✨ 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.
✨ feat(chat.py): update build_input_keys_response function to accept artifacts parameter to set input_keys values
The stream_build function now supports the artifacts parameter, which allows passing prompt variables to the build_input_keys_response function. This ensures that the input_keys values are correctly set based on the provided artifacts. The build_input_keys_response function has been updated to accept the artifacts parameter and use it to set the input_keys values. This improves the functionality of the chat module by allowing more flexibility in handling prompt variables.
🐛 fix(vertex/base.py): update instantiation logic to handle tuple result from loading.instantiate_class()
🐛 fix(loading.py): update return value of instantiate_prompt() to return a tuple of prompt and format_kwargs
The Vertex class now has a new attribute called artifacts, which is a dictionary used to store additional data related to the vertex. The instantiation logic in the Vertex class has been updated to handle the case where loading.instantiate_class() returns a tuple containing the built object and additional artifacts. The loading.instantiate_prompt() function now returns a tuple containing the prompt and format_kwargs. These changes fix issues related to storing and handling additional data in the vertex and loading modules.
The build_input_keys_response function now correctly filters out memory variables from the input keys response. Previously, it was using a list comprehension to filter the keys, but it should have been using a dictionary comprehension to preserve the key-value pairs. This fix ensures that only the keys that are not present in the langchain_object's memory variables are included in the input keys response.
The chat history is now reset when building a flow to ensure that the chat starts with a clean state. This helps prevent any potential issues or conflicts that may arise from previous chat interactions.
🐛 fix(loading.py): set input variable values if they are present in params
The "input_variables" field in the prompt's frontend_node template is now updated with the new list of variables, if it exists. This ensures that the input variables are correctly set when validating the prompt. In the loading module, the input variable values are now set if they are present in the params dictionary. This ensures that the prompt is correctly instantiated with the provided input variable values.
🐛 fix(formModal/index.tsx): format chatItem.message only if it is not from a bot to improve readability
🐛 fix(formModal/index.tsx): remove unnecessary console.log statement
🐛 fix(utils.py): rename variable in process_graph function to improve clarity and consistency
In the `ChatManager` class, the variable `chat_message` has been renamed to `chat_inputs` to better reflect its purpose of storing the input messages from the chat payload. This improves clarity and consistency within the class.
In the `process_graph` function in `utils.py`, the variable `chat_message` has been renamed to `chat_inputs` to better reflect its purpose of storing the input messages from the chat payload. This improves clarity and consistency within the function.
🔨 refactor(chatComponent): update code to correctly access template value from node data
🔨 refactor(chatInput): update button styling and positioning
🔨 refactor(chatInput): update Lock icon styling and positioning
🔨 refactor(chatInput): update Send icon styling and positioning
🔨 refactor(formModal): update setKeysValue function to correctly update the value at a specific index in the array
The build_input_keys_response function has been refactored to return an empty string for each input key in the langchain_object. This change ensures consistency in the response structure and provides a default value for each input key.
The input_types attribute is added to the template_field in the post_validate_prompt function. This change allows for specifying the input types that are accepted for the template field, providing more flexibility and control over the input data.
🔧 fix(index.ts): add input_types property to TemplateVariableType interface
The `input_types` property is added to the `TemplateFieldCreator` class in `base.py` and the `TemplateVariableType` interface in `index.ts`. This change allows for specifying the input types for template fields and template variables, respectively.
The message property in the sendAllProps type has been renamed to inputs to better reflect its purpose. This change improves the semantics of the code and makes it easier to understand the purpose of the property.
The message field of the ChatMessage schema now supports a dictionary type in addition to the previous string and None types. This change was made to allow for more complex messages to be sent and received in the chat.
✨ feat(formModal): add function to format message inputs into a string
This commit removes unused imports and variables from the file. A new function was added to format the message inputs into a string, which is used to display the message in the chat. This improves the readability of the code and makes it easier to understand how the message is being constructed.
✨ feat(formModal): add Input Variables section to Chat Form modal to allow users to input variables
🎨 style(formModal): adjust width of Chat Form modal and Input Variables section to improve UI
🎨 style(formModal): adjust layout of Input Variables section to improve UI
🎨 style(formModal): adjust layout of From Chat switch to improve UI
🐛 fix(formModal): replace Switch component with custom ToggleShadComponent to fix styling issue
✨ feat(validate.py): add support for dynamic template fields in prompt validation
The changes in this commit remove unused variables from the prompt.frontend_node.template. The commit also adds support for dynamic template fields in prompt validation. The new variables are added to the template and the custom_fields list. The old custom_fields list is copied and then updated with the new variables. The variables that are not in the template anymore are removed from the prompt.frontend_node.template.
The setNodeClass function is now passed down to PromptAreaComponent from ParameterComponent. This allows the nodeClass to be set when a prompt is used.
The `dict()` method was causing a TypeError when trying to serialize the `template_field` object. The `to_dict()` method is the correct method to use to serialize the object.
The try-catch blocks were added to handle errors that may occur when the function is called. This improves the robustness of the function and prevents it from crashing when an error occurs.
🎨 style(chatMessage.tsx): change icon from MessageCircle to MessageSquare to improve semantics
🎨 style(index.tsx): add new icons to the import statement and change MessageSquareDashed to MessageSquare to improve semantics. Add padding to the chat modal to improve aesthetics.
✨ feat(promptComponent, genericModal): add setNodeClass prop to PromptAreaComponent and GenericModal to update nodeClass
The checkPrompt function has been renamed to postValidatePrompt to better reflect its functionality. The PromptTypeAPI now includes a frontend_node property, which is used to update the nodeClass in the PromptAreaComponent and GenericModal components. The setNodeClass prop has been added to both components to allow for updating the nodeClass.
🔥 chore(base.py): remove unused FrontendNodeRequest class
🔨 refactor(validate.py): modify post_validate_prompt function to update the template field in the frontend_node object
The ValidatePromptRequest class was using the FrontendNode class instead of the FrontendNodeRequest class, which caused an error. The unused FrontendNodeRequest class was removed. The post_validate_prompt function was modified to update the template field in the frontend_node object instead of appending to the fields list.
🚀 feat(formModal.tsx): add support for multiple input keys and values to be sent in the chat message
🐛 fix(formModal.tsx): fix keysValue state initialization and message object creation
🚀 feat(formModal.tsx): add switch component to select which input key to send in the chat message
🎨 style(formModal.tsx): add muted background color to input keys container
🐛 fix(api/index.ts): change message type to any to support multiple input keys and values
The FrontendNode class now has a new attribute called custom_fields, which is a list of strings. This attribute can be used to store any custom fields that are specific to a particular frontend node. This change allows for more flexibility in the data that can be stored in a FrontendNode object.
✨ feat(base.py): add frontend_node parameter to ValidatePromptRequest and PromptValidationResponse models
The validate_prompt endpoint now accepts a frontend_node parameter in the ValidatePromptRequest model. This parameter is used to add input variables to the frontend_node's template fields and custom fields. The PromptValidationResponse model now includes the frontend_node parameter to return the updated frontend_node object.
