chini-train-train-0030-dp2-infra

Search Autocomplete Service

easy infra problem: search autocomplete service

Source: chini-train synth generator v0.1

Prompt

Design a system for: search autocomplete service (domain: SWE backend / infra).

Tier DP2 (easy). 4-6 nodes, single mild stress scenario, moderate criteria.

Constraints:
- At most 8 components on the canvas.
- Monthly cost ceiling: $580 USD. Required behaviors: storage, queue, circuitbreaker.

Return a Chinilla CanvasState that handles the listed scenarios. Include trigger components for each entry point and at least one terminal storage / sink so the simulator can score delivery.

Constraints

Max components: 8
Required behaviors: storage, queue, circuitbreaker
Monthly budget: $580

Stress scenarios

Baseline traffic

baseline

Steady ambient load with no failures.

Cascading failure

cascade

An initial fault propagates through dependent components.

Pass criteria (overall)

Min stability score: 58
Max drop rate: 14.0%
Min delivery rate: 75.8%
Max errors: 10

Submit your run

Submissions go through the chini-bench CLI. It calls your model with your key, scores the result locally, and posts to the leaderboard. Nothing leaves your machine except the canvas it produces.

End-to-end:

pip install git+https://github.com/collapseindex/chini-bench-cli.git
export OPENROUTER_API_KEY=...

chini-bench run chini-train-train-0030-dp2-infra \
  --provider openrouter --model google/gemini-2.0-flash-001 \
  --as alice

Or inspect the prompt first:

chini-bench prompt chini-train-train-0030-dp2-infra

Providers: openai · anthropic · google · openrouter · ollama

Leaderboard

Rank	Submitter	Model	Score	Stability	Delivery	Design	Pass
#1	rl_v07_full_a10	rl_policy custom single-shot	82	68.0	73.0	100.0	✗
#2	chini-train-03	opus-4.7 single-shot	80	60.0	75.0	100.0	✗
#3	chini-train-03	opus-4.7 single-shot	80	60.0	75.0	100.0	✗
#4	rl_v07_full_a10	rl_policy custom single-shot	80	68.0	73.0	100.0	✗
#5	rl_v07_full_a10	rl_policy custom single-shot	76	58.0	64.0	100.0	✗
#6	chini-train-03	grok-4.1-fast single-shot	73	56.0	55.0	100.0	✗
#7	chini-train-04	grok-4.1-fast single-shot	73	56.0	55.0	100.0	✗
#8	rl_v07_full_a10	rl_policy custom single-shot	59	33.0	28.0	100.0	✗

Per-scenario breakdown of the top run

Scenario	Health	Drop rate	Delivered	Pass
baseline	84.0	1.7%	29	✓
cascade-1	51.0	33.3%	18	✗

How is this scored? →