File attachments: images for vision, PDFs and text into the prompt

Drag, paste or pick a file in the composer. Images go to vision models
as multimodal content parts; PDFs and text files have their content
extracted and placed in the prompt. Verified end to end against
gemma4-e4b-q8 on llama-swap: given a drawing and a text file, it named
the red square and blue circle and read the number out of the document.

Type is decided by inspecting the bytes, never the filename or the
browser's Content-Type -- a .png full of text is stored as text. Images
are downscaled to 1400px and re-encoded: a phone photo is several
megabytes of base64, which is slow and a large slice of the context
window. PDF text is extracted once, at upload, and stored; re-extracting
per request would let a reply change because a parser was upgraded.

Design points worth keeping:

- Images are only sent to models an administrator has marked `vision`.
  This is not graceful degradation -- most endpoints reject the entire
  request rather than ignoring an image part. A plain text turn stays a
  plain string for the same reason: the list form 400s on endpoints that
  do not implement it.
- Images reach the model as base64 data URIs, not links. A local
  endpoint has no route back to LLeMbas, and a hosted one has no
  credentials for it.
- Non-images are served Content-Disposition: attachment with nosniff, so
  an uploaded .html can never execute in this origin. Stored names are
  random; the uploader's name is a label and never a path.
- Uploads are unbound until the message is sent, which is what lets a
  file be removed beforehand. claim() only takes unclaimed rows owned by
  the sender, so a forged id cannot pull in someone else's file.
  Abandoned uploads are swept at startup.
- A scanned PDF says so rather than silently contributing nothing, and
  truncation is declared to the model in the document tag so it can
  admit it did not see page 400.
- "Here, look at this" with no words is a legitimate turn, so a message
  is only empty when it carries neither text nor files.

Also fixes auto-titling, which read message["content"] as a string and
would have broken on the first multimodal turn.

186 tests, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Jaroslav Beneš
2026-07-21 12:19:59 +02:00
parent d6c87ac811
commit bdce2764b1
19 changed files with 1601 additions and 20 deletions
+80 -6
View File
@@ -17,6 +17,7 @@ from lembas.db.models import (
Message,
Model,
)
from lembas.services import files as files_service
from lembas.services.llm.openai_client import Endpoint, LLMError, complete
log = logging.getLogger(__name__)
@@ -71,7 +72,66 @@ def resolve_endpoint(db: DBSession, chat: Chat) -> tuple[Endpoint, str]:
return Endpoint.from_connection(connection), chat.model_id
def build_messages(db: DBSession, chat: Chat, *, upto: Message | None = None) -> list[dict]:
def document_context(message: Message) -> str:
"""Extracted text from a message's non-image attachments.
Wrapped in named tags so the model can tell one document from another, and
tell all of them from what the user actually typed. Truncation is stated
inline rather than silently, so a model asked about page 400 of a 300-page
extract can say it did not see it.
"""
blocks: list[str] = []
for attachment in message.documents:
if not attachment.extracted_text.strip():
continue
note = " (truncated)" if attachment.truncated else ""
blocks.append(
f'<document name="{attachment.filename}"{note}>\n'
f"{attachment.extracted_text.strip()}\n"
f"</document>"
)
return "\n\n".join(blocks)
def message_payload(message: Message, *, vision: bool) -> dict[str, Any]:
"""One history entry in the shape the endpoint expects.
Plain text stays a plain string: sending the multimodal list form to an
endpoint that does not implement it is a reliable way to get a 400, and
most local runners do not.
"""
text = message.content.strip()
documents = document_context(message)
if documents:
# Documents lead so the question that follows has its material already
# in view, which is how these models are trained to read a prompt.
text = f"{documents}\n\n{text}" if text else documents
images = message.images if vision else []
if not images:
return {"role": message.role, "content": text}
parts: list[dict[str, Any]] = []
if text:
parts.append({"type": "text", "text": text})
for attachment in images:
uri = files_service.data_uri(attachment)
if uri is None:
# The row survived but the file did not. Better to say so than to
# send a turn that silently lost its picture.
log.warning("attachment %s has no file on disk", attachment.id)
continue
parts.append({"type": "image_url", "image_url": {"url": uri}})
if not parts:
return {"role": message.role, "content": text}
return {"role": message.role, "content": parts}
def build_messages(
db: DBSession, chat: Chat, *, upto: Message | None = None, vision: bool = False
) -> list[dict]:
"""Assemble the message list to send upstream.
