Generative AI Application

Accenture Search & Content Analytics

For search and generative AI projects, the Search & Generative AI Application is composed of a collection of technology-independent components. These can help improve search & generative AI development for repeatable use cases, accelerate project timelines, and reduce overall project costs.

The framework provides a REST service created in Python (GAIA API) which is well documented with Swagger.  It has a pipeline architecture optimized for search and generative AI applications which makes it easy to customize functionality to handle complex generative AI requests through the addition or customization of individual stages.

The Search & Gen-AI user interface is the accompanying UI for the framework, made in React and having common functionality found in many search UIs like dynamic fields, facets, filtering, pagination, sorting, highlighting, type ahead, search analytics. etc. It also contains many useful user interface components for generative AI, such as content comparison, semantic search, question-answer, and an assistant (e.g. chat-bot like) interactive dialog interface.


Use Cases

It will flatten the user interface

  • The user will just type what they want.
  • This will replace multitudes of complex nested menus, tabs, dialogs and navigators.
  • New features can be implemented much more quickly and easily as independent plug-ins and add-ons.


Computers will be expected to do much more complex, end-to-end tasks

  • Users will want to be able to make complex, multi-step requests with natural language.
  • The computer will be expected to guide the user through those steps, prompting them along the way


The search box now becomes the single-most critical user interface component

  • It is, today, the only place where people enter text to get what they want.
  • It will become the first & primary method by which users interact with your application.


Expectations on language understanding will grow dramatically

  • Users will expect it to have human-like interactive capabilities.
  • This includes answering complex questions and helping you to achieve complex tasks.


Click here to see available Generative AI components


GAIA although it is a very complete template, it is NOT a final product that solves a specific problem. Its main objective is to speed up the initial process of creating an application. The code base is maintained, enhanced and delivered with multiple out of the box functionality, but it always requires initial configuration and probably customization.

GAIA API is the new successor of the Enterprise Search UI, an API framework built with Python 3.11+

The key features are:

  • Python 3.11+: Coded in Python, to reach a broader audience of programmers.
  • FastAPI: Web framework with a high performance, on par with NodeJS
  • Truly Engine Agnostic: Add new Non-SQL engines without disrupting the rest of the code

  • UI Independent: Worked without an UI, and generic enough to adapt one to it

  • Pipeline Framework: Execute complex process of functional modules, editable on runtime

  • True Http Endpoints: Enable E2E management of HTTP request for custom process

  • PyQPL: New PyQPL integrated for complex query generation (1.1.1)
  • Authentication: Local, LDAP, Delegated already implemented, more as demanded
  • Validation: Communication with the API with JWT for UI and API Keys, for S2S
  • Built-In Documentation: API via Swagger and configuration data via Pydantic

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