+        file_path = Path(file)
         if file_path.is_file() and file_path.suffix.lower() in valid_extensions:
             # 1. Extract the text (called separately)
             extracted_text = img_to_text(str(file_path))
@@ -195,4 +191,4 @@ def img_classify(path: str, ticket_id: int) -> Ticket:
 
 
 if __name__ == "__main__":
-    img_classify("./data/screenshots/", ticket_id=1)
+    img_classify(["./data/screenshots/2.png"], ticket_id=1)