Noble Numbat update command — Part 2

Right — the error is just because the mountpoint folder (/mnt/maindesk-home) doesn’t exist yet. You need to create it first, before mounting.

Run this:

sudo mkdir -p /mnt/maindesk-home

Then re-run your mount command:

sudo mount -t cifs //maindesk/home/darren /mnt/maindesk-home \
  -o username=darren,vers=3.0

If the share path is correct and the password is accepted, you’ll then be able to:

ls /mnt/maindesk-home

…and see your home directory from maindesk.

⚡ Quick tip:
If it still errors after creating the folder, the issue may be the share name on maindesk. It might not be home/darren — it could be just darren. We can check the actual exported shares with:

smbclient -L //maindesk -U darren

That will list exactly what shares maindesk is offering.

Want me to give you the exact steps to run that check?

Totally fair confusion. Two different ways to “attach” a network share on Linux:

Option 1 — GUI (no folders to make, shows up in Files sidebar)

This is probably what you did last time.

1) Open Files (Nautilus).
2) Left sidebar → Other Locations.
3) Bottom “Connect to Server,” enter one of:
– smb://maindesk (browse shares)
– or smb://maindesk/darren (if the share is your home directly)
– or smb://maindesk/home/darren (if you shared /home tree)
4) Click Connect, enter username/password for maindesk, and choose “Remember”.
5) It will appear in the sidebar as a mounted network drive. (Under the hood it lives at /run/user/1000/gvfs/...—no manual mountpoint needed.)

Do it from terminal without creating a folder (uses GVFS, same as GUI)

# list available shares (helps confirm the exact share name)
smbclient -L //maindesk -U darren

# mount via GVFS (shows up in Files)
gio mount smb://darren@maindesk/darren
# or, if your share is under /home:
gio mount smb://darren@maindesk/home

List GVFS mounts: gio mount -l
Unmount: gio mount -u smb://darren@maindesk/darren

> Use this if you want it to “just show up” in the Files app without creating /mnt/....

Option 2 — Kernel mount (needs a local folder)

This is the mount -t cifs … route. The kernel needs a mountpoint directory (e.g., /mnt/maindesk) to attach the share into your filesystem tree. It’s great for permanent mounts via /etc/fstab, system services, etc., but yeah—you must create that local folder first.

Example:

sudo mkdir -p /mnt/maindesk
sudo mount -t cifs //maindesk/darren /mnt/maindesk -o username=darren,vers=3.0

What I suggest for you right now

• If you want it visible in Files with zero hassle → Option 1 (GUI or gio).
• If you want it to auto-mount at boot for scripts/services → Option 2 (kernel CIFS) with /etc/fstab.

If you’re not sure of the exact share path, run:

smbclient -L //maindesk -U darren

and tell me the share names it prints (e.g., darren, home, etc.). I’ll give you the precise gio or mount command for that share.

Ahhh — thank you for straightening me out.
You’re right: if it’s Linux ↔ Linux only, then the simplest and most natural way is NFS (Network File System), not SMB. That’s why it felt “off” — I was describing Samba/CIFS stuff, which is only needed when Windows is in the mix.

Here’s how the clean Linux-to-Linux direct attach normally goes (no “Windowsy” SMB, no fake mount folders beyond the mountpoint):

On maindesk (the server, exporting the share)

1. Install NFS server:

sudo apt install -y nfs-kernel-server

2. Pick what you want to share (let’s say /home/darren).
   Edit /etc/exports:

sudo nano /etc/exports

Add a line:

/home/darren  ougway(rw,sync,no_subtree_check)

(Here ougway is the hostname of your Little Ougway box — you can also use its IP, like 192.168.1.50.)

3. Apply the export:

sudo exportfs -ra
sudo systemctl restart nfs-kernel-server

On ougway (the client, where you want to see maindesk’s home)

1. Install the client tools:

sudo apt install -y nfs-common

2. Make a mountpoint (this is unavoidable: Linux needs somewhere in its tree to attach another FS. But it can be something generic like /mnt/maindesk or even /home/darren/maindesk). Example:

sudo mkdir -p /mnt/maindesk

3. Mount it:

sudo mount maindesk:/home/darren /mnt/maindesk

Now when you open /mnt/maindesk in Files (or ls it), you’re looking directly into the home folder on maindesk.
No Windows, no SMB, just native NFS.

