Task Manager Submodule

Purpose

This submodule manages the state, task tracking, and coordination for the solfunmeme-dioxus project and its related submodules (e.g., social media, dataset, sync, campaign phases).

Features

Centralized state recording (state.json)
Tracks project, dataset, and social media status
Designed for extensibility (add scripts, dashboards, etc.)

Directory Structure

task_manager/
├── README.md         # This file
├── Cargo.toml        # Crate manifest
├── src/              # Rust source code
├── datasets/         # Data related to tasks (e.g., task definitions, progress logs)
├── states/           # State definitions and management logic
└── state.json        # Current state of the project (example/placeholder)

Example State File

See state.json for the current state structure.

Usage

Update state.json after major project events (dataset update, campaign phase change, etc.)
Use scripts in src/ to automate state management (coming soon)

Extending

Add new fields to state.json as needed
Add scripts for automation, dashboards, or integrations

Part of the solfunmeme-dioxus project ecosystem

AI Agent Directives

Refer to GEMINI.md in this directory for specific guidelines for AI agents contributing to task_manager.

Task Manager: Turtle-Based Semantic Migration Plan

1. Semantic Task Representation

Each task, dependency, and status will be a node in an RDF/Turtle graph.

Example:

tm:Task123 a tm:Task ;
    tm:content "Implement emoji ontology export" ;
    tm:status "pending" ;
    tm:dependsOn tm:Task122 .

2. Sophia Integration

Use Sophia to parse, query, and update the task graph in Rust.
Tasks can be queried by status, dependencies, or content.

3. SerDe for Task State

Serialize/deserialize task instances and state to/from Turtle using SerDe.
Enables persistence, sharing, and versioning of task data.

4. Integration with Universal Semantic Code Graph

Tasks can reference or be referenced by code, component, or contract nodes in the main ontology.
Enables unified project management, code, and UI orchestration.

5. Future LLM and GUI Integration

LLMs can query, generate, or update tasks via the semantic graph.
Dioxus GUI can render and edit tasks live from the Turtle graph.

This migration will make the task manager a first-class, semantic, and LLM-accessible part of the universal code graph.

Internal AI TODO Integration

Internal TODOs generated by the AI assistant are now tracked as Task entries in the codebase.
These TODOs can be exported to Turtle (RDF) format using the export_internal_todos_to_turtle function in src/main.rs.

Exporting Internal TODOs to Turtle

To export the internal TODOs to a Turtle file:

// In your main or a script:
export_internal_todos_to_turtle("./states/gemini/internal_todos.ttl").expect("Export failed");

This will create a Turtle file with all internal TODOs, making them part of your semantic code graph and ontology workflows.

Each TODO is exported as a tm:Task with id, content, status, and dependencies.
Emoji annotations are included if available in the ontology.

For more details, see the Task struct and export functions in src/main.rs.

Exporting All Tasks as JSON

You can export all tasks in the state directory as a single JSON array file using the CLI:

cargo run --package task-manager -- export-all-tasks-json

This will create task_manager/states/gemini/all_tasks.json containing all tasks as an array.

You can specify a custom output path:

cargo run --package task-manager -- export-all-tasks-json --output my_tasks.json

Adding Tasks

You can add tasks in two ways:

1. Using the CLI

cargo run --package task-manager -- add <task_id> <content> --dependencies dep1 dep2