LangChain Automate

This workflow is ideal for:

• Project Managers who need to efficiently break down tasks into manageable sub-tasks.
• Team Leaders looking to streamline project planning and task delegation.
• Individual Contributors who want to improve their productivity by utilizing a structured task management approach.
• Developers interested in integrating AI tools for project management in their applications.
• Telegram Users who prefer voice or text communication for task management.

This workflow addresses the challenge of task decomposition in project management. It allows users to:

• Convert vague project descriptions into clear, actionable sub-tasks formatted for Todoist.
• Efficiently manage tasks by utilizing AI to analyze and break down project requirements, ensuring no important details are overlooked.
• Facilitate communication through Telegram, making it easier for teams to collaborate and stay organized.

1. Receive Messages: The workflow starts by listening for incoming messages on Telegram. It can handle both voice and text messages.
2. Determine Message Type: A switch node identifies whether the incoming message is a voice message or text. If it's a voice message, it fetches the audio file; if it's text, it prepares the text for processing.
3. Transcribe Voice Messages: If the message is a voice note, it transcribes the audio into text using OpenAI's Whisper API.
4. Prepare Input for LLM: The workflow prepares the text (either from the original message or the transcribed voice) for processing by the LLM (Language Model).
5. Process with LLM: The text is analyzed by the OpenAI Chat Model, which generates structured sub-tasks formatted for Todoist.
6. Extract Tasks: The output from the LLM is parsed to extract individual tasks.
7. Create Todoist Tasks: Each extracted task is sent to Todoist, where it is created with the specified priority.
8. Send Confirmation: Finally, a confirmation message is sent back to the user on Telegram, providing details about the created tasks and their links.