python/README.md

ClaimCheck — Python implementation

The reference implementation. Same rules as the JavaScript port that powers the Space, verified at 100% behavioural parity across all 158 cases of NagaYu/claimcheck-eval.

Use this when you want a server-side API rather than a browser page: a Gradio UI with seven REST endpoints, an in-memory observability dashboard (per-model/per-prompt-version comparison, latency percentiles, savings), and a false-positive audit tab.

pip install -r requirements.txt
python app.py          # http://127.0.0.1:7860

from gradio_client import Client
client = Client("http://127.0.0.1:7860/")
result, highlighted, summary = client.predict(
    answer="Operating margin was 15%.",
    context="Revenue was 12,000 million and operating profit 1,800 million.",
    system_prompt="", user_input="", schema_json="",
    policy_json='{"enable_entity": false}',
    tags_json='{"model": "my-model", "prompt_version": "v1"}',
    api_name="/verify",
)
print(result["verdict"], result["grounding_score"], result["coverage"])

Endpoints: /verify, /retry_advice, /stats, /structure, /health, /audit_refresh, /audit_mark.

deploy.md is a step-by-step deployment guide (in Japanese) including a staged rollout plan.

Note on Hugging Face Spaces: Gradio Spaces now require a PRO subscription on cpu-basic. Only static Spaces are free, which is why the hosted demo is the JavaScript port. This Python version is for self-hosting anywhere you like.

Verification itself uses only the standard library — gradio and pandas are for the UI and the dashboard. Apache-2.0.