Files
odysseus/scripts/import_from_vllm_recipes.py
pewdiepie-archdaemon 2cbd55b8bd Open email context for agent, email search across All Mail, cookbook serve polish
- Agent: pass the open email reader (uid/folder/account/from/subject/body
  preview) on every chat submit so 'reply to this' / 'write email saying
  hi' route to ui_control open_email_reply with the right UID instead of
  inventing a new .md draft. Code-level enforcement (chat_routes strips
  create_document + send_email when active_email is set); cross-session
  active_doc_id is now trusted instead of being silently dropped.
  set_active_email/clear_active_email tool-layer helpers in
  tool_implementations.

- ui_control open_email_reply: optional body argument so the agent can
  open-and-write in one call; envelope now forwards uid/folder/account/
  body/panel through tool_output. Tool description sharpened and the
  parser rejects empty bodies on reply/reply-all (forces the agent to
  write rather than open an empty draft).

- Email library: search now runs against [Gmail]/All Mail when the
  current folder is INBOX (archived emails surface). Whirlpool spinner
  + 'Searching…' placeholder while in flight. Each search result is
  stamped with its source folder so clicks open the right email instead
  of whatever shares its UID in INBOX. Search no longer re-applies the
  same text pill locally (which only checks subject/from/snippet, never
  body) so body-only matches don't get dropped after IMAP returns them.
  Initial inbox load bumped 100→500.

- Email favorites: 'Favorite (pin to top)' / 'Unfavorite' in both the
  card menu and the open-reader more menu, backed by a new
  /api/email/flag/{uid}?on=true|false endpoint. Flagged emails always
  bubble to the top of the grid regardless of active sort.

- AI reply in doc editor: never overwrites existing draft text or the
  quoted history. AI suggestion is prepended; AI-generated 'On …
  wrote:' re-quotes are stripped so the original quote isn't visually
  edited.

- Cookbook serve: pre-launch GPU driver / has_gpu / install / version-
  floor checks (vllm minimax_m2 needs 0.10.0+, deepseek_r1 needs 0.7.0
  etc.) before the launch chain starts. Detect 'another model already
  running on this host' and offer Stop & launch (with graceful then
  force tmux kill helpers, port release wait). Per-vendor deep-link
  buttons (vLLM recipe / SGLang cookbook) with hardware hash. Backend
  picker is now a custom dropdown with accent-coloured logos for vLLM,
  SGLang, llama.cpp, Ollama, Diffusers; same glyphs added next to
  package names in Dependencies. Runtime-readiness note moved inside
  the panel (green when ready, red when missing) with an × dismiss.
  Esc collapses the expanded card; expanded card scrolls when it
  overflows; Trust Remote / Auto Tool / Reasoning Parser / Enforce
  Eager / Prefix Caching / Expert Parallel / Speculative / MoE Env on
  one row (Reasoning Parser auto-detected per model family).
  Dtype→Row 1, GPUs→Row 2 (rightmost). Removed redundant GPU 'auto'
  input — command builders read from the GPU button strip. Default
  cookbook open is Download tab.

- Cookbook hwfit: 'Model (latest)' / 'Model (oldest)' header sorts by
  release_date; release dates can be backfilled with the new
  scripts/backfill_model_release_dates.py and recipe metadata pulled
  with scripts/import_from_vllm_recipes.py against the upstream
  vllm-project/recipes catalog (vllm_recipe + min_vllm_version stamped
  on entries).

- Calendar: Quick add hint cycles a random Odysseus-themed example per
  open (wooden horse Friday, crew muster 10am daily, council on
  Ithaca, …). Typing a time like '11pm' in the event title updates
  the hero clock live.

- Doc editor: email-mode Reply button (sparkle icon, accent) opens the
  same Fast/Full + context popover the email reader uses; Ctrl+Alt+M
  toggles markdown preview.

