Blame for routes/consultation.py

"""
AI Consultation Session Routes
──────────────────────────────────────────────────────────────────────────────
Manages proactive AI Consultation sessions distinct from passive AI Chat.

AI Chat:    passive — waits for user questions
Consultation: proactive — AI opens with agenda, leads through structured phases
              (Discovery → Analysis → Prescription) and produces a written report

Routes:
  POST /api/consultation/start  → AI reads profile, generates opening message
  POST /api/consultation/report → AI generates structured report from session
"""

import json
from datetime import datetime
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 StartRequest(BaseModel):
    userId:     str
    businessId: str


class ReportRequest(BaseModel):
    userId:     str
    businessId: str
    messages:   list[dict]  # [{"role": "user"|"assistant", "content": "..."}]


def _read_profile(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", "customerProfile", "marketData"]:
        doc = biz.collection("profile_output").document(key).get()
        if doc.exists:
            ctx[key] = doc.to_dict()
    return ctx


@router.post("/start")
def start_consultation(
    body: StartRequest,
    user: dict = Depends(with_rate_limit("generation")),
):
    """
    Reads the entrepreneur's business profile and generates a warm, structured
    opening message with 5 focus areas. The AI has already 'read the brief'
    so the session starts with context rather than from scratch.
    """
    profile = _read_profile(body.userId, body.businessId)
    identity = profile.get("businessIdentity", {})

    biz_name  = identity.get("businessName",    "your business")
    sector    = identity.get("sector",           "")
    value_prop = identity.get("valueProposition", "")
    summary   = identity.get("summary",          "")

    book_ctx = query_book_context(
        "business consultation strategy discovery analysis Nigerian entrepreneur",
        top_k=2,
    )

    system = (
        "You are a senior business consultant at VenThrive, trained in the "
        "Business Footing Framework from 'Built on Rock' by Iyanuoluwa Joseph Akinnusi. "
        "You are warm, direct, and speak in plain everyday English. "
        "You do NOT use business jargon. You speak like a trusted advisor, not a textbook. "
        "Return ONLY valid JSON."
        + (f"\n\n{book_ctx}" if book_ctx else "")
    )

    prompt = f"""
You are starting a consultation session with the founder of "{biz_name}"
({sector}). Their value proposition is: "{value_prop}".
Brief summary: {summary[:300]}

Generate a warm, professional opening message that:
1. Greets them by referencing their specific business (not generic)
2. Mentions you've reviewed their Business Footing Framework profile
3. Presents exactly 5 focus areas as a numbered list
4. Asks them to pick the one they want to focus on today

The 5 focus areas should be:
1. Strategy & Market Position
2. Customer Acquisition & Retention
3. Financial Planning & Pricing
4. Operations & Standard Processes
5. Investor Readiness & Growth

Return JSON:
{{
  "openingMessage": "<your full opening message here>",
  "focusAreas": ["Strategy & Market Position", "Customer Acquisition & Retention", "Financial Planning & Pricing", "Operations & Standard Processes", "Investor Readiness & Growth"]
}}"""

    try:
        result = call_groq_json(system, prompt, model=HEAVY_MODEL, max_tokens=800, fixture="consultation_start")
        return {
            "openingMessage": result.get("openingMessage", ""),
            "focusAreas":     result.get("focusAreas", []),
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Could not start consultation: {str(e)}")


@router.post("/report")
def generate_report(
    body: ReportRequest,
    user: dict = Depends(with_rate_limit("generation")),
):
    """
    Takes the full session transcript and generates a structured consultation
    report with findings, specific recommendations, and next steps.
    """
    if user.get("uid") != body.userId:
        raise HTTPException(status_code=403, detail="Forbidden.")

    if len(body.messages) < 2:
        raise HTTPException(status_code=400, detail="Session too short to generate a report.")

    transcript = "\n".join([
        f"{'CONSULTANT' if m['role'] == 'assistant' else 'ENTREPRENEUR'}: {m['content']}"
        for m in body.messages
    ])

    book_ctx = query_book_context(
        "consultation findings recommendations action plan Nigerian business",
        top_k=2,
    )

    system = (
        "You are a business consultant writing a formal post-consultation report. "
        "Analyze the conversation and produce a structured, actionable document. "
        "Be specific to what was actually discussed — no generic advice. "
        "Write in clear, plain English. "
        "Return ONLY valid JSON."
        + (f"\n\n{book_ctx}" if book_ctx else "")
    )

    prompt = f"""
Consultation transcript:
{transcript[:4000]}

Today's date: {datetime.now().strftime('%B %d, %Y')}

Write a formal consultation report. Return JSON:
{{
  "date": "{datetime.now().strftime('%B %d, %Y')}",
  "sessionSummary": "2-3 sentences summarising what was discussed and the main concern addressed",
  "keyFindings": [
    "Specific finding 1 from the conversation",
    "Specific finding 2",
    "Specific finding 3"
  ],
  "recommendations": [
    {{
      "action": "What to do",
      "rationale": "Why this matters for their specific business",
      "timeline": "When to do it (e.g. This week / Within 30 days)"
    }}
  ],
  "nextSteps": [
    "Concrete action step 1",
    "Concrete action step 2",
    "Concrete action step 3"
  ],
  "closingNote": "A personalised, encouraging closing sentence referencing their business."
}}"""

    try:
        result = call_groq_json(system, prompt, model=HEAVY_MODEL, max_tokens=2000, fixture="consultation_report")
        return {"report": result}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Report generation failed: {str(e)}")