feat(tasks): migrate trust_photo_analysis to cf-orch image_assessment task endpoint (#43)

- _assess_via_orch(): uses CFOrchClient.task_allocate('snipe', 'image_assessment')
  with multimodal image_url payload; falls back to local LLMRouter on TaskNotFound
- _assess_via_local_llm(): lazy LLMRouter import, unchanged local path
- CF_ORCH_URL env var selects path at runtime; local users unaffected
- Added circuitforge-orch>=0.1.0 to main dependencies
- 5 new runner tests covering orch happy path, task tag, image_url payload format,
  TaskNotFound fallback, and non-JSON response handling (13 tests total, 244 suite)
This commit is contained in:
pyr0ball 2026-05-13 15:43:18 -07:00
parent 1bf95bba2a
commit 263c8522ee
3 changed files with 258 additions and 48 deletions

View file

@ -7,28 +7,30 @@ Current task types:
trust_photo_analysis download primary photo, run vision LLM, write
result to trust_scores.photo_analysis_json (Paid tier).
Prompt note: The vision prompt is a functional first pass. Tune against real
eBay listings before GA specifically stock-photo vs genuine-product distinction
and the damage vocabulary.
Image assessment routing:
Cloud (CF_ORCH_URL set): allocates via cf-orch task endpoint
product=snipe, task=image_assessment.
Local (no CF_ORCH_URL) or TaskNotFound fallback: uses LLMRouter
with a vision-capable local backend (moondream2, llava, etc.).
"""
from __future__ import annotations
import base64
import json
import logging
import os
from pathlib import Path
import httpx
import requests
from circuitforge_core.db import get_connection
from circuitforge_core.llm import LLMRouter
log = logging.getLogger(__name__)
LLM_TASK_TYPES: frozenset[str] = frozenset({"trust_photo_analysis"})
VRAM_BUDGETS: dict[str, float] = {
# moondream2 / vision-capable LLM — single image, short response
"trust_photo_analysis": 2.0,
"trust_photo_analysis": 6000, # Q5_K_M Qwen2-VL via cf-orch; LLMRouter fallback uses 2.0 GB
}
_VISION_SYSTEM_PROMPT = (
@ -51,8 +53,7 @@ def insert_task(
) -> tuple[int, bool]:
"""Insert a background task if no identical task is already in-flight.
Uses get_connection() so WAL mode and timeout=30 apply same as all other
Snipe DB access. Returns (task_id, is_new).
Returns (task_id, is_new).
"""
conn = get_connection(db_path)
conn.row_factory = __import__("sqlite3").Row
@ -120,32 +121,26 @@ def _run_trust_photo_analysis(
p = json.loads(params or "{}")
photo_url = p.get("photo_url", "")
listing_title = p.get("listing_title", "")
# user_db: per-user DB in cloud mode; same as db_path in local mode.
result_db = Path(p.get("user_db", str(db_path)))
if not photo_url:
raise ValueError("trust_photo_analysis: 'photo_url' is required in params")
# Download and base64-encode the photo
resp = requests.get(photo_url, timeout=10)
resp.raise_for_status()
image_b64 = base64.b64encode(resp.content).decode()
image_data_url = f"data:image/jpeg;base64,{image_b64}"
# Build user prompt with optional title context
user_prompt = "Evaluate this eBay listing photo."
user_prompt = "Assess this listing image."
if listing_title:
user_prompt = f"Evaluate this eBay listing photo for: {listing_title}"
user_prompt = f"Assess this eBay listing image: {listing_title}"
# Call LLMRouter with vision capability
router = LLMRouter()
raw = router.complete(
user_prompt,
system=_VISION_SYSTEM_PROMPT,
images=[image_b64],
max_tokens=128,
)
cforch_url = os.getenv("CF_ORCH_URL")
if cforch_url:
raw = _assess_via_orch(cforch_url, image_data_url, user_prompt)
else:
raw = _assess_via_local_llm(image_b64, user_prompt)
# Parse — be lenient: strip markdown fences if present
try:
cleaned = raw.strip().removeprefix("```json").removeprefix("```").removesuffix("```").strip()
analysis = json.loads(cleaned)
@ -168,3 +163,54 @@ def _run_trust_photo_analysis(
analysis.get("visible_damage"),
analysis.get("confidence"),
)
def _assess_via_orch(cforch_url: str, image_data_url: str, user_prompt: str) -> str:
"""Run photo assessment via cf-orch task endpoint (cloud path)."""
from circuitforge_orch.client import CFOrchClient, TaskNotFound
client = CFOrchClient(cforch_url)
try:
with client.task_allocate("snipe", "image_assessment") as alloc:
resp = httpx.post(
f"{alloc.url}/v1/chat/completions",
json={
"model": alloc.model or "__auto__",
"messages": [
{
"role": "system",
"content": _VISION_SYSTEM_PROMPT,
},
{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": image_data_url}},
{"type": "text", "text": user_prompt},
],
},
],
"max_tokens": 128,
},
timeout=60.0,
)
resp.raise_for_status()
return resp.json()["choices"][0]["message"]["content"]
except TaskNotFound:
log.warning(
"snipe.image_assessment not registered in cf-orch — falling back to local LLM"
)
image_b64 = image_data_url.split(",", 1)[1]
return _assess_via_local_llm(image_b64, user_prompt)
def _assess_via_local_llm(image_b64: str, user_prompt: str) -> str:
"""Run photo assessment via local LLMRouter (local/self-hosted path)."""
from app.llm.router import LLMRouter
router = LLMRouter()
return router.complete(
user_prompt,
system=_VISION_SYSTEM_PROMPT,
images=[image_b64],
max_tokens=128,
)

