Query Agents

Query Agents serve as the foundational layer within DA3N's DeFAI Agent OS, acting as the bridge between natural language inputs and precise blockchain data retrieval and analysis. These agents are designed to interpret complex user queries, breaking them down into structured, machine-readable commands that interact with decentralized networks.

Beyond simple data retrieval, Query Agents are equipped with analytical capabilities that enable them to perform real-time data aggregation, trend analysis, and predictive modeling.

Query Agents are highly adaptable, capable of integrating with multiple blockchain protocols and ecosystems, ensuring compatibility across a wide range of decentralized platforms.

Natural Language to SQL Conversion

NLP Engine Architecture

Core Technology: GPT-4 based network

Processing Capabilities

// def natural_language_to_sql(query, blockchain_context):
    # Advanced NLP processing
    parsed_intent = analyze_query_intent(query)
    optimized_sql = generate_sql_query(parsed_intent, blockchain_context)
    return optimized_sql

Conversion Capabilities

1. Multi-language query support

2. Complex query interpretation

3. Domain-specific blockchain terminology understanding

Use Case Examples

Example 1: DeFi Token Analysis

Query: "Compare liquidity of top 5 DeFi tokens on Ethereum in last 30 days"

Example 2: Cross-Chain Comparison

Query: "Show total value locked for lending protocols on Ethereum and Polygon"

Request Parameters

Query Specification

// 
{
"prompt": "string, natural language query",
  "chains": ["ethereum", "polygon"],
  "context": {
    "time_range": "last_30_days",
    "asset_type": "defi_tokens",
    "minimum_liquidity": 1000000
 }
}

Parameter Details

• prompt: Natural language input

• chains: Target blockchain networks

• context: Additional query refinement

Response Formats

Standard Response Structure

// {
  "query_id": "unique_identifier",
  "optimized_sql": "generated_query_string",
  "results": [
    // Blockchain data results
  ],
  "metadata": {
    "confidence_score": 0.92,
    "execution_time": 0.3,
    "chains_queried": ["ethereum", "polygon"],
    "total_records": 157
  }
}

Response Components

1. Query Identifier: Unique tracking

2. Optimized SQL: Generated query

3. Results: Raw blockchain data

4. Metadata: Confidence scoring Performance metrics Queried network details