feat(streaming): add complete_stream() generator and POST /complete/stream NDJSON endpoint to llm-pool
- complete_stream() in router.py yields token strings via acompletion(stream=True) - POST /complete/stream returns NDJSON: chunk lines then a done line - Streaming path does not support tool calls (plain text only) - Non-streaming POST /complete endpoint unchanged
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@@ -3,18 +3,22 @@ LLM Backend Pool — FastAPI service on port 8004.
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Endpoints:
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POST /complete — route a completion request through the LiteLLM Router.
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POST /complete/stream — streaming variant; returns NDJSON token chunks.
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GET /health — liveness probe.
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"""
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from __future__ import annotations
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import json
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import logging
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from typing import Any
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from fastapi import FastAPI
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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from llm_pool.router import complete as router_complete
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from llm_pool.router import complete_stream as router_complete_stream
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logger = logging.getLogger(__name__)
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@@ -69,6 +73,19 @@ class HealthResponse(BaseModel):
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status: str
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class StreamCompleteRequest(BaseModel):
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"""Body for POST /complete/stream."""
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model: str
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"""Model group name: "quality" or "fast"."""
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messages: list[dict]
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"""OpenAI-format message list."""
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tenant_id: str
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"""Konstruct tenant UUID for cost tracking."""
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# ---------------------------------------------------------------------------
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# Routes
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# ---------------------------------------------------------------------------
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@@ -123,3 +140,44 @@ async def complete_endpoint(request: CompleteRequest) -> CompleteResponse:
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status_code=503,
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content={"error": "All providers unavailable"},
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)
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@app.post("/complete/stream")
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async def complete_stream_endpoint(request: StreamCompleteRequest) -> StreamingResponse:
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"""
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Stream a completion through the LiteLLM Router using NDJSON.
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Each line of the response body is a JSON object:
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{"type": "chunk", "text": "<token>"} — zero or more times
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{"type": "done"} — final line, signals end of stream
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On provider failure, yields:
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{"type": "error", "message": "All providers unavailable"}
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The caller (orchestrator runner) reads line-by-line and forwards chunks
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to Redis pub-sub for the web WebSocket handler.
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NOTE: Tool calls are NOT supported in this endpoint — only plain text
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streaming. Use POST /complete for tool-call responses.
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"""
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async def _generate() -> Any:
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try:
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async for token in router_complete_stream(
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model_group=request.model,
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messages=request.messages,
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tenant_id=request.tenant_id,
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):
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yield json.dumps({"type": "chunk", "text": token}) + "\n"
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yield json.dumps({"type": "done"}) + "\n"
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except Exception:
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logger.exception(
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"Streaming LLM failed for tenant=%s model=%s",
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request.tenant_id,
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request.model,
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)
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yield json.dumps({"type": "error", "message": "All providers unavailable"}) + "\n"
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return StreamingResponse(
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_generate(),
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media_type="application/x-ndjson",
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)
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@@ -16,6 +16,7 @@ NOTE: LiteLLM is pinned to ==1.82.5 in pyproject.toml.
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from __future__ import annotations
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import logging
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from collections.abc import AsyncGenerator
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from typing import Any
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from litellm import Router
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@@ -173,3 +174,48 @@ async def complete(
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content: str = message.content or ""
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return LLMResponse(content=content, tool_calls=tool_calls)
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async def complete_stream(
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model_group: str,
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messages: list[dict],
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tenant_id: str,
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) -> AsyncGenerator[str, None]:
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"""
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Stream a completion from the LiteLLM Router, yielding token strings.
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Only used for the web channel streaming path — does NOT support tool calls
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(tool-call responses are not streamed). The caller is responsible for
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assembling the full response from the yielded chunks.
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Args:
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model_group: "quality", "fast", etc. — selects the provider group.
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messages: OpenAI-format message list.
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tenant_id: Konstruct tenant UUID for cost tracking metadata.
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Yields:
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Token strings as they are generated by the LLM.
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Raises:
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Exception: Propagated if all providers (and fallbacks) fail.
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"""
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logger.info(
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"LLM stream request",
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extra={"model_group": model_group, "tenant_id": tenant_id},
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)
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response = await llm_router.acompletion(
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model=model_group,
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messages=messages,
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metadata={"tenant_id": tenant_id},
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stream=True,
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)
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async for chunk in response:
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try:
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delta = chunk.choices[0].delta
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token = getattr(delta, "content", None)
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if token:
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yield token
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except (IndexError, AttributeError):
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continue
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