Add mypy checker #346
Add mypy checker #346
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WalkthroughThis pull request introduces several changes across multiple files, focusing on enhancing code quality, improving error handling, and refining type annotations. Notably, a new command for formatting checks is added to the pre-commit hook. The test suite for resolving Python dependencies is restructured for specific checks, while various functions across the codebase receive updates to their type annotations and error handling mechanisms. Additionally, the Changes
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Actionable comments posted: 12
🧹 Outside diff range and nitpick comments (24)
templates/components/vectordbs/python/milvus/vectordb.py (2)
19-19: Approve change with suggestions for further improvementThe modification to provide a default value for
EMBEDDING_DIMis a good improvement in robustness. It prevents potentialValueErrors when the environment variable is not set.However, consider the following enhancements for even better user experience and robustness:
- Add a warning log when falling back to the default value, to notify users that they haven't set
EMBEDDING_DIM.- Consider adding a validation check to ensure the dimension is within an expected range for your use case.
Here's a suggested implementation incorporating these improvements:
import logging # ... (rest of the imports) def get_vector_store(): # ... (previous code) embedding_dim = os.getenv("EMBEDDING_DIM") if embedding_dim is None: logging.warning("EMBEDDING_DIM not set. Using default value of 768.") embedding_dim = 768 else: embedding_dim = int(embedding_dim) # Optional: Add validation if not (100 <= embedding_dim <= 2000): # adjust range as needed raise ValueError(f"EMBEDDING_DIM {embedding_dim} is outside the expected range (100-2000)") store = MilvusVectorStore( # ... (other parameters) dim=embedding_dim, ) return storeThis implementation provides more visibility into the use of default values and adds a safeguard against unexpected dimension values.
Consistent Handling of Environment Variables
The verification confirms that environment variables across the codebase are handled inconsistently. Implementing a uniform approach, as suggested in the review comment, will enhance code robustness and maintainability.
🔗 Analysis chain
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1-21: Suggest consistent handling of environment variablesWhile the function correctly handles critical environment variables and the recent change improves robustness for
EMBEDDING_DIM, there's an opportunity to make the handling of all environment variables more consistent. This would improve overall code quality and prevent potential issues.Consider refactoring the function to handle all environment variables uniformly. Here's a suggested approach:
import os import logging from typing import Optional from llama_index.vector_stores.milvus import MilvusVectorStore def get_env_var(name: str, default: Optional[str] = None, required: bool = False) -> Optional[str]: value = os.getenv(name, default) if required and value is None: raise ValueError(f"Environment variable {name} is required but not set.") return value def get_vector_store() -> MilvusVectorStore: address = get_env_var("MILVUS_ADDRESS", required=True) collection = get_env_var("MILVUS_COLLECTION", required=True) username = get_env_var("MILVUS_USERNAME") password = get_env_var("MILVUS_PASSWORD") embedding_dim_str = get_env_var("EMBEDDING_DIM", default="768") try: embedding_dim = int(embedding_dim_str) if not (100 <= embedding_dim <= 2000): # adjust range as needed raise ValueError except ValueError: logging.warning(f"Invalid EMBEDDING_DIM '{embedding_dim_str}'. Using default value of 768.") embedding_dim = 768 return MilvusVectorStore( uri=address, user=username, password=password, collection_name=collection, dim=embedding_dim, )This refactoring:
- Introduces a helper function
get_env_varfor consistent environment variable handling.- Treats all variables consistently, with clear indication of which are required.
- Improves error handling and logging for the
EMBEDDING_DIMvariable.- Makes the function more readable and maintainable.
