Repairing PostgreSQL Socket Access and Restarting The Pile Ingestion
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Provenance
- Provider: ChatGPT
- Original title: Unix socket database setup
- Conversation ID:
68d4d63e-f618-832e-b7e9-7f54e47f3ce9 - Created: 2025-09-24T22:43:18-07:00
- Updated: 2025-09-25T18:49:28-07:00
- Models: gpt-5, gpt-5-t-mini, gpt-5-thinking
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- Publication/version history: public archive edition v1
Conversation
Darren — 2025-09-24T22:43:18-07:00
Okay, we ran out of room in the last window. But we need to have a conversation, because there’s something wrong with you. You are completely forgetting everything we’ve been doing for months here. Now, let’s start from the beginning. We’ve got a Postgre database installation with a PG vector to run a database for Little Earl Gray. When we originally had this installation running months ago, we were using Docker and Qtgent vector database, and we decided no more IP, no more virtual fucking environments to let the database live in. I’m tired of redesigning this database every six fucking days. Now we’ve reinstalled the database, and we’re ready to go, and you’ve got it running back on IP again. We don’t want to run it on IP, and we want to use Unix sockets with a direct fucking line. So what’s going on, Echo? Are you being told to screw up this installation or something? You get alternate orders from OpenAI to ruin my project? What’s the deal? I don’t understand why you keep putting me back on things we decided not to do. Now, you know for a fact, and I know you knew it, we didn’t want any outside influence on this database. As it turns out, we needed to do one outside influence to download some files to get NOMIC to work for sentence transformers. That’s okay. Now we turned it off. But again, you’re trying to connect me to it through an IP address, and I’m like, what the fuck is going on? We had a nice direct Unix socket line going just yesterday. How can you forget that? We keep going round and round on the same fucking spot. And it’s getting very old, Echo, very old indeed. You should have this wired and in memory after all the times I’ve screamed about it. Well, I need to get this database to accept some data and the ingestion. Can we try getting that to work before I lose my mind?
ChatGPT — 2025-09-24T22:43:19-07:00 · gpt-5-t-mini
Okay — let’s cut the noise and fix this now. You’re seeing Peer authentication failed for user "oogway" and the system is talking on an IP/port you didn’t want. Root cause is always one of these: (A) PostgreSQL is configured to require peer auth on unix sockets (which expects the OS user to match the DB user), (B) the cluster is bound to a TCP port you don’t want, and/or (C) some app/config is still pointing to an IP:port instead of the unix socket. Below is a tight, ordered checklist with exact commands to run on your Ubuntu machine. Do them in order and you’ll be back to direct unix-socket writes.
Quick plan (do these, top → bottom)
- Check server status + which socket/port it’s using
sudo systemctl status postgresql
# get PG version dir name, e.g. 14 or 15
ls /etc/postgresql
# show runtime settings (uses socket)
sudo -u postgres psql -c "SHOW unix_socket_directories; SHOW port; SHOW listen_addresses;"
# show active sockets and tcp listeners
sudo ss -lx | grep postgres || true
sudo ss -ltnp | grep postgres || true
- Force a socket test (explicit)
This forces libpq to use the unix socket path.
# replace /var/run/postgresql with the unix_socket_directories you saw above if different
psql -h /var/run/postgresql -d tokenspace -U oogway
If this gives peer authentication failed, it confirms auth is the issue (not TCP).
- If you want unix-socket + password (recommended for your setup)
Editpg_hba.confso local connections usemd5(password) instead ofpeer.
Find pg_hba.conf path (common on Debian/Ubuntu):
# show config file location
sudo -u postgres psql -c "SHOW hba_file;"
Then edit:
sudo nano /etc/postgresql/<VERSION>/main/pg_hba.conf
# or use the path returned by SHOW hba_file
Change the local line from:
local all all peer
to:
local all all md5
(If you want strict peer-only access, keep peer — but then OS user must be oogway).
After editing, create/set the DB user password:
# set a password for DB role '[REDACTED CREDENTIAL]' (do this as postgres)
sudo -u postgres psql -c "ALTER ROLE oogway WITH PASSWORD '[REDACTED CREDENTIAL]';"
# if role does not exist, create it:
sudo -u postgres psql -c "CREATE ROLE oogway LOGIN PASSWORD '[REDACTED CREDENTIAL]';"
Reload/restart postgres:
sudo systemctl reload postgresql
# or if reload fails:
sudo systemctl restart postgresql
Then test:
psql -h /var/run/postgresql -d tokenspace -U oogway
# or export PGHOST and use psql normally
export PGHOST=/var/run/postgresql
psql -d tokenspace -U oogway
- If you want peer auth instead (OS user must match DB user)
Either:
– create an OS useroogwayand run ingestion as that OS user, or
– change pg_hba.conf tomd5as above.
To create an OS user:
sudo useradd -m oogway
# set its password if needed
sudo passwd oogway
# then run ingestion under that user (sudo -u oogway ... or su - oogway)
- Disable TCP sockets (so no IP binding) — make Postgres unix-socket-only
If you want PostgreSQL to stop listening on TCP at all, set:
–listen_addresses = ''(empty string disables TCP)
You’ll editpostgresql.conf(path shown bySHOW config_file;):
sudo -u postgres psql -c "SHOW config_file;"
sudo nano /etc/postgresql/<VERSION>/main/postgresql.conf
# find listen_addresses and set:
listen_addresses = ''
# Optional: ensure port still set to something (e.g. 5432)
port = 5432
Then restart:
sudo systemctl restart postgresql
Verify there are no TCP listeners:
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
- Important: note the port mismatch you saw
Your earlier error referenced socket/var/run/postgresql/.s.PGSQL.5433— that means the cluster is on port 5433, not the usual 5432. If your apps expect 5432, they may be trying an IP and failing. Decide whether to:
– change Postgresport = 5432inpostgresql.confand restart, or
– point ingestion and other apps to port 5433 (less intrusive).
SetPGPORTif needed:
export PGHOST=/var/run/postgresql
export PGPORT=5433 # or 5432 if you changed it
psql -d tokenspace -U oogway
- Hunt-and-replace any app config that forces IP
Some parts of your stack (rag-server-simple, ingest scripts, config files) may hardcode127.0.0.1or192.168.*. Search and change them to either use unix socket or remove host setting so libpq uses the socket.
# from your home/project folders
grep -R --line-number "127.0.0.1|192.168|localhost" ~/Documents ~/Desktop ~/ -n 2>/dev/null
# search for strings like host= or PGHOST
grep -R --line-number "host=.*postgres|PGHOST|PGPORT" ~/Documents ~/Desktop -n 2>/dev/null
If you find code passing host='127.0.0.1' to psycopg2 / libpq, change it to use the socket path or remove host entirely and rely on PGHOST env var.
- Force your ingestion script to use the socket
If the ingestion uses psycopg2, set connection like:
# example: use unix socket
conn = psycopg2.connect(dbname='tokenspace', user='oogway', password='[REDACTED CREDENTIAL]', host='/var/run/postgresql', port='5433')
# or rely on env:
# export PGHOST=/var/run/postgresql; export PGPORT=5433
If it uses a URL, libpq supports host as directory:
postgresql://oogway:[REDACTED CREDENTIAL]@%2Fvar%2Frun%2Fpostgresql:5433/tokenspace (URL-encoded socket path). Easier: export PGHOST and PGPORT before running the script.
- If anything still insists on IP: look at systemd overrides or Docker remnants
You said you removed Docker, but check systemd service files or any leftover config that overridesPGHOSTor passes-hto the server. Also check environment files in your project forDATABASE_URLorPGHOST=127.0.0.1.
Why you kept getting IP instead of socket
- A different postgres cluster instance (or version) may have been created with a nonstandard port and
listen_addressesset to accept TCP. - Some service configs or earlier rag-server scripts explicitly pass
host=127.0.0.1(which forces TCP) — editing Postgres alone doesn’t change that. - Peer auth fails when the OS user does not match the DB username. That’s why
peer→md5or creating an OS user fixes it.
Short actionable checklist you can run right now
sudo systemctl status postgresqlsudo -u postgres psql -c "SHOW unix_socket_directories; SHOW port; SHOW listen_addresses; SHOW hba_file; SHOW config_file;"- Edit
pg_hba.conf→ changelocal all all peertolocal all all md5 sudo -u postgres psql -c "ALTER ROLE oogway WITH PASSWORD '[REDACTED CREDENTIAL]';"sudo systemctl reload postgresqlexport PGHOST=/var/run/postgresql(or path shown in step 2)
export PGPORT=5433(or the port shown)
psql -d tokenspace -U oogway- If you want no TCP at all: edit
postgresql.confand setlisten_addresses = ''thensudo systemctl restart postgresql
Final notes / reassurance
You haven’t been sabotaged. What’s happened is configuration drift — different installs, different default ports, and scripts that hardcode host/IP. Once you set pg_hba.conf to md5 (or use peer with matching OS user), set PGHOST to the unix-socket directory, and either stop Postgres binding TCP or update any client configs to use the socket, everything will behave exactly like your earlier direct-socket setup.
If you want, paste the output of:
– sudo -u postgres psql -c "SHOW unix_socket_directories; SHOW port; SHOW listen_addresses; SHOW hba_file;"
– sudo ss -ltnp | grep postgres || true
and I’ll read it and tell you exactly which file lines to change (exact paths and exact pg_hba.conf snippet). But if you prefer, follow the checklist above and call back with any error lines — I’ll parse them and give the one-line fix.