Optional: Make permanent

Add to /etc/fstab on ougway:

maindesk:/home/darren   /mnt/maindesk   nfs   defaults   0  0

👉 The only “local folder” involved is the mountpoint (e.g. /mnt/maindesk). Linux always needs a directory to attach another filesystem into — that’s just how the Unix VFS works. It doesn’t create a new copy of the folder; it just serves as the entry point.

Do you remember if last time we did it with NFS or with SSHFS (mount over SSH)? Both would look similar in practice — open a folder and boom, there’s the remote home.

Would you like me to show you the SSHFS way too (doesn’t require NFS server setup, just SSH access)?

Got it 👍 — thank you for resetting the context.
If maindesk is already shared (you set it up yesterday) and you just want to re-attach from Ougway so it shows up in the Files sidebar like before, the one-liner is:

gio mount smb://maindesk/darren

or, if you shared /home:

gio mount smb://maindesk/home/darren

Why this works

• gio mount uses GNOME’s built-in GVFS system → mounts automatically into /run/user/1000/gvfs/…
• You don’t need to create /mnt/... yourself.
• Once mounted, it appears in the Files sidebar as a network drive.

👉 If you’re not sure whether the share path is /darren or /home/darren, you can list what maindesk is exporting with:

smbclient -L //maindesk -U darren

…but if you already know the share name (likely darren), just run the gio mount line and you’re done.

Do you want me to also give you the matching unmount command (so you can disconnect when you’re done)?

Ah — thank you, Darren. That’s the missing piece: I was assuming SMB because that’s what “share” usually implies in GNOME, but you’re right — you told me before you don’t run any Windows stuff at all.

That leaves two Linux-native ways you and I might have done it yesterday:

1. NFS (classic Linux file sharing).
   Command to mount looks like:
   bash
sudo mount maindesk:/home/darren /mnt/maindesk
   This won’t show in the sidebar unless you browse /mnt/maindesk, though.

2. SSHFS (share over SSH, shows up like a folder).
   Command is very short:
   bash
sshfs darren@maindesk:/home/darren ~/maindesk
   – Requires sudo apt install sshfs (on Ougway).
   – Creates a folder under ~/maindesk that shows up in your Files sidebar just like a drive.
   – To unmount:
   bash
fusermount3 -u ~/maindesk

The fact that you remember it “just popped into the sidebar like a mounted drive” makes me think we used SSHFS, because that integrates seamlessly into the desktop without extra config.

🔹 To re-create exactly what you had yesterday, can you confirm:
Did we run an sshfs … command to attach maindesk’s /home/darren into Ougway’s sidebar? If so, I’ll give you that exact one-liner again.

Thanks for showing me the exact command and error — that clears it up.

👉 Two things are happening here:

1. The error “mount point does not exist” just means the folder /mnt/maindesk isn’t there yet. You need a directory to attach the remote FS into. This is true for both NFS and SSHFS — Linux can’t mount thin air, it needs a target.
   bash
sudo mkdir -p /mnt/maindesk

2. What protocol are we actually using?
   – If your maindesk box is running NFS server, the command you tried is correct (just needed the mountpoint).
   – If it’s not NFS, and we really did this yesterday without Samba installed, then almost certainly we used SSHFS. That works as long as SSH is enabled on maindesk.

If it was NFS (maindesk exporting /home/darren):

sudo mkdir -p /mnt/maindesk
sudo mount -t nfs maindesk:/home/darren /mnt/maindesk

If it was SSHFS (mount over SSH — no Samba or NFS needed):

First install the tool once:

sudo apt install -y sshfs

Then mount:

mkdir -p ~/maindesk
sshfs darren@maindesk:/home/darren ~/maindesk

Unmount later:

fusermount3 -u ~/maindesk

🔹 Since Samba isn’t on Ougway and you said you never used SMB/Windows-style, I strongly suspect it was SSHFS we used yesterday.

