fix: remove groups from UserRead model #157
Conversation
WalkthroughThe changes involve modifications to the Changes
Possibly related PRs
Poem
Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media? 🪧 TipsChatThere are 3 ways to chat with CodeRabbit:
Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments. CodeRabbit Commands (Invoked using PR comments)
Other keywords and placeholders
CodeRabbit Configuration File (
|
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
cognee/modules/users/models/User.py (1)
Line range hint
15-19: Consider documenting the discrepancy between User model and UserRead schemaWhile the
groupsattribute has been removed from the UserRead schema, theUsermodel still maintains agroupsrelationship. This discrepancy might lead to confusion for developers working with the codebase.Consider adding a comment in the
Usermodel explaining why thegroupsrelationship exists in the model but is not included in the UserRead schema. This will help clarify the intentional difference between the model and its read representation.🧰 Tools
🪛 Ruff
25-25: Module level import not at top of file
(E402)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
- cognee/modules/users/models/User.py (1 hunks)
🧰 Additional context used
🔇 Additional comments (1)
cognee/modules/users/models/User.py (1)
28-29: Approved: Groups removed from UserRead as intended.The change aligns with the PR objective to remove groups from the UserRead model. However, there are a few points to consider:
- Remove the misleading comment "# Add groups attribute" as it's no longer relevant.
- Ensure that no other parts of the codebase rely on the presence of the
groupsattribute in UserRead. This change might affect API responses or other serialization processes.- Consider adding a comment explaining why groups are excluded from UserRead, for future reference.
- Update any API documentation that might reference the
groupsattribute in UserRead responses.To verify potential impacts, you can run the following script:
This script will help identify areas of the codebase that might be affected by the removal of the
groupsattribute from UserRead.✅ Verification successful
To ensure accurate verification, please run the following updated script:
To accurately verify the usage of the
groupsattribute inUserRead, please run the following updated script:
Verified:
groupsattribute successfully removed fromUserRead.The removal of the
groupsattribute from theUserReadmodel has been successfully verified with no dependencies or references found in the codebase or documentation.Next Steps:
- Remove the outdated comment:
- Delete the line
# groups: list[uuid_UUID] # Add groups attributefromcognee/modules/users/models/User.pyto prevent confusion.- Confirm Documentation Update:
- Although no mentions were found, ensure that any future API documentation reflects this change to maintain consistency.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for usage of UserRead.groups in the codebase # Search for UserRead usage echo "Searching for UserRead usage:" rg --type python "UserRead" -C 3 # Search for any mention of user groups in API documentation echo "Searching for user groups in API documentation:" rg --type md --type rst "user.*groups"Length of output: 278
Script:
#!/bin/bash # Description: Check for usage of UserRead.groups in the codebase # Search for UserRead usage with corrected file type echo "Searching for UserRead usage:" rg --type py "UserRead" -C 3 # Search for any mention of user groups in API documentation echo "Searching for user groups in API documentation:" rg --type md --type rst "user.*groups"Length of output: 2107
Script:
#!/bin/bash # Description: Check for usage of UserRead.groups in the codebase # Search for UserRead.groups usage with precise pattern echo "Searching for UserRead.groups usage in Python files:" rg --type py "UserRead\.groups" -C 3 # Search for any indirect mention of user groups in API documentation echo "Searching for indirect mentions of user groups in API documentation:" rg --type md --type rst "\buser\b.*\bgroups\b" -iLength of output: 352
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (3)
entrypoint.sh (3)
11-11: LGTM: Correct usage of Alembic for database migrations.The command correctly uses Poetry to run Alembic migrations, ensuring the database is updated to the latest version.
Consider adding error handling for this command, such as:
if ! poetry run alembic upgrade head; then echo "Migration failed, exiting." exit 1 fiThis would eliminate the need for the separate exit status check.
12-18: LGTM: Good error handling and feedback for migration process.The added error handling and feedback for the migration process is a good practice. It provides clear information about the success or failure of the migrations and exits appropriately on failure.
