fix: metadata search for provider

context_chat_backend/chain/ingest/injest.py

@@ -78,6 +78,7 @@ def _sources_to_documents(sources: list[UploadFile]) -> list[Document]:
 			'title': source.headers.get('title'),
 			'type': source.headers.get('type'),
 			'modified': source.headers.get('modified'),
+			'provider': source.headers.get('provider'),
 		}
 
 		document = Document(page_content=content, metadata=metadata)
@@ -158,7 +159,7 @@ def embed_sources(
 	# either not a file or a file that is allowed
 	sources_filtered = [
 		source for source in sources
-		if not source.filename.startswith('file: ')
+		if (source.filename is not None and not source.filename.startswith('file: '))
 		or _allowed_file(source)
 	]
 

context_chat_backend/controller.py

@@ -57,20 +57,21 @@ def _(userId: str):
 # TODO: for testing, remove later
 @app.get('/search')
 @enabled_guard(app)
-def _(userId: str, keyword: str):
-	from chromadb import ClientAPI
-	from .vectordb import COLLECTION_NAME
+def _(userId: str, sourceNames: str):
+	sourceNames: list[str] = [source.strip() for source in sourceNames.split(',') if source.strip() != '']
+
+	if len(sourceNames) == 0:
+		return JSONResponse('No sources provided', 400)
 
 	db: BaseVectorDB = app.extra.get('VECTOR_DB')
-	client: ClientAPI = db.client
-	db.setup_schema(userId)
 
-	return JSONResponse(
-		client.get_collection(COLLECTION_NAME(userId)).get(
-			where_document={'$contains': [{'source': keyword}]},
-			include=['metadatas'],
-		)
-	)
+	if db is None:
+		return JSONResponse('Error: VectorDB not initialised', 500)
+
+	source_objs = db.get_objects_from_metadata(userId, 'source', sourceNames)
+	sources = list(map(lambda s: s.get('id'), source_objs.values()))
+
+	return JSONResponse({ 'sources': sources })
 
 
 @app.put('/enabled')
@@ -110,47 +111,26 @@ def _(userId: Annotated[str, Body()], sourceNames: Annotated[list[str], Body()])
 	if db is None:
 		return JSONResponse('Error: VectorDB not initialised', 500)
 
-	source_objs = db.get_objects_from_metadata(userId, 'source', sourceNames)
-	res = db.delete_by_ids(userId, [
-		source.get('id')
-		for source in source_objs.values()
-		if value_of(source.get('id') is not None)
-	])
-
-	# NOTE: None returned in `delete_by_ids` should have meant an error but it didn't in the case of
-	# weaviate maybe because of the way weaviate wrapper is implemented (langchain's api does not take
-	# class name as input, which will be required in future versions of weaviate)
-	if res is None:
-		print('Deletion query returned "None". This can happen in Weaviate even if the deletion was \
-successful, therefore not considered an error for now.')
+	res = db.delete(userId, 'source', sourceNames)
 
 	if res is False:
 		return JSONResponse('Error: VectorDB delete failed, check vectordb logs for more info.', 400)
 
 	return JSONResponse('All valid sources deleted')
 
 
-@app.post('/deleteMatchingSources')
+@app.post('/deleteSourcesByProvider')
 @enabled_guard(app)
-def _(userId: Annotated[str, Body()], keyword: Annotated[str, Body()]):
+def _(userId: Annotated[str, Body()], providerKey: Annotated[str, Body()]):
+	if value_of(providerKey) is None:
+		return JSONResponse('Invalid provider key provided', 400)
+
 	db: BaseVectorDB = app.extra.get('VECTOR_DB')
 
 	if db is None:
 		return JSONResponse('Error: VectorDB not initialised', 500)
 
-	objs = db.get_objects_from_metadata(userId, 'source', [keyword], True)
-	res = db.delete_by_ids(userId, [
-		obj.get('id')
-		for obj in objs.values()
-		if value_of(obj.get('id') is not None)
-	])
-
-	# NOTE: None returned in `delete_by_ids` should have meant an error but it didn't in the case of
-	# weaviate maybe because of the way weaviate wrapper is implemented (langchain's api does not take
-	# class name as input, which will be required in future versions of weaviate)
-	if res is None:
-		print('Deletion query returned "None". This can happen in Weaviate even if the deletion was \
-successful, therefore not considered an error for now.')
+	res = db.delete(userId, 'provider', [providerKey])
 
 	if res is False:
 		return JSONResponse('Error: VectorDB delete failed, check vectordb logs for more info.', 400)
@@ -169,6 +149,7 @@ def _(sources: list[UploadFile]):
 		value_of(source.headers.get('userId'))
 		and value_of(source.headers.get('type'))
 		and value_of(source.headers.get('modified'))
+		and value_of(source.headers.get('provider'))
 		for source in sources]
 	):
 		return JSONResponse('Invaild/missing headers', 400)

context_chat_backend/vectordb/base.py

@@ -4,6 +4,8 @@
 from langchain.schema.embeddings import Embeddings
 from langchain.vectorstores import VectorStore
 
+from ..utils import value_of
+
 
 class BaseVectorDB(ABC):
 	client = None
@@ -56,7 +58,6 @@ def get_objects_from_metadata(
 		user_id: str,
 		metadata_key: str,
 		values: List[str],
-		contains: bool = False,
 	) -> dict:
 		'''
 		Get all objects with the given metadata key and values.
@@ -70,9 +71,6 @@ def get_objects_from_metadata(
 			Metadata key to get.
 		values: List[str]
 			List of metadata names to get.
-		contains: bool
-			If True, gets all objects that contain any of the given values,
-			otherwise gets all objects that have the given values.
 
