LLM Consortium
Orchestrate multiple LLMs, iteratively refine & achieve consensus through structured dialogue and evaluation.
Powered by Solana blockchain for transparent and verifiable AI decisions
Core Features
Harness the power of multiple language models with blockchain security
Multi-Model Orchestration
Coordinate multiple LLMs with blockchain verification
Iterative Refinement
Auto-refine responses through consensus tracking
Advanced Arbitration
Synthesize responses with on-chain verification
SYNTH Agent
Your AI orchestration agent powered by blockchain technology
Follow @AgentSynth07Multi-Model Orchestration
Coordinates responses from multiple LLMs to reach optimal solutions through structured dialogue
Blockchain Verification
Every decision and consensus is recorded on Solana for complete transparency
Advanced Arbitration
Uses specialized models to evaluate and synthesize responses for optimal results
Example Usage:
from llm_consortium import Synth
# Initialize SYNTH agent
agent = Synth(
models=["gpt-4", "claude-3", "gemini-pro"],
consensus_threshold=0.8,
blockchain_verification=True
)
# Process a complex query
result = await agent.process(
query="Analyze the impact of AI on healthcare",
max_iterations=3
)
print(f"Consensus Score: {result.consensus_score}")
print(f"Verified Hash: {result.blockchain_hash}")$SYNTH Token
As an open-source project, SYNTH token enables community governance and sustainable development while maintaining our commitment to transparency and decentralization.
1,000,000,000 SYNTH
Total Supply
Solana
Network
Contract Address: TBA
Community Governance
Token holders can participate in key decisions about the project's development and future features
Open Source Development
Token proceeds fund continued open-source development and community initiatives
Network Security
Staking SYNTH helps secure the network and validate AI consensus decisions
Open Source
LLM Consortium is open source and available on GitHub. Join our community of contributors!
Repository
# Initialize a consortium
llm consortium init \
--models gpt-4,claude-3,gemini-pro \
--confidence 0.8
# Run a query
llm consortium "Analyze the impact of AI on healthcare"Documentation
Everything you need to know about using LLM Consortium.
Multi-Model Orchestration
Coordinate responses from multiple LLMs simultaneously
Iterative Refinement
Automatically refine responses through multiple rounds
Advanced Arbitration
Uses a designated arbiter model to synthesize responses
Installation
# Using uv
uv tool install llm
# Using pipx
pipx install llm
llm install llm-consortiumBasic Usage
# Simple query
llm consortium "What are the key considerations for AGI safety?"
# Advanced usage with options
llm consortium "Your complex query" \
--models claude-3,gpt-4,gemini-pro \
--confidence 0.8 \
--max-iterations 3Configuration
{
"models": ["gpt-4", "claude-3", "gemini-pro"],
"confidence_threshold": 0.8,
"max_iterations": 3,
"arbiter_model": "claude-3-opus"
}