"""
Planning AI Suggestions
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Reads the business profile and generates actionable task / milestone suggestions
grounded in the BFF data and "Built on Rock" philosophy.

Routes:
  POST /api/planning/suggest  →  task or milestone suggestions
"""

import json
from datetime import datetime, timedelta
from fastapi import APIRouter, HTTPException, Depends
from pydantic import BaseModel
from firebase_admin import firestore
from utils.rate_limiter import with_rate_limit
from utils.groq_client import call_groq_json, HEAVY_MODEL
from utils.pinecone_client import query_book_context

router = APIRouter()


class SuggestRequest(BaseModel):
    userId:     str
    businessId: str
    type:       str          # "tasks" | "milestones"
    existing:   list[str] = []  # existing task/milestone titles (to avoid duplicates)


def _read_context(user_id: str, business_id: str) -> dict:
    db  = firestore.client()
    biz = (
        db.collection("user_data").document(user_id)
        .collection("businesses").document(business_id)
    )
    ctx: dict = {}
    for key in ["businessIdentity", "marketData", "businessModel"]:
        doc = biz.collection("profile_output").document(key).get()
        if doc.exists:
            ctx[key] = doc.to_dict()
    s1 = biz.collection("bff").document("section1").get()
    if s1.exists:
        ctx["section1"] = s1.to_dict()
    return ctx


@router.post("/suggest")
def suggest_planning_items(
    body: SuggestRequest,
    user: dict = Depends(with_rate_limit("generation")),
):
    if body.type not in ("tasks", "milestones"):
        raise HTTPException(status_code=400, detail="type must be 'tasks' or 'milestones'")

    ctx  = _read_context(body.userId, body.businessId)
    biz_name  = ctx.get("businessIdentity", {}).get("businessName", "this business")
    sector    = ctx.get("businessIdentity", {}).get("sector", "")
    value_prop = ctx.get("businessIdentity", {}).get("valueProposition", "")
    summary   = ctx.get("businessIdentity", {}).get("summary", "")

    book_ctx = query_book_context(
        f"action plan milestones tasks Nigerian entrepreneur {sector}", top_k=2
    )

    existing_str = (
        f"\nDo NOT duplicate any of these existing items: {body.existing}"
        if body.existing else ""
    )

    system = (
        "You are a business consultant helping a Nigerian entrepreneur plan their next steps. "
        "Suggest practical, specific, achievable actions grounded in the Business Footing Framework. "
        "All suggestions must be relevant to their specific business — no generic advice. "
        "Write in plain English. Return ONLY valid JSON."
        + (f"\n\n{book_ctx}" if book_ctx else "")
    )

    if body.type == "tasks":
        prompt = f"""
Business: {biz_name} ({sector})
Value proposition: {value_prop}
Summary: {summary[:400]}
{existing_str}

Generate exactly 5 actionable Kanban tasks for this business right now.
Tasks should be specific, achievable within 2 weeks, and move the business forward.
Spread them across different priorities: some for this week, some for next week.

Return JSON:
{{
  "suggestions": [
    {{
      "title": "specific task title",
      "description": "why this matters for {biz_name}",
      "column": "todo"
    }},
    ...
  ]
}}

column must be one of: "todo", "in_progress", "done"
Most tasks should be "todo" unless clearly already started.
"""
    else:  # milestones
        today = datetime.now()
        dates = [(today + timedelta(days=d)).strftime("%Y-%m-%d") for d in [30, 60, 90, 180, 365]]
        prompt = f"""
Business: {biz_name} ({sector})
Value proposition: {value_prop}
Summary: {summary[:400]}
{existing_str}

Generate exactly 5 business milestones for the next 12 months.
Milestones should be measurable achievements that mark significant progress.
Space them across different timeframes.

Available target dates to choose from: {dates}
(Choose the most appropriate date for each milestone)

Return JSON:
{{
  "suggestions": [
    {{
      "title": "milestone title (specific and measurable)",
      "targetDate": "YYYY-MM-DD"
    }},
    ...
  ]
}}
"""

    try:
        result = call_groq_json(
            system, prompt, model=HEAVY_MODEL, max_tokens=800,
            fixture=f"planning_{body.type}",
        )
        suggestions = result.get("suggestions", [])
        if not suggestions:
            raise ValueError("No suggestions returned")
        return {"suggestions": suggestions}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Suggestion generation failed: {str(e)}")