Advanced Patterns
🎯 Purpose: Explore cutting-edge ADK capabilities for real-time interaction, standardized protocols, and distributed agent systems.
📚 Source of Truth: google/adk-python/src/google/adk/agents/live_request_queue.py (ADK 1.15) + MCP/A2A implementations
📺 Streaming & Real-Time Interaction
SSE (Server-Sent Events)
# Text streaming to users
async def stream_response(query):
runner = Runner()
async for event in runner.run_async(streaming=SSE):
if event.type == 'content':
yield f"data: {event.content}\n\n"
elif event.type == 'done':
yield "data: [DONE]\n\n"
BIDI (Bidirectional Streaming)
# Voice/video conversations
queue = LiveRequestQueue()
runner = Runner()
async def live_conversation():
async for event in runner.run_live(queue):
if event.type == 'audio_response':
play_audio(event.audio_data)
# Send user input
queue.send_realtime(audio_blob)
Models: gemini-2.0-flash-live-*
, gemini-live-2.5-*
🔌 MCP (Model Context Protocol)
Universal Tool Standard
# Standardized tool interface
mcp_tools = MCPToolset(
connection_params=StdioConnectionParams(
command='npx',
args=['-y', '@modelcontextprotocol/server-filesystem', '/data']
)
)
# Works with any MCP-compatible server
# - Filesystem operations
# - Database queries
# - Git operations
# - Slack/Teams integration
MCP Benefits
- Interoperability: One protocol, many tools
- Security: Built-in authentication
- Discovery: Auto-detect capabilities
- Community: 100+ MCP servers available
🤝 A2A (Agent-to-Agent Communication)
Microservices Architecture
# Remote agent integration
youtube_agent = RemoteA2aAgent(
name='youtube_expert',
base_url='https://youtube-agent.company.com'
)
# Local agent uses remote expertise
orchestrator = Agent(
name="content_strategist",
tools=[AgentTool(youtube_agent)],
instruction="Create strategy using YouTube analytics"
)
A2A vs Local Multi-Agent
- Distribution: Agents on different services
- Scaling: Independent deployment/scaling
- Teams: Cross-team collaboration
- Specialization: Domain-specific experts
🚀 Next-Level Capabilities
Multimodal Integration
- Images: Vision analysis and generation
- Audio: Speech recognition and synthesis
- Video: Real-time video processing
- Documents: PDF/text extraction and analysis
Code Execution
# Built-in Python interpreter
code_agent = Agent(
name="programmer",
model="gemini-2.0-flash", # Code execution enabled
instruction="Write and test Python code"
)
Custom Planners
# Advanced reasoning strategies
reasoning_planner = CustomPlanner(
strategy="tree_of_thought",
max_depth=5
)
agent = Agent(
name="deep_reasoner",
planner=reasoning_planner
)
🎯 Key Takeaways
- Streaming: Real-time text (SSE) and voice/video (BIDI)
- MCP: Universal tool protocol for interoperability
- A2A: Distributed agent communication
- Multimodal: Images, audio, video, documents
- Code Execution: Built-in Python interpreter
- Custom Planners: Advanced reasoning strategies
🔗 Next: Master Decision Frameworks for choosing the right patterns.