To ensure this refactoring doesn't introduce any regressions, please run the following verification script:
This script will help identify any other places in the codebase where these environment variables are used, ensuring that the proposed changes are consistent with the rest of the project.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the usage of environment variables in the codebase # Test: Search for direct os.getenv calls that might need updating echo "Searching for direct os.getenv calls:" rg --type python 'os\.getenv\(' --glob '!templates/components/vectordbs/python/milvus/vectordb.py' # Test: Check for other uses of the environment variables to ensure consistency echo "Checking for other uses of MILVUS_ environment variables:" rg --type python 'MILVUS_' --glob '!templates/components/vectordbs/python/milvus/vectordb.py' echo "Checking for other uses of EMBEDDING_DIM:" rg --type python 'EMBEDDING_DIM' --glob '!templates/components/vectordbs/python/milvus/vectordb.py'Length of output: 690
Script:
#!/bin/bash # Description: Verify the usage of environment variables in the codebase # Test: Search for direct os.getenv calls that might need updating echo "Searching for direct os.getenv calls:" rg --type py 'os\.getenv\(' --glob '!templates/components/vectordbs/python/milvus/vectordb.py' # Test: Check for other uses of the MILVUS_ environment variables to ensure consistency echo "Checking for other uses of MILVUS_ environment variables:" rg --type py 'MILVUS_' --glob '!templates/components/vectordbs/python/milvus/vectordb.py' # Test: Check for other uses of EMBEDDING_DIM echo "Checking for other uses of EMBEDDING_DIM:" rg --type py 'EMBEDDING_DIM' --glob '!templates/components/vectordbs/python/milvus/vectordb.py'Length of output: 11239
templates/components/vectordbs/python/astra/vectordb.py (1)
18-18: Approved: Good error handling improvementThe change enhances the robustness of the
get_vector_storefunction by providing a default value forEMBEDDING_DIM. This prevents potentialValueErrors when the environment variable is not set, which aligns well with the PR's objective of improving error handling.For improved clarity and maintainability, consider extracting the default value to a named constant at the module level. For example:
DEFAULT_EMBEDDING_DIM = 768 # ... in the function ... embedding_dimension=int(os.getenv("EMBEDDING_DIM", DEFAULT_EMBEDDING_DIM)),This makes it easier to update the default value in the future if needed and provides context for why this specific number was chosen.
templates/components/loaders/python/db.py (1)
15-21: Approve error handling for DatabaseReader importThe addition of error handling for the DatabaseReader import is a good improvement. It provides a clear error message and maintains the original exception.
Consider adding a type hint for the
DatabaseReaderimport to improve code readability:from llama_index.readers.database import DatabaseReader as DatabaseReaderTypeThen use
DatabaseReaderTypein the function body.templates/components/loaders/python/web.py (1)
13-14: LGTM: Improved type annotations in WebLoaderConfig class.The changes to the
WebLoaderConfigclass are good improvements:
- Making
driver_argumentsoptional with a default empty list improves flexibility.- Using
Listinstead oflistforurlsis more consistent with type hinting best practices.These changes align well with the PR objective of adding mypy checker and improving type checking.
Consider adding a type annotation to the
get_web_documentsfunction for consistency:def get_web_documents(config: WebLoaderConfig) -> List[Any]: # or a more specific return typeThis would further improve type checking and code readability.
templates/types/streaming/fastapi/pyproject.toml (1)
27-39: Approve mypy configuration with suggestions for improvementThe addition of a mypy configuration is a positive step towards better type checking. However, some settings might be too permissive:
- Consider enabling
warn_unused_ignores = trueto catch unnecessary type ignore comments.- The
ignore_missing_imports = truesetting might hide real import issues. Consider using stub files for third-party libraries instead.follow_imports = "silent"might suppress important error messages from imported modules.implicit_optional = trueandstrict_optional = falsecould allow None to be used where it's not expected. Consider making these stricter.- The
disable_error_codelist includes important checks. Consider removing or narrowing these disabled checks.Also, verify if Pydantic is used in the project, as the
plugins = "pydantic.mypy"setting is included.These suggestions aim to make the type checking stricter and catch more potential issues.
templates/components/loaders/python/__init__.py (1)
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19-38: LGTM: Return type annotation added correctly.The return type annotation
List[Document]accurately reflects the function's behavior of aggregating and returning a list of documents.Consider adding a type annotation for the
documentvariable in each case of the match statement. This would improve type checking and make the code more self-documenting. For example:document: List[Document] = get_file_documents(FileLoaderConfig(**loader_config))This change would be consistent with the function's return type and provide more precise type information throughout the function.
templates/components/engines/python/agent/engine.py (2)
30-31: LGTM: Improved handling of configured tools with type annotation.The introduction of the
configured_toolsvariable with theList[BaseTool]type annotation enhances type safety. Usingextendinstead of+=is a good practice for list concatenation.Consider adding a comment explaining the purpose of
ToolFactory.from_env()for better code documentation. For example:# Load additional tools from environment configuration configured_tools: List[BaseTool] = ToolFactory.from_env()
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14-41: Overall improvements in type safety and code quality.The changes to the
get_chat_enginefunction enhance type safety and code quality without altering its core functionality. The addition of type annotations and the improved handling of configured tools align well with the PR objective of adding a mypy checker. These modifications will facilitate better static type checking and potentially catch type-related errors earlier in the development process.Consider adding type annotations to the function parameters and return value to further improve type safety and documentation. For example:
def get_chat_engine( filters: Optional[Dict[str, Any]] = None, params: Optional[Dict[str, Any]] = None, event_handlers: Optional[List[BaseEventHandler]] = None, **kwargs: Any ) -> AgentRunner: # ... function body ...This would provide a more complete type-safe interface for the function.
templates/components/settings/python/llmhub.py (2)
57-61: Improved error handling for OpenAILike import.The addition of the try-except block for importing
OpenAILikeis a good improvement:
- It provides better error handling and user feedback.