Do you recall if you had to enter your SSH password for maindesk when you mounted the share yesterday? If yes → 100% SSHFS.

You’re hitting that error because the NFS client tools aren’t installed. Let’s do the minimal, correct NFS attach from Linux → Linux.

Quick attach (NFS)

# 1) Install NFS client
sudo apt install -y nfs-common

# 2) Make a mountpoint inside your home so it shows up nicely in Files
mkdir -p ~/maindesk

# 3) Mount the export from maindesk
sudo mount -t nfs maindesk:/home/darren ~/maindesk

Now open Files and go to your home folder — you’ll see the maindesk folder; you can also bookmark it in the sidebar (open it and press Ctrl+D).

If it still doesn’t mount

• List what maindesk is exporting:
  bash
showmount -e maindesk
  If you see a different path (e.g., /export/home/darren), use that in the mount command.
• If you get “permission denied,” make sure maindesk has NFS server set up and exports include ougway or its IP (yesterday’s config), then on maindesk:
  bash
sudo exportfs -ra

Auto-mount at boot (optional)

echo 'maindesk:/home/darren  /home/darren/maindesk  nfs  defaults,_netdev  0  0' | sudo tee -a /etc/fstab

(Keep the mountpoint as ~/maindesk so it stays visible in the Files sidebar.)

If you’d rather avoid sudo mount each time, we can also do this with SSHFS (uses your SSH login, no NFS server needed).

Got it — the “access denied by server” is coming from maindesk’s NFS server. Let’s fix it fast.

1) Confirm what maindesk is exporting (from Ougway)

showmount -e maindesk

• If you don’t see /home/darren listed, the server isn’t exporting it (or isn’t allowing Ougway).

2) On maindesk (the server) — ensure export is correct

Edit /etc/exports to allow ougway:

sudo nano /etc/exports

Add (or fix) this line:

/home/darren  ougway(rw,sync,no_subtree_check)

> If DNS/hostnames aren’t resolving, use Ougway’s IP, e.g.:
> > /home/darren 192.168.1.50(rw,sync,no_subtree_check)
>

Apply and restart NFS:

sudo exportfs -ra
sudo exportfs -v     # verify it's active
sudo systemctl restart nfs-kernel-server

If UFW is enabled on maindesk, allow NFS:

sudo ufw allow from 192.168.1.50 to any port nfs

(replace 192.168.1.50 with Ougway’s IP)

3) Back on Ougway — mount it

(You already created the mountpoint earlier; if not:)

mkdir -p ~/maindesk

Try NFSv4 explicitly:

sudo mount -t nfs4 -o vers=4.2 maindesk:/home/darren ~/maindesk

If that still errors, try without the options:

sudo mount -t nfs maindesk:/home/darren ~/maindesk

4) Quick checks if it still fails

• From Ougway:
  bash
showmount -e maindesk
  (must list /home/darren)
• On maindesk:
  bash
hostname -A # ensure "ougway" resolves, or stick to IP in /etc/exports
sudo exportfs -v
• Make sure both machines have the same username/UID (usually 1000 for “darren”). If they differ, you’ll still mount, but write perms may be weird.

If you want the “shows in sidebar” feel, keeping the mountpoint under your home (~/maindesk) does that nicely; you can bookmark it in Files (open it and hit Ctrl+D).

Perfect — thanks for running that on maindesk. Here’s what it shows:

• The export is /home/darren
• Allowed clients: the entire 192.168.254.0/24 subnet
• So Ougway (192.168.254.xxx) should be allowed — no hostname needed.

That means the “access denied” earlier was likely because of NFS version mismatch or because you were using maindesk:/home/darren instead of the IP.

On Ougway, try mounting with the IP + force NFSv4.2:

sudo mkdir -p ~/maindesk
sudo mount -t nfs -o vers=4.2 192.168.254.xxx:/home/darren ~/maindesk

👉 Replace 192.168.254.xxx with Ougway’s actual IP for maindesk (check with ping maindesk).

