AOSSIE-Org / AOSSIE-Org/DebateAI

Feature Proposal: Multi-LLM Support for Redundancy, Cost Optimization, and User Selection

Abierto
#186 0 comentarios 0 reacciones 0 asignados Ver en GitHub
Lenguaje dominante
TypeScript
Estrellas
84
Forks
198
Merge medio
2 d 19 h
PR fusionados (30 d)
30

Descripción

Description

Currently, DebateAI relies on a single LLM provider for AI-powered debates. This creates potential risks related to availability, rate limits, token constraints, and cost variability. A single-provider dependency may also limit future extensibility and experimentation.

Solution

I propose introducing a provider-agnostic Multi-LLM architecture that allows DebateAI to integrate and switch between multiple Large Language Model (LLM) providers.

Key aspects of the proposed solution:

Abstract the LLM logic behind a common interface

Support multiple providers (e.g., Gemini, OpenAI, Claude, open-source LLMs)

Allow runtime selection of the LLM per debate room

Enable fallback mechanisms if a provider becomes unavailable

Why this is useful

Redundancy & Reliability: Ensures AI debate features remain available even if one provider fails or is rate-limited.

Cost Efficiency: Different models can be selected based on cost-per-token, reducing operational expenses.

Scalability: Enables usage of models with larger context windows for long-form debates.

Vendor Neutrality: Avoids lock-in and aligns with open-source sustainability principles.

Proposed High-Level Design

Introduce an LLM service layer/interface in the backend

Implement provider-specific adapters (e.g., GeminiAdapter, OpenAIAdapter)

Select provider based on configuration or user preference

Maintain graceful degradation to human-only debates if no LLM is configured

User Impact

Users can choose an LLM when creating or joining a debate room

Flexibility to switch between faster/cheaper models and more powerful models

No disruption to existing human-vs-human debate workflows

Additional Context

This feature aligns well with GSoC-style contributions, as it involves:

Backend architecture design

Clean abstractions

Extensibility for future contributors

Real-world scalability and cost considerations

I would be happy to work on this feature and discuss the design further with maintainers.

@Zahnentferner @keshav-nischal Assign this to me!!

Guía de contribución

No hay ninguna guía de contribución indexada para este repositorio

Evaluación

Este issue todavía no se ha evaluado.

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.