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14 changes: 14 additions & 0 deletions libs/infinity_emb/infinity_emb/args.py
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
from copy import deepcopy


from infinity_emb import oci
from infinity_emb._optional_imports import CHECK_PYDANTIC
from infinity_emb.env import MANAGER
from infinity_emb.primitives import (
Expand Down Expand Up @@ -74,6 +75,19 @@ class EngineArgs:
_loading_strategy: Optional[LoadingStrategy] = None

def __post_init__(self):
# A CNCF ModelPack artifact is pulled through an llmman daemon and
# extracted to a local directory, which every engine then loads exactly
# as it would a local path. Done first so the rest of this method, and
# the loading strategy, only ever see a local path.
if oci.is_oci_ref(self.model_name_or_path):
if not self.served_model_name:
# Keep the reference the user typed as the served name; the
# resolved path is an implementation detail of the store.
object.__setattr__(self, "served_model_name", self.model_name_or_path)
object.__setattr__(
self, "model_name_or_path", oci.resolve(self.model_name_or_path)
)

# convert the following strings to enums
# so they don't need to be exported to the external interface
if not isinstance(self.engine, InferenceEngine):
Expand Down
222 changes: 222 additions & 0 deletions libs/infinity_emb/infinity_emb/llmman.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,222 @@
"""Client for a running ``llmman serve`` daemon.

Used to acquire models published as CNCF ModelPack
(https://github.com/modelpack/model-spec) OCI artifacts. The daemon owns the
registry work -- ModelPack media types, registry auth, resumable blob download
and a content-addressed store -- so it is not reimplemented here.

Contract (from llmman's src/cmd/serve.rs and src/daemon.rs):
- LLMMAN_HOST is ``[scheme://]host[:port][/path]``, default 127.0.0.1:17434.
A wildcard bind host (0.0.0.0, ::) is rewritten to loopback, since a client
cannot connect to "every interface".
- ``GET /api/version`` -> ``{"version":..., "exe":..., "pid":...}``.
- ``POST /api/pull`` ``{"model": ref}`` -> NDJSON stream of ``{"status":...}``
objects, terminated by ``{"status":"success"}`` or ``{"error":"..."}``.
An error can arrive in-band at HTTP 200.
- ``llmman resolve --no-pull <ref>`` -> one line of JSON carrying ``path``.
"""

import ipaddress
import json
import logging
import os
import shutil
import subprocess
import urllib.error
import urllib.request

logger = logging.getLogger(__name__)

HOST_ENV = "LLMMAN_HOST"
BIN_ENV = "INFINITY_LLMMAN_BIN"

DEFAULT_HOST = "127.0.0.1"
DEFAULT_PORT = 17434

PROBE_TIMEOUT_SECONDS = 5


def _connectable_host(host: str) -> str:
"""Rewrite a wildcard bind host to its loopback equivalent."""
try:
ip = ipaddress.ip_address(host.strip("[]"))
except ValueError:
return host
if not ip.is_unspecified:
return host
return "127.0.0.1" if ip.version == 4 else "::1"


def endpoint() -> str:
"""The http origin of the llmman daemon, honouring LLMMAN_HOST."""
raw = os.getenv(HOST_ENV, "").strip().strip("\"'")
if not raw:
return f"http://{DEFAULT_HOST}:{DEFAULT_PORT}"

if "://" in raw:
raw = raw.split("://", 1)[1]
Comment on lines +56 to +57

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P1 Configured HTTPS scheme discarded

If LLMMAN_HOST specifies an HTTPS daemon, endpoint() removes that scheme and unconditionally produces an http:// URL, causing OCI model initialization to fail against a TLS-only endpoint or silently dropping the configured transport protection.

