README.md

metadata

title: The Agora
emoji: 🌍
colorFrom: red
colorTo: blue
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: true
license: mit
short_description: Where artificial minds gather to forge wisdom

The Agora: Where artificial minds gather to forge wisdom

TRACK : mcp-server-track

🌟 Project Overview

Agora, also known as "AI Democracy," is an innovative Gradio-based server designed to foster collaborative decision-making among diverse large language models (LLMs).

Imagine an "AI Council" where specialized AI agents deliberate and vote on complex problems, providing reasoned arguments, highlighting disagreements, and ultimately arriving at a synthesized consensus.

This system transcends the limitations of single-model outputs by leveraging the unique strengths of various LLMs, making it perfect for scenarios demanding nuanced.

✨ Features

Multi-Model AI Council: Orchestrates a diverse panel of AI models, each playing a specific role:

• Anthropic Claude: Specialized in ethical considerations and moral reasoning.

• OpenAI GPT (e.g., GPT-4o): Excels in creative problem-solving and brainstorming novel solutions.

• Mistral: Focused on robust technical analysis and detailed breakdowns.

• Sambanova: Provides rapid, high-throughput inference and quick factual recall.

• Hyperbolic Labs (placeholder for specialized models): Integrated for highly specialized tasks or domain-specific knowledge.

• Orchestrated AI Debates: Facilitates structured dialogues and 'debates' between AI models, allowing them to present arguments and counter-arguments.

• Transparent Reasoning: Each model's individual reasoning, thought process, and initial stance are transparently displayed.

• Disagreement Highlight: Clearly identifies areas of disagreement between models, providing insights into differing perspectives.

• Final Consensus & Synthesis: Synthesizes the collective insights and votes into a consolidated, consensus-driven final answer.

• Gradio User Interface: Provides an intuitive and interactive web interface for users to submit problems and view the council's deliberations.

🚀 Workflow:

• How Agora Reaches Consensus:
  • Agora operates through a sophisticated, multi-stage process to transform a complex problem into a collective AI consensus.
  • The system acts as a Multi-Council Orchestration Protocol (MCP) server, managing the flow between the user interface and the various AI models.

Here's a conceptual workflow:

• User Problem Submission (Gradio UI):

IMAGE

A user submits a complex problem or query via the Gradio web interface. The input is typically a natural language prompt, potentially with accompanying data.

Image Description:

A screenshot of a Gradio interface with an input text box for the user's problem and a "Submit" button.

• Problem Parsing & Initial Distribution (MCP Orchestrator):

• The MCP Orchestrator (a custom backend server) receives the user's problem.

• It parses the input and determines the initial context for the AI Council.

Based on pre-defined roles, the orchestrator dispatches the problem to specific models or groups of models for initial analysis and proposals. For instance, Claude might get an ethical framing, GPT a creative angle, and Mistral a technical breakdown.

• A diagram showing the MCP Orchestrator sending the problem to multiple distinct AI models.

• Individual Model Reasoning & Proposals:

  • Each designated AI model processes the problem based on its specialty.

  • Models generate their initial solutions, ethical considerations, technical analyses, or creative approaches.

  • These individual outputs (including their 'reasoning' and 'confidence scores' if applicable) are sent back to the MCP Orchestrator.

Debate Orchestration (MCP Orchestrator): Everything happens at backend and Final winner response is displayed in frontend

The orchestrator initiates a multi-turn 'debate' or 'review' phase.

• Round 1 (Initial Review): Each model's proposal is shared (anonymously or attributed) with other relevant models.
• Round 2 (Rebuttal & Refinement): Models respond to critiques, refine their initial proposals, or adjust their positions.

Image Description: A visual representation of AI models exchanging arguments, possibly with arrows indicating flow of information and feedback loops.

• Voting & Consensus Formation:

  • After the debate rounds, the orchestrator prompts each AI model to "vote" on the most optimal solution or to provide a final, refined recommendation.

• A consensus algorithm (e.g., majority vote, weighted average based on model confidence/role importance, or a final synthesis by a designated 'moderator' AI) is applied to derive the final collective decision. Disagreements are explicitly logged.

Result Presentation (Gradio UI):

• The MCP Orchestrator sends the complete deliberation log, including:-

  • Each model's initial reasoning.

  • Key arguments and counter-arguments during the debate.

  • Areas of significant disagreement.

  • The final, synthesized consensus or voted-upon solution.

  • Gradio renders this information to the user in a clear, structured, and interactive format.

• A Gradio output screen showing a structured summary of the AI council's deliberation and the final consensus.

🛠️ Technologies Used

Frontend: Gradio (for interactive web interface)

Backend: Custom Python MCP Orchestrator (Flask/FastAPI recommended for server implementation)

AI Models (via APIs):

• Anthropic Claude

• OpenAI GPT (e.g., GPT-4o)

• Mistral AI

• Sambanova (or similar, e.g., via Hugging Face Inference API)

• Hyperbolic Labs (or other specialized custom models/APIs)

🎯 Potential Use Cases

• Medical Diagnoses: AI council reviewing patient data, lab results, and symptoms to propose the most likely diagnosis, considering ethical implications, treatment creativity, and technical accuracy.

• Legal Advice: Analyzing case details, precedents, and laws to provide comprehensive legal advice, weighing ethical considerations and strategic options.

• Business Strategy: Developing complex business plans, marketing strategies, or investment decisions by leveraging creative, analytical, and ethical AI perspectives.

• Scientific Research: Formulating hypotheses, designing experiments, and interpreting results across various scientific disciplines.

⚙️ Setup and Installation

1. Clone the repository:

git clone https://huggingface.co/spaces/Agents-MCP-Hackathon/TheAgora

cd .\TheAgora\

2. Install dependencies:

pip install -r requirements.txt

3. Run the MCP App:

python app.py

🤝 Contributing

Aditya Katkar
Github
LinkedIn