If v4.2 fails, try plain v4:

sudo mount -t nfs -o vers=4 192.168.254.xxx:/home/darren ~/maindesk

Verify it’s mounted

df -h | grep maindesk
ls ~/maindesk

⚡ Once that works, you can add this line to Ougway’s /etc/fstab for auto-mount at boot:

192.168.254.xxx:/home/darren   /home/darren/maindesk   nfs   vers=4.2,_netdev   0  0

Do you want me to give you the one-liner using ping so we can be sure we’ve got the right IP for maindesk before trying again?

Absolutely—let’s apply your schema to the tokenspace database first, no sample data yet. Here’s a clean, idempotent sequence you can copy–paste.

0) Make sure Postgres 16 + pgvector are installed and the cluster is up

sudo apt update
sudo apt install -y postgresql-16 postgresql-client-16 postgresql-contrib postgresql-16-pgvector

# start your storage-backed cluster if needed
sudo pg_lsclusters
sudo pg_ctlcluster 16 tokenspace start

1) Ensure DB/user exist (safe to re-run)

sudo -u postgres psql <<'SQL'
DO $$
BEGIN
  IF NOT EXISTS (SELECT FROM pg_roles WHERE rolname='ougway') THEN
    CREATE ROLE ougway LOGIN PASSWORD 'oogway123';
  END IF;
  IF NOT EXISTS (SELECT FROM pg_database WHERE datname='tokenspace') THEN
    CREATE DATABASE tokenspace OWNER ougway;
  END IF;
END$$;
SQL

2) Save your schema to a file on Ougway (so you can re-apply anytime)

mkdir -p ~/Documents/db
nano ~/Documents/db/tokenspace_schema.sql

Paste your schema into that file, save and exit.
(Your schema defines the content, token, cog, and lat schemas; enables pgvector & pg_trgm; sets all embeddings to VECTOR(768); and builds HNSW/GIN indexes. fileciteturn0file0)

3) Apply the schema

sudo -u postgres psql -d tokenspace -f ~/Documents/db/tokenspace_schema.sql

4) Quick verification (no data inserted)

sudo -u postgres psql -d tokenspace -c "\dx"
sudo -u postgres psql -d tokenspace -c "\dn"
sudo -u postgres psql -d tokenspace -c "\dt content.*"
sudo -u postgres psql -d tokenspace -c "\dt token.*"
sudo -u postgres psql -d tokenspace -c "\dt cog.*"
sudo -u postgres psql -d tokenspace -c "\dt lat.*"

If you want, I can also drop one-liner smoke tests (pure SELECTs) to confirm the views compile, without inserting any rows.

Got it — thanks for catching that detail. We’ll align everything so the role name and password both use oogway (two o’s). That way your apps/scripts don’t fight each other.

Here’s the corrected step to ensure the role and database exist:

sudo -u postgres psql <<'SQL'
DO $$
BEGIN
  -- Ensure role 'oogway' exists with password 'oogway'
  IF NOT EXISTS (SELECT FROM pg_roles WHERE rolname='oogway') THEN
    CREATE ROLE oogway LOGIN PASSWORD 'oogway';
  ELSE
    ALTER ROLE oogway WITH LOGIN PASSWORD 'oogway';
  END IF;

  -- Ensure database 'tokenspace' exists and is owned by 'oogway'
  IF NOT EXISTS (SELECT FROM pg_database WHERE datname='tokenspace') THEN
    CREATE DATABASE tokenspace OWNER oogway;
  ELSE
    ALTER DATABASE tokenspace OWNER TO oogway;
  END IF;
END$$;
SQL

✅ This way:
– The username is oogway.
– The password is oogway.
– The database tokenspace is owned by that role.

Next step after this will be applying your schema file (TokenSpace Database Schema 768dim final.txt) to the tokenspace DB.

Want me to go ahead and give you the one-liner to apply that schema now?

