feat: improve API request and response models and docs #154
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WalkthroughThis pull request introduces various changes across multiple files, primarily focusing on improving documentation clarity, standardizing API response structures, and updating naming conventions for configuration attributes. Key modifications include enhancements to the Changes
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Actionable comments posted: 13
🧹 Outside diff range and nitpick comments (21)
cognee/api/DTO.py (3)
1-2: Remove unused importto_snake.The
to_snakefunction is imported frompydantic.alias_generatorsbut is not used in the current code. It's a good practice to remove unused imports to keep the codebase clean and avoid potential confusion.Apply this diff to remove the unused import:
-from pydantic.alias_generators import to_camel, to_snake +from pydantic.alias_generators import to_camel
5-9: Add a docstring to clarify the purpose of OutDTO.The
OutDTOclass is well-defined and follows Pydantic conventions. The use ofto_camelas the alias generator is good for API consistency, especially when interacting with frontend JavaScript.Consider adding a docstring to explain the purpose of this class and how it should be used. For example:
class OutDTO(BaseModel): """ Base class for outgoing Data Transfer Objects. This class provides a configuration that converts all attribute names to camelCase when the model is serialized, which is useful for maintaining consistent API responses. Subclasses should define their specific fields. """ model_config = ConfigDict( alias_generator = to_camel, populate_by_name = True, )
11-15: Add a docstring and consider configuration differences for InDTO.The
InDTOclass is well-defined and follows the same structure asOutDTO. Having separate classes for input and output DTOs is a good practice for clear separation of concerns.
Consider adding a docstring to explain the purpose of this class, similar to the suggestion for
OutDTO.The configuration for
InDTOis identical toOutDTO. While this might be intentional, it's worth considering if there should be any differences in how input data is handled compared to output data. For example, you might want stricter validation rules for input data.Here's an example of how you might implement these suggestions:
class InDTO(BaseModel): """ Base class for incoming Data Transfer Objects. This class provides a configuration that converts all attribute names to camelCase when the model is deserialized, which is useful for maintaining consistent API requests. Subclasses should define their specific fields and any additional validation rules. """ model_config = ConfigDict( alias_generator = to_camel, populate_by_name = True, # Consider adding any input-specific configuration here # For example: extra = 'forbid' to disallow extra attributes in input )Do you want to keep the configurations identical, or should there be any input-specific settings?
cognee/modules/settings/save_llm_config.py (1)
15-16: LGTM! Consider simplifying the condition.The updates to use
api_keyinstead ofapiKeyare correct and consistent with the earlier change. The logic for handling the API key is sound.Consider simplifying the condition to remove the redundant length check:
- if "*****" not in new_llm_config.api_key and len(new_llm_config.api_key.strip()) > 0: + if "*****" not in new_llm_config.api_key: llm_config.llm_api_key = new_llm_config.api_keyThis simplification maintains the same functionality while making the code more concise.
cognee/modules/pipelines/models/PipelineRun.py (2)
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12-24: Update PipelineRun class to use the new PipelineRunStatus enumThe
PipelineRunclass should be updated to use the newly createdPipelineRunStatusenum for itsstatuscolumn. This will provide better type safety and ensure consistency with the defined statuses. Here's the suggested change:- from sqlalchemy import Column, DateTime, String, JSON + from sqlalchemy import Column, DateTime, String, JSON, Enum class PipelineRun(Base): __tablename__ = "pipeline_runs" id = Column(UUID, primary_key = True, default = uuid4) created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) - status = Column(String) + status = Column(Enum(PipelineRunStatus)) run_id = Column(UUID, index = True) run_info = Column(JSON)This change will ensure that only valid statuses from the
PipelineRunStatusenum can be assigned to thestatuscolumn.
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1-24: Overall good addition, but further integration neededThe introduction of the
PipelineRunStatusenum is a positive step towards better code organization and type safety. However, to fully realize its benefits, consider the following next steps:
- Update the
PipelineRunclass to use the new enum for itsstatuscolumn.- Ensure all code that interacts with pipeline run statuses (e.g., status checks, updates) uses the new enum instead of string literals.
- Update any related documentation or API specifications to reflect the new status values.
- If there are any database migrations needed to support this change, ensure they are created and tested.
These steps will help maintain consistency across the codebase and reduce the likelihood of errors related to invalid status values.
docs/api_reference.md (11)
26-29: Approve changes with a minor suggestion.The standardization of the response format is a good improvement for consistency. However, consider making the status code dynamic to accommodate different scenarios (e.g., error responses).
