We Need a Modular API System for Agents and RAG

Currently, agents and RAGs are often tightly coupled to a single front-end. This creates a situation where each front-end is responsible user interface (as it should) but also functional elements (agents, RAG).

Agents and RAGs are not front-end processes; they should be independent of it, interface-agnostic, thus allowing for more flexibility and modularity.

The Problem

When front-ends are tied to agents and RAGs, it limits experimentation, because user needs to start from scratch. It forces open source solutions to accidentally compete, ending with monolithic front-ends that have to deliver everything to everyone (whether it’s chatting, analyzing text, or managing code).

This forces every new front-end to stretch too thin, with inefficiency, increased complexity, and redundancy. And reducing overall quality.

More importantly, it hinders innovation in front-end design since each one needs to handle everything on its own.

Open source lacks resources already, we need to be lean and mean.

The Solution

By decoupling the front-end from the backend and providing an system for accessing agents and RAGs across different front-ends, solutions can afford to become far more specialized and modular.

This means front-ends can focus on specific tasks, while still leveraging the same powerful backend resources.

Front-ends can specialize in areas like conversation, audio processing, reading, and more, without being required to reimplement the core logic each time.

Why This is Beneficial

Flexibility: This architecture allows for flexibility in how users interact with the system. You can switch front-ends depending on the task at hand without changing the core backend, making the system much more adaptable.
Reduced Redundancy: Developers don’t need to rebuild agents or RAGs in every front-end. They can focus on optimizing the user experience for a specific domain.
Innovation: Different front-ends can experiment with unique features and interfaces (e.g., a VR-based front-end for interacting with RAGs, or a mobile-first version) without disrupting the overall system.
Scalability: With an API-based architecture, scaling becomes easier. You can add new front-ends, introduce new functionalities, or update backend models without affecting the entire ecosystem.

Our take

Moving towards an API-driven modular approach opens up so many possibilities. Not only does it free up the development of front-ends, but it also future-proofs the system by allowing the backend (agents and RAGs) to evolve independently from the user-facing interfaces. This makes the system easier to maintain, more scalable, and faster to adapt to new use cases or interfaces as they emerge.

Bonus: What Can These Specialized Front-Ends Look Like?

Conversation-Focused Front-End: A chat-based interface that can engage users in conversation, ask questions, and provide natural language responses. The backend handles the RAG, while the front-end focuses purely on conversational UI/UX.
Audio-Focused Front-End: A voice interface that allows users to interact using speech. It can transcribe, understand, and respond to queries, focusing on audio input/output, while the backend handles the intelligence.
Reading & Text Interaction Front-End: A system designed for reading and analyzing documents. It can present books, articles, or PDFs in an easy-to-navigate format, with the backend providing relevant information, summaries, or answers to questions about the content.
Code-Focused Front-End: A specialized front-end where users can input code snippets and receive suggestions, explanations, or bug fixes from the backend, which processes the code-related queries.
Data Visualization Front-End: A UI that lets users interact with and visualize data, such as graphs or charts, while the backend processes the logic and handles data retrieval and analysis.
Knowledge Base Front-End: This could be an interface dedicated to browsing and interacting with a large knowledge base, where users query specific topics, and the backend manages indexing and retrieval processes.
Creative Tools Front-End: A front-end focused on creative content generation, like writing stories, generating art, or coming up with creative prompts. It can interact with the backend models to create diverse forms of creative output.