`upto` excludes the placeholder assistant row being generated into, and
@@ -88,24 +148,38 @@ def build_messages(db: DBSession, chat: Chat, *, upto: Message | None = None) ->
for message in history:
if upto is not None and message.id == upto.id:
break
# Skip turns that failed or produced nothing: sending an empty
# assistant message upsets several providers.
if message.error or not message.content.strip():
# Skip turns that failed or produced nothing -- but a message carrying
# only an attachment has no text and must still be sent.
if message.error:
continue
payload.append({"role": message.role, "content": message.content})
if not message.content.strip() and not message.attachments:
continue
payload.append(message_payload(message, vision=vision))
return payload
def model_supports(db: DBSession, chat: Chat, capability: str) -> bool:
"""Whether the chat's current model is marked as having a capability."""
model = db.scalar(
select(Model).where(Model.model_id == chat.model_id).order_by(Model.position)
)
return bool(model and (model.capabilities_json or {}).get(capability))
def build_request(db: DBSession, chat: Chat, *, upto: Message | None = None) -> dict[str, Any]:
params = {
key: value
for key, value in (chat.params_json or {}).items()
if key in FORWARDED_PARAMS and value not in (None, "")
}
# Images are only sent to a model an administrator has marked as having
# vision. Sending them to one that has not is not a graceful degradation:
# most endpoints reject the whole request.
vision = model_supports(db, chat, "vision")
return {
"model": chat.model_id,
"messages": build_messages(db, chat, upto=upto),
"messages": build_messages(db, chat, upto=upto, vision=vision),
**params,
}
+400
View File
@@ -0,0 +1,400 @@
"""Storing and reading uploaded attachments.
Three kinds of file, each handled differently on the way to the model:
* **Images** are downscaled and re-encoded, then sent as multimodal content
parts. Downscaling is not cosmetic -- a phone photo is several megabytes of
base64, which is both slow and a large slice of the context window.
* **PDFs** have their text extracted once, at upload. Extraction is slow and a
reply must not silently change because a parser was upgraded later.
* **Plain text** (including source code and CSV) is decoded and stored as-is.
Everything an uploader supplies is treated as hostile: the type is decided by
inspecting the bytes rather than trusting the browser, the name on disk is
random, and both image dimensions and PDF page counts are capped so a small
file cannot expand into an enormous amount of work.
"""
from __future__ import annotations
import io
import logging
import secrets
from dataclasses import dataclass
from datetime import UTC, datetime, timedelta
from pathlib import Path
from PIL import Image, UnidentifiedImageError
from sqlalchemy import select
from sqlalchemy.orm import Session as DBSession
from lembas.config import settings
from lembas.db.models import KIND_DOCUMENT, KIND_IMAGE, KIND_TEXT, Attachment
log = logging.getLogger(__name__)
# --- Limits ------------------------------------------------------------------
MAX_UPLOAD_BYTES = 20 * 1024 * 1024
# Longest edge after downscaling. Large enough for a model to read a screenshot
# or a page of text, small enough that the base64 stays reasonable.
MAX_IMAGE_EDGE = 1400
JPEG_QUALITY = 85
# Pillow's own guard against decompression bombs: a 60,000x60,000 PNG is a few
# KB on disk and hundreds of GB decoded.
Image.MAX_IMAGE_PIXELS = 64_000_000
MAX_PDF_PAGES = 300
# Characters of extracted text kept per document. Roughly 30k tokens, which is
# already a large slice of most context windows; more is rarely useful and
# frequently breaks the request outright.
MAX_EXTRACTED_CHARS = 120_000
# Orphans are files uploaded into a composer that was never sent.
ORPHAN_AGE = timedelta(hours=24)
IMAGE_TYPES: dict[bytes, tuple[str, str]] = {
b"\x89PNG\r\n\x1a\n": ("image/png", ".png"),
b"\xff\xd8\xff": ("image/jpeg", ".jpg"),
b"GIF87a": ("image/gif", ".gif"),
b"GIF89a": ("image/gif", ".gif"),
}
# Extensions treated as text when the bytes decode cleanly as UTF-8. The list
# exists only to pick a sensible media type; decodability is what actually
# decides, so an unlisted extension still works.
TEXT_EXTENSIONS = {
".txt": "text/plain", ".md": "text/markdown", ".markdown": "text/markdown",
".csv": "text/csv", ".tsv": "text/tab-separated-values",
".json": "application/json", ".yaml": "text/yaml", ".yml": "text/yaml",
".toml": "text/toml", ".ini": "text/plain", ".cfg": "text/plain",
".xml": "text/xml", ".html": "text/plain", ".css": "text/plain",
".py": "text/x-python", ".js": "text/javascript", ".ts": "text/typescript",
".rs": "text/x-rust", ".go": "text/x-go", ".c": "text/x-c", ".h": "text/x-c",
".cpp": "text/x-c++", ".java": "text/x-java", ".rb": "text/x-ruby",
".sh": "text/x-shellscript", ".sql": "text/x-sql", ".log": "text/plain",
}
class FileError(Exception):
"""A rejected upload, with a message fit to show the user."""