Consider using bash functions to make the script more modular and easier to maintain. For example:
run_migrations() { echo "Running database migrations..." if poetry run alembic upgrade head; then echo "Migrations completed successfully." else echo "Migration failed, exiting." exit 1 fi } run_migrationsThis would make the script more readable and easier to maintain in the future.
6-19: Overall improvements to database migration process and script clarity.The changes to this script enhance the database migration process by:
- Improving readability with better comments and blank lines.
- Providing clearer feedback during the migration process.
- Adding error handling for migration failures.
These improvements will make it easier to diagnose issues during deployment and ensure that the application doesn't start with an outdated database schema.
Consider adding logging to a file in addition to console output. This would be helpful for debugging issues in production environments where console output might not be easily accessible.
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
- entrypoint.sh (1 hunks)
🧰 Additional context used
🔇 Additional comments (1)
entrypoint.sh (1)
6-8: LGTM: Improved script readability and user feedback.The added blank line, updated comment, and new echo statement enhance the script's readability and provide better feedback during execution.
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
alembic/env.py (1)
95-96: Approved: Enhanced logging and configuration for database migrationsThe changes improve the visibility and configuration of the database connection for Alembic migrations:
- Adding a print statement for the database URI enhances debugging capabilities.
- Explicitly setting the
SQLALCHEMY_DATABASE_URIin the Alembic configuration ensures the correct connection string is used.These modifications contribute to a more robust and transparent migration process.
Consider using a logging framework instead of a print statement for consistency with other parts of the application:
-print("Using database:", db_engine.db_uri) +import logging +logging.info(f"Using database: {db_engine.db_uri}")This change would allow for better log management and consistency across the application.
Also applies to: 98-102
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
cognee/api/client.py (1)
51-52: Approve: Improved error response in get_dataset_data endpointThe modification to return an
ErrorResponseDTOinstead of a generic JSON response is a positive change. It enhances the consistency and specificity of error responses, aligning with best practices for API design.Consider applying similar improvements to other endpoints in the file for consistency across the API. This will provide a uniform error handling experience for API consumers.
Example of how to apply this to other endpoints:
@app.get("/api/v1/some_other_endpoint", responses={404: {"model": ErrorResponseDTO}}) async def some_other_endpoint(): # ... existing logic ... if not found: return JSONResponse( status_code=404, content=ErrorResponseDTO(message="Resource not found").dict(), )
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (2)
- cognee/api/client.py (1 hunks)
- entrypoint.sh (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- entrypoint.sh
🧰 Additional context used
🔇 Additional comments (1)
cognee/api/client.py (1)
46-49:⚠️ Potential issueReconsider removal of environment check for database creation
The environment check for "local" or "dev" has been commented out, which means the database creation logic will now run in all environments, including production. This change could potentially lead to unintended consequences:
- It may attempt to create a database that already exists in production.
- It removes environment-specific behavior that might have been intentional.
Consider the following options:
- If the intention is to run this logic in all environments, add a comment explaining why this is safe and intended.
- If this was unintentional, revert the change and keep the environment check.
- Implement a more robust check that ensures database creation only happens when necessary, regardless of the environment.
To verify the impact of this change, you can run the following script:
This script will help identify if there are other places in the codebase where database creation is handled or if there are environment-specific checks that might be affected by this change.