Consider updating the example to show how error responses would look:
{ "status": 200, // or appropriate status code "body": { "message": "Hello, World, I am alive!" } }
43-43: Approve changes with a suggestion for improvement.The standardization of the response format is good. However, consider expanding the response to include more meaningful health check information.
Consider updating the health check response to provide more detailed information:
{ "status": 200, "body": { "status": "healthy", "version": "1.0.0", "uptime": "10d 2h 30m", "services": { "database": "connected", "cache": "connected" } } }This provides more valuable information about the system's health.
56-67: Approve changes with a suggestion for pagination.The standardization of the response format is good. The example clearly shows the new structure.
Consider adding pagination information to the response for better scalability:
{ "status": 200, "body": { "datasets": [ { "id": "dataset_id_1", "name": "Dataset Name 1", "description": "Description of Dataset 1", ... }, ... ], "pagination": { "total": 100, "page": 1, "per_page": 20, "next_page": 2 } } }This addition would help clients handle large numbers of datasets more efficiently.
83-83: Approve changes with a suggestion for more informative response.The standardization of the response format is good. However, the response could be more informative.
Consider updating the response to provide more information about the deleted dataset:
{ "status": 200, "body": { "message": "Dataset successfully deleted", "deleted_dataset_id": "dataset_id_1" } }This provides confirmation of the deletion and identifies which dataset was deleted.
114-124: Approve changes with a suggestion for pagination.The standardization of the response format is good. The example clearly shows the new structure.
Consider adding pagination information to the response for better scalability:
{ "status": 200, "body": { "data": [ { "data_id": "data_id_1", "content": "Data content here", ... }, ... ], "pagination": { "total": 1000, "page": 1, "per_page": 50, "next_page": 2 } } }This addition would help clients handle large datasets more efficiently.
140-145: Approve changes with a suggestion for more detailed status information.The standardization of the response format is good. The example clearly shows the new structure.
Consider providing more detailed status information for each dataset:
{ "status": 200, "body": { "dataset_id_1": { "status": "processing", "progress": 75, "last_updated": "2023-05-15T14:30:00Z" }, "dataset_id_2": { "status": "ready", "last_updated": "2023-05-14T09:15:00Z" }, ... } }This provides more comprehensive information about each dataset's status.
184-184: Approve changes with a suggestion for more informative response.The standardization of the response format is good. However, the response could be more informative.
Consider updating the response to provide more information about the added data:
{ "status": 200, "body": { "message": "Data successfully added", "dataset_id": "ID_OF_THE_DATASET", "added_files": [ { "filename": "file1.txt", "size": 1024, "data_id": "generated_data_id_1" }, ... ] } }This provides confirmation of the data addition and details about the added files.
205-205: Approve changes with a suggestion for more informative response.The standardization of the response format is good. However, the response could be more informative about the cognify process.
Consider updating the response to provide more information about the cognify process:
{ "status": 200, "body": { "message": "Cognify process initiated", "process_id": "cognify_process_123", "datasets": ["ID_OF_THE_DATASET_1", "ID_OF_THE_DATASET_2"], "estimated_completion_time": "2023-05-15T16:30:00Z" } }This provides confirmation of the process initiation and additional useful information.
228-261: Approve changes with suggestions for improvements.The standardization of the response format across all search types is excellent. The examples clearly show the new structure for each search type.
Consider the following improvements:
- For the "INSIGHTS" search type, add more context to the relationships:
{ "status": 200, "body": [ { "source": { "name": "source_node_name", "type": "node_type" }, "relationship": { "name": "between_nodes_relationship_name", "strength": 0.85 }, "target": { "name": "target_node_name", "type": "node_type" } } ] }
- For "SUMMARIES" and "CHUNKS" search types, add metadata and relevance scores:
{ "status": 200, "body": { "results": [ { "text": "summary_text or chunk_text", "relevance_score": 0.95, "metadata": { "source": "document_name", "page": 5, "timestamp": "2023-05-15T14:30:00Z" } }, ... ], "total_results": 100, "page": 1, "per_page": 10 } }These changes provide more context and allow for better result interpretation and pagination.
274-279: Approve changes with a suggestion for versioning.The standardization of the response format is good. The example clearly shows the new structure.
