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yyy188
by yyy188

bootstrap_models

Pre-download the embedding model and optional reranker to prevent sync delays. Run before initializing a project.

Instructions

Pre-download the embedding model (and optionally the reranker) so syncs never wait on them.

Downloads the local embedding model (bge-small-en-v1.5, ~130MB ONNX) into
the project-local cache, ASYNCHRONOUSLY, via onnxruntime/fastembed (no
torch/transformers dependency). Returns a job_id immediately. This is the
recommended first step after installing/configuring the server — call it
BEFORE init_jama_project so the first sync isn't slowed by a model
download. Models already cached are skipped. Poll progress with
get_bootstrap_progress roughly every 2 minutes, reporting each sample to
the user, until status is DONE or ERROR.

The cross-encoder reranker (ms-marco-MiniLM-L-6-v2, ~80MB ONNX) is only
downloaded when explicitly enabled via RERANKER_ENABLED=1. The default
search path is pure RRF ordering (benchmarking showed it outperforms
rerank), so a default install needs NO reranker weights and bootstrap
completes after the embedding model alone.

Returns:
    {"job_id": "...", "status": "RUNNING"} or, if a bootstrap is already
    running, {"job_id": "...", "status": "RUNNING", "note": "..."}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. Discloses asynchronous download, caching behavior, reranker toggle via environment variable, and default RRF ordering avoiding reranker need.

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?

Well-structured with clear paragraphs and bullet points for return values. Concise yet comprehensive, no superfluous content.

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?

Covers model details, caching, polling advice, return format, and reranker toggle. Complete for a setup tool with no output schema.

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

Parameters4/5

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

No parameters exist, baseline 4. Description adds value by clarifying default behavior regarding reranker but no parameter details needed.

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?

Clearly states it pre-downloads embedding model and optional reranker to avoid wait during syncs. Specifies model names and sizes, and distinguishes from sibling tools like init_jama_project.

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

Usage Guidelines5/5

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

Explicitly states it's the recommended first step after installing/configuring the server, call BEFORE init_jama_project. Also explains when reranker is needed and suggests polling with get_bootstrap_progress.

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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