It’s probably not hung. It’s almost certainly slogging through a very large metadata-upsert pass with no intermediate logging.

Why I think that:

• The script logged existing chunks for doc_id=2: 40974. fileciteturn1file0L1-L4
• After that, it reads the file, rechunks it, and then does a CHUNK_UPSERT_SQL once per chunk in a plain Python loop. There is no progress print inside that loop. fileciteturn1file2L45-L57
• Only after finishing all those upserts does it log either “skipping re-embed” or the final [ok ...] line. fileciteturn1file0L20-L24 fileciteturn1file0L32-L48

So if that first document really maps to ~40,974 chunks, the script can appear frozen while it does tens of thousands of row updates one by one.

The important detail is this line in the code:

• It skips re-embedding if chunks already exist.
• It does not skip the chunk metadata upserts. fileciteturn1file0L20-L24 fileciteturn1file2L51-L57

That means the flow is effectively:

1. find doc
2. count existing chunks
3. read file
4. rechunk file
5. upsert every chunk row again, one by one
6. then maybe skip embedding
7. commit
8. finally log completion

So yes — “it already did some and now checking gets messed up” is close. It’s resuming, but the resume logic is only partial. It avoids recomputing embeddings, yet still reprocesses chunk metadata for every chunk.

What to do right now

First, confirm it is actively working rather than dead:

tail -f ~/Documents/tokenspace/ingest.log

In another terminal, watch Postgres activity:

ps aux | grep ingest_pile_v2
ps aux | grep postgres

And optionally check whether chunk count is moving:

psql -h /var/run/postgresql -p 5432 -d tokenspace -c "SELECT COUNT(*) FROM content.chunks;"

If that count is stable and the process is burning CPU a bit, it is probably still walking the big upsert loop.

The simplest practical move is to patch the script so that if a doc already has chunks and FORCE_REEMBED=0, it skips the whole file immediately instead of re-upserting all metadata again.

The change is this block, right after pre_existing_chunks is logged:

# check if chunks already exist for this doc
cur.execute("SELECT COUNT(*) FROM content.chunks WHERE doc_id = %s;", (doc_id,))
pre_existing_chunks = cur.fetchone()[0]
log(f"[file {idx}] existing chunks for doc_id={doc_id}: {pre_existing_chunks}")

if pre_existing_chunks > 0 and not FORCE_REEMBED:
    log(f"[file {idx}] skipping file entirely (chunks already exist and FORCE_REEMBED=0)")
    conn.commit()
    continue

That would make resume behavior actually fast.

If you want to try without editing the main script yet, a quick diagnostic is to test with a tiny subset folder, but since you’re resuming, the better answer is to fix the skip logic.

There’s one more possibility: chunk_0000.txt may itself be a very large file, and 40,974 chunks for one doc is plausible with this chunker. The script chunks text into ~1500-character windows with overlap, which can explode row count on a giant source file. fileciteturn1file3L14-L18 fileciteturn1file4L22-L36

So the diagnosis is:

• database is now reachable
• model is loading
• corpus path is correct
• the script is likely stalling on a huge per-chunk upsert loop during resume, not on Ollama or the DB startup anymore. fileciteturn1file2L14-L23 fileciteturn1file2L51-L57

Use this exact command to see whether that first file is enormous:

wc -c /mnt/storage/pile_uncopyrighted/chunk_0000.txt

And if you want, paste the result plus the current tail of ~/Documents/tokenspace/ingest.log, and I’ll give you the exact patched version of ingest_pile_v2.py.

That matches what the script is actually doing.

It has partial resume, not true checkpoint resume.

What it currently seems to do is:

• rescan all files
• for each file, look up the document record
• count existing chunks
• still walk the file/chunk logic again
• avoid some embedding work if chunks already exist
• but not cleanly skip to “next unfinished file”

So your memory of the intended behavior makes sense, but this script is not really doing that cleanly.

Letting it run is a good call for now. That will answer the immediate practical question: does it eventually move past chunk_0000.txt and continue, or is it effectively unusable in its current resume mode?

What I’d watch for is just two signs:

1. whether it eventually prints an [ok ...] or skipping re-embed style message for that first file
2. whether it starts logging file 2/15325

If it does, then it is slow but functional.
If it sits there forever, then the restart path needs surgery before it is worth using.

And yes, later the changes you probably want are:

• a real progress ledger for completed files
• immediate skip of files already fully ingested
• optional --start-at or --resume-from-file
• better progress output during large files
• maybe batched SQL writes instead of per-chunk row handling

For now, you’re doing the right thing: observe first, patch second. When you’re ready, we can turn this into a proper resumable ingestion pipeline instead of this half-memory creature.

That is the right direction.

What you want is really two separate end states:

1. Reliable manual recovery
A single known-good startup order, so you can bring the whole stack up without guessing.

2. Controlled auto-start
The machine boots, the right services come up, and ingestion can run automatically only when conditions are right.

