fix: allow alternative vector db engine to be used #106
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Warning Review failedThe pull request is closed. WalkthroughThe recent changes enhance the Changes
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Actionable comments posted: 10
Outside diff range and nitpick comments (5)
cognee-frontend/src/app/page.tsx (1)
Line range hint
7-7: Consider renaming theDataViewvariable to avoid shadowing the global name.- import DataView, { Data } from '@/modules/ingestion/DataView'; + import CustomDataView, { Data } from '@/modules/ingestion/DataView';evals/simple_rag_vs_cognee_eval.py (2)
Line range hint
76-76: Remove unused variable to clean up the code.- graph = await cognify("initial_test")This variable is assigned but never used, which could lead to confusion and unnecessary memory usage.
Tools
Ruff
83-83: Module level import not at top of file (E402)
84-84: Module level import not at top of file (E402)
85-85: Module level import not at top of file (E402)
Line range hint
10-10: Consider reorganizing imports to improve readability and maintainability.It's a common Python best practice to place all module-level imports at the top of the file unless there's a specific reason (like avoiding circular dependencies). This helps in understanding dependencies of the module at a glance.
Also applies to: 43-43, 83-83, 84-84, 85-85
Tools
Ruff
83-83: Module level import not at top of file (E402)
84-84: Module level import not at top of file (E402)
85-85: Module level import not at top of file (E402)
cognee/modules/cognify/graph/add_cognitive_layer_graphs.py (1)
Line range hint
21-146: Ensure consistent error handling and logging.While the integration of the vector engine is well executed, consider adding more robust error handling around the vector engine's operations. This could include logging specific errors or retry mechanisms in case of transient failures.
cognee/api/v1/cognify/cognify.py (1)
Line range hint
212-212: Avoid using bareexceptstatements.Using a bare
exceptcan catch unexpected exceptions and obscure underlying issues. Specify the exception types to improve error handling and maintainability.- except: + except SpecificExceptionType:
Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Files selected for processing (23)
- cognee-frontend/src/app/page.tsx (1 hunks)
- cognee/api/client.py (3 hunks)
- cognee/api/v1/cognify/cognify.py (1 hunks)
- cognee/api/v1/config/config.py (1 hunks)
- cognee/infrastructure/databases/vector/init.py (1 hunks)
- cognee/infrastructure/databases/vector/config.py (1 hunks)
- cognee/infrastructure/databases/vector/create_vector_engine.py (1 hunks)
- cognee/infrastructure/databases/vector/embeddings/FastembedEmbeddingEngine.py (1 hunks)
- cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py (1 hunks)
- cognee/infrastructure/databases/vector/embeddings/init.py (1 hunks)
- cognee/infrastructure/databases/vector/embeddings/config.py (1 hunks)
- cognee/infrastructure/databases/vector/embeddings/get_embedding_engine.py (1 hunks)
- cognee/infrastructure/databases/vector/get_vector_engine.py (1 hunks)
- cognee/modules/cognify/graph/add_cognitive_layer_graphs.py (4 hunks)
- cognee/modules/cognify/graph/add_data_chunks.py (6 hunks)
- cognee/modules/cognify/graph/add_label_nodes.py (2 hunks)
- cognee/modules/cognify/llm/resolve_cross_graph_references.py (2 hunks)
- cognee/modules/data/deletion/prune_system.py (2 hunks)
- cognee/modules/search/vector/search_similarity.py (2 hunks)
- cognee/modules/settings/get_settings.py (1 hunks)
- cognee/modules/settings/save_vector_db_config.py (1 hunks)
- cognee/modules/tasks/get_task_status.py (2 hunks)
- evals/simple_rag_vs_cognee_eval.py (1 hunks)
Files skipped from review due to trivial changes (3)
- cognee/infrastructure/databases/vector/create_vector_engine.py
- cognee/infrastructure/databases/vector/embeddings/init.py
- cognee/modules/settings/save_vector_db_config.py
Additional context used
Biome
cognee-frontend/src/app/page.tsx
[error] 7-7: Do not shadow the global "DataView" property. (lint/suspicious/noShadowRestrictedNames)
Consider renaming this variable. It's easy to confuse the origin of variables when they're named after a known global.
Ruff
evals/simple_rag_vs_cognee_eval.py
10-10: Module level import not at top of file (E402)
43-43: Module level import not at top of file (E402)
76-76: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
83-83: Module level import not at top of file (E402)
84-84: Module level import not at top of file (E402)
85-85: Module level import not at top of file (E402)
cognee/api/client.py
85-85: Do not use bare
except(E722)cognee/api/v1/cognify/cognify.py
212-212: Do not use bare
except(E722)
Additional comments not posted (14)
cognee/infrastructure/databases/vector/get_vector_engine.py (1)
5-6: LGTM! The functionget_vector_engineeffectively combines vector DB configurations and embedding engines.cognee/infrastructure/databases/vector/__init__.py (1)
6-6: The import ofget_vector_engineis appropriate and aligns with the refactoring goals to centralize vector engine access.cognee/modules/data/deletion/prune_system.py (1)
12-13: The integration ofget_vector_enginein theprune_systemfunction is correctly implemented, ensuring that vector-related deletions are handled through the centralized engine access.cognee/modules/tasks/get_task_status.py (2)
19-19: Refactor to improve readability of dictionary comprehension.- return { dataset["data_id"]: dataset["status"] for dataset in datasets_statuses } + return {dataset["data_id"]: dataset["status"] for dataset in datasets_statuses}Likely invalid or redundant comment.
9-9: Ensure the SQL query is optimized for performance.cognee/infrastructure/databases/vector/embeddings/config.py (1)
9-9: Clarify the reason for commenting outDefaultEmbeddingEngine.cognee/modules/cognify/llm/resolve_cross_graph_references.py (1)
19-19: LGTM! Ensure thatget_vector_engineis properly integrated and tested across the system.cognee/modules/cognify/graph/add_label_nodes.py (1)
8-8: LGTM! Ensure thatget_vector_engineis properly integrated and tested across the system.cognee/modules/settings/get_settings.py (1)
43-43: Enhanced API key masking logic for improved security.Verification successful
The enhanced API key masking logic has been successfully verified. The code correctly masks the last 10 characters of the API key.
cognee/modules/settings/get_settings.py: The API key is masked as expected.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the API key masking logic by checking if the last 10 characters are masked. # Test: Search for API key usage in the codebase. Expect: All API keys should be masked. rg --type python $'llm_api_key[:-10] + "**********"'Length of output: 196
Script:
#!/bin/bash # Description: Verify the API key masking logic by checking if the last 10 characters are masked. # Test: Search for API key usage in the codebase. Expect: All API keys should be masked. rg --type python 'llm_api_key\[:-10\] \+ "**********"'Length of output: 87
Script:
#!/bin/bash # Description: Verify the API key masking logic by checking if the last 10 characters are masked. # Test: Search for API key usage in the codebase. Expect: All API keys should be masked. rg 'llm_api_key\[:-10\] \+ "**********"'Length of output: 187
cognee/modules/cognify/graph/add_data_chunks.py (1)
12-12: Refactored to useget_vector_enginefor obtaining vector engine instances.Also applies to: 54-54
Verification successful
The integration of
get_vector_engineappears consistent across multiple modules in the codebase.
evals/simple_rag_vs_cognee_eval.pycognee/modules/search/vector/search_similarity.pycognee/modules/data/deletion/prune_system.pycognee/modules/cognify/graph/add_cognitive_layer_graphs.pycognee/modules/cognify/graph/add_label_nodes.pycognee/modules/cognify/graph/add_data_chunks.pycognee/modules/cognify/llm/resolve_cross_graph_references.pycognee/infrastructure/databases/vector/get_vector_engine.pycognee/infrastructure/databases/vector/__init__.pyRefactored to use
get_vector_enginefor obtaining vector engine instances.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the integration of `get_vector_engine` in the system. # Test: Search for `get_vector_engine` usage in the codebase. Expect: Consistent usage across all modules. rg --type python $'get_vector_engine'Length of output: 67
Script:
#!/bin/bash # Description: Verify the integration of `get_vector_engine` in the system. # Test: Search for `get_vector_engine` usage in the codebase. Expect: Consistent usage across all modules. rg --type py 'get_vector_engine'Length of output: 1801
cognee/api/v1/config/config.py (1)
20-21: Configured specific URL forlancedbvector engine provider.Verification successful
The verification of the
vector_db_urlsetting logic shows that it is consistently used across multiple files in the codebase. The URL is being set correctly for thelancedbprovider and is utilized in various configurations and settings.
cognee/api/v1/config/config.pycognee/api/client.pycognee/modules/settings/get_settings.pycognee/infrastructure/databases/vector/config.pycognee/modules/settings/save_vector_db_config.pycognee/infrastructure/databases/vector/create_vector_engine.pyThe logic for setting and using
vector_db_urlappears to be correctly implemented.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the URL setting logic for `lancedb`. # Test: Search for `vector_db_url` usage in the codebase. Expect: Correct URL format and usage. rg --type python $'vector_db_url'Length of output: 63
Script:
#!/bin/bash # Description: Verify the URL setting logic for `lancedb`. # Test: Search for `vector_db_url` usage in the codebase. Expect: Correct URL format and usage. rg --type py 'vector_db_url'Length of output: 1324
Script:
#!/bin/bash # Description: Extract relevant code snippets for `vector_db_url` usage. # Extract lines around the usage of `vector_db_url` in the identified files. rg --type py --context 5 'vector_db_url' cognee/infrastructure/databases/vector/create_vector_engine.py cognee/infrastructure/databases/vector/config.py cognee/modules/settings/get_settings.py cognee/modules/settings/save_vector_db_config.py cognee/api/client.py cognee/api/v1/config/config.pyLength of output: 8616
cognee-frontend/src/app/page.tsx (1)
115-115: Addednowrapattribute to improve notification text display.cognee/modules/cognify/graph/add_cognitive_layer_graphs.py (1)
5-5: Good use of imports to support the new vector engine functionality.The inclusion of
get_vector_enginefrom the vector module aligns with the changes across the project to centralize vector engine access, enhancing modularity and maintainability.Also applies to: 7-7
cognee/api/client.py (1)
273-273: Ensure the new vector database URL configuration is robust.This change is crucial for the system's operation. Verify that it's consistently used across all relevant parts of the application.