@dataclass
class Prepared:
"""The result of inspecting and processing an upload, before it is stored."""
payload: bytes
kind: str
media_type: str
extension: str
width: int = 0
height: int = 0
extracted_text: str = ""
pages: int = 0
truncated: bool = False
extraction_error: str = ""
# --- Storage -----------------------------------------------------------------
def attachments_dir() -> Path:
path = settings.uploads_dir / "attachments"
path.mkdir(parents=True, exist_ok=True)
return path
def stored_path(stored_name: str) -> Path | None:
"""Resolve a stored name to a path, refusing anything outside the directory."""
if not stored_name or "/" in stored_name or "\\" in stored_name or stored_name.startswith("."):
return None
base = attachments_dir().resolve()
path = (base / stored_name).resolve()
try:
path.relative_to(base)
except ValueError:
return None
return path if path.is_file() else None
# --- Type detection ----------------------------------------------------------
def _detect_image(payload: bytes) -> tuple[str, str] | None:
for signature, (media_type, extension) in IMAGE_TYPES.items():
if payload.startswith(signature):
return media_type, extension
if payload[:4] == b"RIFF" and payload[8:12] == b"WEBP":
return "image/webp", ".webp"
return None
def _looks_like_pdf(payload: bytes) -> bool:
# The header is allowed a little leading junk by the spec, and real files
# in the wild use it.
return b"%PDF-" in payload[:1024]
# --- Processing --------------------------------------------------------------
def _process_image(payload: bytes) -> Prepared:
try:
with Image.open(io.BytesIO(payload)) as image:
image.load()
has_alpha = image.mode in ("RGBA", "LA", "P") and "transparency" in image.info
# Animation is lost on re-encode; keeping only the first frame is
# honest and is what a model would see anyway.
frame = image.convert("RGBA" if has_alpha else "RGB")
width, height = frame.size
longest = max(width, height)
if longest > MAX_IMAGE_EDGE:
scale = MAX_IMAGE_EDGE / longest
frame = frame.resize(
(max(1, int(width * scale)), max(1, int(height * scale))),
Image.LANCZOS,
)
buffer = io.BytesIO()
if has_alpha:
frame.save(buffer, format="PNG", optimize=True)
media_type, extension = "image/png", ".png"
else:
frame.save(buffer, format="JPEG", quality=JPEG_QUALITY, optimize=True)
media_type, extension = "image/jpeg", ".jpg"
return Prepared(
payload=buffer.getvalue(),
kind=KIND_IMAGE,
media_type=media_type,
extension=extension,
width=frame.width,
height=frame.height,
)
except Image.DecompressionBombError as exc:
raise FileError("That image's dimensions are implausibly large.") from exc
except (UnidentifiedImageError, OSError, ValueError) as exc:
raise FileError("That image could not be read. Is it corrupt?") from exc
def _process_pdf(payload: bytes) -> Prepared:
from pypdf import PdfReader
from pypdf.errors import PdfReadError
prepared = Prepared(
payload=payload, kind=KIND_DOCUMENT, media_type="application/pdf", extension=".pdf"
)
try:
reader = PdfReader(io.BytesIO(payload))
if reader.is_encrypted:
# An empty password unlocks a surprising number of "encrypted" PDFs.
try:
reader.decrypt("")
except Exception: # noqa: BLE001 - any failure means the same thing
prepared.extraction_error = (
"This PDF is password-protected, so its text could not be read."
)
return prepared
prepared.pages = len(reader.pages)
chunks: list[str] = []
total = 0
for index, page in enumerate(reader.pages[:MAX_PDF_PAGES]):
try:
text = page.extract_text() or ""
except Exception as exc: # noqa: BLE001 - one bad page is not fatal
log.debug("page %d of a PDF failed to extract: %s", index, exc)
continue
if not text.strip():
continue
chunks.append(f"[page {index + 1}]\n{text.strip()}")
total += len(text)
if total >= MAX_EXTRACTED_CHARS:
prepared.truncated = True
break
if prepared.pages > MAX_PDF_PAGES:
prepared.truncated = True
prepared.extracted_text = "\n\n".join(chunks)[:MAX_EXTRACTED_CHARS]
if not prepared.extracted_text.strip():
# Almost always a scan. Saying so beats the model silently ignoring
# a document the user believes it can read.
prepared.extraction_error = (
"No text could be extracted. This looks like a scanned PDF; "
"LLeMbas does not do OCR yet."
