Spaces:
Sleeping
Sleeping
File size: 4,765 Bytes
0c591a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 | # A2A Researcher Agent Architecture
## Overview
The Researcher agent supports two modes:
- **Direct Mode** (default): Calls MCP servers directly from the main process
- **A2A Mode**: Delegates to a standalone A2A server for parallel data fetching
Enable A2A mode by setting `USE_A2A_RESEARCHER=true` in your environment.
## Architecture
```
┌─────────────────────────────────────────────────────────┐
│ Main Orchestrator (LangGraph) │
│ │
│ ┌──────────────────────────────────────────────────┐ │
│ │ Researcher Node │ │
│ │ (src/nodes/researcher.py) │ │
│ │ │ │
│ │ if USE_A2A_RESEARCHER: │ │
│ │ → A2A Client (researcher_a2a_client.py) │ │
│ │ else: │ │
│ │ → Direct MCP calls │ │
│ └──────────────────────────────────────────────────┘ │
│ │ │
│ │ JSON-RPC 2.0 over HTTP (A2A mode only) │
│ ↓ │
└───────┼─────────────────────────────────────────────────┘
│
┌───────┴─────────────────────────────────────────────────┐
│ Researcher A2A Server (optional, external) │
│ (a2a/researcher_server.py) │
│ │
│ Endpoints: │
│ - GET /.well-known/agent.json (Agent Card) │
│ - POST / (JSON-RPC: message/send, tasks/get) │
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ Financials │ │ Sentiment │ │ News │ ... │
│ │ MCP Server │ │ MCP Server │ │ MCP Server │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
└─────────────────────────────────────────────────────────┘
```
## A2A Protocol
A2A (Agent-to-Agent) is Google's open protocol for agent interoperability.
Reference: https://github.com/google-a2a/A2A
### Agent Card
Served at `/.well-known/agent.json`:
```json
{
"name": "swot-researcher",
"version": "1.0.0",
"description": "Financial research agent for SWOT analysis",
"capabilities": {
"streaming": false,
"pushNotifications": false
},
"skills": [{
"id": "research-company",
"name": "Company Research",
"inputModes": ["text"],
"outputModes": ["text", "data"]
}]
}
```
### JSON-RPC Methods
| Method | Description |
|--------|-------------|
| `message/send` | Submit research task |
| `tasks/get` | Get task status/results |
| `tasks/cancel` | Cancel running task |
### Task Lifecycle
```
SUBMITTED → WORKING → COMPLETED
↘ FAILED
```
## File Structure
```
a2a/
├── researcher_server.py # A2A server implementation
├── agent_card.json # Agent capabilities metadata
└── mcp_aggregator.py # Calls MCP servers in parallel
src/nodes/
├── researcher.py # Mode switch (A2A vs Direct)
└── researcher_a2a_client.py # A2A client wrapper
```
## Benefits of A2A Mode
| Aspect | Direct Mode | A2A Mode |
|--------|-------------|----------|
| Latency | Sequential MCP calls | Parallel MCP calls |
| Scaling | Coupled with orchestrator | Independent scaling |
| Fault Isolation | Shared process | Separate process |
| Reusability | Single workflow | Any A2A client |
## Fallback Behavior
If the A2A server is unavailable, the system falls back to direct mode automatically.
|