Consider adding a version field to the settings response:
{ "status": 200, "body": { "version": "1.0", "last_updated": "2023-05-15T14:30:00Z", "settings": { "llm": {...}, "vectorDB": {...}, ... } } }This addition would help track changes in settings over time and ensure compatibility.
297-297: Approve changes with a suggestion for more informative response.The standardization of the response format is good. However, the response could be more informative about the saved settings.
Consider updating the response to provide more information about the saved settings:
{ "status": 200, "body": { "message": "Settings successfully saved", "updated_settings": ["llm", "vectorDB"], "version": "1.1", "timestamp": "2023-05-15T14:30:00Z" } }This provides confirmation of the settings update and details about what was changed.
cognee/modules/settings/get_settings.py (2)
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96-98: Correct the OpenAI model name from 'gpt-4o' to 'gpt-4'The model name
'gpt-4o'appears to be incorrect. The correct model name is likely'gpt-4'. Please update both the"value"and"label"fields to reflect the correct model name.Apply this diff to fix the model name:
"openai": [{ - "value": "gpt-4o", - "label": "gpt-4o", + "value": "gpt-4", + "label": "gpt-4", }, { "value": "gpt-4-turbo", "label": "gpt-4-turbo",
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61-112: Ensure consistency in dictionary key casingThroughout the returned dictionary, some keys use snake_case (e.g.,
"api_key","llm_provider"), while others use camelCase (e.g.,"vector_engine_provider"). For consistency and to adhere to Python conventions, consider using snake_case for all keys.Example adjustment:
"provider": { - "label": vector_config.vector_engine_provider, - "value": vector_config.vector_engine_provider.lower(), + "label": vector_config.vector_engine_provider, + "value": vector_config.vector_engine_provider.lower(), }, "url": vector_config.vector_db_url, "api_key": vector_config.vector_db_key, "providers": vector_dbs,cognee/api/client.py (2)
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164-173: UseHTTPExceptionfor consistent error handlingIn the
delete_datasetendpoint, instead of returning aJSONResponsewith anErrorResponseDTO, it's better to raise anHTTPExceptionto let FastAPI handle the error according to the specified response model.Apply this diff to fix the issue:
if dataset is None: - return JSONResponse( - status_code = 404, - content = ErrorResponseDTO(f"Dataset ({dataset_id}) not found."), - ) + raise HTTPException( + status_code = 404, + detail = f"Dataset ({dataset_id}) not found." + )
223-224: Simplify return statement when no data is foundWhen
dataset_dataisNone, you return an empty list. Sinceget_dataset_datashould return a list (which can be empty), you can simplify your code by removing theifcheck.Simplify the code:
dataset_data = await get_dataset_data(dataset_id = dataset.id) - if dataset_data is None: - return [] return dataset_dataEnsure that
get_dataset_datareturns an empty list when there's no data.
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📒 Files selected for processing (12)
- README.md (1 hunks)
- cognee-frontend/src/ui/Partials/SettingsModal/Settings.tsx (2 hunks)
- cognee/api/DTO.py (1 hunks)
- cognee/api/client.py (7 hunks)
- cognee/infrastructure/llm/config.py (1 hunks)
- cognee/modules/pipelines/models/PipelineRun.py (1 hunks)
- cognee/modules/pipelines/models/init.py (1 hunks)
- cognee/modules/settings/init.py (1 hunks)
- cognee/modules/settings/get_settings.py (4 hunks)
- cognee/modules/settings/save_llm_config.py (2 hunks)
- cognee/modules/settings/save_vector_db_config.py (1 hunks)
- docs/api_reference.md (12 hunks)
✅ Files skipped from review due to trivial changes (1)
- README.md
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cognee/api/client.py
353-353: Module level import not at top of file
(E402)
🔇 Additional comments (12)
cognee/modules/pipelines/models/__init__.py (1)
1-1: LGTM! Consider verifying usage ofPipelineRunStatus.The addition of
PipelineRunStatusto the import statement is appropriate and aligns with the PR objective of improving API models. This change makesPipelineRunStatuspublicly accessible from this module, which can be beneficial for API responses or requests.To ensure
PipelineRunStatusis being utilized as intended, you may want to verify its usage across the codebase. Here's a script to help with that:This script will help you confirm that
PipelineRunStatusis being used appropriately throughout the codebase, especially in API-related files.✅ Verification successful
Verified: PipelineRunStatus is utilized appropriately.