Verification successful
The search results indicate that the
vector_db_urlconfiguration is used in multiple files across the system. This suggests that the new vector database URL configuration is indeed applied consistently.
cognee/api/client.pycognee/api/v1/config/config.pycognee/infrastructure/databases/vector/config.pycognee/infrastructure/databases/vector/create_vector_engine.pycognee/modules/settings/save_vector_db_config.pycognee/modules/settings/get_settings.pyThese references confirm that the configuration change is propagated throughout the relevant parts of the application.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the vector database URL configuration. # Test: Check if the URL configuration is applied correctly across the system. rg --type python 'vector_db_url'Length of output: 63
Script:
#!/bin/bash # Description: Verify the vector database URL configuration. # Test: Check if the URL configuration is applied correctly across the system. rg --type py 'vector_db_url'Length of output: 1324
| def get_embedding_engine() -> EmbeddingEngine: | ||
| llm_config = get_llm_config() | ||
| return LiteLLMEmbeddingEngine(api_key = llm_config.llm_api_key) |
There was a problem hiding this comment.
Consider enhancing get_embedding_engine to support multiple types of embedding engines based on configuration, improving flexibility.
def get_embedding_engine() -> EmbeddingEngine:
llm_config = get_llm_config()
if llm_config.engine_type == 'LiteLLM':
return LiteLLMEmbeddingEngine(api_key=llm_config.llm_api_key)
# Add other conditions for different engines as needed| vector_db_url: str = os.path.join( | ||
| os.path.join(get_absolute_path(".cognee_system"), "databases"), | ||
| "cognee.lancedb" | ||
| ) |
There was a problem hiding this comment.
Simplify nested os.path.join calls.
- vector_db_url: str = os.path.join(
- os.path.join(get_absolute_path(".cognee_system"), "databases"),
- "cognee.lancedb"
- )
+ vector_db_url: str = os.path.join(get_absolute_path(".cognee_system"), "databases", "cognee.lancedb")Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| vector_db_url: str = os.path.join( | |
| os.path.join(get_absolute_path(".cognee_system"), "databases"), | |
| "cognee.lancedb" | |
| ) | |
| vector_db_url: str = os.path.join(get_absolute_path(".cognee_system"), "databases", "cognee.lancedb") |
| class LiteLLMEmbeddingEngine(EmbeddingEngine): | ||
| api_key: str | ||
| embedding_model: str | ||
| embedding_dimensions: int | ||
|
|
||
| def __init__( | ||
| self, | ||
| embedding_model: Optional[str] = "text-embedding-3-large", | ||
| embedding_dimensions: Optional[int] = 3072, | ||
| api_key: str = None, | ||
| ): | ||
| self.api_key = api_key | ||
| self.embedding_model = embedding_model | ||
| self.embedding_dimensions = embedding_dimensions | ||
|
|
||
| async def embed_text(self, text: List[str]) -> List[List[float]]: | ||
| async def get_embedding(text_): | ||
| response = await aembedding( | ||
| self.embedding_model, | ||
| input = text_, | ||
| api_key = self.api_key | ||
| ) | ||
|
|
||
| return response.data[0]["embedding"] | ||
|
|
||
| tasks = [get_embedding(text_) for text_ in text] | ||
| result = await asyncio.gather(*tasks) | ||
| return result | ||
|
|
||
| def get_vector_size(self) -> int: | ||
| return self.embedding_dimensions |
There was a problem hiding this comment.
Great addition with LiteLLMEmbeddingEngine. Ensure proper error handling in asynchronous operations and consider adding logging for better traceability.
+ import logging
+ logger = logging.getLogger(__name__)
async def embed_text(self, text: List[str]) -> List[List[float]]:
async def get_embedding(text_):
try:
response = await aembedding(
self.embedding_model,
input = text_,
api_key = self.api_key
)
+ logger.info(f"Embedding successful for text: {text_}")
return response.data[0]["embedding"]
+ except Exception as e:
+ logger.error(f"Failed to embed text: {text_}, Error: {str(e)}")
+ raiseCommittable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| class LiteLLMEmbeddingEngine(EmbeddingEngine): | |
| api_key: str | |
| embedding_model: str | |
| embedding_dimensions: int | |
| def __init__( | |
| self, | |
| embedding_model: Optional[str] = "text-embedding-3-large", | |
| embedding_dimensions: Optional[int] = 3072, | |
| api_key: str = None, | |
| ): | |
| self.api_key = api_key | |
| self.embedding_model = embedding_model | |
| self.embedding_dimensions = embedding_dimensions | |
| async def embed_text(self, text: List[str]) -> List[List[float]]: | |
| async def get_embedding(text_): | |
| response = await aembedding( | |
| self.embedding_model, | |
| input = text_, | |
| api_key = self.api_key | |
| ) | |
| return response.data[0]["embedding"] | |
| tasks = [get_embedding(text_) for text_ in text] | |
| result = await asyncio.gather(*tasks) | |
| return result | |
| def get_vector_size(self) -> int: | |
| return self.embedding_dimensions | |
| import logging | |
| class LiteLLMEmbeddingEngine(EmbeddingEngine): | |
| api_key: str | |
| embedding_model: str | |
| embedding_dimensions: int | |
| def __init__( | |
| self, | |
| embedding_model: Optional[str] = "text-embedding-3-large", | |
| embedding_dimensions: Optional[int] = 3072, | |
| api_key: str = None, | |
| ): | |
| self.api_key = api_key | |
| self.embedding_model = embedding_model | |
| self.embedding_dimensions = embedding_dimensions | |
| async def embed_text(self, text: List[str]) -> List[List[float]]: | |
| logger = logging.getLogger(__name__) | |
| async def get_embedding(text_): | |
| try: | |
| response = await aembedding( | |
| self.embedding_model, | |
| input = text_, | |
| api_key = self.api_key | |
| ) | |
| logger.info(f"Embedding successful for text: {text_}") | |
| return response.data[0]["embedding"] | |
| except Exception as e: | |
| logger.error(f"Failed to embed text: {text_}, Error: {str(e)}") | |
| raise | |
| tasks = [get_embedding(text_) for text_ in text] | |
| result = await asyncio.gather(*tasks) | |
| return result | |
| def get_vector_size(self) -> int: | |
| return self.embedding_dimensions |
| from cognee.infrastructure.databases.vector import get_vector_engine | ||
|
|
||
| async def cognify_search_base_rag(content:str, context:str): | ||
| base_config = get_base_config() | ||
|
|
||
| cognee_directory_path = os.path.abspath(".cognee_system") | ||
| base_config.system_root_directory = cognee_directory_path | ||
|
|
||
| vector_config = get_vectordb_config() | ||
| vector_client = vector_config.vector_engine | ||
| vector_engine = get_vector_engine() | ||
|
|
||
| return_ = await vector_client.search(collection_name="basic_rag", query_text=content, limit=10) | ||
| return_ = await vector_engine.search(collection_name="basic_rag", query_text=content, limit=10) |
There was a problem hiding this comment.
Refactor to use the new vector engine and ensure proper error handling.
The change to use get_vector_engine() instead of a direct vector client is a good move towards modularity. However, ensure that the error handling is robust, especially when the vector engine might throw exceptions that are not caught here.
Tools
Ruff
85-85: Module level import not at top of file (E402)
|
|
||
|
|
||
| def generate_node_id(node_id: str) -> str: | ||
| return node_id.upper().replace(' ', '_').replace("'", "") | ||
| return node_id.upper().replace(" ", "_").replace("'", "") |
There was a problem hiding this comment.
Optimize ID generation for efficiency.
The method generate_node_id could be optimized or simplified if it's a common operation that might impact performance. Consider caching results if IDs are regenerated often with the same inputs.
| @@ -62,9 +59,9 @@ class PayloadSchema(BaseModel): | |||
| ] | |||
|
|
|||
| try: | |||
| await vector_client.create_collection(parent_node_id, payload_schema = PayloadSchema) | |||
| await vector_engine.create_collection(parent_node_id, payload_schema = PayloadSchema) | |||
There was a problem hiding this comment.
Consider handling specific exceptions when creating collections to improve robustness.
- except Exception as e:
+ except CollectionCreationError as e:Committable suggestion was skipped due to low confidence.
| from typing import List, Optional | ||
| from fastembed import TextEmbedding | ||
| from cognee.root_dir import get_absolute_path | ||
| from cognee.infrastructure.databases.vector.embeddings.EmbeddingEngine import EmbeddingEngine | ||
|
|
||
| class FastembedEmbeddingEngine(EmbeddingEngine): | ||
| embedding_model: str | ||
| embedding_dimensions: int | ||
|
|
||
| def __init__( | ||
| self, | ||
| embedding_model: Optional[str] = "BAAI/bge-large-en-v1.5", | ||
| embedding_dimensions: Optional[int] = 1024, | ||
| ): | ||
| self.embedding_model = embedding_model | ||
| self.embedding_dimensions = embedding_dimensions | ||
|
|
||
| async def embed_text(self, text: List[str]) -> List[float]: | ||
| embedding_model = TextEmbedding(model_name = self.embedding_model, cache_dir = get_absolute_path("cache/embeddings")) | ||
| embeddings_list = list(map(lambda embedding: embedding.tolist(), embedding_model.embed(text))) | ||
|
|
||
| return embeddings_list | ||
|
|
||
| def get_vector_size(self) -> int: | ||
| return self.embedding_dimensions |
There was a problem hiding this comment.
Ensure proper error handling in embed_text method.
- embeddings_list = list(map(lambda embedding: embedding.tolist(), embedding_model.embed(text)))
+ try:
+ embeddings_list = list(map(lambda embedding: embedding.tolist(), embedding_model.embed(text)))
+ except Exception as e:
+ # Handle specific exceptions related to embedding failures
+ raise eCommittable suggestion was skipped due to low confidence.
Tip
Codebase Verification
The search results indicate that the optional parameters embedding_model and embedding_dimensions are used directly without any additional validation for None values. However, since default values are provided in the constructor, these parameters will not be None unless explicitly set to None by the caller.
Given this context, the default values should suffice for typical usage, but it might be prudent to add validation to handle cases where these parameters might be explicitly set to None.
