feat(streaming): wire streaming path through orchestrator task pipeline
- _stream_agent_response_to_redis() publishes chunk/done messages to Redis pub-sub - _process_message() uses streaming path for web channel with no tools registered - Non-web channels (Slack, WhatsApp) and tool-enabled agents use non-streaming run_agent() - streaming_delivered flag prevents double-publish when streaming path is active - _send_response() web branch changed from 'response' to 'done' message type for consistency
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@@ -66,7 +66,7 @@ import redis.asyncio as aioredis
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from gateway.channels.whatsapp import send_whatsapp_message
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from orchestrator.agents.builder import build_messages_with_memory
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from orchestrator.agents.runner import run_agent
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from orchestrator.agents.runner import run_agent, run_agent_streaming
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from orchestrator.audit.logger import AuditLogger
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from orchestrator.escalation.handler import check_escalation_rules, escalate_to_human
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from orchestrator.main import app
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@@ -526,15 +526,39 @@ async def _process_message(
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tool_registry = get_tools_for_agent(agent)
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# -------------------------------------------------------------------------
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# Run agent with tool loop
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# Run agent — streaming for web channel (no tools), non-streaming otherwise
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# -------------------------------------------------------------------------
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response_text = await run_agent(
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msg,
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agent,
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messages=enriched_messages,
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audit_logger=audit_logger,
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tool_registry=tool_registry if tool_registry else None,
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)
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is_web_channel = str(msg.channel) == "web"
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has_tools = bool(tool_registry)
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# Track whether the streaming path already published to Redis so we can
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# skip the _send_response() call below (avoids a duplicate publish).
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streaming_delivered = False
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if is_web_channel and not has_tools:
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# Streaming path: yield tokens directly to Redis pub-sub so the
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# WebSocket handler can forward them to the browser immediately.
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# The tool-call loop is skipped because there are no tools registered.
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web_conversation_id: str = extras.get("conversation_id", "") or ""
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web_tenant_id: str = extras.get("tenant_id", "") or str(msg.tenant_id or "")
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response_text = await _stream_agent_response_to_redis(
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msg=msg,
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agent=agent,
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messages=enriched_messages,
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conversation_id=web_conversation_id,
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tenant_id=web_tenant_id,
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)
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streaming_delivered = True
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else:
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# Non-streaming path: tool-call loop + full response (Slack, WhatsApp,
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# and web channel when tools are registered).
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response_text = await run_agent(
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msg,
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agent,
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messages=enriched_messages,
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audit_logger=audit_logger,
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tool_registry=tool_registry if tool_registry else None,
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)
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# -------------------------------------------------------------------------
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# Escalation post-check — evaluate rules against conversation metadata
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@@ -592,8 +616,12 @@ async def _process_message(
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len(relevant_context),
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)
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# Send response via channel-aware routing
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await _send_response(msg.channel, response_text, response_extras)
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# Send response via channel-aware routing.
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# Skip for the streaming path — _stream_agent_response_to_redis already
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# published chunk + done messages to Redis; calling _send_response here
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# would publish a duplicate done message.
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if not streaming_delivered:
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await _send_response(msg.channel, response_text, response_extras)
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# -------------------------------------------------------------------------
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# Memory persistence (after LLM response)
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@@ -733,6 +761,87 @@ def _extract_tool_name_from_confirmation(confirmation_message: str) -> str:
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return "unknown_tool"
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# Fallback text for streaming errors (mirrors runner._FALLBACK_RESPONSE)
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_FALLBACK_RESPONSE_TEXT = (
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"I'm having trouble processing your request right now. "
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"Please try again in a moment."
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)
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async def _stream_agent_response_to_redis(
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msg: "KonstructMessage",
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agent: Any,
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messages: list[dict],
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conversation_id: str,
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tenant_id: str,
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) -> str:
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"""
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Stream LLM token chunks to Redis pub-sub for web channel delivery.
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Calls run_agent_streaming() and publishes each token as a
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``{"type": "chunk", "text": "<token>"}`` message to the webchat response
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channel. Publishes a final ``{"type": "done", "text": "<full_response>"}``
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when the stream completes.
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The WebSocket handler (web.py) listens on this channel and forwards
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chunk/done messages directly to the browser, enabling word-by-word display.
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Args:
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msg: The inbound KonstructMessage.
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agent: The ORM Agent instance.
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messages: Memory-enriched messages array.
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conversation_id: Web conversation UUID string.
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tenant_id: Konstruct tenant UUID string.
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Returns:
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The full assembled response text (for memory persistence and audit).
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"""
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response_channel = webchat_response_key(tenant_id, conversation_id)
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chunks: list[str] = []
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full_response = _FALLBACK_RESPONSE_TEXT
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publish_redis = aioredis.from_url(settings.redis_url)
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try:
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async for token in run_agent_streaming(msg, agent, messages=messages):
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chunks.append(token)
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await publish_redis.publish(
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response_channel,
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json.dumps({"type": "chunk", "text": token}),
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)
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full_response = "".join(chunks) or _FALLBACK_RESPONSE_TEXT
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await publish_redis.publish(
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response_channel,
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json.dumps({
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"type": "done",
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"text": full_response,
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"conversation_id": conversation_id,
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}),
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)
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except Exception:
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logger.exception(
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"Streaming agent response failed for conversation=%s tenant=%s",
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conversation_id,
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tenant_id,
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)
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# Publish a done marker with fallback so the browser doesn't hang
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try:
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await publish_redis.publish(
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response_channel,
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json.dumps({
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"type": "done",
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"text": full_response,
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"conversation_id": conversation_id,
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}),
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)
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except Exception:
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pass
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finally:
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await publish_redis.aclose()
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return full_response
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async def _send_response(
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channel: Any,
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text: str,
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@@ -792,7 +901,9 @@ async def _send_response(
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)
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elif channel_str == "web":
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# Publish agent response to Redis pub-sub so the WebSocket handler can deliver it
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# Publish agent response to Redis pub-sub so the WebSocket handler can deliver it.
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# Uses "done" type (consistent with streaming path) so the WebSocket handler
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# processes it identically whether or not streaming was used.
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web_conversation_id: str = extras.get("conversation_id", "") or ""
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web_tenant_id: str = extras.get("tenant_id", "") or ""
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@@ -808,7 +919,7 @@ async def _send_response(
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await publish_redis.publish(
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response_channel,
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json.dumps({
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"type": "response",
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"type": "done",
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"text": text,
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"conversation_id": web_conversation_id,
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}),
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