View file

@ -24,6 +24,7 @@ dependencies = [
"cryptography>=42.0",
"PyJWT>=2.8",
"httpx>=0.27",
"circuitforge-orch>=0.1.0",
]
[project.optional-dependencies]

View file

@ -4,7 +4,7 @@ from __future__ import annotations
import json
import sqlite3
from pathlib import Path
from unittest.mock import patch
from unittest.mock import MagicMock, patch, call
import pytest
@ -47,6 +47,19 @@ def tmp_db(tmp_path: Path) -> Path:
return db
_VISION_JSON = json.dumps({
"is_stock_photo": False,
"visible_damage": False,
"authenticity_signal": "genuine_product_photo",
"confidence": "high",
})
_PARAMS = json.dumps({
"photo_url": "https://example.com/photo.jpg",
"listing_title": "Used iPhone 13",
})
def test_llm_task_types_defined():
assert "trust_photo_analysis" in LLM_TASK_TYPES
@ -75,29 +88,17 @@ def test_insert_task_dedup(tmp_db: Path):
assert new2 is False
def test_run_task_photo_analysis_success(tmp_db: Path):
"""Vision analysis result is written to trust_scores.photo_analysis_json."""
params = json.dumps({
"listing_id": 1,
"photo_url": "https://example.com/photo.jpg",
"listing_title": "Used iPhone 13",
})
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=params)
# ── Local LLMRouter path ──────────────────────────────────────────────────────
vision_result = {
"is_stock_photo": False,
"visible_damage": False,
"authenticity_signal": "genuine_product_photo",
"confidence": "high",
}
def test_run_task_photo_analysis_local_success(tmp_db: Path):
"""Local path: vision result is written to trust_scores.photo_analysis_json."""
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
with patch("app.tasks.runner.requests") as mock_req, \
patch("app.tasks.runner.LLMRouter") as MockRouter:
patch("app.tasks.runner._assess_via_local_llm", return_value=_VISION_JSON):
mock_req.get.return_value.content = b"fake_image_bytes"
mock_req.get.return_value.raise_for_status = lambda: None
instance = MockRouter.return_value
instance.complete.return_value = json.dumps(vision_result)
run_task(tmp_db, task_id, "trust_photo_analysis", 1, params)
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
conn = sqlite3.connect(tmp_db)
score_row = conn.execute(
@ -110,20 +111,16 @@ def test_run_task_photo_analysis_success(tmp_db: Path):
assert task_row[0] == "completed"
parsed = json.loads(score_row[0])
assert parsed["is_stock_photo"] is False
assert parsed["confidence"] == "high"
def test_run_task_photo_fetch_failure_marks_failed(tmp_db: Path):
"""If photo download fails, task is marked failed without crashing."""
params = json.dumps({
"listing_id": 1,
"photo_url": "https://example.com/bad.jpg",
"listing_title": "Laptop",
})
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=params)
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
with patch("app.tasks.runner.requests") as mock_req:
mock_req.get.side_effect = ConnectionError("fetch failed")
run_task(tmp_db, task_id, "trust_photo_analysis", 1, params)
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
conn = sqlite3.connect(tmp_db)
row = conn.execute(
@ -156,3 +153,169 @@ def test_run_task_unknown_type_marks_failed(tmp_db: Path):
