# SingleStore Loader
```bash
pip install llama-index-readers-singlestore
```
The SingleStore Loader retrieves a set of documents from a specified table in a SingleStore database. The user initializes the loader with database information and then provides a search embedding for retrieving similar documents.
## Usage
Here's an example usage of the SingleStoreReader:
```python
from llama_index.readers.singlestore import SingleStoreReader
# Initialize the reader with your SingleStore database credentials and other relevant details
reader = SingleStoreReader(
scheme="mysql",
host="localhost",
port="3306",
user="username",
password="password",
dbname="database_name",
table_name="table_name",
content_field="text",
vector_field="embedding",
)
# The search_embedding is an embedding representation of your query_vector.
# Example search_embedding:
# search_embedding=[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3]
search_embedding = [n1, n2, n3, ...]
# load_data fetches documents from your SingleStore database that are similar to the search_embedding.
# The top_k argument specifies the number of similar documents to fetch.
documents = reader.load_data(search_embedding=search_embedding, top_k=5)
```
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