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Running on Zero
Running on Zero
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2407511 | 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 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 | """Hugging Face ZeroGPU entrypoint for SatQuery AI."""
from __future__ import annotations
import gradio as gr
import spaces
from satquery_space_bridge import (
api_contract,
preload_models,
run_bitemporal,
run_optical_sar,
run_single_image,
space_health,
)
# ZeroGPU provides CUDA emulation during module initialization. Keep model
# construction here and inference inside the decorated request handlers below.
preload_models()
@spaces.GPU(duration=90)
def single_image_api(
primary_image: str | None,
query: str,
primary_modality: str,
primary_image_modality: str,
use_cache: bool,
force_rerun: bool,
):
return run_single_image(
primary_image,
query,
primary_modality,
primary_image_modality,
use_cache,
force_rerun,
)
@spaces.GPU(duration=75)
def optical_sar_api(
optical_image: str | None,
sar_image: str | None,
query: str,
use_cache: bool,
force_rerun: bool,
):
return run_optical_sar(optical_image, sar_image, query, use_cache, force_rerun)
@spaces.GPU(duration=90)
def bitemporal_api(
earlier_image: str | None,
later_image: str | None,
query: str,
primary_date: str,
secondary_date: str,
primary_modality: str,
use_cache: bool,
force_rerun: bool,
):
return run_bitemporal(
earlier_image,
later_image,
query,
primary_date,
secondary_date,
primary_modality,
use_cache,
force_rerun,
)
def _outputs():
return [
gr.JSON(label="Result envelope"),
gr.JSON(label="Artifact manifest"),
gr.File(label="Evidence files", file_count="multiple"),
]
with gr.Blocks(title="SatQuery AI ZeroGPU Bridge") as demo:
gr.Markdown(
"# SatQuery AI API bridge\n"
"This minimal Space exposes the existing SatQuery workflows as named Gradio APIs. "
"Use **View API** for the generated client contract."
)
with gr.Tab("Single Image"):
single_file = gr.File(label="Image", type="filepath")
single_query = gr.Textbox(label="Query", value="Describe this satellite image.")
single_modality = gr.Dropdown(
["optical", "multispectral", "sar", "unknown"], value="optical", label="Modality"
)
single_image_modality = gr.Dropdown(
[
"auto",
"optical_rgb",
"optical_grayscale",
"panchromatic",
"sar_preview",
"sar_vv",
"sar_vh",
"sar_vv_vh",
"multispectral",
"unknown",
],
value="auto",
label="Image modality",
)
single_cache = gr.Checkbox(value=True, label="Use cache")
single_rerun = gr.Checkbox(value=False, label="Force rerun")
single_submit = gr.Button("Run single-image workflow", variant="primary")
single_submit.click(
single_image_api,
[single_file, single_query, single_modality, single_image_modality, single_cache, single_rerun],
_outputs(),
api_name="single_image",
)
with gr.Tab("Optical + SAR"):
optical_file = gr.File(label="Optical image", type="filepath")
sar_file = gr.File(label="SAR image", type="filepath")
cross_query = gr.Textbox(label="Query", value="Compare the optical and SAR observations.")
cross_cache = gr.Checkbox(value=True, label="Use cache")
cross_rerun = gr.Checkbox(value=False, label="Force rerun")
cross_submit = gr.Button("Run optical + SAR workflow", variant="primary")
cross_submit.click(
optical_sar_api,
[optical_file, sar_file, cross_query, cross_cache, cross_rerun],
_outputs(),
api_name="optical_sar",
)
with gr.Tab("Bi-temporal"):
earlier_file = gr.File(label="Earlier image", type="filepath")
later_file = gr.File(label="Later image", type="filepath")
temporal_query = gr.Textbox(label="Query", value="What changed between these images?")
earlier_date = gr.Textbox(label="Earlier date", placeholder="YYYY-MM-DD")
later_date = gr.Textbox(label="Later date", placeholder="YYYY-MM-DD")
temporal_modality = gr.Dropdown(
["optical", "multispectral", "sar", "unknown"], value="optical", label="Modality"
)
temporal_cache = gr.Checkbox(value=True, label="Use cache")
temporal_rerun = gr.Checkbox(value=False, label="Force rerun")
temporal_submit = gr.Button("Run bi-temporal workflow", variant="primary")
temporal_submit.click(
bitemporal_api,
[
earlier_file,
later_file,
temporal_query,
earlier_date,
later_date,
temporal_modality,
temporal_cache,
temporal_rerun,
],
_outputs(),
api_name="bitemporal",
)
with gr.Tab("Readiness"):
readiness_output = gr.JSON(label="Health")
contract_output = gr.JSON(label="Contract")
gr.Button("Health (CPU only)").click(space_health, outputs=readiness_output, api_name="health")
gr.Button("Contract (CPU only)").click(api_contract, outputs=contract_output, api_name="contract")
demo.queue(default_concurrency_limit=1, max_size=8)
if __name__ == "__main__":
demo.launch()
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