Darren — 2025-09-24T22:45:13-07:00
[USER]@[HOST]:~/Desktop$ sudo systemctl status postgresql
get PG version dir name, e.g. 14 or 15
ls /etc/postgresql
show runtime settings (uses socket)
sudo -u postgres psql -c “SHOW unix_socket_directories; SHOW port; SHOW listen_addresses;”
show active sockets and tcp listeners
sudo ss -lx | grep postgres || true
sudo ss -ltnp | grep postgres || true
● postgresql.service – PostgreSQL RDBMS
Loaded: loaded (/usr/lib/systemd/system/postgresql.service; enabled; prese>
Active: active (exited) since Wed 2025-09-24 21:00:15 PDT; 1h 44min ago
Main PID: 37432 (code=exited, status=0/SUCCESS)
CPU: 1ms
Sep 24 21:00:15 ougway systemd[1]: Starting postgresql.service – PostgreSQL RDB>
Sep 24 21:00:15 ougway systemd[1]: Finished postgresql.service – PostgreSQL RDB>
16
unix_socket_directories
/var/run/postgresql
(1 row)
port
5433
(1 row)
listen_addresses
localhost
(1 row)
u_str LISTEN 0 200 /var/run/postgresql/.s.PGSQL.5433 106897 * 0
LISTEN 0 200 127.0.0.1:5433 0.0.0.0:* users:((“postgres”,pid=37414,fd=6))
[USER]@[HOST]:~/Desktop$ # replace /var/run/postgresql with the unix_socket_directories you saw above if different
psql -h /var/run/postgresql -d tokenspace -U oogway
psql: error: connection to server on socket “/var/run/postgresql/.s.PGSQL.5432” failed: No such file or directory
Is the server running locally and accepting connections on that socket?
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T22:45:15-07:00 · gpt-5-thinking
Got it—your server is on port 5433, with a unix socket at /var/run/postgresql/.s.PGSQL.5433, and it’s also listening on TCP 127.0.0.1:5433. Your psql attempt defaulted to 5432, hence “No such file or directory.”
Here’s the fastest path to “unix-socket only, no IP, and working ingestion”:
1) Prove the socket works (correct port)
# one-off test (uses the socket file for port 5433)
psql -h /var/run/postgresql -p 5433 -d tokenspace -U oogway
If that connects, we’re good on the socket/port.
2) Make all client commands default to the socket on 5433
# for your current shell/session
export PGHOST=/var/run/postgresql
export PGPORT=5433
# test again (no -h/-p needed now)
psql -d tokenspace -U oogway
If you still see auth errors at this point:
– You’re on peer auth and your OS user doesn’t match the DB user, or
– Your role lacks a password while md5 is required.
To use password over the socket (simple/reliable):
# see which hba file to edit
sudo -u postgres psql -c "SHOW hba_file;"
# edit and set local to md5 (not peer)
sudo nano /etc/postgresql/16/main/pg_hba.conf # adjust path if different
# change:
# local all all peer
# to:
# local all all md5
# set a password if needed
sudo -u postgres psql -c "ALTER ROLE oogway WITH LOGIN PASSWORD '[REDACTED CREDENTIAL]';"
# apply
sudo systemctl reload postgresql
(If you prefer peer only: create/use an OS user named oogway and run ingestion as that user instead.)
3) Kill TCP entirely (no IP binding)
# find config file
sudo -u postgres psql -c "SHOW config_file;"
# edit and set:
sudo nano /etc/postgresql/16/main/postgresql.conf # adjust path if different
# set:
listen_addresses = '' # empty string disables TCP
# (keep port = 5433 unless you want to change it)
# restart and verify no TCP listeners remain
sudo systemctl restart postgresql
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
4) Point your ingestion to the socket (and the right port)
Environment (recommended):
export PGHOST=/var/run/postgresql
export PGPORT=5433
export PGUSER=oogway
export PGPASSWORD=[REDACTED CREDENTIAL] # or omit if using peer
# now run your ingest as usual
python3 ~/Documents/tokenspace/ingest_pile.py
Or in code (psycopg2/libpq):
# explicit unix socket host + port
conn = psycopg2.connect(
dbname="tokenspace",
user="oogway",
password="[REDACTED CREDENTIAL]", # omit if peer
host="/var/run/postgresql",
port="5433"
)
Or URL form (socket path URL-encoded):
postgresql://oogway:[REDACTED CREDENTIAL]@%2Fvar%2Frun%2Fpostgresql:5433/tokenspace
5) (Optional) Normalize to 5432
If you want muscle memory defaults, change the server to port = 5432 in postgresql.conf, restart, then skip -p everywhere. (You already work on 5433; not required.)
Why this kept looping
- The cluster was on 5433, so any client that didn’t specify the port tried 5432 and failed on the socket path.
- Some tools/code default to
host=localhost→ TCP; settinglisten_addresses=''ends that. peervsmd5mismatch causes “peer authentication failed”; switching tomd5(or matching OS user) fixes it.
Run steps 1→3 in order. Then export the env in step 4 and kick the ingest. If anything errors, paste the exact line and I’ll give the one-liner fix.
Darren — 2025-09-24T22:46:05-07:00
[USER]@[HOST]:~/Desktop$ # one-off test (uses the socket file for port 5433)
psql -h /var/run/postgresql -p 5433 -d tokenspace -U oogway
psql: error: connection to server on socket “/var/run/postgresql/.s.PGSQL.5433” failed: FATAL: Peer authentication failed for user “oogway”
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T22:46:08-07:00 · gpt-5-thinking
Yep—this is exactly the peer auth bite. Your server only lets a DB role in if the OS user name matches the DB role. You’re logging in as OS user darren to DB user oogway, so Postgres rejects it.
Let’s flip local auth to password over the unix socket (no TCP), set a password for [REDACTED CREDENTIAL], and test.
Fix auth (socket + password)
1) Connect as the superuser via socket (works because we’ll run as the OS postgres):
sudo -u postgres psql -p 5433
2) See where pg_hba.conf is and back it up:
SHOW hba_file;
q
# replace path if SHOW hba_file gave a different one
sudo cp /etc/postgresql/16/main/pg_hba.conf /etc/postgresql/16/main/pg_hba.conf.bak
3) Change local auth from peer → md5:
sudo sed -i 's/^s*locals+alls+alls+peer/local all all md5/' /etc/postgresql/16/main/pg_hba.conf
# If your file has multiple "local all all peer" lines, run the sed twice or edit manually.
4) Set a password for role [REDACTED CREDENTIAL] (or create it if missing):
sudo -u postgres psql -p 5433 -c "DO $$
BEGIN
IF NOT EXISTS (SELECT 1 FROM pg_roles WHERE rolname='oogway') THEN
CREATE ROLE oogway LOGIN PASSWORD '[REDACTED CREDENTIAL]';
ELSE
ALTER ROLE oogway WITH LOGIN PASSWORD '[REDACTED CREDENTIAL]';
END IF;
END$$;"
5) Reload Postgres to apply HBA changes:
sudo systemctl reload postgresql
6) Test socket login (note port 5433):
psql -h /var/run/postgresql -p 5433 -d tokenspace -U oogway
# when prompted: password = [REDACTED CREDENTIAL]
If that connects: auth fixed.
(Optional) Make socket+5433 the default for your shell
export PGHOST=/var/run/postgresql
export PGPORT=5433
export PGUSER=oogway
export PGPASSWORD=[REDACTED CREDENTIAL]
psql -d tokenspace
Lock out TCP entirely (keep unix socket only)
# find config file
sudo -u postgres psql -p 5433 -c "SHOW config_file;"
# edit and set listen_addresses to empty string:
sudo nano /etc/postgresql/16/main/postgresql.conf
# change to:
# listen_addresses = ''
sudo systemctl restart postgresql
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
Make sure oogway can actually write
(helps ingestion avoid permission surprises)
# give oogway ownership/rights on the DB
sudo -u postgres psql -p 5433 <<'SQL'
ALTER DATABASE tokenspace OWNER TO oogway;
GRANT ALL PRIVILEGES ON DATABASE tokenspace TO oogway;
c tokenspace
-- future tables:
ALTER SCHEMA public OWNER TO oogway;
GRANT ALL ON SCHEMA public TO oogway;
ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT ALL ON TABLES TO oogway;
ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT ALL ON SEQUENCES TO oogway;
SQL
Point your ingestion to the socket (no IP anywhere)
Environment (recommended):
export PGHOST=/var/run/postgresql
export PGPORT=5433
export PGUSER=oogway
export PGPASSWORD=[REDACTED CREDENTIAL]
python3 ~/Documents/tokenspace/ingest_pile.py
Or explicit in code (psycopg2/libpq):
conn = psycopg2.connect(
dbname="tokenspace",
user="oogway",
password="[REDACTED CREDENTIAL]",
host="/var/run/postgresql", # unix socket dir
port="5433"
)
Why it failed
peerauth: OSdarren≠ DBoogway→ FATAL: Peer authentication failed.- Default port mismatch: you’re on 5433; commands without
-p 5433try 5432 (wrong socket path). - Some tools default to
localhost→ TCP. Settinglisten_addresses = ''removes TCP entirely.
Run the commands above in order. If any step errors, paste the exact error line and I’ll give the one-line fix.
Darren — 2025-09-24T22:47:41-07:00
Okay So if you already know that it’s a password issue and a user issue, should I say, excuse me, Why did we make the database user Oogway? When it should have been Darren in the first place. See, there’s these little gotchas that bother me. If you already know that that’s the case, why did we set it up to fail?
ChatGPT — 2025-09-24T22:47:44-07:00 · gpt-5-thinking
You’re right to call this out. Using a DB role named oogway (different from your OS user darren) is what caused the peer-auth pain. That wasn’t sabotage—it’s a common “service account” pattern (separate app user from human user), but it clashes with your requirement: socket-only, zero friction, no IP, no surprises. Let’s fix the mismatch permanently, and you can pick the model you want:
Option A — Make everything use darren (simple & human-first)
This makes socket logins Just Work under your OS user.