- The error message is informative, suggesting the potential fix.
- Logging the error before raising the exception aids in debugging.
Consider adding more context to the error message:
logger.error("Failed to import OpenAILike. Make sure llama_index is installed and up to date.")This additional information might help users troubleshoot version-related issues as well.
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1-61: Consider adding more type hints for improved code quality.While the code generally has good type annotations, there are a few areas where additional type hints could be beneficial:
- In
llm_config_from_env()andembedding_config_from_env(), consider adding type hints to local variables.- Add a return type annotation to
init_llmhub(), even if it'sNone.Here's an example of how you could improve type hinting in
llm_config_from_env():def llm_config_from_env() -> Dict[str, Union[str, float, int, None]]: from llama_index.core.constants import DEFAULT_TEMPERATURE model: str = os.getenv("MODEL", DEFAULT_MODEL) temperature: str = os.getenv("LLM_TEMPERATURE", str(DEFAULT_TEMPERATURE)) max_tokens: Optional[str] = os.getenv("LLM_MAX_TOKENS") api_key: Optional[str] = os.getenv("T_SYSTEMS_LLMHUB_API_KEY") api_base: Optional[str] = os.getenv("T_SYSTEMS_LLMHUB_BASE_URL") config: Dict[str, Union[str, float, int, None]] = { "model": model, "api_key": api_key, "api_base": api_base, "temperature": float(temperature), "max_tokens": int(max_tokens) if max_tokens is not None else None, } return configSimilar improvements can be made to
embedding_config_from_env(). Forinit_llmhub(), you can add a return type:def init_llmhub() -> None: # ... existing code ...These changes will enhance code readability and help catch potential type-related issues earlier in the development process.
templates/types/streaming/fastapi/app/engine/generate.py (1)
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1-85: Suggestion: Add type annotations to functions for better type checking.While the changes made are good, to fully leverage the mypy checker being added, consider adding type annotations to function parameters and return values throughout the file. This would further enhance type safety and align with the PR objective.
For example, the
generate_datasourcefunction could be annotated like this:def generate_datasource() -> None: ...Similarly, other functions like
get_doc_store,run_pipeline, andpersist_storagecould benefit from type annotations.Would you like assistance in adding type annotations to these functions?
templates/types/streaming/fastapi/app/api/routers/chat.py (1)
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23-45: Enhance error handling and logging in thechatendpointWhile the current implementation catches and logs exceptions, there's room for improvement in error handling and logging to aid in debugging and maintenance.
Consider the following enhancements:
- Log input parameters (excluding sensitive data) at the beginning of the function to aid in debugging.
- Use more specific exception types instead of catching all exceptions.
- Include more context in the error message returned to the client.
Here's a suggested implementation:
@r.post("") async def chat( request: Request, data: ChatData, background_tasks: BackgroundTasks, ): logger.info(f"Received chat request with {len(data.messages)} messages") try: last_message_content = data.get_last_message_content() messages = data.get_history_messages() doc_ids = data.get_chat_document_ids() filters = generate_filters(doc_ids) params = data.data or {} logger.info( f"Creating chat engine with filters: {str(filters)} and {len(params)} additional parameters", ) event_handler = EventCallbackHandler() chat_engine = get_chat_engine( filters=filters, params=params, event_handlers=[event_handler] ) response = await chat_engine.astream_chat(last_message_content, messages) process_response_nodes(response.source_nodes, background_tasks) return VercelStreamResponse(request, event_handler, response, data) except ValueError as ve: logger.error(f"Invalid input: {str(ve)}", exc_info=True) raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail=f"Invalid input: {str(ve)}", ) from ve except Exception as e: logger.exception("Unexpected error in chat engine", exc_info=True) raise HTTPException( status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="An unexpected error occurred while processing your request. Please try again later.", ) from eThis implementation provides more detailed logging and distinguishes between input validation errors and unexpected exceptions, improving the ability to diagnose and respond to issues.