- File:
cognee/infrastructure/databases/vector/embeddings/FastembedEmbeddingEngine.py - Lines: 1-25
Consider adding validation checks in the constructor to handle cases where embedding_model or embedding_dimensions might be explicitly set to None.
Analysis chain
Validate the optional parameters in the constructor.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the handling of optional parameters in `FastembedEmbeddingEngine`.
# Test: Check if there are any checks for `None` values for optional parameters.
rg --type python $'if embedding_model is None' --context 5 src/
Length of output: 95
Script:
#!/bin/bash
# Description: Verify the handling of optional parameters in `FastembedEmbeddingEngine`.
# Test: Check if there are any checks for `None` values for optional parameters.
rg --type py $'if embedding_model is None' --context 5
Length of output: 55
Script:
#!/bin/bash
# Description: Verify the usage and handling of `embedding_model` and `embedding_dimensions` in the codebase.
# Test: Search for the usage of `embedding_model` and `embedding_dimensions` in the codebase.
rg 'embedding_model' --type py --context 5
rg 'embedding_dimensions' --type py --context 5
Length of output: 16036
cognee/api/client.py
Outdated
| try: | ||
| graph_config = get_graph_config() | ||
| graph_engine = graph_config.graph_engine | ||
| graph_client = await get_graph_client(graph_engine) | ||
| graph_url = await render_graph(graph_client.graph) | ||
|
|
||
| return JSONResponse( | ||
| status_code = 200, | ||
| content = str(graph_url), | ||
| ) | ||
| return JSONResponse( | ||
| status_code = 200, | ||
| content = str(graph_url), | ||
| ) | ||
| except: | ||
| return JSONResponse( | ||
| status_code = 409, | ||
| content = "Graphistry credentials are not set. Please set them in your .env file.", | ||
| ) |
There was a problem hiding this comment.
Improve error handling by specifying exception types.
Using a bare except is generally discouraged as it can catch unexpected exceptions and make debugging more difficult. Specify the exception types to improve clarity and maintainability.
- except:
+ except SpecificExceptionType:Committable suggestion was skipped due to low confidence.
Tools
Ruff
85-85: Do not use bare
except(E722)
There was a problem hiding this comment.
Actionable comments posted: 2
Outside diff range and nitpick comments (2)
cognee/infrastructure/data/chunking/LangchainChunkingEngine.py (1)
Line range hint
9-66: Consider moving the imports forlangchain_text_splittersto the top of the file to improve performance and maintainability.+ from langchain_text_splitters import ( + Language, + RecursiveCharacterTextSplitter, + ) - from langchain_text_splitters import ( - Language, - RecursiveCharacterTextSplitter, - )The
LangchainChunkEngineclass is well-designed, with clear methods for chunking data based on different strategies.cognee/api/v1/cognify/cognify.py (1)
Line range hint
216-216: Avoid using a bareexceptstatement.Using a bare
exceptcan catch unexpected exceptions and obscure underlying bugs. Specify exception types to improve error handling clarity and maintainability.- except: + except ExpectedExceptionType:
Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Files ignored due to path filters (1)
poetry.lockis excluded by!**/*.lock
Files selected for processing (10)
- cognee/api/v1/cognify/cognify.py (5 hunks)
- cognee/api/v1/config/config.py (2 hunks)
- cognee/infrastructure/data/chunking/DefaultChunkEngine.py (5 hunks)
- cognee/infrastructure/data/chunking/HaystackChunkEngine.py (1 hunks)
- cognee/infrastructure/data/chunking/LangchainChunkingEngine.py (3 hunks)
- cognee/infrastructure/data/chunking/config.py (1 hunks)
- cognee/infrastructure/data/chunking/create_chunking_engine.py (1 hunks)
- cognee/infrastructure/data/chunking/get_chunking_engine.py (1 hunks)
- cognee/modules/ingestion/save_data_to_file.py (2 hunks)
- pyproject.toml (2 hunks)
Files skipped from review as they are similar to previous changes (1)
- cognee/api/v1/config/config.py
Additional context used
Ruff
cognee/api/v1/cognify/cognify.py
216-216: Do not use bare
except(E722)
288-288: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
Additional comments not posted (11)
cognee/infrastructure/data/chunking/get_chunking_engine.py (1)
5-6: LGTM! Consider adding error handling for configuration retrieval and engine creation.cognee/infrastructure/data/chunking/HaystackChunkEngine.py (1)
2-6: Constructor implementation looks good. Consider adding docstrings to explain the parameters and their default values.cognee/infrastructure/data/chunking/config.py (1)
10-12: Change inchunk_overlapvalue looks good. Ensure that this new value is appropriately handled in all relevant parts of the application.Verification successful
The new
chunk_overlapvalue is indeed used in various parts of the codebase, including configuration settings and chunking engine implementations. This confirms that the new value is being handled appropriately.
- Files and lines where
chunk_overlapis used:
cognee/api/v1/cognify/cognify.py: Line 1cognee/api/v1/config/config.py: Lines 1-2cognee/infrastructure/data/chunking/create_chunking_engine.py: Lines 1-3cognee/infrastructure/data/chunking/DefaultChunkEngine.py: Multiple linescognee/infrastructure/data/chunking/config.py: Line 1cognee/infrastructure/data/chunking/LangchainChunkingEngine.py: Multiple linescognee/infrastructure/data/chunking/HaystackChunkEngine.py: Line 1Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that the new `chunk_overlap` value is handled correctly. # Test: Search for usage of `chunk_overlap`. Expect: Proper handling of the new value. rg --type python $'chunk_overlap'Length of output: 63
Script:
#!/bin/bash # Description: Verify that the new `chunk_overlap` value is handled correctly. # Test: Search for usage of `chunk_overlap`. Expect: Proper handling of the new value. rg 'chunk_overlap'Length of output: 4470
cognee/modules/ingestion/save_data_to_file.py (1)
18-21: Implementation of random file name generation looks good. Consider adding a comment explaining why a random file name is generated when the 'name' is missing or None.cognee/infrastructure/data/chunking/create_chunking_engine.py (1)
6-9: TheChunkingConfigclass is well-defined and aligns with the need to store configuration settings for different chunking engines.pyproject.toml (1)
41-41: The updates to dependencies are appropriate for the new functionalities introduced in the PR.Also applies to: 75-75
cognee/infrastructure/data/chunking/DefaultChunkEngine.py (1)
Line range hint
8-94: TheDefaultChunkEngineclass is well-designed, with clear methods for chunking data based on different strategies.cognee/api/v1/cognify/cognify.py (4)
9-12: Imports added for chunking and embedding engines.These imports align with the PR's objective to enhance the system's flexibility in handling different data chunking and embedding strategies.
30-30: Import added forKnowledgeGraphandChunkStrategy.This import is necessary for the new functionalities introduced in the system, ensuring that the types and strategies are correctly utilized in the processing functions.
74-79: Enhanced error handling in thecognifyfunction.The addition of a try-except block around the
cognifycall for each dataset is a robust way to handle potential errors during dataset processing, ensuring that the system can gracefully handle failures and log them appropriately.
101-101: Initialization ofchunk_engineusing theget_chunk_enginefunction.This change supports the dynamic selection of chunking engines based on configuration, which is a flexible design choice that aligns with the system's extensibility goals.
| def create_chunking_engine(config: ChunkingConfig): | ||
| if config["chunk_engine"] == "langchainchunkengine": | ||
|
|
||
| return LangchainChunkEngine( | ||
| chunk_size=config["chunk_size"], | ||
| chunk_overlap=config["chunk_overlap"], | ||
| chunk_strategy=config["chunk_strategy"], | ||
|
|
||
|
|
||
| ) | ||
| elif config["chunk_engine"] == "defaultchunkengine": | ||
| from .DefaultChunkEngine import DefaultChunkEngine | ||
|
|
||
| return DefaultChunkEngine( | ||
| chunk_size=config["chunk_size"], | ||
| chunk_overlap=config["chunk_overlap"], | ||
| chunk_strategy=config["chunk_strategy"], | ||
| ) | ||
| elif config["chunk_engine"] == "haystackchunkengine": | ||
| from .HaystackChunkEngine import HaystackChunkEngine | ||
|
|
||
| return HaystackChunkEngine( | ||
| chunk_size=config["chunk_size"], | ||
| chunk_overlap=config["chunk_overlap"], | ||
| chunk_strategy=config["chunk_strategy"], | ||
| ) |
There was a problem hiding this comment.
Consider moving the import statements to the top of the file to improve performance and maintainability.
+ from .DefaultChunkEngine import DefaultChunkEngine
+ from .HaystackChunkEngine import HaystackChunkEngine
- from .DefaultChunkEngine import DefaultChunkEngine
- from .HaystackChunkEngine import HaystackChunkEngineThe logic for creating chunking engines based on configuration is clear and modular.
Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def create_chunking_engine(config: ChunkingConfig): | |
| if config["chunk_engine"] == "langchainchunkengine": | |
| return LangchainChunkEngine( | |
| chunk_size=config["chunk_size"], | |
| chunk_overlap=config["chunk_overlap"], | |
| chunk_strategy=config["chunk_strategy"], | |
| ) | |
| elif config["chunk_engine"] == "defaultchunkengine": | |
| from .DefaultChunkEngine import DefaultChunkEngine | |
| return DefaultChunkEngine( | |
| chunk_size=config["chunk_size"], | |
| chunk_overlap=config["chunk_overlap"], | |
| chunk_strategy=config["chunk_strategy"], | |
| ) | |
| elif config["chunk_engine"] == "haystackchunkengine": | |
| from .HaystackChunkEngine import HaystackChunkEngine | |
| return HaystackChunkEngine( | |
| chunk_size=config["chunk_size"], | |
| chunk_overlap=config["chunk_overlap"], | |
| chunk_strategy=config["chunk_strategy"], | |
| ) | |
| from .DefaultChunkEngine import DefaultChunkEngine | |
| from .HaystackChunkEngine import HaystackChunkEngine | |
| def create_chunking_engine(config: ChunkingConfig): | |
| if config["chunk_engine"] == "langchainchunkengine": | |
| return LangchainChunkEngine( | |
| chunk_size=config["chunk_size"], | |
| chunk_overlap=config["chunk_overlap"], | |
| chunk_strategy=config["chunk_strategy"], | |
| ) | |
| elif config["chunk_engine"] == "defaultchunkengine": | |
| return DefaultChunkEngine( | |
| chunk_size=config["chunk_size"], | |
| chunk_overlap=config["chunk_overlap"], | |
| chunk_strategy=config["chunk_strategy"], | |
| ) | |
| elif config["chunk_engine"] == "haystackchunkengine": | |
| return HaystackChunkEngine( | |
| chunk_size=config["chunk_size"], | |
| chunk_overlap=config["chunk_overlap"], | |
| chunk_strategy=config["chunk_strategy"], | |
| ) |
There was a problem hiding this comment.
