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Full end-to-end smoke test for the RICS Report Genius AI system.
Flow:
1. Notes-expander unit check (rule-based abbreviations)
2. Health check
3. Ingest a sample DOCX via /test/ingest
4. Create a report linked to that document
5. Generate section D (About the property) with messy notes, default ai_level=3 (Balanced)
6. Poll until complete, print result + style profile
7. Re-generate section D at ai_level=1 (RAG Only) β should still succeed
8. Proofread section D
9. Enhance section D
10. Style-profile roundtrip: all 7 fields must be present
11. /extract-notes endpoint: upload the sample DOCX, verify lines returned
12. /upload/batch endpoint: upload the sample DOCX as a batch, verify doc row
13. /documents/batch-status endpoint: poll the batch-uploaded doc
14. /documents/tenant-chunk-summary endpoint: returns chunk count
15. Oversized notes-file rejection: expect 413 from /extract-notes
"""
import io
import sys
import time
from pathlib import Path
import requests
from app.generator.notes_expander import expand_notes
BASE = "http://localhost:8000"
TENANT = "e2e-smoke-test"
HEADERS = {"X-Tenant-ID": TENANT}
JSON_HEADERS = {**HEADERS, "Content-Type": "application/json"}
# Resolve relative to this script so the test runs on any OS and from any directory.
SAMPLE_FILE = Path(__file__).parent / "sample_survey_doc.docx"
# βββ helpers ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def ok(msg: str) -> None:
print(f" β {msg}")
def fail(msg: str) -> None:
print(f" β {msg}")
sys.exit(1)
def poll_report(report_id: str, timeout: int = 60) -> str:
deadline = time.time() + timeout
while time.time() < deadline:
r = requests.get(f"{BASE}/reports/{report_id}/status", headers=HEADERS)
r.raise_for_status()
status = r.json()["status"]
print(f" status={status}")
if status == "complete":
return "complete"
if status == "failed":
fail(f"Report {report_id} failed")
time.sleep(3)
fail(f"Timed out waiting for report {report_id}")
return "timeout"
# βββ Step 1: Notes expander unit check ββββββββββββββββββββββββββββββββββββββββ
def test_notes_expander() -> None:
print("\n=== Step 1: Notes expander (rule-based) ===")
cases = [
("semi det nw3 1965ish 95sqm", "semi-detached"),
("roof bad needs work", "in poor condition"),
("mains e mains g connected", "electricity"),
("dg windows ok", "double-glazed"),
("w/o insulation", "without"),
("w/ cavity wall insulation", "with"),
("v bad boiler", "very poor condition"),
]
for note, expected_fragment in cases:
expanded = expand_notes([note])[0]
if expected_fragment.lower() in expanded.lower():
ok(f"{note!r} β ...{expected_fragment}... β (full: {expanded!r})")
else:
fail(f"{note!r} β expected {expected_fragment!r} but got {expanded!r}")
# βββ Step 2: Health check βββββββββββββββββββββββββββββββββββββββββββββββββββββ
def test_health() -> None:
print("\n=== Step 2: Health check ===")
r = requests.get(f"{BASE}/health")
r.raise_for_status()
assert r.json()["status"] == "ok"
ok("GET /health β ok")
# βββ Step 3: Ingest sample doc ββββββββββββββββββββββββββββββββββββββββββββββββ
def ingest_document() -> str:
print("\n=== Step 3: Test ingest ===")
payload = {"file_path": str(SAMPLE_FILE), "tenant_id": TENANT}
r = requests.post(f"{BASE}/test/ingest", json=payload, headers=JSON_HEADERS)
if r.status_code != 200:
fail(f"POST /test/ingest failed {r.status_code}: {r.text}")
doc_id = r.json()["document_id"]
ok(f"Ingested document_id={doc_id}")
return doc_id
# βββ Step 4: Create report ββββββββββββββββββββββββββββββββββββββββββββββββββββ
def create_report(doc_id: str) -> str:
print("\n=== Step 4: Create report ===")
r = requests.post(f"{BASE}/reports", headers=HEADERS, params={"document_id": doc_id})
if r.status_code != 201:
fail(f"POST /reports failed {r.status_code}: {r.text}")
report_id = r.json()["report_id"]
ok(f"Created report_id={report_id}")