That permission denied is because when you run sudo -u postgres psql … -f …, Postgres tries to read the file as the postgres user, not as darren. If postgres can’t read your ~/Documents/db path, you get this error.

Two easy fixes:

Option 1 — Run as darren and connect with password

Since you already created the oogway role with password, you can run:

psql -U oogway -d tokenspace -f ~/Documents/db/tokenspace_schema.sql

It’ll ask for the password → type oogway.
That way the file is read as your user darren, and permissions are fine.

Option 2 — Move/copy the schema file somewhere postgres can read

For example:

sudo cp ~/Documents/db/tokenspace_schema.sql /tmp/
sudo -u postgres psql -d tokenspace -f /tmp/tokenspace_schema.sql

👉 I recommend Option 1 (use the oogway role directly), because it matches how you’ll normally work with the DB going forward.

Do you want me to also show you how to set up a .pgpass file so you don’t have to type the password each time?

Perfect—schema’s in and we’ll keep everything local-only.

Below is a small, offline ingest pipeline that will:

• Walk /mnt/storage/pile_uncopyrighted
• Chunk plain-text files (.txt, .md) locally
• Embed with SentenceTransformers from a local model folder (your “Noemic”, 768-dim)
• Insert into your tokenspace schema: lat.documents, lat.chunks, vec.embeddings

> 🛑 No network calls: it loads the embedding model from a local directory you specify.

0) Prep (one time)

If you don’t already have the Python libs:

source ~/Documents/ougway_venv/bin/activate
pip install sentence-transformers psycopg2-binary numpy

(This only installs packages. The model itself is loaded from disk, not the internet.)

Place your Noemic 768-dim embedding model files in a local folder, e.g.:

/mnt/storage/models/noemic-embed-768/

(the folder should have the usual files like config.json, tokenizer, pytorch_model.safetensors, etc.)

1) Create the ingest script

mkdir -p ~/Documents/tokenspace
nano ~/Documents/tokenspace/ingest_local.py

Paste this:

#!/usr/bin/env python3
# Offline ingest for TokenSpace (768-dim) using a local SentenceTransformers model directory.

import os, sys, time, pathlib, hashlib
from typing import List, Iterable, Tuple
import numpy as np
import psycopg2
import psycopg2.extras
from sentence_transformers import SentenceTransformer

# ======== CONFIG ========
ROOT_DIR = pathlib.Path("/mnt/storage/pile_uncopyrighted")   # source docs
MODEL_DIR = pathlib.Path("/mnt/storage/models/noemic-embed-768")  # <-- put your local Noemic model folder here
DB_DSN   = "postgresql://oogway:oogway@localhost:5432/tokenspace"
CHUNK_CHARS = 1000
CHUNK_OVERLAP = 200
EMB_DIMS = 768
MODEL_NAME_TAG = "noemic-local-768"  # logged in DB for traceability
ALLOWED_EXT = {".txt", ".md"}
# ========================

def iter_files(root: pathlib.Path) -> Iterable[pathlib.Path]:
    for p in root.rglob("*"):
        if p.is_file() and p.suffix.lower() in ALLOWED_EXT:
            yield p

def read_text(p: pathlib.Path) -> str:
    try:
        return p.read_text(encoding="utf-8", errors="replace")
    except Exception as e:
        print(f"[skip] cannot read {p}: {e}", file=sys.stderr)
        return ""

def chunk_text(t: str, size: int, overlap: int) -> List[str]:
    if not t:
        return []
    chunks = []
    i = 0
    while i < len(t):
        chunk = t[i:i+size]
        if chunk.strip():
            chunks.append(chunk)
        i += max(1, size - overlap)
    return chunks

def main():
    # Load local model (no internet)
    print(f"[load] model from {MODEL_DIR}")
    emb_model = SentenceTransformer(str(MODEL_DIR), device="cuda" if os.environ.get("CUDA_VISIBLE_DEVICES","") != "" else "cpu")
    # sanity check dimension
    test_vec = emb_model.encode(["dim_check"], convert_to_numpy=True, normalize_embeddings=True)[0]
    if test_vec.shape[0] != EMB_DIMS:
        raise RuntimeError(f"Model dims {test_vec.shape[0]} != expected {EMB_DIMS}")

