POCKET-35B-CPU / app.py
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A/B: show reasoning again (remove no_think prefill); raise A/B max_tokens 96->256 so thinking completes
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# -*- coding: utf-8 -*-
"""POCKET-35B CPU chat + live A/B vs Bonsai.
FastAPI frontend proxying to two local llama.cpp servers (upstream prebuilt release,
supports POCKET's qwen35moe arch). Native /completion + manual ChatML. No GPU."""
import os, json, time
import httpx
from fastapi import FastAPI, Request
from fastapi.responses import HTMLResponse, StreamingResponse, JSONResponse
BACKEND = os.environ.get("BACKEND", "http://127.0.0.1:8080") # POCKET
BONSAI_BACKEND = os.environ.get("BONSAI_BACKEND", "http://127.0.0.1:8081") # Bonsai
HERE = os.path.dirname(__file__)
app = FastAPI(title="POCKET-35B CPU chat")
def build_chatml(messages, no_think=False):
"""Qwen-family ChatML prompt (works for POCKET and Bonsai).
When no_think is set, the assistant turn is prefilled with a closed (empty)
<think></think> block so the model skips reasoning and answers directly — the
reliable way to get short, fast replies for the A/B race (the /no_think soft
switch is not honored through a raw prompt)."""
parts = []
if not any(m.get("role") == "system" for m in messages):
parts.append("<|im_start|>system\nYou are a helpful assistant. Answer concisely.<|im_end|>\n")
for m in messages:
parts.append("<|im_start|>%s\n%s<|im_end|>\n" % (m.get("role", "user"), m.get("content", "")))
if no_think:
parts.append("<|im_start|>assistant\n<think>\n\n</think>\n\n")
else:
parts.append("<|im_start|>assistant\n")
return "".join(parts)
def _sse(obj):
return "data: " + json.dumps(obj) + "\n\n"
async def _health(backend):
try:
async with httpx.AsyncClient(timeout=3.0) as c:
r = await c.get(backend + "/health")
return r.status_code == 200
except Exception:
return False
async def run_one(backend, tag, messages, max_tokens, temperature=0.7, no_think=False):
"""Stream one model's /completion output as SSE, tagged with `tag` (None = untagged)."""
payload = {
"prompt": build_chatml(messages, no_think=no_think),
"temperature": float(temperature),
"top_p": 0.95,
"n_predict": int(max_tokens),
"stream": True,
"cache_prompt": True,
"stop": ["<|im_end|>", "<|im_start|>"],
}
n_tok = 0
t_first = None
tagd = {"m": tag} if tag else {}
async with httpx.AsyncClient(timeout=None) as c:
async with c.stream("POST", backend + "/completion", json=payload) as r:
if r.status_code != 200:
detail = (await r.aread()).decode("utf-8", "ignore")[:200]
yield _sse(dict(tagd, error="backend %s: %s" % (r.status_code, detail)))
return
async for line in r.aiter_lines():
if not line or not line.startswith("data:"):
continue
try:
obj = json.loads(line[5:].strip())
except Exception:
continue
delta = obj.get("content")
if delta:
if t_first is None:
t_first = time.monotonic()
n_tok += 1
yield _sse(dict(tagd, t=delta))
if obj.get("stop"):
tim = obj.get("timings") or {}
tok_s = tim.get("predicted_per_second")
if not tok_s and t_first is not None and n_tok > 0:
dt = time.monotonic() - t_first
tok_s = (n_tok / dt) if dt > 0 else 0.0
yield _sse(dict(tagd, done=True, tok_s=round(tok_s or 0.0, 1),
n=int(tim.get("predicted_n") or n_tok)))
return
yield _sse(dict(tagd, done=True, tok_s=0.0, n=n_tok))
@app.get("/api/status")
async def status():
pk = await _health(BACKEND)
bn = await _health(BONSAI_BACKEND)
if pk:
detail = "POCKET-35B on CPU · ready" if bn else "POCKET ready · loading Bonsai for the A/B…"
else:
detail = "downloading & loading models… (first boot can take a few minutes)"
return JSONResponse({"state": "ready" if pk else "loading", "detail": detail,
"pocket": pk, "bonsai": bn})
@app.post("/api/chat")
async def chat(req: Request):
body = await req.json()
messages = body.get("messages") or [{"role": "user", "content": body.get("prompt", "Hi")}]
mt = int(body.get("max_tokens", 512))
async def gen():
try:
async for chunk in run_one(BACKEND, None, messages, mt, body.get("temperature", 0.7)):
yield chunk
except Exception as e:
yield _sse({"error": str(e)[:200]})
return StreamingResponse(gen(), media_type="text/event-stream")
@app.post("/api/chat_ab")
async def chat_ab(req: Request):
"""Sequential race: Bonsai runs first, then POCKET (each gets the full CPU)."""
body = await req.json()
messages = body.get("messages") or [{"role": "user", "content": body.get("prompt", "Hi")}]
mt = int(body.get("max_tokens", 200))
async def gen():
try:
async for chunk in run_one(BONSAI_BACKEND, "bonsai", messages, mt):
yield chunk
async for chunk in run_one(BACKEND, "pocket", messages, mt):
yield chunk
yield _sse({"ab_done": True})
except Exception as e:
yield _sse({"error": str(e)[:200]})
return StreamingResponse(gen(), media_type="text/event-stream")
@app.get("/", response_class=HTMLResponse)
def index():
with open(os.path.join(HERE, "index.html"), encoding="utf-8") as f:
return f.read()