* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
Agent Response Callbacks with Redis Streaming
This sample demonstrates how to use Redis Streams with agent response callbacks to enable reliable, resumable streaming for durable agents. Clients can disconnect and reconnect without losing messages by using cursor-based pagination.
Key Concepts Demonstrated
- Using
AgentResponseCallbackProtocolto capture streaming agent responses - Persisting streaming chunks to Redis Streams for reliable delivery
- Building a custom HTTP endpoint to read from Redis with Server-Sent Events (SSE) format
- Supporting cursor-based resumption for disconnected clients
- Managing Redis client lifecycle with async context managers
Prerequisites
In addition to the common setup steps in ../README.md, this sample requires Redis:
# Start Redis
docker run -d --name redis -p 6379:6379 redis:latest
Update local.settings.json with your Redis connection string:
{
"Values": {
"REDIS_CONNECTION_STRING": "redis://localhost:6379"
}
}
Running the Sample
Start the agent run
The agent executes in the background via durable orchestration. The RedisStreamCallback persists streaming chunks to Redis:
curl -X POST http://localhost:7071/api/agents/TravelPlanner/run \
-H "Content-Type: text/plain" \
-d "Plan a 3-day trip to Tokyo"
Response (202 Accepted):
{
"status": "accepted",
"response": "Agent request accepted",
"conversation_id": "abc-123-def-456",
"correlation_id": "xyz-789"
}
Stream the response from Redis
Use the custom /api/agent/stream/{conversation_id} endpoint to read persisted chunks:
curl http://localhost:7071/api/agent/stream/abc-123-def-456 \
-H "Accept: text/event-stream"
Response (SSE format):
id: 1734649123456-0
event: message
data: Here's a wonderful 3-day Tokyo itinerary...
id: 1734649123789-0
event: message
data: Day 1: Arrival and Shibuya...
id: 1734649124012-0
event: done
data: [DONE]
Resume from a cursor
Use a cursor ID from an SSE event to skip already-processed messages:
curl "http://localhost:7071/api/agent/stream/abc-123-def-456?cursor=1734649123456-0" \
-H "Accept: text/event-stream"
How It Works
1. Redis Callback
The RedisStreamCallback class implements AgentResponseCallbackProtocol to capture streaming updates:
class RedisStreamCallback(AgentResponseCallbackProtocol):
async def on_streaming_response_update(self, update, context):
# Write chunk to Redis Stream
async with await get_stream_handler() as handler:
await handler.write_chunk(thread_id, update.text, sequence)
async def on_agent_response(self, response, context):
# Write end-of-stream marker
async with await get_stream_handler() as handler:
await handler.write_completion(thread_id, sequence)
2. Custom Streaming Endpoint
The /api/agent/stream/{conversation_id} endpoint reads from Redis:
@app.route(route="agent/stream/{conversation_id}", methods=["GET"])
async def stream(req):
conversation_id = req.route_params.get("conversation_id")
cursor = req.params.get("cursor") # Optional
async with await get_stream_handler() as handler:
async for chunk in handler.read_stream(conversation_id, cursor):
# Format and return chunks
3. Redis Streams
Messages are stored in Redis Streams with automatic TTL (default: 10 minutes):
Stream Key: agent-stream:{conversation_id}
Entry: {
"text": "chunk content",
"sequence": "0",
"timestamp": "1734649123456"
}