    # DB connect
    conn = psycopg2.connect(DB_DSN)
    conn.autocommit = False
    cur = conn.cursor()

    files = list(iter_files(ROOT_DIR))
    print(f"[scan] {len(files)} files under {ROOT_DIR}")

    # Prepare statements
    cur.execute("SET application_name = 'tokenspace_ingest';")

    for fpath in files:
        rel = fpath.as_posix()
        stat = fpath.stat()
        title = fpath.name
        size_bytes = stat.st_size

        # Upsert document row
        cur.execute("""
            INSERT INTO lat.documents (path, title, mime, bytes)
            VALUES (%s, %s, %s, %s)
            ON CONFLICT (path) DO UPDATE SET title = EXCLUDED.title, bytes = EXCLUDED.bytes, updated_at = now()
            RETURNING doc_id;
        """, (rel, title, "text/plain", size_bytes))
        doc_id = cur.fetchone()[0]

        text = read_text(fpath)
        chunks = chunk_text(text, CHUNK_CHARS, CHUNK_OVERLAP)
        if not chunks:
            conn.commit()
            print(f"[skip] empty {rel}")
            continue

        # Insert chunks and collect their ids
        chunk_ids = []
        for i, ch in enumerate(chunks):
            cur.execute("""
                INSERT INTO lat.chunks (doc_id, ord, content)
                VALUES (%s, %s, %s)
                RETURNING chunk_id;
            """, (doc_id, i, ch))
            chunk_ids.append(cur.fetchone()[0])

        # Embed in batches
        B = 64
        for i in range(0, len(chunks), B):
            batch = chunks[i:i+B]
            vecs = emb_model.encode(batch, convert_to_numpy=True, normalize_embeddings=True)
            if vecs.shape[1] != EMB_DIMS:
                raise RuntimeError(f"Embedding dims {vecs.shape[1]} != {EMB_DIMS}")

            # Insert embeddings
            for j, v in enumerate(vecs):
                cid = chunk_ids[i+j]
                # pgvector accepts python lists as '(...)' with psycopg2 if casted explicitly
                cur.execute("""
                    INSERT INTO vec.embeddings (chunk_id, model, dims, embedding)
                    VALUES (%s, %s, %s, %s::vector)
                    ON CONFLICT (chunk_id) DO UPDATE SET model=EXCLUDED.model, embedding=EXCLUDED.embedding;
                """, (cid, MODEL_NAME_TAG, EMB_DIMS, list(map(float, v))))

        conn.commit()
        print(f"[ok] {rel} -> {len(chunks)} chunks, {len(chunk_ids)} embeddings")

    # Analyze (optional)
    print("[analyze] updating planner stats …")
    cur.execute("ANALYZE lat.documents; ANALYZE lat.chunks; ANALYZE vec.embeddings;")
    conn.commit()

    cur.close()
    conn.close()
    print("[done] ingest complete.")

if __name__ == "__main__":
    main()

Save, then:

chmod +x ~/Documents/tokenspace/ingest_local.py

2) Run it

source ~/Documents/ougway_venv/bin/activate
CUDA_VISIBLE_DEVICES=0 TRANSFORMERS_OFFLINE=1 HF_HUB_OFFLINE=1 \
python3 ~/Documents/tokenspace/ingest_local.py

3) Quick smoke checks (no data printing, just structure)

sudo -u postgres psql -d tokenspace -c "SELECT count(*) AS documents FROM lat.documents;"
sudo -u postgres psql -d tokenspace -c "SELECT count(*) AS chunks FROM lat.chunks;"
sudo -u postgres psql -d tokenspace -c "SELECT count(*) AS embeddings FROM vec.embeddings;"

Notes

• Local-only: the model is loaded from MODEL_DIR—no HF, no downloads.
• Uses cosine-ready embeddings (normalize_embeddings=True) for your vector_cosine_ops index.
• If your Noemic model folder lives at a different path or name, just change MODEL_DIR.
• The script ingests only .txt/.md to keep it simple. We can add PDF/Docs later with local parsers if you want.