).fetchone()
conn.close()
assert row[0] == "failed"
# ── cf-orch path ──────────────────────────────────────────────────────────────
def _make_orch_client_mock(vision_json: str) -> MagicMock:
"""Build a CFOrchClient mock whose task_allocate context manager returns an Allocation."""
alloc = MagicMock()
alloc.url = "http://cf-vlm.local:8000"
alloc.model = "bartowski--qwen2-vl-7b-instruct-gguf"
cm = MagicMock()
cm.__enter__ = MagicMock(return_value=alloc)
cm.__exit__ = MagicMock(return_value=False)
client = MagicMock()
client.task_allocate.return_value = cm
return client
def test_run_task_photo_analysis_orch_success(tmp_db: Path):
"""Cloud path: CFOrchClient.task_allocate is used when CF_ORCH_URL is set."""
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
chat_resp = MagicMock()
chat_resp.json.return_value = {"choices": [{"message": {"content": _VISION_JSON}}]}
chat_resp.raise_for_status = MagicMock()
with patch("app.tasks.runner.requests") as mock_req, \
patch.dict("os.environ", {"CF_ORCH_URL": "http://cf-orch.local:8700"}), \
patch("app.tasks.runner.httpx") as mock_httpx, \
patch("circuitforge_orch.client.CFOrchClient") as MockClient:
mock_req.get.return_value.content = b"fake_image_bytes"
mock_req.get.return_value.raise_for_status = lambda: None
mock_httpx.post.return_value = chat_resp
client_instance = _make_orch_client_mock(_VISION_JSON)
MockClient.return_value = client_instance
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
conn = sqlite3.connect(tmp_db)
score_row = conn.execute(
"SELECT photo_analysis_json FROM trust_scores WHERE listing_id=1"
).fetchone()
task_row = conn.execute(
"SELECT status FROM background_tasks WHERE id=?", (task_id,)
).fetchone()
conn.close()
assert task_row[0] == "completed"
parsed = json.loads(score_row[0])
assert parsed["authenticity_signal"] == "genuine_product_photo"
def test_run_task_photo_analysis_orch_uses_image_assessment_task(tmp_db: Path):
"""task_allocate must be called with product='snipe', task='image_assessment'."""
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
chat_resp = MagicMock()
chat_resp.json.return_value = {"choices": [{"message": {"content": _VISION_JSON}}]}
chat_resp.raise_for_status = MagicMock()
with patch("app.tasks.runner.requests") as mock_req, \
patch.dict("os.environ", {"CF_ORCH_URL": "http://cf-orch.local:8700"}), \
patch("app.tasks.runner.httpx") as mock_httpx, \
patch("circuitforge_orch.client.CFOrchClient") as MockClient:
mock_req.get.return_value.content = b"fake_image_bytes"
mock_req.get.return_value.raise_for_status = lambda: None
mock_httpx.post.return_value = chat_resp
client_instance = _make_orch_client_mock(_VISION_JSON)
MockClient.return_value = client_instance
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
client_instance.task_allocate.assert_called_once_with("snipe", "image_assessment")
def test_run_task_photo_analysis_orch_sends_image_url_content(tmp_db: Path):
"""Vision payload must include image_url content block with data URI."""
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
captured_body: dict = {}
def capture_post(url, **kwargs):