The
PipelineRunStatusis actively used inapi/client.py, specifically in API response models, confirming its intended usage aligns with the PR objectives.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check the usage of PipelineRunStatus in the codebase # Search for PipelineRunStatus usage echo "Searching for PipelineRunStatus usage:" rg --type python -A 5 "PipelineRunStatus" # Check if PipelineRunStatus is used in API-related files echo "Checking PipelineRunStatus usage in API-related files:" rg --type python -A 5 "PipelineRunStatus" $(fd -e py api)Length of output: 409
Script:
#!/bin/bash # Description: Find all usages of PipelineRunStatus in the codebase using ast-grep # Search for PipelineRunStatus usage across all Python files echo "Searching for PipelineRunStatus usage in all Python files:" ast-grep --lang python --pattern 'PipelineRunStatus' . # Search specifically within API-related Python files echo "Searching for PipelineRunStatus usage in API-related Python files:" ast-grep --lang python --pattern 'PipelineRunStatus' $(fd -e py api)Length of output: 811
cognee/modules/settings/__init__.py (1)
1-1: LGTM! Verify usage ofSettingsDict.The addition of
SettingsDictto the import statement is syntactically correct and aligns with the PR objectives of improving API models. This change makesSettingsDictavailable to other parts of the codebase that import from this__init__.pyfile.To ensure this change doesn't introduce any issues, please run the following script to check for any existing usage of
SettingsDictin the codebase:This script will help verify that
SettingsDictis properly defined inget_settings.pyand identify any existing usage in the codebase that might be affected by this change.✅ Verification successful
Verified usage of
SettingsDict.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for existing usage of SettingsDict in the codebase # Search for SettingsDict usage echo "Searching for SettingsDict usage:" rg --type python "SettingsDict" -g "!cognee/modules/settings/__init__.py" # Check if SettingsDict is defined in get_settings.py echo "Verifying SettingsDict definition in get_settings.py:" rg --type python "^(class|type) SettingsDict" cognee/modules/settings/get_settings.pyLength of output: 417
Script:
#!/bin/bash # Description: Check for existing usage of SettingsDict in the codebase # Search for SettingsDict usage echo "Searching for SettingsDict usage:" rg --type py "SettingsDict" -g "!cognee/modules/settings/__init__.py" # Check if SettingsDict is defined in get_settings.py echo "Verifying SettingsDict definition in get_settings.py:" rg --type py "^(class|type) SettingsDict" cognee/modules/settings/get_settings.pyLength of output: 610
cognee/modules/settings/save_llm_config.py (1)
5-5: LGTM! Verify usage in other files.The renaming of
apiKeytoapi_keyimproves consistency with Python naming conventions. This change aligns well with the PR objective of updating naming conventions for configuration attributes.To ensure this change doesn't break other parts of the codebase, please run the following script to check for any remaining usage of
apiKey:✅ Verification successful
Verified: No remaining usage of
apiKeyfound in the codebase.The renaming of
apiKeytoapi_keyhas been successfully applied throughout the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining usage of 'apiKey' in Python files # Test: Search for 'apiKey' in Python files. Expect: No results or only in comments. rg --type python 'apiKey'Length of output: 56
Script:
#!/bin/bash # Description: Check for any remaining usage of 'apiKey' in Python files # Test: Search for 'apiKey' in Python files. Expect: No results or only in comments. find . -type f -name "*.py" -exec grep -Hn 'apiKey' {} \;Length of output: 60
cognee/modules/settings/save_vector_db_config.py (2)
7-7: Verify consistent renaming across the project.While the changes in this file are correct, it's important to ensure that similar renaming has been applied consistently across the entire project.
Run the following script to check for any inconsistencies in naming conventions:
#!/bin/bash # Description: Check for inconsistent naming conventions in Python files # Search for camelCase variable names in Python files echo "Searching for potential camelCase variable names in Python files:" rg --type python '[a-z]+[A-Z][a-zA-Z]*\s*[:=]' # Search for snake_case variable names in Python files echo "Verifying snake_case usage in Python files:" rg --type python '[a-z_]+\s*[:=]'Please review the results and ensure that the naming convention is applied consistently throughout the project.
