frank-medium: route by workload — spread batches, pin agent loops
The two replicas behind :7770 were on plain round-robin, which throws away prefix-cache hits: an agent loop re-sends its system prompt and file context every turn, and alternating replicas means every other turn pays a cold prefill. Measured with 90k-token contexts, warm-turn TTFT was 2676 ms. Pinning everything to one replica is not the answer either — a cold batch (the shape a benchmark or a burst of parallel subagents produces) then loses a card's worth of prefill: 16 requests took 30.1 s pinned against 18.6 s spread. So the policy routes by request shape. A continuation (more than one message — the agent-loop signature) is pinned to the replica that served its prefix; anything else spreads across the cards by counter. Measured: 19.97 s for the burst and 1095 ms warm-turn TTFT — the best of both, without a regression on either workload. The policy lives in proxy/routing.py, separate from the HTTP plumbing in proxy/affinity-proxy.py, so it can be tested without aiohttp, a network or a GPU. tests/frank_medium_proxy.bats covers it, and it earned its keep: the first version hashed fresh prefixes to pick a card, which sends every member of a same-prefix burst to one card (29.8 s, measured), and a stale index in the pin path returned 500 on every continuation. Both are now assertions. ROUTING=roundrobin and ROUTING=affinity stay available to re-measure the choice on this host; the default is adaptive.
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#!/usr/bin/env python3
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"""Routing policy for the frank-medium proxy: which replica serves a request.
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Kept apart from the HTTP plumbing in affinity-proxy.py so the decisions can be
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tested without aiohttp, a network or a GPU — the first version of these rules
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shipped with a bug that only appeared on a continuation request, and a test
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that loads this module catches that class of mistake directly.
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Two cards, two behaviours, and the workload decides which is right:
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* A **single-turn** request is one member of a batch (a benchmark run, a burst
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of parallel subagents). Spreading those over both replicas lets both cards
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prefill at once; measured on this host, a 16-request burst of 15k-token
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prompts finishes in 18.6 s spread versus 30.1 s pinned.
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* A **continuation** re-sends a prefix the replica has already prefilled. Pinned
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to that replica the turn costs a cache lookup; spread, half the turns pay a
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cold prefill again (measured: 1096 ms versus 2676 ms mean warm-turn TTFT on
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90k-token contexts).
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ROUTING picks the strategy; the default `adaptive` applies both rules above.
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`affinity` and `roundrobin` exist so the choice can be re-measured, and are not
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production settings.
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"""
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from __future__ import annotations
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import collections
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import hashlib
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import itertools
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import json
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import os
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UPSTREAMS = [u.strip() for u in os.environ.get(
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"UPSTREAMS", "http://127.0.0.1:7771,http://127.0.0.1:7772").split(",") if u.strip()]
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ROUTING = os.environ.get("ROUTING", "adaptive").strip().lower()
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# Leading bytes of prompt text that identify a conversation's shared prefix.
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# 4 KiB covers a system prompt plus the start of the first user turn, which is
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# where agent loops keep the text they resend every turn.
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AFFINITY_BYTES = int(os.environ.get("AFFINITY_BYTES", "4096"))
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# Prefixes remembered for pinning. Bounded so a long-lived proxy cannot grow
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# without limit; 4096 conversations is far beyond what this fleet runs at once.
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KNOWN_MAX = int(os.environ.get("KNOWN_MAX", "4096"))
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_counter = itertools.count()
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# digest -> replica index, insertion-ordered for O(1) LRU eviction. A prefix is
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# remembered as soon as any request carries it; only a continuation is pinned
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# there, because only a continuation can profit from the cache entry.
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_known: "collections.OrderedDict[bytes, int]" = collections.OrderedDict()
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def affinity_key(body: bytes, remote: str | None) -> tuple[bytes, bool]:
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"""Key a request by its shared prefix, and report whether it continues one.
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Chat and completions bodies both carry their prompt text in JSON, so the
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leading bytes of that text are the prefix; a body we cannot parse (or an
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endpoint with no prompt, e.g. /v1/models) falls back to the client address,
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which still beats nothing for a single-client loop.
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"""
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fallback = (remote or "anonymous").encode()
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try:
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payload = json.loads(body)
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except Exception:
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return fallback, False
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text = ""
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continuation = False
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if isinstance(payload, dict):
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if isinstance(payload.get("prompt"), str):
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text = payload["prompt"]
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elif isinstance(payload.get("messages"), list):
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continuation = len(payload["messages"]) > 1
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parts = []
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for msg in payload["messages"]:
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if isinstance(msg, dict):
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content = msg.get("content")
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if isinstance(content, str):
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parts.append(content)
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elif isinstance(content, list): # multimodal content blocks
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parts.extend(
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blk.get("text", "") for blk in content
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if isinstance(blk, dict) and isinstance(blk.get("text"), str)
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)
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text = "\n".join(parts)
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if not text:
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return fallback, continuation
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return text[:AFFINITY_BYTES].encode("utf-8", "replace"), continuation
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def pick(key: bytes, continuation: bool, up: list[bool]) -> int:
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"""Replica for a request, or -1 when none is available.
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Down replicas are never selected — a rollout must not send traffic to an
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engine that is still compiling its graphs — and a pin whose replica is down
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is re-established on a live one rather than kept pointing at a corpse.
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"""
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digest = hashlib.sha1(key).digest()
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if ROUTING == "roundrobin":
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start = next(_counter) % len(UPSTREAMS)
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elif ROUTING == "adaptive":
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entry = _known.get(digest)
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if continuation and entry is not None and up[entry]:
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_known.move_to_end(digest)
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return entry
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# Anything that is not a continuation spreads by counter — including a
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# batch of requests that happen to share one prefix. Hashing the prefix
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# would send every member of such a batch to whichever card the hash
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# names (measured: 29.8 s for a 16-request burst, against 18.6 s when
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# spread). The counter is only advanced by these requests, so batch
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# members alternate across the cards.
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start = next(_counter) % len(UPSTREAMS)
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else: # affinity
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start = int.from_bytes(digest[:8], "big") % len(UPSTREAMS)
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for offset in range(len(UPSTREAMS)):
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idx = (start + offset) % len(UPSTREAMS)
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if up[idx]:
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if ROUTING == "adaptive":
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_known[digest] = idx
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_known.move_to_end(digest)
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if len(_known) > KNOWN_MAX:
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_known.popitem(last=False)
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return idx
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return -1
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def route(body: bytes, remote: str | None, up: list[bool]) -> int:
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"""Convenience wrapper: decode the request body and choose a replica."""
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return pick(*affinity_key(body, remote), up)
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