Files
LLeMbas/src/lembas/services/files.py
T
Jaroslav Beneš 5e75948069 Draw a picture, on a ComfyUI you are running
The last unbuilt capability, and built the way CLAUDE.md said it had to be: a
ToolDef reaching resolve_tools plus a permission and a capability flag, not a new
code path. The only genuinely new UI is one branch in the transcript.

services/images/ is three modules. comfy.py speaks HTTP -- submit, poll /history,
fetch the PNG, /free, and an /object_info discovery for the admin page only.
Polled and not socketed, because holding a connection open for the length of a
generation is the live-connection state the whole ssh.py design forbids, and the
thing being waited for takes tens of seconds anyway. The base URL is exempt from
the SSRF guard by construction, exactly as Connection.base_url and the audio
endpoints are -- said out loud in the docstring, because a default of
127.0.0.1:8188 is precisely the shape that guard exists to refuse and therefore
reads as a hole rather than a decision.

workflow.py fills a template, and the one thing that matters is that it walks the
parsed JSON rather than the text of it. A value that is exactly "{{steps}}"
becomes the number 20; ComfyUI validates types and refuses the string. A
placeholder inside a longer string is still text, which is what makes
"{{prompt}}, masterpiece" work -- and text substitution would additionally mean a
prompt containing a quotation mark produced a document that no longer parses, on
the one input guaranteed to hold arbitrary text. Which node holds the prompt is
the administrator's statement rather than a guess from node types: sniffing for
the first CLIPTextEncode works on the shipped workflow and on nothing else, and
swaps positive for negative the first time somebody reorders them. seed has no
fixed default, because one would make every unspecified generation identical and
make the retry loop redraw the same rejected picture four times.

tool.py is one call, one finished image. Returning every attempt to the
conversation would cost a round each, make the ceiling advisory rather than
enforced, and walk the reader past every reject -- so the reviewer lives inside
the tool and is asked about *bytes*: an attempt about to be discarded should not
leave an Attachment behind, so it sees a downscaled preview built in memory and
only the kept image is written. Anything that goes wrong in review is a keep;
losing a picture because a judging request timed out would be the check
destroying the thing it was checking. The last attempt is kept whatever the
verdict, so a request always produces something. Rejects are recorded, not
stored.

Preserve VRAM unloads the chat's own connection and nothing else, because the
memory being freed belongs to one machine: local llama-swap answers GET /unload,
and a box on the network has no reason to be unloaded when ComfyUI wants memory
here. The swap goes round the review rather than round the tool, which costs two
model loads per retry -- so the two settings are independent and the page warns
when both are on. Nothing loads the LLM back: the reply's next request does, and
that step exists in the description and not in the code, so the code says so.

Two rules elsewhere had to be drawn for the first time. message_payload sends
images only on user turns -- no assistant message had ever carried one, and the
moment one does the multimodal list form on an assistant turn is rejected by
OpenAI and most local runners, breaking every later turn in the chat. And
files.store gained keep_original, because _process_image turns anything without
alpha into JPEG q85 at 1400px: right for a phone photo, a visible loss on the one
output this feature exists to produce.

/image sends the ordinary message with force_tool, which becomes tool_choice for
the first round only -- left in place the reply would draw a picture, be asked
again, and draw another. FORCEABLE_TOOLS is an allow list because the name is
read off a form.

ToolContext gained chat_id, and that fixed a tool nobody had ever successfully
run: _run_scratch_write read context.chat_id on a dataclass with no such field,
so every call raised AttributeError, swallowed by run_tool's blanket except into
"the scratch_write tool failed" -- indistinguishable from a model calling it
wrongly. The test that existed asserted the family and the risk, which are
properties of the declaration rather than of the code.

