Swiss AI Hub Pipeline SDK: Dagster-based document ingestion, parsing, embedding, and vector storage for RAG.
Project description
Swiss AI Hub Pipeline
Data ingestion and processing SDK for the Swiss AI Hub platform. A Dagster-based, asset-oriented framework that turns documents into RAG-ready vectors.
- Two-stage architecture — source-specific ingestion (SharePoint, OneDrive, S3, local FS via rclone) into an S3-compatible data lake, then a unified parse → chunk → embed → store pipeline into Milvus and MongoDB.
- Factory pattern — compose pipelines from asset factories, resources, IO managers, and sensors.
- Lineage — every vector embedding traces back to its source document.
Installation
pip install swiss-ai-hub-pipeline
This pulls in swiss-ai-hub-core.
Usage
from swiss_ai_hub.pipeline import default_definitions
Links
- Source & issues: https://github.com/bbvch-ai/aihub-core
- Documentation: https://bbvch-ai.github.io/aihub-core/
License
Apache-2.0
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