For now, letting ingestion run is the cleanest way to learn whether the current script is merely slow or actually broken on resume.

Once you’re ready to tighten it up, I’d structure it like this:

Boot order you’ll want nailed down

1. storage mount available
2. PostgreSQL starts
3. any vector/db dependencies confirmed
4. Python venv and env vars available
5. ingestion starts only if enabled
6. Ollama and any retrieval layer start separately

That separation matters, because ingestion is a batch workload, while Ollama is a service workload. You do not really want them tangled together at boot unless you deliberately choose that.

Best long-term setup

Have three little startup layers:

• a system service for PostgreSQL
• a system or user service for Ollama
• a separate ingestion launcher that can be turned on or off

That way:
– the database always comes up
– Ollama always comes up if you want
– ingestion only runs when the machine is idle enough, or only when you enable it

What I would build next, once you’re ready

A small set of files:

• check_ougway_stack.sh
  Verifies mount, DB, model path, corpus path, GPU, and venv
• start_ingest.sh
  Exports the right vars and launches ingestion
• start_ollama.sh
  Starts Ollama cleanly
• optionally a systemd service for ingestion, but only after the script is fixed

Why not auto-run ingestion immediately at boot

Because right now you still do not know:

• whether resume is truly safe
• how much RAM/VRAM/CPU it eats over time
• whether it interferes with anything else you want that box doing

So the smart path is:

Phase 1: observe this current run
Phase 2: patch resume logic
Phase 3: create one-command startup scripts
Phase 4: move selected parts into boot-time services

What you’re really aiming for

A machine where, after boot, this is already true:

• storage mounted
• Postgres online
• Ollama ready
• model paths valid
• ingestion can be started with one command, or auto-started if desired

That is very doable.

And yes, once the startup order is stable, we can wire it into boot so the machine becomes more like an appliance than a project bench.

For now, let this run and see if it advances past file 1. That result tells us whether the next job is optimization or repair.

Yep. What you need is not more memory. You need a re-entry kit.

Make it so Future Darren can sit down cold and recover the whole box in a few minutes.

The clean setup would be:

On the desktop

A folder called something like:

~/Desktop/Ougway Startup

Inside it:

• 00_README_FIRST.txt
• 01_check_stack.sh
• 02_start_database.sh
• 03_start_ollama.sh
• 04_start_ingestion.sh
• 05_status_check.sh

That gives you both:
– a human-readable recovery path
– clickable or runnable helpers

What goes in 00_README_FIRST.txt

Very short, very blunt:

• storage must be mounted at /mnt/storage
• Postgres must be online
• venv is ~/Documents/ougway_venv
• tokenspace scripts are in ~/Documents/tokenspace
• corpus is /mnt/storage/pile_uncopyrighted
• model is the Nomic snapshot path
• ingestion script is ingest_pile_v2.py
• DB port is whichever one you confirm, likely 5432

Then a dead simple startup order:

1. run 01_check_stack.sh
2. if DB is down, run 02_start_database.sh
3. if Ollama needed, run 03_start_ollama.sh
4. run 04_start_ingestion.sh
5. use 05_status_check.sh to verify everything

Why this helps

Because when your context is fragmented, you do not want to reconstruct architecture. You want a trail of breadcrumbs.

Best next build

Once this current ingestion test tells us what the script actually does on resume, the next thing to make is:

• one plain-English checklist
• one stack check script
• one ingestion launcher
• one status script

That gets you out of “what the hell did I do last time?” mode.

The status script should report

At minimum:

• is /mnt/storage mounted
• is Postgres running
• which port is Postgres using
• does tokenspace DB exist
• is the venv present
• does the model path exist
• does the corpus path exist
• is Ollama running
• is ingestion already running

That way one command tells you the whole machine state.

Important design choice

Do not rely on memory for any path or port again.

Put every important path into either:

• a single env file, or
• the startup scripts themselves

For example:

VENV=~/Documents/ougway_venv
TOKENSCRIPT=~/Documents/tokenspace/ingest_pile_v2.py
ROOT_DIR=/mnt/storage/pile_uncopyrighted
MODEL_DIR=/mnt/storage/hf-cache/hub/models--nomic-ai--nomic-embed-text-v1.5/snapshots/e5cf08aadaa33385f5990def41f7a23405aec398
DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5432'

Then every helper script sources the same values.

The right order from here

Let the current run prove what it does.
After that, we build the re-entry kit.
Then, once that works, we decide what should auto-start at boot and what should remain manual.

That is the sane path.

When you’re ready, I’d make you the full set of scripts and the README in one shot.

That is normal, not failure.

You did leave breadcrumbs. They were just tied to a moving system, so the breadcrumbs aged.

What you need now is not “be more scientific.” What you need is a living startup pack that is easy to update when paths or filenames change.