Also applies to: 14-14
7-7: LGTM! Consistent naming convention applied.The changes from
apiKeytoapi_keyalign with Python's naming convention (PEP 8) and improve code consistency. The corresponding update in thesave_vector_db_configfunction ensures correct functionality.To ensure these changes don't introduce any issues, please run the following script to check for any remaining instances of
apiKeyin Python files and verify that all occurrences have been updated:Also applies to: 14-14
cognee/infrastructure/llm/config.py (1)
21-24: Approved: Improved naming consistencyThe changes to the dictionary keys in the
to_dictmethod improve consistency by using snake_case, which aligns with Python's recommended style guide (PEP 8). This enhancement makes the code more idiomatic and easier to read.cognee-frontend/src/ui/Partials/SettingsModal/Settings.tsx (2)
148-148: LGTM! Consistent naming applied.The change from
settings.vectorDBtosettings.vectorDbwhen setting the state is consistent with the previous change and maintains naming consistency throughout the component.To ensure all occurrences of
vectorDBhave been updated, please run the following script:#!/bin/bash # Description: Check for any remaining occurrences of 'vectorDB' in the file # Test: Search for 'vectorDB' in the current file rg --type typescript 'vectorDB' cognee-frontend/src/ui/Partials/SettingsModal/Settings.tsx # Note: This should return no results if all occurrences have been updatedThis script will help verify that no occurrences of the old naming convention (
vectorDB) remain in the file.
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1-205: Overall LGTM! Consider reviewing related files for consistency.The changes in this file are minimal and focused on renaming
vectorDBtovectorDb, which improves naming consistency and aligns with the PR objectives. The overall structure and functionality of theSettingscomponent remain unchanged.To ensure consistency across the entire project, consider running the following script:
#!/bin/bash # Description: Check for any remaining occurrences of 'vectorDB' in the project # Test: Search for 'vectorDB' in all TypeScript and JavaScript files rg --type-add 'frontend:*.{ts,tsx,js,jsx}' --type frontend 'vectorDB' cognee-frontend/ # Note: Review any results to determine if they also need to be updatedThis script will help identify any other files in the project that might need similar updates to maintain consistency with the new naming convention.
docs/api_reference.md (1)
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1-297: Overall approval with commendations and suggestions for further improvements.The changes to the API documentation significantly improve the consistency of response formats across all endpoints. This standardization will make API integration easier and more predictable for clients.
Key improvements:
- Addition of a
statusfield to all responses.- Wrapping of response data in a
bodyobject.- Consistent structure across different types of endpoints (GET, POST, DELETE).
Suggestions for further enhancements:
- Consider adding pagination information where applicable (e.g., for list responses).
- Provide more detailed information in responses, especially for action endpoints (e.g., delete, add, save).
- Include versioning information where relevant.
- Add more context and metadata to search results.
These changes represent a significant step forward in API design and documentation. Great work on improving the overall consistency and clarity of the API!
cognee/modules/settings/get_settings.py (2)
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111-116: Verify Anthropic model names for accuracyThe Anthropic models
'Claude 3 Opus','Claude 3 Sonnet', and'Claude 3 Haiku'are not standard model names known publicly. Please confirm the correct model names provided by Anthropic, such as'claude-1'or'claude-2', and update the list accordingly.
104-107:⚠️ Potential issueVerify the 'llama3' model name for the 'ollama' provider
The model
'llama3'under the'ollama'provider may not be widely recognized. It might be a typo or an outdated model name. Please verify that'llama3'is the correct model, or consider updating it to a known model like'llama-2'.cognee/api/client.py (1)
355-360: Verify multiple inheritance of DTO classesThe classes
LLMConfigDTOandVectorDBConfigDTOinherit from bothOutDTOand their respective config classes. Ensure that this inheritance correctly combines fields without conflicts.Please verify that all fields are appropriately inherited and there are no attribute conflicts between
OutDTO,LLMConfig, andVectorDBConfig.
