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sap-genai-hub-with-sap-hana-cloud-vector-engine

A hands-on workshop that works through SAP HANA Cloud's vector engine, SAP Generative AI Hub and the Python LangChain framework in one Jupyter notebook.

The workshop puts three pieces together and uses them on unstructured and semi-structured data: SAP HANA Cloud's vector engine, SAP Generative AI Hub and the Python LangChain framework. Setup runs in SAP Business Application Studio with the notebook the repository provides, installing hdbcli for the SAP HANA database connection, generative-ai-hub-sdk for calling models such as ChatGPT through the hub, and Folium for showing results on a map; the kernel needs a restart afterwards. It asks for an SAP HANA Cloud Introduction Academy or Basic Trial registration, and the repository does not accept community contributions.

GitHub20 ★

Facts

Last pushLicenceApache-2.0

Where it sits

Lives in
BTP/BAIP
Demonstrates
Retrieval-augmented generationBTPRetrieval-augmented generationcapabilityGrounding a model's answer in data retrieved at question time: text split into chunks, each chunk embedded as a vector, and the chunks nearest to the question placed into the prompt. Semantic search is the same retrieval with a person reading the matches, and fine-tuning changes the model's weights, not its input.
Requires
SAP HANA CloudSAP HANA Cloudartifactthe database whose vector engine the notebook works with, reached from Python through hdbcli; the README asks for an Introduction Academy or Basic Trial registration.

Who is behind it

SAP SamplesSAP SamplesOrganisationMaintains this
In the atlas: maintains 222@SAP-samplesmaintainerChris BezuidenhoutPersonContributes to this
In the atlas: contributes to 1@boefbrakJames FitzpatrickPersonContributes to this
In the atlas: contributes to 1@fitzgin2 contributors

What it declares

Every artifact

Type
Sample
Origin
By SAP
Use as
A reference

As a sample

Form
Workshop or CodeJam material

Connections2

README

quoted from SAP-samples/sap-genai-hub-with-sap-hana-cloud-vector-engine under Apache-2.0, read
SAP-samples/sap-genai-hub-with-sap-hana-cloud-vector-engine/README.mdOn GitHub

SAP HANA Cloud with Vector Engine and GenAI Hub

REUSE status

Description

In this use case, we will embark on a journey to explore the capabilities of SAP HANA Cloud vector engine, SAP Generative AI Hub and the Python Langchain Framework. The goal is to equip you with the knowledge and skills to handle unstructured and semi-structured data and build efficient applications.

Requirements

SAP HANA Cloud Introduction Academy or Basic Trial registration.

Setup and Installation

Beginning with setup via SAP Business Application Studio (BAS) and Jupyter notebook provided, execute the Python code installing libraries needed.

  • hdbcli

The Python Database API Specification v2.0 (PEP 249) defines a set of methods that provides a consistent database interface independent of the actual database being used. The Python extension module for SAP HANA implements PEP 249. Once you install the module, you can access and change the information in SAP HANA databases from Python.

  • generative-ai-hub-sdk

With this SAP python SDK you can leverage the power of generative Models like ChatGPT available in SAP Generative AI Hub.

  • Folium

Folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js library. Manipulate your data in Python, then visualize it in a Leaflet map via folium.

  • Generative AI Hub configuration

Configure client access to SAP BTP Generative AI foundation-models.


Note Jupyter Notebook kernel needs a restart after installation of libraries.


Known Issues

No known issues.

Contributing

We currently do not accept community contributions.

License

Copyright (c) 2024 SAP SE or an SAP affiliate company. All rights reserved. This project is licensed under the Apache Software License, version 2.0 except as noted otherwise in the LICENSE file.

Apache-2.0, read

Details

Sources3
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github.com/SAP-samples/sap-genai-hub-with-sap-hana-cloud-vector-enginetree, pushes, contributors, CIchecked
README.mdquoted, and what the entry declareschecked

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Compatibility and provenance
discovered viaAdded by hand
first seen in the atlas
ecosystem and domainbtp, ai-and-agents
Contributors2
Chris BezuidenhoutJames Fitzpatrick

From the repository’s contributor list, .

History in the atlas1
  1. First seen.
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