Source code for neo4j_graphrag.experimental.components.embedder

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from pydantic import validate_call

from neo4j_graphrag.embeddings.base import Embedder
from neo4j_graphrag.experimental.components.types import TextChunk, TextChunks
from neo4j_graphrag.experimental.pipeline.component import Component


[docs] class TextChunkEmbedder(Component): """Component for creating embeddings from text chunks. Args: embedder (Embedder): The embedder to use to create the embeddings. Example: .. code-block:: python from neo4j_graphrag.experimental.components.embedder import TextChunkEmbedder from neo4j_graphrag.embeddings.openai import OpenAIEmbeddings from neo4j_graphrag.experimental.pipeline import Pipeline embedder = OpenAIEmbeddings(model="text-embedding-3-large") chunk_embedder = TextChunkEmbedder(embedder) pipeline = Pipeline() pipeline.add_component(chunk_embedder, "chunk_embedder") """ def __init__(self, embedder: Embedder): self._embedder = embedder def _embed_chunk(self, text_chunk: TextChunk) -> TextChunk: """Embed a single text chunk. Args: text_chunk (TextChunk): The text chunk to embed. Returns: TextChunk: The text chunk with an added "embedding" key in its metadata containing the embeddings of the text chunk's text. """ embedding = self._embedder.embed_query(text_chunk.text) metadata = text_chunk.metadata if text_chunk.metadata else {} metadata["embedding"] = embedding return TextChunk( text=text_chunk.text, index=text_chunk.index, metadata=metadata )
[docs] @validate_call async def run(self, text_chunks: TextChunks) -> TextChunks: """Embed a list of text chunks. Args: text_chunks (TextChunks): The text chunks to embed. Returns: TextChunks: The input text chunks with each one having an added embedding. """ return TextChunks( chunks=[self._embed_chunk(text_chunk) for text_chunk in text_chunks.chunks] )