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Actionable comments posted: 5
🧹 Outside diff range and nitpick comments (8)
cognee/modules/settings/get_settings.py (5)
6-9: Add a docstring to the ConfigChoice classWhile the
ConfigChoiceclass is well-structured, adding a docstring would improve its clarity and maintainability.Consider adding a docstring like this:
class ConfigChoice(BaseModel): """ Represents a configuration choice with a value and a label. Attributes: value (str): The internal value of the choice. label (str): The human-readable label for the choice. """ value: str label: str
10-14: Add a docstring to the ModelName enumThe
ModelNameenum is a good addition for type safety. Adding a docstring would further improve its clarity.Consider adding a docstring like this:
class ModelName(Enum): """ Enumeration of supported language model providers. """ openai = "openai" ollama = "ollama" anthropic = "anthropic"
15-21: Add a docstring to the LLMConfig classAdding a docstring to the
LLMConfigclass would improve its clarity and maintainability.Consider adding a docstring like this:
class LLMConfig(BaseModel): """ Configuration settings for the Language Model (LLM). Attributes: api_key (str): The API key for the LLM provider. model (ConfigChoice): The selected LLM model. provider (ConfigChoice): The selected LLM provider. models (dict[str, list[ConfigChoice]]): Available models for each provider. providers (list[ConfigChoice]): List of available LLM providers. """ # ... (existing fields)
22-27: Add a docstring to the VectorDBConfig classAdding a docstring to the
VectorDBConfigclass would improve its clarity and maintainability.Consider adding a docstring like this:
class VectorDBConfig(BaseModel): """ Configuration settings for the Vector Database. Attributes: api_key (str): The API key for the vector database. url (str): The URL of the vector database. provider (ConfigChoice): The selected vector database provider. providers (list[ConfigChoice]): List of available vector database providers. """ # ... (existing fields)
28-31: Add a docstring to the SettingsDict classAdding a docstring to the
SettingsDictclass would improve its clarity and maintainability.Consider adding a docstring like this:
class SettingsDict(BaseModel): """ Aggregates all settings for the application. Attributes: llm (LLMConfig): Configuration settings for the Language Model. vector_db (VectorDBConfig): Configuration settings for the Vector Database. """ llm: LLMConfig vector_db: VectorDBConfigcognee/api/v1/cognify/cognify_v2.py (1)
124-132: Good consistency in using PipelineRunStatus enumThe use of
PipelineRunStatusenum values for logging pipeline status in both success and error cases is consistent and improves the overall code quality.However, I have a minor suggestion to improve error handling:
Consider logging the error details when catching the exception. This can help with debugging and monitoring. You can modify the error handling as follows:
except Exception as error: send_telemetry("cognee.cognify EXECUTION ERRORED", user.id) logger.error(f"Error processing dataset {dataset_name}: {str(error)}", exc_info=True) await log_pipeline_status(dataset_id, PipelineRunStatus.DATASET_PROCESSING_ERRORED, { "dataset_name": dataset_name, "files": document_ids_str, "error": str(error) }) raise errorThis change will log the error details and include the error message in the pipeline status, which can be valuable for troubleshooting.
cognee/api/client.py (2)
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179-190: Simplify response handling inget_dataset_graphendpointThe
get_dataset_graphendpoint declares aresponse_model = strbut returns aJSONResponsewith the graph URL as content. This is unnecessary because FastAPI can automatically handle and serialize string responses when the response model is specified asstr.Apply this diff to simplify the response:
try: graph_client = await get_graph_engine() graph_url = await render_graph(graph_client.graph) - return JSONResponse( - status_code = 200, - content = str(graph_url), - ) + return graph_url except: - return JSONResponse( - status_code = 409, - content = "Graphistry credentials are not set. Please set them in your .env file.", - ) + raise HTTPException( + status_code = 409, + detail = "Graphistry credentials are not set. Please set them in your .env file.", + )This change allows FastAPI to handle the serialization, and using
HTTPExceptionprovides consistent error handling.
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275-288: Type inconsistency inaddendpoint'sdataparameterThe
dataparameter is annotated asList[UploadFile], but within the function, there's a checkisinstance(data, str), suggesting thatdatamight also be a string. This inconsistency can lead to runtime errors or unexpected behavior.Consider updating the function signature to reflect the possible types of
data:@app.post("/api/v1/add", response_model = None) async def add( - data: List[UploadFile], + data: Union[List[UploadFile], str], datasetId: str = Form(...), user: User = Depends(get_authenticated_user), ):Also, ensure that the logic within the function correctly handles both cases. Alternatively, you might separate the handling of file uploads and URL strings into different endpoints or parameters for clarity and type safety.