templates/components/engines/python/agent/tools/__init__.py (2)
47-57: LGTM: Method signature and docstring improvementsThe return type of
from_envhas been updated to be more specific usingUnion[Dict[str, List[FunctionTool]], List[FunctionTool]]. The docstring has been improved to reflect this change and provide more detailed information about the method's behavior.Consider adding a brief explanation of what this method does at the beginning of the docstring. For example:
""" Load tools from the configured file based on the environment. Args: map_result: If True, return a map of tool names to their corresponding tools. Returns: A dictionary of tool names to lists of FunctionTools if map_result is True, otherwise a list of FunctionTools. """
68-74: LGTM with suggestions: Improved readability and type handlingThe
load_toolscall has been split across multiple lines, improving readability. The addition of# type: ignorecomments addresses potential type checking issues.To avoid using
# type: ignorecomments, consider using type casting or creating a custom type fortools. For example:from typing import Dict, List, Union, TypeVar T = TypeVar('T', Dict[str, List[FunctionTool]], List[FunctionTool]) class ToolFactory: # ... @staticmethod def from_env( map_result: bool = False, ) -> Union[Dict[str, List[FunctionTool]], List[FunctionTool]]: tools: T = {} if map_result else [] # type: ignore # ... if map_result: tools = cast(Dict[str, List[FunctionTool]], tools) tools[tool_name] = loaded_tools else: tools = cast(List[FunctionTool], tools) tools.extend(loaded_tools) return toolsThis approach provides better type safety and eliminates the need for
# type: ignorecomments.templates/components/engines/python/agent/tools/artifact.py (1)
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66-95: Consider refactoring theartifactmethod for improved readability and error handling.While the current implementation works, there are a few areas where it could be improved:
Error Handling: The current try-except block catches all exceptions. Consider catching specific exceptions and providing more detailed error messages.
Type Annotations: Add type annotations to the
responsevariable and the return value of the method.Logging: Consider adding more detailed logging throughout the method to aid in debugging.
Here's a suggested refactoring of the
artifactmethod:from llama_index.core.base.llms.types import ChatResponse import json def artifact(self, query: str, old_code: Optional[str] = None) -> Dict[str, Any]: """Generate a code artifact based on the input.""" try: user_message = f"{query}\n\nThe existing code is: \n```\n{old_code}\n```" if old_code else query messages: List[ChatMessage] = [ ChatMessage(role="system", content=CODE_GENERATION_PROMPT), ChatMessage(role="user", content=user_message), ] sllm = Settings.llm.as_structured_llm(output_cls=CodeArtifact) response: ChatResponse = sllm.chat(messages) data: CodeArtifact = response.raw logger.info(f"Successfully generated artifact: {data.title}") return data.model_dump() except AttributeError as e: logger.error(f"Invalid Settings configuration: {str(e)}") raise ValueError("Invalid Settings configuration") from e except json.JSONDecodeError as e: logger.error(f"Failed to parse response: {str(e)}") raise ValueError("Invalid response format") from e except Exception as e: logger.error(f"Unexpected error while generating artifact: {str(e)}") raise RuntimeError("Failed to generate artifact") from eThis refactored version:
- Adds more specific exception handling.
- Includes type annotations for
responseand the return value.- Adds more detailed logging.
- Simplifies the user message construction.
Please consider implementing these changes to improve the overall quality and maintainability of the code.
templates/types/streaming/fastapi/app/api/routers/events.py (2)
34-35: Improved error handling inget_tool_messagemethod.The addition of null checks for
self.payloadandtoolenhances the robustness of the method by preventing potentialNoneTypeattribute access errors. This is a good practice for defensive programming.Consider combining the two checks to reduce the number of early returns:
if self.payload is None or self.payload.get("tool") is None: return NoneThis would make the code slightly more concise while maintaining the same functionality.
Also applies to: 39-40
125-125: LGTM: Enhancedon_event_startmethod with parent_id and return value.The addition of the
parent_idparameter and the return ofevent_idimprove the functionality and usability of theon_event_startmethod. These changes allow for better event tracking and relationship management.Consider adding a docstring to the
on_event_startmethod to explain the purpose of theparent_idparameter and the return value. This would improve the method's documentation and make it easier for other developers to understand and use the method correctly.Also applies to: 131-131
templates/types/streaming/fastapi/app/api/routers/models.py (2)
65-81: LGTM: Improved type annotations and error handling.The changes in the
Annotationclass improve type safety and error handling:
- Using
Unioninstead of|for type unions enhances compatibility.- The
to_contentmethod now includes type checking and better error handling.Consider adding a type annotation for the
csv_filesvariable on line 71 for consistency:csv_files: List[File] = [file for file in self.data.files if file.filetype == "csv"]
254-254: LGTM: Improved return type annotation inget_url_from_metadata.The change from
strtoOptional[str]as the return type is accurate and consistent with the method's logic. This improves type safety and helps prevent potential issues.Consider adding type annotations to the local variables within the method for consistency. For example:
url_prefix: Optional[str] = os.getenv("FILESERVER_URL_PREFIX") file_name: Optional[str] = metadata.get("file_name")helpers/python.ts (2)
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201-217: Good addition of 'groq' provider dependencies with version constraints.The addition of specific dependencies for the 'groq' provider, including the Python version constraint, is a good practice to ensure compatibility. However, consider adding a comment explaining why the Python version is constrained to less than 3.13, as it might not be immediately clear to other developers.
