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second-brain-env
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name: second_brain_env
version: "1.0.0"
description: >
  A Personal Knowledge Management environment where AI agents learn to
  capture, organize, and retrieve information — simulating the real-world
  challenge of managing a second brain. Three tasks of increasing difficulty:
  note categorization (easy), memory retrieval (medium), and knowledge
  synthesis (hard).
author: RAc1928
tags:
  - openenv
  - knowledge-management
  - information-retrieval
  - real-world
  - nlp

tasks:
  - name: note_categorization
    difficulty: easy
    description: Categorize 10 raw notes into correct categories (work/personal/reference/action_item)
    max_steps: 12
    reward_range: [-0.02, 0.10]
    success_threshold: 0.5

  - name: memory_retrieval
    difficulty: medium
    description: Retrieve the most relevant note from a 30-note knowledge base for each of 5 questions
    max_steps: 15
    reward_range: [-0.10, 0.20]
    success_threshold: 0.5

  - name: knowledge_synthesis
    difficulty: hard
    description: Collect and synthesize insights from a 50-note knowledge base to answer complex multi-theme questions
    max_steps: 20
    reward_range: [-0.10, 0.35]
    success_threshold: 0.5

action_space:
  type: SecondBrainAction
  fields:
    action_type:
      type: string
      enum: [categorize, retrieve, synthesize, tag, skip]
    content:
      type: string
      description: Category name / search query / synthesized answer
    note_id:
      type: string
      optional: true
    tags:
      type: array
      items: string
      optional: true

observation_space:
  type: SecondBrainObservation
  fields:
    current_note:
      type: object
      optional: true
    query:
      type: string
      optional: true
    retrieved_notes:
      type: array
      optional: true
    knowledge_base_size:
      type: integer
    step_count:
      type: integer
    task_name:
      type: string
    reward:
      type: float
    done:
      type: boolean
    score:
      type: float
      description: Running normalized score in [0.0, 1.0]
    feedback:
      type: string
    valid_categories:
      type: array
      items: string
    remaining_items:
      type: integer

environment:
  type: http
  framework: fastapi
  dockerfile: Dockerfile
  port: 8000
  endpoints:
    reset: POST /reset
    step:  POST /step
    state: GET  /state
    tasks: GET  /tasks
    health: GET /health