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name: embeddings-and-generative description: "Select Chonkie embedding models, provider embeddings, and generative chunking workflows without hidden network assumptions." disable-model-invocation: true metadata: disco-role: operating license: MIT

Chonkie embeddings and generative workflows

Use this sub-skill when a task depends on embedding vectors, semantic/late/neural/LLM chunking, embedding-based refinement, or provider-backed generation inside Chonkie.

Route here for

• Selecting or wiring AutoEmbeddings, BaseEmbeddings, Model2VecEmbeddings, SentenceTransformerEmbeddings, CatsuEmbeddings, provider embedding wrappers, or LiteLLMEmbeddings.
• Adding chunk embeddings with EmbeddingsRefinery before retrieval, export, or vector storage.
• Operating SemanticChunker, LateChunker, NeuralChunker, or SlumberChunker with explicit optional dependencies, model cache/download, credential, batching, and timeout decisions.
• Debugging provider Genie classes used by SlumberChunker: OpenAI, Azure OpenAI, Gemini, Groq, and Cerebras.

Route elsewhere first

• Deterministic token/sentence/recursive/table/code chunking and Chunk/tokenizer contracts: ../chunking-and-types/.
• Pipeline placement, CHOMP ordering, file processing, chefs, and refinery orchestration: ../pipelines-and-processing/.
• Chonkie Cloud, local FastAPI/API schemas, and CLI deployment: ../interfaces-and-deployment/.
• Vector DB handshakes and chunk/document storage targets: ../integrations-and-storage/.

Operating procedure

1. Identify whether the user needs local embeddings, third-party provider embeddings, model-dependent chunking, or generative LLM chunking.
2. Read references/embeddings-reference.md for embedding/provider selection, constructor arguments, extras, credentials, and batching/timeout notes.
3. Read references/model-dependent-chunking.md before using EmbeddingsRefinery, SemanticChunker, LateChunker, NeuralChunker, or SlumberChunker.
4. Run scripts/optional_dependency_probe.py to inspect installed optional modules without making network calls. Use --instantiate-safe only for the script's safe no-network checks.
5. If optional dependencies, credentials, models, or services are missing, read references/troubleshooting.md and select a deterministic fallback or ask the user to authorize the required install/network/API-key path.

Verification boundary

The Chonkie skill's required environment only verified CPU-local core package behavior. Model downloads, accelerator use, third-party provider APIs, provider credentials, and live generative calls are optional and must be treated as unverified unless the current user explicitly supplies and authorizes those resources.