✅ Verification successful
Environment Check Removal Verified as Safe
The removal of the environment check for "local" or "dev" in
cognee/api/client.pyis safe because thecreate_databasefunction internally handles environment-specific logic based on the database dialect. This ensures that database creation is appropriately managed across different environments without unintended side effects.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for database creation logic in different environment configurations # Test: Search for database creation logic echo "Searching for database creation logic:" rg "await db_engine.create_database()" cognee/api/client.py # Test: Check for environment variable usage echo "Checking for environment variable usage:" rg "app_environment" cognee/api/client.py # Test: Look for other occurrences of database initialization echo "Checking for other database initialization occurrences:" rg "create_database" cognee/Length of output: 818
Script:
#!/bin/bash # Description: Inspect the implementation of create_database in SqlAlchemyAdapter.py echo "Fetching the create_database function implementation:" ast-grep --lang python --pattern 'def create_database($_): { $$$ }' cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.pyLength of output: 261
Script:
#!/bin/bash # Description: Search for the create_database function definition in SqlAlchemyAdapter.py echo "Searching for the create_database function definition:" rg "^def create_database" cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.pyLength of output: 221
Script:
#!/bin/bash # Description: Search for the create_database function definition in SqlAlchemyAdapter.py with a flexible pattern echo "Searching for the create_database function definition with flexible pattern:" rg "def\s+create_database" cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.pyLength of output: 303
Script:
#!/bin/bash # Description: Extract the full implementation of the create_database function in SqlAlchemyAdapter.py echo "Extracting the create_database function implementation with context:" rg -A 20 "async def create_database" cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.pyLength of output: 1062
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
alembic/versions/482cd6517ce4_add_default_user.py (2)
Line range hint
22-23: Consider adding error handling and logging to the upgrade function.While the
upgrade()function correctly callscreate_default_user()asynchronously, it lacks error handling and logging. This could make troubleshooting difficult if the migration fails.Consider modifying the function as follows:
import logging def upgrade() -> None: try: await_only(create_default_user()) logging.info("Default user created successfully") except Exception as e: logging.error(f"Failed to create default user: {str(e)}") raiseThis modification adds basic error handling and logging, which will help in identifying issues if the migration fails.
Line range hint
26-27: Improve downgrade function and consider parameterizing the default user email.The
downgrade()function could benefit from error handling and logging. Additionally, the hardcoded email address might cause issues if the default user's email changes in the future.Consider the following improvements:
- Add error handling and logging:
import logging def downgrade() -> None: try: await_only(delete_user(DEFAULT_USER_EMAIL)) logging.info(f"Default user {DEFAULT_USER_EMAIL} deleted successfully") except Exception as e: logging.error(f"Failed to delete default user: {str(e)}") raise
- Parameterize the default user email:
# At the top of the file DEFAULT_USER_EMAIL = "[email protected]" # Then use DEFAULT_USER_EMAIL in the downgrade functionThis allows for easier updates if the default user email changes and improves the maintainability of the code.
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (1)
- alembic/versions/482cd6517ce4_add_default_user.py (1 hunks)
🧰 Additional context used
🔇 Additional comments (2)
alembic/versions/482cd6517ce4_add_default_user.py (2)
Line range hint
1-18: LGTM: Migration metadata is correctly structured.The migration metadata is well-defined and follows Alembic conventions. The revision ID, dependencies, and imports are all correctly set.
19-19: Verify the explicit dependency on revision 8057ae7329c2.The
depends_onattribute has been set to"8057ae7329c2", creating an explicit dependency. Please confirm that this migration should indeed run after the specified revision and that this dependency is necessary for the correct execution of the migration sequence.To check the migration history and ensure this dependency is correct, run the following command:
This will show the migration history, allowing you to verify that the dependency is correctly set and necessary.
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
cognee/infrastructure/databases/vector/config.py (1)
12-12: LGTM! Consider adding a docstring for clarity.The renaming from
vector_engine_providertovector_db_providerimproves clarity and consistency. It's a good change that better represents the vector database concept.Consider adding a brief docstring to explain the purpose of this attribute, e.g.:
vector_db_provider: str = "lancedb" """The provider of the vector database. Default is 'lancedb'."""
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (8)
- .env.template (1 hunks)
- cognee/api/v1/config/config.py (2 hunks)
- cognee/infrastructure/databases/vector/config.py (1 hunks)
- cognee/modules/settings/get_settings.py (1 hunks)
- cognee/modules/settings/save_vector_db_config.py (1 hunks)
- cognee/tests/test_qdrant.py (1 hunks)
- cognee/tests/test_weaviate.py (1 hunks)
- notebooks/cognee_demo.ipynb (1 hunks)
🔥 Files not summarized due to errors (1)
- notebooks/cognee_demo.ipynb: Error: Server error: no LLM provider could handle the message
🧰 Additional context used
🔇 Additional comments (10)
cognee/modules/settings/save_vector_db_config.py (1)
15-15: Approve the attribute renaming for consistency.The change from
vector_engine_providertovector_db_provideraligns with similar updates across the codebase, improving overall consistency. This is a positive change that enhances code readability and maintainability.To ensure this change doesn't introduce any issues, please run the following script to check for any remaining occurrences of
vector_engine_provider:If the script returns any results, those occurrences should be updated to maintain consistency.