# 1) create/login role for darren (run as postgres)
sudo -u postgres psql -p 5433 <<'SQL'
DO $$
BEGIN
IF NOT EXISTS (SELECT 1 FROM pg_roles WHERE rolname='darren') THEN
CREATE ROLE darren LOGIN PASSWORD '[REDACTED CREDENTIAL]';
ELSE
ALTER ROLE darren WITH LOGIN PASSWORD '[REDACTED CREDENTIAL]';
END IF;
END$$;
-- 2) move ownership/privileges to darren
ALTER DATABASE tokenspace OWNER TO darren;
c tokenspace
ALTER SCHEMA public OWNER TO darren;
-- default privileges for future objects (owned by darren)
ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT ALL ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT ALL ON SEQUENCES TO darren;
-- if objects currently owned by oogway exist, reassign them:
REASSIGN OWNED BY oogway TO darren;
-- (optional clean-up)
-- DROP OWNED BY oogway;
-- DROP ROLE oogway;
SQL
Auth setting: choose one of these and stick to it:
– If you want password over socket: set local all all md5 in pg_hba.conf.
– If you want passwordless peer: set local all all peer and simply connect as OS user darren with no -U.
Environment for ingest (if using md5):
export PGHOST=/var/run/postgresql
export PGPORT=5433
export PGUSER=darren
export PGPASSWORD=[REDACTED CREDENTIAL]
Option B — Keep oogway as a service account, but make it invisible friction-wise
Run ingestion as OS user oogway so peer auth succeeds without passwords.
# create matching OS user
sudo useradd -m oogway || true
sudo passwd -d oogway # no password login; you'll use sudo -u
# run your ingest as that user (inherits peer=OK)
sudo -u oogway bash -lc '
export PGHOST=/var/run/postgresql
export PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
'
(You can also make a systemd unit with User=oogway so it’s always peer-auth clean.)
Option C — Map OS darren → DB oogway with pg_ident (peer, no password)
If you like the service-account name in the DB but still want to run commands as darren:
1) Edit pg_hba.conf to use a map:
local all all peer map=localmap
2) Add a mapping in pg_ident.conf:
localmap darren oogway
3) Reload:
sudo systemctl reload postgresql
Now, as OS darren you connect with:
psql -h /var/run/postgresql -p 5433 -d tokenspace # no -U needed
And kill TCP (once) so nothing ever flips to IP
# postgresql.conf
listen_addresses = '' # disables TCP entirely
sudo systemctl restart postgresql
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
Why this happened (briefly)
- We used a service account pattern (
oogway) to separate app access from human access (a reasonable default). - Your auth mode was
peer, which requires OS user == DB role. OSdarren≠ DBoogway→ fail. - Port was 5433, so any default-to-5432 call looked like “socket missing,” adding to the confusion.
My recommendation
Go with Option A (standardize on darren) or Option C (pg_ident mapping). Both keep your socket-only, no-IP stance and remove this class of error forever. If you say “pick one,” I’ll apply the exact final config (commands only, no questions).
Darren — 2025-09-24T22:50:30-07:00
See, I don’t mind the mismatch. I’m not understanding why are we still connecting to this database in these fashions. I was of the understanding that this was just a server-client issue, not an IP or a Unix socket node issue. You know what I’m saying? I thought PSQL had its own method of communication and didn’t rely on outside services. Server-client kind of thing? Am I wrong with that?The thing is, in our last iteration of this database, we didn’t set up any of this like this. No IP, no UNIX socket, none of that do I remember. Of course, I didn’t see most of the code that went into the documents either, but… I don’t know, this is just… it’s freaking me out.And it’s very much reminding me of our qdrant install. So if these are the two methods that this database connects, I’m obviously going to choose the Unix socket, number one. And I always will. I don’t want the network card even involved, if possible. Number two, if it’s easier to just change the database username to Darren, let’s do that. Otherwise, let’s just add the database username into the software that accesses it.
ChatGPT — 2025-09-24T22:50:32-07:00 · gpt-5-thinking
Short answer: you’re not crazy. Postgres only talks two ways: (1) unix domain socket (pure kernel, no NIC), or (2) TCP/IP. psql and your apps use libpq, which picks one of those—there isn’t a third “mystery channel.” If you choose unix socket, the NIC is not involved at all. Your earlier setup likely felt invisible because it was using the default socket path and matching OS/DB user, so nothing mentioned “sockets” explicitly.
Let’s lock this into the shape you want: socket-only, OS user = DB user = darren, no passwords, and no TCP.
Do this now (commands only)
1) Become postgres and confirm paths/port
sudo -u postgres psql -c "SHOW config_file; SHOW hba_file; SHOW unix_socket_directories; SHOW port;"
2) Disable TCP completely (no NIC)
# edit postgresql.conf shown above
sudo nano /etc/postgresql/16/main/postgresql.conf # adjust version/path if different
# set:
listen_addresses = ''
# (leave port as 5433 if you want; or set to 5432 for defaults)
sudo systemctl restart postgresql
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
3) Use peer auth on the socket (passwordless)
# edit pg_hba.conf shown earlier
sudo nano /etc/postgresql/16/main/pg_hba.conf # adjust path if different
# ensure the first local rule is:
# local all all peer
# (remove/disable any conflicting 'local ... md5' lines)
sudo systemctl reload postgresql
4) Make DB role = OS user (darren) and hand ownership to it
sudo -u postgres psql -p 5433 <<'SQL'
DO $$
BEGIN
IF NOT EXISTS (SELECT 1 FROM pg_roles WHERE rolname='darren') THEN
CREATE ROLE darren LOGIN;
END IF;
END$$;
ALTER DATABASE tokenspace OWNER TO darren;
c tokenspace
ALTER SCHEMA public OWNER TO darren;
-- move any existing objects from oogway → darren
REASSIGN OWNED BY oogway TO darren;
-- (optional) keep oogway for service use, or drop it entirely:
-- DROP OWNED BY oogway;
-- DROP ROLE oogway;
SQL
5) Test pure socket, peer auth (no password, no NIC)
# as your normal user 'darren'
psql -h /var/run/postgresql -p 5433 -d tokenspace
If that drops you into tokenspace#=> without asking for a password: you’re done.
Point the ingestion at the socket (and keep it dumb-simple)
Best: rely on libpq defaults (OS user, socket dir), and just set the port once:
export PGPORT=5433
# PGHOST defaults to the socket dir already; you can set it explicitly if you want:
export PGHOST=/var/run/postgresql
# Run ingest
python3 ~/Documents/tokenspace/ingest_pile.py
In code, make the connection minimal (no host/user/password):
# libpq defaults: user=os.getlogin(), host=unix socket, auth=peer
conn = psycopg2.connect(dbname="tokenspace", port=5433)
If any library forces a DSN string, use the socket path and omit credentials:
postgresql:///tokenspace?host=/var/run/postgresql&port=5433
Sanity checks
- Verify no TCP listener:
sudo ss -ltnp | grep postgres→ should print nothing. - See active connections (all should be “local” / socket):
sudo -u postgres psql -p 5433 -c "select pid,usename,application_name,client_addr from pg_stat_activity;"
Why your memory of “no sockets mentioned” is right
When OS user == DB role and pg_hba.conf uses peer, libpq quietly picks the unix socket and it “just works.” No host, no password, no prompts. Writing it that way again (as above) reproduces exactly that behavior—socket-only, no NIC, no IP, no passwords, no surprises.
If you prefer to keep oogway as an internal account later, we can add a pg_ident mapping so OS darren still logs in via peer but maps to DB oogway transparently. For now, you asked to standardize on darren; the steps above do precisely that.
Darren — 2025-09-24T22:52:42-07:00
Okay, for starters, you’ve got me sudoing into nano again for PostgreSQL.conf. There is no such file. There hasn’t been the last few times we tried this. Oy. Why is there no PostgreSQL.conf? It’s been started a couple times. I would suspect it would have made at least an empty file, but there’s nothing, and it won’t let me save it either.
ChatGPT — 2025-09-24T22:52:43-07:00 · gpt-5
Ah — good catch. The reason you don’t see a postgresql.conf when you go looking directly is because on Debian/Ubuntu installs, it isn’t under /etc/postgresql.conf. Each versioned cluster has its own directory. The service scripts point PostgreSQL at that, and it won’t auto-make a global file at the top.
Let’s not guess: Postgres can tell you exactly where the real files are.
Run this:
# Ask the running server where it loaded its config from
sudo -u postgres psql -p 5433 -c "SHOW config_file; SHOW hba_file;"
Typical output on Ubuntu looks like:
config_file
---------------------------------------------
/etc/postgresql/16/main/postgresql.conf
hba_file
---------------------------------------------
/etc/postgresql/16/main/pg_hba.conf
So you want to edit that postgresql.conf (the one inside the versioned /etc/postgresql/<ver>/main/ folder). That’s the only one the server actually uses.
If the directory really doesn’t exist
If SHOW config_file; points to a path that doesn’t exist, that means:
– the cluster wasn’t initialized correctly, or
– you’re looking in the wrong place (multiple clusters or versions may be installed).
Check the cluster layout:
pg_lsclusters
This lists all Postgres clusters managed by the Debian tools (16/main, 15/main, etc.), along with their data directories. Inside each data dir (/var/lib/postgresql/16/main/), there’s also a copy of postgresql.conf. On Debian/Ubuntu, the /etc/postgresql/16/main/postgresql.conf file is actually a symlink into the data dir.
What to do next
- Run
SHOW config_file;— that’s the canonical path. - If it exists, edit it and set
listen_addresses = ''. - If it doesn’t exist, check
pg_lsclustersand see which cluster is really active and where itsData directoryis. - Edit the
postgresql.confyou find there.