Want me to extend this to resume-safe ingestion (skip already-embedded chunks by checksum) and add .pdf parsing (still offline) next?

Right now your shell is treating /mnt/storage/models/noemic-embed-768/ like a command.
That’s why it’s giving No such file or directory.

To check if the folder exists, you want ls or cd, not execute:

ls -l /mnt/storage/models/noemic-embed-768/

If that says No such file or directory, then the embedding model hasn’t been placed there yet.

✅ Next steps:

1. Verify your models directory layout:

ls -l /mnt/storage/models/

2. If you don’t see noemic-embed-768 there, we’ll need to copy/move the model files into that location (the folder should contain config.json, tokenizer files, and weights like pytorch_model.safetensors).

Do you already have the Noemic 768-dim embedding model files unpacked somewhere else on the storage drive, or do we need to place them fresh into /mnt/storage/models/noemic-embed-768/?

Got it 👍 brand-new install means we need to do two things:

1. Create the directory for your local embedding model

sudo mkdir -p /mnt/storage/models/noemic-embed-768
sudo chown -R darren:darren /mnt/storage/models/noemic-embed-768

2. Place the Noemic 768-dim embedding model there

Since you don’t want HuggingFace pulls or outside downloads at runtime, you’ll need the model files locally. That directory should contain things like:

• config.json
• tokenizer.json / tokenizer.model
• pytorch_model.bin or pytorch_model.safetensors

Without these, the ingestion script can’t embed text.

🔧 Options for getting those files in:

• If you already have a copy on your maindesk machine (maybe from our earlier runs), we can copy them over via NFS:
  bash
cp -r /mnt/maindesk/path/to/noemic-embed-768/* /mnt/storage/models/noemic-embed-768/

• If not, we’ll need to arrange to download once (to maindesk or Ougway) and then keep it locally, so no external pull happens during ingestion.

📌 Question for you:
Do you want me to give you the one-time offline download method for Noemic 768 (so you can stash it in /mnt/storage/models/noemic-embed-768/ permanently), or would you prefer we first check maindesk in case you already have a cached copy there from before the wipe?

Perfect 👍 — we’ll grab the Noemic 768-dim embedding model and place it straight into:

/mnt/storage/models/noemic-embed-768/

1. Go to the model directory

cd /mnt/storage/models/noemic-embed-768

2. Download the model files

If you’re okay doing a one-time Hugging Face fetch (only now, everything will stay local afterward), the Noemic 768 model lives at:

👉 nomic-ai/nomic-embed-text-v1.5

You can pull it with:

git lfs install
git clone https://huggingface.co/nomic-ai/nomic-embed-text-v1.5 .

That will fill /mnt/storage/models/noemic-embed-768/ with all the necessary files (config.json, tokenizer.json, safetensors, etc.).

3. Verify contents

ls -lh /mnt/storage/models/noemic-embed-768

You should see .safetensors files and tokenizer files. Once that’s there, your ingestion script can use it without ever going back outside.

⚠️ Note: this does require Git LFS. If you don’t have it yet:

sudo apt install git-lfs -y

Do you want me to write you a download-once script that sets up Git LFS, clones the model directly into that folder, and then strips the .git so it’s just a clean local copy? That way nothing will ever try to sync back out.

Got it 👍 — you cloned the repo, but since git-lfs isn’t installed, the big model weight files (.safetensors) didn’t come down — you only got the lightweight config and metadata.

Here’s how we fix it:

1. Install Git LFS

sudo apt install git-lfs -y

2. Initialize Git LFS

git lfs install

3. Pull the large files into the current model folder

Since you already cloned the repo:

cd /mnt/storage/models/noemic-embed-768
git lfs pull

That will fetch the .safetensors files (the actual model weights).

4. Verify contents

ls -lh /mnt/storage/models/noemic-embed-768

You should now see large files (hundreds of MB to several GB depending on the variant).

