# Python Intelligence (v30 Architecture)

This directory contains the modernized Python-based multi-agent system (`v30`), built around a Swarm/Mesh architecture.

## Overview

The `v30` architecture focuses on distributed, asynchronous intelligence. Agents communicate via a unified `NeuralMesh` using standardized `emit_packet` workflows.

### BaseAgent Implementations

All operational agents inherit from `BaseAgent` (`core/v30_architecture/python_intelligence/agents/base_agent.py`), which provides standardized telemetry and NeuralMesh integration. This standardized base class ensures that all agents, regardless of their specific domain (e.g., risk analysis, market scanning), can uniformly broadcast their state and findings.

**Usage Example:**
```python
from core.v30_architecture.python_intelligence.agents.base_agent import BaseAgent

class MyCustomAgent(BaseAgent):
    def __init__(self):
        super().__init__(name="CustomAgent01", role="Specialized Analyzer")

    async def execute_task(self, data):
        # Implement agent-specific logic here
        processed_data = data * 2

        # Asynchronously emit telemetry to the NeuralMesh
        await self.emit(packet_type="THOUGHT", payload={"status": "processing", "result": processed_data})
```

### NeuralMesh Interactions

The `NeuralMesh` (`core/v30_architecture/python_intelligence/bridge/neural_mesh.py`) handles real-time broadcasting and inter-agent communication via WebSockets.

**Usage Example:**
```python
from core.v30_architecture.python_intelligence.bridge.neural_mesh import NeuralPacket, emit_packet

packet = NeuralPacket(
    source_agent="RiskGuardian",
    packet_type="risk_alert",
    payload={"level": "high", "asset": "TSLA"}
)
await emit_packet(packet)
```

### emit_packet Workflows

The `emit_packet` function is the primary entry point for sending data into the NeuralMesh. It asynchronously dispatches `NeuralPacket` objects to all subscribed clients.