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File size: 1,239 Bytes
3325388 539c11b 535e4d9 3325388 535e4d9 539c11b 535e4d9 3325388 535e4d9 539c11b 535e4d9 539c11b | 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 | from __future__ import annotations
import json
from pathlib import Path
import gradio as gr
ROOT = Path(__file__).resolve().parent
RESULTS_PATH = ROOT / "evidence" / "results.json"
PROVENANCE_PATH = ROOT / "evidence" / "provenance.json"
def load_data():
results = json.loads(RESULTS_PATH.read_text(encoding="utf-8"))
provenance = json.loads(PROVENANCE_PATH.read_text(encoding="utf-8"))
return results, provenance
results, provenance = load_data()
with gr.Blocks(title="Know More, Know Clearer Reproduction") as demo:
gr.Markdown(
f"# {results['title']}\n\n"
f"**Paper ID**: `{results['paper_id']}` | **Execution**: `{provenance['execution_environment']}` | **API Cost**: `${provenance['actual_api_cost_usd']:.2f}`\n\n"
f"**Upstream Revision**: `{results['upstream_revision']}`\n"
)
claims_data = [
[c["claim"], c["status"], c["observation"]]
for c in results["target_claims"]
]
gr.Dataframe(
headers=["Target Claim", "Status", "Observation"],
value=claims_data,
wrap=True,
interactive=False,
)
gr.JSON(value=results.get("metrics", {}), label="Metrics & Statistical Fit")
if __name__ == "__main__":
demo.launch()
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