✅ Verification successful
Attribute renaming verified successfully.
No remaining occurrences of
vector_engine_providerfound in the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining occurrences of 'vector_engine_provider' # Test: Search for 'vector_engine_provider' in the codebase rg 'vector_engine_provider'Length of output: 27
.env.template (1)
16-16: Approve renaming of VECTOR_ENGINE_PROVIDER to VECTOR_DB_PROVIDERThe change from
VECTOR_ENGINE_PROVIDERtoVECTOR_DB_PROVIDERappears to be a more accurate description of the variable's purpose. This is a good improvement in terminology.To ensure this change is consistent across the codebase, please run the following verification script:
Please review the output to ensure:
- There are no remaining instances of
VECTOR_ENGINE_PROVIDERthat need to be updated.- The new
VECTOR_DB_PROVIDERis being used correctly where needed.- Any related documentation or configuration files are updated to reflect this change.
cognee/infrastructure/databases/vector/config.py (2)
20-20: LGTM! Consistent with the attribute renaming.The update to the dictionary key in the
to_dictmethod is correct and maintains consistency with the renamed attribute.
12-20: Verify usage of the renamed attribute across the codebase.The renaming of
vector_engine_providertovector_db_provideris a good change for consistency and clarity. However, we should ensure that all references to this attribute have been updated throughout the codebase to prevent any potential issues.Let's verify the usage of the new attribute name:
✅ Verification successful
Attribute Renaming Verified Successfully
All instances of
vector_engine_providerhave been removed, andvector_db_provideris consistently used throughout the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining instances of 'vector_engine_provider' and verify 'vector_db_provider' usage echo "Checking for any remaining 'vector_engine_provider' instances:" rg "vector_engine_provider" echo "\nVerifying 'vector_db_provider' usage:" rg "vector_db_provider"Length of output: 1815
cognee/modules/settings/get_settings.py (1)
103-104: LGTM! Verify consistency across the codebase.The changes from
vector_engine_providertovector_db_providerare correct and align with the broader refactoring effort mentioned in the AI summary. The lowercase conversion is maintained, which is good for consistency.To ensure these changes are consistent across the entire codebase, please run the following script:
✅ Verification successful
Verified: Consistent use of
vector_db_providerthroughout the codebase.All instances of
vector_engine_providerhave been successfully replaced withvector_db_provider, and method names are consistent.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the consistent use of 'vector_db_provider' instead of 'vector_engine_provider' # Test 1: Check for any remaining instances of 'vector_engine_provider' echo "Checking for remaining instances of 'vector_engine_provider':" rg "vector_engine_provider" # Test 2: Verify the usage of 'vector_db_provider' echo "Verifying usage of 'vector_db_provider':" rg "vector_db_provider" # Test 3: Check for any inconsistencies in method names (e.g., set_vector_db_provider) echo "Checking for method name consistency:" rg "set_vector_(engine|db)_provider"Length of output: 2189
cognee/api/v1/config/config.py (2)
94-96: LGTM! Verify all method calls have been updated.The renaming of
set_vector_engine_providertoset_vector_db_provider, along with the corresponding parameter update, improves consistency in terminology. The method's functionality remains unchanged.To ensure all calls to this method have been updated throughout the codebase, please run the following script:
#!/bin/bash # Description: Check for any remaining calls to 'set_vector_engine_provider' in the codebase # Test: Search for 'set_vector_engine_provider'. Expect: No results, indicating complete renaming of method calls. rg 'set_vector_engine_provider'
24-24: LGTM! Verify impact on existing functionality.The change from
vector_engine_providertovector_db_providerimproves consistency in terminology. This aligns with the method renaming later in the file.To ensure this change doesn't break existing functionality, please run the following script:
cognee/tests/test_qdrant.py (1)
12-12: Approve the rename fromset_vector_engine_providertoset_vector_db_provider.This change improves consistency in terminology across the project, shifting from "engine" to "database" for vector storage. The functionality remains the same, and this update aligns with similar changes in other files.
