Spaces:
Running on CPU Upgrade
Running on CPU Upgrade
A/B: show reasoning again (remove no_think prefill); raise A/B max_tokens 96->256 so thinking completes
8bfa67a verified | # -*- 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)) | |
| 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}) | |
| 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") | |
| 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") | |
| def index(): | |
| with open(os.path.join(HERE, "index.html"), encoding="utf-8") as f: | |
| return f.read() | |