- Memories panel: custom sort picker with per-option icons, default
  'Latest', visible Enabled/Disabled toggle text matching the section
  description style.
2026-06-15 20:47:51 +09:00

342 lines
13 KiB
Python
Executable File

#!/usr/bin/env python3
"""Import models from the upstream vllm-project/recipes catalog into our
local hf_models.json. Two modes:
--update-existing Stamp min_vllm_version + vllm_recipe=True on rows we
already carry. Cheap, no HF API calls.
--add-missing Create new catalog rows for every recipe model we
don't carry. Hits the HF API for created_at + downloads
(~1 req per missing model, paced).
Both modes write atomically (tmp + rename) so a crashed run leaves the
catalog intact. Default with no mode flags runs both, prefer to pass them
explicitly.
Usage:
python scripts/import_from_vllm_recipes.py --update-existing
python scripts/import_from_vllm_recipes.py --add-missing
python scripts/import_from_vllm_recipes.py --dry-run
python scripts/import_from_vllm_recipes.py --limit 10
Auth: set HF_TOKEN to access gated repos when --add-missing.
"""
import argparse
import json
import os
import re
import sys
import time
from datetime import datetime
from pathlib import Path
try:
import httpx
import yaml
except ImportError:
print("pip install httpx PyYAML", file=sys.stderr)
sys.exit(1)
try:
from huggingface_hub import HfApi
from huggingface_hub.utils import HfHubHTTPError
except ImportError:
HfApi = None
HfHubHTTPError = Exception
CATALOG_PATH = Path(__file__).resolve().parent.parent / "services" / "hwfit" / "data" / "hf_models.json"
RECIPES_TREE_URL = (
"https://api.github.com/repos/vllm-project/recipes/git/trees/main?recursive=1"
)
RECIPE_RAW_URL = (
"https://raw.githubusercontent.com/vllm-project/recipes/main/models/{repo}.yaml"
)
# Map recipe `precision` to the closest catalog `quantization` label that
# fit.py / models.py already understand.
_PRECISION_TO_QUANT = {
"fp8": "FP8",
"nvfp4": "NVFP4",
"mxfp4": "MXFP4",
"bf16": "BF16",
"fp16": "F16",
"f16": "F16",
"fp4": "FP4",
"int8": "INT8",
"int4": "INT4",
"awq-4bit": "AWQ-4bit",
"awq-8bit": "AWQ-8bit",
}
# Architecture name → use_case fallback. fit.py weights use_case for filtering;
# missing field defaults to a generic bucket.
_ARCH_USE_CASE = {
"moe": "General-purpose reasoning, long-context",
"llama": "General-purpose chat",
"qwen2": "General-purpose chat",
"qwen3": "General-purpose reasoning",
"deepseek_v3_moe": "General-purpose reasoning, long-context",
"deepseek_v4_moe": "General-purpose reasoning, long-context",
}
def _parse_param_count(s) -> int:
"""'230B' / '8.6B' / '4.2T' → integer parameter count."""
if s is None:
return 0
s = str(s).strip().replace(",", "")
m = re.match(r"^([\d.]+)\s*([KMBT]?)$", s, re.I)
if not m:
return 0
num = float(m.group(1))
unit = (m.group(2) or "").upper()
mult = {"K": 1e3, "M": 1e6, "B": 1e9, "T": 1e12, "": 1.0}[unit]
return int(num * mult)
def _capabilities_for(arch: str, hardware: dict, ctx_len: int, has_reasoning: bool) -> list[str]:
caps = []
if "moe" in (arch or "").lower():
caps.append("moe")
if has_reasoning:
caps.append("reasoning")
if ctx_len and ctx_len >= 100_000:
caps.append("long_context")
if any(hw in (hardware or {}) for hw in ("mi300x", "mi325x", "mi350x", "mi355x")):
caps.append("amd_supported")
return caps
def _fetch_manifest(client: httpx.Client) -> set[str]:
r = client.get(RECIPES_TREE_URL, headers={"Accept": "application/vnd.github+json"}, timeout=15)
r.raise_for_status()
tree = (r.json() or {}).get("tree") or []
out: set[str] = set()
for e in tree:
path = (e or {}).get("path") or ""
if path.startswith("models/") and path.endswith(".yaml"):
body = path[len("models/"):-len(".yaml")]
if "/" in body:
out.add(body)
return out
def _fetch_recipe(client: httpx.Client, repo: str) -> dict | None:
