[Consensus Engine] Implement Pluggable Interface for Custom Consensus Algorithms

[dineshpinto]

• Description:
  Design and implement a pluggable interface within the Consensus Engine that allows for the integration of various consensus methodologies. The system should provide a suite of standard consensus algorithms out-of-the-box (e.g., majority voting, weighted averaging, confidence-based scoring, potentially LLM-based aggregation) and enable developers to easily add custom consensus strategies tailored to specialized use-cases.
• Acceptance Criteria:
  • At least two standard consensus algorithms (e.g., majority voting, weighted averaging based on agent-provided confidence) are implemented and available.
  • A clear, well-documented interface (e.g., an abstract base class) for defining and registering custom consensus algorithms is provided.
  • The Consensus Engine can dynamically select and use different consensus algorithms based on configuration, task type, or other criteria.
• Key Files/Modules Involved (Tentative):
  • flare_ai_kit/consensus/library/
• Tasks / Implementation Steps:
  • Define an abstract base class in flare_ai_kit/consensus/library/base.py.
  • Use existing implementations in confidence_ranking.py, majority.py and weighted_average.py as examples when defining the base class methods.

[tasneemtoolba]

I'm very interested, already started to read about the consensus layer, and would love to get more experience

[tasneemtoolba]

Hello @dineshpinto, I'll try to make a progress on this issue today! and send a daily updates! so sorry for this confusion, didn't know I got assigned to the issue!