+ # Fastembed==0.2.0 does not support python3.13 at the moment dependencies.push({ name: "python", version: "^3.11,<3.13", });This will help maintain the code's clarity and make it easier for future updates.
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218-234: Consistent implementation for 'anthropic' provider dependencies.The changes for the 'anthropic' provider are consistent with those made for the 'groq' provider, which is excellent for maintaining code uniformity. As suggested for the 'groq' case, consider adding a comment explaining the Python version constraint:
+ # Fastembed==0.2.0 does not support python3.13 at the moment dependencies.push({ name: "python", version: "^3.11,<3.13", });This will enhance code readability and make future maintenance easier.
e2e/python/resolve_dependencies.spec.ts (2)
18-18: Address the TODO comment for supporting other templatesThe code includes a TODO comment indicating that support for other templates should be added. Please ensure this is tracked or addressed to enhance the test coverage for other templates.
Would you like assistance in implementing support for other templates or opening a GitHub issue to track this task?
233-234: Remove redundant assertionThe assertion
expect(true).toBeTruthy();is unnecessary because if the code reaches this point without throwing an error, the test has already passed. Removing this line will clean up the code without affecting functionality.Consider removing the redundant assertion:
-// If we reach this point without throwing an error, the test passes -expect(true).toBeTruthy();
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📒 Files selected for processing (26)
- .husky/pre-commit (1 hunks)
- e2e/python/resolve_dependencies.spec.ts (3 hunks)
- helpers/python.ts (1 hunks)
- templates/components/engines/python/agent/engine.py (2 hunks)
- templates/components/engines/python/agent/tools/init.py (3 hunks)
- templates/components/engines/python/agent/tools/artifact.py (1 hunks)
- templates/components/engines/python/agent/tools/duckduckgo.py (2 hunks)
- templates/components/engines/python/chat/init.py (1 hunks)
- templates/components/engines/python/chat/engine.py (1 hunks)
- templates/components/loaders/python/init.py (1 hunks)
- templates/components/loaders/python/db.py (2 hunks)
- templates/components/loaders/python/web.py (2 hunks)
- templates/components/settings/python/llmhub.py (2 hunks)
- templates/components/settings/python/settings.py (3 hunks)
- templates/components/vectordbs/python/astra/vectordb.py (1 hunks)
- templates/components/vectordbs/python/chroma/vectordb.py (2 hunks)
- templates/components/vectordbs/python/milvus/vectordb.py (2 hunks)
- templates/components/vectordbs/python/none/index.py (1 hunks)
- templates/types/extractor/fastapi/app/engine/generate.py (2 hunks)
- templates/types/extractor/fastapi/app/engine/index.py (1 hunks)
- templates/types/streaming/fastapi/app/api/routers/chat.py (1 hunks)
- templates/types/streaming/fastapi/app/api/routers/events.py (5 hunks)
- templates/types/streaming/fastapi/app/api/routers/models.py (4 hunks)
- templates/types/streaming/fastapi/app/engine/init.py (1 hunks)
- templates/types/streaming/fastapi/app/engine/generate.py (2 hunks)
- templates/types/streaming/fastapi/pyproject.toml (1 hunks)
✅ Files skipped from review due to trivial changes (3)
- templates/components/engines/python/chat/init.py
- templates/components/engines/python/chat/engine.py
- templates/types/streaming/fastapi/app/engine/init.py
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templates/components/engines/python/agent/engine.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/engines/python/agent/tools/__init__.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/engines/python/agent/tools/artifact.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/engines/python/agent/tools/duckduckgo.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/loaders/python/__init__.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/loaders/python/db.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/vectordbs/python/astra/vectordb.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/types/extractor/fastapi/app/engine/generate.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/types/streaming/fastapi/app/api/routers/chat.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/types/streaming/fastapi/app/api/routers/events.py (1)
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templates/components/settings/python/settings.py
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🔇 Additional comments (33)
templates/components/vectordbs/python/chroma/vectordb.py (1)
22-22: Consider the implications of passing port as a stringThe change from
int(os.getenv("CHROMA_PORT"))toos.getenv("CHROMA_PORT", "8001")has several implications:
- It provides a default value of "8001", improving robustness when the environment variable is not set.
