Persist discovery answers to CSV for reprocessing and recovery

Save each discovery conversation's prompts and answers to durable CSV
files (per-conversation + append-only master log) on both save and
completion, so answers survive an extraction error, can be re-fed to the
AI, and can be reviewed/resumed by the user.

- app/services/answer_store.py: canonical prompt list + atomic CSV writes,
  master append, and read-back helpers (DB stays system of record; CSV
  failures are logged, never fatal).
- discovery router: write CSV on /respond and /complete; new endpoints
  GET /answers, GET /answers.csv, POST /reprocess (shared extraction
  helper; locked profiles return 409).
- discovery.html: prefill/resume from saved answers after an error and a
  "Re-run analysis" button wired to /reprocess.
- scripts/reprocess_csv.py: offline CLI to re-run extraction from a CSV
  (print or --write-db).
- QUESTIONS_DIR / QUESTIONS_MASTER_CSV config, .gitignore, README, tests.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Dg6XWUwprmP5QCL18HxssY
This commit is contained in:
Claude
2026-06-19 01:06:40 +00:00
parent c1daef6411
commit 866bd60225
10 changed files with 988 additions and 51 deletions
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"""Unit tests for the CSV answer store.
These exercise the file I/O directly with a lightweight stand-in for the
DiscoveryConversation/User ORM objects, so they need no database. The
QUESTIONS_DIR / QUESTIONS_MASTER_CSV env vars are pointed at tmp_path.
"""
import csv
import os
from types import SimpleNamespace
from app.services import answer_store
def _conversation(conv_id="conv-1", user_id="user-1", **answers):
base = {
"id": conv_id,
"user_id": user_id,
"prompt_alive": "",
"prompt_friction": "",
"prompt_pull": "",
"prompt_recognition": "",
"prompt_future": "",
"prompt_goals_short": "",
"prompt_goals_long": "",
}
base.update(answers)
return SimpleNamespace(**base)
def _point_env(monkeypatch, tmp_path):
qdir = tmp_path / "questions"
master = tmp_path / "questions_master.csv"
monkeypatch.setenv("QUESTIONS_DIR", str(qdir))
monkeypatch.setenv("QUESTIONS_MASTER_CSV", str(master))
return qdir, master
def test_write_conversation_csv_round_trips(monkeypatch, tmp_path):
_point_env(monkeypatch, tmp_path)
conv = _conversation(prompt_alive="felt alive", prompt_goals_long="big plans")
user = SimpleNamespace(email="a@b.com")
assert answer_store.write_conversation_csv(conv, user, "responses_saved")
path = answer_store.conversation_csv_path("conv-1")
assert os.path.exists(path)
answers = answer_store.read_conversation_answers("conv-1")
assert answers["alive"] == "felt alive"
assert answers["goals_long"] == "big plans"
# Unanswered prompts round-trip as empty strings, all 7 present.
assert len(answers) == 7
assert answers["friction"] == ""
def test_write_is_atomic_overwrite(monkeypatch, tmp_path):
_point_env(monkeypatch, tmp_path)
user = SimpleNamespace(email="a@b.com")
answer_store.write_conversation_csv(
_conversation(prompt_alive="first"), user, "responses_saved"
)
answer_store.write_conversation_csv(
_conversation(prompt_alive="second"), user, "completed"
)
answers = answer_store.read_conversation_answers("conv-1")
assert answers["alive"] == "second"
# No leftover temp file.
assert not os.path.exists(
answer_store.conversation_csv_path("conv-1") + ".tmp"
)
def test_append_master_writes_header_once(monkeypatch, tmp_path):
_, master = _point_env(monkeypatch, tmp_path)
user = SimpleNamespace(email="a@b.com")
answer_store.append_master(
_conversation("c1", prompt_alive="x"), user, "responses_saved"
)
answer_store.append_master(
_conversation("c2", prompt_alive="y"), user, "completed"
)
with open(master, newline="", encoding="utf-8") as fh:
rows = list(csv.DictReader(fh))
# 7 prompts per event, two events.
assert len(rows) == 14
conv_ids = {r["conversation_id"] for r in rows}
assert conv_ids == {"c1", "c2"}
statuses = {r["status"] for r in rows}
assert statuses == {"responses_saved", "completed"}
def test_read_missing_file_returns_empty(monkeypatch, tmp_path):
_point_env(monkeypatch, tmp_path)
assert answer_store.read_conversation_answers("nope") == {}
def test_conversation_csv_text_from_db(monkeypatch, tmp_path):
_point_env(monkeypatch, tmp_path)
conv = _conversation(prompt_pull="natural pull")
user = SimpleNamespace(email="a@b.com")
text = answer_store.conversation_csv_text(conv, user, "completed")
assert "prompt_key" in text # header present
assert "natural pull" in text
assert text.count("\n") >= 8 # header + 7 rows
def test_save_answers_writes_both_artifacts(monkeypatch, tmp_path):
qdir, master = _point_env(monkeypatch, tmp_path)
conv = _conversation(prompt_alive="hi")
user = SimpleNamespace(email="a@b.com")
answer_store.save_answers(conv, user, "responses_saved")
assert os.path.exists(answer_store.conversation_csv_path("conv-1"))
assert os.path.exists(master)
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"""Tests for the discovery CSV/reprocess endpoints.