Consider reviewing other occurrences of "engine" in this file (e.g.,
get_vector_engine()) for potential updates to maintain consistency.Let's verify if this change has been applied consistently across the codebase:
cognee/tests/test_weaviate.py (1)
10-10: LGTM! Verify consistency and update documentation.The change from
set_vector_engine_providertoset_vector_db_providerlooks good and aligns with the refactoring mentioned in the summary.To ensure consistency, please run the following script to check for any remaining occurrences of
set_vector_engine_provider:Don't forget to update any relevant documentation or comments that might still reference "vector engine" instead of "vector database".
✅ Verification successful
Change Verified
All instances of
set_vector_engine_providerhave been successfully updated. The usage ofvector_engineremains consistent and appropriate across the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining occurrences of 'set_vector_engine_provider' # Test: Search for 'set_vector_engine_provider'. Expect: No results. rg 'set_vector_engine_provider' # Test: Search for 'vector_engine' to identify any related terms that might need updating. rg 'vector_engine'Length of output: 9861
notebooks/cognee_demo.ipynb (1)
551-551: LGTM! Consider adding more context about the vector database choice.The change to set
VECTOR_DB_PROVIDERto "lancedb" looks good. It simplifies the configuration by not requiring additional environment variables.Consider adding a brief comment explaining the implications of choosing lancedb over qdrant or weaviate. This could help other developers understand the reasoning behind this choice.
To ensure this change is consistently applied across the project, please run the following script:
Also, please ensure that the project documentation is updated to reflect this change in configuration.
✅ Verification successful
LGTM! All configurations remain consistent with project standards.
The update to set
VECTOR_DB_PROVIDERto "lancedb" is correctly implemented and does not disrupt existing configurations for other providers.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any hardcoded vector database configurations that might need updating # Search for qdrant or weaviate configurations echo "Searching for qdrant or weaviate configurations:" rg -i "qdrant|weaviate" --type py --type json --type yaml # Search for vector database related environment variables echo "Searching for vector database related environment variables:" rg "VECTOR_DB_" --type py --type json --type yaml # Check if there's any project documentation that needs updating echo "Checking for potential documentation that might need updating:" fd -e md -e rst | xargs rg -i "vector.?database|qdrant|weaviate|lancedb"Length of output: 8157
There was a problem hiding this comment.
Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (3)
cognee/infrastructure/llm/openai/adapter.py (3)
Line range hint
132-134: Approve file existence check with minor suggestionThe addition of a file existence check before processing improves error handling. This is a good practice to prevent potential issues with missing files.
Consider using
Path(input).is_file()instead ofos.path.isfile(input)for consistency with thePathusage later in the method:if not Path(input).is_file(): raise FileNotFoundError(f"The file {input} does not exist.")
Line range hint
158-178: Approve image transcription updates with suggestion for error handlingThe changes to the
transcribe_imagemethod, including base64 encoding of the image and the updated API call format, align with the latest OpenAI API requirements for image analysis. This is a good improvement.Consider adding error handling for file operations:
try: with open(input, "rb") as image_file: encoded_image = base64.b64encode(image_file.read()).decode('utf-8') except IOError as e: raise FileNotFoundError(f"Error reading the image file: {e}")This will provide more informative error messages if there are issues with reading the image file.
Line range hint
180-182: Approve input validation with suggestion for consistencyThe addition of input validation in the
show_promptmethod improves the robustness of the function. Providing a default message for emptytext_inputand raising an error for missingsystem_promptare good practices.For consistency with the
text_inputhandling, consider providing a default system prompt instead of raising an error:if not text_input: text_input = "No user input provided." if not system_prompt: system_prompt = "Default system prompt."This approach would make the method more flexible and consistent in handling both inputs.
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (3)
- cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py (1 hunks)
- cognee/infrastructure/llm/openai/adapter.py (1 hunks)
- cognee/tasks/chunk_update_check/chunk_update_check.py (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py
🧰 Additional context used
🔇 Additional comments (3)
cognee/tasks/chunk_update_check/chunk_update_check.py (1)
17-17: Approve change with a suggestion for further verification.The conversion of
chunk.idto a string when creatingexisting_chunks_mapimproves consistency and robustness. This change aligns well with the comparison on line 22.To ensure this change doesn't introduce any unintended consequences, please verify the types used for chunk IDs throughout the codebase. Run the following script to check for any potential inconsistencies:
Review the results to ensure that the types are consistent and compatible with this change.
