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https://github.com/computerim/impactflow-discovery.git
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866bd60225
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
159 lines
5.2 KiB
Python
159 lines
5.2 KiB
Python
"""Tests for the discovery CSV/reprocess endpoints.
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Run under the X-API-Key admin identity so they don't depend on the Google
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OAuth flow. The DiscoveryExtractor is replaced with a fake so no network call
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or API key is needed. QUESTIONS_DIR / QUESTIONS_MASTER_CSV are pointed at
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tmp_path so the suite never writes into the repo's data dir.
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"""
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import os
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from app.services import answer_store
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API_KEY = {"X-API-Key": "test-api-key"}
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class FakeExtractor:
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"""Stand-in for DiscoveryExtractor: returns a fixed well-formed profile."""
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def __init__(self, api_key=None, model=None):
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pass
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async def extract(self, responses):
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return {
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"triad": "gut",
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"probable_type": 8,
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"wing": 9,
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"instinctual_variant": "sp",
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"instinctual_stack": "sp/so/sx",
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"love_summary": "love",
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"strength_summary": "strength",
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"mission_summary": "mission",
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"vocation_summary": "vocation",
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"overlap_narrative": "narrative",
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"short_term_goals": "short",
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"long_term_goals": "long",
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"confidence": {
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"triad": "high",
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"type": "high",
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"variant": "medium",
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"ikigai": "high",
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},
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"extraction_notes": "ok",
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}
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def _patch(monkeypatch, tmp_path):
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monkeypatch.setenv("QUESTIONS_DIR", str(tmp_path / "questions"))
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monkeypatch.setenv("QUESTIONS_MASTER_CSV", str(tmp_path / "master.csv"))
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monkeypatch.setattr(
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"app.routers.discovery.DiscoveryExtractor", FakeExtractor
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)
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async def _start_and_respond(app_client):
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start = await app_client.post("/discovery/start", headers=API_KEY)
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assert start.status_code == 200
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conv_id = start.json()["conversation_id"]
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r = await app_client.put(
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f"/discovery/{conv_id}/respond",
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headers=API_KEY,
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json={
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"prompt_alive": "I felt alive building things",
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"prompt_friction": "unfairness bothers me",
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"prompt_goals_short": "ship the app",
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},
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)
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assert r.status_code == 200
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return conv_id
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async def test_respond_writes_csv(app_client, monkeypatch, tmp_path):
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_patch(monkeypatch, tmp_path)
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conv_id = await _start_and_respond(app_client)
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assert os.path.exists(answer_store.conversation_csv_path(conv_id))
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answers = answer_store.read_conversation_answers(conv_id)
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assert answers["alive"] == "I felt alive building things"
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assert os.path.exists(str(tmp_path / "master.csv"))
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async def test_get_answers(app_client, monkeypatch, tmp_path):
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_patch(monkeypatch, tmp_path)
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conv_id = await _start_and_respond(app_client)
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r = await app_client.get(f"/discovery/{conv_id}/answers", headers=API_KEY)
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assert r.status_code == 200
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body = r.json()
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assert body["conversation_id"] == conv_id
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assert body["completed_at"] is None
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by_key = {a["prompt_key"]: a["answer"] for a in body["answers"]}
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assert by_key["friction"] == "unfairness bothers me"
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assert len(body["answers"]) == 7
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async def test_download_answers_csv(app_client, monkeypatch, tmp_path):
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_patch(monkeypatch, tmp_path)
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conv_id = await _start_and_respond(app_client)
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r = await app_client.get(
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f"/discovery/{conv_id}/answers.csv", headers=API_KEY
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)
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assert r.status_code == 200
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assert r.headers["content-type"].startswith("text/csv")
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assert "attachment" in r.headers["content-disposition"]
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assert "ship the app" in r.text
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async def test_reprocess_creates_profile(app_client, monkeypatch, tmp_path):
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_patch(monkeypatch, tmp_path)
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conv_id = await _start_and_respond(app_client)
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r = await app_client.post(
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f"/discovery/{conv_id}/reprocess", headers=API_KEY
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)
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assert r.status_code == 200
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body = r.json()
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assert body["conversation_id"] == conv_id
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assert body["triad"] == "gut"
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assert body["probable_type"] == 8
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# A profile now exists for the user.
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prof = await app_client.get("/discovery/profile/me", headers=API_KEY)
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assert prof.status_code == 200
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async def test_reprocess_locked_returns_409(app_client, monkeypatch, tmp_path):
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_patch(monkeypatch, tmp_path)
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conv_id = await _start_and_respond(app_client)
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# Complete to create a profile, then lock it via confirm.
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complete = await app_client.post(
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f"/discovery/{conv_id}/complete", headers=API_KEY
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)
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assert complete.status_code == 200
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confirm = await app_client.put(
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"/discovery/profile/me/confirm", headers=API_KEY
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)
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assert confirm.status_code == 200
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r = await app_client.post(
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f"/discovery/{conv_id}/reprocess", headers=API_KEY
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)
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assert r.status_code == 409
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async def test_complete_writes_completed_csv(app_client, monkeypatch, tmp_path):
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_patch(monkeypatch, tmp_path)
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conv_id = await _start_and_respond(app_client)
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complete = await app_client.post(
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f"/discovery/{conv_id}/complete", headers=API_KEY
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)
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assert complete.status_code == 200
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# The answers endpoint now reports a completion timestamp.
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answers = await app_client.get(
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f"/discovery/{conv_id}/answers", headers=API_KEY
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)
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assert answers.json()["completed_at"] is not None
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