Using ChromaDB locally

# Install dependencies first (if not already installed):
# pip install chromadb sentence-transformers

import chromadb
from chromadb.utils import embedding_functions

# 1. Create or connect to a local ChromaDB client
client = chromadb.Client()

# 2. Define an embedding function (using a small local model)
embedding_func = embedding_functions.SentenceTransformerEmbeddingFunction(
    model_name="all-MiniLM-L6-v2"
)

# 3. Create a collection (like a table)
collection = client.create_collection(name="my_collection", embedding_function=embedding_func)

# 4. Add some documents
collection.add(
    ids=["doc1", "doc2", "doc3"],
    documents=[
        "Chroma is a database for embeddings.",
        "OpenAI builds powerful language models.",
        "Python is a versatile programming language."
    ]
)

# 5. Run a similarity search
results = collection.query(
    query_texts=["What is Chroma?"],
    n_results=2
)

print(results)