 		Returns
 		-------
@@ -89,7 +87,7 @@ def get_objects_from_metadata(
 			}
 		'''
 
-	def delete_by_ids(self, user_id: str, ids: list[str]) -> Optional[bool]:
+	def delete_by_ids(self, user_id: str, ids: list[str]) -> bool:
 		'''
 		Deletes all documents with the given ids for the given user.
 
@@ -102,9 +100,9 @@ def delete_by_ids(self, user_id: str, ids: list[str]) -> Optional[bool]:
 
 		Returns
 		-------
-		Optional[bool]
-			Optional[bool]: True if deletion is successful,
-			False otherwise, None if not implemented.
+		bool
+			True if deletion is successful,
+			False otherwise
 		'''
 		if len(ids) == 0:
 			return True
@@ -113,4 +111,49 @@ def delete_by_ids(self, user_id: str, ids: list[str]) -> Optional[bool]:
 		if user_client is None:
 			return False
 
-		return user_client.delete(ids)
+		res = user_client.delete(ids)
+
+		# NOTE: None should have meant an error but it didn't in the case of
+		# weaviate maybe because of the way weaviate wrapper is implemented (langchain's api does not take
+		# class name as input, which will be required in future versions of weaviate)
+		if res is None:
+			print('Deletion query returned "None". This can happen in Weaviate even if the deletion was \
+successful, therefore not considered an error for now.')
+			return True
+
+		return res
+
+	def delete(self, user_id: str, metadata_key: str, values: list[str]) -> bool:
+		'''
+		Deletes all documents with the matching values for the given metadata key.
+
+		Args
+		----
+		user_id: str
+			User ID from whose database to delete the documents.
+		metadata_key: str
+			Metadata key to delete by.
+		values: list[str]
+			List of metadata values to match.
+
+		Returns
+		-------
+		bool
+			True if deletion is successful,
+			False otherwise
+		'''
+		if len(values) == 0:
+			return True
+
+		user_client = self.get_user_client(user_id)
+		if user_client is None:
+			return False
+
+		objs = self.get_objects_from_metadata(user_id, metadata_key, values)
+		ids = [
+			obj.get('id')
+			for obj in objs.values()
+			if value_of(obj.get('id') is not None)
+		]
+
+		return self.delete_by_ids(user_id, ids)

context_chat_backend/vectordb/chroma.py

@@ -65,7 +65,6 @@ def get_objects_from_metadata(
 		user_id: str,
 		metadata_key: str,
 		values: List[str],
-		contains: bool = False,
 	) -> dict:
 		# NOTE: the limit of objects returned is not known, maybe it would be better to set one manually
 
@@ -77,16 +76,7 @@ def get_objects_from_metadata(
 		if len(values) == 0:
 			return {}
 
-		if len(values) == 1:
-			if contains:
-				data_filter = { metadata_key: { '$in': values[0] } }
-			else:
-				data_filter = { metadata_key: values[0] }
-		else:
-			if contains:
-				data_filter = {'$or': [{ metadata_key: { '$in': val } } for val in values]}
-			else:
-				data_filter = {'$or': [{ metadata_key: val } for val in values]}
+		data_filter = { metadata_key: { '$in': values } }
 
 		try:
 			results = self.client.get_collection(COLLECTION_NAME(user_id)).get(

context_chat_backend/vectordb/weaviate.py

@@ -51,6 +51,11 @@
 			'description': 'Last modified time of the file',
 			'name': 'modified',
 		},
+		{
+			'dataType': ['text'],
+			'description': 'The provider of the source',
+			'name': 'provider',
+		}
 	],
 	# TODO: optimisation for large number of objects
 	'vectorIndexType': 'hnsw',
@@ -126,31 +131,17 @@ def get_objects_from_metadata(
 		user_id: str,
 		metadata_key: str,
 		values: List[str],
-		contains: bool = False,
 	) -> dict:
 		# NOTE: the limit of objects returned is not known, maybe it would be better to set one manually
 
 		if not self.client:
 			raise Exception('Error: Weaviate client not initialised')
 
-		if not self.client.schema.exists(COLLECTION_NAME(user_id)):
-			self.setup_schema(user_id)
+		self.setup_schema(user_id)
 
 		if len(values) == 0:
 			return {}
 
-		# todo
-		if len(values) == 1:
-			if contains:
-				data_filter = { metadata_key: { '$in': values[0] } }
-			else:
-				data_filter = { metadata_key: values[0] }
-		else:
-			if contains:
-				data_filter = {'$or': [{ metadata_key: { '$in': val } } for val in values]}
-			else:
-				data_filter = {'$or': [{ metadata_key: val } for val in values]}
-
 		data_filter = {
 			'path': [metadata_key],
 			'operator': 'ContainsAny',