Best form for that is:

• one master config file
• a few small launcher scripts
• one plain-English desktop note

So instead of hardcoding everything in five places, you keep the moving parts in one file.

For example, later we should make something like:

~/Documents/ougway_config.env

with lines like:

VENV=/home/darren/Documents/ougway_venv
TOKENSPACE_DIR=/home/darren/Documents/tokenspace
INGEST_SCRIPT=/home/darren/Documents/tokenspace/ingest_pile_v2.py
HF_HOME=/mnt/storage/hf-cache
MODEL_DIR=/mnt/storage/hf-cache/hub/models--nomic-ai--nomic-embed-text-v1.5/snapshots/e5cf08aadaa33385f5990def41f7a23405aec398
ROOT_DIR=/mnt/storage/pile_uncopyrighted
DB_DSN=postgresql:///tokenspace?host=/var/run/postgresql&port=5432

Then every desktop helper script just loads that one file.

That way, when something changes, you update one place instead of chasing old notes.

Your desktop note can then stay simple:

1. start database
2. run stack check
3. start ingestion
4. start ollama if needed

And the scripts do the real work.

So no, this is not “you’re not much of a scientist.” This is just what happens when a hand-built system grows faster than its documentation.

Let this run for now. After that, the next useful step is to turn your current scattered hints into one single source of truth.

That’s actually the right instinct, Darren — but the trick is to document in a way that future-you can use in 30 seconds, not in a way that becomes another pile of notes. The goal isn’t more documentation, it’s operational documentation.

Think of it like leaving a cockpit checklist for the machine.

Here’s a structure that works very well for systems like the one you’re building.

---

1. One “Single Source of Truth” File

Create one file that contains all critical paths and settings.

Example:

~/Documents/ougway_system_config.md

Inside:

OUGWAY SYSTEM CONFIG
====================

Virtual Environment
-------------------
/home/darren/Documents/ougway_venv

TokenSpace Scripts
------------------
/home/darren/Documents/tokenspace

Ingestion Script
----------------
ingest_pile_v2.py

Corpus Location
---------------
/mnt/storage/pile_uncopyrighted

Embedding Model
---------------
/mnt/storage/hf-cache/hub/models--nomic-ai--nomic-embed-text-v1.5/snapshots/e5cf08aadaa33385f5990def41f7a23405aec398

Database
--------
Name: tokenspace
Port: 5432
Socket: /var/run/postgresql

Startup Order
-------------
1. Start PostgreSQL
2. Activate venv
3. Set environment variables
4. Start ingestion
5. Start Ollama if needed

This is not a tutorial.
It’s just the facts.

---

2. A Simple “Cold Start” Checklist

This is the file you click when your brain is blank.

Example:

~/Desktop/Ougway Startup Checklist.txt

OUGWAY COLD START
=================

1. Start PostgreSQL
   sudo systemctl start postgresql

2. Check database
   pg_lsclusters

3. Activate environment
   source ~/Documents/ougway_venv/bin/activate

4. Run ingestion
   ~/Documents/start_ougway_ingest.sh

5. Verify progress
   tail -f ingest.log

This lets you recover the system even months later.

---

3. One Launcher Script

Instead of remembering commands, you run one script.

Example:

~/Documents/start_ougway_ingest.sh

#!/bin/bash

source ~/Documents/ougway_venv/bin/activate

export HF_HOME=/mnt/storage/hf-cache
export TRANSFORMERS_OFFLINE=1
export HF_HUB_OFFLINE=1
export HF_HUB_DISABLE_TELEMETRY=1

export DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5432'
export ROOT_DIR='/mnt/storage/pile_uncopyrighted'
export MODEL_DIR='/mnt/storage/hf-cache/hub/models--nomic-ai--nomic-embed-text-v1.5/snapshots/e5cf08aadaa33385f5990def41f7a23405aec398'

CUDA_VISIBLE_DEVICES=0 python3 ~/Documents/tokenspace/ingest_pile_v2.py

Make it executable:

chmod +x ~/Documents/start_ougway_ingest.sh

Then future you runs:

~/Documents/start_ougway_ingest.sh

Done.

---

4. One Status Script (Optional but Powerful)

~/Documents/check_ougway_stack.sh

This can report:

• storage mounted
• postgres running
• model exists
• corpus exists
• ingestion running

One command tells you the whole machine state.

---

5. The Philosophy That Keeps Systems Maintainable

Never rely on remembering:

• paths
• ports
• filenames
• startup order

Always assume future-you remembers nothing.

Your documentation should be written for the version of you who just woke up from a two-month gap and says:

> “What the hell was I doing?”

If that version of you can restart the system in five minutes, the documentation is perfect.

---

When your ingestion finishes (or we see what it does), we can also tighten the system by:

• fixing the resume logic
• adding progress checkpoints
• optionally letting ingestion auto-run when the machine boots

But for now, what you’re talking about—organized documentation for operations—is exactly the right next step.