- It removes the explicit integer conversion, which changes the type of the port parameter from int to str.
While this change increases flexibility and removes a potential ValueError from invalid integer conversions, it may have unintended consequences:
- If ChromaVectorStore expects an integer for the port, this could lead to type-related issues.
- Configuration errors (non-numeric ports) that were previously caught by the int() conversion will now be passed through, potentially causing issues later.
To ensure this change doesn't introduce issues, please verify:
- ChromaVectorStore can handle string port values correctly.
- There's no loss of error checking for invalid port values.
You can use the following script to check the ChromaVectorStore implementation:
If ChromaVectorStore expects an integer, consider keeping the int() conversion:
port=int(os.getenv("CHROMA_PORT", "8001")),This maintains the default value while ensuring type consistency and error checking.
templates/components/loaders/python/web.py (1)
1-1: LGTM: Import statement updated for better type hinting.The addition of
Optionalfrom thetypingmodule is a good improvement. It allows for more precise type annotations, which is in line with the PR objective of adding mypy checker for enhanced type checking.templates/types/extractor/fastapi/app/engine/index.py (1)
19-19: Excellent type annotation improvements!The updated function signature enhances type clarity and aligns well with the PR objective of adding mypy checker:
- Using
Optional[IndexConfig]is more explicit and mypy-friendly.- Adding the return type annotation
-> VectorStoreIndexclearly specifies the function's output.These changes will facilitate more accurate type checking by mypy while maintaining the function's existing behavior.
templates/types/streaming/fastapi/pyproject.toml (1)
20-21: LGTM: mypy added as a development dependencyThe addition of mypy as a development dependency is consistent with the PR objective of adding a mypy checker. The version specification "^1.8.0" allows for compatible updates, which is a good practice for maintaining up-to-date dependencies.
templates/components/loaders/python/__init__.py (3)
2-2: LGTM: Import statements are correctly updated.The new imports for typing annotations and
Documentfromllama_index.coreare appropriate for the added type hints. The type ignore comment foryamlis also acceptable if there are known issues with its type stubs.Also applies to: 4-4, 8-8
13-17: LGTM: Appropriate return type annotation added.The return type annotation
Dict[str, Any]accurately reflects the function's behavior of loading and returning YAML content as a dictionary.
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1-38: Summary: Type annotations successfully added.The changes in this file successfully introduce type annotations to the
load_configsandget_documentsfunctions, as well as add necessary imports. These modifications align well with the PR objective of adding a mypy checker and will enhance the code's type safety and readability.The added type annotations will facilitate static type checking with mypy, potentially catching type-related errors early in the development process. This improvement in code quality is a positive step towards more robust and maintainable code.
templates/components/vectordbs/python/none/index.py (2)
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1-52: Overall implementation looks good.The file structure, use of environment variables for configuration, and caching implementation for
get_storage_contextare well-designed. The type annotations are consistent throughout the file, which aligns with the PR objective of adding mypy checker support.
6-6: Consider addressing the type ignore comment.The addition of
# type: ignoreto the import statement suggests that there might be type-related issues with thecachetoolslibrary. While this change allows the code to pass mypy checks, it's worth considering if there's a more robust solution.To better understand the nature of the type-related issue, let's run a verification script:
Depending on the results, consider the following options:
- If type stubs are available for cachetools, install them to resolve the issue without using
# type: ignore.- If the issue is due to an outdated version of cachetools, consider upgrading to a version with better type support.
- If the issue persists and is known, add a comment explaining why the type ignore is necessary.
templates/components/engines/python/agent/engine.py (2)
2-2: LGTM: Import statements for type hinting added.The addition of
ListfromtypingandBaseToolfromllama_index.core.toolsis appropriate for the new type annotations in the code. This change supports the PR objective of adding a mypy checker by enabling proper type hinting.Also applies to: 9-9
16-16: LGTM: Type annotation added to tools variable.The addition of the type annotation
List[BaseTool]to thetoolsvariable improves type safety and code readability. This change is in line with the PR objective of adding a mypy checker and will help catch type-related errors early in the development process.templates/components/settings/python/llmhub.py (1)
1-1: LGTM: Improved imports and added logging.The changes to the import statements and the addition of logging are good improvements:
- Adding
loggingimport enhances error tracking capabilities.- Import statements are now properly ordered according to PEP 8 style guide.
- Logger initialization is correctly implemented.
