fix(ocr+safety): stop document-content hallucinations from empty OCR

Three independent bugs combined to make Shira fabricate the content of
case-46-Friedman's appeal in production (CTS case rewritten as a knee
injury, wrong dates, wrong court file number, wrong %-of-disability —
written into save_memory/Task/Meeting on prod).

* api/services/ocr.py — ocr_docx_images now reads word/document.xml first
  (text content), then OCRs embedded images. Previously it only OCR'd the
  word/media/* images, so a text-heavy DOCX with one signature image
  returned only "[signature]" to the LLM. Verified against the same
  Friedman appeal: 16633 chars / 80 paragraphs / 0 XML noise.

* mcp_server/tools/document_tools.py — _ocr_fallback now refuses to wrap
  an empty/signature-only OCR result as success. If <80 useful chars or
  just "[signature]", returns an explicit failure that instructs the LLM
  not to describe / summarize the document.

* api/services/prompt_builder.py — TOOL_RULES adds the absolute rule
  "DOCUMENT FAITHFULNESS": never quote a document not literally in the
  tool result for THIS turn; never infer content from a file name; treat
  dates and case numbers as especially dangerous to invent.

Refs Task Master #5, #6, #7

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-26 13:58:37 +00:00
parent 90c60f45e6
commit 7b517e12b3
5 changed files with 170 additions and 28 deletions
+61 -18
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@@ -84,32 +84,75 @@ async def ocr_pdf(base64_data: str) -> str:
return "\n\n".join(pages_text)
def _extract_docx_xml_text(docx_zip) -> str:
"""Parse word/document.xml from a DOCX and return plain text.
The DOCX text payload is a flat sequence of <w:t>...</w:t> runs grouped
inside <w:p> paragraphs. We turn each paragraph into one text line.
"""
import re
try:
xml = docx_zip.read("word/document.xml").decode("utf-8", errors="replace")
except KeyError:
return ""
# Anchor the run-open to either `<w:t>` (no attrs) or `<w:t ...>` (with attrs).
# The `(?:\s[^>]*)?` keeps us from also matching `<w:tab>` / `<w:tbl>` etc.
run_re = re.compile(r"<w:t(?:\s[^>]*)?>(.*?)</w:t>", flags=re.DOTALL)
para_re = re.compile(r"<w:p(?:\s[^>]*)?>.*?</w:p>", flags=re.DOTALL)
paragraphs = []
for p_match in para_re.finditer(xml):
block = p_match.group(0)
line = "".join(run_re.findall(block)).strip()
if line:
paragraphs.append(line)
return "\n".join(paragraphs).strip()
async def ocr_docx_images(base64_data: str) -> str:
"""Extract images from a DOCX archive and OCR each via Claude Vision."""
"""Extract text + images from a DOCX archive.
Order of operations:
1. Read word/document.xml for the actual text content (the LLM needs this).
2. OCR any embedded images via Claude Vision (signatures, scanned inserts).
Previously this only OCR'd images, so a text-heavy DOCX with one signature
image returned only `[signature]` — and downstream LLMs hallucinated the rest.
"""
import zipfile
docx_bytes = base64.b64decode(base64_data)
image_extracts = []
try:
with zipfile.ZipFile(io.BytesIO(docx_bytes)) as z:
media = [n for n in z.namelist() if n.startswith("word/media/")]
logger.info("[ocr] docx images found=%d", len(media))
for i, name in enumerate(media[:MAX_PDF_PAGES]):
ext = name.rsplit(".", 1)[-1].lower()
mime = {"png": "image/png", "jpg": "image/jpeg", "jpeg": "image/jpeg", "gif": "image/gif"}.get(ext, "image/png")
img_bytes = z.read(name)
img_b64 = base64.b64encode(img_bytes).decode("ascii")
try:
text = await _call_vision([(mime, img_b64)])
image_extracts.append(f"=== תמונה {i + 1} ({name}) ===\n{text}")
except Exception as e:
logger.error("[ocr] docx image %s failed: %s", name, e)
z = zipfile.ZipFile(io.BytesIO(docx_bytes))
except zipfile.BadZipFile:
return "❌ הקובץ אינו DOCX תקין."
if not image_extracts:
return "❌ לא נמצאו תמונות ב-DOCX לחילוץ טקסט."
return "\n\n".join(image_extracts)
sections = []
# 1. Text from document.xml
xml_text = _extract_docx_xml_text(z)
logger.info("[ocr] docx xml text chars=%d", len(xml_text))
if xml_text:
sections.append(f"=== טקסט מהמסמך ({len(xml_text)} תווים) ===\n{xml_text}")
# 2. OCR each embedded image
media = [n for n in z.namelist() if n.startswith("word/media/")]
logger.info("[ocr] docx images found=%d", len(media))
for i, name in enumerate(media[:MAX_PDF_PAGES]):
ext = name.rsplit(".", 1)[-1].lower()
mime = {"png": "image/png", "jpg": "image/jpeg", "jpeg": "image/jpeg", "gif": "image/gif"}.get(ext, "image/png")
img_bytes = z.read(name)
img_b64 = base64.b64encode(img_bytes).decode("ascii")
try:
text = await _call_vision([(mime, img_b64)])
sections.append(f"=== תמונה {i + 1} ({name}) ===\n{text}")
except Exception as e:
logger.error("[ocr] docx image %s failed: %s", name, e)
if not sections:
return "❌ לא נמצא טקסט וגם לא תמונות ב-DOCX."
return "\n\n".join(sections)
async def extract_text_from_bytes(base64_data: str, mime_type: str, file_name: str = "") -> str:
+7
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@@ -44,6 +44,13 @@ TOOL_RULES = (
"- If a tool call fails, tell the user exactly what went wrong. Never pretend it succeeded.\n"
"- If you cannot perform an action (missing context, wrong mode), explain why honestly.\n"
"- After a successful tool call, you will receive the result. Only THEN confirm to the user what happened.\n"
"- DOCUMENT FAITHFULNESS (absolute rule — violations have already caused real damage in production):\n"
" * NEVER quote or summarize a document unless you literally see its text in a tool result returned in THIS conversation.\n"
" * If read_document / read_document_ocr returns an error, an empty body, or a message saying 'לא הצלחתי לחלץ טקסט' — STOP. Tell the user 'לא הצלחתי לקרוא את המסמך' and stop. Do not guess. Do not infer. Do not fill from memory or from the file name.\n"
" * If the tool result contains only '[signature]', '[חתימה]', or fewer than ~80 useful characters — treat it as an empty read. Do NOT invent content around it.\n"
" * The file name (e.g. 'כתב ערעור') tells you the TYPE of document, NEVER its CONTENT. Never write 'במסמך כתוב X' based on the file name.\n"
" * If the user asks you to base an action on a document and you could not read it — ask the user to paste the relevant text, or to send it differently. Do not proceed with a fabricated version.\n"
" * Numbers (dates, percentages, case numbers, IDs) are ESPECIALLY dangerous to invent — they will end up in CRM records and in tasks. When in doubt, ask the user, never guess.\n"
"- Dates: pass in YYYY-MM-DD format. If user says DD/MM/YYYY, convert it before calling the tool.\n"
"- If user does not specify a time for a task or meeting, default to 08:00 morning.\n"
"- CALL vs MEETING: When user reports they spoke/talked/called someone (שוחחתי, דיברתי, התקשרתי) — use create_call. When user reports a physical meeting or Zoom (נפגשתי, פגישה) — use create_meeting. NEVER use create_meeting for phone calls.\n"