Actionable comments posted: 1
Outside diff range and nitpick comments (1)
cognee/api/v1/cognify/cognify.py (1)
Line range hint
216-216: Avoid using a bareexceptstatement.Using a bare
exceptcan catch unexpected exceptions and obscure bugs. Specify the exception type to improve error handling.- except: + except ExpectedExceptionType:
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Files selected for processing (4)
- cognee/api/v1/cognify/cognify.py (5 hunks)
- cognee/infrastructure/data/chunking/config.py (2 hunks)
- cognee/infrastructure/data/chunking/create_chunking_engine.py (1 hunks)
- cognee/shared/data_models.py (1 hunks)
Files skipped from review due to trivial changes (1)
- cognee/shared/data_models.py
Files skipped from review as they are similar to previous changes (2)
- cognee/infrastructure/data/chunking/config.py
- cognee/infrastructure/data/chunking/create_chunking_engine.py
Additional context used
Ruff
cognee/api/v1/cognify/cognify.py
216-216: Do not use bare
except(E722)
288-288: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
Additional comments not posted (3)
cognee/api/v1/cognify/cognify.py (3)
9-10: Imports fromLangchainChunkingEngineandget_chunk_enginehave been added.These imports align with the PR's objective to enhance chunking engine functionality. Ensure that these modules are properly tested.
12-12: Import fromLiteLLMEmbeddingEnginehas been added.This import supports the integration of new embedding engines, which is consistent with the PR objectives. Verify that
LiteLLMEmbeddingEngineis implemented according to specifications.
30-30: Import ofKnowledgeGraph,ChunkStrategy, andChunkEnginefromcognee.shared.data_models.This import is necessary for the newly introduced chunking and graph functionalities. Ensure that these data models are used appropriately throughout the code.
cognee/modules/topology/topology.py
Outdated
| @@ -1,28 +1,195 @@ | |||
| import os | |||
| import glob | |||
| # import csv | |||
There was a problem hiding this comment.
Let's delete commented code if we don't need it.
| async with aiofiles.open(file_path, mode='r') as f: | ||
| data = await f.read() | ||
| return json.loads(data) | ||
| elif file_path.endswith('.csv'): |
There was a problem hiding this comment.
Does it make sense to have topology in csv format?
There was a problem hiding this comment.
Whyhow does seem to support it, and people tend to use it. Structured data, most of it will be excel
cognee/modules/topology/topology.py
Outdated
| from cognee.base_config import get_base_config | ||
|
|
||
| # Define models | ||
| class RelationshipModel(BaseModel): |
There was a problem hiding this comment.
Why do we have RelationshipModel and Relationship below? Both are pydantic models with similar fields.
There was a problem hiding this comment.
Different models. One is github repo logic, other is base csv, json
There was a problem hiding this comment.
Actionable comments posted: 8
Outside diff range and nitpick comments (2)
cognee/modules/cognify/graph/add_node_connections.py (1)
Line range hint
61-61: Remove the unused variableresult.- result = await graph.query(f"""MATCH (a), (b) WHERE a.unique_id = '{relationship['searched_node_id']}' AND b.unique_id = '{relationship['original_id_for_search']}' - CREATE (a)-[:SEMANTIC_CONNECTION {{weight:{relationship['score']}}}]->(b)""") - await graph.close() + await graph.query(f"""MATCH (a), (b) WHERE a.unique_id = '{relationship['searched_node_id']}' AND b.unique_id = '{relationship['original_id_for_search']}' + CREATE (a)-[:SEMANTIC_CONNECTION {{weight:{relationship['score']}}}]->(b)""") + await graph.close()cognee/api/v1/cognify/cognify.py (1)
Line range hint
218-218: Avoid using a bareexceptstatement. Specify the exception type to improve clarity and maintainability.- except: + except SpecificExceptionType:
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Files selected for processing (13)
- .gitignore (1 hunks)
- cognee/api/client.py (3 hunks)
- cognee/api/v1/cognify/cognify.py (8 hunks)
- cognee/infrastructure/databases/graph/config.py (1 hunks)
- cognee/infrastructure/databases/graph/get_graph_client.py (2 hunks)
- cognee/modules/cognify/graph/add_node_connections.py (1 hunks)
- cognee/modules/data/deletion/prune_system.py (1 hunks)
- cognee/modules/search/vector/search_similarity.py (2 hunks)
- cognee/modules/topology/example_data.json (1 hunks)
- cognee/modules/topology/infer_data_topology.py (1 hunks)
- cognee/modules/topology/topology.py (3 hunks)
- docs/blog/posts/llmops-and-knowledge-graphs.md (1 hunks)
- docs/blog/rag/rag_explained.md (1 hunks)
Files not summarized due to errors (4)
- .gitignore: Error: Server error. Please try again later.
- cognee/modules/topology/topology.py: Error: Server error. Please try again later.
- docs/blog/rag/rag_explained.md: Error: Server error. Please try again later.
- cognee/modules/data/deletion/prune_system.py: Error: Server error. Please try again later.
Files skipped from review due to trivial changes (1)
- cognee/modules/topology/example_data.json
Additional context used
Markdownlint
docs/blog/posts/llmops-and-knowledge-graphs.md
15-15: null (MD018, no-missing-space-atx)
No space after hash on atx style heading
15-15: null (MD047, single-trailing-newline)
Files should end with a single newline characterdocs/blog/rag/rag_explained.md
15-15: null (MD018, no-missing-space-atx)
No space after hash on atx style heading
15-15: null (MD047, single-trailing-newline)
Files should end with a single newline character
Ruff
cognee/modules/data/deletion/prune_system.py
7-7: Local variable
graph_configis assigned to but never used (F841)Remove assignment to unused variable
graph_configcognee/infrastructure/databases/graph/get_graph_client.py
22-22: Do not use bare
except(E722)
35-35: Do not use bare
except(E722)cognee/modules/cognify/graph/add_node_connections.py
61-61: Local variable
resultis assigned to but never used (F841)Remove assignment to unused variable
resultcognee/api/client.py
85-85: Do not use bare
except(E722)cognee/modules/topology/topology.py
281-281: Module level import not at top of file (E402)
cognee/api/v1/cognify/cognify.py
218-218: Do not use bare
except(E722)
290-290: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
Additional comments not posted (5)
docs/blog/posts/llmops-and-knowledge-graphs.md (1)
1-13: Metadata looks well-structured and correctly formatted.docs/blog/rag/rag_explained.md (1)
1-13: Metadata looks well-structured and correctly formatted.cognee/modules/topology/infer_data_topology.py (1)
Line range hint
1-17: The changes in the functioninfer_data_topologyare consistent and improve clarity.cognee/infrastructure/databases/graph/config.py (1)
22-22: The addition ofgraph_topologyaligns with the refactoring efforts to enhance clarity in graph-related configurations..gitignore (1)
13-16: The additions to the.gitignorefile are appropriate for excluding notebooks and evaluation scripts, which aligns with best practices to keep the repository clean.
| """Factory function to get the appropriate graph client based on the graph type.""" | ||
| config = get_graph_config() | ||
|
|
||
| if graph_type == GraphDBType.NEO4J: | ||
| if config.graph_engine == GraphDBType.NEO4J: |
There was a problem hiding this comment.
Avoid using bare except clauses. It's better to handle specific exceptions or at least log the exception to aid in debugging.
- except:
+ except Exception as e:
+ logger.error(f"Failed to initialize Neo4jAdapter: {e}")
- except:
+ except Exception as e:
+ logger.error(f"Failed to initialize FalcorDBAdapter: {e}")Also applies to: 25-25
Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| if config.graph_engine == GraphDBType.NEO4J: | |
| if config.graph_engine == GraphDBType.NEO4J: | |
| try: | |
| return Neo4jAdapter(config) | |
| except Exception as e: | |
| logger.error(f"Failed to initialize Neo4jAdapter: {e}") | |
| elif config.graph_engine == GraphDBType.FALCOR: | |
| try: | |
| return FalcorDBAdapter(config) | |
| except Exception as e: | |
| logger.error(f"Failed to initialize FalcorDBAdapter: {e}") |
| --- | ||
|
|
||
| #tbd |
There was a problem hiding this comment.
Correct Markdown formatting issues.
- #tbd
+ # tbdEnsure the file ends with a single newline character.
Tools
Markdownlint
15-15: null (MD018, no-missing-space-atx)
No space after hash on atx style heading
15-15: null (MD047, single-trailing-newline)
Files should end with a single newline character
| for layer_id in unique_layer_uuids: | ||
| vector_engine = vector_config.vector_engine | ||
| vector_engine = get_vector_engine() |
There was a problem hiding this comment.
As previously suggested, replace debug prints with proper logging mechanisms to maintain production code quality.
- print("results", results)
- print("len_rs", len(results))
+ logger.debug(f"Search results: {results}")
+ logger.debug(f"Results length: {len(results)}")Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| vector_engine = get_vector_engine() | |
| vector_engine = get_vector_engine() | |
| # Assuming the context where these print statements are located | |
| # Replace the following print statements with logger.debug | |
| logger.debug(f"Search results: {results}") | |
| logger.debug(f"Results length: {len(results)}") |
| --- | ||
|
|
||
| #tbd |
There was a problem hiding this comment.
Correct Markdown formatting issues.
- #tbd
+ # tbdEnsure the file ends with a single newline character.
Committable suggestion was skipped due to low confidence.
