Update the TextOperatorComponent to handle default outputs when the true_output or false_output is not passed. If not provided, the default output will be the input text. This change improves the flexibility and usability of the component.
Refactor the Vertex class to enhance the handling of template_dicts inputs. Instead of using list comprehensions, explicit loops are now used to append the required and optional inputs. This change improves the readability and maintainability of the code.
Refactor the Vertex class to improve the handling of template_dicts inputs. Instead of using list comprehensions, the code now uses explicit loops to append the required and optional inputs. This change enhances the readability and maintainability of the code.
Fix the issue where None values were not being handled correctly in the ResultData class. This ensures that the code properly handles cases where the message is None, preventing any potential errors or unexpected behavior.
Sort the fields alphabetically and prioritize fields with DIRECT_TYPES in the Template class. This improves the organization and readability of the code, ensuring that fields with specific types are listed first.
Update the OpenAIModelComponent to handle an optional model name and temperature. This allows for more flexibility in configuring the component. The model name can now be set to None if not provided, and the temperature can be set to 0.1 if not specified. This improves the usability and customization options of the OpenAIModelComponent.
Update langflow components and constants to improve functionality, error handling, and user experience. This includes fixing rendering issues in dropdownComponent and improving value handling in tableNodeCellRender. The MonitorService now supports read-only mode in the exec_query method. The APIRequestComponent has been enhanced to parse curl commands and update the build configuration accordingly. The URLComponent now includes metadata in the returned data objects. Additionally, the SessionView and MessagesPage components have been updated to sort columns using the messagesSorter utility function, ensuring consistent column ordering. The unused Tabs component has been removed from FlowLogsModal. The CHAT_FIRST_INITIAL_TEXT and CHAT_SECOND_INITIAL_TEXT constants have been updated. Lastly, the error message in the Vertex class of base.py has been improved for building Components. These changes enhance the overall performance, functionality, and clarity of the codebase.
Update the APIRequestComponent and URLComponent to improve functionality and error handling. In APIRequestComponent, add the ability to parse curl commands and update the build configuration accordingly. In URLComponent, include metadata in the returned data objects. These changes enhance the overall performance and user experience of the components.
Update the error message in the Vertex class of base.py to provide more specific information when encountering an error while building Components. Instead of mentioning "vertex", the message now refers to "Component" to align with the terminology used in the codebase. This change improves clarity and consistency in the error messages.
Update the FileComponent in File.py to handle the case where no file path is provided. If the path is empty, raise a ValueError with the message "Please, upload a file to use this component." This change improves the error handling and user experience of the component.
Update the Message.from_data method in message.py to change the parameter name from "record" to "data". This change improves clarity and consistency in the codebase.
Update the ChatInput and ChatOutput components in ChatInput.py and ChatOutput.py to handle Message input. If the input value is an instance of the Message class, extract the text attribute and use it as the input value. This change ensures compatibility with the langflow schema and improves the flexibility of the components.
Update the Vertex class in base.py to fix a bug in the logic for checking if a parameter is a list. The current implementation only checks if the "list" key exists in the template_dict, but it should also check if the value of the "list" key is truthy. This change ensures that the correct condition is used to determine if a parameter is a list, preventing potential overwriting of params with the same name but different target_id.
Update the TextInput component in TextInput.py to handle Message input. If the input value is an instance of the Message class, extract the text attribute and use it as the input value. This change ensures compatibility with the langflow schema and improves the flexibility of the component.
Update the StrInput class in inputs.py to include a default value of an empty string. This change ensures consistency and improves the usability of the class.
Update the ChatOutput class in ChatOutput.py to use the MultilineInput class from the langflow library for text input. This change improves the usability and flexibility of the component, allowing for multiline messages to be passed as output.
Update the display name and info of the TextInput component in TextInput.py to improve clarity and consistency. The display name is changed to "Text" and the info is updated to reflect that it expects text input. This change aligns with recent updates to the langflow library and enhances the usability of the component.
Update the CustomComponent class in CustomComponent.py to use the StrInput and Output classes from the langflow library. This change ensures compatibility with the latest langflow updates and improves the clarity and consistency of the code.
Refactor the URLComponent and FileComponent classes to inherit from the langflow custom Component class instead of the deprecated CustomComponent class. This change ensures compatibility with the latest langflow library updates and improves the maintainability of the code.
📝 (chat.py): Remove commented out code related to logs in build_vertex function for better code readability
📝 (schemas.py): Change the type of logs field in ResultDataResponse class to be a dictionary with string keys and Log values for consistency
📝 (schema.py): Refactor build_logs_from_artifacts function to use a dictionary instead of defaultdict for logs variable for simplicity and consistency
Update the logs field in the ResultDataResponse schema to allow for a list of logs or a single log. This change ensures compatibility with the latest langflow library updates and improves the flexibility of the schema.
Update the field classes in the codebase to use the 'hidden' attribute instead of 'hide' for consistency and clarity. This change aligns with recent updates to the langflow library and improves the readability of the code.
Update the imports in TextInput.py to match the latest changes in the langflow library. This ensures compatibility and consistency with the rest of the codebase.
refactor: Add value attribute to ChatInput
Add a new value attribute to the ChatInput class in ChatInput.py. This allows for the pre-filling of the input field with a default value.
Update the logs field type in the ResultDataResponse schema of schemas.py to use a single Log object instead of a list of Log objects. This change aligns the schema with the actual data structure and improves consistency throughout the codebase.
Refactor the build_vertex function in chat.py to handle logs and result data response more efficiently. Instead of using a conditional statement to check the type of vertex.artifacts_raw, the code now directly assigns the logs variable based on the type. Additionally, the logs variable is only assigned to result_data_response if it is not empty. This change improves the clarity and maintainability of the code.
Update the Log class in schema.py to allow the message field to accept a list type in addition to str, dict, and StreamURL. This change enhances the flexibility of the Log class and accommodates scenarios where multiple messages need to be stored.
Update the inputs of the ChatInput class in ChatInput.py to use specific input classes such as StrInput and DropdownInput. This change improves the organization and separation of concerns in the codebase, making it easier to understand and maintain.