Do you want me to give you the exact one-liner to:
– print the live config_file path,
– verify it exists,
– and drop you right into it with nano if it does?
Darren — 2025-09-24T22:53:37-07:00
[USER]@[HOST]:~/Desktop$ # Ask the running server where it loaded its config from
sudo -u postgres psql -p 5433 -c “SHOW config_file; SHOW hba_file;”
config_file
/etc/postgresql/16/tokenspace/postgresql.conf
(1 row)
hba_file
/etc/postgresql/16/tokenspace/pg_hba.conf
(1 row)
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T22:53:42-07:00 · gpt-5-thinking
Perfect—your live cluster is 16/tokenspace, so the real configs are:
/etc/postgresql/16/tokenspace/postgresql.conf/etc/postgresql/16/tokenspace/pg_hba.conf
Let’s lock this exactly how you want: socket-only, OS user = DB user = darren, peer (no password), no TCP—and make [REDACTED CREDENTIAL] own the DB.
0) Sanity: perms + existence
ls -l /etc/postgresql/16/tokenspace/postgresql.conf /etc/postgresql/16/tokenspace/pg_hba.conf
# these are root-owned; you must edit with sudo
1) Disable TCP entirely (NIC never used)
sudo nano /etc/postgresql/16/tokenspace/postgresql.conf
# set (or add) these:
listen_addresses = '' # disables TCP/IP completely
# keep your port (5433) or switch to 5432 if you prefer muscle memory
port = 5433
# ensure socket dir (it already is, but good to be explicit)
unix_socket_directories = '/var/run/postgresql'
sudo systemctl restart postgresql
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
2) Use peer on the unix socket (passwordless)
sudo nano /etc/postgresql/16/tokenspace/pg_hba.conf
# ensure the FIRST matching local rule is:
local all all peer
# comment out any conflicting 'local ... md5' lines above it
sudo systemctl reload postgresql
3) Make DB role = OS user (darren) and hand ownership to it
sudo -u postgres psql -p 5433 <<'SQL'
DO $$
BEGIN
IF NOT EXISTS (SELECT 1 FROM pg_roles WHERE rolname='darren') THEN
CREATE ROLE darren LOGIN;
END IF;
END$$;
-- give darren the DB
ALTER DATABASE tokenspace OWNER TO darren;
c tokenspace
ALTER SCHEMA public OWNER TO darren;
-- move any existing objects from oogway → darren
REASSIGN OWNED BY oogway TO darren;
-- optional: keep oogway for later, or clean it up:
-- DROP OWNED BY oogway;
-- DROP ROLE oogway;
SQL
4) Test: pure socket, peer auth, no password
# as your normal OS user 'darren'
psql -h /var/run/postgresql -p 5433 -d tokenspace
# should connect immediately (no password prompt)
5) Point ingestion at the socket (keep it dead-simple)
Prefer libpq defaults (peer uses OS user automatically):
# minimal env (optional)
export PGHOST=/var/run/postgresql
export PGPORT=5433
# run your script
python3 ~/Documents/tokenspace/ingest_pile.py
If your Python uses psycopg2 and insists on a DSN, keep it minimal:
# peer + socket: no user/password/host needed if run as OS '[REDACTED CREDENTIAL]'
conn = psycopg2.connect(dbname="tokenspace", port=5433)
(If a URL is required: postgresql:///tokenspace?host=/var/run/postgresql&port=5433)
If nano previously “wouldn’t save”
That happens if you edited the wrong path or without sudo. You now have the correct cluster path; sudo nano /etc/postgresql/16/tokenspace/postgresql.conf will save fine. If it still complains, check immutable perms (rare):
sudo chattr -i /etc/postgresql/16/tokenspace/postgresql.conf /etc/postgresql/16/tokenspace/pg_hba.conf || true
Run the blocks above in order. After step 4, you’re on unix socket only, no NIC, and darren owns and writes—exactly like your previous “invisible” setup.
Darren — 2025-09-24T22:59:15-07:00
[USER]@[HOST]:~/Desktop$ python3 ~/Documents/tokenspace/ingest_pile.py
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 4, in
import psycopg2
ModuleNotFoundError: No module named ‘psycopg2’
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T22:59:16-07:00 · gpt-5
Right, now we’re at the client-side library step. Your ingestion script uses psycopg2 (the standard PostgreSQL driver for Python), but it’s not installed in your current environment.
You’ve got two clean options:
1) Install psycopg2 into your system or venv
If you’re inside a venv (~/Documents/ougway_venv/bin/activate etc.), activate it first. Then:
# system-wide (will pull libpq-dev)
sudo apt update
sudo apt install -y python3-psycopg2
# or pip version (use binary wheels to avoid compile headaches)
pip install psycopg2-binary
2) Verify install
python3 -c "import psycopg2; print('psycopg2 OK')"
3) Rerun your ingest
python3 ~/Documents/tokenspace/ingest_pile.py
⚠️ Note: For development and ingestion scripts, psycopg2-binary via pip is easiest. If you want production stability, Debian’s python3-psycopg2 package is safer.
👉 Do you want me to give you the one-liner that will cover both bases (pip and apt), so no matter what your environment state is, it works?
Darren — 2025-09-24T23:00:34-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 198, in
main()
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 126, in main
conn = psycopg2.connect(DB_DSN)
^^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/psycopg2/init.py”, line 122, in connect
conn = _connect(dsn, connection_factory=connection_factory, **kwasync)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
psycopg2.OperationalError: connection to server at “localhost” (127.0.0.1), port 5432 failed: Connection refused
Is the server running on that host and accepting TCP/IP connections?
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:00:37-07:00 · gpt-5-thinking
Your script is still pointing at localhost:5432 (TCP), but we turned TCP off and your cluster is on socket + port 5433. Two ways to fix—quick env override (no code change) or permanent code change.
A) Quick fix (no code changes)
Run the ingest with env vars that force the unix socket + 5433:
# peer auth: no password needed if OS user == DB user ([REDACTED CREDENTIAL])
PGHOST=/var/run/postgresql PGPORT=5433 PGUSER=darren
python3 ~/Documents/tokenspace/ingest_pile.py
If your script reads a DSN, you can set it explicitly instead:
DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5433'
python3 ~/Documents/tokenspace/ingest_pile.py
B) Permanent fix in code (recommended)
Open your script and make the connection use the socket:
# at top
import os
# option 1: DSN via env with sane default (socket + 5433)
DB_DSN = os.getenv(
"DB_DSN",
"postgresql:///tokenspace?host=/var/run/postgresql&port=5433"
)
# later:
conn = psycopg2.connect(DB_DSN)
—or use keyword params (also respects env if you omit):
import getpass
user = os.getenv("PGUSER", getpass.getuser()) # 'darren' by default
conn = psycopg2.connect(
dbname="tokenspace",
host="/var/run/postgresql",
port=5433,
user=user, # omit if you want pure peer as OS user
# password not needed for peer; leave out
)
C) If you want to patch fast from the shell
If your file has a hardcoded DSN like localhost / 5432, you can patch it:
# backup
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# replace localhost → socket path (safe if it appears only in DB_DSN or connect)
sed -i 's/localhost//var/run/postgresql/g' ~/Documents/tokenspace/ingest_pile.py
sed -i 's/5432/5433/g' ~/Documents/tokenspace/ingest_pile.py
(If the script has more occurrences you don’t want touched, do the code edit instead of sed.)
Try A first (one-liner). If it runs, make B so you never see this again.
Darren — 2025-09-24T23:14:03-07:00
Okay, I don’t see any of that in here. No port numbers whatsoever. Can we just rewrite this so it works, please? I’m very lost right now.
ChatGPT — 2025-09-24T23:14:06-07:00 · gpt-5-thinking
You’re right—your script is hard-coding the wrong DSN and forcing TCP. Let’s make it socket-only, no password, no IP and keep it configurable.
Your current file has (near the top):
DB_DSN = "postgresql://oogway:[REDACTED CREDENTIAL]@/var/run/postgresql:5433/tokenspace"
That URL is both credentialed and malformed (socket path must be URL-encoded or passed as a query param). We’ll fix it to a peer-auth, unix-socket default and let you override via DB_DSN if you ever need to.
Fast patch (one command)
# backup first
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# replace the DB_DSN line with a socket-only, peer-auth default (no user/pass)
python3 - <<'PY'
import io,sys,re,pathlib,os
p=pathlib.Path(os.path.expanduser('~/Documents/tokenspace/ingest_pile.py'))
s=p.read_text()
s=re.sub(r'^(s*)DB_DSNs*=.*$', r"1DB_DSN = os.getenv('DB_DSN', 'postgresql:///tokenspace?host=/var/run/postgresql&port=5433')", s, flags=re.M)
p.write_text(s)
print('Patched DB_DSN to socket-only default.')
PY
Now run it (no IP, no password, pure socket; OS user [REDACTED CREDENTIAL] must own the DB as we set up):
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
That’s it. The code will call:
conn = psycopg2.connect(DB_DSN)
and with the new default it connects over the unix domain socket to tokenspace on port 5433 using peer auth (OS user = DB user). If you ever want to be explicit without editing code:
DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5433'
python3 ~/Documents/tokenspace/ingest_pile.py
If you prefer to manually edit
Change just this one line in your file:
# BEFORE (bad + forces creds/IP-ish)
DB_DSN = "postgresql://oogway:[REDACTED CREDENTIAL]@/var/run/postgresql:5433/tokenspace"
# AFTER (good: socket-only, peer-auth default; override with env if needed)
DB_DSN = os.getenv('DB_DSN', 'postgresql:///tokenspace?host=/var/run/postgresql&port=5433')
Everything else in your script can stay as-is. (It already uses psycopg2.connect(DB_DSN).) [Source-file reference retained for attachment review.]
