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get grpo run weights

get_grpo_run_weights
Read-onlyIdempotent

Retrieve presigned download links for a finished GRPO run's trained adapter files to self-host the weights. Works for completed, stopped, or failed runs with partial checkpoints.

Instructions

Get short-lived presigned download links for a finished online-RL (GRPO) run's trained adapter files so you can self-host the weights — use it after a run completes (or stops with a partial checkpoint). GET /v1/grpo/runs/{id}/weights (API-key scope: read). Returns: JSON object: { run_id, status, partial: boolean (true for STOPPED/FAILED — files are a partial checkpoint, not the finished adapter), files: [ { name (e.g. adapter_model.safetensors), size_bytes: integer|null, url (presigned GET, valid 15 minutes), expires_at (ISO) } ], empty_reason?: string (present when files is empty), storage_unavailable?: true (weight storage not configured — try later) }. Files sorted safetensors first, then adapter files, then config/tokenizer. Notes: 400 while the run is ACTIVE ('Weights are available once the run finishes.') and for OVERBUDGET runs ('This run has no trained adapter to download.'). 404 for foreign/unknown runs. Links expire after 15 minutes — re-call to refresh. Every call is audit-logged as a weight export. Feature-flag gated (fineTuning flag off → 404). OWNER/ADMIN key required (403).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe GRPO run id. Must be in a terminal status (COMPLETED, STOPPED, or FAILED).
Install Server

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark this as read-only, idempotent, and non-destructive, and the description adds substantial behavioral context beyond that: presigned URLs expire in 15 minutes, calls are audit-logged as weight exports, OWNER/ADMIN permission is required, feature-flag gating returns 404, and partial checkpoints are handled differently. This is rich and useful transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every sentence carries operational value: purpose, timing, endpoint, auth scope, response shape, error semantics, expiry, audit logging, and feature-flag behavior. It is front-loaded with the core purpose and usage condition before diving into return details and edge cases.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description fully specifies the return JSON structure, field meanings, sort order, partial-checkpoint semantics, error cases, permission requirements, expiry behavior, and storage-unavailable handling. An agent has everything needed to call this tool correctly and interpret its response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully documents the single `id` parameter, including the requirement that the run be in a terminal status (COMPLETED, STOPPED, or FAILED). The description mostly repeats that status constraint; it adds error-case context (400/404/403) but does not add significant meaning about the parameter itself beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Get... presigned download links'), a specific resource ('a finished online-RL (GRPO) run's trained adapter files'), and a clear goal ('so you can self-host the weights'). It is easily distinguished from sibling tools like get_grpo_run, which is about run metadata, not weight export.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states when to use it: after a run completes or stops with a partial checkpoint, and explicitly excludes ACTIVE and OVERBUDGET runs. It does not name an alternative tool to use instead, but the timing and error conditions provide strong contextual guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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