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Embedding Generator Pack

★Trusted◇Sandbox optionalv1.0.0MIT✔Verified80

by AgentNode · published 6 months ago · toolpack

Generate vector embeddings from text using sentence transformers.

Creates dense vector representations for semantic similarity and retrieval.

langchaincrewaigeneric

Quick Start

bash
agentnode install embedding-generator-pack

Runs in a subprocess with filtered environment by default. Declared permissions are policy-checked, not sandboxed.

Usage

From package
python
from embedding_generator_pack.tool import run

# Generate embeddings for a set of documents
result = run(
    action="generate_embedding",
    texts=[
        "Kubernetes pod scheduling and resource allocation",
        "Docker container orchestration with Swarm",
        "How to make sourdough bread at home",
        "Helm chart templating best practices"
    ],
    model="all-MiniLM-L6-v2"
)

embeddings = result["embeddings"]
print(f"Generated {len(embeddings)} embeddings")
print(f"Dimensions: {result['dimensions']}")
print(f"Model: {result['model']}")

# Compare similarity between first and other documents
for i, score in enumerate(result["similarity_matrix"][0]):
    print(f"  Doc 0 vs Doc {i}: {score:.4f}")

Runs locally on your machine. No execution data is sent to AgentNode. Permissions are checked before execution. Learn how this works

Verification

high confidence80/100✔ Verified
smokeReturned valid result
+25/25
testsTests failed
0/15
importAll tools imported successfully
+15/15
installInstalled in 34.1s
+15/15
contractAll contract checks passed
+10/10
determinismConsistent output across runs (normalized)
+5/5
reliability3/3 runs passed
+10/10

Package installs and imports correctly. runtime checks passed.

✔install34.1s
✔import76ms
✔smoke28.9s
✖tests1.3s

This package was executed and validated by AgentNode before listing. Install, import, and runtime checks passed.

Verified in real_auto mode

Python 3.12.3ffmpegpopplertesseractuv

Last verified 18d ago· Runner v2.0.0

Use this when you need to...

  • ›Generate embeddings for semantic search over a knowledge base
  • ›Compute similarity scores between job descriptions and resumes
  • ›Cluster customer feedback into topic groups by vector proximity
  • ›Build a recommendation engine using text embedding cosine similarity
  • ›Create vector indexes for retrieval-augmented generation pipelines

README

Version History

v1.0.0latestverified
3/16/2026

Capabilities

embedding_generationgenerate_embeddingtool

Permissions

◇Sandbox optionalFrom a trusted publisher — runs on the host by default. You can require isolation with sandbox.host_trust_policy.

Declared by the publisher. Checked before execution by the policy gate.

Networknone
Filesystemtemp
Code Executionnone
Data Accessinput_only
User Approvalnever

Permissions are policy-checked before execution. For trusted and curated packages that run on the host, network and filesystem access are policy-checked but not OS-sandboxed. When runtime isolation is required for untrusted/community code, AgentNode uses sandbox-or-fail-closed if the required container runtime and pinned image are available. Learn more

Privacy

All tool execution happens locally on your machine. AgentNode never receives:

  • • Tool inputs or outputs
  • • Execution logs
  • • Data your agent processes

Only install events and search queries are sent to the registry.

bash
agentnode install embedding-generator-pack

Files (3)

License

MIT

Stats

Downloads0
Installs0
Versionv1.0.0
Published3/16/2026
Channelstable
Typetoolpack
Entrypointembedding_generator_pack.tool

Compatibility

Frameworks

langchaincrewaigeneric

Runtime

python

Python Version

>=3.10

Trust & Security

Publisher★Trusted
SignatureNone
ProvenanceNone
Security Issues0

Publisher

A

AgentNode

@agentnode

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