rgboards/rg-boards

Lanes, team task boards you run from the web or from Claude/ChatGPT (MCP). FastAPI + DataK3 + appid + Dodil Models.

• dodil-challenge
• dodil-challenge-boards

A remix template · 0 remixes · Remix rgboards/rg-boards

app/boards/infrastructure/dodil.py

"""The Dodil side: a service-account token, DataK3 on the Postgres wire, and Dodil Models.

The remix generated the service account and put its id and secret into the repo's CI secrets;
.dodil/deploy.yaml hands them to the app as environment variables.
"""
import os
import threading
import time

import httpx
import psycopg

TOKEN_URL = "https://id.dodil.io/realms/dodil/protocol/openid-connect/token"
PG_HOST = os.environ.get("PG_HOST", "pg.uk-lon-1.dodil.io")
MODELS_BASE = os.environ.get("MODELS_BASE", "https://api.dodil.io/v1").rstrip("/")
CHAT_MODEL = os.environ.get("CHAT_MODEL", "kimi-k2.6")
EMBED_MODEL = os.environ.get("EMBED_MODEL", "jina-embeddings-v4")

_lock, _tok = threading.Lock(), {"v": None, "exp": 0.0}


def token() -> str:
    """A short-lived service-account token (client_credentials), cached until near expiry.
    It is the DataK3 password AND the Models bearer.

    Local only: DODIL_TOKEN=<your own `dodil auth` token> skips the service account."""
    if os.environ.get("DODIL_TOKEN"):
        return os.environ["DODIL_TOKEN"]
    with _lock:
        if _tok["v"] and time.time() < _tok["exp"] - 60:
            return _tok["v"]
        r = httpx.post(TOKEN_URL, timeout=15, data={
            "grant_type": "client_credentials",
            "client_id": os.environ["DODIL_SERVICE_ACCOUNT_ID"],
            "client_secret": os.environ["DODIL_SERVICE_ACCOUNT_SECRET"]})
        r.raise_for_status()
        d = r.json()
        _tok.update(v=d["access_token"], exp=time.time() + float(d.get("expires_in", 300)))
        return _tok["v"]


def connect() -> psycopg.Connection:
    """DataK3 speaks Postgres: the database is the bucket, TLS is required."""
    return psycopg.connect(host=PG_HOST, port=5432, dbname=os.environ["BUCKET"], user="token",
                           password=token(), sslmode="require", autocommit=True)


def _unwrap(body: dict) -> dict:
    """The gateway may wrap the OpenAI body as {"status": ..., "data": {...}}."""
    inner = body.get("data") if isinstance(body, dict) else None
    if isinstance(inner, dict) and ("choices" in inner or "data" in inner):
        return inner
    return body


def chat(prompt: str, system: str = "") -> str:
    """One chat call to Dodil Models (OpenAI-compatible)."""
    messages = ([{"role": "system", "content": system}] if system else []) + \
        [{"role": "user", "content": prompt}]
    r = httpx.post(f"{MODELS_BASE}/chat/completions", timeout=120,
                   headers={"Authorization": f"Bearer {token()}"},
                   json={"model": CHAT_MODEL, "messages": messages})
    r.raise_for_status()
    body = _unwrap(r.json())
    return (body["choices"][0]["message"].get("content") or "").strip()


def embed(texts: list) -> list:
    """Embeddings from Dodil Models (jina-embeddings-v4), in input order."""
    out = []
    for i in range(0, len(texts), 32):
        r = httpx.post(f"{MODELS_BASE}/embeddings", timeout=120,
                       headers={"Authorization": f"Bearer {token()}"},
                       json={"model": EMBED_MODEL, "input": [t[:4000] for t in texts[i:i + 32]]})
        r.raise_for_status()
        rows = sorted(_unwrap(r.json())["data"], key=lambda d: d.get("index", 0))
        out += [d["embedding"] for d in rows]
    return out


class ModelsAssistant:
    def checklist(self, card_title: str, description: str = "") -> list:
        text = chat("Break this task into a short checklist of 3 to 6 concrete steps. "
                    "One step per line, no numbering, no preamble, nothing else.\n\n"
                    f"Task: {card_title}\n{description}".strip())
        steps = [line.strip().lstrip("-*•0123456789.)[] ").strip() for line in text.splitlines()]
        return [s for s in steps if s][:8]

    def summary(self, board_title: str, facts: str) -> str:
        return chat(f"Board: {board_title}\n{facts}",
                    system="You write a short daily summary of a team task board for its "
                           "members: at most 5 bullet points covering what moved, what is "
                           "overdue, what is blocked and who should look at what. Plain text, "
                           "use the card numbers like #12. No preamble.")

    def embed(self, texts: list) -> list:
        return embed(texts)