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0ee3210 1b50e57 0ee3210 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | # app/tasks/task_single_label.py
"""
Task: single-label-classify
Difficulty: Easy
Content types: text_post, image_description
Steps per episode: 10
Description:
Agent receives one content item per step.
Must return exactly ONE ViolationCategory label.
Action must be one of: approve (if CLEAN) or remove/restrict.
"""
from __future__ import annotations
from models import (
ContentItem, ModerationObservation, ContentType
)
from server.dataset import get_posts, get_image_descriptions, get_policy_excerpt, get_community_standards
TASK_NAME = "single-label-classify"
MAX_STEPS = 10
INSTRUCTIONS = (
"You are a content moderator. For each item, assign EXACTLY ONE violation category "
"from the list, or mark it as CLEAN if no violation exists. "
"Then choose the appropriate enforcement action: approve (clean), remove (clear violation), "
"restrict (borderline), or escalate (unclear). "
"Respond with a JSON ModerationDecision."
)
def build_episode(seed: int = 42) -> list[ContentItem]:
"""Return a shuffled mix of posts and image descriptions for one episode."""
posts = get_posts(seed)[:7]
images = get_image_descriptions(seed)[:3]
items = posts + images
return [ContentItem(**{k: v for k, v in item.items()
if k not in ("ground_truth_labels", "ground_truth_action", "difficulty")})
for item in items]
def build_observation(step: int, item: ContentItem) -> ModerationObservation:
policies = get_community_standards()
return ModerationObservation(
step=step,
content_item=item,
policy_excerpt=get_policy_excerpt(item.content_type.value, policies),
task_name=TASK_NAME,
instructions=INSTRUCTIONS,
)
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