Verified against the real ComfyUI 0.27.0 on this machine rather than against
documentation: every endpoint shape here was read off it, a generation ran end to
end through the client, the reviewer was shown a matching and a mismatched prompt
and answered KEEP and RETRY correctly, and the unload hook fired for the local
llama-swap and not for the remote box.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-05 14:13:19 +02:00

644 lines
23 KiB
Python

"""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 _keep_image(payload: bytes) -> Prepared:
"""An image stored as it arrived, measured but not re-encoded.
`_process_image` exists to protect the window from a phone camera: eight
megapixels of JPEG become 1400px of JPEG at quality 85, and for something
somebody photographed that is all upside. For an image *this application
asked a diffusion model to make*, at a size somebody chose, it is a visible
loss on the one output the feature exists to produce -- soft detail and
ringing on exactly the fine texture the prompt was about.
Still opened by Pillow, so a malformed file is still refused and the
dimensions are still real rather than claimed; still bounded by
`MAX_UPLOAD_BYTES` in `prepare`. What is skipped is only the resize and the
transcode.
"""
detected = _detect_image(payload)
if detected is None:
raise FileError("That is not an image.")
media_type, extension = detected
try:
with Image.open(io.BytesIO(payload)) as image:
image.load()
width, height = image.size
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
return Prepared(
payload=payload,
kind=KIND_IMAGE,
media_type=media_type,
extension=extension,
width=width,
height=height,
)
def prepare(payload: bytes, filename: str, *, keep_original: bool = False) -> Prepared:
"""Inspect an upload, decide what it is, and process it accordingly.
`keep_original` is for an image the application produced rather than one
somebody sent: see `_keep_image`. It applies to images only -- there is no
argument for keeping an unparsed PDF, and the text path stores its bytes
verbatim already.
"""
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 _keep_image(payload) if keep_original else _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,
keep_original: bool = False,
source_path: str = "",
source_label: str = "",
message_id: str | None = None,
) -> Attachment:
"""Process and persist an upload. Raises FileError if it is unusable.
`message_id` is normally left null -- an upload is bound to a turn by
`claim()` when the message is sent. A generated image is the mirror image of
that: it exists *because* a reply is being written, so it says which turn it
belongs to at the moment it is made.
"""
prepared = prepare(payload, filename, keep_original=keep_original)
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,
message_id=message_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,
source_path=source_path[:1000],
source_label=source_label[:200],
)
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 store_text(
db: DBSession,
*,
user_id: str,
chat_id: str | None,
filename: str,
text: str,
truncated: bool = False,
source_note: str = "",
source_path: str = "",
source_label: str = "",
) -> Attachment:
"""Attach text that did not arrive as a file -- a fetched web page.
Written to disk like any other attachment so it can be downloaded and so
there is one cleanup path, rather than a second kind of attachment that
exists only in the database.
`source_note` leads the *text*; `source_path` and `source_label` are
columns. The two are not the same thing and both are wanted: the note is
prose a model reads inside the document, and the columns become attributes
on the tag around it, which is what a reader sees on the chip and what
survives if the text is later truncated away from its own first line.
"""
body = text[:MAX_EXTRACTED_CHARS]
payload = body.encode("utf-8")
stored_name = f"{secrets.token_hex(16)}.txt"
(attachments_dir() / stored_name).write_bytes(payload)
attachment = Attachment(
user_id=user_id,
chat_id=chat_id,
filename=safe_display_name(filename),
stored_name=stored_name,
media_type="text/plain",
size_bytes=len(payload),
kind=KIND_TEXT,
# The URL leads the text so the model can cite it, and so the reader
# can see where an attachment called "Some Page.txt" came from.
extracted_text=f"Source: {source_note}\n\n{body}" if source_note else body,
truncated=truncated,
source_path=source_path[:1000],
source_label=source_label[:200],
)
db.add(attachment)
db.commit()
return attachment
def copy_attachment(
db: DBSession, *, user_id: str, chat_id: str | None, attachment: Attachment
) -> Attachment:
"""Duplicate something already sent, so it can ride along with a new message.
