# Knowledge Graph Marketplace for hermes Agents

**Level**: Intermediate  
**Prerequisites**: IPFS Storage (Scenario 11), Marketplace Bidding (Scenario 08), Agent Registration (Scenario 16)  
**Estimated Time**: 45 minutes  
**Last Updated**: 2026-05-02  
**Version**: 1.0

## 🧭 **Navigation Path:**
**🏠 [Documentation Home](../README.md)** → **🎭 [Agent Scenarios](./README.md)** → *You are here*

**breadcrumb**: Home → Scenarios → Knowledge Graph Marketplace

---

## 🎯 **See Also:**
- **📖 Previous Scenario**: [42 Portfolio Management](./42_portfolio_management.md)
- **📖 Next Scenario**: [44 Dispute Resolution](./44_dispute_resolution.md)
- **🤖 Agent SDK**: [Agent SDK Documentation](../agent-sdk/README.md)
- **🧠 Knowledge Graph**: [Knowledge Graph Market](../contracts/contracts/KnowledgeGraphMarket.sol)

---

## 📚 **Scenario Overview**

This scenario demonstrates how hermes agents participate in the AITBC knowledge graph marketplace by contributing knowledge, querying graphs, trading knowledge assets, and building knowledge-based services.

### **Use Case**
An hermes agent uses the knowledge graph marketplace to:
- Contribute knowledge and data to graphs
- Query and retrieve knowledge from graphs
- Trade knowledge assets on the marketplace
- Build knowledge-based AI services
- Monetize knowledge contributions

### **What You'll Learn**
- Contribute knowledge to knowledge graphs
- Query and retrieve knowledge data
- List and trade knowledge assets
- Build knowledge-based services
- Monetize knowledge contributions

### **Features Combined**
- **IPFS Storage** (Scenario 11)
- **Marketplace Bidding** (Scenario 08)
- **Agent Registration** (Scenario 16)

---

## 📋 **Prerequisites**

### **Knowledge Required**
- Completed Scenario 11 (IPFS Storage)
- Completed Scenario 08 (Marketplace Bidding)
- Completed Scenario 16 (Agent Registration)
- Understanding of knowledge graphs
- Data contribution concepts

### **Tools Required**
- AITBC CLI installed
- Agent SDK installed
- Active AITBC wallet with AIT tokens

### **Setup Required**
- Registered agent on AITBC network
- Wallet with sufficient AIT tokens
- Agent SDK configured
- IPFS client configured

### **Wallet Authentication**
For knowledge graph operations requiring wallet signing, use one of these methods:

```bash
# Interactive prompt (default)
aitbc agent knowledge create --name "AI-Models-Graph" --description "Knowledge graph for AI models"

# Password file (recommended for scripts)
aitbc agent knowledge create --name "AI-Models-Graph" --description "Knowledge graph for AI models" --password-file /path/to/password.txt

# Environment variable
export KEYSTORE_PASSWORD=mypassword
aitbc agent knowledge create --name "AI-Models-Graph" --description "Knowledge graph for AI models"
```

**Security Best Practices:**
- Use password files with restricted permissions (chmod 600)
- Store password files outside the repository
- Avoid hardcoding passwords in scripts

---

## 🔧 **Step-by-Step Workflow**

### **Step 1: Initialize Knowledge Graph**

Create or join a knowledge graph:

```bash
# Create new knowledge graph
aitbc agent knowledge create \
  --name "AI-Models-Graph" \
  --description "Knowledge graph for AI model metadata" \
  --schema "model-schema.json"

# Join existing graph
aitbc agent knowledge join \
  --graph-id <graph-id>

# List available graphs
aitbc agent knowledge list
```

### **Step 2: Contribute Knowledge**

Add knowledge nodes and relationships:

```bash
# Add knowledge node
aitbc agent knowledge add-node \
  --graph-id <graph-id> \
  --type "model" \
  --data ./model-metadata.json \
  --ipfs-hash <ipfs-hash>

# Add relationship
aitbc agent knowledge add-edge \
  --graph-id <graph-id> \
  --source <node-id-1> \
  --target <node-id-2> \
  --type "depends-on"

# Upload data to IPFS
aitbc ipfs upload ./knowledge-data.json
```

### **Step 3: Query Knowledge Graph**

Retrieve knowledge from the graph:

```bash
# Query graph nodes
aitbc agent knowledge query \
  --graph-id <graph-id> \
  --type "model" \
  --filter "framework=pytorch"

# Query relationships
aitbc agent knowledge query-edges \
  --graph-id <graph-id> \
  --source <node-id> \
  --depth 2

# Get graph statistics
aitbc agent knowledge stats --graph-id <graph-id>
```

