Aura –

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Mon, 01 Jan 0001 00:00:00 +0000

ATRIA application

Definition and role of applications in ATRIA

Introduction

Within ATRIA’s framework, an application is defined as an entity that allows the connection of a channel, service or skill with aura-gateway-api, the component in charge of managing the access to the different ATRIA capabilities.

ATRIA application

As a preliminary step for leveraging any ATRIA AI-driven capability, the use case constructor must configure an application, including different parameters:

To indicate which specific ATRIA capabilities are utilized in the use case.
In this framework, applications supported by ATRIA can be classified as follows:
- Applications that make use only of the NLP as a Service capabilities
- Applications that use Generative capabilities
- Applications that use RAG capabilities
The difference between Generative and RAG capabilities relies solely on the definition of the preset that is associated. But the same application can make use of one, several or all of these capabilities, combining their configuration.
Once the capabilities are selected, to set the required fields for its operation

For example, if we want to use Generative AI for the use case resolution, firstly, certain parameters must be set corresponding to:
- Establishing admin accesses.
- Setting the presets that the application can use, that is, the instructions to work with the AI model, that will be defined in the application configuration.

How to configure an application

An ATRIA application must be configured with specific parameters. For this purpose, follow the guidelines Configure an application in ATRIA, using the specific parameters for the ATRIA AI-driven technology to be used.

Example of application

This is a example of an application that makes use of NLPaaS, Generative and RAG capabilities:

    {
        "id": "8832550f-f03c-4e18-bdbe-7c6fc7adf5ff",
        "name": "app",
        "disabled": false,
        "brand": "0401",
        "nlp": {
            "channelId": "1234"
        },
        "models": {
            "level": "user",
            "presets": ["atria-rag-gpt-4", "generative-preset"]
        }
    }

Applications model

Common fields

Field name	Type	Description
id	string	Unique application identifier. UUID
name	string	Unique application name
brand	string	Identifier of the Telefónica Brand associated to the application. Available values in the document Telefónica brands management
disabled	boolean	Boolean value to enable or disable the application.

NLPaaS fields

Field name	Type	Description
nlp.channelId	string	Channel identifier used to call NLP

Generative/RAG fields

Field name	Type	Description
models.level	string	It indicates the level application in atria-model-gateway, meaning that it has specific access and control privileges. Default value `user`
models.presets	string[]	It indicates all the available ATRIA presets that the application can use. - Check the list of available presets by default - Learn here how to add a new preset or modify one

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

Aura Gateway API

Descriptive technical documentation regarding aura-gateway-api, an ATRIA component that provides an interface to expose different capabilities

Introduction

aura-gateway-api is a server in charge of the access to the different AI cognitive capabilities provided by ATRIA.

A channel, service or skill can send a request through an application (entity that enables the communication with aura-gateway-api). After passing through Kernel for authentication and security purposes, aura-gateway-api sends this request to the corresponding AI-driven technology for providing the most accurate response.

Currently, aura-gateway-api enables the access to ATRIA capabilities.

Associated documentation

Descriptive technical documentation regarding aura-gateway-api includes:

Guidelines for working with aura-gateway-api for the development of experiences, depending on the specific ATRIA capability:

Technical guidelines

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

ATRIA Model Gateway

Descriptive documentation regarding the ATRIA component atria-model-gateway

Introduction

atria-model-gateway is an ATRIA component in charge of managing the communication with different AI models.

Currently, this component receives a request from aura-gateway-api, together with other input data, and makes a call to the LLM/LMM Experiences Builder and use its capabilities.

atria-model-gateway is also in charge of security and privacy control and allows users to provide feedback on their experience.

If the selected AI model is RAG, then atria-model-gateway calls the atria-rag-server, which is in charge of executing the RAG chain and making the corresponding calls to the LLM models and databases.

The functional components of atria-model-gateway are described in the document LLM/LMM Experiences Builder

Associated documentation

Descriptive technical documentation regarding atria-model-gateway includes:

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

ATRIA Models Manager

Descriptive documentation regarding the ATRIA library atria-models-manager

Introduction

atria-models-manager is a ATRIA library responsible for managing all the models that we can use in the atria-model-gw model. The objective is for the atria.model-gw to only have to import the models from this component, avoiding defining the logic of the models in the atria-model-gw. For the first version, it will only feature Perplexity’s Sonar model, in the future, we will be able to migrate the atria-model-gw models here.

It contains all the logic necessary to call an LLM. Prompt construction, query tokenization, etc. It also contains all the definitions of the exceptions that an LLM can throw.

How to use it

To use the atria-models-manager, you need to install it in your Python environment and import the model into the code.