return report_id
# βββ Step 5: Generate section (messy notes, ai_level=3 Balanced) ββββββββββββββ
# Uses section D (About the property) β best match for general property description notes.
_TEST_SECTION = "D"
_TEST_BULLETS_D = [
"semi det nw3 1965ish 95sqm",
"3 bed 2 storey Victorian terrace",
"faces NW front elevation",
"solid brick walls, no cavity",
]
_TEST_BULLETS_E2 = [
"roof bad needs work",
"hip roof slate tiles, several slipped",
"flat felt extension roof cracked",
]
def generate_section(report_id: str, ai_level: int = 3) -> dict:
print(f"\n=== Step 5: Generate section {_TEST_SECTION} (messy notes, ai_level={ai_level}) ===")
payload = {
"template_id": _TEST_SECTION,
"bullets": _TEST_BULLETS_D,
"mode": "generate",
"ai_level": ai_level,
}
r = requests.post(
f"{BASE}/reports/{report_id}/generate",
headers=JSON_HEADERS,
json=payload,
)
if r.status_code != 200:
fail(f"POST generate failed {r.status_code}: {r.text}")
ok(f"Generation queued (ai_level={ai_level}): {r.json()['status']}")
print(" Pollingβ¦")
poll_report(report_id)
r2 = requests.get(f"{BASE}/reports/{report_id}/sections", headers=HEADERS)
r2.raise_for_status()
sections = r2.json()["sections"]
if _TEST_SECTION not in sections:
fail(f"Section {_TEST_SECTION} not found in response")
section = sections[_TEST_SECTION]
text = section["text"]
mode = section.get("mode", "?")
sp = section.get("style_profile") or {}
ok(f"Section {_TEST_SECTION} generated β mode={mode} ai_level={ai_level} chars={len(text)}")
ok(f"Style profile β tone={sp.get('tone','?')} summary={sp.get('writing_style_summary','?')[:60]}β¦")
print(f"\n ββ GENERATED TEXT (first 400 chars) ββ")
print(f" {text[:400]}")
return sections
# βββ Step 7: Generate at ai_level=1 (RAG Only) ββββββββββββββββββββββββββββββββ
def generate_rag_only(report_id: str) -> None:
print(f"\n=== Step 7: Re-generate section {_TEST_SECTION} at ai_level=1 (RAG Only) ===")
payload = {
"template_id": _TEST_SECTION,
"bullets": _TEST_BULLETS_D[:2],
"mode": "generate",
"ai_level": 1,
"force_regenerate": True,
}
r = requests.post(
f"{BASE}/reports/{report_id}/generate",
headers=JSON_HEADERS,
json=payload,
)
if r.status_code != 200:
fail(f"POST generate (RAG Only) failed {r.status_code}: {r.text}")
ok("RAG-only generation queued")
print(" Pollingβ¦")
poll_report(report_id)
r2 = requests.get(f"{BASE}/reports/{report_id}/sections", headers=HEADERS)
r2.raise_for_status()
section = r2.json()["sections"].get(_TEST_SECTION, {})
ok(f"RAG-only section {_TEST_SECTION} returned chars={len(section.get('text',''))}")
# βββ Step 8: Proofread mode βββββββββββββββββββββββββββββββββββββββββββββββββββ
def proofread_section(report_id: str) -> None:
print(f"\n=== Step 8: Proofread section {_TEST_SECTION} ===")
payload = {
"template_id": _TEST_SECTION,
"bullets": _TEST_BULLETS_D[:2],
"mode": "proofread",
"ai_level": 3,
}
r = requests.post(
f"{BASE}/reports/{report_id}/generate",
headers=JSON_HEADERS,
json=payload,
)
if r.status_code != 200:
fail(f"POST proofread failed {r.status_code}: {r.text}")
ok("Proofread queued")
print(" Pollingβ¦")
poll_report(report_id)
r2 = requests.get(f"{BASE}/reports/{report_id}/sections", headers=HEADERS)
r2.raise_for_status()
section = r2.json()["sections"].get(_TEST_SECTION, {})
text = section.get("text", "")
mode = section.get("mode", "?")
