🔀 refactor(types.py): add langchain_types_dict as a separate variable to improve code readability and maintainability
The import statement in `endpoints.py` has been updated to import `langchain_types_dict` instead of `build_langchain_types_dict` for consistency with the variable name. This change improves code readability and maintainability.
In `types.py`, a new variable `langchain_types_dict` has been added as a separate variable to store the result of `build_langchain_types_dict()`. This change improves code readability and makes it easier to understand the purpose of the variable.
🔧 chore(settings.py): add retrievers attribute to Settings class
The config.yaml file now includes a documentation link for the MultiQueryRetriever in the retrievers section. This link provides additional information on how to use the MultiQueryRetriever. In the settings.py file, the Settings class now includes a retrievers attribute to store retriever-related settings. This allows for easier management and configuration of retrievers in the application.
💄 style(NodeModal): remove unused import and variable to clean up code
The import and variable name for `nodeIconsLucide` has been updated to improve code readability. The unused import and variable `nodeIcons` and `toNormalCase` have been removed to clean up the code.
🎨 style(utils.ts): reorganize nodeColors and nodeNames objects to improve readability and maintainability
The changes in this commit remove unused imports and icons from the `utils.ts` file, which helps improve code cleanliness and reduces the bundle size. Additionally, the `nodeColors` and `nodeNames` objects have been reorganized to improve readability and maintainability.
💡 refactor(base.py): The field formatting logic in the FrontendNode class has been refactored into a separate class called FieldFormatters. This improves code organization and separation of concerns, making it easier to maintain and extend the field formatting functionality in the future.
The trailing whitespace has been removed for consistency and readability. The unused import of `DEFAULT_CONNECTION_STRING` from `langchain.memory.chat_message_histories.postgres` has been removed. The `PostgresChatMessageHistoryFrontendNode` now has a default value for the `connection_string` field, which is set to `DEFAULT_CONNECTION_STRING`. This ensures that the field has a default value when creating instances of the class.
🔧 chore(memories.py): remove trailing whitespace and unused import
🔧 refactor(field_formatters.py): refactor field formatters for template frontend_node
The commit adds a new file `field_formatters.py` to the `frontend_node/formatter` directory in the `langflow/template` backend. This file contains multiple field formatters for the template frontend_node. The formatters handle various formatting tasks such as formatting field names, setting field options, handling special fields, and formatting field types. The commit aims to improve the code organization and maintainability by separating the field formatting logic into dedicated formatters.
The base.py file is a new addition to the project. It introduces the FieldFormatter class, which is an abstract base class (ABC) for formatting template fields. This class provides a format() method that takes a TemplateField object as input and is meant to be implemented by subclasses. This addition allows for the creation of custom field formatters in the project.
The "RetrievalQA" memory field in the template frontend node is updated to have the "show" and "required" properties set to False. This change is made to hide the memory field and make it optional. Additionally, the "advanced" property is set to False for all fields, and the "password" property is set to False for fields containing the word "key" in their name.
⬆️ feat(pyproject.toml): update beautifulsoup4 to version 4.12.2
⬆️ feat(pyproject.toml): update langchain to version 0.0.219
⬆️ feat(pyproject.toml): update pandas to version 2.0.0
⬆️ feat(pyproject.toml): update huggingface-hub to version 0.15.0
⬆️ feat(pyproject.toml): update unstructured to version 0.7.0
⬆️ feat(pyproject.toml): update pypdf to version 3.11.0
⬆️ feat(pyproject.toml): update langchain-serve to version >0.0.47
⬆️ feat(pyproject.toml): update qdrant-client to version 1.3.0
⬆️ feat(pyproject.toml): update ctransformers to version 0.2.10
⬆️ feat(pyproject.toml): update cohere to version 4.11.0
⬆️ feat(pyproject.toml): update anthropic to version 0.3.0
⬆️ feat(pyproject.toml): update types-pyyaml to version 6.0.12.8
The dependencies in the pyproject.toml file have been updated to their latest versions. These updates include various bug fixes, performance improvements, and new features. It is important to keep the dependencies up to date to ensure compatibility and take advantage of the latest enhancements and fixes provided by the library maintainers.
- Adjusted styling in chatComponent, buildTrigger, dropdownComponent, and other components to improve visual consistency and enhance user experience.
- Updated button styles, background colors, and text colors to create a more cohesive design across the application.
- Fixed incorrect color values and replaced them with appropriate color variables from the tailwind configuration.
