From 544e08930b3ab43f5a936024e9d41542e60ec297 Mon Sep 17 00:00:00 2001
From: hajdul88 <52442977+hajdul88@users.noreply.github.com>
Date: Wed, 13 Aug 2025 14:42:57 +0200
Subject: [PATCH] feat: removing invalidValueErrors

---
 cognee-mcp/src/server.py                      | 16 -----------
 cognee/api/v1/add/add.py                      |  5 ----
 cognee/api/v1/cognify/cognify.py              |  8 ------
 cognee/api/v1/search/search.py                |  7 -----
 .../data/utils/extract_keywords.py            |  2 +-
 .../databases/exceptions/__init__.py          |  2 ++
 .../databases/exceptions/exceptions.py        | 28 +++++++++++++++++++
 .../hybrid/falkordb/FalkorDBAdapter.py        |  4 +--
 .../NeptuneAnalyticsAdapter.py                |  9 +++---
 .../vector/chromadb/ChromaDBAdapter.py        |  4 +--
 .../vector/lancedb/LanceDBAdapter.py          |  4 +--
 .../vector/pgvector/PGVectorAdapter.py        |  3 +-
 .../databases/vector/qdrant/QDrantAdapter.py  |  6 ++--
 .../vector/weaviate_db/WeaviateAdapter.py     |  6 ++--
 .../llm/anthropic/adapter.py                  |  4 +--
 .../litellm_instructor/llm/gemini/adapter.py  |  6 ++--
 .../litellm_instructor/llm/get_llm_client.py  |  4 +--
 .../litellm_instructor/llm/openai/adapter.py  |  2 +-
 .../graph/cognee_graph_elements_test.py       | 11 ++++----
 19 files changed, 62 insertions(+), 69 deletions(-)

diff --git a/cognee-mcp/src/server.py b/cognee-mcp/src/server.py
index a657225f5..3e65a5eb7 100755
--- a/cognee-mcp/src/server.py
+++ b/cognee-mcp/src/server.py
@@ -221,14 +221,6 @@ async def cognify(data: str, graph_model_file: str = None, graph_model_name: str
     - The actual cognify process may take significant time depending on text length
     - Use the cognify_status tool to check the progress of the operation
 
-    Raises
-    ------
-    InvalidValueError
-        If LLM_API_KEY is not set
-    ValueError
-        If chunks exceed max token limits (reduce chunk_size)
-    DatabaseNotCreatedError
-        If databases are not properly initialized
     """
 
     async def cognify_task(
@@ -512,14 +504,6 @@ async def search(search_query: str, search_type: str) -> list:
     - Different search types produce different output formats
     - The function handles the conversion between Cognee's internal result format and MCP's output format
 
-    Raises
-    ------
-    InvalidValueError
-        If LLM_API_KEY is not set (for LLM-based search types)
-    ValueError
-        If query_text is empty or search parameters are invalid
-    NoDataError
-        If no relevant data found for the search query
     """
 
     async def search_task(search_query: str, search_type: str) -> str:
diff --git a/cognee/api/v1/add/add.py b/cognee/api/v1/add/add.py
index 3e4aaae49..a9ad42923 100644
--- a/cognee/api/v1/add/add.py
+++ b/cognee/api/v1/add/add.py
@@ -133,11 +133,6 @@ async def add(
         - VECTOR_DB_PROVIDER: "lancedb" (default), "chromadb", "qdrant", "weaviate"
         - GRAPH_DATABASE_PROVIDER: "kuzu" (default), "neo4j", "networkx"
 
