satiregram/HealthDataOps-Env

1#!/usr/bin/env python32"""3Gradio interactive demo for HealthDataOps-Env.4Deployed as a Hugging Face Space with tag: openenv5 6Run locally:7    PYTHONPATH=. python3 app.py8"""9 10import os11import sys12import json13 14sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))15 16import gradio as gr17from env.health_data_ops_env import HealthDataOpsEnv18 19# ─── Helpers ──────────────────────────────────────────────────────────────────20 21def format_obs(obs: dict) -> str:22    return json.dumps(obs, indent=2)23 24def run_task1(is_valid: bool, issue_type: str, issue_desc: str):25    env = HealthDataOpsEnv()26    obs, info = env.reset()27    obs_str = format_obs(obs)28 29    issues = []30    if issue_type != "none" and issue_desc.strip():31        issues.append({"issue_type": issue_type, "description": issue_desc.strip()})32 33    action = {"is_valid": is_valid, "issues": issues}34    _, reward, _, info2 = env.step(action)35 36    result = {37        "task": info2["task_completed"],38        "reward": round(reward, 3),39        "action_submitted": action40    }41    return obs_str, json.dumps(result, indent=2)42 43def run_task2(anomaly_types_raw: str):44    env = HealthDataOpsEnv()45    obs, info = env.reset()46    # Skip task 1 quickly47    env.step({"is_valid": True, "issues": []})48    # Now task 249    obs, info = env._load_current_task()50    obs_str = format_obs(obs)51 52    records = obs.get("batch_records", [])53    lines = [l.strip() for l in anomaly_types_raw.strip().splitlines() if l.strip()]54    severity_map = {55        "none": "low", "missing_field": "medium",56        "outlier_vital": "high", "privacy_risk_pii": "high", "duplicate": "low"57    }58    anomalies = []59    for i, rec in enumerate(records):60        atype = lines[i] if i < len(lines) else "none"61        atype = atype if atype in severity_map else "none"62        anomalies.append({63            "record_id": rec["record_id"],64            "anomaly_type": atype,65            "severity": severity_map[atype],66            "suggested_action": "Review record.",67            "confidence_score": 0.868        })69 70    action = {"anomalies": anomalies}71    _, reward, _, info2 = env.step(action)72    result = {"task": info2["task_completed"], "reward": round(reward, 3)}73    return obs_str, json.dumps(result, indent=2)74 75def run_task3(risk: str, diet: str, activity: str, med_timing: str):76    env = HealthDataOpsEnv()77    obs, _ = env.reset()78    env.step({"is_valid": True, "issues": []})79    dummy_records = [{"record_id": "X", "anomaly_type": "none", "severity": "low",80                      "suggested_action": "N/A", "confidence_score": 0.5}]81    env.step({"anomalies": dummy_records})82    obs, info = env._load_current_task()83    obs_str = format_obs(obs)84 85    action = {86        "risk_assessment": risk,87        "dietary_adjustments": diet,88        "medication_timing_adjustments": med_timing if med_timing.strip() else None,89        "safe_activity_recommendation": activity90    }91    _, reward, _, info2 = env.step(action)92    result = {"task": info2["task_completed"], "reward": round(reward, 3)}93    return obs_str, json.dumps(result, indent=2)94 95def run_full_heuristic():96    """Run the full heuristic baseline and return results."""97    from baseline.run_baseline import (98        HealthDataOpsEnv, heuristic_task1, heuristic_task2, heuristic_task399    )100    env = HealthDataOpsEnv()101    obs, info = env.reset()102    dispatch = [heuristic_task1, heuristic_task2, heuristic_task3]103    scores = {}104    log = []105    terminated = False106    while not terminated:107        idx = info["task_index"]108        action = dispatch[idx](obs)109        obs, reward, terminated, info = env.step(action)110        scores[info["task_completed"]] = round(reward, 3)111        log.append(f"  {info['task_completed']}: {reward:.3f}")112 113    avg = sum(scores.values()) / len(scores)114    log.append(f"\n  Overall Average: {avg:.3f}")115    return "\n".join(log), json.dumps(scores, indent=2)116 117# ─── UI ───────────────────────────────────────────────────────────────────────118 119with gr.Blocks() as demo:120 121    gr.HTML("""122    <div class="header">123      <h1>🏥 HealthDataOps-Env</h1>124      <p>An OpenEnv AI agent training environment for Health Informatics · 125         <a href="https://huggingface.co" target="_blank">🤗 Hugging Face</a></p>126    </div>127    """)128 129    with gr.Tabs():130 131        # ── Tab 0: Quick Demo ──────────────────────────────────────────────────132        with gr.Tab("⚡ Quick Demo (Heuristic Agent)"):133            gr.Markdown("""134Run the built-in heuristic baseline agent across all 3 tasks instantly.135No