url = RECIPE_RAW_URL.format(repo=repo)
try:
r = client.get(url, timeout=10)
if r.status_code != 200:
return None
return yaml.safe_load(r.text) or {}
except Exception:
return None
def _stamp_from_recipe(entry: dict, recipe: dict) -> bool:
"""Mutate entry with recipe-derived fields. Returns True if anything changed."""
model = recipe.get("model") or {}
meta = recipe.get("meta") or {}
features = recipe.get("features") or {}
changed = False
new_min = (model.get("min_vllm_version") or "").strip()
if new_min and entry.get("min_vllm_version") != new_min:
entry["min_vllm_version"] = new_min
changed = True
if not entry.get("vllm_recipe"):
entry["vllm_recipe"] = True
changed = True
# Hardware support map — useful for filtering "which models run on my AMD box".
hw = meta.get("hardware") or {}
if hw and entry.get("recipe_hardware") != hw:
entry["recipe_hardware"] = {k: str(v) for k, v in hw.items()}
changed = True
# Tool/reasoning parser hints — purely informational at catalog level;
# the live launch command builder still reads them from the recipe API.
if features.get("reasoning") and not entry.get("has_reasoning_parser"):
entry["has_reasoning_parser"] = True
changed = True
if features.get("tool_calling") and not entry.get("has_tool_call_parser"):
entry["has_tool_call_parser"] = True
changed = True
return changed
def _build_new_entry(repo: str, recipe: dict, hf_info=None) -> dict | None:
"""Build a fresh catalog entry from a recipe + (optional) HF model info."""
model = recipe.get("model") or {}
meta = recipe.get("meta") or {}
features = recipe.get("features") or {}
variants = recipe.get("variants") or {}
org, name = repo.split("/", 1)
raw_params = _parse_param_count(model.get("parameter_count"))
active_raw = _parse_param_count(model.get("active_parameters"))
ctx = model.get("context_length") or 0
# Pick the smallest-VRAM variant as the catalog quant — that's what most
# users land on first. NVFP4/MXFP4 typically win this on Blackwell;
# FP8 elsewhere; BF16 baseline only.
pick_quant = None
pick_vram = None
for vk, vv in variants.items():
if not isinstance(vv, dict):
continue
prec = (vv.get("precision") or "").lower()
vram = vv.get("vram_minimum_gb") or 0
quant = _PRECISION_TO_QUANT.get(prec)
if quant and (pick_vram is None or (vram and vram < pick_vram)):
pick_quant = quant
pick_vram = vram or pick_vram
if not pick_quant:
pick_quant = "BF16"
arch = (model.get("architecture") or "").lower()
use_case = _ARCH_USE_CASE.get(arch, "General-purpose chat")
caps = _capabilities_for(arch, meta.get("hardware") or {}, ctx, bool(features.get("reasoning")))
rel_date = ""
downloads = 0
likes = 0
if hf_info is not None:
created = getattr(hf_info, "created_at", None)
if created:
rel_date = created.strftime("%Y-%m-%d")
downloads = int(getattr(hf_info, "downloads", 0) or 0)
likes = int(getattr(hf_info, "likes", 0) or 0)
if not rel_date:
rel_date = str(meta.get("date_updated") or datetime.utcnow().strftime("%Y-%m-%d"))
entry: dict = {
"name": repo,
"provider": org,
"parameter_count": str(model.get("parameter_count") or "?"),
"parameters_raw": raw_params,
"is_moe": "moe" in arch,
"quantization": pick_quant,
"context_length": int(ctx or 0),
"use_case": use_case,
"capabilities": caps,
"pipeline_tag": "text-generation",
"architecture": arch or "unknown",
"hf_downloads": downloads,
"hf_likes": likes,
"release_date": rel_date,
# Recipe-derived bits.
"vllm_recipe": True,
"min_vllm_version": (model.get("min_vllm_version") or "").strip() or None,
"recipe_hardware": {k: str(v) for k, v in (meta.get("hardware") or {}).items()},
"has_reasoning_parser": bool(features.get("reasoning")),
"has_tool_call_parser": bool(features.get("tool_calling")),
}
if active_raw:
entry["active_parameters"] = active_raw
if pick_vram:
# min_vram_gb is what hwfit uses for "does this fit". Recipe states a
# minimum for the chosen variant; round up slightly for KV-cache room.
entry["min_vram_gb"] = float(pick_vram)
entry["min_ram_gb"] = float(round(pick_vram * 0.6, 1))
entry["recommended_ram_gb"] = float(round(pick_vram * 1.2, 1))
# Drop empty / None fields to keep the JSON tidy.
return {k: v for k, v in entry.items() if v not in (None, "", [], {})}
def main():
p = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
p.add_argument("--update-existing", action="store_true", help="Stamp min_vllm_version + vllm_recipe on existing rows.")
p.add_argument("--add-missing", action="store_true", help="Add new rows for recipe models not in the catalog.")
p.add_argument("--limit", type=int, default=0, help="Stop after N recipe fetches.")
p.add_argument("--dry-run", action="store_true", help="Don't write back; just report.")
p.add_argument("--sleep", type=float, default=0.05, help="Seconds between HTTP requests.")
args = p.parse_args()
if not args.update_existing and not args.add_missing:
args.update_existing = args.add_missing = True
with CATALOG_PATH.open(encoding="utf-8") as f:
catalog = json.load(f)
by_name = {m.get("name"): m for m in catalog if m.get("name")}
client = httpx.Client(follow_redirects=True)
print(f"Catalog: {CATALOG_PATH} ({len(catalog)} entries)")
print("Fetching upstream manifest…")
try:
manifest = _fetch_manifest(client)
except Exception as e:
print(f"FATAL: manifest fetch failed: {e}", file=sys.stderr)
sys.exit(2)
print(f"Manifest: {len(manifest)} recipes")
existing = sorted(by_name.keys() & manifest)
missing = sorted(manifest - by_name.keys())
print(f"Match catalog ↔ manifest: existing={len(existing)} missing={len(missing)}")
targets: list[tuple[str, str]] = [] # (repo, action)
if args.update_existing:
targets.extend((r, "update") for r in existing)
if args.add_missing:
targets.extend((r, "add") for r in missing)
if args.limit:
targets = targets[: args.limit]
print(f"Targets: {len(targets)}")
hf_api = HfApi(token=os.environ.get("HF_TOKEN") or None) if HfApi else None
updated = added = skipped = 0
started = time.time()
for n, (repo, action) in enumerate(targets, 1):
recipe = _fetch_recipe(client, repo)
if not recipe:
print(f"[{n}/{len(targets)}] {repo:55} skip (no recipe fetched)")
skipped += 1
time.sleep(args.sleep)
continue
if action == "update":
entry = by_name[repo]
if _stamp_from_recipe(entry, recipe):
updated += 1
print(f"[{n}/{len(targets)}] {repo:55} updated")
else:
print(f"[{n}/{len(targets)}] {repo:55} unchanged")
else: # add
hf_info = None
if hf_api:
try:
hf_info = hf_api.model_info(repo, files_metadata=False)
except HfHubHTTPError as e:
code = getattr(getattr(e, "response", None), "status_code", "?")
print(f" HF {code} for {repo} — building from recipe only", file=sys.stderr)
except Exception as e:
print(f" HF error for {repo}: {e}", file=sys.stderr)
new_entry = _build_new_entry(repo, recipe, hf_info)
if new_entry:
catalog.append(new_entry)
by_name[repo] = new_entry
added += 1
print(f"[{n}/{len(targets)}] {repo:55} added ({new_entry.get('parameter_count','?')}, {new_entry.get('quantization','?')})")
else:
skipped += 1
print(f"[{n}/{len(targets)}] {repo:55} skip (couldn't build entry)")
time.sleep(args.sleep)
elapsed = time.time() - started
print()
print(f"Done in {elapsed:.1f}s — added={added}, updated={updated}, skipped={skipped}")
if args.dry_run:
print("Dry run — no write.")
return
if added or updated:
tmp = CATALOG_PATH.with_suffix(".json.tmp")
with tmp.open("w", encoding="utf-8") as f:
json.dump(catalog, f, indent=1, ensure_ascii=False)
f.write("\n")
tmp.replace(CATALOG_PATH)
print(f"Wrote {CATALOG_PATH} ({len(catalog)} entries)")
else:
print("No changes — catalog untouched.")
if __name__ == "__main__":
main()