-    Raises:
-        FileNotFoundError: If specified file paths don't exist
-        PermissionError: If user lacks access to files or dataset
-        UnsupportedFileTypeError: If file format cannot be processed
-        InvalidValueError: If LLM_API_KEY is not set or invalid
     """
     tasks = [
         Task(resolve_data_directories, include_subdirectories=True),
diff --git a/cognee/api/v1/cognify/cognify.py b/cognee/api/v1/cognify/cognify.py
index c6508f3a7..23984b9a6 100644
--- a/cognee/api/v1/cognify/cognify.py
+++ b/cognee/api/v1/cognify/cognify.py
@@ -177,14 +177,6 @@ async def cognify(
         - LLM_PROVIDER, LLM_MODEL, VECTOR_DB_PROVIDER, GRAPH_DATABASE_PROVIDER
         - LLM_RATE_LIMIT_ENABLED: Enable rate limiting (default: False)
         - LLM_RATE_LIMIT_REQUESTS: Max requests per interval (default: 60)
-
-    Raises:
-        DatasetNotFoundError: If specified datasets don't exist
-        PermissionError: If user lacks processing rights
-        InvalidValueError: If LLM_API_KEY is not set
-        OntologyParsingError: If ontology file is malformed
-        ValueError: If chunks exceed max token limits (reduce chunk_size)
-        DatabaseNotCreatedError: If databases are not properly initialized
     """
     tasks = await get_default_tasks(user, graph_model, chunker, chunk_size, ontology_file_path)
 
diff --git a/cognee/api/v1/search/search.py b/cognee/api/v1/search/search.py
index 66ce48cc2..f4f4831c1 100644
--- a/cognee/api/v1/search/search.py
+++ b/cognee/api/v1/search/search.py
@@ -158,13 +158,6 @@ async def search(
         - VECTOR_DB_PROVIDER: Must match what was used during cognify
         - GRAPH_DATABASE_PROVIDER: Must match what was used during cognify
 
-    Raises:
-        DatasetNotFoundError: If specified datasets don't exist or aren't accessible
-        PermissionDeniedError: If user lacks read access to requested datasets
-        NoDataError: If no relevant data found for the search query
-        InvalidValueError: If LLM_API_KEY is not set (for LLM-based search types)
-        ValueError: If query_text is empty or search parameters are invalid
-        CollectionNotFoundError: If vector collection not found (data not processed)
     """
     # We use lists from now on for datasets
     if isinstance(datasets, UUID) or isinstance(datasets, str):
diff --git a/cognee/infrastructure/data/utils/extract_keywords.py b/cognee/infrastructure/data/utils/extract_keywords.py
index 2915131a4..8085459c9 100644
--- a/cognee/infrastructure/data/utils/extract_keywords.py
+++ b/cognee/infrastructure/data/utils/extract_keywords.py
@@ -8,7 +8,7 @@ def extract_keywords(text: str) -> list[str]:
     """
     Extract keywords from the provided text string.
 
-    This function raises an InvalidValueError if the input text is empty. It processes the
+    This function raises an KeyWordExtractionError if the input text is empty. It processes the
     text to extract parts of speech, focusing on nouns, and uses TF-IDF to identify the most
     relevant keywords based on their frequency. The function returns a list of up to 15
     keywords, each having more than 3 characters.
diff --git a/cognee/infrastructure/databases/exceptions/__init__.py b/cognee/infrastructure/databases/exceptions/__init__.py
index c7d2a8feb..56deaac74 100644
--- a/cognee/infrastructure/databases/exceptions/__init__.py
+++ b/cognee/infrastructure/databases/exceptions/__init__.py
@@ -9,4 +9,6 @@ from .exceptions import (
     EntityAlreadyExistsError,
     DatabaseNotCreatedError,
     EmbeddingException,
+    MissingQueryParameterError,
+    MutuallyExclusiveQueryParametersError
 )
diff --git a/cognee/infrastructure/databases/exceptions/exceptions.py b/cognee/infrastructure/databases/exceptions/exceptions.py
index 66740fa5e..6e1bb74f6 100644
--- a/cognee/infrastructure/databases/exceptions/exceptions.py
+++ b/cognee/infrastructure/databases/exceptions/exceptions.py
@@ -102,3 +102,31 @@ class EmbeddingException(CogneeConfigurationError):
         status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
     ):
         super().__init__(message, name, status_code)
+
+class MissingQueryParameterError(CogneeValidationError):
+    """
+    Raised when neither 'query_text' nor 'query_vector' is provided,
+    and at least one is required to perform the operation.
+    """
+    def __init__(
+        self,
+        name: str = "MissingQueryParameterError",
+        status_code: int = status.HTTP_400_BAD_REQUEST,
+    ):
+        message = "One of query_text or query_vector must be provided!"
+        super().__init__(message, name, status_code)
+
+class MutuallyExclusiveQueryParametersError(CogneeValidationError):
+    """
+    Raised when both 'text' and 'embedding' are provided to the search function,
+    but only one type of input is allowed at a time.
+    """
+    def __init__(
+        self,
+        name: str = "MutuallyExclusiveQueryParametersError",
+        status_code: int = status.HTTP_400_BAD_REQUEST,
+    ):
+        message = (
+            "The search function accepts either text or embedding as input, but not both."
+        )
+        super().__init__(message, name, status_code)
diff --git a/cognee/infrastructure/databases/hybrid/falkordb/FalkorDBAdapter.py b/cognee/infrastructure/databases/hybrid/falkordb/FalkorDBAdapter.py
index 35ce7c77e..cb6899925 100644
--- a/cognee/infrastructure/databases/hybrid/falkordb/FalkorDBAdapter.py
+++ b/cognee/infrastructure/databases/hybrid/falkordb/FalkorDBAdapter.py
@@ -9,7 +9,7 @@ from typing import List, Dict, Any, Optional, Tuple, Type, Union
 
