api.py was 933 lines mixing four distinct concerns: indicators + news + strategic log (the JSON/HTMX API proper), the chat endpoint + its three private helpers (~200 lines), and the two HTML-only ops endpoints /markets-bar + /health (~150 lines). Extracted: - app/routers/chat.py — POST /api/chat + _latest_quotes_by_group_chat, _thesis_headlines_for_chat, _month_spend - app/routers/ops.py — GET /api/markets-bar + GET /api/health + _fmt_price helper Both new routers use the same dependencies=[Depends(require_token)] as api.py and are mounted at the /api prefix in app/main.py. URL surface is byte-identical with no externally-visible change. api.py shrinks to ~620 lines focused on indicators+news+log+settings. Helpers shared with the original api.py (_md_to_html, _resolve_tone_param) are imported from app.routers.api where needed in chat.py to avoid duplication. Also updated tests/test_chat_and_log_gates.py to mount chat_router in its local test app, since /api/chat now lives there. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
193 lines
6.6 KiB
Python
193 lines
6.6 KiB
Python
"""Chat endpoint — POST /api/chat.
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Grounded on the latest strategic log, current market quotes, and
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thesis-filtered headlines. Ephemeral: the conversation lives in the
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client; this endpoint just records each call's cost in `ai_calls`.
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"""
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from __future__ import annotations
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from collections import defaultdict
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from datetime import timedelta
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import httpx
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from fastapi import APIRouter, Depends, HTTPException
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from pydantic import BaseModel, Field
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from sqlalchemy import desc, func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.auth import require_token, maybe_current_user, CurrentUser
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from app.config import get_settings
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from app.db import get_session, utcnow
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from app.jobs._market_context import REFERENCE_LINE
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from app.models import AICall, Headline, Quote, StrategicLog
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from app.routers.api import _md_to_html
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from app.services.llm_prompts import build_chat_system_prompt
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from app.services.openrouter import call_llm, month_start
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router = APIRouter(dependencies=[Depends(require_token)])
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# ---------------------------------------------------------------------------
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# Pydantic models
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# ---------------------------------------------------------------------------
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class ChatMessage(BaseModel):
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role: str = Field(pattern="^(user|assistant)$")
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content: str
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class ChatRequest(BaseModel):
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messages: list[ChatMessage]
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# ---------------------------------------------------------------------------
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# Private helpers
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# ---------------------------------------------------------------------------
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THESIS_KEYWORDS_FALLBACK = [
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"hormuz", "iran", "opec", "brent", "wti", "crude", "oil",
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"china", "taiwan", "yuan", "fed", "inflation", "cpi", "yield",
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"gold", "dollar", "yen", "saudi", "russia", "ukraine", "israel",
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"nato", "defence", "defense",
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]
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async def _latest_quotes_by_group_chat(session: AsyncSession) -> dict[str, list[dict]]:
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sub = (
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select(Quote.group_name, Quote.symbol,
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func.max(Quote.fetched_at).label("mx"))
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.group_by(Quote.group_name, Quote.symbol)
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.subquery()
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)
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rows = (await session.execute(
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select(Quote).join(
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sub,
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(Quote.group_name == sub.c.group_name)
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& (Quote.symbol == sub.c.symbol)
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& (Quote.fetched_at == sub.c.mx),
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).order_by(Quote.group_name, Quote.symbol)
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)).scalars().all()
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by_group: dict[str, list[dict]] = defaultdict(list)
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for q in rows:
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by_group[q.group_name].append({
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"symbol": q.symbol, "label": q.label,
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"price": q.price, "currency": q.currency,
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"as_of": q.as_of, "changes": q.changes,
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})
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return by_group
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async def _thesis_headlines_for_chat(session: AsyncSession, limit: int = 50) -> list[dict]:
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cutoff = utcnow() - timedelta(hours=24)
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rows = (await session.execute(
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select(Headline)
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.where(Headline.published_at >= cutoff)
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.order_by(desc(Headline.published_at))
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.limit(300)
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)).scalars().all()
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out = []
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for h in rows:
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if any(kw in h.title.lower() for kw in THESIS_KEYWORDS_FALLBACK):
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out.append({"source": h.source, "title": h.title})
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if len(out) >= limit:
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break
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return out
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async def _month_spend(session: AsyncSession) -> float:
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total = (await session.execute(
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select(func.coalesce(func.sum(AICall.cost_usd), 0.0))
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.where(AICall.called_at >= month_start())
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)).scalar()
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return float(total or 0.0)
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# ---------------------------------------------------------------------------
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# Route
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# ---------------------------------------------------------------------------
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@router.post("/chat")
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async def chat(
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body: ChatRequest,
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session: AsyncSession = Depends(get_session),
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principal: CurrentUser | None = Depends(maybe_current_user),
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):
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"""Answer one user turn given the conversation so far. Grounded on the
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latest strategic log + market data + thesis-filtered headlines.
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Ephemeral — the conversation lives entirely in the client; the endpoint
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just records each call's cost in `ai_calls`."""
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# Paid-only feature. Free users get the static log but not the
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# interactive chat (see /pricing).
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from app.services.access import is_paid_active
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if not is_paid_active(principal):
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raise HTTPException(
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status_code=402,
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detail={"code": "paid_required",
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"message": "Follow-up chat is a paid-tier feature."},
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)
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s = get_settings()
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if not s.OPENROUTER_API_KEY:
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raise HTTPException(status_code=503, detail="OPENROUTER_API_KEY not set")
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# Monthly cost cap — same one the log job respects.
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spent = await _month_spend(session)
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if spent >= s.OPENROUTER_MONTHLY_CAP_USD:
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raise HTTPException(
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status_code=429,
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detail=f"Monthly OpenRouter cap reached (${spent:.2f})",
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)
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# Trim runaway conversations: keep last 20 turns.
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history = body.messages[-20:]
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if not history or history[-1].role != "user":
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raise HTTPException(status_code=400, detail="Last message must be user")
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# Gather grounding context.
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log_row = (await session.execute(
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select(StrategicLog).order_by(desc(StrategicLog.generated_at)).limit(1)
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)).scalar_one_or_none()
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quotes = await _latest_quotes_by_group_chat(session)
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headlines = await _thesis_headlines_for_chat(session)
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system_prompt = build_chat_system_prompt(
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s.CASSANDRA_TONE, s.CASSANDRA_ANALYSIS,
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log_content=log_row.content if log_row else None,
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log_generated_at=log_row.generated_at if log_row else None,
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quotes_by_group=quotes,
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headlines=headlines,
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reference_line=REFERENCE_LINE,
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)
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msgs = [{"role": "system", "content": system_prompt}]
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for m in history:
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msgs.append({"role": m.role, "content": m.content})
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try:
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async with httpx.AsyncClient(follow_redirects=True) as client:
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result = await call_llm(client, msgs)
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except Exception as e:
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session.add(AICall(
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model=s.OPENROUTER_MODEL, status="error", error=str(e)[:500],
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))
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await session.commit()
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raise HTTPException(status_code=502, detail=f"OpenRouter error: {e}")
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session.add(AICall(
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model=result.model,
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prompt_tokens=result.prompt_tokens,
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completion_tokens=result.completion_tokens,
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cost_usd=result.cost_usd,
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status="ok",
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))
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await session.commit()
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return {
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"role": "assistant",
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"content": result.content,
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"content_html": _md_to_html(result.content),
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"prompt_tokens": result.prompt_tokens,
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"completion_tokens": result.completion_tokens,
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}
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