Enrichment now processed via chunks. 2 documents -> into the vector storage. Also geussing source from the file extension

services/rag/langchain/helpers.py

@@ -115,13 +115,11 @@ def extract_russian_event_names(text: str) -> List[str]:
 
 class _AdaptiveFile(ABC):
     extension: str  # Format: .jpg
-    local_path: str
     filename: str
 
-    def __init__(self, filename: str, extension: str, local_path: str):
+    def __init__(self, filename: str, extension: str):
         self.filename = filename
         self.extension = extension
-        self.local_path = local_path
 
     # This method allows to work with file locally, and lambda should be provided for this.
     # Why separate method? For possible cleanup after work is done. And to download file, if needed
@@ -139,8 +137,11 @@ class _AdaptiveCollection(ABC):
 
 
 class LocalFilesystemAdaptiveFile(_AdaptiveFile):
+    local_path: str
+
     def __init__(self, filename: str, extension: str, local_path: str):
-        super().__init__(filename, extension, local_path)
+        super().__init__(filename, extension)
+        self.local_path = local_path
 
     def work_with_file_locally(self, func: Callable[[str], None]):
         func(self.local_path)
@@ -171,7 +172,7 @@ class YandexDiskAdaptiveFile(_AdaptiveFile):
     remote_path: str
 
     def __init__(self, filename: str, extension: str, remote_path: str, token: str):
-        super().__init__(filename, extension, remote_path)
+        super().__init__(filename, extension)
         self.token = token
         self.remote_path = remote_path