meida_backend/scripts/smoke.sh

#!/usr/bin/env bash
# End-to-end proof that the scaffold works against the REAL DeepSeek API.
#
#   compose up → migrate → start API → dev token → POST /v1/agent/chat
#   → print the ob_ai_call row and the bl_ledger rows
#
# This is the only script that spends real money. Everything in `make test` is
# hermetic.
set -Eeuo pipefail

cd "$(dirname "$0")/.."

COMPOSE="docker compose -f deploy/docker-compose.dev.yml"
API_PORT="${API_PORT:-8010}"
BASE="http://127.0.0.1:${API_PORT}"
LOG_DIR=".smoke"
API_LOG="${LOG_DIR}/api.log"
API_PID=""

bold() { printf '\n\033[1m== %s\033[0m\n' "$1"; }
fail() { printf '\033[31mFAIL: %s\033[0m\n' "$1" >&2; exit 1; }

cleanup() {
  if [[ -n "${API_PID}" ]] && kill -0 "${API_PID}" 2>/dev/null; then
    kill "${API_PID}" 2>/dev/null || true
    wait "${API_PID}" 2>/dev/null || true
  fi
}
trap cleanup EXIT

mkdir -p "${LOG_DIR}"

[[ -f .env ]] || fail ".env not found. Copy .env.example to .env and set DEEPSEEK_API_KEY."
# 只取需要的这一个键，不 `source .env`：那些 *_JSON 值含双引号，
# 被 shell 解析后引号会消失，应用侧再读就成了非法 JSON。
DEEPSEEK_API_KEY=$(sed -n 's/^[[:space:]]*DEEPSEEK_API_KEY[[:space:]]*=[[:space:]]*//p' .env | tail -1)
DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY%\"}; DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY#\"}
DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY%\'}; DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY#\'}
[[ -n "${DEEPSEEK_API_KEY}" ]] || fail "DEEPSEEK_API_KEY is empty in .env"
[[ "${DEEPSEEK_API_KEY}" == sk-* ]] || fail "DEEPSEEK_API_KEY does not look like a real key"

bold "1/7  Starting PostgreSQL (pgvector) and Redis"
${COMPOSE} up -d postgres redis
for _ in $(seq 1 60); do
  if ${COMPOSE} exec -T postgres pg_isready -U meida -d meida >/dev/null 2>&1; then break; fi
  sleep 1
done
${COMPOSE} exec -T postgres pg_isready -U meida -d meida >/dev/null || fail "PostgreSQL never became ready"
${COMPOSE} exec -T redis redis-cli ping >/dev/null || fail "Redis never became ready"
echo "postgres + redis ready"

bold "2/7  Applying migrations"
uv run alembic upgrade head
${COMPOSE} exec -T postgres psql -U meida -d meida -c "\dt"
${COMPOSE} exec -T postgres psql -U meida -d meida -tAc \
  "SELECT extname FROM pg_extension WHERE extname='vector'" | grep -q vector \
  || fail "pgvector extension missing"
echo "pgvector extension present"

bold "3/7  Starting the API"
uv run uvicorn apps.api.main:app --host 127.0.0.1 --port "${API_PORT}" >"${API_LOG}" 2>&1 &
API_PID=$!
for _ in $(seq 1 60); do
  if curl -fsS "${BASE}/healthz" >/dev/null 2>&1; then break; fi
  sleep 0.5
done
curl -fsS "${BASE}/healthz" >/dev/null || { cat "${API_LOG}"; fail "API did not start"; }
curl -fsS "${BASE}/readyz" | tee /dev/null >/dev/null || { cat "${API_LOG}"; fail "API not ready"; }
echo "api up on ${BASE} (logs: ${API_LOG})"