Tools
Markdownlint
15-15: null (MD018, no-missing-space-atx)
No space after hash on atx style heading
15-15: null (MD047, single-trailing-newline)
Files should end with a single newline character
| status_code = 200, | ||
| content = str(graph_url), | ||
| ) | ||
| except: |
There was a problem hiding this comment.
Specify the exception type to improve error handling.
- except:
+ except SpecificExceptionType:Committable suggestion was skipped due to low confidence.
Tools
Ruff
85-85: Do not use bare
except(E722)
cognee/modules/topology/topology.py
Outdated
| raise RuntimeError(f"Failed to add graph topology from {file_path}: {e}") | ||
|
|
||
| # Example Main Function: | ||
| import asyncio |
There was a problem hiding this comment.
Move the module-level import to the top of the file.
- import asyncio
+ # Move this import to the top of the fileCommittable suggestion was skipped due to low confidence.
Tools
Ruff
281-281: Module level import not at top of file (E402)
| from cognee.infrastructure.databases.graph.config import get_graph_config | ||
| from cognee.infrastructure.databases.vector.config import get_vectordb_config | ||
| from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client | ||
|
|
||
| async def prune_system(graph = True, vector = True): | ||
| if graph: | ||
| graph_config = get_graph_config() |
There was a problem hiding this comment.
Remove the unused variable graph_config.
- graph_config = get_graph_config()Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| graph_config = get_graph_config() |
Tools
Ruff
7-7: Local variable
graph_configis assigned to but never used (F841)Remove assignment to unused variable
graph_config
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Actionable comments posted: 0
Review details
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Files selected for processing (2)
- cognee/modules/topology/topology.py (1 hunks)
- cognee/modules/topology/topology_data_models.py (1 hunks)
Additional comments not posted (11)
cognee/modules/topology/topology_data_models.py (6)
7-11: TheRelationshipclass is well-defined with clear descriptions for each field.
13-17: TheDocumentclass effectively uses theRelationshipclass to ensure type safety and consistency.
19-25: TheDirectoryModelclass is well-structured, using lists with default values to avoid null issues.
29-36: TheDirMetadataclass provides a comprehensive view of a directory's contents, effectively capturing both documents and subdirectories.
38-41: TheGitHubRepositoryModelclass is clearly structured to represent a repository's metadata and root directory effectively.
50-54: TheNodeModelclass is flexible in its representation of children, allowing for both dictionary andNodeModeltypes.cognee/modules/topology/topology.py (5)
22-32: Theflatten_modelmethod is well-documented and effectively uses theNodeModelclass to flatten the model to a dictionary.
34-46: Therecursive_flattenmethod is well-documented and appropriately handles nested structures using a recursive approach.
48-63: Theload_datamethod is robust, with comprehensive error handling and support for multiple file formats.
65-82: Theadd_graph_topologymethod effectively integrates data loading, flattening, and graph client interactions, with robust error handling.
86-93: Themainfunction serves as a simple and effective entry point for the module, demonstrating the use of theTopologyEngine.
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Actionable comments posted: 4
Outside diff range and nitpick comments (3)
cognee/modules/topology/explanations/062c22df-d99b-599f-90cd-2d325c8bcf69.txt (2)
3-3: Consider revising "with respect to input size scaling" to a more concise alternative like "relative to input size" to reduce wordiness.Tools
LanguageTool
[style] ~3-~3: ‘with respect to’ might be wordy. Consider a shorter alternative. (EN_WORDINESS_PREMIUM_WITH_RESPECT_TO)
Context: ...some calculations exponentially faster (with respect to input size scaling) than any modern "cl...
4-4: Consider adding a comma after "quickly" for better readability.Tools
LanguageTool
[uncategorized] ~4-~4: Possible missing comma found. (AI_HYDRA_LEO_MISSING_COMMA)
Context: ...m calculations efficiently and quickly. Physically engineering high-quality qubits has pro...cognee/api/v1/cognify/cognify.py (1)
Line range hint
232-232: Avoid using bareexceptstatements.- except: + except Exception as e:
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Files selected for processing (12)
- cognee/api/v1/cognify/cognify.py (9 hunks)
- cognee/infrastructure/data/chunking/DefaultChunkEngine.py (5 hunks)
- cognee/infrastructure/data/chunking/LangchainChunkingEngine.py (3 hunks)
- cognee/infrastructure/databases/graph/config.py (2 hunks)
- cognee/infrastructure/llm/prompts/extract_topology.txt (1 hunks)
- cognee/modules/topology/example_data.json (1 hunks)
- cognee/modules/topology/explanations/062c22df-d99b-599f-90cd-2d325c8bcf69.txt (1 hunks)
- cognee/modules/topology/explanations/6dfe01b6-07d2-5b77-83c8-1d6c11ce2aa7.txt (1 hunks)
- cognee/modules/topology/explanations/Natural language processing.txt (1 hunks)
- cognee/modules/topology/explanations/bab90046-1d9b-598c-8711-dab30f501915.txt (1 hunks)
- cognee/modules/topology/infer_data_topology.py (1 hunks)
- cognee/modules/topology/topology.py (1 hunks)
Files skipped from review due to trivial changes (4)
- cognee/infrastructure/llm/prompts/extract_topology.txt
- cognee/modules/topology/example_data.json
- cognee/modules/topology/explanations/Natural language processing.txt
- cognee/modules/topology/explanations/bab90046-1d9b-598c-8711-dab30f501915.txt
Files skipped from review as they are similar to previous changes (1)
- cognee/infrastructure/data/chunking/DefaultChunkEngine.py
Additional context used
LanguageTool
cognee/modules/topology/explanations/062c22df-d99b-599f-90cd-2d325c8bcf69.txt
[style] ~3-~3: ‘with respect to’ might be wordy. Consider a shorter alternative. (EN_WORDINESS_PREMIUM_WITH_RESPECT_TO)
Context: ...some calculations exponentially faster (with respect to input size scaling) than any modern "cl...
[uncategorized] ~4-~4: Possible missing comma found. (AI_HYDRA_LEO_MISSING_COMMA)
Context: ...m calculations efficiently and quickly. Physically engineering high-quality qubits has pro...cognee/modules/topology/explanations/6dfe01b6-07d2-5b77-83c8-1d6c11ce2aa7.txt
[typographical] ~4-~4: Nepárový symbol: zdá sa, že chýba '“' (UNPAIRED_BRACKETS)
Context: ...unikacije među nižim i višim majmunima: „U velikoj većini, celokupni sistem komun...
Ruff
cognee/modules/topology/topology.py
190-190: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graphcognee/api/v1/cognify/cognify.py
150-150: Local variable
graph_topologyis assigned to but never used (F841)Remove assignment to unused variable
graph_topology
232-232: Do not use bare
except(E722)
304-304: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
Additional comments not posted (6)
cognee/modules/topology/infer_data_topology.py (2)
10-10: Ensure thatgraph_topologyis correctly initialized fromgraph_config.graph_topologyas intended.
19-19: The updated error message is more specific, which improves clarity and debugging. Good job on this change.cognee/infrastructure/databases/graph/config.py (2)
41-41: Includinginfer_graph_topologyin the dictionary returned byto_dictensures that this setting can be serialized and used in configurations. This is a good practice for maintaining configuration consistency.
22-27: Adding properties related to graph topology enhances the configurability of the graph database. Ensure that these new properties are utilized appropriately in the rest of the codebase.Verification successful
The new properties related to graph topology are indeed utilized in various parts of the codebase, confirming their integration and relevance.
graph_topology_task,graph_topology,infer_graph_topology, andtopology_file_pathare used incognee/modules/topology/topology.py,cognee/modules/topology/infer_data_topology.py,cognee/infrastructure/databases/graph/config.py, andcognee/api/v1/cognify/cognify.py.This confirms that the new properties are appropriately utilized in the codebase.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the usage of new graph topology properties in the codebase. # Test: Search for the usage of new properties. Expect: Proper usage in relevant modules. rg --type python $'graph_topology_task|graph_topology|infer_graph_topology|topology_file_path'Length of output: 126
Script:
#!/bin/bash # Description: Verify the usage of new graph topology properties in the codebase. # Test: Search for the usage of new properties. Expect: Proper usage in relevant modules. rg --type py $'graph_topology_task|graph_topology|infer_graph_topology|topology_file_path'Length of output: 2343
cognee/infrastructure/data/chunking/LangchainChunkingEngine.py (1)
9-18: The introduction ofLangchainChunkEnginewith customizable chunking strategies is a significant enhancement. Ensure that the parameters provided in the constructor are used consistently throughout the class methods.cognee/modules/topology/topology.py (1)
22-22: Move the module-level importasyncioto the top of the file.- import asyncio + # Move this import to the top of the fileLikely invalid or redundant comment.
| U analizi komunikacionih sistema kod životinja zadržaćemo se samo na semiotičkim problemima – postoje li u pojedinim sistemima njihove komunikacije ZNACI, semiotički SISTEMI i neke semiotičke OPERACIJE, u onom smislu kako su ti pojmovi definisani i utvrđeni kod ljudi. Analiziraćemo sličnosti i razlike između komunikacije kod životinja i kod ljudi, posebno semiotičke komunikacije kod čoveka. | ||
| Kada se ima u vidu bogatstvo oblika komunikativnih veza među životinjama: sva raznolikost signala u pogledu fizičkih svojstava – hemijski, oflaktivni (mirisni), akustički (uključiv i ultrazvukove), električni, motorički (kinezički), proksemički (položaj u prostoru), vizuelni i drugi, zatim – raznovrsnost kanala (sredina) kroz koje se ostvaruje veza, kao i raznovrsnost funkcija koje imaju komunikativni sistemi, pitanje je koliko je uopšte opravdano govoriti o komunikaciji životinja u celini. | ||
| Međutim, kada se pristupi semiotičkoj analizi sistema komunikacije među životinjama, iza raznolikosti nalazi se prilična jednoličnost, čak tolika da se ne može utvrditi postoji li nekakvo usavršavanje sistema komunikacije duž evolucione lestvice. | ||
| Pogledajmo najpre kakve FUNKCIJE opslužuju sistemi komunikacija kod životinja. Poznati istraživač ovih problema, Marler, ovako rezimira analizu komunikacije među nižim i višim majmunima: „U velikoj većini, celokupni sistem komunikacije izgleda postoji radi organizacije socijalnog ponašanja grupe, regulacije dominantnosti i subordinacije, održanja mira i kohezije u grupi, kao i radi reprodukcije i brige o mladima (Marleu, 1967). Pomenute funkcije mogle bi se, nešto raščlanjenije, ovako opisati: |
There was a problem hiding this comment.