 from falkordb import FalkorDB
 
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
 from cognee.infrastructure.databases.graph.graph_db_interface import (
     GraphDBInterface,
     record_graph_changes,
@@ -721,7 +721,7 @@ class FalkorDBAdapter(VectorDBInterface, GraphDBInterface):
             Returns the search results as a result set from the graph database.
         """
         if query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
 
         if query_text and not query_vector:
             query_vector = (await self.embed_data([query_text]))[0]
diff --git a/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py b/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py
index a04e6f09e..4baf8ff13 100644
--- a/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py
+++ b/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py
@@ -5,7 +5,8 @@ import json
 from typing import List, Optional, Any, Dict, Type, Tuple
 from uuid import UUID
 
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
+from cognee.infrastructure.databases.exceptions import MutuallyExclusiveQueryParametersError
 from cognee.infrastructure.databases.graph.neptune_driver.adapter import NeptuneGraphDB
 from cognee.infrastructure.databases.vector.vector_db_interface import VectorDBInterface
 from cognee.infrastructure.engine import DataPoint
@@ -274,11 +275,9 @@ class NeptuneAnalyticsAdapter(NeptuneGraphDB, VectorDBInterface):
             limit = self._TOPK_UPPER_BOUND
 
         if query_vector and query_text:
-            raise InvalidValueError(
-                message="The search function accepts either text or embedding as input, but not both."
-            )
+            raise MutuallyExclusiveQueryParametersError()
         elif query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
         elif query_vector:
             embedding = query_vector
         else:
diff --git a/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py b/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py
index d4b858348..81f47dddd 100644
--- a/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py
+++ b/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py
@@ -3,13 +3,13 @@ from uuid import UUID
 from typing import List, Optional
 from chromadb import AsyncHttpClient, Settings
 
-from cognee.exceptions import InvalidValueError
 from cognee.shared.logging_utils import get_logger
 from cognee.modules.storage.utils import get_own_properties
 from cognee.infrastructure.engine import DataPoint
 from cognee.infrastructure.engine.utils import parse_id
 from cognee.infrastructure.databases.vector.exceptions import CollectionNotFoundError
 from cognee.infrastructure.databases.vector.models.ScoredResult import ScoredResult
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
 
 from ..embeddings.EmbeddingEngine import EmbeddingEngine
 from ..vector_db_interface import VectorDBInterface
@@ -373,7 +373,7 @@ class ChromaDBAdapter(VectorDBInterface):
             Returns a list of ScoredResult instances representing the search results.
         """
         if query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
 
         if query_text and not query_vector:
             query_vector = (await self.embedding_engine.embed_text([query_text]))[0]
diff --git a/cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py b/cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py
index f37c83113..0184ec3ee 100644
--- a/cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py
+++ b/cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py
@@ -5,7 +5,7 @@ from pydantic import BaseModel
 from lancedb.pydantic import LanceModel, Vector
 from typing import Generic, List, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
 