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📒 Files selected for processing (6)
- README.md (1 hunks)
- cognee/api/client.py (6 hunks)
- cognee/api/v1/cognify/cognify_v2.py (3 hunks)
- cognee/infrastructure/llm/config.py (1 hunks)
- cognee/modules/pipelines/models/PipelineRun.py (1 hunks)
- cognee/modules/settings/get_settings.py (4 hunks)
✅ Files skipped from review due to trivial changes (1)
- README.md
🚧 Files skipped from review as they are similar to previous changes (2)
- cognee/infrastructure/llm/config.py
- cognee/modules/pipelines/models/PipelineRun.py
🧰 Additional context used
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cognee/api/client.py
353-353: Module level import not at top of file
(E402)
🔇 Additional comments (7)
cognee/modules/settings/get_settings.py (3)
1-2: LGTM: Necessary imports addedThe new imports for
EnumandBaseModelare correctly added and are essential for the new class definitions in this file.
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32-58: LGTM: Redundant get_llm_config() call removedThe redundant call to
get_llm_config()has been removed as suggested in a previous review. This improves the efficiency of the function.
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59-110: LGTM: Proper use of SettingsDict.model_validateThe use of
SettingsDict.model_validateensures that the returned settings object adheres to the defined structure and validates the data. This is a good practice for maintaining data integrity and type safety.cognee/api/v1/cognify/cognify_v2.py (3)
15-15: LGTM: Import statement added correctlyThe import of
PipelineRunStatusfrom the appropriate module is correctly placed and necessary for the enum usage in the code.
79-83: Excellent use of enum for pipeline statusThe replacement of string literals with
PipelineRunStatusenum values is a great improvement. This change:
- Enhances code maintainability
- Reduces the risk of typos
- Provides better type safety and IDE support
The logic remains unchanged, ensuring that the functionality is preserved while improving the code quality.
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1-141: Overall assessment: Excellent improvements to code qualityThe changes in this file consistently introduce the use of
PipelineRunStatusenum, replacing string literals for pipeline status representation. This improvement enhances code maintainability, reduces the risk of errors, and provides better type safety.Key points:
- Appropriate import of
PipelineRunStatusadded.- Consistent use of the enum throughout the
run_cognify_pipelinefunction.- Functionality appears to be preserved while improving code quality.
The only suggestion is a minor improvement in error handling to include more detailed logging.
Great job on these changes!
cognee/api/client.py (1)
386-391:⚠️ Potential issueEnsure asynchronous functions are properly awaited
In the
save_settingsendpoint, thesave_llm_configfunction is correctly awaited, but there's a missingawaitbeforesave_vector_db_config.Apply this diff to fix the issue:
if new_settings.llm is not None: await save_llm_config(new_settings.llm) if new_settings.vector_db is not None: - save_vector_db_config(new_settings.vector_db) + await save_vector_db_config(new_settings.vector_db)This ensures that the asynchronous operation completes before moving on, preventing potential bugs.
Likely invalid or redundant comment.
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (6)
cognee/api/client.py (6)
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179-197: Simplify return value in get_dataset_graphWhile the change in response model to
stris correct, the function is still returning aJSONResponsewith a string content. This is unnecessary and might lead to confusion.Consider simplifying the return statement:
- return JSONResponse( - status_code = 200, - content = str(graph_url), - ) + return str(graph_url)This change would make the function's return value consistent with its declared response model.
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199-225: Improved data response structure, but inconsistent error handlingThe introduction of
DataDTOis a great improvement, providing a clear and consistent structure for data responses. However, there's an inconsistency in error handling:
- The function declares it uses
ErrorResponseDTOfor 404 responses in its signature.- But it actually returns a
JSONResponsewithErrorResponseDTOcontent.For consistency with other endpoints and to leverage FastAPI's automatic error handling, consider using
HTTPException:- if dataset is None: - return JSONResponse( - status_code = 404, - content = ErrorResponseDTO(f"Dataset ({dataset_id}) not found."), - ) + if dataset is None: + raise HTTPException( + status_code = 404, + detail = f"Dataset ({dataset_id}) not found." + )This change would make the error handling consistent across all endpoints.
228-241: Improved response model, but inconsistent error handlingThe update to the response model (
dict[str, PipelineRunStatus]) is a good improvement, providing better type clarity. However, the error handling is inconsistent with other endpoints:Consider updating the error handling to use
HTTPExceptionfor consistency:- except Exception as error: - return JSONResponse( - status_code = 409, - content = {"error": str(error)} - ) + except Exception as error: + raise HTTPException( + status_code = 409, + detail = str(error) + )This change would make the error handling consistent across all endpoints and leverage FastAPI's automatic error response generation.
