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app.py

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+import gradio as gr
+
+def piv_tool(velocity, shear, hr):
+    v = "HIGH - stenosis risk" if float(velocity) > 2.0 else "NORMAL"
+    s = "HIGH - thrombosis risk" if float(shear) > 10 else "NORMAL"
+    return "Velocity: " + str(velocity) + " m/s - " + v + "\nShear: " + str(shear) + " Pa - " + s
+
+def tgt_tool(tat, pf12, hemo, platelets, time):
+    risk = sum([float(tat)>15, float(pf12)>2.0, float(hemo)>50, float(platelets)<150])
+    overall = "HIGH THROMBOGENIC RISK" if risk>=3 else "MODERATE RISK" if risk>=2 else "LOW RISK"
+    return "TAT:" + str(tat) + " PF1.2:" + str(pf12) + " Hemo:" + str(hemo) + " Platelets:" + str(platelets) + "\nResult: " + overall
+
+def upad_tool(r, g, b):
+    creatinine = max(0, round(0.02*(float(r)-float(b))-0.5, 2))
+    stage = "Normal" if creatinine<1.2 else "Borderline" if creatinine<1.5 else "Stage 2 CKD" if creatinine<3.0 else "Stage 3-4 CKD" if creatinine<6.0 else "Stage 5 CKD"
+    return "Creatinine: " + str(creatinine) + " mg/dL\nStage: " + stage
+
+def ask(q):
+    answers = {
+        "sylgard": "Sylgard 184 is used in the MCL to create transparent test sections for PIV imaging. Mixed at 10:1 ratio, cured 48hrs.",
+        "tgt": "TGT uses Arduino Uno + Stepper Motor at 70 bpm. Blood sampled at 0,20,40,60 min. Measures TAT, PF1.2, hemolysis.",
+        "jaffe": "Jaffe reaction: creatinine + picric acid = orange-red color. Used in uPAD for CKD creatinine detection.",
+        "piv": "PIV = Particle Image Velocimetry. Green laser + high speed camera measures velocity and shear stress in MCL.",
+        "ckd": "CKD detected via uPAD Jaffe reaction. Normal creatinine < 1.2 mg/dL. CKD threshold > 1.5 mg/dL.",
+        "mhv": "Lab uses 27mm SJM Regent MHV. Tested in MCL for hemodynamics and TGT for thrombogenicity.",
+    }
+    for key, answer in answers.items():
+        if key in q.lower():
+            return answer
+    return "CardioLab AI covers MCL, PIV, TGT, uPAD, CKD, FSI, MHV. Ask about any topic!"
+
+with gr.Blocks(title="CardioLab AI - SJSU") as demo:
+    gr.Markdown("# CardioLab AI Agent")
+    gr.Markdown("### SJSU Biomedical Engineering | Open Source")
+    gr.Markdown("GitHub: github.com/pranatechsol/Cardio-Lab-Ai")
+    with gr.Tab("Ask Agent"):
+        q = gr.Textbox(label="Ask about CardioLab research")
+        a = gr.Textbox(label="Answer", lines=4)
+        gr.Button("Ask CardioLab AI").click(ask, inputs=q, outputs=a)
+    with gr.Tab("PIV Analysis"):
+        v = gr.Number(label="Max Velocity m/s", value=1.8)
+        s = gr.Number(label="Shear Stress Pa", value=6.5)
+        h = gr.Number(label="Heart Rate bpm", value=72)
+        out = gr.Textbox(label="Result", lines=4)
+        gr.Button("Analyze PIV").click(piv_tool, inputs=[v,s,h], outputs=out)
+    with gr.Tab("TGT Results"):
+        t1 = gr.Number(label="TAT", value=18)
+        t2 = gr.Number(label="PF1.2", value=2.5)
+        t3 = gr.Number(label="Free Hemoglobin", value=60)
+        t4 = gr.Number(label="Platelet Count", value=140)
+        t5 = gr.Number(label="Time minutes", value=40)
+        out2 = gr.Textbox(label="Result", lines=5)
+        gr.Button("Analyze TGT").click(tgt_tool, inputs=[t1,t2,t3,t4,t5], outputs=out2)
+    with gr.Tab("uPAD CKD"):
+        r = gr.Number(label="R value", value=210)
+        g = gr.Number(label="G value", value=140)
+        b = gr.Number(label="B value", value=80)
+        out3 = gr.Textbox(label="Result", lines=4)
+        gr.Button("Analyze uPAD").click(upad_tool, inputs=[r,g,b], outputs=out3)
+
+demo.launch()

requirements.txt

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+gradio