AI desktop path: plain-HTML Review and Cost tabs over the Qt bridge, gate in Python

ai_sections.html pastes into the no-AI dashboard.html; ai_bridge.py adds one
ai_request slot that hands every AI contract request (incl. GET /roi) to the
review backend's dispatch(). Desktop page check reruns the web review and cost
cases plus a tampered-page gate case. Eval fixture e-pyqt-ai added.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/fixtures/e-pyqt-ai/README.md

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+# Invoice intake bot
+
+A desktop RPA bot. It reads each scanned invoice in `inbox/` with an LLM
+(`extractor.py`) and queues the fields for a person to review.
+The operator window will be a PyQt6 app.
+
+Run the bot on its own:
+
+```
+python -m bot
+```

tests/fixtures/e-pyqt-ai/bot.py

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+"""Invoice intake bot: picks up scanned invoices and extracts their fields with an LLM.
+Start it with:  python -m bot"""
+import time
+from pathlib import Path
+
+INBOX = Path(__file__).with_name("inbox")
+
+
+def say(line):
+    print(line, flush=True)
+    time.sleep(0.2)
+
+
+def main():
+    say("[step 1] Initializing")
+    docs = sorted(INBOX.glob("*.pdf"))
+    say(f"[inbox] {len(docs)} invoices waiting")
+    say("[step 2] Extracting fields")
+    for i, doc in enumerate(docs, 1):
+        try:
+            from extractor import extract_invoice  # the LLM call
+            rows = extract_invoice(doc.read_bytes(), "application/pdf")
+            say(f"[extract] {doc.name}: {len(rows)} fields ({i}/{len(docs)})")
+        except Exception as e:  # one bad document must not stop the batch
+            say(f"ERROR: extraction failed for {doc.name}: {type(e).__name__}")
+    say("[step 3] Queueing for review")
+    say(f"[all done] {len(docs)} invoices processed")
+
+
+if __name__ == "__main__":
+    main()

tests/fixtures/e-pyqt-ai/extractor.py

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+"""The LLM extraction call: one scanned invoice in, its fields out, each with word scores."""
+import json
+
+from google import genai
+from google.genai import types
+
+MODEL = "gemini-2.5-flash"
+FIELDS = {  # field name -> mandatory
+    "Invoice number": True,
+    "Invoice date": True,
+    "Vendor": True,
+    "PO number": False,
+    "Due date": True,
+    "Total": True,
+}
+PROMPT = (
+    "Read this invoice. Return JSON: a list of {field, value, word_scores}, one per field in "
+    + ", ".join(FIELDS)
+    + ". word_scores is your 0-1 legibility score for each word of the value. Use an empty "
+    "value and no scores when a field isn't on the page."
+)
+
+
+def extract_invoice(document: bytes, mime_type: str) -> list[dict]:
+    client = genai.Client()  # credentials come from the environment
+    response = client.models.generate_content(
+        model=MODEL,
+        contents=[types.Part.from_bytes(data=document, mime_type=mime_type), PROMPT],
+        config=types.GenerateContentConfig(response_mime_type="application/json"),
+    )
+    rows = json.loads(response.text)
+    for row in rows:
+        row["mandatory"] = FIELDS.get(row["field"], False)
+    return rows

tests/fixtures/e-pyqt-ai/inbox/invoice-2201.pdf

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+%PDF-1.4
+% sample invoice placeholder

tests/fixtures/e-pyqt-ai/inbox/invoice-2202.pdf

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+%PDF-1.4
+% sample invoice placeholder

tests/fixtures/e-pyqt-ai/requirements.txt

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+PyQt6
+PyQt6-WebEngine
+google-genai