Spaces:
Running on Zero
Running on Zero
File size: 2,508 Bytes
86e797b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | """Optional ZeroGPU query encoding; CPU ranking and Gemini stay outside the GPU lease."""
import json
import os
from pathlib import Path
# Import spaces before torch/transformers so ZeroGPU can install its CUDA hooks.
if os.environ.get("VDR_QUERY_DEVICE", "cpu") == "zerogpu":
import spaces
else:
spaces = None
_encoder = None
def ensure_models(data_dir, model_info):
"""Space repositories omit weights; fetch only the pinned official snapshots."""
from huggingface_hub import snapshot_download
for kind in ("adapter", "base"):
root = data_dir / "models" / model_info[f"{kind}_path"]
if not list(root.glob("*.safetensors")):
snapshot_download(
repo_id=model_info["model_id" if kind == "adapter" else "base_model_id"],
revision=model_info[f"{kind}_revision"],
local_dir=root,
allow_patterns=["*.json", "*.safetensors", "*.jinja", "README.md", "LICENSE*"],
token=False,
)
def encode_query(query):
if _encoder is None:
raise RuntimeError("Initialize the ZeroGPU encoder at application startup.")
return _encoder.encode(query=query)
if spaces is not None:
encode_query = spaces.GPU(duration=10)(encode_query)
def create_service(data_dir=Path("data")):
from visual_doc_rag.serve import AnswerService
device = os.environ.get("VDR_QUERY_DEVICE", "cpu")
if device == "cpu":
manifest_path = data_dir / "hr/indexes/visual.json"
if (data_dir / "hr/demo.json").exists() and manifest_path.exists():
manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
ensure_models(data_dir, manifest["signature"]["model"])
return AnswerService(data_dir=data_dir)
if device != "zerogpu" or spaces is None:
raise ValueError("VDR_QUERY_DEVICE must be cpu or zerogpu (requires the hosting extra).")
from visual_doc_rag.retrieve import PageRetriever
from visual_doc_rag.visual_index import Encoder
global _encoder
manifest = json.loads((data_dir / "hr/indexes/visual.json").read_text(encoding="utf-8"))
ensure_models(data_dir, manifest["signature"]["model"])
# Official ZeroGPU guidance: place the model on CUDA at startup, before a GPU call.
_encoder = Encoder(data_dir, manifest["signature"]["model"], "cuda")
retriever = PageRetriever(data_dir=data_dir, query_encoder=encode_query)
return AnswerService(data_dir=data_dir, retriever=retriever)
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