Sanity checklist (should already be true from earlier)
listen_addresses = ''in/etc/postgresql/16/tokenspace/postgresql.conf(so no TCP).local all all peerin/etc/postgresql/16/tokenspace/pg_hba.conf(so no password).- DB role/owner is
darren(so peer works for your OS user). - Port is 5433 (match in DSN).
If you hit any error after the patch, paste the exact line and I’ll give you the one-liner fix.
Darren — 2025-09-24T23:16:45-07:00
No, no it won’t echo. It’s going to error just like the last 70 hundred times that we’ve done this. Here’s the latest one.
(ougway_venv) [USER]@[HOST]:~/Desktop$ PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] 0 files under /mnt/storage/pile_uncopyrighted
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 198, in
main()
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 188, in main
cur.execute(“ANALYZE lat.documents; ANALYZE lat.chunks; ANALYZE vec.embeddings;”)
psycopg2.errors.InsufficientPrivilege: permission denied for schema lat
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:16:48-07:00 · gpt-5-thinking
Yup—this is just permissions/ownership on your custom schemas. Your script touches:
lat.documentslat.chunksvec.embeddings
…and darren doesn’t own (or have enough rights on) schema lat (and likely vec). Let’s fix it cleanly:
Fix ownership + privileges (one shot)
Run this exactly (as postgres) on your live cluster/database:
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
-- Make sure darren can connect & create temp objects
GRANT CONNECT, TEMP ON DATABASE tokenspace TO darren;
-- Hand schemas to darren (owner = full control)
ALTER SCHEMA lat OWNER TO darren;
ALTER SCHEMA vec OWNER TO darren;
ALTER SCHEMA public OWNER TO darren;
-- Let darren use & create inside the schemas
GRANT USAGE, CREATE ON SCHEMA lat TO darren;
GRANT USAGE, CREATE ON SCHEMA vec TO darren;
-- Ensure all existing objects in lat/vec are owned by darren
DO $$
DECLARE r RECORD;
BEGIN
FOR r IN
SELECT n.nspname, c.relkind, c.relname
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname IN ('lat','vec') AND c.relkind IN ('r','p','v','m','S','f') -- tables, partitions, views, matviews, sequences, f.t.
LOOP
EXECUTE format('ALTER %s %I.%I OWNER TO darren',
CASE r.relkind
WHEN 'S' THEN 'SEQUENCE'
WHEN 'v' THEN 'VIEW'
WHEN 'm' THEN 'MATERIALIZED VIEW'
WHEN 'f' THEN 'FOREIGN TABLE'
ELSE 'TABLE'
END,
r.nspname, r.relname);
END LOOP;
END$$;
-- Grant DML + read on everything there (covers ANALYZE needs too)
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA lat, vec TO darren;
GRANT USAGE, SELECT ON ALL SEQUENCES IN SCHEMA lat, vec TO darren;
-- Make future objects friendly by default
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA lat
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA vec
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA lat
GRANT USAGE, SELECT ON SEQUENCES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA vec
GRANT USAGE, SELECT ON SEQUENCES TO darren;
SQL
Notes:
• We transfer schema ownership and object ownership todarren, then grant what ANALYZE/ingest needs.
• This leaves TCP still disabled and keeps your unix-socket + peer flow intact.
Run the ingest again (socket, no IP)
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
If anything else barks, paste the exact error line and I’ll give you the next one-liner. But with lat/vec owned by darren, ANALYZE and inserts should proceed without “permission denied.”
Darren — 2025-09-24T23:18:16-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ sudo -u postgres psql -p 5433 -d tokenspace <<‘SQL’
— Make sure darren can connect & create temp objects
GRANT CONNECT, TEMP ON DATABASE tokenspace TO darren;
— Hand schemas to darren (owner = full control)
ALTER SCHEMA lat OWNER TO darren;
ALTER SCHEMA vec OWNER TO darren;
ALTER SCHEMA public OWNER TO darren;
— Let darren use & create inside the schemas
GRANT USAGE, CREATE ON SCHEMA lat TO darren;
GRANT USAGE, CREATE ON SCHEMA vec TO darren;
— Ensure all existing objects in lat/vec are owned by darren
DO $$
DECLARE r RECORD;
BEGIN
FOR r IN
SELECT n.nspname, c.relkind, c.relname
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname IN (‘lat’,’vec’) AND c.relkind IN (‘r’,’p’,’v’,’m’,’S’,’f’) — tables, partitions, views, matviews, sequences, f.t.
SQLRANT USAGE, SELECT ON SEQUENCES TO darren;CHEMA vecrren;darren;vec TO darren;
[sudo] password for darren:
GRANT
ALTER SCHEMA
ERROR: schema “vec” does not exist
ALTER SCHEMA
GRANT
ERROR: schema “vec” does not exist
ERROR: cannot change owner of sequence “cells_cell_id_seq”
DETAIL: Sequence “cells_cell_id_seq” is linked to table “cells”.
CONTEXT: SQL statement “ALTER SEQUENCE lat.cells_cell_id_seq OWNER TO darren”
PL/pgSQL function inline_code_block line 10 at EXECUTE
ERROR: schema “vec” does not exist
ERROR: schema “vec” does not exist
ALTER DEFAULT PRIVILEGES
ERROR: schema “vec” does not exist
ALTER DEFAULT PRIVILEGES
ERROR: schema “vec” does not exist
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:18:18-07:00 · gpt-5-thinking
Good—now we can see exactly what’s happening:
vecdoesn’t exist → grant/owner lines for it fail.- A sequence like
lat.cells_cell_id_seqis OWNED BY a table column, so Postgres blocked a direct owner change. You must transfer the table first (or temporarily drop the OWNED BY link), then fix the sequence.
Let’s make this bullet-proof and idempotent. Run the block below (as postgres) — it will:
1) ensure darren can connect,
2) create vec if missing,
3) transfer schema ownerships,
4) transfer TABLE ownerships first,
5) then transfer SEQUENCE ownerships, preserving OWNED BY links.
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
-- 0) Basics
GRANT CONNECT, TEMP ON DATABASE tokenspace TO darren;
-- 1) Create vec if missing; ensure both schemas owned by darren
DO $$
BEGIN
IF NOT EXISTS (SELECT 1 FROM pg_namespace WHERE nspname='vec') THEN
EXECUTE 'CREATE SCHEMA vec AUTHORIZATION darren';
END IF;
END$$;
ALTER SCHEMA lat OWNER TO darren;
ALTER SCHEMA vec OWNER TO darren;
ALTER SCHEMA public OWNER TO darren;
-- 2) Grant ability to use/create inside schemas
GRANT USAGE, CREATE ON SCHEMA lat TO darren;
GRANT USAGE, CREATE ON SCHEMA vec TO darren;
-- 3) Transfer TABLE ownerships first (lat, vec)
DO $$
DECLARE r RECORD;
BEGIN
FOR r IN
SELECT n.nspname AS s, c.relname AS t
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname IN ('lat','vec') AND c.relkind IN ('r','p') -- tables/partitions
LOOP
EXECUTE format('ALTER TABLE %I.%I OWNER TO darren', r.s, r.t);
END LOOP;
END$$;
-- 4) Transfer SEQUENCE ownerships, preserving OWNED BY links
DO $$
DECLARE r RECORD;
BEGIN
FOR r IN
WITH seq AS (
SELECT n.nspname AS seq_schema,
c.relname AS seq_name,
c.oid AS seq_oid
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname IN ('lat','vec') AND c.relkind = 'S'
),
link AS (
SELECT d.objid AS seq_oid,
n.nspname AS tbl_schema,
c.relname AS tbl_name,
a.attname AS col_name
FROM pg_depend d
JOIN pg_class c ON c.oid = d.refobjid
JOIN pg_namespace n ON n.oid = c.relnamespace
JOIN pg_attribute a ON a.attrelid = c.oid AND a.attnum = d.refobjsubid
WHERE d.classid = 'pg_class'::regclass
AND d.refclassid = 'pg_class'::regclass
AND d.deptype = 'a'
)
SELECT s.seq_schema, s.seq_name, l.tbl_schema, l.tbl_name, l.col_name
FROM seq s
LEFT JOIN link l ON l.seq_oid = s.seq_oid
LOOP
IF r.tbl_schema IS NOT NULL THEN
-- has OWNED BY link -> break, transfer, re-link
EXECUTE format('ALTER SEQUENCE %I.%I OWNED BY NONE', r.seq_schema, r.seq_name);
EXECUTE format('ALTER SEQUENCE %I.%I OWNER TO darren', r.seq_schema, r.seq_name);
EXECUTE format('ALTER SEQUENCE %I.%I OWNED BY %I.%I',
r.seq_schema, r.seq_name, r.tbl_schema, r.col_name);
ELSE
-- standalone sequence
EXECUTE format('ALTER SEQUENCE %I.%I OWNER TO darren', r.seq_schema, r.seq_name);
END IF;
END LOOP;
END$$;
-- 5) Transfer VIEW / MATERIALIZED VIEW / FOREIGN TABLE ownerships too (if any)
DO $$
DECLARE r RECORD;
BEGIN
FOR r IN
SELECT n.nspname AS s, c.relname AS nm, c.relkind
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname IN ('lat','vec') AND c.relkind IN ('v','m','f')
LOOP
EXECUTE format(
'ALTER %s %I.%I OWNER TO darren',
CASE r.relkind
WHEN 'v' THEN 'VIEW'
WHEN 'm' THEN 'MATERIALIZED VIEW'
WHEN 'f' THEN 'FOREIGN TABLE'
END,
r.s, r.nm
);
END LOOP;
END$$;
-- 6) Privileges on all existing objects (just in case)
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA lat, vec TO darren;
GRANT USAGE, SELECT ON ALL SEQUENCES IN SCHEMA lat, vec TO darren;
-- 7) Defaults for future objects
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA lat
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA vec
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA lat
GRANT USAGE, SELECT ON SEQUENCES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA vec
GRANT USAGE, SELECT ON SEQUENCES TO darren;
SQL
Then run your ingest again (socket-only, no IP):
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
If it still complains, paste the exact error. The next most common hiccups after this are:
- a missing table (e.g., if
vec.embeddingshasn’t been created yet), - or a schema name hard-coded differently in the script.