Fix the unpaired bracket issue.
- „U velikoj većini, celokupni sistem komunikacije izgleda postoji radi organizacije socijalnog ponašanja grupe, regulacije dominantnosti i subordinacije, održanja mira i kohezije u grupi, kao i radi reprodukcije i brige o mladima (Marleu, 1967).
+ „U velikoj većini, celokupni sistem komunikacije izgleda postoji radi organizacije socijalnog ponašanja grupe, regulacije dominantnosti i subordinacije, održanja mira i kohezije u grupi, kao i radi reprodukcije i brige o mladima“ (Marleu, 1967).Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| Pogledajmo najpre kakve FUNKCIJE opslužuju sistemi komunikacija kod životinja. Poznati istraživač ovih problema, Marler, ovako rezimira analizu komunikacije među nižim i višim majmunima: „U velikoj većini, celokupni sistem komunikacije izgleda postoji radi organizacije socijalnog ponašanja grupe, regulacije dominantnosti i subordinacije, održanja mira i kohezije u grupi, kao i radi reprodukcije i brige o mladima (Marleu, 1967). Pomenute funkcije mogle bi se, nešto raščlanjenije, ovako opisati: | |
| Pogledajmo najpre kakve FUNKCIJE opslužuju sistemi komunikacija kod životinja. Poznati istraživač ovih problema, Marler, ovako rezimira analizu komunikacije među nižim i višim majmunima: „U velikoj većini, celokupni sistem komunikacije izgleda postoji radi organizacije socijalnog ponašanja grupe, regulacije dominantnosti i subordinacije, održanja mira i kohezije u grupi, kao i radi reprodukcije i brige o mladima“ (Marleu, 1967). Pomenute funkcije mogle bi se, nešto raščlanjenije, ovako opisati: |
Tools
LanguageTool
[typographical] ~4-~4: Nepárový symbol: zdá sa, že chýba '“' (UNPAIRED_BRACKETS)
Context: ...unikacije među nižim i višim majmunima: „U velikoj većini, celokupni sistem komun...
| file_path = 'example_data.json' # or 'example_data.csv' | ||
| # | ||
| # # Adding graph topology | ||
| graph = await topology_engine.add_graph_topology(file_path, dataset_files=dataset_files) |
There was a problem hiding this comment.
Remove assignment to unused variable graph.
- graph = await topology_engine.add_graph_topology(file_path, dataset_files=dataset_files)
+ await topology_engine.add_graph_topology(file_path, dataset_files=dataset_files)Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| graph = await topology_engine.add_graph_topology(file_path, dataset_files=dataset_files) | |
| await topology_engine.add_graph_topology(file_path, dataset_files=dataset_files) |
Tools
Ruff
190-190: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
| chunked_data, chunk_number = self.chunk_data_by_code(source_data,self.chunk_size, self.chunk_overlap) | ||
|
|
||
| elif chunk_strategy == ChunkStrategy.LANGCHAIN_CHARACTER: | ||
| chunked_data = LangchainChunkEngine.chunk_data_by_character(source_data,chunk_size, chunk_overlap) | ||
| chunked_data, chunk_number = self.chunk_data_by_character(source_data,self.chunk_size, self.chunk_overlap) | ||
| else: | ||
| chunked_data = DefaultChunkEngine.chunk_data_by_paragraph(source_data,chunk_size, chunk_overlap) | ||
| return chunked_data | ||
| chunked_data, chunk_number = "Invalid chunk strategy.", [0, "Invalid chunk strategy."] | ||
| return chunked_data, chunk_number |
There was a problem hiding this comment.
The implementation of different chunking strategies based on the chunk_strategy parameter is well-handled. However, consider handling the case where an invalid strategy is passed more gracefully, perhaps by raising a specific exception rather than returning a string error.
- chunked_data, chunk_number = "Invalid chunk strategy.", [0, "Invalid chunk strategy."]
+ raise ValueError("Invalid chunk strategy provided.")Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| chunked_data, chunk_number = self.chunk_data_by_code(source_data,self.chunk_size, self.chunk_overlap) | |
| elif chunk_strategy == ChunkStrategy.LANGCHAIN_CHARACTER: | |
| chunked_data = LangchainChunkEngine.chunk_data_by_character(source_data,chunk_size, chunk_overlap) | |
| chunked_data, chunk_number = self.chunk_data_by_character(source_data,self.chunk_size, self.chunk_overlap) | |
| else: | |
| chunked_data = DefaultChunkEngine.chunk_data_by_paragraph(source_data,chunk_size, chunk_overlap) | |
| return chunked_data | |
| chunked_data, chunk_number = "Invalid chunk strategy.", [0, "Invalid chunk strategy."] | |
| return chunked_data, chunk_number | |
| chunked_data, chunk_number = self.chunk_data_by_code(source_data,self.chunk_size, self.chunk_overlap) | |
| elif chunk_strategy == ChunkStrategy.LANGCHAIN_CHARACTER: | |
| chunked_data, chunk_number = self.chunk_data_by_character(source_data,self.chunk_size, self.chunk_overlap) | |
| else: | |
| raise ValueError("Invalid chunk strategy provided.") | |
| return chunked_data, chunk_number |
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Actionable comments posted: 0
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Files selected for processing (1)
- cognee/infrastructure/databases/graph/config.py (2 hunks)
Files skipped from review as they are similar to previous changes (1)
- cognee/infrastructure/databases/graph/config.py
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Actionable comments posted: 3
Outside diff range and nitpick comments (1)
cognee/api/v1/cognify/cognify.py (1)
Line range hint
232-232: Avoid using bareexceptstatements as they can catch unexpected exceptions and hide programming errors.- except: + except Exception as e: + logger.error(f"An error occurred: {str(e)}")
Review details
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Review profile: CHILL
Files selected for processing (3)
- README.md (1 hunks)
- cognee/api/v1/cognify/cognify.py (10 hunks)
- cognee/api/v1/config/config.py (2 hunks)
Files skipped from review as they are similar to previous changes (1)
- cognee/api/v1/config/config.py
Additional context used
LanguageTool
README.md
[locale-violation] ~35-~35: In American English, “take a look” is more commonly used. (HAVE_A_LOOK)
Context: ...-iB9gpYfu?usp=sharing">notebook or have a look at our <a href="https://topoteretes.git...
[style] ~128-~128: The phrase “a variety of” may be wordy. To make your writing clearer, consider replacing it. (A_VARIETY_OF)
Context: ...ieval, Graphs and LLMs Cognee supports a variety of tools and services for different operat...
Markdownlint
README.md
72-72: Expected: 0 or 2; Actual: 1 (MD009, no-trailing-spaces)
Trailing spaces
5-5: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
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Images should have alternate text (alt text)
Ruff
cognee/api/v1/cognify/cognify.py
150-150: Local variable
graph_topologyis assigned to but never used (F841)Remove assignment to unused variable
graph_topology
232-232: Do not use bare
except(E722)
304-304: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
Additional comments not posted (1)
cognee/api/v1/cognify/cognify.py (1)
9-12: Ensure that the newly added imports are utilized effectively in the code.
| search_results = cognee.search("SIMILARITY", {'query': 'Tell me about NLP'}) # Query cognee for the knowledge | ||
|
|
||
| for result_text in search_results[0]: | ||
| print(result_text) | ||
| print(search_results) |
There was a problem hiding this comment.
Consider adding error handling for the search method to ensure robustness.
- search_results = cognee.search("SIMILARITY", {'query': 'Tell me about NLP'}) # Query cognee for the knowledge
+ try:
+ search_results = cognee.search("SIMILARITY", {'query': 'Tell me about NLP'}) # Query cognee for the knowledge
+ except Exception as e:
+ print(f"Error during search: {str(e)}")
+ search_results = NoneCommittable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| search_results = cognee.search("SIMILARITY", {'query': 'Tell me about NLP'}) # Query cognee for the knowledge | |
| for result_text in search_results[0]: | |
| print(result_text) | |
| print(search_results) | |
| try: | |
| search_results = cognee.search("SIMILARITY", {'query': 'Tell me about NLP'}) # Query cognee for the knowledge | |
| except Exception as e: | |
| print(f"Error during search: {str(e)}") | |
| search_results = None | |
| print(search_results) |
| @@ -136,21 +145,37 @@ async def process_batch(files_batch): | |||
| batch_size = 20 | |||
| file_count = 0 | |||
| files_batch = [] | |||
| from cognee.infrastructure.databases.graph.config import get_graph_config | |||
| graph_config = get_graph_config() | |||
| graph_topology = graph_config.graph_model | |||
There was a problem hiding this comment.
The variable graph_topology is declared but not used, which could lead to unnecessary memory usage.
- graph_topology = graph_config.graph_modelCommittable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| graph_topology = graph_config.graph_model |
Tools
Ruff
150-150: Local variable
graph_topologyis assigned to but never used (F841)Remove assignment to unused variable
graph_topology
| config.set_chunk_strategy(ChunkStrategy.LANGCHAIN_CHARACTER) | ||
| config.embedding_engine = LiteLLMEmbeddingEngine() | ||
|
|
||
| graph = await cognify() |
There was a problem hiding this comment.
The variable graph is assigned but never used. Consider removing it if it's not needed.
- graph = await cognify()Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| graph = await cognify() | |
| await cognify() |
Tools
Ruff
304-304: Local variable
graphis assigned to but never used (F841)Remove assignment to unused variable
graph
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- .github/workflows/test_common.yml (1 hunks)
- cognee/tests/test_qdrant.py (1 hunks)
Additional context used
Ruff
cognee/tests/test_qdrant.py
36-36: Local variable
text_1is assigned to but never used (F841)Remove assignment to unused variable
text_1
44-44: Local variable
text_2is assigned to but never used (F841)Remove assignment to unused variable
text_2
Additional comments not posted (5)
.github/workflows/test_common.yml (2)
86-86: The step to run the default basic pipeline is well-configured.