These changes will contribute to better code organization and easier debugging.
Also applies to: 3-8
templates/components/engines/python/agent/tools/duckduckgo.py (2)
26-32: Improved code clarity and directnessThe changes to the
duckduckgo_searchfunction enhance readability by directly passing keyword arguments toddg.text(). This approach is more Pythonic and aligns with the principle of explicitness. The functionality remains the same, but the code is now more straightforward.
56-62: Consistent improvement in code clarityThe changes to
duckduckgo_image_searchmirror those made toduckduckgo_search, maintaining consistency across the file. By directly passing keyword arguments toddg.images(), the code becomes more readable and explicit. This change aligns well with Python best practices and improves overall code quality.templates/types/extractor/fastapi/app/engine/generate.py (3)
9-9: LGTM: New import statement is correctly placed and necessary.The addition of
DocstoreStrategyimport is consistent with the file's coding style and is required for the changes in therun_pipelinefunction.
44-44: Good improvement: Using enum instead of string literal.The change from
"upserts_and_delete"toDocstoreStrategy.UPSERTS_AND_DELETEenhances type safety and reduces the risk of typos. It also improves code maintainability by providing better IDE support for code completion and refactoring.
44-44: Query: Why is# type: ignorenecessary here?The addition of
# type: ignoresuggests that there might be a type checking issue. Could you please explain why this comment is needed? If there's an underlying type mismatch, it would be better to address it directly rather than suppressing the type checker.To investigate this further, let's check the type hints for the
IngestionPipelineclass:This will help us understand if there's a mismatch between the expected type and the
DocstoreStrategyenum.templates/types/streaming/fastapi/app/engine/generate.py (2)
9-17: LGTM: Import changes enhance type safety and readability.The addition of
DocstoreStrategyimport and the reordering of import statements improve type safety and code organization. These changes align well with the PR objective of adding a mypy checker.
44-44: Approve enum usage, but question type ignore comment.The use of
DocstoreStrategy.UPSERTS_AND_DELETEinstead of a string literal is a good improvement for type safety. However, the addition of# type: ignoreseems to contradict the PR objective of adding mypy checking.Could you explain why the
# type: ignorecomment is necessary here? If it's due to a mypy error, we should investigate how to resolve it without suppressing the type check. Let's run a mypy check on this file:If mypy is not installed or configured, we might need to add it to the project's development dependencies.
templates/components/engines/python/agent/tools/__init__.py (3)
3-5: LGTM: Import changes look goodThe new import from
typingis necessary for the updated type annotations in the file. The# type: ignorecomment for theyamlimport is appropriate if there are known issues with type checking for this library.
21-22: LGTM: Method signature update improves type hintingThe return type of
load_toolshas been updated fromlist[FunctionTool]toList[FunctionTool]. This change is consistent with the new import fromtypingand provides better type hinting.
59-61: LGTM: Improved type annotation fortoolsvariableThe
toolsvariable now has a proper type annotation that matches the method's return type. This change improves type safety and code readability while maintaining the same initialization logic.templates/components/engines/python/agent/tools/artifact.py (1)
90-90:⚠️ Potential issueConsider addressing the underlying type issue instead of using a type ignore comment.
The addition of
# type: ignoresuggests there's a type-related issue that mypy is detecting. While this temporarily resolves the mypy error, it's generally better to address the underlying issue rather than suppressing it.To better understand and potentially resolve this issue, please run the following script:
This script will help us understand:
- The specific mypy error being suppressed.
- The definition of the
Settingsclass andas_structured_llmmethod.- Any existing type annotations for
Settings.llm.With this information, we can provide more specific guidance on how to properly type-annotate this code instead of using a type ignore comment.
templates/types/streaming/fastapi/app/api/routers/events.py (3)
2-2: LGTM: Import statements updated appropriately.The addition of
jsonandAsyncGeneratorimports aligns with the new functionality in the code. These changes improve the module's capabilities for JSON handling and asynchronous operations.Also applies to: 4-4
57-58: LGTM: Improved error handling inget_agent_tool_responsemethod.The addition of a null check for
self.payloadenhances the robustness of the method by preventing potentialNoneTypeattribute access errors. This is consistent with the improvements made in theget_tool_messagemethod and follows good defensive programming practices.
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1-162: LGTM: Overall improvements to error handling and type annotations.The changes made to this file consistently improve error handling and maintain good type annotation practices. The modifications enhance the robustness of the event handling logic while preserving the existing structure and style of the code.
