Pinecone Handshake

Export Chonkie’s Chunks into a Pinecone index.

The PineconeHandshake class provides seamless integration between Chonkie’s chunking system and Pinecone, a managed vector database.

Embed and store your Chonkie chunks in Pinecone directly from the Chonkie SDK.

Installation

Before using the Pinecone handshake, make sure to install the required dependencies:

pip install chonkie[pinecone]

Basic Usage

Initialization

from chonkie import PineconeHandshake

# Initialize with default settings (auto-generated index)
handshake = PineconeHandshake(api_key="YOUR_API_KEY")

# Or connect to an existing Pinecone client
import pinecone
client = pinecone.Pinecone(api_key="YOUR_API_KEY")
handshake = PineconeHandshake(client=client, index_name="my_index")

# Specify embedding model and dimension
handshake = PineconeHandshake(
    api_key="YOUR_API_KEY",
    index_name="my_index",
    embedding_model="minishlab/potion-retrieval-32M",
    dimension=384
)

Writing Chunks to Pinecone

from chonkie import PineconeHandshake, SemanticChunker    

# Initialize the handshake
handshake = PineconeHandshake(api_key="YOUR_API_KEY", index_name="my_documents")

# Create some chunks
chunker = SemanticChunker()
chunks = chunker.chunk("Chonkie loves to chonk your texts!")

# Write chunks to Pinecone
handshake.write(chunks)

Parameters

client · Optional[pinecone.Pinecone] · default: "None"

Pinecone client instance. If not provided, a new client will be created based on other parameters.

api_key · Optional[str] · default: "None"

Pinecone API key for authentication.

index_name · Union[str, Literal['random']] · default: "random"

Name of the index to use. If “random”, a unique name will be generated.

embedding_model · Union[str, BaseEmbeddings] · default: "minishlab/potion-retrieval-32M"

Embedding model to use. Can be a model name or a BaseEmbeddings instance.

dimension · Optional[int] · default: "None"

Dimension of the embeddings. If not provided, will be inferred from the embedding model.

**kwargs · Dict[str, Any] · default: "{}"

Additional keyword arguments to pass to the Pinecone client or index creation.