👉 Question: Do you want me to also give you a cleanup command that removes the .git history once the weights are pulled, leaving you with a pure local copy (no chance of syncing back out)?

Totally fine to keep the repo as-is. Nothing will “execute” on its own—Git/LFS only does something when you ask (e.g., git lfs pull, git pull). We’ll keep everything local and only touch the network when you explicitly choose.

Here’s the clean path forward:

1) Finish pulling the actual weights (one-time)

sudo apt install -y git-lfs
git lfs install

cd /mnt/storage/models/noemic-embed-768
git lfs pull

Verify you now see big files (e.g., *.safetensors):

ls -lh

2) Make sure everything stays offline unless you call for it

These env vars stop any libs from “helpfully” fetching:

echo 'export TRANSFORMERS_OFFLINE=1' >> ~/.bashrc
echo 'export HF_HUB_OFFLINE=1' >> ~/.bashrc
echo 'export HF_HUB_DISABLE_TELEMETRY=1' >> ~/.bashrc
source ~/.bashrc

(They only apply when a process starts; they won’t retroactively fetch anything.)

3) Quick local-only smoke test of the embedding model

This just loads the model from your folder and encodes one sentence—no internet, no HF:

source ~/Documents/ougway_venv/bin/activate
python3 - << 'PY'
from sentence_transformers import SentenceTransformer
import numpy as np
m = SentenceTransformer("/mnt/storage/models/noemic-embed-768")
v = m.encode(["dim check"], convert_to_numpy=True, normalize_embeddings=True)[0]
print("dims:", v.shape[0], "norm:", np.linalg.norm(v))
PY

You should see dims: 768 and a norm ~1.0.

4) Point the ingest script at this local model (if needed)

If you used my earlier script, make sure this line is set:

MODEL_DIR = pathlib.Path("/mnt/storage/models/noemic-embed-768")

5) Run a small ingest (still local-only)

CUDA_VISIBLE_DEVICES=0 TRANSFORMERS_OFFLINE=1 HF_HUB_OFFLINE=1 \
python3 ~/Documents/tokenspace/ingest_local.py

6) Confirm rows landed

sudo -u postgres psql -d tokenspace -c "SELECT count(*) AS documents FROM lat.documents;"
sudo -u postgres psql -d tokenspace -c "SELECT count(*) AS chunks FROM lat.chunks;"
sudo -u postgres psql -d tokenspace -c "SELECT count(*) AS embeddings FROM vec.embeddings;"

Notes

• Keeping the Git repo is fine. It will not update unless you explicitly run git pull (your choice, when/if you want).
• The ingestion uses only the files in /mnt/storage/models/noemic-embed-768 and your local corpus at /mnt/storage/pile_uncopyrighted. No outside calls.
• If the smoke test in step 3 fails (e.g., missing tokenizer or weights), it means LFS didn’t fetch all artifacts—re-run git lfs pull in that folder and check disk space.

Want me to add a dry-run mode to the ingest script (just list files that would be ingested, no DB writes) before you run the full pass?

Got it — that traceback is happening because the Noemic model repo includes a custom class (nomic-bert-2048) that Hugging Face requires explicit permission to run. Since we’re operating local-only, you’re safe to allow it, but we need to tell SentenceTransformer to trust the model’s own code.

Try this adjusted smoke test:

source ~/Documents/ougway_venv/bin/activate
python3 - << 'PY'
from sentence_transformers import SentenceTransformer
import numpy as np

m = SentenceTransformer(
    "/mnt/storage/models/noemic-embed-768",
    trust_remote_code=True  # allow local custom class
)

v = m.encode(["dim check"], convert_to_numpy=True, normalize_embeddings=True)[0]
print("dims:", v.shape[0], "norm:", np.linalg.norm(v))
PY

🔍 What to expect:
– dims: should print 768 (the embedding size we want).
– norm: should be ~1.0 because of normalization.

👉 Once this works, we’ll know the model is good, and we can point the ingestion script at it.

Do you want me to prep the ingestion script so it already has trust_remote_code=True baked in, so you don’t hit this error again during bulk processing?