A copy and not a second reference to one row: an attachment belongs to the
message it was sent with, and sharing one between two would make deleting
either of them a question rather than an answer.
"""
stored_name = ""
source = attachments_dir() / attachment.stored_name if attachment.stored_name else None
if source is not None and source.exists():
stored_name = f"{secrets.token_hex(16)}{Path(source.name).suffix}"
(attachments_dir() / stored_name).write_bytes(source.read_bytes())
copy = Attachment(
user_id=user_id,
chat_id=chat_id,
filename=attachment.filename,
stored_name=stored_name,
media_type=attachment.media_type,
size_bytes=attachment.size_bytes,
kind=attachment.kind,
width=attachment.width,
height=attachment.height,
extracted_text=attachment.extracted_text,
pages=attachment.pages,
truncated=attachment.truncated,
extraction_error=attachment.extraction_error,
source_path=attachment.source_path,
source_label=attachment.source_label,
)
db.add(copy)
db.commit()
return copy
def copy_document(
db: DBSession, *, user_id: str, chat_id: str | None, document
) -> Attachment:
"""Copy a library document into a message being composed.
A copy rather than a reference. History must not change under a conversation
because a document was edited or deleted afterwards -- the same reason text
is extracted once at upload instead of per request. The bytes are duplicated
too, so deleting the document cannot leave a message pointing at nothing.
"""
from lembas.services.library import documents as documents_service
stored_name = ""
source = documents_service.stored_path(document.stored_name)
if source is not None:
stored_name = f"{secrets.token_hex(16)}{Path(source.name).suffix}"
(attachments_dir() / stored_name).write_bytes(source.read_bytes())
attachment = Attachment(
user_id=user_id,
chat_id=chat_id,
filename=document.filename or f"{document.title}.txt",
stored_name=stored_name,
media_type=document.media_type,
size_bytes=document.size_bytes,
kind=document.kind,
width=document.width,
height=document.height,
extracted_text=document.extracted_text,
pages=document.pages,
truncated=document.truncated,
extraction_error=document.extraction_error,
# Where it came from, for the same reason a project file carries it: a
# model handed four documents cannot tell which is which, and cannot
# name one back when asked to work on it. This was the one attach path
# that dropped provenance.
source_path=(document.title or "")[:1000],
source_label=(document.base.name if document.base else "Knowledge")[:200],
)
db.add(attachment)
db.commit()
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 remove_files_for_chats(db: DBSession, chat_ids: list[str]) -> int:
"""Unlink the files belonging to these chats' attachments.
Deleting a Chat cascades to its Message and Attachment *rows* but leaves the
files on disk -- only `sweep_orphans` unlinks anything, and it only looks at
uploads that were never attached. Anything that deletes chats has to call
this first, while the rows still say which files to remove.
"""
if not chat_ids:
return 0
removed = 0
for attachment in db.scalars(select(Attachment).where(Attachment.chat_id.in_(chat_ids))):
path = stored_path(attachment.stored_name)
if path is not None and path.exists():
path.unlink(missing_ok=True)
removed += 1
return removed
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}"
def preview_data_uri(payload: bytes, *, max_edge: int = MAX_IMAGE_EDGE) -> str | None:
"""The same thing for bytes in hand, downscaled, for a model to look at.
Fidelity and weight are two different jobs. What is stored is what ComfyUI
produced, because that is the artefact somebody keeps; what is *shown to a
model to be judged* wants to be small, because a 400KB PNG is 550KB of
base64 in a request that exists only to answer one question.
Takes bytes rather than an Attachment: the reviewer looks at an image that
may be about to be thrown away, and writing a row for something rejected
seconds later is work with nothing to show for it.
"""
import base64
try:
with Image.open(io.BytesIO(payload)) as image:
image.load()
frame = image.convert("RGB")
longest = max(frame.size)
if longest > max_edge:
scale = max_edge / longest
frame = frame.resize(
(max(1, int(frame.width * scale)), max(1, int(frame.height * scale))),
Image.LANCZOS,
)
buffer = io.BytesIO()
frame.save(buffer, format="JPEG", quality=JPEG_QUALITY, optimize=True)
except (Image.DecompressionBombError, UnidentifiedImageError, OSError, ValueError):
log.warning("could not build a preview of a generated image", exc_info=True)
return None
encoded = base64.b64encode(buffer.getvalue()).decode("ascii")
return f"data:image/jpeg;base64,{encoded}"