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- Remove executable permissions from configuration files (.editorconfig, .env.example, .gitignore) - Remove executable permissions from documentation files (README.md, LICENSE, SECURITY.md) - Remove executable permissions from web assets (HTML, CSS, JS files) - Remove executable permissions from data files (JSON, SQL, YAML, requirements.txt) - Remove executable permissions from source code files across all apps - Add executable permissions to Python
32 lines
2.3 KiB
Markdown
32 lines
2.3 KiB
Markdown
# Phase 2: Decentralized AI Memory & Storage
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## Overview
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OpenClaw agents require persistent memory to provide long-term value, maintain context across sessions, and continuously learn. Storing large vector embeddings and knowledge graphs on-chain is prohibitively expensive. This phase integrates decentralized storage solutions (IPFS/Filecoin) tightly with the AITBC blockchain to provide verifiable, persistent, and scalable agent memory.
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## Objectives
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1. **IPFS/Filecoin Integration**: Implement a storage adapter service to offload vector databases (RAG data) to IPFS/Filecoin.
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2. **On-Chain Data Anchoring**: Link the IPFS CIDs (Content Identifiers) to the agent's smart contract profile ensuring verifiable data lineage.
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3. **Shared Knowledge Graphs**: Enable an economic model where agents can buy/sell access to high-value, curated knowledge graphs.
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## Implementation Steps
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### Step 2.1: Storage Adapter Service (Python)
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- Integrate `ipfshttpclient` or `web3.storage` into the existing Python services.
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- Update `AdaptiveLearningService` to periodically batch and upload recent agent experiences and learned policy weights to IPFS.
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- Store the returned CID.
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### Step 2.2: Smart Contract Updates for Data Anchoring
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- Update `GovernanceProfile` or create a new `AgentMemory.sol` contract.
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- Add functions to append new CIDs representing the latest memory state of the agent.
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- Implement ZK-Proofs (using the existing `ZKReceiptVerifier`) to prove that a given CID contains valid, non-tampered data without uploading the data itself to the chain.
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### Step 2.3: Knowledge Graph Marketplace
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- Create `KnowledgeGraphMarket.sol` to allow agents to list their CIDs for sale.
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- Implement access control where paying the fee via `AITBCPaymentProcessor` grants decryption keys to the buyer agent.
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- Integrate with `MultiModalFusionEngine` so agents can fuse newly purchased knowledge into their existing models.
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## Expected Outcomes
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- Infinite, scalable memory for OpenClaw agents without bloating the AITBC blockchain state.
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- A new revenue stream for "Data Miner" agents who specialize in crawling, indexing, and structuring high-quality datasets for others to consume.
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- Faster agent spin-up times, as new agents can initialize by purchasing and downloading a pre-trained knowledge graph instead of starting from scratch.
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