app/advisor.py

"""AOI Advisor — Claude-powered region insight for analysis recommendations."""
from __future__ import annotations

import json
import logging
from datetime import date

from app.config import ANTHROPIC_API_KEY

logger = logging.getLogger(__name__)

_SYSTEM_PROMPT = """\
You are a remote sensing advisor for humanitarian programme teams. Given a geographic location, provide a brief analysis recommendation.

Available EO products:
- ndvi: Vegetation health from Sentinel-2. Detects drought, crop stress, deforestation.
- water: Water extent (MNDWI) from Sentinel-2. Detects flooding, drought, reservoir changes.
- sar: Radar backscatter from Sentinel-1. Detects ground surface changes, flooding, construction.
- buildup: Settlement extent (NDBI) from Sentinel-2. Detects urban growth, displacement camps.

Coverage: East Africa region. Resolution: 100m. Max analysis window: 3 years.

Respond with JSON only, no markdown. Structure:
{
  "context": "1-3 sentences about this region and recent relevant events",
  "recommended_start": "YYYY-MM-DD",
  "recommended_end": "YYYY-MM-DD",
  "product_priorities": ["product_id", ...],
  "reasoning": "1 sentence per EO product explaining why it is relevant here"
}"""

_EMPTY_RESPONSE = {
    "context": None,
    "recommended_start": None,
    "recommended_end": None,
    "product_priorities": None,
    "reasoning": None,
}

# Lazily-initialized Anthropic client (reused across requests for connection pooling)
_client = None


def _get_client():
    global _client
    if _client is None:
        import anthropic
        _client = anthropic.AsyncAnthropic(api_key=ANTHROPIC_API_KEY)
    return _client


async def get_aoi_advice(bbox: list[float]) -> dict:
    """Call Claude to get region-aware analysis recommendations.

    Returns structured advice dict. On any failure, returns all-null dict.
    """
    if not ANTHROPIC_API_KEY:
        logger.warning("ANTHROPIC_API_KEY not set — skipping AOI advisor")
        return _EMPTY_RESPONSE

    center_lng = (bbox[0] + bbox[2]) / 2
    center_lat = (bbox[1] + bbox[3]) / 2
    today = date.today().isoformat()

    lat_label = f"{abs(center_lat):.4f}°{'N' if center_lat >= 0 else 'S'}"
    lng_label = f"{abs(center_lng):.4f}°{'E' if center_lng >= 0 else 'W'}"

    user_prompt = (
        f"Location: {lat_label}, {lng_label}\n"
        f"Current date: {today}\n"
        f"Recommend an analysis timeframe and indicator priorities for this area."
    )

    try:
        client = _get_client()
        message = await client.messages.create(
            model="claude-haiku-4-5-20251001",
            max_tokens=500,
            temperature=0,
            system=_SYSTEM_PROMPT,
            messages=[{"role": "user", "content": user_prompt}],
        )

        raw = message.content[0].text
        advice = json.loads(raw)

        # Validate expected keys are present
        for key in ("context", "recommended_start", "recommended_end", "product_priorities", "reasoning"):
            if key not in advice:
                logger.warning("AOI advisor response missing key: %s", key)
                return _EMPTY_RESPONSE

        # Validate dates are parseable
        date.fromisoformat(advice["recommended_start"])
        date.fromisoformat(advice["recommended_end"])

        # Filter product_priorities to only known indicators
        valid_ids = {"ndvi", "water", "sar", "buildup"}
        advice["product_priorities"] = [
            i for i in advice["product_priorities"] if i in valid_ids
        ]

        return advice

    except Exception as exc:
        logger.warning("AOI advisor failed: %s", exc)
        return _EMPTY_RESPONSE