import gradio as gr
import requests
import json
import os

# -----------------------------
# CONFIG
# -----------------------------
GROQ_API_KEY = os.getenv("GROQ_API_KEY")

DEVICE_PARAMS = {
    "Apple Watch": [
        "RMSSD", "lnRMSSD", "MeanRR", "HR", "SDNN",
        "StressScore", "baseline", "pNN50", "AMo50", "MxDMn"
    ],
    "Polar": [
        "RMSSD", "SDNN", "MeanRR", "HR", "pNN50", "StressScore"
    ],
    "Garmin": [
        "RMSSD", "SDNN", "MeanRR", "HR", "StressScore"
    ],
    "Other": [
        "RMSSD", "SDNN", "MeanRR", "HR", "pNN50", "AMo50",
        "StressScore", "baseline", "MxDMn"
    ],
}

THRESHOLDS = """
Use these physiological ranges for interpretation:

- RMSSD: Low <25, Moderate 25–60, High >60
- SDNN: Low <40, Moderate 40–70, High >70
- lnRMSSD: Low <3.0, Moderate 3.0–3.9, High >3.9
- HR: High stress >80 bpm, Normal 55–80, Excellent <55
- MeanRR: Low <700 (fast heart rate, higher stress), Moderate 700–950 (balanced rhythm), High >950 (good recovery)
- StressScore: Low <30, Moderate 30–60, High >60
- Baseline: <10 = low trend, 10–12 = stable, >12 = improving
- pNN50: Low <10%, Moderate 10–25%, High >25%
- AMo50: Low <1.5 (good adaptability), High >2.5 (rigidity)
- CV: Low <2, Moderate 2–6, High >6
"""

# -----------------------------
# Groq API Call
# -----------------------------
def call_groq_api(device, data):
    prompt = f"""
You are a Welltory-style health assistant who analyzes HRV data with empathy and scientific precision.

Here is the HRV dataset from a {device} device:
{json.dumps(data, indent=2)}

{THRESHOLDS}

Instructions:
1. Evaluate each parameter relative to its physiological range.
2. Explain what it means for stress, recovery, and adaptability.
3. If baseline > 0, describe it as a long-term recovery trend.
4. Maintain a calm, motivating, yet realistic tone — if HRV is low or stress is high, clearly say so.
5. Address the user directly using “you” and “your”.
6. Do not mention numeric thresholds in the output.
7. Output in Markdown format with these sections:

**Parameter Insights:**
[List of parameters, each explained clearly — what it measures, what the value means, and what it indicates.]

**Overall Interpretation:**
[A realistic summary of stress, recovery, and physiological state.]

**Actionable Suggestions:**
[3–4 specific, habit-based recommendations to improve HRV and stress recovery.]

If most parameters indicate stress or low HRV, the output tone should sound *concerned but encouraging*, not overly positive.
"""

    headers = {
        "Authorization": f"Bearer {GROQ_API_KEY}",
        "Content-Type": "application/json",
    }

    body = {
        "model": "llama-3.3-70b-versatile",
        "messages": [{"role": "user", "content": prompt}],
        "temperature": 0.4,  # lower temperature = more consistent, realistic tone
    }

    response = requests.post(
        "https://api.groq.com/openai/v1/chat/completions",
        headers=headers,
        json=body
    )

    try:
        return response.json()["choices"][0]["message"]["content"]
    except Exception as e:
        return f"⚠️ Error: {e}\n\nRaw response: {response.text}"

# -----------------------------
# HRV Analyzer
# -----------------------------
def analyze_hrv(device, *values):
    params = DEVICE_PARAMS.get(device, [])
    data = {p: v for p, v in zip(params, values) if v is not None and v != 0}
    if not data:
        return "⚠️ Please input at least one HRV parameter."
    return call_groq_api(device, data)

# -----------------------------
# Dynamic Parameter Visibility
# -----------------------------
def update_params(device):
    visible_params = DEVICE_PARAMS.get(device, [])
    updates = [gr.update(visible=(p in visible_params)) for p in ALL_PARAM_NAMES]
    return updates

# -----------------------------
# BUILD GRADIO UI
# -----------------------------
with gr.Blocks() as demo:
    gr.Markdown("## 💓 HRV Wellness Insight — Powered by Groq")

    device = gr.Dropdown(
        choices=list(DEVICE_PARAMS.keys()),
        value="Apple Watch",
        label="Select Your Device",
    )

    ALL_PARAM_NAMES = sorted({p for params in DEVICE_PARAMS.values() for p in params})

    with gr.Row():
        param_inputs = [
            gr.Number(label=p, visible=(p in DEVICE_PARAMS["Apple Watch"]))
            for p in ALL_PARAM_NAMES
        ]

    analyze_btn = gr.Button("🔍 Analyze HRV")
    output = gr.Markdown()

    analyze_btn.click(fn=analyze_hrv, inputs=[device] + param_inputs, outputs=output)
    device.change(fn=update_params, inputs=device, outputs=param_inputs)

# -----------------------------
# RUN APP
# -----------------------------
if __name__ == "__main__":
    demo.launch()