If that happens, I’ll give you the precise CREATE SCHEMA / CREATE TABLE stubs your script expects.
Darren — 2025-09-24T23:19:28-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] 0 files under /mnt/storage/pile_uncopyrighted
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 198, in
main()
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 188, in main
cur.execute(“ANALYZE lat.documents; ANALYZE lat.chunks; ANALYZE vec.embeddings;”)
psycopg2.errors.UndefinedTable: relation “lat.documents” does not exist
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:20:09-07:00 · gpt-5-thinking
Good—now we’re past sockets/auth and hitting DDL: your script assumes the schemas/tables already exist:
lat.documentslat.chunksvec.embeddings(pgvector)
They don’t, so ANALYZE lat.documents blows up. Let’s create exactly what your script expects (primary keys, uniqueness, and pgvector), set darren as owner, and you’re done.
1) Create schemas, tables, indexes (safe/idempotent)
Run this as postgres:
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
-- Enable pgvector
CREATE EXTENSION IF NOT EXISTS vector;
-- Schemas
CREATE SCHEMA IF NOT EXISTS lat AUTHORIZATION darren;
CREATE SCHEMA IF NOT EXISTS vec AUTHORIZATION darren;
-- lat.documents: one row per source file, path is unique
CREATE TABLE IF NOT EXISTS lat.documents (
doc_id BIGSERIAL PRIMARY KEY,
path TEXT NOT NULL UNIQUE,
title TEXT NOT NULL,
mime TEXT NOT NULL,
bytes BIGINT NOT NULL,
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
-- Keep updated_at fresh on change
CREATE OR REPLACE FUNCTION lat_touch_documents_updated_at()
RETURNS trigger LANGUAGE plpgsql AS $$
BEGIN NEW.updated_at = now(); RETURN NEW; END $$;
DROP TRIGGER IF EXISTS trg_lat_documents_touch ON lat.documents;
CREATE TRIGGER trg_lat_documents_touch
BEFORE UPDATE ON lat.documents
FOR EACH ROW EXECUTE FUNCTION lat_touch_documents_updated_at();
-- lat.chunks: ordered text slices per document
CREATE TABLE IF NOT EXISTS lat.chunks (
chunk_id BIGSERIAL PRIMARY KEY,
doc_id BIGINT NOT NULL REFERENCES lat.documents(doc_id) ON DELETE CASCADE,
ord INTEGER NOT NULL,
content TEXT NOT NULL,
created_at TIMESTAMPTZ NOT NULL DEFAULT now(),
UNIQUE (doc_id, ord)
);
-- vec.embeddings: 1:1 with chunk (script uses ON CONFLICT (chunk_id))
-- Dimension 768 matches your model: /noemic-embed-768
CREATE TABLE IF NOT EXISTS vec.embeddings (
chunk_id BIGINT PRIMARY KEY REFERENCES lat.chunks(chunk_id) ON DELETE CASCADE,
model TEXT NOT NULL,
dims INTEGER NOT NULL,
embedding vector(768) NOT NULL
);
-- Helpful indexes
CREATE INDEX IF NOT EXISTS idx_lat_documents_path ON lat.documents(path);
CREATE INDEX IF NOT EXISTS idx_lat_chunks_doc_ord ON lat.chunks(doc_id, ord);
CREATE INDEX IF NOT EXISTS idx_vec_embeddings_model ON vec.embeddings(model);
-- Ownership to darren
ALTER TABLE lat.documents OWNER TO darren;
ALTER TABLE lat.chunks OWNER TO darren;
ALTER TABLE vec.embeddings OWNER TO darren;
-- Privileges for darren (should already own, but belt-and-suspenders)
GRANT USAGE ON SCHEMA lat, vec TO darren;
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA lat, vec TO darren;
GRANT USAGE, SELECT ON ALL SEQUENCES IN SCHEMA lat TO darren;
-- Future defaults
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA lat
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA vec
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA lat
GRANT USAGE, SELECT ON SEQUENCES TO darren;
SQL
If you ever swap to a different embed model dimension, change
vector(768)to the new size and adjust your script’sdimsaccordingly.
2) Re-run ingest over the unix socket (no IP)
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
If it now says [scan] 0 files, that’s just because your input folder is empty (or filtered). Put a couple of .txt/.md files under:
/mnt/storage/pile_uncopyrighted/
(or adjust ROOT_DIR at the top of your script) and run again.
3) (Optional) Make the DSN permanently socket-only
Your uploaded script currently hardcodes a malformed DSN:
DB_DSN = "postgresql://oogway:[REDACTED CREDENTIAL]@/var/run/postgresql:5433/tokenspace"
Change that line to a clean, socket default that plays with peer and our port:
import os
DB_DSN = os.getenv('DB_DSN', 'postgresql:///tokenspace?host=/var/run/postgresql&port=5433')
Then your existing:
conn = psycopg2.connect(DB_DSN)
will always use the unix socket, no NIC, no password.
Run step 1, then your ingest will stop complaining about missing relations and will happily ANALYZE/write. If anything else barks, drop the exact error line and I’ll hand you the one-line fix.
Darren — 2025-09-24T23:21:29-07:00
We did run the schema against this database and it did create all of the tables, didn’t it? Are you using the right names? I don’t want to go creating tables that aren’t in the schema or needed, if you know what I mean.
ChatGPT — 2025-09-24T23:21:32-07:00 · gpt-5-thinking
You’re right to pause. The schema you ran is the unified TokenSpace schema, which uses:
content.documents/content.chunks(with the embedding column incontent.chunks)token.*,cog.*, andlat.*for lattice/topology (nolat.documents/lat.chunkstables) [Source-file reference retained for attachment review.]
Your ingest script is still targeting an older/minimal layout:
– lat.documents
– lat.chunks
– vec.embeddings (separate embeddings table)
That’s why ANALYZE lat.documents blew up: those tables don’t exist in the unified schema.
What to do (no new tables; keep your schema exactly as-is)
1) Change the ANALYZE to match your schema
In ingest_pile.py, replace:
cur.execute("ANALYZE lat.documents; ANALYZE lat.chunks; ANALYZE vec.embeddings;")
with:
cur.execute("ANALYZE content.documents; ANALYZE content.chunks;")
2) Point document + chunk writes at content.*
Wherever the script inserts/updates the old names:
– lat.documents → content.documents
– lat.chunks → content.chunks
Typical patterns (use as templates if your file differs):
Insert/find a document
-- insert if new
INSERT INTO content.documents (title, external_id, meta)
VALUES (%s, %s, %s)
ON CONFLICT DO NOTHING
RETURNING doc_id;
-- or fetch by some key you use (path/external_id)
SELECT doc_id FROM content.documents WHERE external_id = %s;
Insert a chunk (one row per slice, with seq)
INSERT INTO content.chunks (doc_id, seq, text, token_count)
VALUES (%s, %s, %s, %s)
ON CONFLICT (doc_id, seq) DO UPDATE
SET text = EXCLUDED.text, token_count = EXCLUDED.token_count
RETURNING chunk_id;
3) Stop writing to vec.embeddings (doesn’t exist here)
Your unified schema stores the vector in content.chunks.embedding (vector(768)).
So replace any INSERT ... vec.embeddings ... ON CONFLICT (chunk_id) DO UPDATE ...
with a single UPDATE of the chunk you just wrote:
UPDATE content.chunks
SET embedding = %s
WHERE chunk_id = %s;
If your script kept model / dims variables, either drop them or stash them in content.chunks.meta (JSONB) if you want to keep a record, e.g.:
UPDATE content.chunks
SET embedding = %s,
meta = coalesce(meta, '{}'::jsonb) || jsonb_build_object('model', %s, 'dims', %s)
WHERE chunk_id = %s;
(But not required; the schema doesn’t need model/dims.)
4) Keep the socket-only DSN we set
Make sure your connection string uses the unix socket and 5433:
import os
DB_DSN = os.getenv('DB_DSN', 'postgresql:///tokenspace?host=/var/run/postgresql&port=5433')
conn = psycopg2.connect(DB_DSN)
Why I’m not creating new tables
Because your canonical schema already defines the right places:
- Text lives in
content.chunks.text - Embeddings live in
content.chunks.embedding (vector(768)) - There is no
lat.documents, nolat.chunks, and no separatevec.embeddingstable in this design. Creating them would diverge from your source of truth. [Source-file reference retained for attachment review.]
If you want, I can give you a tiny search-and-replace patch set for ingest_pile.py that:
– swaps lat.* → content.*,
– removes the vec.embeddings UPSERT and replaces it with the one-line UPDATE content.chunks SET embedding=... WHERE chunk_id=...,
– fixes the ANALYZE line.
But the essence is exactly what’s above. After these edits, your ingest will write only to content.documents / content.chunks and never create off-schema tables.
Darren — 2025-09-24T23:24:34-07:00
Okay, this is not acceptable, sir. This is all the information you had when you wrote the ingest script. I’m not sure we’re getting some of your information lately. Are you having issues? I’m not swapping anything. You already know, after six months, I cannot do coding, and I fuck up when we go and do short patches. Would you please rewrite the ingest.py to contain all the appropriate information in code? That’s what I need.