The enhancements to null checks and the addition of the
parent_idparameter in theEventCallbackHandlerclass contribute to a more reliable and flexible event handling system. Great job on maintaining code quality and improving functionality!templates/types/streaming/fastapi/app/api/routers/models.py (3)
3-3: LGTM: Import statement updated correctly.The addition of
Unionto the import statement is consistent with the changes made in the file. This improves compatibility with older Python versions and aligns with the type annotation updates in the code.
224-226: LGTM: Enhanced type checking inget_chat_document_ids.The additional type checking for
annotation.dataimproves type safety and prevents potential runtime errors. This change ensures that thefilesattribute is only accessed whenannotation.datais an instance ofAnnotationFileData.
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1-324: Overall LGTM: Improved type annotations and error handling.The changes in this file consistently improve type annotations and error handling throughout the code. These improvements align well with the PR objective of adding mypy checker and will help catch potential type-related issues earlier in the development process. The code is now more robust and type-safe.
Key improvements:
- Use of
Unionfor complex type annotations.- More accurate return type annotations (e.g.,
Optional[str]).- Enhanced type checking in methods like
get_chat_document_ids.- Consistent use of
Optionalinstead of| None.These changes will make the codebase more maintainable and less prone to type-related bugs.
helpers/python.ts (2)
126-128: Improved PostgreSQL dependency.The change from "psycopg2" to "psycopg2-binary" is a good improvement. This pre-compiled binary version is easier to install and doesn't require a compiler, which can simplify the setup process for many users.
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1-590: Overall improvements in dependency management and provider support.The changes made to this file significantly enhance the dependency management for various providers, particularly for PostgreSQL, 'groq', and 'anthropic'. The use of specific versions and version constraints helps ensure compatibility and prevents potential issues with newer, incompatible versions.
The consistency in implementing these changes across different providers is commendable. It makes the code more maintainable and easier to update in the future.
The only suggestion for improvement is to add comments explaining the rationale behind certain version constraints, which will aid in future maintenance and updates.
Great job on these enhancements!
templates/components/settings/python/settings.py (2)
70-73: Ensure default embedding model is valid ininit_openaiThe default embedding model is set to
"text-embedding-3-small". Verify that this model name is valid and supported by OpenAI's API. Using an incorrect model name could lead to runtime errors.Would you like to confirm that
"text-embedding-3-small"is a valid model name? If unsure, consider updating it to a known valid model like"text-embedding-ada-002".
63-67: Ensure default LLM model is valid ininit_openaiThe default LLM model is set to
"gpt-4o-mini". Please verify that this model is available and correctly specified. An invalid model name could result in runtime errors.Would you like to confirm that
"gpt-4o-mini"is a valid OpenAI model? If it's a custom or lesser-known model, ensure it's accessible in your environment or update the default to a commonly used model like"gpt-3.5-turbo".
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templates/components/settings/python/settings.py (1)
Pattern
templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
🪛 Ruff
templates/components/settings/python/settings.py
40-42: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
83-85: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
120-122: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
145-147: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
158-160: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
180-182: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
🔇 Additional comments (9)
templates/components/settings/python/settings.py (9)
36-42: LGTM!The exception handling and import statements for
init_ollamaare appropriately implemented.🧰 Tools
🪛 Ruff
40-42: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
64-67: Verify default LLM model name ininit_openaiThe default model name for the LLM is set to
"gpt-4o-mini"(line 64). Please verify that this is the correct model name and corresponds to a valid OpenAI model, as it may not be a standard model provided by OpenAI.
71-73: Verify default embedding model name ininit_openaiThe default embedding model name is set to
"text-embedding-3-small"(line 71). Please verify that this is the intended model and corresponds to a valid OpenAI embedding model.
79-85: LGTM!The exception handling for missing Azure OpenAI dependencies is correctly implemented in
init_azure_openai.🧰 Tools
🪛 Ruff
83-85: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
117-122: LGTM!The exception handling for the FastEmbed import is properly implemented in
init_fastembed.🧰 Tools
🪛 Ruff
120-122: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
131-134: LGTM!The check for the
EMBEDDING_MODELenvironment variable ensures that it is set before proceeding.
142-147: LGTM!Exception handling in
init_groqfor missing dependencies is correctly implemented.🧰 Tools
🪛 Ruff
145-147: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
155-160: LGTM!The exception handling for importing Anthropic dependencies in
init_anthropicis appropriate.🧰 Tools
🪛 Ruff
158-160: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
176-182: LGTM!The import statements and exception handling for
init_geminiare correctly structured.🧰 Tools
🪛 Ruff
180-182: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
Summary by CodeRabbit
New Features
Bug Fixes
Documentation
Chores
mypyfor type-checking capabilities in the project.