ok(f"Section {_TEST_SECTION} after proofread β mode={mode} chars={len(text)}")
print(f"\n ββ PROOFREAD TEXT (first 400 chars) ββ")
print(f" {text[:400]}")
# βββ Step 9: Enhance mode βββββββββββββββββββββββββββββββββββββββββββββββββββββ
def enhance_section(report_id: str) -> None:
print(f"\n=== Step 9: Enhance section {_TEST_SECTION} ===")
payload = {
"template_id": _TEST_SECTION,
"bullets": _TEST_BULLETS_D[:2],
"mode": "enhance",
"ai_level": 4,
}
r = requests.post(
f"{BASE}/reports/{report_id}/generate",
headers=JSON_HEADERS,
json=payload,
)
if r.status_code != 200:
fail(f"POST enhance failed {r.status_code}: {r.text}")
ok("Enhance queued (ai_level=4)")
print(" Pollingβ¦")
poll_report(report_id)
r2 = requests.get(f"{BASE}/reports/{report_id}/sections", headers=HEADERS)
r2.raise_for_status()
section = r2.json()["sections"].get(_TEST_SECTION, {})
text = section.get("text", "")
mode = section.get("mode", "?")
ok(f"Section {_TEST_SECTION} after enhance β mode={mode} chars={len(text)}")
print(f"\n ββ ENHANCED TEXT (first 400 chars) ββ")
print(f" {text[:400]}")
# βββ Step 10: Style profile roundtrip βββββββββββββββββββββββββββββββββββββββββ
def test_style_profile_roundtrip(report_id: str) -> None:
print("\n=== Step 10: Style profile roundtrip ===")
r = requests.get(f"{BASE}/reports/{report_id}/sections", headers=HEADERS)
r.raise_for_status()
section = r.json()["sections"].get(_TEST_SECTION, {})
sp = section.get("style_profile") or {}
required_keys = [
"tone", "formality_level", "avg_sentence_complexity",
"vocabulary_level", "common_phrases", "structural_patterns",
"writing_style_summary",
]
missing = [k for k in required_keys if k not in sp]
if missing:
fail(f"style_profile missing keys: {missing}")
ok(f"All 7 style_profile fields present: {list(sp.keys())}")
# βββ Step 11: /extract-notes β valid DOCX βββββββββββββββββββββββββββββββββββββ
def test_extract_notes_docx() -> None:
print("\n=== Step 11: POST /extract-notes β DOCX upload ===")
with open(SAMPLE_FILE, "rb") as fh:
r = requests.post(
f"{BASE}/extract-notes",
headers=HEADERS,
files={"file": ("sample_survey_doc.docx", fh, "application/vnd.openxmlformats-officedocument.wordprocessingml.document")},
)
if r.status_code != 200:
fail(f"/extract-notes failed {r.status_code}: {r.text}")
data = r.json()
lines = data.get("lines", [])
line_count = data.get("line_count", 0)
if line_count == 0 or not lines:
fail(f"/extract-notes returned no lines: {data}")
ok(f"/extract-notes extracted {line_count} line(s) from DOCX")
print(f" First 3 lines: {lines[:3]}")
# βββ Step 12: /extract-notes β oversized file rejected (413) βββββββββββββββββ
def test_extract_notes_oversized() -> None:
print("\n=== Step 12: POST /extract-notes β oversized file β 413 ===")
# Create an in-memory fake .txt that is exactly 10 MB + 1 byte
big_data = b"x" * (10 * 1024 * 1024 + 1)
r = requests.post(
f"{BASE}/extract-notes",
headers=HEADERS,
files={"file": ("big.txt", io.BytesIO(big_data), "text/plain")},
)
if r.status_code != 413:
fail(f"Expected 413 for oversized file but got {r.status_code}: {r.text}")
