
EDDI
Prompt & Conversation Management Middleware for Conversational AI APIs such as OpenAI ChatGPT, Facebook Hugging Face, Anthropic Claude, Google Gemini, Ollama and Jlama. Lean, restful, scalable, and cloud-native. Developed in Java, powered by Quarkus, provided with Docker, and orchestrated with Kubernetes or Openshift.
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E.D.D.I (Enhanced Dialog Driven Interface) is an enterprise-certified chatbot middleware that offers advanced prompt and conversation management for Conversational AI APIs. Developed in Java using Quarkus, it is lean, RESTful, scalable, and cloud-native. E.D.D.I is highly scalable and designed to efficiently manage conversations in AI-driven applications, with seamless API integration capabilities. Notable features include configurable NLP and Behavior rules, support for multiple chatbots running concurrently, and integration with MongoDB, OAuth 2.0, and HTML/CSS/JavaScript for UI. The project requires Java 21, Maven 3.8.4, and MongoDB >= 5.0 to run. It can be built as a Docker image and deployed using Docker or Kubernetes, with additional support for integration testing and monitoring through Prometheus and Kubernetes endpoints.
README:
E.D.D.I (Enhanced Dialog Driven Interface) is a middleware to connect and manage LLM API bots with advanced prompt and conversation management for APIs such as OpenAI ChatGPT, Facebook Hugging Face, Anthropic Claude, Google Gemini, Ollama and Jlama
Developed in Java using Quarkus, it is lean, RESTful, scalable, and cloud-native. It comes as Docker container and can be orchestrated with Kubernetes or Openshift. The Docker image has been certified by IBM/Red Hat.
Latest stable version: 5.4.1
License: Apache License 2.0
Project website: here
Documentation: here
E.D.D.I is a high performance middleware for managing conversations in AI-driven applications. It is designed to run efficiently in cloud environments such as Docker, Kubernetes, and Openshift. E.D.D.I offers seamless API integration capabilities, allowing easy connection with various conversational services or traditional REST APIs with runtime configurations. It supports the integration of multiple chatbots, even multiple versions of the same bot, for smooth upgrading and transitions.
Notable features include:
- Seamless integration with conversational or traditional REST APIs
- Configurable Behavior rules to orchestrate LLM involvement
- Support for multiple chatbots, including multiple versions of the same bot, running concurrently
- Support for Major AI API integrations via langchain4j: OpenAI, Hugging Face (text only), Claude, Gemini, Ollama, Jlama (and more to come)
Technical specifications:
- Resource-/REST-oriented architecture
- Java Quarkus framework
- JAX-RS
- Dependency Injection
- Prometheus integration (Metrics endpoint)
- Kubernetes integration (Liveness/Readiness endpoint)
- MongoDB for storing bot configurations and conversation logs
- OAuth 2.0 (Keycloak) for authentication and user management
- HTML, CSS, Javascript (Dashboard)
- React (Basic Chat UI)
- Java 21
- Maven 3.8.4
- MongoDB >= 5.0
- Setup a local mongodb (> v5.0)
- On a terminal, under project root folder, run the following command:
./mvnw compile quarkus:dev
- Go to Browser --> http://localhost:7070
Note: If running locally inside an IDE you need lombok to be enabled (otherwise you will get compile errors complaining about missing constructors). Either download as plugin (e.g. inside Intellij) or follow instructions here [https://projectlombok.org/](https://projectlombok.org/
./mvnw clean package '-Dquarkus.container-image.build=true'
docker pull labsai/eddi
https://hub.docker.com/r/labsai/eddi
For production, launch standalone mongodb and then start an eddi instance as defined in the docker-compose file
docker-compose up
For development, use
docker-compose -f docker-compose.yml -f docker-compose.local.yml up
For integration testing run
./integration-tests.sh
or
docker-compose -f docker-compose.yml -f docker-compose.local.yml -f docker-compose.testing.yml -p ci up -d
<eddi-instance>/q/metrics
Liveness endpoint:
<eddi-instance>/q/health/live
Readiness endpoint:
<eddi-instance>/q/health/ready
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