raw = raw.split("/", 1)[0]

host, port = raw, DEFAULT_PORT
if raw.startswith("["): # bracketed IPv6, optionally with :port
close = raw.find("]")
if close != -1:
host = raw[: close + 1]
rest = raw[close + 1 :]
if rest.startswith(":") and rest[1:].isdigit():
port = int(rest[1:])
elif raw.count(":") == 1:
maybe_host, maybe_port = raw.rsplit(":", 1)
if maybe_port.isdigit():
host, port = maybe_host, int(maybe_port)

host = host or DEFAULT_HOST
resolved = _connectable_host(host)
if ":" in resolved and not resolved.startswith("["):
resolved = f"[{resolved}]"
return f"http://{resolved}:{port}"


def llmman_bin() -> str:
"""The llmman executable name, overridable per project."""
return os.getenv(BIN_ENV, "").strip() or "llmman"


def check_daemon(base: str) -> None:
"""Confirm an llmman daemon is listening and is actually llmman."""
url = base + "/api/version"
try:
with urllib.request.urlopen(url, timeout=PROBE_TIMEOUT_SECONDS) as resp:
if resp.status != 200:
raise RuntimeError(
f"llmman daemon at {base} answered /api/version with HTTP {resp.status}"
)
payload = json.loads(resp.read().decode("utf-8"))
except urllib.error.URLError as exc:
raise RuntimeError(
f"no llmman daemon reachable at {base} ({exc.reason}). Start one with "
f"`llmman serve`, or point {HOST_ENV} at an existing daemon."
) from exc
except json.JSONDecodeError as exc:
raise RuntimeError(
f"the server at {base} is not an llmman daemon (unparseable /api/version)"
) from exc

if not isinstance(payload, dict) or not payload.get("version"):
raise RuntimeError(
f"the server at {base} is not an llmman daemon (no version in /api/version)"
)


def pull(base: str, reference: str, progress=None) -> None:
"""Stream POST /api/pull until the daemon reports success.

``progress`` receives ``(status, completed, total)``. An error can arrive
in-band at HTTP 200, and a stream that ends without ``success`` is also a
failure -- neither is treated as a completed pull.
"""
body = json.dumps({"model": reference}).encode("utf-8")
req = urllib.request.Request(
base + "/api/pull",
data=body,
headers={"Content-Type": "application/json"},
method="POST",
)

succeeded = False
try:
with urllib.request.urlopen(req) as resp:

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P1 Model pull can hang startup

If the daemon accepts /api/pull but stalls its response or leaves the NDJSON stream open without a terminal status, this timeout-free urlopen and response loop block synchronous EngineArgs construction indefinitely, preventing the application server from completing startup.

if resp.status != 200:
raise RuntimeError(f"llmman pull of {reference!r} failed: HTTP {resp.status}")
for raw_line in resp:
line = raw_line.decode("utf-8").strip()
if not line:
continue
try:
obj = json.loads(line)
except json.JSONDecodeError:
# Tolerate a non-JSON diagnostic rather than aborting a
# pull that may still be progressing.
continue
if not isinstance(obj, dict):
continue
if obj.get("error"):
raise RuntimeError(f"llmman pull of {reference!r} failed: {obj['error']}")
status = obj.get("status")
if status == "success":
succeeded = True
continue
if progress is not None and status:
progress(status, obj.get("completed", 0), obj.get("total", 0))
except urllib.error.HTTPError as exc:
raise RuntimeError(f"llmman pull of {reference!r} failed: HTTP {exc.code}") from exc
except urllib.error.URLError as exc:
raise RuntimeError(f"llmman pull of {reference!r} failed: {exc.reason}") from exc

if not succeeded:
raise RuntimeError(f"llmman pull of {reference!r} ended without reporting success")


def parse_resolve_output(stdout: str, reference: str) -> str:
"""Parse ``llmman resolve`` stdout into the resolved local path."""
lines = [line.strip() for line in stdout.splitlines() if line.strip()]
if not lines:
raise RuntimeError(f"llmman resolve {reference!r}: no output on stdout")

try:
payload = json.loads(lines[-1])
except json.JSONDecodeError as exc:
raise RuntimeError(
f"llmman resolve {reference!r}: could not parse output as JSON: {lines[-1]}"
) from exc

if not isinstance(payload, dict):
# A protocol violation rather than a caller type error, so RuntimeError
# keeps every llmman failure one exception type for callers.
msg = f"llmman resolve {reference!r}: expected a JSON object, got {lines[-1]}"
raise RuntimeError(msg) # noqa: TRY004

path = payload.get("path")
if not isinstance(path, str) or not path.strip():
raise RuntimeError(f"llmman resolve {reference!r}: returned an empty path")
if not os.path.exists(path):
raise RuntimeError(f"llmman resolve {reference!r}: reported path {path!r} does not exist")
return path


def resolve(reference: str) -> str:
"""Ask the CLI where the daemon's pull left the model on disk.