ok("Oversized notes file correctly rejected with 413")
# βββ Step 13: /upload/batch β batch upload DOCX βββββββββββββββββββββββββββββββ
def test_batch_upload() -> str:
print("\n=== Step 13: POST /upload/batch β batch upload ===")
with open(SAMPLE_FILE, "rb") as fh:
r = requests.post(
f"{BASE}/upload/batch",
headers=HEADERS,
data={"tenant_id": TENANT},
files=[("files", ("sample_survey_doc.docx", fh, "application/vnd.openxmlformats-officedocument.wordprocessingml.document"))],
)
if r.status_code != 202:
fail(f"POST /upload/batch failed {r.status_code}: {r.text}")
data = r.json()
if data.get("accepted", 0) < 1:
fail(f"Batch upload accepted 0 files: {data}")
doc_id = data["items"][0]["document_id"]
ok(f"Batch upload accepted={data['accepted']} rejected={data['rejected']} doc_id={doc_id}")
return doc_id
# βββ Step 14: /documents/batch-status βββββββββββββββββββββββββββββββββββββββββ
def test_batch_status(doc_id: str) -> None:
print("\n=== Step 14: POST /documents/batch-status ===")
r = requests.post(
f"{BASE}/documents/batch-status",
headers=JSON_HEADERS,
json={"document_ids": [doc_id, "non-existent-id-000"]},
)
if r.status_code != 200:
fail(f"/documents/batch-status failed {r.status_code}: {r.text}")
data = r.json()
items = data.get("items", [])
found = [i for i in items if i["document_id"] == doc_id]
not_found = [i for i in items if i["status"] == "not_found"]
if not found:
fail(f"batch-status did not return entry for doc_id={doc_id}")
if not not_found:
fail("batch-status did not return 'not_found' for non-existent ID")
ok(f"batch-status: doc_id status={found[0]['status']} non-existentβnot_found β")
ok(f"Aggregates: pending={data['pending']} processing={data['processing']} complete={data['complete']} failed={data['failed']}")
# βββ Step 15: /documents/tenant-chunk-summary ββββββββββββββββββββββββββββββββ
def test_chunk_summary() -> None:
print("\n=== Step 15: GET /documents/tenant-chunk-summary ===")
r = requests.get(f"{BASE}/documents/tenant-chunk-summary", headers=HEADERS)
if r.status_code != 200:
fail(f"/documents/tenant-chunk-summary failed {r.status_code}: {r.text}")
data = r.json()
if "indexed_chunk_count" not in data:
fail(f"Missing 'indexed_chunk_count' in response: {data}")
ok(f"tenant-chunk-summary: indexed_chunk_count={data['indexed_chunk_count']}")
# βββ main βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def main() -> None:
print("=" * 65)
print(" RICS Report Genius AI β Full End-to-End Smoke Test")
print("=" * 65)
test_notes_expander()
test_health()
doc_id = ingest_document()
report_id = create_report(doc_id)
generate_section(report_id, ai_level=3)
generate_rag_only(report_id)
proofread_section(report_id)
enhance_section(report_id)
test_style_profile_roundtrip(report_id)
test_extract_notes_docx()
test_extract_notes_oversized()
batch_doc_id = test_batch_upload()
test_batch_status(batch_doc_id)
test_chunk_summary()
print("\n" + "=" * 65)
print(" ALL END-TO-END CHECKS PASSED β")
print("=" * 65)
if __name__ == "__main__":
main()
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