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Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters.
Passed 21 of 22 test cases with the skill, and 20 of 22 without it.
1 fixed20 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
Show the Python snippet to instantiate a HuggingFace embedding utility using model 'sentence-transformers/all-mpnet-base-v2' and pass it to a collection named 'hf_docs'.
| Checked | Without skill | With skill |
|---|---|---|
| embedding_functions.HuggingFaceEmbeddingFunction | Missed | Passed |
| model_name="sentence-transformers/all-mpnet-base-v2" | Passed | Passed |
The instructions your model reads when the skill loads.
The AI-native database for building LLM applications with memory.
Use Chroma when:
Metrics:
Use alternatives instead:
# Python
pip install chromadb
# JavaScript/TypeScript
npm install chromadb @chroma-core/default-embed
test cases passed, vs 20 / 22 without
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