bold "4/7  Issuing a dev token"
DEVICE_KEY="smoke-$(date +%s)"
TOKEN_JSON=$(curl -fsS -X POST "${BASE}/v1/auth/dev-token" \
  -H 'Content-Type: application/json' \
  -d "{\"device_key\":\"${DEVICE_KEY}\"}")
TOKEN=$(printf '%s' "${TOKEN_JSON}" | python3 -c 'import json,sys;print(json.load(sys.stdin)["data"]["access_token"])')
USER_ID=$(printf '%s' "${TOKEN_JSON}" | python3 -c 'import json,sys;print(json.load(sys.stdin)["data"]["user_id"])')
[[ -n "${TOKEN}" ]] || fail "no access token issued"
echo "user_id=${USER_ID}"

bold "5/7  Calling POST /v1/agent/chat against the REAL DeepSeek API"
CHAT_JSON=$(curl -fsS -X POST "${BASE}/v1/agent/chat" \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer ${TOKEN}" \
  -d '{"message":"三十岁男生，第一次去互联网公司面试，穿什么比较稳妥？"}')
printf '%s\n' "${CHAT_JSON}" | python3 -m json.tool
# 走临时文件而不是管道：heredoc 会占用 stdin，管道里的 JSON 读不到
printf '%s' "${CHAT_JSON}" >"${LOG_DIR}/chat.json"
python3 - "${LOG_DIR}/chat.json" <<'PY'
import json
import sys

with open(sys.argv[1], encoding="utf-8") as fh:
    body = json.load(fh)
assert body["code"] == 0, body
data = body["data"]
assert data["reply"].strip(), "empty model reply"
usage = data["usage"]

print("\n--- MODEL REPLY -------------------------------------------------")
print(data["reply"])
print("-----------------------------------------------------------------")
print("provider={} model={} prompt={}@{}".format(
    data["provider"], data["model"], data["prompt_id"], data["prompt_version"]))
print("latency={}ms tokens_in={} tokens_out={} cached={} cost_cents={}".format(
    usage["latency_ms"], usage["tokens_in"], usage["tokens_out"],
    usage["tokens_cached"], usage["cost_cents"]))
print("quota_remaining={}".format(data["quota_remaining"]))

# 对话必须在 NFR-PERF-02b 的整轮 15s 之内。这里只量单次 LLM 调用，
# 留出检索与后处理的余量，因此阈值取 10s。
assert usage["latency_ms"] < 10_000, f"LLM 调用耗时 {usage['latency_ms']}ms，超出预期"
PY

bold "6/7  ob_ai_call row (成本归因的唯一数据源, 架构文档 §13)"
${COMPOSE} exec -T postgres psql -U meida -d meida -x -c \
  "SELECT call_id, user_id, scene, provider, model, prompt_id, prompt_version,
          tokens_in, tokens_out, tokens_cached, latency_ms, cost_cents,
          success, error_code, ref_type, created_at
     FROM ob_ai_call
    WHERE user_id = ${USER_ID}
    ORDER BY created_at DESC"
ROWS=$(${COMPOSE} exec -T postgres psql -U meida -d meida -tAc \
  "SELECT count(*) FROM ob_ai_call WHERE user_id = ${USER_ID} AND success")
[[ "${ROWS// /}" -ge 1 ]] || fail "no successful ob_ai_call row was written"

bold "7/7  bl_ledger rows (预扣三段式, 架构文档 §7.4)"
${COMPOSE} exec -T postgres psql -U meida -d meida -c \
  "SELECT tx_id, delta, tx_type, status, quota_key, period_key, balance_after,
          idempotency_key, created_at
     FROM bl_ledger
    WHERE user_id = ${USER_ID}
    ORDER BY created_at"
COMMITTED=$(${COMPOSE} exec -T postgres psql -U meida -d meida -tAc \
  "SELECT count(*) FROM bl_ledger
    WHERE user_id = ${USER_ID} AND tx_type='consume' AND status='committed'")
[[ "${COMMITTED// /}" -ge 1 ]] || fail "quota was not committed after a successful call"

${COMPOSE} exec -T postgres psql -U meida -d meida -c \
  "SELECT quota_key, period_key, used, limit_value FROM bl_quota WHERE user_id = ${USER_ID}"

printf '\n\033[32mSMOKE PASSED\033[0m — real DeepSeek reply received, ob_ai_call and bl_ledger populated.\n'