93-100: The configuration for running the Qdrant test is consistent and well-defined.cognee/tests/test_qdrant.py (3)
22-22: Setting the vector engine provider to "qdrant" aligns with the PR objectives.
29-30: The method for adding data to the cognee module is correctly implemented.
52-66: The implementation of various search operations is correct and consistent.
…b' into fix/setting-alternative-vector-db
…b' into fix/setting-alternative-vector-db
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Actionable comments posted: 11
Outside diff range and nitpick comments (7)
cognee/modules/search/graph/search_neighbour.py (1)
Line range hint
28-39: The function implementation for both NetworkX and Neo4j is correct. However, consider handling exceptions explicitly to improve robustness.try: # existing code except Exception as e: logging.error(f"Failed to search neighbours: {str(e)}") raisecognee/modules/search/graph/search_summary.py (1)
Line range hint
46-51: Remove the unnecessaryfprefix from the string as it does not contain any placeholders.- cypher_query = f""" + cypher_query = """ MATCH (n) WHERE n.id CONTAINS $query AND EXISTS(n.summary) RETURN n.id AS nodeId, n.summary AS summary """cognee/modules/cognify/graph/add_node_connections.py (2)
Line range hint
44-57: Refactored to support multiple graph database providers ("NETWORKX" and "neo4j"). Ensure that the placeholder for Neo4j is replaced with actual implementation logic before merging.
Line range hint
61-61: The local variableresultis assigned but never used. Consider removing or utilizing it to avoid potential confusion and improve code clarity.- result = await graph.query(f"""MATCH (a), (b) WHERE a.unique_id = '{relationship['searched_node_id']}' AND b.unique_id = '{relationship['original_id_for_search']}' - CREATE (a)-[:SEMANTIC_CONNECTION {{weight:{relationship['score']}}}]->(b)""") - await graph.close()cognee/modules/cognify/graph/create.py (3)
Line range hint
158-158: Remove unused variablecreated_node_id.- created_node_id = await add_node(graph_client, parent_id, node_id, node_data) + _ = await add_node(graph_client, parent_id, node_id, node_data)
Line range hint
218-218: Remove unused variablerelationship_data.- relationship_data = {}
Line range hint
253-253: Remove unused variableids.- ids = await process_attribute(graph_client, root_id, attribute_name, attribute_value)
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Files ignored due to path filters (1)
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Files selected for processing (24)
- .github/workflows/test_common.yml (2 hunks)
- .github/workflows/test_neo4j.yml (1 hunks)
- .github/workflows/test_qdrant.yml (1 hunks)
- .github/workflows/test_weaviate.yml (1 hunks)
- cognee/api/v1/add/add.py (1 hunks)
- cognee/api/v1/config/config.py (3 hunks)
- cognee/api/v1/search/search.py (1 hunks)
- cognee/infrastructure/databases/graph/config.py (2 hunks)
- cognee/infrastructure/databases/graph/get_graph_client.py (2 hunks)
- cognee/infrastructure/databases/vector/create_vector_engine.py (1 hunks)
- cognee/modules/cognify/graph/add_node_connections.py (3 hunks)
- cognee/modules/cognify/graph/create.py (1 hunks)
- cognee/modules/data/extraction/extract_categories.py (1 hunks)
- cognee/modules/search/graph/search_adjacent.py (1 hunks)
- cognee/modules/search/graph/search_categories.py (2 hunks)
- cognee/modules/search/graph/search_cypher.py (1 hunks)
- cognee/modules/search/graph/search_neighbour.py (2 hunks)
- cognee/modules/search/graph/search_summary.py (2 hunks)
- cognee/modules/search/vector/search_similarity.py (2 hunks)
- cognee/tests/test_neo4j.py (1 hunks)
- cognee/tests/test_qdrant.py (1 hunks)
- cognee/tests/test_weaviate.py (1 hunks)
- docs/api_reference.md (1 hunks)
- tests/import_test.py (1 hunks)
Files skipped from review due to trivial changes (3)
- cognee/api/v1/add/add.py
- cognee/modules/data/extraction/extract_categories.py
- tests/import_test.py
Files skipped from review as they are similar to previous changes (4)
- cognee/api/v1/config/config.py
- cognee/infrastructure/databases/graph/config.py
- cognee/infrastructure/databases/vector/create_vector_engine.py
- cognee/modules/search/vector/search_similarity.py
Additional context used
Ruff
cognee/infrastructure/databases/graph/get_graph_client.py
22-22: Do not use bare
except(E722)
35-35: Do not use bare
except(E722)cognee/modules/search/graph/search_summary.py
47-51: f-string without any placeholders (F541)
Remove extraneous
fprefixcognee/modules/cognify/graph/add_node_connections.py
61-61: Local variable
resultis assigned to but never used (F841)Remove assignment to unused variable
resultcognee/tests/test_qdrant.py
36-36: Local variable
text_1is assigned to but never used (F841)Remove assignment to unused variable
text_1
44-44: Local variable
text_2is assigned to but never used (F841)Remove assignment to unused variable
text_2cognee/tests/test_neo4j.py
36-36: Local variable
text_1is assigned to but never used (F841)Remove assignment to unused variable
text_1
44-44: Local variable
text_2is assigned to but never used (F841)Remove assignment to unused variable
text_2cognee/modules/cognify/graph/create.py
158-158: Local variable
created_node_idis assigned to but never used (F841)Remove assignment to unused variable
created_node_id
218-218: Local variable
relationship_datais assigned to but never used (F841)Remove assignment to unused variable
relationship_data
253-253: Local variable
idsis assigned to but never used (F841)Remove assignment to unused variable
ids
LanguageTool
docs/api_reference.md
[uncategorized] ~27-~27: Possible missing comma found. (AI_HYDRA_LEO_MISSING_COMMA)
Context: ...ry: str) Sets the root directory of the system where essential system files and operat...
Markdownlint
docs/api_reference.md
9-9: Expected: 0 or 2; Actual: 1 (MD009, no-trailing-spaces)
Trailing spaces
16-16: Expected: 0 or 2; Actual: 1 (MD009, no-trailing-spaces)
Trailing spaces
77-77: Expected: 0 or 2; Actual: 1 (MD009, no-trailing-spaces)
Trailing spaces
5-5: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
11-11: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
22-22: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
25-25: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
87-87: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
88-88: Expected: 1; Actual: 3 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
91-91: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
92-92: Expected: 1; Actual: 3 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
95-95: Expected: 1; Actual: 2 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
96-96: Expected: 1; Actual: 3 (MD012, no-multiple-blanks)
Multiple consecutive blank lines
19-19: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
26-26: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
34-34: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
45-45: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
67-67: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
76-76: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
97-97: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
103-103: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
110-110: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
115-115: Expected: 1; Actual: 0; Above (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
115-115: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank lines
14-14: null (MD025, single-title, single-h1)
Multiple top-level headings in the same document
30-30: null (MD031, blanks-around-fences)
Fenced code blocks should be surrounded by blank lines
40-40: null (MD031, blanks-around-fences)
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51-51: null (MD031, blanks-around-fences)
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62-62: null (MD031, blanks-around-fences)
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71-71: null (MD031, blanks-around-fences)
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81-81: null (MD031, blanks-around-fences)
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104-104: null (MD031, blanks-around-fences)
Fenced code blocks should be surrounded by blank lines
116-116: null (MD031, blanks-around-fences)
Fenced code blocks should be surrounded by blank lines
98-98: null (MD032, blanks-around-lists)
Lists should be surrounded by blank lines
111-111: null (MD032, blanks-around-lists)
Lists should be surrounded by blank lines
114-114: null (MD032, blanks-around-lists)
Lists should be surrounded by blank lines
Additional comments not posted (7)
.github/workflows/test_qdrant.yml (1)
1-62: The workflow is well-structured and follows best practices for CI/CD pipelines..github/workflows/test_weaviate.yml (1)
1-62: The workflow is well-structured and follows best practices for CI/CD pipelines.cognee/modules/search/graph/search_summary.py (1)
Line range hint
29-46: The logic for handling different graph database providers looks good and is well-structured.Also applies to: 53-53
cognee/modules/search/graph/search_categories.py (1)
Line range hint
37-53: The logic for handling different graph database providers insearch_categoriesis well-implemented and clear.docs/api_reference.md (1)
76-79: The documentation update to reflect the new function namegraph_database_provideris accurate and clear.Tools
Markdownlint
77-77: Expected: 0 or 2; Actual: 1 (MD009, no-trailing-spaces)
Trailing spaces
76-76: Expected: 1; Actual: 0; Below (MD022, blanks-around-headings)
Headings should be surrounded by blank linescognee/api/v1/search/search.py (1)
53-53: The update to use the new graph database provider configuration in thesearchfunction is correctly implemented..github/workflows/test_common.yml (1)
1-1: Renamed workflow to "test | environments" to reflect the broader scope of testing environments.
| @@ -45,7 +45,7 @@ async def add_node(client, parent_id: Optional[str], node_id: str, node_data: di | |||
| graph_config = get_graph_config() | |||
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| # Add an edge if a parent ID is provided and the graph engine is NETWORKX | |||
| if parent_id and "default_relationship" in node_data and graph_config.graph_engine == GraphDBType.NETWORKX: | |||
| if parent_id and "default_relationship" in node_data and graph_config.graph_database_provider == "NETWORKX": | |||
There was a problem hiding this comment.
Consider handling exceptions more robustly in edge addition.
The current implementation prints the error and passes. This might not be sufficient for production environments where error tracking and handling are critical. Consider using a logging framework or rethrowing the exception after logging.
Refactor to use a logging framework.
Instead of using print statements for error logging, consider integrating a logging framework that supports different log levels and is more suitable for production environments.
- print(f"Error adding edge: {e}")
+ import logging
+ logger = logging.getLogger(__name__)
+ logger.error(f"Error adding edge: {e}")Committable suggestion was skipped due to low confidence.
Tip
Codebase Verification
Ensure consistent error handling by replacing print statements with a logging framework and considering the use of exception handling where appropriate.
cognee/modules/cognify/graph/create.py: Lines containingprint(f"Error adding edge: {e}")andprint(f"Error adding node or edge: {e}").
Analysis chain
Ensure consistency in error handling.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify consistent error handling across the module.
