sieve / openenv.yaml
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Made some documentation updates
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name: sieve
version: "1.0.0"
description: >
A customer support reinforcement learning environment where an agent triages,
classifies, drafts responses to, and prioritizes real-world support emails.
tags:
- openenv
- customer-support
- email-triage
- nlp
api:
base_url: http://localhost:7860
reset: POST /reset
step: POST /step
state: GET /state
tasks: GET /tasks
tasks:
- id: email_classification
name: Email Classification
difficulty: easy
description: >
Classify each incoming customer support email by category
(billing/technical/general/spam/account/feature_request)
and urgency (high/medium/low) using action_type='classify'.
max_steps: 15
score_range: [0.0, 1.0]
- id: response_drafting
name: Response Drafting
difficulty: medium
description: >
Draft professional, empathetic responses to customer support emails.
Each response must cover required keywords, exceed 50 characters,
and maintain a professional tone. Use action_type='respond'.
max_steps: 10
score_range: [0.0, 1.0]
- id: support_session
name: Full Support Session
difficulty: hard
description: >
Manage a queue of 15 mixed emails. Prioritize VIP customers first,
then high-urgency emails. Choose the correct action (respond/escalate/archive)
per email, provide category and urgency, and use email_id to select
which email to process each step.
max_steps: 40
score_range: [0.0, 1.0]
observation_space:
current_email:
id: string
subject: string
body: string
sender: string
sender_tier: "standard | vip"
received_minutes_ago: integer
email_queue: "array of Email objects (populated in support_session only)"
processed_count: integer
step_count: integer
task_id: string
task_description: string
available_actions: "array of strings"
context:
max_steps: integer
remaining_steps: integer
queue_size: integer
action_space:
action_type: "classify | respond | escalate | archive | skip"
category: "billing | technical | general | spam | account | feature_request"
urgency: "high | medium | low"
response_text: "string — required for respond"
escalation_reason: "string — required for escalate"
email_id: "string — used in support_session to select target email"
baseline:
agent: gpt-4o-mini
scores:
email_classification: 0.930
response_drafting: 0.920
support_session: 0.882
average: 0.911