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ops-chutes

Manage Chutes.ai resources, tracking subscription quota and account balance. Integrates with scheduler to pause operations when quota is reached.

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grahama1970/agent-stack-public
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24 de septiembre de 2026 a las 15:51
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SKILL.md
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name
ops-chutes
description
Manage Chutes.ai resources, tracking subscription quota and account balance. Integrates with scheduler to pause operations when quota is reached.
triggers
["check chutes","chutes usage","chutes budget","chutes status","chutes models","list chutes models","what models are on chutes","chutes model list","is model X ready?","wait for chutes reset","can I run X calls?","check chutes health","chutes api check","is chutes slow","chutes overloaded","switch from TEE","recommend non-TEE","TEE vs non-TEE"]
metadata
{"short-description":"Chutes.ai API management and Quota tracking"}
provides
["ops-chutes"]
composes
["task-monitor","agentic-evals"]
disciplines
["observability-operations","model-ops"]
# Ops Chutes Skill Manage Chutes.ai resources and monitor subscription quota and account balance. ## Triggers - "Check chutes status" -> `status` - "How much chutes budget left?" -> `usage` - "Is chutes working?" -> `sanity [model]` ## Commands ```bash # Check model status (hot/cold/down) ./run.sh status # Check Subscription Quota and Remaining Balance ./run.sh usage [--chute-id <id>] [--json] # Explore all available models (filterable) # Flags: --query (name), --owner (sglang/vllm), --modality (text/image), --feature (reasoning/tools), --json ./run.sh models [--query <search>] [--owner <owner>] [--modality <modality>] [--feature <feature>] [--json] # Check model health (HOT/COLD/DOWN) ./run.sh model-health <model_id> # Rank all variants in a model family by speed, recommend the best # Finds TEE + non-TEE siblings, pings each, shows ranked table ./run.sh recommend <model_id> # e.g. deepseek-ai/DeepSeek-V3.1-TEE ./run.sh recommend <model_id> --json # JSON output for automation ./run.sh recommend <model_id> --skip-ping # Metadata only, no latency test # Run sanity check (Inference via Qwen/Qwen2.5-72B-Instruct) ./run.sh sanity [model_name] # Check budget (exit 1 if Quota exhausted OR Balance < CHUTES_MIN_BALANCE) ./run.sh budget-check # Wait until quota resets (7PM ET) ./run.sh wait-for-reset [--timeout <seconds>] # Verify if a batch of calls is feasible (exit 1 if not) ./run.sh can-complete <num_calls> ``` ## Environment Variables | Variable | Description | | -------------------- | ----------------------------------------- | | `CHUTES_API_TOKEN` | API Token (standard) | | `CHUTES_API_KEY` | API Key (alternative naming) | | `CHUTES_MIN_BALANCE` | Minimum balance threshold (default: 0.05) | ## TEE vs Non-TEE Model Selection Chutes.ai miners generally prefer non-TEE models because: - **Higher throughput**: TEE enclave overhead reduces TPS by ~10-20% - **More miners serving**: Non-TEE models get higher utilization and more active nodes - **Faster cold starts**: No enclave initialization delay Use `recommend` to find the fastest variant. TEE is only needed when data privacy/isolation is a legal or compliance requirement. ## Usage Reports & Analytics ```bash # Daily usage (last 30 days, default) ./run.sh report # Monthly aggregation (all-time) ./run.sh report --monthly # Show only days that exceeded the 5K quota ./run.sh report --spikes # Hourly breakdown for a specific date ./run.sh report --hourly 2026-02-18 # JSON output for automation / /create-figure ./run.sh report --monthly --json ./run.sh report --spikes --json ./run.sh report --hourly 2026-02-18 --json # Last 7 days only ./run.sh report --days 7 ``` Data source: `/users/me/usage` API (hourly granular buckets with token counts and costs). ## Concurrency Throttle Cross-process semaphore enforcing the 5-slot Chutes.ai concurrency limit. Uses `fcntl.flock()` on 5 slot files — lock auto-releases on process crash. ```bash # Acquire a slot (blocks until available, 90s timeout) ./run.sh acquire [--timeout 90] # Show slot usage ./run.sh slots # Python context manager from throttle import ChutesSemaphore with ChutesSemaphore() as slot: print(f"Using slot {slot}") # ... make Chutes API calls ... ``` Slot files: `~/.pi/ops-chutes/semaphore/slot_{0..4}` > [!WARNING] > **Concurrency Limit**: Chutes.ai allows **5 concurrent connections** per token. > The throttle enforces this via OS-level file locks. Exceeding the limit returns > a 429 Rate Limit error with a **90-second pause**. ## Common Mistakes ### WRONG: Using TEE model variants for batch work ```python model = "deepseek-ai/DeepSeek-V3.1-TEE" # 4x slower, 429s at high load ``` ### RIGHT: Use non-TEE variants for batch operations ```bash ./run.sh recommend deepseek-ai/DeepSeek-V3.1-TEE # shows fastest variant # Use the recommended non-TEE model ``` ### WRONG: Launching batch jobs without checking budget first ```bash ./run.sh # starts burning tokens without checking quota ``` ### RIGHT: Budget-check before batch operations ```bash ./run.sh budget-check # exits 1 if quota exhausted or balance low ./run.sh can-complete 500 # verify 500 calls are feasible ``` ### WRONG: Exceeding 5 concurrent connections across processes ```python # Multiple processes each opening 6 async connections = self-DoS ``` ### RIGHT: Use the ChutesSemaphore for cross-process coordination ```python from throttle import ChutesSemaphore with ChutesSemaphore() as slot: # make Chutes API calls safely pass ``` ## References (retrieve on demand — do not vendor) External docs drift; cite the canonical URLs and fetch them when needed with `/context7` (library docs) or `/fetcher` (any URL/PDF) rather than caching stale copies. Verified reachable (HTTP 200) 2026-08-24. - Chutes.ai documentation: <https://docs.chutes.ai/> - llms.txt (LLM-friendly doc index): <https://chutes.ai/llms.txt> ```bash skills/context7/run.sh "chutes.ai api quota" skills/fetcher/run.sh "https://docs.chutes.ai/" ```
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