Run under the X-API-Key admin identity so they don't depend on the Google
OAuth flow. The DiscoveryExtractor is replaced with a fake so no network call
or API key is needed. QUESTIONS_DIR / QUESTIONS_MASTER_CSV are pointed at
tmp_path so the suite never writes into the repo's data dir.
"""
import os
from app.services import answer_store
API_KEY = {"X-API-Key": "test-api-key"}
class FakeExtractor:
"""Stand-in for DiscoveryExtractor: returns a fixed well-formed profile."""
def __init__(self, api_key=None, model=None):
pass
async def extract(self, responses):
return {
"triad": "gut",
"probable_type": 8,
"wing": 9,
"instinctual_variant": "sp",
"instinctual_stack": "sp/so/sx",
"love_summary": "love",
"strength_summary": "strength",
"mission_summary": "mission",
"vocation_summary": "vocation",
"overlap_narrative": "narrative",
"short_term_goals": "short",
"long_term_goals": "long",
"confidence": {
"triad": "high",
"type": "high",
"variant": "medium",
"ikigai": "high",
},
"extraction_notes": "ok",
}
def _patch(monkeypatch, tmp_path):
monkeypatch.setenv("QUESTIONS_DIR", str(tmp_path / "questions"))
monkeypatch.setenv("QUESTIONS_MASTER_CSV", str(tmp_path / "master.csv"))
monkeypatch.setattr(
"app.routers.discovery.DiscoveryExtractor", FakeExtractor
)
async def _start_and_respond(app_client):
start = await app_client.post("/discovery/start", headers=API_KEY)
assert start.status_code == 200
conv_id = start.json()["conversation_id"]
r = await app_client.put(
f"/discovery/{conv_id}/respond",
headers=API_KEY,
json={
"prompt_alive": "I felt alive building things",
"prompt_friction": "unfairness bothers me",
"prompt_goals_short": "ship the app",
},
)
assert r.status_code == 200
return conv_id
async def test_respond_writes_csv(app_client, monkeypatch, tmp_path):
_patch(monkeypatch, tmp_path)
conv_id = await _start_and_respond(app_client)
assert os.path.exists(answer_store.conversation_csv_path(conv_id))
answers = answer_store.read_conversation_answers(conv_id)
assert answers["alive"] == "I felt alive building things"
assert os.path.exists(str(tmp_path / "master.csv"))
async def test_get_answers(app_client, monkeypatch, tmp_path):
_patch(monkeypatch, tmp_path)
conv_id = await _start_and_respond(app_client)
r = await app_client.get(f"/discovery/{conv_id}/answers", headers=API_KEY)
assert r.status_code == 200
body = r.json()
assert body["conversation_id"] == conv_id
assert body["completed_at"] is None
by_key = {a["prompt_key"]: a["answer"] for a in body["answers"]}
assert by_key["friction"] == "unfairness bothers me"
assert len(body["answers"]) == 7
async def test_download_answers_csv(app_client, monkeypatch, tmp_path):
_patch(monkeypatch, tmp_path)
conv_id = await _start_and_respond(app_client)
r = await app_client.get(
f"/discovery/{conv_id}/answers.csv", headers=API_KEY
)
assert r.status_code == 200
assert r.headers["content-type"].startswith("text/csv")
assert "attachment" in r.headers["content-disposition"]
assert "ship the app" in r.text
async def test_reprocess_creates_profile(app_client, monkeypatch, tmp_path):
_patch(monkeypatch, tmp_path)
conv_id = await _start_and_respond(app_client)
r = await app_client.post(
f"/discovery/{conv_id}/reprocess", headers=API_KEY
)
assert r.status_code == 200
body = r.json()
assert body["conversation_id"] == conv_id
assert body["triad"] == "gut"
assert body["probable_type"] == 8
# A profile now exists for the user.
prof = await app_client.get("/discovery/profile/me", headers=API_KEY)
assert prof.status_code == 200
async def test_reprocess_locked_returns_409(app_client, monkeypatch, tmp_path):
_patch(monkeypatch, tmp_path)
conv_id = await _start_and_respond(app_client)
# Complete to create a profile, then lock it via confirm.
complete = await app_client.post(
f"/discovery/{conv_id}/complete", headers=API_KEY
)
assert complete.status_code == 200
confirm = await app_client.put(
"/discovery/profile/me/confirm", headers=API_KEY
)
assert confirm.status_code == 200
r = await app_client.post(
f"/discovery/{conv_id}/reprocess", headers=API_KEY
)
assert r.status_code == 409
async def test_complete_writes_completed_csv(app_client, monkeypatch, tmp_path):
_patch(monkeypatch, tmp_path)
conv_id = await _start_and_respond(app_client)
complete = await app_client.post(
f"/discovery/{conv_id}/complete", headers=API_KEY
)
assert complete.status_code == 200
# The answers endpoint now reports a completion timestamp.
answers = await app_client.get(
f"/discovery/{conv_id}/answers", headers=API_KEY
)
assert answers.json()["completed_at"] is not None