``--no-pull`` guarantees this only reports on bytes ``/api/pull`` already
fetched, so the daemon stays the only thing that touches the network.
"""
binary = llmman_bin()
if shutil.which(binary) is None and not os.path.isfile(binary):
raise RuntimeError(
f"{binary!r} not found. Install llmman "
"(https://github.com/llmmanorg/llmman) and put it on PATH, or set "
f"{BIN_ENV} to its location."
)

completed = subprocess.run(
[binary, "resolve", "--no-pull", reference],
capture_output=True,
stdin=subprocess.DEVNULL,
text=True,
check=False,
)
if completed.returncode != 0:
Comment on lines +201 to +208

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P1 Resolver can hang startup

If llmman resolve --no-pull hangs because of daemon, lock, or filesystem contention, this subprocess.run has no timeout and blocks synchronous model initialization indefinitely, so the application server never becomes ready or reports a resolver failure.

raise RuntimeError(
f"`{binary} resolve --no-pull {reference}` failed with exit code "
f"{completed.returncode}: {completed.stderr.strip()}"
)
return parse_resolve_output(completed.stdout, reference)


def pull_and_resolve(reference: str, progress=None) -> str:
"""Full acquisition: probe the daemon, pull through it, report the path."""
base = endpoint()
check_daemon(base)
logger.info("Pulling %s via llmman daemon at %s", reference, base)
pull(base, reference, progress)

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P2 Badge Check for the llmman binary before pulling

When the daemon is reachable but llmman is absent or INFINITY_LLMMAN_BIN is misconfigured, this starts and may complete a multi-gigabyte registry pull before resolve() performs the binary check and inevitably fails startup. Preflight the executable after probing the daemon but before beginning the expensive pull.

Useful? React with 👍 / 👎.

return resolve(reference)
56 changes: 56 additions & 0 deletions libs/infinity_emb/infinity_emb/oci.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,56 @@
"""Resolve ``oci://`` model references to a local path.

A model published as a CNCF ModelPack (https://github.com/modelpack/model-spec)
artifact lives in an ordinary container registry, so it reuses the registry,
credentials, mirroring and air-gap tooling a deployment already has for
container images.

Acquisition is delegated to a running ``llmman serve``
(https://github.com/llmmanorg/llmman), which already implements the ModelPack
media types, registry auth, resumable blob download and a content-addressed
store. The daemon does the pull (POST /api/pull, streamed so a multi-gigabyte
fetch is not silent) but deliberately exposes no local path, so
``llmman resolve --no-pull`` reports where the bytes landed.

An explicit ``oci://`` scheme is required rather than sniffing a bare
``registry/name:tag``: that shape is indistinguishable from a HuggingFace repo
id (``org/model``), so guessing would silently hijack existing deployments.
"""

import logging

from infinity_emb import llmman

logger = logging.getLogger("infinity_emb")

SCHEME = "oci://"


def is_oci_ref(model_name_or_path) -> bool:
"""Whether the reference carries the ``oci://`` scheme."""
if not model_name_or_path:
return False
return str(model_name_or_path).lower().startswith(SCHEME)


def strip_scheme(model_name_or_path) -> str:
"""Drop the ``oci://`` prefix, leaving the bare registry reference."""
text = str(model_name_or_path)
if is_oci_ref(text):
return text[len(SCHEME) :]
return text


def resolve(model_name_or_path) -> str:
"""Pull an ``oci://`` reference through llmman and return the local path."""
reference = strip_scheme(model_name_or_path).strip()
if not reference:
raise ValueError(f"empty OCI model reference: {model_name_or_path!r}")

def _progress(status, completed, total):
if total:
logger.info("llmman: %s (%s/%s bytes)", status, completed, total)
else:
logger.info("llmman: %s", status)

return llmman.pull_and_resolve(reference, progress=_progress)
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