Add field input classes for different data types in the `inputs.py` file. This change allows for better organization and separation of concerns in the codebase. Each input class specifies the field type and provides default values or options where applicable. This update improves the maintainability and extensibility of the codebase.
📝 (custom_component.py): Move type extraction functions to type_extraction module for better organization and separation of concerns
📝 (utils.py): Update import statements to reflect the move of type extraction functions to type_extraction module
📝 (type_extraction.py): Add functions to extract inner types and union types from generic aliases for type extraction operations
Refactor the get_component_instance function in utils.py to handle the instantiation of custom components. This change ensures compatibility with the latest version of the langflow library and improves code readability.
Handle the case where inputs are missing in custom components by setting them to None and logging a warning. This ensures compatibility with the latest version of the langflow library and improves code robustness.
Refactor the OpenAIModelComponent in OpenAIModel.py to use the BaseLanguageModel field type from langflow.field_typing and the langflow.template module. This change ensures compatibility with the latest version of the langflow library and improves code readability.
Update the LCModelComponent class in model.py to inherit from the Component class instead of the deprecated CustomComponent class. Also, update the import statement for the Component class. This change ensures compatibility with the latest version of the langflow library and improves code readability.
Refactor the instantiation of the custom component in the endpoints.py file. Replace the usage of the deprecated CustomComponent class with the Component class. This change ensures compatibility with the latest version of the langflow library and improves code readability.
Update the Input field type in the base.py file to allow None as the default value for the 'value' attribute. This change ensures consistency and improves code readability.
Refactor the ChatOutput and InterfaceVertex classes to improve message handling. In ChatOutput, remove the unnecessary storage of the message response and update the text_response method to only store the message if a session ID is present. In InterfaceVertex, update the text_output assignment to handle different scenarios and ensure the correct text is used. Also, update the message assignment to handle instances of Message and str. These changes improve the code logic and maintain consistency in message handling across the components.
Update the VertexAIEmbeddingsComponent to use the `Embeddings` field type instead of importing it from `langchain_google_vertexai`. This ensures compatibility with the latest version of the langflow library and improves code readability.
Update the langflow components to use the `Prompt` field type instead of the deprecated `type` attribute. This ensures compatibility with the latest version of the langflow library and improves code readability.
Refactor the ChatInput and ChatOutput components to store the message response in the session. This ensures that the message is properly stored and can be accessed later.
This pull request includes two changes. First, the `.gitignore` file is
updated to include `*.db-shm` and `*.db-wal` files. Second, the
`ChatInput` and `ChatOutput` classes are refactored to include a new
`return_message` parameter. This parameter allows the caller to specify
whether they want the message to be returned as a `Message` object or
just the message text. These changes improve the functionality and
maintainability of the code.
🐛 (schemas.py): Fix issue with logs field type in ResultDataResponse class
🐛 (Prompt.py): Fix issue with kwargs assignment in build_prompt method
🐛 (component.py): Fix issue with results and arguments assignment in Component class
🐛 (schema.py): Fix issue with logs field type in ResultData class
📝 (types.py): Add ResultData import and build_logs_from_artifacts function for better logging and message extraction
📝 (setup.py): Set DEFAULT_PROMPT_INTUT_TYPES for missing template keys to provide default input types
📝 (loading.py): Update build_component function to return artifacts along with build_results
📝 (schema.py): Add build_logs_from_artifacts function to generate logs from artifacts
📝 (utils.py): Update log_transaction function to use source instead of vertex and handle source result for outputs
📝 (prompt.py): Define DEFAULT_PROMPT_INTUT_TYPES constant and use it for missing template input types
* Create PythonStructuredTool
This draft involves receiving two 'Code' types as inputs and creating a structured tool.
* Delete src/backend/base/langflow/components/experimental/PythonStructuredTool
* Create PythonCodeStructuredTool.py
* feat: Update Couchbase component to handle import errors
* chore: Update package versions in pyproject.toml and poetry.lock
* refactor: Fix encoding issue in read_text_file function
* 🐛 (parse.py): fix issue where method was always set to "post" when data or data binary was provided in curl command
* refactor: Fix string formatting in MonitorService delete_messages method
* fix: Update Couchbase import instructions in CouchbaseComponent
* refactor: Fix encoding issue in read_text_file function