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
 from cognee.infrastructure.engine import DataPoint
 from cognee.infrastructure.engine.utils import parse_id
 from cognee.infrastructure.files.storage import get_file_storage
@@ -228,7 +228,7 @@ class LanceDBAdapter(VectorDBInterface):
         normalized: bool = True,
     ):
         if query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
 
         if query_text and not query_vector:
             query_vector = (await self.embedding_engine.embed_text([query_text]))[0]
diff --git a/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py b/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py
index 96b2056c4..4dfd9792f 100644
--- a/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py
+++ b/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py
@@ -17,6 +17,7 @@ from cognee.infrastructure.databases.relational import get_relational_engine
 
 from distributed.utils import override_distributed
 from distributed.tasks.queued_add_data_points import queued_add_data_points
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
 
 from ...relational.ModelBase import Base
 from ...relational.sqlalchemy.SqlAlchemyAdapter import SQLAlchemyAdapter
@@ -302,7 +303,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         with_vector: bool = False,
     ) -> List[ScoredResult]:
         if query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
 
         if query_text and not query_vector:
             query_vector = (await self.embedding_engine.embed_text([query_text]))[0]
diff --git a/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py b/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py
index 716fc969f..aa1368716 100644
--- a/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py
+++ b/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py
@@ -4,7 +4,7 @@ from qdrant_client import AsyncQdrantClient, models
 
 from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.engine.utils import parse_id
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
 from cognee.infrastructure.engine import DataPoint
 from cognee.infrastructure.databases.vector.exceptions import CollectionNotFoundError
 from cognee.infrastructure.databases.vector.models.ScoredResult import ScoredResult
@@ -363,7 +363,7 @@ class QDrantAdapter(VectorDBInterface):
         Search for data points in a collection based on either a textual query or a vector
         query.
 
-        Raises InvalidValueError if both query_text and query_vector are None.
+        Raises MissingQueryParameterError if both query_text and query_vector are None.
 
         Returns a list of scored results that match the search criteria.
 
@@ -388,7 +388,7 @@ class QDrantAdapter(VectorDBInterface):
         from qdrant_client.http.exceptions import UnexpectedResponse
 
         if query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
 
         if not await self.has_collection(collection_name):
             return []
diff --git a/cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py b/cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py
index 00a6a0411..db68e004e 100644
--- a/cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py
+++ b/cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py
@@ -3,7 +3,7 @@ from typing import List, Optional
 from tenacity import retry, retry_if_exception, stop_after_attempt, wait_exponential
 
 from cognee.shared.logging_utils import get_logger
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.databases.exceptions import MissingQueryParameterError
 from cognee.infrastructure.engine import DataPoint
 from cognee.infrastructure.engine.utils import parse_id
 from cognee.infrastructure.databases.vector.exceptions import CollectionNotFoundError
@@ -390,7 +390,7 @@ class WeaviateAdapter(VectorDBInterface):
         """
         Perform a search on a collection using either a text query or a vector query.
 
-        Return scored results based on the search criteria provided. Raise InvalidValueError if
+        Return scored results based on the search criteria provided. Raise MissingQueryParameterError if
         no query is provided.
 
         Parameters:
@@ -413,7 +413,7 @@ class WeaviateAdapter(VectorDBInterface):
         import weaviate.exceptions
 
         if query_text is None and query_vector is None:
-            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+            raise MissingQueryParameterError()
 
         if query_vector is None:
             query_vector = (await self.embed_data([query_text]))[0]
diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py
index 636e6c0f2..6845fb6aa 100644
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py
@@ -2,7 +2,7 @@ from typing import Type
 from pydantic import BaseModel
 import instructor
 
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.llm.exceptions import MissingSystemPromptPathError
 from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.llm_interface import (
     LLMInterface,
 )
@@ -89,7 +89,7 @@ class AnthropicAdapter(LLMInterface):
         if not text_input:
             text_input = "No user input provided."
         if not system_prompt:
-            raise InvalidValueError(message="No system prompt path provided.")
+            raise MissingSystemPromptPathError()
 
         system_prompt = LLMGateway.read_query_prompt(system_prompt)
 
diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py
index 61d42ff5f..3cde1fdc4 100644
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py
@@ -5,7 +5,7 @@ from litellm import acompletion, JSONSchemaValidationError
 
 from cognee.shared.logging_utils import get_logger
 from cognee.modules.observability.get_observe import get_observe
-from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.llm.exceptions import MissingSystemPromptPathError
 from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.llm_interface import (
     LLMInterface,
 )
@@ -118,7 +118,7 @@ class GeminiAdapter(LLMInterface):
         """
         Format and display the prompt for a user query.
 