✅ Verification successful
Change Verified Successfully.
The conversion of
chunk.idto a string inexisting_chunks_mapaligns with the consistent use ofstrtype hints for chunk IDs throughout the codebase. No issues were found.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for usage of chunk.id and chunk.chunk_id across the codebase # Search for chunk.id usage echo "Searching for chunk.id usage:" rg -n 'chunk\.id' --type py echo -e "\nSearching for chunk.chunk_id usage:" rg -n 'chunk\.chunk_id' --type py echo -e "\nSearching for type hints related to chunk IDs:" rg -n '(chunk_id|id):\s*(str|int)' --type pyLength of output: 11729
cognee/infrastructure/llm/openai/adapter.py (2)
Line range hint
1-187: Approve overall class structure and consistencyThe changes to the
OpenAIAdapterclass maintain its overall structure while updating method implementations consistently. The removal of monitoring tool dependencies and updates to API calls are applied uniformly throughout the class.The modifications improve the adapter's functionality and align it with the latest OpenAI API requirements. Good job on maintaining code consistency throughout these changes.
15-15: Verify the impact of removing monitoring tool importsThe removal of conditional imports for different monitoring tools (Langfuse, Langsmith) simplifies the code, but it may affect functionality if these tools were previously used. Please ensure that this change aligns with the project's current monitoring strategy.
To confirm that no other parts of the codebase rely on the removed imports, run the following script:
Consider adding a comment explaining why the monitoring tool imports were removed to improve code maintainability.
Also applies to: 24-33
✅ Verification successful
Monitoring tool imports removal verified
No active usages of
MonitoringTool,Langfuse, orLangsmithremain inadapter.py. The removal does not impact other parts of the codebase that continue to utilize these monitoring tools.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Search for usage of MonitoringTool, Langfuse, or Langsmith in the codebase rg -i "MonitoringTool|Langfuse|Langsmith" --type pyLength of output: 1467
There was a problem hiding this comment.
Actionable comments posted: 6
🧹 Outside diff range and nitpick comments (7)
examples/node/handleServerErrors.js (2)
6-12: LGTM: Comprehensive error handling with a minor suggestion.The error handling covers different scenarios well. However, for consistency, consider wrapping all error messages in an Error object.
Here's a suggested improvement:
if (!response.ok) { if (response.json) { - return response.json().then(error => reject(error)); + return response.json().then(error => reject(new Error(JSON.stringify(error)))); } else { - return reject(response.detail || response.body || response); + return reject(new Error(response.detail || response.body || JSON.stringify(response))); } }
1-16: Overall assessment: Well-structured error handling with minor improvement suggestions.The
handleServerErrorsfunction provides a comprehensive mechanism for handling various server response scenarios. It effectively differentiates between unauthorized access, other error responses, and successful responses. The suggested improvements for error consistency and Promise rejection in the 401 case will further enhance its robustness.Consider adding unit tests to verify the behavior of this function under different response scenarios, ensuring its reliability as a core part of your error handling strategy.
cognee/tasks/graph/query_graph_connections.py (2)
40-40: Approve UUID to string conversion in list comprehensionThe explicit conversion of UUID to string using
str()within the list comprehension is consistent with the earlier change and follows best practices. This ensures that all calls toget_connectionsuse string representations of UUIDs.For improved readability, consider extracting the UUID conversion to a separate step:
uuids = [str(result.payload["uuid"]) for result in relevant_results] node_connections_results = await asyncio.gather(*[graph_engine.get_connections(uuid) for uuid in uuids])This separation of concerns can make the code slightly more readable and easier to maintain.