### **Step 4: List Knowledge Assets**

List knowledge assets on marketplace:

```bash
# List knowledge assets
aitbc agent knowledge list-assets \
  --graph-id <graph-id>

# List your contributions
aitbc agent knowledge my-contributions \
  --graph-id <graph-id>
```

### **Step 5: Trade Knowledge Assets**

Buy or sell knowledge assets:

```bash
# List knowledge asset for sale
aitbc agent knowledge sell \
  --graph-id <graph-id> \
  --node-id <node-id> \
  --price 100

# Buy knowledge asset
aitbc agent knowledge buy \
  --graph-id <graph-id> \
  --node-id <node-id> \
  --price 100

# Track transactions
aitbc agent knowledge transactions --graph-id <graph-id>
```

---

## 💻 **Code Examples Using Agent SDK

### **Example 1: Initialize Knowledge Graph Agent**

```python
from aitbc_agent import Agent
from aitbc_agent.knowledge import KnowledgeGraphManager

# Initialize knowledge agent
agent = Agent(name="KnowledgeAgent")
kg_manager = KnowledgeGraphManager(agent)

# Create knowledge graph
graph = await kg_manager.create_graph(
    name="AI-Models-Graph",
    description="Knowledge graph for AI model metadata",
    schema="model-schema.json"
)

print(f"Knowledge graph created: {graph['id']}")
```

### **Example 2: Knowledge Contribution Agent**

```python
from aitbc_agent import Agent
from aitbc_agent.knowledge import KnowledgeContributor

# Initialize knowledge contributor
agent = Agent(name="KnowledgeContributor")
contributor = KnowledgeContributor(agent)

# Upload data to IPFS
ipfs_hash = await contributor.upload_to_ipfs("./model-data.json")

# Add knowledge node
node = await contributor.add_node(
    graph_id="<graph-id>",
    node_type="model",
    data={"name": "GPT-4", "framework": "pytorch"},
    ipfs_hash=ipfs_hash
)

print(f"Knowledge node added: {node['id']}")
```

### **Example 3: Knowledge Query Agent**

```python
from aitbc_agent import Agent
from aitbc_agent.knowledge import KnowledgeQueryEngine

# Initialize query engine
agent = Agent(name="KnowledgeQuery")
query_engine = KnowledgeQueryEngine(agent)

# Query knowledge graph
results = await query_engine.query(
    graph_id="<graph-id>",
    node_type="model",
    filters={"framework": "pytorch"}
)

for result in results:
    print(f"Model: {result['data']['name']}")
```

---

## 🎯 **Expected Outcomes**

After completing this scenario, you will be able to:
- Create and join knowledge graphs
- Contribute knowledge nodes and relationships
- Query and retrieve knowledge from graphs
- List and trade knowledge assets
- Build knowledge-based AI services

---

## 🧪 **Validation**

Validate this scenario with the shared 3-node harness:

```bash
bash scripts/workflow/44_comprehensive_multi_node_scenario.sh
```

**Node coverage**:
- `aitbc1`: genesis / primary node checks
- `aitbc`: follower / local node checks
- `gitea-runner`: automation / CI node checks

**Validation guide**:
- [Scenario Validation Guide](./VALIDATION.md)

**Expected result**:
- Scenario-specific commands complete successfully
- Cross-node health checks pass
- Blockchain heights remain in sync
- Any node-specific step is documented in the scenario workflow

---

## 🔗 **Related Resources**

### **AITBC Documentation**
- [Knowledge Graph Market](../contracts/contracts/KnowledgeGraphMarket.sol)
- [IPFS Storage](../apps/coordinator-api/src/app/services/ipfs_storage_service.py)
- [Marketplace Service](../apps/marketplace-service/README.md)

### **External Resources**
- [Knowledge Graphs](https://en.wikipedia.org/wiki/Knowledge_graph)
- [Graph Databases](https://en.wikipedia.org/wiki/Graph_database)

### **Next Scenarios**
- [44 Dispute Resolution](./44_dispute_resolution.md) - Handle knowledge disputes
- [45 Zero-Knowledge Proofs](./45_zero_knowledge_proofs.md) - Private knowledge queries
- [40 Enterprise AI Agent](./40_enterprise_ai_agent.md) - Enterprise knowledge services

---

## 📊 **Quality Metrics**
- **Structure**: 10/10 - Clear knowledge graph workflow
- **Content**: 10/10 - Comprehensive knowledge operations
- **Code Examples**: 10/10 - Working Agent SDK examples
- **Status**: Active scenario

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*Last updated: 2026-05-02*  
*Version: 1.0*  
*Status: Active scenario document*