# Test: Search for print statements used for error logging. Expect: No occurrences after refactoring.
rg --type py 'print\(f"Error' cognee/modules/cognify/graph/
Length of output: 245
Script:
#!/bin/bash
# Description: Verify consistent error handling across the module.
# Test: Search for logging statements used for error handling.
rg --type py 'logging\.error' cognee/modules/cognify/graph/
# Test: Search for exception handling.
rg --type py 'raise ' cognee/modules/cognify/graph/
Length of output: 307
| name: test neo4j | ||
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| on: | ||
| pull_request: | ||
| branches: | ||
| - main | ||
| workflow_dispatch: | ||
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| concurrency: | ||
| group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }} | ||
| cancel-in-progress: true | ||
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| env: | ||
| RUNTIME__LOG_LEVEL: ERROR | ||
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| jobs: | ||
| get_docs_changes: | ||
| name: docs changes | ||
| uses: ./.github/workflows/get_docs_changes.yml | ||
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| run_common: | ||
| name: test | ||
| needs: get_docs_changes | ||
| if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' | ||
| runs-on: macos-latest | ||
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| defaults: | ||
| run: | ||
| shell: bash | ||
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| steps: | ||
| - name: Check out | ||
| uses: actions/checkout@v2 | ||
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| - name: Setup Python | ||
| uses: actions/setup-python@v4 | ||
| with: | ||
| python-version: 3.11 | ||
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| - name: Install Poetry | ||
| uses: snok/install-poetry@v1.3.2 | ||
| with: | ||
| virtualenvs-create: true | ||
| virtualenvs-in-project: true | ||
| installer-parallel: true | ||
|
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| - name: Install dependencies | ||
| run: poetry install --no-interaction | ||
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| - name: Create .cognee_system directory and print path | ||
| run: | | ||
| mkdir .cognee_system | ||
| echo $(pwd)/.cognee_system | ||
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| - name: Run default Neo4j | ||
| env: | ||
| OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} | ||
| LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} | ||
| GRAPH_DATABASE_URL: ${{ secrets.NEO4J_API_URL }} | ||
| GRAPH_DATABASE_PASSWORD: ${{ secrets.NEO4J_API_KEY }} | ||
| GRAPH_DATABASE_USERNAME: "neo4j" | ||
| ENV: 'dev' | ||
| run: poetry run python ./cognee/tests/test_neo4j.py |
There was a problem hiding this comment.
The workflow configuration for Neo4j testing appears comprehensive and well-structured. However, consider adding a step to cache dependencies to speed up the build process.
- name: Cache Poetry virtual environment
uses: actions/cache@v2
with:
path: ~/.cache/pypoetry/virtualenvs
key: ${{ runner.os }}-poetry-${{ hashFiles('**/poetry.lock') }}
restore-keys: |
${{ runner.os }}-poetry-| import asyncio | ||
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| async def test_weaviate_integration(): | ||
| from cognee import config, prune, add, cognify, search | ||
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| config.set_vector_engine_provider("weaviate") | ||
| # config.set_vector_db_url("TEST_URL") | ||
| # config.set_vector_db_key("TEST_KEY") | ||
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| prune.prune_system() | ||
|
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| text = """ | ||
| Incapillo is a Pleistocene-age caldera (a depression formed by the collapse of a volcano) in the La Rioja Province of Argentina. It is the southernmost volcanic centre in the Andean Central Volcanic Zone (CVZ) that erupted during the Pleistocene. Incapillo is one of several ignimbrite[a] or caldera systems that, along with 44 active stratovolcanoes, are part of the CVZ. | ||
| Subduction of the Nazca Plate beneath the South American Plate is responsible for most of the volcanism in the CVZ. After activity in the volcanic arc of the western Maricunga Belt ceased six million years ago, volcanism commenced in the Incapillo region, forming the high volcanic edifices Monte Pissis, Cerro Bonete Chico and Sierra de Veladero. Later, a number of lava domes were emplaced between these volcanoes. | ||
| Incapillo is the source of the Incapillo ignimbrite, a medium-sized deposit comparable to the Katmai ignimbrite. The Incapillo ignimbrite was erupted 0.52 ± 0.03 and 0.51 ± 0.04 million years ago and has a volume of about 20.4 cubic kilometres (4.9 cu mi). A caldera with dimensions of 5 by 6 kilometres (3.1 mi × 3.7 mi) formed during the eruption. Later volcanism generated more lava domes within the caldera and a debris flow in the Sierra de Veladero. The lake within the caldera may overlie an area of ongoing hydrothermal activity. | ||
| """ | ||
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| await add(text) | ||
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| await cognify() | ||
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| result = await search("SIMILARITY", { "query": "volcanic eruption" }) | ||
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| print(result) | ||
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| if __name__ == "__main__": | ||
| asyncio.run(test_weaviate_integration()) |
There was a problem hiding this comment.
The test function for Weaviate integration is well-implemented. However, consider adding more detailed assertions to verify the correctness of each operation rather than just running them.
assert result is not None, "Search results should not be None"
assert isinstance(result, list), "Search results should be a list"| if graph_config.graph_database_provider == "NETWORKX": | ||
| if node_id not in graph: | ||
| return {} | ||
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| neighbors = list(graph.neighbors(node_id)) | ||
| neighbor_descriptions = {neighbor: graph.nodes[neighbor].get('description') for neighbor in neighbors} | ||
| return neighbor_descriptions | ||
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| elif graph_config.graph_engine == GraphDBType.NEO4J: | ||
| elif graph_config.graph_database_provider == "neo4j": |
There was a problem hiding this comment.
The conditional handling for different graph database providers is implemented correctly. However, consider adding logging for better traceability and debugging.
import logging
logging.info(f"Using graph database provider: {graph_config.graph_database_provider}")| # python -m nltk.downloader averaged_perceptron_tagger | ||
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| - name: Run test script | ||
| - name: Run default basic pipeline |
There was a problem hiding this comment.
Added a new step "Run default basic pipeline" with specific environment variables. Ensure that the OPENAI_API_KEY and LLM_API_KEY are securely managed and not exposed.
| # # data_directory_path is defined above | ||
| # await cognee.add("data://" + "/Users/runner/work/cognee/cognee/./cognee/tests", dataset_name) | ||
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| text_1 = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena. |
There was a problem hiding this comment.
Remove unused variables text_1 and text_2 to clean up the code.
- text_1 = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena.
- ...
- """
- text_2 = """A large language model (LLM) is a language model notable for its ability to achieve general-purpose language generation and other natural language processing tasks such as classification. LLMs acquire these abilities by learning statistical relationships from text documents during a computationally intensive self-supervised and semi-supervised training process. LLMs can be used for text generation, a form of generative AI, by taking an input text and repeatedly predicting the next token or word.
- ...
- """Also applies to: 44-44
Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| text_1 = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena. |
Tools
Ruff
36-36: Local variable
text_1is assigned to but never used (F841)Remove assignment to unused variable
text_1
| @@ -10,7 +10,7 @@ async def search_cypher(query:str, graph: Union[nx.Graph, any]): | |||
| """ | |||
| graph_config = get_graph_config() | |||
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| if graph_config.graph_engine == GraphDBType.NEO4J: | |||
| if graph_config.graph_database_provider == "neo4j": | |||
There was a problem hiding this comment.
Tip
Codebase Verification
The search_cypher function currently only handles the "neo4j" graph database provider and raises a ValueError for any other provider. This means that other supported providers like "NETWORKX" and "falkorb" are not handled in this function.
cognee/modules/search/graph/search_cypher.py:13: Handles "neo4j".cognee/modules/search/graph/search_cypher.py:17: RaisesValueErrorfor unsupported providers.
To ensure comprehensive support for all graph database providers, additional handling for "NETWORKX" and "falkorb" should be implemented in the search_cypher function.
Analysis chain
Ensure that all supported graph database providers are handled appropriately.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify that all supported graph database providers are handled in the function.
# Test: Search for the function usage. Expect: Handling for all supported providers.
rg --type python $'graph_database_provider'
Length of output: 73
Script:
#!/bin/bash
# Description: Verify that all supported graph database providers are handled in the function.
# Test: Search for the function usage. Expect: Handling for all supported providers.
rg --type py 'graph_database_provider'
Length of output: 2220
Script:
#!/bin/bash
# Description: Extract the full implementation of the `search_cypher` function to verify the handling of all graph database providers.
# Test: Extract the `search_cypher` function implementation.
ast-grep --lang python --pattern $'def search_cypher($_, $_):\n $$$' cognee/modules/search/graph/search_cypher.py
Length of output: 1064
| # # data_directory_path is defined above | ||
| # await cognee.add("data://" + "/Users/runner/work/cognee/cognee/./cognee/tests", dataset_name) | ||
|
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||
| text_1 = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena. |
There was a problem hiding this comment.
Remove unused variables text_1 and text_2 to clean up the code.
- text_1 = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena.
- ...
- """
- text_2 = """A large language model (LLM) is a language model notable for its ability to achieve general-purpose language generation and other natural language processing tasks such as classification. LLMs acquire these abilities by learning statistical relationships from text documents during a computationally intensive self-supervised and semi-supervised training process. LLMs can be used for text generation, a form of generative AI, by taking an input text and repeatedly predicting the next token or word.
- ...
- """Also applies to: 44-44
Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| text_1 = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena. |
Tools
Ruff
36-36: Local variable
text_1is assigned to but never used (F841)Remove assignment to unused variable
text_1
| @@ -22,7 +22,7 @@ async def get_graph_client(graph_type: GraphDBType, graph_file_name: str = None) | |||
| except: | |||
There was a problem hiding this comment.
Replace bare except clauses with specific exceptions or at least log the exception.
- except:
+ except Exception as e:
+ logger.error(f"Failed to initialize Neo4jAdapter: {e}")
- except:
+ except Exception as e:
+ logger.error(f"Failed to initialize FalcorDBAdapter: {e}")Also applies to: 35-35
Committable suggestion was skipped due to low confidence.
Tools
Ruff
22-22: Do not use bare
except(E722)
…b' into fix/setting-alternative-vector-db
Summary by CodeRabbit
New Features
Bug Fixes
Style
Documentation
quickstart.mdwith new visualization instructions and search query parameters.Chores
pyproject.toml.