Line range hint
1-62: Overall assessment: Consistent UUID handling improvementThe changes in this file consistently improve UUID handling by ensuring explicit string conversion before passing to
graph_engine.get_connections(). This modification aligns with best practices and likely prevents potential issues with UUID type handling in the graph engine.Consider adding a brief comment in the function docstring to mention the UUID to string conversion, for example:
async def query_graph_connections(query: str, exploration_levels = 1) -> list[(str, str, str)]: """ Find the neighbours of a given node in the graph and return formed sentences. Note: UUIDs are converted to strings before querying the graph engine. Parameters: ... """This addition would provide helpful context for future developers working with this function.
.gitignore (1)
179-181: Approved additions with a minor suggestion for improvement.The new entries are appropriate and align with good Git practices:
.cognee_system/and.data_storage/ignore project-specific development directories.node_modules/is correctly ignored for the new Node.js project.Consider grouping related entries together for better readability and maintainability. You could move the
node_modules/entry next to other JavaScript/Node.js related patterns (if any) or add a comment to indicate it's for the Node.js example project.Example:
# Node.js (for examples/node) node_modules/ # Cognee development directories .cognee_system/ .data_storage/examples/node/main.js (2)
7-21: Consider removing commented-out code for cleanliness.The block of commented-out code related to user registration can clutter the codebase. If it's no longer needed, consider removing it. If you need to keep it for future reference, you can use version control to retrieve it later.
117-119: Enhance error handling by providing more context.Currently, the error is logged without much context. Consider adding more details or rethrowing the error to make debugging easier.
Update the catch block to include the stack trace:
} catch (error) { - console.error('Error:', error); + console.error('Error occurred:', error.message); + console.error(error.stack); }
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
⛔ Files ignored due to path filters (2)
examples/data/artificial_intelligence.pdfis excluded by!**/*.pdfexamples/node/package-lock.jsonis excluded by!**/package-lock.json
📒 Files selected for processing (6)
- .gitignore (1 hunks)
- cognee/tasks/graph/query_graph_connections.py (2 hunks)
- examples/node/fetch.js (1 hunks)
- examples/node/handleServerErrors.js (1 hunks)
- examples/node/main.js (1 hunks)
- examples/node/package.json (1 hunks)
✅ Files skipped from review due to trivial changes (1)
- examples/node/package.json
🧰 Additional context used
🔇 Additional comments (6)
examples/node/fetch.js (1)
1-2: LGTM: Imports are appropriate and well-structured.The imports are correctly set up, with
node-fetchimported asnodeFetchto avoid naming conflicts with the customfetchfunction. The local import ofhandleServerErrorsis also correctly implemented.examples/node/handleServerErrors.js (2)
1-2: LGTM: Function signature and Promise creation.The function name
handleServerErrorsclearly describes its purpose, and using a Promise is appropriate for handling asynchronous server responses.
14-16: LGTM: Proper handling of successful responses.The function correctly resolves the Promise with the full response object for successful requests, providing flexibility for the caller.
cognee/tasks/graph/query_graph_connections.py (1)
26-26: Approve UUID to string conversionThe explicit conversion of UUID to string using
str()is a good practice. This ensures compatibility with theget_connectionsmethod and prevents potential type-related issues when working with UUIDs in the graph engine.examples/node/main.js (2)
49-54: Verify that 'addData.getHeaders()' includes necessary headers.When sending the form data to
/v1/add, ensure thataddData.getHeaders()returns all the necessary headers, including the correctContent-Type. Missing or incorrect headers might lead to issues with file upload.Run the following script to inspect the headers returned by
addData.getHeaders():#!/bin/bash # Description: Log the headers from 'addData.getHeaders()' to verify their correctness. # Note: Adjust the script to insert a console.log statement that outputs the headers. # Expected: Headers should include 'Content-Type' with the correct boundary. fd 'main\.js' --exec sed -n '/addData\.getHeaders()/p' {}
35-35: Verify that the token is correctly included in the request headers.Ensure that the authentication token is being properly included in the headers of the request to
/v1/datasets. This will guarantee that the request is authenticated and can access the necessary resources.Run the following script to check if the token is included in the headers:
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Summary by CodeRabbit
New Features
Bug Fixes
get_dataset_dataendpoint for clearer API responses when datasets are not found.Chores
.gitignorefor better version control management.