For search and generative AI projects, the Search & Generative AI orchestration framework 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 (Search 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, "did you mean", search analytics. etc. It also contains many useful user interface components for generative AI, such as content comparison, semantic search, question-answer, and a “chatty” an assistant (e.g. chat-bot like) interactive dialog interface.
It allows integration with Saga to enable the usage of On-prem language models as well as all of the out of the box Saga NLP algorithms to process natural language content.Vector
It allows to calculate embedding vector from the query for semantic search, it can be used with Saga or directly with models like: Open AI and Sentence Transformer GTR.
Use Azure OpenAI chat-completion models (like gpt-35-turbo or ChatGPT) to answering user requests and queries with summaries, content classification, data extraction, etc. You design and configure the prompts and include whatever metadata or content from the user query to generate answers.
It is the executor of the semantic search in the search engine to fetch relevant data that could provide context for the prompt creation.
UseCases
It will flatten the user interface
Computers will be expected to do much more complex, end-to-end tasks
The search box now becomes the single-most critical user interface component
Expectations on language understanding will grow dramatically
Click here to see available Generative AI components
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Search API GAIA although it is a very complete template, it is NOT a final projectproduct that solves a specific problem. Its main objective is to speed up the initial process of creating a projectan 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. |
Documentation: https://contentanalytics.digital.accenture.com/display/SEARCHAPI
Source Code: https://source.digital.accenture.com/projects/ST/repos/searchgaia-api/browse
Search GAIA API is the new successor of the Enterprise Search UI, an API framework built with Python 3.911+
The key features are:
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
Built-In Documentation: API via Swagger and configuration data via Pydantic
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