API key needed.136            """)137            run_btn = gr.Button("▶ Run Full Heuristic Baseline", variant="primary")138            with gr.Row():139                log_out = gr.Textbox(label="Task Scores", lines=8)140                json_out = gr.JSON(label="Score JSON")141            run_btn.click(fn=run_full_heuristic, outputs=[log_out, json_out])142 143        # ── Tab 1: Diet Validator ──────────────────────────────────────────────144        with gr.Tab("🥗 Task 1 — Diet Validator"):145            gr.Markdown("""146**Difficulty:** Easy  147Submit a validation action for a newly generated patient diet plan.148            """)149            is_valid = gr.Checkbox(label="Mark plan as valid?", value=True)150            issue_type = gr.Dropdown(151                choices=["none","allergen_conflict","imbalanced_macros","wrong_meal_frequency","other"],152                value="none", label="Issue Type (if any)"153            )154            issue_desc = gr.Textbox(label="Issue Description", placeholder="e.g. Peanuts found in plan despite allergy")155            t1_btn = gr.Button("Submit Action", variant="primary")156            with gr.Row():157                t1_obs = gr.Textbox(label="Observation", lines=12)158                t1_result = gr.JSON(label="Result")159            t1_btn.click(fn=run_task1, inputs=[is_valid, issue_type, issue_desc], outputs=[t1_obs, t1_result])160 161        # ── Tab 2: EHR Triage ─────────────────────────────────────────────────162        with gr.Tab("🏥 Task 2 — EHR Triage"):163            gr.Markdown("""164**Difficulty:** Medium  165Enter one anomaly type per line (10 lines for 10 records).  166Options: `none` · `missing_field` · `outlier_vital` · `privacy_risk_pii` · `duplicate`167            """)168            anomaly_input = gr.Textbox(169                label="Anomaly Types (one per line, 10 lines)",170                lines=10,171                value="\n".join(["none"] * 10),172                placeholder="none\nmissing_field\noutlier_vital\n..."173            )174            t2_btn = gr.Button("Submit Action", variant="primary")175            with gr.Row():176                t2_obs = gr.Textbox(label="Observation (batch_records)", lines=20)177                t2_result = gr.JSON(label="Result")178            t2_btn.click(fn=run_task2, inputs=[anomaly_input], outputs=[t2_obs, t2_result])179 180        # ── Tab 3: Weather Health ─────────────────────────────────────────────181        with gr.Tab("🌤 Task 3 — Weather Health"):182            gr.Markdown("""183**Difficulty:** Hard  184Craft a weather-aware health recommendation for the generated patient + weather profile.185            """)186            risk = gr.Textbox(label="Risk Assessment", lines=2,187                              placeholder="Describe the patient's health risks today…")188            diet = gr.Textbox(label="Dietary Adjustments", lines=2,189                              placeholder="Specific food/recipe recommendations…")190            activity = gr.Textbox(label="Safe Activity Recommendation", lines=2,191                                  placeholder="Exercise or activity guidance…")192            med_timing = gr.Textbox(label="Medication Timing Adjustments (optional)", lines=1,193                                    placeholder="Leave blank if N/A")194            t3_btn = gr.Button("Submit Action", variant="primary")195            with gr.Row():196                t3_obs = gr.Textbox(label="Observation", lines=12)197                t3_result = gr.JSON(label="Result")198            t3_btn.click(fn=run_task3, inputs=[risk, diet, activity, med_timing],199                         outputs=[t3_obs, t3_result])200 201        # ── Tab 4: About ──────────────────────────────────────────────────────202        with gr.Tab("📋 About"):203            gr.Markdown("""204## HealthDataOps-Env205An OpenEnv AI agent training environment for Health Informatics professionals.206 207### Tasks208| Task | Difficulty | Domain |209|------|-----------|--------|210| Patient Diet Plan Validator | Easy | Clinical Nutrition |211| EHR Anomaly Detection & Triage | Medium | Data Quality / HIPAA |212| Weather-Aware Health Recommendations | Hard | Personalized Medicine |213 214### Reward Function215| Signal | Reward |216|--------|--------|217| Correct issue identification | +0.20 |218| Correct severity classification | +0.15 |219| Medically safe recommendation | +0.25 |220| Contradicted medical guidelines | −0.30 |221| Repeated / loop action | −0.10 |222| Full task completion bonus | +0.10 |223 224### Links225- [GitHub Repository](https://github.com)  226- Built with Python · Pydantic · Faker · Gradio227            """)228 229if __name__ == "__main__":230    demo.launch()231