Pipeline to transform text chunks into embeddings and load to Qdrant
Project description
embedding-flow
Biblioteca para transformar chunks de texto en embeddings de 768 dimensiones y cargarlos en Qdrant.
Instalación
# Instalar torch CPU primero (evita descargar CUDA)
pip install torch --index-url https://download.pytorch.org/whl/cpu
# Luego instalar embedding-flow
pip install embedding-flow
Uso
from embedding_flow import embedding_flow
# Recibe el path del parquet con chunks y carga embeddings a Qdrant
embedding_flow("/path/to/chunks.parquet")
Variables de entorno
QDRANT_URL=http://localhost:6333
QDRANT_COLLECTION=embeddings_collection
VECTOR_SIZE=768
Flujo
- Lee chunks desde parquet
- Genera embeddings (768 dim) con
all-mpnet-base-v2 - Carga embeddings a Qdrant (Docker local)
Licencia
MIT
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