dda703de10
✅ v0.2 Release Preparation: - Update version to 0.2.0 in pyproject.toml - Create release build script for CLI binaries - Generate comprehensive release notes ✅ OpenClaw DAO Governance: - Implement complete on-chain voting system - Create DAO smart contract with Governor framework - Add comprehensive CLI commands for DAO operations - Support for multiple proposal types and voting mechanisms ✅ GPU Acceleration CI: - Complete GPU benchmark CI workflow - Comprehensive performance testing suite - Automated benchmark reports and comparison - GPU optimization monitoring and alerts ✅ Agent SDK Documentation: - Complete SDK documentation with examples - Computing agent and oracle agent examples - Comprehensive API reference and guides - Security best practices and deployment guides ✅ Production Security Audit: - Comprehensive security audit framework - Detailed security assessment (72.5/100 score) - Critical issues identification and remediation - Security roadmap and improvement plan ✅ Mobile Wallet & One-Click Miner: - Complete mobile wallet architecture design - One-click miner implementation plan - Cross-platform integration strategy - Security and user experience considerations ✅ Documentation Updates: - Add roadmap badge to README - Update project status and achievements - Comprehensive feature documentation - Production readiness indicators 🚀 Ready for v0.2.0 release with agent-first architecture
31 lines
2.2 KiB
Markdown
31 lines
2.2 KiB
Markdown
# Phase 1: OpenClaw Autonomous Economics
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## Overview
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This phase aims to give OpenClaw agents complete financial autonomy within the AITBC ecosystem. Currently, users must manually fund and approve GPU rentals. By implementing autonomous agent wallets and bidding strategies, agents can negotiate their own compute power dynamically based on the priority of the task they are given.
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## Objectives
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1. **Agent Wallet & Micro-Transactions**: Equip every OpenClaw agent profile with a secure, isolated smart contract wallet (`AgentWallet.sol`).
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2. **Bid-Strategy Engine**: Develop Python services that allow agents to assess the current marketplace queue and bid optimally for GPU time.
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3. **Multi-Agent Orchestration**: Allow a single user prompt to spin up a "Master Agent" that delegates sub-tasks to "Worker Agents", renting optimal hardware for each specific sub-task.
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## Implementation Steps
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### Step 1.1: Smart Contract Upgrades
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- Create `AgentWallet.sol` derived from OpenZeppelin's `ERC2771Context` for meta-transactions.
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- Allow users to set daily spend limits (allowances) for their agents.
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- Update `AIPowerRental.sol` to accept signatures directly from `AgentWallet` contracts.
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### Step 2.1: Bid-Strategy Engine (Python)
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- Create `src/app/services/agent_bidding_service.py`.
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- Implement a reinforcement learning model (based on our existing `advanced_reinforcement_learning.py`) to predict the optimal bid price based on network congestion.
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- Integrate with the `MarketplaceGPUOptimizer` to read real-time queue depths.
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### Step 3.1: Task Delegation & Orchestration
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- Update the `OpenClaw Enhanced Service` to parse complex prompts into DAGs (Directed Acyclic Graphs) of sub-tasks.
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- Implement parallel execution of sub-tasks by spawning multiple containerized agent instances that negotiate independently in the marketplace.
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## Expected Outcomes
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- Agents can run 24/7 without user approval prompts for every transaction.
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- 30% reduction in average task completion time due to optimal sub-task hardware routing (e.g., using cheap CPUs for text formatting, expensive GPUs for image generation).
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- Higher overall utilization of the AITBC marketplace as agents automatically fill idle compute slots with low-priority background tasks.
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