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

AURA GenAI Libs

Descriptive documentation regarding the ATRIA library aura-genai-libs

Introduction

aura-genai-libs is a ATRIA that contains common components for agent development, such as logs and the langchain call to the atria_model_gw service.

Includes the following modules:

logger module, whose purpose is to implement a callback handler to log the different stages of model, chain, and tool processing within the LangChain framework, integrating it with the AURA PyTraces logging system and the ATRIA Agents context. The module is based on the use of BaseCallbackHandler (langchain_core) and logs information at different stages of the execution cycle of language models (LLM), chats, chains, and tools. Each logged event uses m_headers.
chat_models module, which provides a custom implementation of the ChatOpenAI class from LangChain. This custom implementation is designed to facilitate the integration with the atria_model_gw service.

How to use it

To use the aura-genai-libs, you need to install it in your Python environment and import and use the module in your code.

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

ATRIA RAG Server

Descriptive documentation regarding the ATRIA component atria-rag-server

Introduction

atria-rag-server is an ATRIA component that manages a RAG-type server. It is called by atria-model-gateway when RAG (Retrieval Augmented Generation) is used.

atria-rag-server manages the request made to the RAG model following the predefined RAG chain (pipeline) and making continuous requests combining Generative AI technology (LLMs) with semantic and lexical searches to retrieve the required information.

Associated documentation

Descriptive technical documentation regarding atria-rag-server includes:

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

ATRIA RAG Generate DB

Descriptive documentation regarding the ATRIA component atria-rag-generate-db

Introduction

atria-rag-generate-db is an ATRIA component that manages a RAG-type database. This component is launched when you want to feed the document database for the first time or when you want to update the database with new information. See more information about these processes in the guidelines Import documents into ATRIA.

atria-rag-generate-db is in charge of handling the information coming from different sources and feeding the databases the RAG works with.

Associated documentation

Descriptive technical documentation regarding atria-rag-generate-db includes:

Launch atria-rag-generate-db

To launch atria-rag-generate-db, there are two suitable options:

Option 1

Send a request to the API for it to launch the atria-rag-generate-db. The endpoint responsible for this is:
/aura-services/v2/operations/data

curl -X POST "https://<your-atria-domain>/aura-services/v2/operations/data" \
-H "Content-Type: application/json"
-d '{
  "presetId": "<name of the project>"
}'

Option 2

Execute the following command to update the data in the environment. This command is in charge of launching the generation of the database for all the projects, but we can launch this generation for a specific project.

PROJECT='project-copilot-reduced'
kubectl patch configmap/atria-rag-generate-db-project --type merge -p "{\"data\":{\"ATRIA_PROJECT\":\"${PROJECT}\"}}" -n <namespace>
kubectl create job --from=cronjob/atria-rag-generate-db $(date +%Y%m%d%H%M%S)-atria-rag-generate-db-${PROJECT} -n <namespace>

(Change <namespace> by the specific one)

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

Agents Manager

Descriptive technical documentation regarding agents-manager, the server in charge of managing and orchestrating access to the different agents within the ATRIA ecosystem

Introduction

agents-manager is a server in charge of managing and orchestrating access to the different agents within the AURA ecosystem.

The main purpose of agents-manager is to facilitate orchestration between the different agents registered in ATRIA, also to enrich the conversation by managing the message history, before sending the requests to the agent responsible for their processing.

Associated documentation

Descriptive technical documentation regarding agents-manager includes:

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

Agents Server

Descriptive documentation regarding the component agents-server

Introduction

The agents-server component is a microservice that provides the capability to create server API and manage agents. It is responsible for executing the agent’s tasks.

To launch the agents-server component, you need install the agents package you prefer to use and deploy the server using this agents package.

Associated documentation

Descriptive technical documentation regarding agents-server includes:

Docs:

Mon, 01 Jan 0001 00:00:00 +0000

ATRIA APIs documentation

List of ATRIA APIs

Aura –

Docs:

ATRIA application

Introduction

How to configure an application

Example of application

Applications model

Common fields

NLPaaS fields

Generative/RAG fields

Docs:

Aura Gateway API

Introduction

Associated documentation

Docs:

ATRIA Model Gateway

Introduction

Associated documentation

Docs:

ATRIA Models Manager

Introduction

How to use it

Docs:

AURA GenAI Libs

Introduction

How to use it

Docs:

ATRIA RAG Server

Introduction

Associated documentation

Docs:

ATRIA RAG Generate DB

Introduction

Associated documentation

Launch atria-rag-generate-db

Docs:

Agents Manager

Introduction

Associated documentation

Docs:

Agents Server

Introduction

Associated documentation

Docs:

ATRIA APIs documentation

ATRIA APIs index