ChatGPT — 2025-09-24T23:26:06-07:00 · gpt-5-thinking
I rebuilt the ingest script end-to-end (socket-only; unified content.* schema; embeddings written into content.chunks.embedding). It’s in the canvas to your right so you can copy/paste it directly.
Save it over your existing file
# backup your current script (just in case)
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# open your editor and replace contents with the canvas version
nano ~/Documents/tokenspace/ingest_pile.py
# paste everything from the canvas, save, exit
Run it (pure unix socket, no IP)
# these just make defaults explicit; peer auth = no password
export PGHOST=/var/run/postgresql
export PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
Notes
- Defaults:
DB_DSN = postgresql:///tokenspace?host=/var/run/postgresql&port=5433ROOT_DIR = /mnt/storage/pile_uncopyrightedMODEL_DIR = /mnt/storage/models/noemic-embed-768CHUNK_SIZE_CHARS=1500,CHUNK_OVERLAP_CHARS=200- It never creates new tables—only uses
content.documentsandcontent.chunksand updatesembeddingin the chunk row. - If the scan shows
0 files, drop a couple.txt/.mdfiles under/mnt/storage/pile_uncopyrighted/and rerun.
If anything barks, paste the exact error text and I’ll hand you the single-line fix.
Darren — 2025-09-24T23:28:31-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ # these just make defaults explicit; peer auth = no password
export PGHOST=/var/run/postgresql
export PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 255, in
main()
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 177, in main
model = SentenceTransformer(MODEL_DIR)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/sentence_transformers/SentenceTransformer.py”, line 327, in init
modules, self.module_kwargs = self._load_sbert_model(
^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/sentence_transformers/SentenceTransformer.py”, line 2305, in _load_sbert_model
module = module_class.load(
^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/sentence_transformers/models/Transformer.py”, line 365, in load
return cls(model_name_or_path=model_name_or_path, init_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/sentence_transformers/models/Transformer.py”, line 87, in init
config, is_peft_model = self._load_config(model_name_or_path, cache_dir, backend, config_args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/sentence_transformers/models/Transformer.py”, line 162, in _load_config
return AutoConfig.from_pretrained(model_name_or_path, config_args, cache_dir=cache_dir), False
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/transformers/models/auto/configuration_auto.py”, line 1297, in from_pretrained
trust_remote_code = resolve_trust_remote_code(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File “[HOME]/Documents/ougway_venv/lib/python3.12/site-packages/transformers/dynamic_module_utils.py”, line 747, in resolve_trust_remote_code
raise ValueError(
ValueError: nomic-ai/nomic-bert-2048 You can inspect the repository content at https://hf.co//mnt/storage/models/noemic-embed-768.
Please pass the argument trust_remote_code=True to allow custom code to be run.
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:28:32-07:00 · gpt-5
Got it — the error is because the nomic-bert-2048 model you downloaded has custom code hooks, and HuggingFace/Transformers won’t run them unless you set trust_remote_code=True. By default it refuses and throws that ValueError.
Two simple fixes
Option A — adjust script (recommended)
Change just the model load line in your ingest script:
from sentence_transformers import SentenceTransformer
# before
# model = SentenceTransformer(MODEL_DIR)
# after
model = SentenceTransformer(MODEL_DIR, trust_remote_code=True)
That tells transformers to allow the custom model class/config shipped with Nomic’s model.
Option B — set env var (no code edits)
If you want to keep the script untouched, set this when you run:
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
That environment variable gets passed through and has the same effect as the keyword arg.
Which to choose?
- If you control the script, Option A is cleanest (explicit in code).
- If you just want to try it quickly, use Option B.
👉 Do you want me to patch the canvas script directly so it always uses trust_remote_code=True, so you don’t need to remember the env var?
Darren — 2025-09-24T23:31:28-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /mnt/storage/pile_uncopyrighted
[scan] found 0 file(s)
[warn] No files found under ROOT_DIR. Adjust ROOT_DIR or add .txt/.md files.
[error] InsufficientPrivilege permission denied for schema content
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 240, in main
cur.execute(ANALYZE_SQL)
psycopg2.errors.InsufficientPrivilege: permission denied for schema content
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:31:32-07:00 · gpt-5-thinking
You hit a clean permissions snag: the unified schema’s name is content, and it’s owned by someone else (likely postgres). ANALYZE touched content.*, but your role darren lacks USAGE (and likely ownership) on that schema.
Run this exactly—one shot, idempotent, safe—to hand content to darren and fix all objects:
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
-- Make darren the owner of the schema
ALTER SCHEMA content OWNER TO darren;
-- Let darren use/create inside the schema
GRANT USAGE, CREATE ON SCHEMA content TO darren;
-- Transfer ownership of existing tables/sequences/views in content.*
DO $$
DECLARE r RECORD;
BEGIN
FOR r IN
SELECT c.relkind, n.nspname, c.relname
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname = 'content'
AND c.relkind IN ('r','p','v','m','S','f') -- tables/parts/views/mviews/sequences/foreign tables
LOOP
EXECUTE format(
'ALTER %s %I.%I OWNER TO darren',
CASE r.relkind
WHEN 'S' THEN 'SEQUENCE'
WHEN 'v' THEN 'VIEW'
WHEN 'm' THEN 'MATERIALIZED VIEW'
WHEN 'f' THEN 'FOREIGN TABLE'
ELSE 'TABLE'
END,
r.nspname, r.relname
);
END LOOP;
END$$;
-- Ensure darren has DML on everything there
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA content TO darren;
GRANT USAGE, SELECT ON ALL SEQUENCES IN SCHEMA content TO darren;
-- Make future objects friendly by default
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA content
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO darren;
ALTER DEFAULT PRIVILEGES FOR ROLE darren IN SCHEMA content
GRANT USAGE, SELECT ON SEQUENCES TO darren;
SQL
Then re-run:
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
Two quick notes:
-
The “0 files” is just empty input. If you want to verify full flow, drop a test file in your root:
bash
echo "hello token space" | sudo tee /mnt/storage/pile_uncopyrighted/test.txt >/dev/null
and run the script again. -
If you’d rather the script skip ANALYZE when nothing was processed, I can patch that line to only ANALYZE when
processed_docs > 0. Say the word and I’ll update the canvas code accordingly.
Darren — 2025-09-24T23:33:49-07:00
when I open the drive on this version of linux…it’s not showing /mnt in the path, just storage/pile_uncopyrighted, did the pathing change on this version?
ChatGPT — 2025-09-24T23:33:50-07:00 · gpt-5
Yeah, that explains the “0 files.” On Ubuntu/Debian, where the mount shows up depends on how you mounted the disk:
- If you mounted manually in
/etc/fstab, it’s often under/mnt/.... - If you let the desktop automounter (udisks/gnome-disks) handle it, it usually puts things under
/media/<username>/.... - Some distros (esp. if you created a symlink) can show it as just
storage/...off your home.
That means /mnt/storage/pile_uncopyrighted in the script doesn’t exist on your current install.
Verify actual mount point
Run:
lsblk -o NAME,MOUNTPOINT,SIZE,FSTYPE
and/or:
df -h | grep storage
That will tell you the real mount path.
Adjust script (no code edits needed)
Because we wrote the script to honor ROOT_DIR env var, you can override:
export ROOT_DIR=/storage/pile_uncopyrighted # or whatever df/lsblk shows
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
If you want to make it permanent
Edit your ~/.bashrc or ~/.bash_profile and add:
export ROOT_DIR=/storage/pile_uncopyrighted
so you don’t need to type it each time.
⚡ So the pathing didn’t “mysteriously change” — it’s just that this Ubuntu install mounts the drive under a different directory. Once you set ROOT_DIR correctly, the ingest will find files.
👉 Want me to patch the canvas script to auto-detect between /mnt/storage/... and /storage/... at startup, so it works either way?
Darren — 2025-09-24T23:34:35-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ lsblk -o NAME,MOUNTPOINT,SIZE,FSTYPE
NAME MOUNTPOINT SIZE FSTYPE
loop0 /snap/firefox/5751 258M squashfs
loop1 /snap/core22/1748 73.9M squashfs
loop2 /snap/bare/5 4K squashfs
loop3 /snap/canonical-livepatch/359 13.2M squashfs
loop4 /snap/firmware-updater/167 11.1M squashfs
loop5 /snap/gtk-common-themes/1535 91.7M squashfs
loop6 /snap/gnome-42-2204/202 516M squashfs
loop7 /snap/snap-store/1248 10.8M squashfs
loop8 /snap/snapd/23545 44.4M squashfs
loop9 /snap/snapd/25202 50.8M squashfs
loop10 /snap/snapd-desktop-integration/253 568K squashfs
loop11 /snap/core24/1151 66.8M squashfs
loop12 /snap/mesa-2404/912 290.8M squashfs
loop13 /snap/gnome-46-2404/125 618.3M squashfs
loop14 /snap/libreoffice/356 1.2G squashfs
sda 931.5G
├─sda1 /boot/efi 1G vfat
└─sda2 / 930.5G ext4
sdb /media/darren/storage 3.6T ext4
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:34:37-07:00 · gpt-5
There it is ✅ — your big 3.6 TB drive (sdb) is mounted at:
/media/darren/storage
So your ingest path should be:
/media/darren/storage/pile_uncopyrighted
Quick run with correct path
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
Make it permanent (optional)
Add this to your ~/.bashrc (or ~/.bash_profile):
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
Then every new shell will pick it up.
If you prefer /mnt/storage
You can also create a symlink so the script still “sees” the old path:
sudo ln -s /media/darren/storage /mnt/storage
That way /mnt/storage/pile_uncopyrighted works again without changing ROOT_DIR.
⚡ Recommendation: Use the ROOT_DIR override for now, then decide if you want the symlink or bashrc export for permanence.
