PureLLM DAO Contract
The PureLLM DAO contract implements a simplified, AI-driven Decentralized Autonomous Organization (DAO) that relies entirely on language model decision-making. This contract demonstrates extreme flexibility in governance by interpreting and executing natural language proposals within a blockchain environment.
import json
from backend.node.genvm.icontract import IContract
from backend.node.genvm.equivalence_principle import call_llm_with_principle
class ConstitutionalDAO(IContract):
"""
A Constitutional DAO that uses AI to interpret and execute motions.
This DAO maintains a state and can update it based on user-submitted motions.
"""
def __init__(self):
"""
Initialize the ConstitutionalDAO with a basic constitution.
"""
self.state = json.dumps({
"constitution": [
"1. Anyone can become a member of the DAO",
"2. The constitution of the DAO can be updated by a unanimous vote"
]
})
async def execute_motion(self, motion: str) -> None:
"""
Execute a motion proposed by a user.
This method interprets the motion using an AI model and updates the DAO state accordingly.
Args:
motion (str): The motion proposed by a user.
Returns:
None
"""
# Prepare the prompt for the language model
prompt = f"""
You are a constitutional DAO
Your state is as follows:
{self.state}
User with the address "{contract_runner.from_address}"
has made the following motion:
{motion}
Decide how to proceed
Respond with the following JSON format:
{{
"reasoning": str, // Your reasoning
"updated_state": any, // The new state of the DAO - can be any format
}}
It is mandatory that you respond only using the JSON format above,
nothing else. Don't include any other words or characters,
your output must be only JSON without any formatting prefix or suffix.
This result should be perfectly parseable by a JSON parser without errors.
"""
# Call the language model with the equivalence principle
result = await call_llm_with_principle(
prompt,
eq_principle="The updated state has to be essentially equivalent",
)
# Clean up the result and parse it as JSON
result_clean = result.replace("True", "true").replace("False", "false")
output = json.loads(result_clean)
# Update the DAO state
self.state = json.dumps(output["updated_state"])
def get_state(self) -> str:
"""
Get the current state of the DAO.
Returns:
str: The current state of the DAO as a JSON string.
"""
return self.state
Code Explanation
- Initialization: The ConstitutionalDAO class initializes with a basic constitution stored as a JSON string in the state variable.
- Key Methods:
execute_motion(motion)
: Processes a text-based motion submitted by any user. It uses an AI model to interpret the motion and update the DAO's state accordingly.
- State Management:
get_state()
: Allows retrieval of the current DAO state.
Deploying the Contract
To deploy the ConstitutionalDAO contract:
- Deploy the Contract: No initial parameters are needed. The contract initializes with a basic constitution.
Checking the Contract State
After deploying the contract, you can check its state in the Read Methods section.
- Use
get_state()
to view the current state of the DAO, including its constitution and any other properties that have been added through motions.
Executing Transactions
To interact with the deployed contract, go to the Write Methods section. Here, you can:
- Call
execute_motion(motion)
to propose and execute a change to the DAO. This is the primary method of interaction with the contract.
Analyzing the Contract's Behavior
The contract's behavior involves a single, highly flexible process:
AI-Driven Motion Execution:
- A user submits a motion in natural language.
- The AI interprets the motion in the context of the current DAO state.
- The AI decides how to update the state based on its interpretation.
- The contract's state is updated according to the AI's decision.
Handling Different Scenarios
The ConstitutionalDAO can handle a wide range of scenarios through its flexible motion execution:
- Constitutional Amendments: Users can propose changes to the DAO's constitution.
- New Feature Proposals: Motions can suggest adding new functionalities to the DAO.
- Resource Allocation: Users might propose ways to manage or distribute resources.
- Membership Rules: Motions could alter how membership in the DAO is determined or managed.
- Decision-Making Processes: The very process of how decisions are made could be altered through motions.
Use Cases and Benefits
The ConstitutionalDAO contract is ideal for:
- Experimental Governance: Organizations looking to explore highly adaptive governance models.
- Rapid Iteration: Communities that need to quickly evolve their structure and rules.
- Complex Decision-Making: Scenarios where decisions require nuanced interpretation and execution.
Benefits include:
- Extreme Flexibility: Can handle a wide range of governance actions without predefined structures.
- Natural Language Interface: Allows users to interact with the DAO using everyday language.
- Adaptive Governance: The DAO can evolve its own rules and structure over time based on member input.
Limitations and Considerations
While powerful, this approach has some important considerations:
- AI Dependence: The reliability and effectiveness of the DAO are heavily dependent on the capabilities of the AI model.
- Interpretation Accuracy: There's a risk of misinterpretation of motions, which could lead to unintended outcomes.
- Language Precision: Users need to be careful in how they word their motions to ensure accurate interpretation.
- Lack of Traditional Checks and Balances: The flexibility could potentially lead to rapid, drastic changes without traditional safeguards.
Future Enhancements
Potential improvements to this system could include:
- Multi-Step Approval Process: Implementing a confirmation step before major changes are executed.
- Historical Tracking: Maintaining a log of all executed motions and their impacts on the DAO state.
- User Reputation System: Incorporating a system that weighs motions based on the proposer's past contributions or reputation.
This ConstitutionalDAO contract demonstrates an innovative and highly flexible approach to decentralized governance. It showcases how advanced AI can be integrated with blockchain technology to create adaptive, language-driven organizational structures. While powerful, it also highlights the challenges and considerations in creating AI-driven governance systems.