---
license: cc0-1.0
tags:
- chromadb
- legal
- congress
- legislation
- embeddings
size_categories:
- 100K<n<1M
---

# usc-chroma-vecs-v1-chunks-v1-s8192-o512-sentence-transformers-static-retrieval-mrl-en-v1

This dataset contains a pre-built ChromaDB database with US Congressional legislation embeddings.

## Dataset Structure

This dataset contains the ChromaDB files for legislation chunks with embeddings. The database can be loaded directly using ChromaDB's PersistentClient.

## Usage

```python
import chromadb
from huggingface_hub import snapshot_download

# Download the dataset
local_dir = snapshot_download(repo_id="hyperdemocracy/usc-chroma-vecs-v1-chunks-v1-s8192-o512-sentence-transformers-static-retrieval-mrl-en-v1", repo_type="dataset")

# Load the ChromaDB
client = chromadb.PersistentClient(path=local_dir + "/chromadb")
collection = client.get_collection("usc")

# Query the database (embedding function is already configured)
results = collection.query(
    query_texts=["your query here"],
    n_results=10
)

# Get collection metadata to see embedding model info
metadata = collection.metadata
print(f"Embedding model: {metadata['embedding_model']}")
print(f"Chunk size: {metadata['chunk_size']}")
```

## Configuration

This ChromaDB includes the following configuration stored as collection metadata:
- **Embedding model**: The SentenceTransformer model used for embeddings
- **Chunk size**: Character count for text chunking
- **Chunk overlap**: Overlap between adjacent chunks  
- **Chunking version**: Version of the chunking algorithm
- **Embedding version**: Version of the embedding process

The embedding function is automatically configured when loading the collection, enabling direct text queries without manual embedding.