-        Raises an InvalidValueError if no system prompt is provided.
+        Raises an MissingQueryParameterError if no system prompt is provided.
 
         Parameters:
         -----------
@@ -135,7 +135,7 @@ class GeminiAdapter(LLMInterface):
         if not text_input:
             text_input = "No user input provided."
         if not system_prompt:
-            raise InvalidValueError(message="No system prompt path provided.")
+            raise MissingSystemPromptPathError()
         system_prompt = LLMGateway.read_query_prompt(system_prompt)
 
         formatted_prompt = (
diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py
index 3006a795b..fd347aef3 100644
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py
@@ -38,7 +38,7 @@ def get_llm_client():
 
     This function retrieves the configuration for the LLM provider and model, and
     initializes the appropriate LLM client adapter accordingly. It raises an
-    InvalidValueError if the LLM API key is not set for certain providers or if the provider
+    LLMAPIKeyNotSetError if the LLM API key is not set for certain providers or if the provider
     is unsupported.
 
     Returns:
@@ -62,7 +62,7 @@ def get_llm_client():
 
     if provider == LLMProvider.OPENAI:
         if llm_config.llm_api_key is None:
-            raise InvalidValueError(message="LLM API key is not set.")
+            raise LLMAPIKeyNotSetError()
 
         from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.openai.adapter import (
             OpenAIAdapter,
diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py
index 38e1bc82e..4126b3e13 100644
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py
@@ -307,7 +307,7 @@ class OpenAIAdapter(LLMInterface):
         Format and display the prompt for a user query.
 
         This method formats the prompt using the provided user input and system prompt,
-        returning a string representation. Raises InvalidValueError if the system prompt is not
+        returning a string representation. Raises MissingSystemPromptPathError if the system prompt is not
         provided.
 
         Parameters:
diff --git a/cognee/tests/unit/modules/graph/cognee_graph_elements_test.py b/cognee/tests/unit/modules/graph/cognee_graph_elements_test.py
index 000856b12..a852bcee3 100644
--- a/cognee/tests/unit/modules/graph/cognee_graph_elements_test.py
+++ b/cognee/tests/unit/modules/graph/cognee_graph_elements_test.py
@@ -1,9 +1,8 @@
 import numpy as np
 import pytest
 
-from cognee.exceptions import InvalidValueError
 from cognee.modules.graph.cognee_graph.CogneeGraphElements import Edge, Node
-
+from cognee.modules.graph.exceptions import InvalidDimensionsError, DimensionOutOfRangeError
 
 def test_node_initialization():
     """Test that a Node is initialized correctly."""
@@ -16,7 +15,7 @@ def test_node_initialization():
 
 def test_node_invalid_dimension():
     """Test that initializing a Node with a non-positive dimension raises an error."""
-    with pytest.raises(InvalidValueError, match="Dimension must be a positive integer"):
+    with pytest.raises(InvalidDimensionsError, match="Dimensions must be a positive integers"):
         Node("node1", dimension=0)
 
 
@@ -69,7 +68,7 @@ def test_is_node_alive_in_dimension():
 def test_node_alive_invalid_dimension():
     """Test that checking alive status with an invalid dimension raises an error."""
     node = Node("node1", dimension=1)
-    with pytest.raises(InvalidValueError, match="Dimension 1 is out of range"):
+    with pytest.raises(DimensionOutOfRangeError, match="Dimension 1 is out of range"):
         node.is_node_alive_in_dimension(1)
 
 
@@ -106,7 +105,7 @@ def test_edge_invalid_dimension():
     """Test that initializing an Edge with a non-positive dimension raises an error."""
     node1 = Node("node1")
     node2 = Node("node2")
-    with pytest.raises(InvalidValueError, match="Dimensions must be a positive integer."):
+    with pytest.raises(DimensionOutOfRangeError, match="Dimensions must be a positive integer."):
         Edge(node1, node2, dimension=0)
 
 
@@ -125,7 +124,7 @@ def test_edge_alive_invalid_dimension():
     node1 = Node("node1")
     node2 = Node("node2")
     edge = Edge(node1, node2, dimension=1)
-    with pytest.raises(InvalidValueError, match="Dimension 1 is out of range"):
+    with pytest.raises(DimensionOutOfRangeError, match="Dimension 1 is out of range"):
         edge.is_edge_alive_in_dimension(1)