LaTeX Assignments Workflow Documentation
Overview
This workflow generates LaTeX code for a list of assignments based on user-provided tasks. It uses a three-component pipeline: first, user input is gathered; second, a prompt is constructed using this input; finally, a language model generates the LaTeX code, and the result is displayed.
Components Overview
The workflow utilizes the following components:
- Chat Input: Collects user input specifying the assignment tasks.
- Prompt: Constructs a prompt for the language model, incorporating the user-defined tasks.
- Groq Model: A language model that generates the LaTeX code based on the provided prompt.
- Chat Output: Displays the generated LaTeX code to the user.
Detailed Component Descriptions
Chat Input
- Description: Captures user input defining the assignment tasks.
- Input Parameters:
- Text: The user-entered text describing the assignments.
- Sender Type: Specifies whether the input is from a user or machine (default: User).
- Sender Name: The name of the sender (default: User).
- Session ID: A unique identifier for the conversation.
- Conversation ID: A unique identifier for the current conversation.
- Files: Optional files to be included with the input.
- Store Messages: A boolean flag to indicate whether to store the message in the history (default: true).
- Output Parameters:
- Message: Contains the user-provided task list.
- Key Configurations/Conditions: Requires a description of the assignments in the Text field.
Prompt
- Description: Creates a prompt for the language model, dynamically incorporating the task list received from the Chat Input.
- Input Parameters:
- Task List: The list of assignment tasks from the Chat Input component.
- Output Parameters:
- Prompt Message: The formatted prompt ready for the language model.
- Key Configurations/Conditions: Uses a template to format the prompt, inserting the task list dynamically.
Groq Model
- Description: A language model that generates LaTeX code.
- Input Parameters:
- Input Value: The prompt from the Prompt component.
- Model Name: Specifies the language model to be used (default: mixtral-8x7b-32768).
- Max Output Tokens: Limits the length of the generated LaTeX code.
- N: The number of responses to generate (default is unspecified).
- Stream: A boolean indicating whether to stream the response (default: false).
- System Message: An optional system message to provide context to the model.
- Temperature: Controls the randomness of the generated code (default: 0.3).
- Output Parameters:
- Text Output: The generated LaTeX code as a message.
- Model Output: Contains information about the model execution.
- Key Configurations/Conditions: The
model_nameparameter controls the model used; thetemperatureparameter influences the creativity of the output.
Chat Output
- Description: Displays the generated LaTeX code to the user.
- Input Parameters:
- Text: The LaTeX code from the Groq Model.
- Sender Type: Specifies whether the output is from a user or machine (default: Machine).
- Sender Name: The name of the sender (default: AI).
- Session ID: A unique identifier for the conversation.
- Conversation ID: A unique identifier for the current conversation.
- Data Template: A template to format the output (default:
{text}).
- Output Parameters:
- Message: Displays the generated LaTeX code.
- Key Configurations/Conditions: Uses a data template to format the output message; default will display only the text content.
Workflow Execution
- The Chat Input component gathers the assignment tasks from the user.
- The task list is passed to the Prompt component, which constructs a prompt for the language model.
- The prompt is sent to the Groq Model component, which generates the LaTeX code.
- The generated LaTeX code (as a message) is passed to the Chat Output component, which displays it to the user.
Additional Notes
Successful execution relies on the user providing a clear and unambiguous description of the assignments in the initial Chat Input. The performance and quality of the generated LaTeX code depend on the capabilities of the chosen language model and the parameters set in the Groq Model component. Error handling and fallback mechanisms are not explicitly defined in this template and should be considered for a production-ready system.
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