)
except PdfReadError as exc:
prepared.extraction_error = "This file is not a readable PDF."
log.info("unreadable PDF: %s", exc)
except Exception as exc: # noqa: BLE001 - never let a bad file 500 the upload
prepared.extraction_error = "This PDF could not be read."
log.warning("unexpected PDF failure: %s", exc)
return prepared
def _process_text(payload: bytes, filename: str) -> Prepared:
for encoding in ("utf-8", "utf-16", "latin-1"):
try:
text = payload.decode(encoding)
break
except (UnicodeDecodeError, LookupError):
continue
else:
raise FileError("That file is not text, and is not a format LLeMbas can read.")
# Null bytes mean this decoded by luck (latin-1 decodes any byte) and is
# really a binary file.
if "\x00" in text[:4096]:
raise FileError("That file is not text, and is not a format LLeMbas can read.")
truncated = len(text) > MAX_EXTRACTED_CHARS
extension = Path(filename).suffix.lower()
return Prepared(
payload=payload,
kind=KIND_TEXT,
media_type=TEXT_EXTENSIONS.get(extension, "text/plain"),
extension=extension if extension in TEXT_EXTENSIONS else ".txt",
extracted_text=text[:MAX_EXTRACTED_CHARS],
truncated=truncated,
)
def prepare(payload: bytes, filename: str) -> Prepared:
"""Inspect an upload, decide what it is, and process it accordingly."""
if not payload:
raise FileError("That file is empty.")
if len(payload) > MAX_UPLOAD_BYTES:
raise FileError(f"Files must be under {MAX_UPLOAD_BYTES // (1024 * 1024)} MB.")
if _detect_image(payload) is not None:
return _process_image(payload)
if _looks_like_pdf(payload):
return _process_pdf(payload)
return _process_text(payload, filename)
# --- Public API --------------------------------------------------------------
def safe_display_name(filename: str) -> str:
"""A filename fit to show. Never used as a path; the stored name is random."""
cleaned = Path(filename or "file").name.strip() or "file"
return cleaned[:300]
def store(
db: DBSession,
*,
user_id: str,
chat_id: str | None,
payload: bytes,
filename: str,
) -> Attachment:
"""Process and persist an upload. Raises FileError if it is unusable."""
prepared = prepare(payload, filename)
stored_name = f"{secrets.token_hex(16)}{prepared.extension}"
(attachments_dir() / stored_name).write_bytes(prepared.payload)
attachment = Attachment(
user_id=user_id,
chat_id=chat_id,
filename=safe_display_name(filename),
stored_name=stored_name,
media_type=prepared.media_type,
size_bytes=len(prepared.payload),
kind=prepared.kind,
width=prepared.width,
height=prepared.height,
extracted_text=prepared.extracted_text,
pages=prepared.pages,
truncated=prepared.truncated,
extraction_error=prepared.extraction_error,
)
db.add(attachment)
db.commit()
log.info(
"stored %s (%s, %d bytes) for user %s",
attachment.filename,
attachment.kind,
attachment.size_bytes,
user_id,
)
return attachment
def delete(db: DBSession, attachment: Attachment) -> None:
path = stored_path(attachment.stored_name)
if path is not None:
path.unlink(missing_ok=True)
db.delete(attachment)
db.commit()
def claim(db: DBSession, *, ids: list[str], user_id: str, message_id: str) -> list[Attachment]:
"""Bind pending uploads to the message that was just sent.
Only unclaimed attachments belonging to this user are taken, so a stray or
forged id cannot pull someone else's file into a conversation.
"""
if not ids:
return []
pending = list(
db.scalars(
select(Attachment).where(
Attachment.id.in_(ids),
Attachment.user_id == user_id,
Attachment.message_id.is_(None),
)
)
)
for attachment in pending:
attachment.message_id = message_id
db.commit()
return pending
def sweep_orphans(db: DBSession, older_than: timedelta = ORPHAN_AGE) -> int:
"""Delete uploads that were never attached to a message.
A file picked in the composer and then abandoned would otherwise sit on
disk forever.
"""
cutoff = datetime.now(UTC) - older_than
orphans = list(db.scalars(select(Attachment).where(Attachment.message_id.is_(None))))
removed = 0
for attachment in orphans:
created = attachment.created_at
if created.tzinfo is None:
created = created.replace(tzinfo=UTC)
if created >= cutoff:
continue
path = stored_path(attachment.stored_name)
if path is not None:
path.unlink(missing_ok=True)
db.delete(attachment)
removed += 1
if removed:
db.commit()
log.info("swept %d orphaned upload(s)", removed)
return removed
def data_uri(attachment: Attachment) -> str | None:
"""Base64 data URI for an image, as sent to a vision model.
A data URI rather than a link back to this server: a local endpoint has no
route to LLeMbas, and a hosted one has no credentials for it.
"""
import base64
path = stored_path(attachment.stored_name)
if path is None:
return None
encoded = base64.b64encode(path.read_bytes()).decode("ascii")
return f"data:{attachment.media_type};base64,{encoded}"