nonlocal captured_body
if "/v1/chat/completions" in url:
captured_body = kwargs.get("json", {})
resp = MagicMock()
resp.json.return_value = {"choices": [{"message": {"content": _VISION_JSON}}]}
resp.raise_for_status = MagicMock()
return resp
with patch("app.tasks.runner.requests") as mock_req, \
patch.dict("os.environ", {"CF_ORCH_URL": "http://cf-orch.local:8700"}), \
patch("app.tasks.runner.httpx") as mock_httpx, \
patch("circuitforge_orch.client.CFOrchClient") as MockClient:
mock_req.get.return_value.content = b"fake_image_bytes"
mock_req.get.return_value.raise_for_status = lambda: None
mock_httpx.post.side_effect = capture_post
client_instance = _make_orch_client_mock(_VISION_JSON)
MockClient.return_value = client_instance
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
user_content = captured_body["messages"][1]["content"]
image_blocks = [b for b in user_content if b.get("type") == "image_url"]
assert image_blocks, "No image_url content block found in vision payload"
url = image_blocks[0]["image_url"]["url"]
assert url.startswith("data:image/jpeg;base64,"), f"Unexpected image URL format: {url[:40]}"
def test_run_task_photo_analysis_orch_task_not_found_falls_back(tmp_db: Path):
"""TaskNotFound from cf-orch → graceful fallback to local LLMRouter."""
from circuitforge_orch.client import TaskNotFound
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
cm = MagicMock()
cm.__enter__ = MagicMock(side_effect=TaskNotFound("snipe", "image_assessment"))
cm.__exit__ = MagicMock(return_value=False)
client_instance = MagicMock()
client_instance.task_allocate.return_value = cm
with patch("app.tasks.runner.requests") as mock_req, \
patch.dict("os.environ", {"CF_ORCH_URL": "http://cf-orch.local:8700"}), \
patch("circuitforge_orch.client.CFOrchClient", return_value=client_instance), \
patch("app.tasks.runner._assess_via_local_llm", return_value=_VISION_JSON) as mock_local:
mock_req.get.return_value.content = b"fake_image_bytes"
mock_req.get.return_value.raise_for_status = lambda: None
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
mock_local.assert_called_once()
conn = sqlite3.connect(tmp_db)
task_row = conn.execute(
"SELECT status FROM background_tasks WHERE id=?", (task_id,)
).fetchone()
conn.close()
assert task_row[0] == "completed"
def test_run_task_photo_analysis_non_json_response_writes_raw(tmp_db: Path):
"""Non-JSON LLM response is stored with parse_error flag rather than crashing."""
task_id, _ = insert_task(tmp_db, "trust_photo_analysis", job_id=1, params=_PARAMS)
with patch("app.tasks.runner.requests") as mock_req, \
patch("app.tasks.runner._assess_via_local_llm", return_value="not valid json at all"):
mock_req.get.return_value.content = b"fake_image_bytes"
mock_req.get.return_value.raise_for_status = lambda: None
run_task(tmp_db, task_id, "trust_photo_analysis", 1, _PARAMS)
conn = sqlite3.connect(tmp_db)
score_row = conn.execute(
"SELECT photo_analysis_json FROM trust_scores WHERE listing_id=1"
).fetchone()
conn.close()
parsed = json.loads(score_row[0])
assert parsed.get("parse_error") is True
assert "raw_response" in parsed