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275-316: Appropriate response model change, but inconsistent error handlingThe change of the response model to
Noneis appropriate for this endpoint, as it doesn't return data on successful execution. However, the error handling is still inconsistent with other endpoints:Consider updating the error handling to use
HTTPExceptionfor consistency:- except Exception as error: - return JSONResponse( - status_code = 409, - content = {"error": str(error)} - ) + except Exception as error: + raise HTTPException( + status_code = 409, + detail = str(error) + )This change would make the error handling consistent across all endpoints and leverage FastAPI's automatic error response generation.
🧰 Tools
🪛 Ruff
353-353: Module level import not at top of file
(E402)
318-352: Improved input validation with new DTOs, but inconsistent error handlingThe introduction of
CognifyPayloadDTOandSearchPayloadDTOis a great improvement. These DTOs enhance input validation and type safety for thecognifyandsearchendpoints.However, the error handling in both endpoints is still inconsistent with the recommended approach:
For both
cognifyandsearchendpoints, consider updating the error handling to useHTTPExceptionfor consistency:- except Exception as error: - return JSONResponse( - status_code = 409, - content = {"error": str(error)} - ) + except Exception as error: + raise HTTPException( + status_code = 409, + detail = str(error) + )This change would make the error handling consistent across all endpoints and leverage FastAPI's automatic error response generation.
353-393: Improved settings handling with new DTOs and correct async usageThe changes to the settings-related code are generally positive:
- The introduction of
LLMConfigDTO,VectorDBConfigDTO, andSettingsPayloadDTOenhances input and output validation and type safety for the settings endpoints.- The
save_settingsfunction now correctly awaits asynchronous calls, preventing potential issues.These improvements make the settings management more robust and type-safe.
However, there's one minor issue to address:
The import statement on line 353 should be moved to the top of the file with the other imports to comply with PEP 8 guidelines and resolve the Ruff warning.
-from cognee.modules.settings.get_settings import LLMConfig, VectorDBConfig +# Move this import to the top of the file with other imports +from cognee.modules.settings.get_settings import LLMConfig, VectorDBConfig🧰 Tools
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353-353: Module level import not at top of file
(E402)
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📒 Files selected for processing (2)
- cognee/api/client.py (6 hunks)
- cognee/modules/settings/get_settings.py (4 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- cognee/modules/settings/get_settings.py
🧰 Additional context used
🪛 Ruff
cognee/api/client.py
353-353: Module level import not at top of file
(E402)
🔇 Additional comments (4)
cognee/api/client.py (4)
141-143: Great addition of ErrorResponseDTOThe introduction of
ErrorResponseDTOis a positive change. It standardizes the error response format across the API, which will improve consistency and make client-side error handling more straightforward.
145-162: Improved dataset response structure and error handlingThe introduction of
DatasetDTOand the updates to theget_datasetsendpoint are excellent improvements:
- The
DatasetDTOprovides a clear and consistent structure for dataset responses.- Error handling in
get_datasetsnow includes logging and raises a more specificHTTPException, which will aid in debugging and provide better feedback to API consumers.These changes enhance the API's consistency and reliability.
164-178: Enhanced delete_dataset endpointThe changes to the
delete_datasetendpoint are beneficial:
- Using
ErrorResponseDTOfor 404 responses improves consistency with the rest of the API.- The addition of
awaitfor theget_datasetcall correctly handles the asynchronous nature of the function, preventing potential issues.These modifications improve the endpoint's reliability and consistency.
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1-393: Overall improvements with some areas for further enhancementThis update to
cognee/api/client.pybrings significant improvements to the API:
- Introduction of various DTOs (ErrorResponseDTO, DatasetDTO, DataDTO, etc.) enhances type safety and input/output validation.
- Improved response models and type annotations across multiple endpoints provide better clarity and consistency.
- Correct handling of asynchronous calls in several places prevents potential issues.
These changes collectively make the API more robust, type-safe, and easier to use and maintain.
However, there are a few areas that could be further improved:
- Error handling is still inconsistent across endpoints. Consider standardizing all error responses to use
HTTPExceptionfor consistency and to leverage FastAPI's automatic error handling.- Some imports could be reorganized to comply with PEP 8 guidelines.
Addressing these minor issues would further enhance the overall quality and consistency of the API.
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🪛 Ruff
353-353: Module level import not at top of file
(E402)
Summary by CodeRabbit
Release Notes
New Features
Improvements
Bug Fixes