Delete app.py

app.py

@@ -1,143 +0,0 @@
-import gradio as gr
-import json
-import pandas as pd
-
-# ----------------------------
-# LOAD DATA
-# ----------------------------
-with open("data.json", "r") as f:
-    df = json.load(f)
-
-# ----------------------------
-# IMPROVED SEPSIS SCORING
-# ----------------------------
-def sepsis_score(patient):
-    score = 0
-    findings = []
-
-    visits = patient.get("visits", [])
-    if not visits:
-        return "Low", ["No visit data"], []
-
-    latest = visits[-1]
-    labs = latest.get("labs", [])
-
-    for lab in labs:
-        name = lab.get("lab_name")
-        value = lab.get("value")
-
-        if name == "WBC":
-            if value > 12:
-                score += 1
-                findings.append(f"WBC elevated ({value})")
-
-        if name == "Glucose":
-            if value > 140:
-                score += 1
-                findings.append(f"Hyperglycemia ({value})")
-
-        if name == "Creatinine":
-            if value > 1.3:
-                score += 1
-                findings.append(f"Renal stress ({value})")
-
-    # More realistic tiers
-    if score == 0:
-        severity = "Low"
-    elif score == 1:
-        severity = "Elevated"
-    elif score == 2:
-        severity = "High"
-    else:
-        severity = "Critical"
-
-    return severity, findings, labs
-
-# ----------------------------
-# EXPLANATION (GEMMA-READY STYLE)
-# ----------------------------
-def explain(severity, findings):
-    return f"""
-Deterministic Sepsis Evaluation
-
-Severity Classification: {severity}
-
-Clinical Indicators:
-{", ".join(findings) if findings else "No abnormal indicators detected"}
-
-Interpretation:
-This assessment is derived from structured laboratory thresholds and rule-based evaluation.
-
-This output is intended for validation and testing purposes only.
-Not for clinical use.
-"""
-
-# ----------------------------
-# ANALYZE FUNCTION
-# ----------------------------
-def analyze(index):
-    index = int(index)
-    patient = df[index]
-
-    severity, findings, labs = sepsis_score(patient)
-    explanation = explain(severity, findings)
-
-    demo = patient.get("demographics", {})
-
-    # Patient summary
-    summary_df = pd.DataFrame([{
-        "Patient Index": index,
-        "Age": demo.get("age"),
-        "Sex": demo.get("sex"),
-        "Conditions": ", ".join(patient.get("conditions", []))
-    }])
-
-    # Labs table
-    labs_rows = []
-    for lab in labs:
-        labs_rows.append({
-            "Lab": lab.get("lab_name"),
-            "Value": lab.get("value")
-        })
-
-    labs_df = pd.DataFrame(labs_rows)
-
-    return summary_df, labs_df, severity, explanation
-
-# ----------------------------
-# UI
-# ----------------------------
-with gr.Blocks() as app:
-
-    gr.Markdown("# HipAAsynth Lab")
-    gr.Markdown("Deterministic Clinical Validation Environment")
-
-    with gr.Row():
-        index = gr.Slider(
-            minimum=0,
-            maximum=len(df) - 1,
-            step=1,
-            value=0,
-            label="Patient Selector"
-        )
-        btn = gr.Button("Run Evaluation")
-
-    with gr.Row():
-        severity_out = gr.Textbox(label="Severity Classification")
-
-    with gr.Row():
-        summary_out = gr.Dataframe(label="Patient Summary")
-
-    with gr.Row():
-        labs_out = gr.Dataframe(label="Latest Laboratory Results")
-
-    with gr.Row():
-        explanation_out = gr.Textbox(label="System Explanation")
-
-    btn.click(
-        fn=analyze,
-        inputs=index,
-        outputs=[summary_out, labs_out, severity_out, explanation_out]
-    )
-
-app.launch()