# api/router_consensus.py
from fastapi import APIRouter, Depends
import numpy as np
from typing import List
from consensus.topo import TopologicalConsciousness
from consensus.metrics import weighted_average_text
from api.schemas import AskRequest, AskResponse
from adapters.base import BaseModelAdapter

router = APIRouter(prefix="/consensus", tags=["consensus"])

def get_models() -> List[BaseModelAdapter]:
    from adapters.openai_adapter import OpenAIAdapter
    from adapters.anthropic_adapter import AnthropicAdapter
    # Two different adapters to enable nontrivial coherence
    return [OpenAIAdapter(), AnthropicAdapter()]

@router.post("/ask", response_model=AskResponse)
def ask(req: AskRequest, models: List[BaseModelAdapter] = Depends(get_models)):
    tc = TopologicalConsciousness(n_anyons=len(models), central_charge=627)
    responses = [m.generate(req.prompt) for m in models]
    embs = [np.array(m.embed_text(r), dtype=float) for r in responses]
    pc = tc.calculate_coherence(embs)
    if pc < req.min_confidence:
        return AskResponse(answer=None, confidence=pc,
                           warning="Models disagree - low confidence")
    E = np.stack(embs); sims = E @ E.T
    w = sims.mean(axis=1); w = np.clip(w, 0, None); w = w/(w.sum()+1e-12)
    return AskResponse(answer=weighted_average_text(responses, w),
                       confidence=pc, weights=w.tolist())