- Removed redundant styles and optimized the code for better maintainability.
- Update class names and colors in parameterComponent, GenericNode, alertDropDown, error, notice, success, buildTrigger, dropdownComponent, headerComponent, and inputListComponent to improve consistency and visual appeal.
The endpoint URL in the test_init_build test has been fixed to "api/v1/build/init/test" to match the correct URL pattern. This ensures that the test is accurately testing the intended functionality.
The unnecessary imports have been removed from the chat.py file to improve code cleanliness and readability. The init_build endpoint in the chat.py file has been updated to include the flow_id as a path parameter instead of extracting it from the graph_data dictionary. This change allows for a more explicit and consistent API design.
🔧 chore(chat.py): remove unnecessary imports and reformat code for better readability
The import statement for the BuildStatus enum in the schemas module has been updated to ensure the correct import. Additionally, a new "status" field has been added to the flow_data_store dictionary to track the build status of flows. The status is set to BuildStatus.IN_PROGRESS when a flow is being built, BuildStatus.SUCCESS when the build is successful, and BuildStatus.FAILURE when there is an error during the build process. This allows for better tracking and management of flow builds.
🐛 fix(chat.py): change import statement for BuildStatus in schemas module
The BuildStatus enum is added to represent the different statuses that a build can have: SUCCESS, FAILURE, and IN_PROGRESS. This enum will be used to provide a more structured and consistent way of handling build statuses in the application.
- Added support for the CustomComponent tool in the Langflow API.
- The tool has been added to the config.yaml file.
- The CustomComponentNode class has been implemented in the frontend nodes.
- The code changes include modifications in various files for the implementation of the CustomComponent tool.
- The code changes include the addition of a new field "code" in the TemplateField class.
- The build_langchain_template_custom_component function has been implemented to build the template for the CustomComponent tool.
- New custom fields "my_id", "year", and "other_field" have been added to the template for the CustomComponent tool.
There is a recurring intermittent bug, where Chains fail to validate, with an error "Required module ____ for module ____ not found". This happens frequently for all LLMs that inherit from the LLM class (example Cohere's wrapper).
This is caused by this chunk of code.
This also explains why the bug is intermittent and not every time.
"in" is matching LLM from source_types with BaseLLM from target_reqs. Also, this doesn't need to be a nested loop, it can be done with one loop.
I'm a user of LangFlow, and a first time contributor. Thanks!
🐛 fix(chatComponent): remove console.log statements for 'open' and 'isBuilt' variables to clean up code
🐛 fix(formModal): remove unnecessary console.log statement for 'tabsState[id.current]' variable to clean up code
🐛 fix(PageComponent): set isPending to true for each tab in the Page component state to fix a bug
The `instantiate_textsplitter` function has been refactored to improve readability and remove unnecessary code. The condition for creating the `text_splitter` object has been simplified and the `separator_type` parameter is now removed from the `params` dictionary if it exists. Additionally, the `language` parameter is now passed as an instance of the `Language` class from the `langchain.text_splitter` module. This change ensures that the `text_splitter` object is created correctly and the `split_documents` method is called with the appropriate parameters.
The options list for the separator_type field in the TextSplittersFrontendNode class has been extracted into a variable called options. This improves code readability and allows for easier modification and sorting of the options list.
The documentation link for ConversationBufferMemory in the memories section has been updated to point to the correct URL "https://python.langchain.com/docs/modules/memory/how_to/buffer". This change ensures that users can access the correct documentation for using ConversationBufferMemory.
💡 chore(loading.py): improve code readability and maintainability by simplifying the instantiation of the prompt object and assignment of format_kwargs dictionary.
The code has been refactored to use a dictionary comprehension to create the format_kwargs dictionary. This simplifies the logic and improves code readability. The commented out code for the prompt.partial() method has been removed as it is no longer necessary.
🔥 chore(promptModal): remove unused promptModal component
🔨 refactor(promptComponent): use useEffect to make a POST request to validate the prompt value and update the nodeClass state if the API returns data
✨ feat(utils.py): add support for setting input keys values from artifacts in build_input_keys_response function
The build_input_keys_response function now takes an additional parameter, artifacts, which is a dictionary containing key-value pairs. The function sets the values of the input keys in the input_keys_response dictionary based on the corresponding keys in the artifacts dictionary. This allows for more flexibility in setting the input keys values dynamically based on the provided artifacts.
