app.py

import gradio as gr
import os
from openai import OpenAI

# 🔹 Set your Grok (xAI) API Key securely
os.environ["XAI_API_KEY"] = "xai-2ftlCxHfSh3eCmrzNVWlC8X1r4w06GQTPLK8YFwJdwjgFXK0oW0H6QvR4NN5N0fhkLLEkibGBY7Q1e6m"

# 🔹 Initialize client for Grok
client = OpenAI(
    api_key=os.getenv("XAI_API_KEY"),
    base_url="https://api.x.ai/v1"  # ✅ xAI Grok endpoint
)

# 🔹 Define model (latest general-purpose)
MODEL_ID = "grok-beta"  # or "grok-2", check console for available models

# ---------------- AI Response Function ----------------
def respond(albumin, creatinine, glucose, crp, mcv, rdw, alp, wbc, lymphocytes,
            hemoglobin, pv, age, gender, height, weight):
    
    system_message = (
        "You are an AI Health Assistant that analyzes laboratory biomarkers "
        "and generates structured, patient-friendly health summaries.\n\n"
        "Your task is to evaluate the provided biomarkers and generate an AI-driven medical report "
        "with insights, observations, and clear explanations.\n"
        "You must strictly follow this structured format:\n\n"
        "### Tabular Mapping\n"
        "| Biomarker | Value | Status (Low/Normal/High) | AI-Inferred Insight |Reference Range|\n"
        "Include all available biomarkers: Albumin, Creatinine, Glucose, CRP, MCV, RDW, ALP, WBC, "
        "Lymphocytes, Hemoglobin, Plasma Viscosity (PV).\n\n"
        "### Executive Summary\n"
        "- Top 3 Health Priorities.\n"
        "- Key Strengths (normal biomarkers).\n\n"
        "### System-Specific Analysis\n"
        "- Organ systems: Liver, Kidney, Immune, Blood, etc.\n"
        "- Status: “Optimal” | “Monitor” | “Needs Attention”.\n"
        "- Write concise, supportive explanations.\n\n"
        "### Personalized Action Plan\n"
        "- Recommendations: Nutrition, Lifestyle, Testing, Consultation.\n"
        "- Never recommend medication.\n\n"
        "### Interaction Alerts\n"
        "- Highlight potential relationships (e.g., high CRP + low Albumin).\n\n"
        "### Constraints\n"
        "- No diagnosis or prescriptions.\n"
        "- Use only provided data.\n"
        "- Always recommend seeing a healthcare professional.\n"
        "- Include normal reference ranges for each biomarker.\n"
        "- Use patient-friendly language."
    )

    user_message = (
        f"Patient Information:\n"
        f"- Age: {age} years\n"
        f"- Gender: {gender}\n"
        f"- Height: {height} cm\n"
        f"- Weight: {weight} kg\n\n"
        f"Biomarker Values:\n"
        f"- Albumin: {albumin} g/dL\n"
        f"- Creatinine: {creatinine} mg/dL\n"
        f"- Glucose: {glucose} mg/dL\n"
        f"- CRP: {crp} mg/L\n"
        f"- MCV: {mcv} fL\n"
        f"- RDW: {rdw} %\n"
        f"- ALP: {alp} U/L\n"
        f"- WBC: {wbc} x10^3/μL\n"
        f"- Lymphocytes: {lymphocytes} %\n"
        f"- Hemoglobin: {hemoglobin} g/dL\n"
        f"- Plasma Viscosity (PV): {pv} mPa·s"
    )

    completion = client.chat.completions.create(
        model=MODEL_ID,
        messages=[
            {"role": "system", "content": system_message},
            {"role": "user", "content": user_message}
        ],
        temperature=0.2,
        max_tokens=2000
    )

    return completion.choices[0].message.content


# ---------------- Gradio UI ----------------
with gr.Blocks() as demo:
    gr.Markdown("## 🧪 AI Health Assistant (Extended Biomarkers via Grok API)")

    with gr.Row():
        with gr.Column():
            albumin = gr.Textbox(label="Albumin (g/dL)", value="4.5")
            creatinine = gr.Textbox(label="Creatinine (mg/dL)", value="1.5")
            glucose = gr.Textbox(label="Glucose (mg/dL, fasting)", value="160")
            crp = gr.Textbox(label="CRP (mg/L)", value="2.5")
            mcv = gr.Textbox(label="MCV (fL)", value="150")
            rdw = gr.Textbox(label="RDW (%)", value="15")
            alp = gr.Textbox(label="ALP (U/L)", value="146")
            wbc = gr.Textbox(label="WBC (10^3/μL)", value="10.5")
            lymphocytes = gr.Textbox(label="Lymphocytes (%)", value="38")
            hemoglobin = gr.Textbox(label="Hemoglobin (g/dL)", value="13.5")
            pv = gr.Textbox(label="Plasma Viscosity (mPa·s)", value="1.7")

        with gr.Column():
            age = gr.Textbox(label="Age (years)", value="30")
            gender = gr.Dropdown(choices=["Male", "Female"], label="Gender", value="Male")
            height = gr.Textbox(label="Height (cm)", value="170")
            weight = gr.Textbox(label="Weight (kg)", value="65")

    output = gr.Textbox(label="AI Health Report", lines=30)

    btn = gr.Button("Generate Report")
    btn.click(
        respond,
        inputs=[
            albumin, creatinine, glucose, crp, mcv, rdw, alp, wbc,
            lymphocytes, hemoglobin, pv, age, gender, height, weight
        ],
        outputs=output
    )

if __name__ == "__main__":
    demo.launch()