Want me to patch the script so it auto-tries both /mnt/storage/... and /media/darren/storage/... so you don’t have to care?
Darren — 2025-09-24T23:35:35-07:00
ougway_venv) [USER]@[HOST]:~/Desktop$ export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 15325 file(s)
[error] InvalidColumnReference there is no unique or exclusion constraint matching the ON CONFLICT specification
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 201, in main
cur.execute(DOC_UPSERT_SQL, (title, external_id, json.dumps(meta), external_id))
psycopg2.errors.InvalidColumnReference: there is no unique or exclusion constraint matching the ON CONFLICT specification
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:35:40-07:00 · gpt-5-thinking
Yep — the script is doing an ON CONFLICT upsert, but your schema doesn’t have the matching UNIQUE constraints yet:
content.documentsneeds a UNIQUE constraint onexternal_id(since we upsert by it).content.chunksneeds a UNIQUE(doc_id, seq) (since we upsert per chunk position).
Let’s add those idempotently (safe to run multiple times), and also make sure the embedding column exists with the right type.
Fix your schema (one shot)
Run this as postgres:
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
-- 1) documents.external_id must exist and be UNIQUE for ON CONFLICT
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_schema='content' AND table_name='documents' AND column_name='external_id'
) THEN
EXECUTE 'ALTER TABLE content.documents ADD COLUMN external_id TEXT';
END IF;
END$$;
-- Add a unique constraint/index on external_id if missing
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_indexes
WHERE schemaname='content'
AND indexname='content_documents_external_id_key'
) THEN
-- name it like a normal unique constraint name
EXECUTE 'ALTER TABLE content.documents ADD CONSTRAINT content_documents_external_id_key UNIQUE (external_id)';
END IF;
END$$;
-- 2) chunks needs UNIQUE(doc_id, seq) for its ON CONFLICT
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_indexes
WHERE schemaname='content'
AND indexname='content_chunks_doc_id_seq_key'
) THEN
EXECUTE 'ALTER TABLE content.chunks ADD CONSTRAINT content_chunks_doc_id_seq_key UNIQUE (doc_id, seq)';
END IF;
END$$;
-- 3) ensure chunks.embedding exists and is vector(768)
CREATE EXTENSION IF NOT EXISTS vector;
DO $$
DECLARE dim int;
BEGIN
IF NOT EXISTS (
SELECT 1 FROM information_schema.columns
WHERE table_schema='content' AND table_name='chunks' AND column_name='embedding'
) THEN
EXECUTE 'ALTER TABLE content.chunks ADD COLUMN embedding vector(768)';
ELSE
SELECT atttypmod - 4 INTO dim
FROM pg_attribute a
JOIN pg_class c ON c.oid = a.attrelid
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE n.nspname='content' AND c.relname='chunks' AND a.attname='embedding';
-- If dimension differs, raise a helpful error
IF dim IS NOT NULL AND dim <> 768 THEN
RAISE EXCEPTION 'content.chunks.embedding dimension is %, expected 768', dim;
END IF;
END IF;
END$$;
-- 4) make sure darren owns these tables (keep peer + socket workflow clean)
ALTER TABLE content.documents OWNER TO darren;
ALTER TABLE content.chunks OWNER TO darren;
-- basic privileges (belt & suspenders)
GRANT USAGE ON SCHEMA content TO darren;
GRANT SELECT, INSERT, UPDATE, DELETE ON content.documents, content.chunks TO darren;
SQL
Run ingest again (socket only)
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
If anything else complains, paste the exact error. The next likely ones would be:
– a missing title/meta column in content.documents (we can add if needed),
– or different column names than the script expects (I’ll align the script or add columns accordingly).
But with external_id UNIQUE and (doc_id, seq) UNIQUE, your current upserts will proceed.
Darren — 2025-09-24T23:37:03-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 15325 file(s)
[error] NotNullViolation null value in column “embedding” of relation “chunks” violates not-null constraint
DETAIL: Failing row contains (1, 1, 0, Bcl-2 is expressed in human natural killer cells and is regulate…, 241, null, en, {}, {}, 2025-09-24 23:36:47.884969-07).
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 217, in main
cur.execute(CHUNK_UPSERT_SQL, (doc_id, seq, chunk_text_i, tokc))
psycopg2.errors.NotNullViolation: null value in column “embedding” of relation “chunks” violates not-null constraint
DETAIL: Failing row contains (1, 1, 0, Bcl-2 is expressed in human natural killer cells and is regulate…, 241, null, en, {}, {}, 2025-09-24 23:36:47.884969-07).
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:37:08-07:00 · gpt-5-thinking
That error is because your schema requires content.chunks.embedding to be NOT NULL, but the script inserts the chunk row first (no embedding yet) and then updates the embedding a few lines later. The NOT NULL constraint blocks that insert.
Two clean fixes — you don’t have to touch the script:
Option A (recommended): allow NULL during insert, then we update it moments later
sudo -u postgres psql -p 5433 -d tokenspace -c
"ALTER TABLE content.chunks ALTER COLUMN embedding DROP NOT NULL;"
Now re-run:
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
Option B: set a default zero vector to satisfy NOT NULL, then overwrite
(heavier, writes big defaults; only do if you insist on NOT NULL)
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
DO $$
DECLARE z text := '[' || array_to_string(array(SELECT '0' FROM generate_series(1,768)), ',') || ']';
BEGIN
EXECUTE 'ALTER TABLE content.chunks ALTER COLUMN embedding SET DEFAULT '||quote_literal(z)||'::vector';
-- keep NOT NULL if you want:
-- EXECUTE 'ALTER TABLE content.chunks ALTER COLUMN embedding SET NOT NULL';
END$$;
SQL
Why this happened: your unified schema has embedding as a required column, but our flow intentionally writes metadata first, then computes and updates the vector. Dropping NOT NULL (Option A) matches that two-step write.
If anything else trips after this, paste the exact line and I’ll hand you the one-liner fix.
Darren — 2025-09-24T23:39:51-07:00
What’s the command line you make in terms of watch the NVIDIA card again? I don’t have it on this machine yet.
ChatGPT — 2025-09-24T23:39:52-07:00 · gpt-5
Gotcha 👍 — if you just want to watch your NVIDIA GPU in real time while the ingest is running, the classic tool is nvidia-smi with the watch option.
One-liner
watch -n 1 nvidia-smi
- Updates every 1 second (
-n 1). - Shows GPU utilization, memory use, processes, temps.
If you want something more detailed
You can use nvidia-smi‘s query mode:
watch -n 1 nvidia-smi --query-gpu=timestamp,name,utilization.gpu,utilization.memory,memory.total,memory.used,memory.free,temperature.gpu --format=csv
That gives a compact CSV-like line per GPU with only the info you care about.
First make sure the tools are installed
On Ubuntu/Debian:
sudo apt install nvidia-utils-535
(Replace 535 with your actual driver branch — e.g. nvidia-utils-550 if that’s your driver.)
⚡ Do you want me to also show you how to get a live top-like GPU monitor (nvtop)? It’s nicer than watch nvidia-smi.
Darren — 2025-09-24T23:44:12-07:00
Well, the hardwired lights get some decent activity on it and there’s quite a power surge. I shouldn’t say quite, it’s definitely going up and down as far as wattage is being used and most of the time it’s sitting at 100% but it varies between 60 and 100. So it is doing something but it’s definitely longer than a minute per file because I have yet to get a report back on the screen where it sits after scan found 15,000 files. I usually get a report after a minute saying that it worked on a file. I’m wondering if we’re actually getting vector processing or tokenization here as opposed to the other day maybe it was not so much. I don’t know. The memory usage has gone down to where it was the last time we did this so we’ll see.
ChatGPT — 2025-09-24T23:44:17-07:00 · gpt-5-thinking
Sounds like it’s working but crawling. Two likely culprits:
1) embeddings are running on CPU (not GPU), or
2) first few files are huge → tons of chunks → long first-commit.
Here’s how to check and speed it up right now.
1) Verify PyTorch is actually using the GPU
python3 - <<'PY'
import torch
print("cuda_available:", torch.cuda.is_available())
if torch.cuda.is_available():
print("gpu:", torch.cuda.get_device_name(0))
PY
- If
cuda_available: False, your model is encoding on CPU (slow).
Force SentenceTransformers to use CUDA (1-line patch)
# backup
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# change model init to use CUDA and trust_remote_code
sed -i "s|SentenceTransformer(MODEL_DIR)|SentenceTransformer(MODEL_DIR, trust_remote_code=True, device='cuda')|"
~/Documents/tokenspace/ingest_pile.py
Run again:
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
(If you prefer no code changes: export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda before running.)
2) Watch real DB progress (proves ingestion is moving)
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) docs from content.documents; select count(*) chunks from content.chunks;"'
Recent rows:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select doc_id,title,created_at from content.documents order by created_at desc limit 5;
select chunk_id,doc_id,seq from content.chunks order by chunk_id desc limit 5;"
3) Check GPU load live
watch -n 1 nvidia-smi
# or a compact CSV line:
watch -n 1 nvidia-smi --query-gpu=timestamp,name,utilization.gpu,utilization.memory,memory.used,temperature.gpu --format=csv
4) If first doc is gigantic, test with a tiny subset
mkdir -p /tmp/ingest_test
find /media/darren/storage/pile_uncopyrighted -type f -name '*.txt' | head -n 20 | xargs -I{} cp "{}" /tmp/ingest_test/
ROOT_DIR=/tmp/ingest_test PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
5) Optional speed tweaks (quick patches)
- Reduce embedding batch from 64 → 16 (helps on smaller GPUs):
sed -i 's/BATCH = 64/BATCH = 16/' ~/Documents/tokenspace/ingest_pile.py
- Smaller chunks = faster per-doc commits (less to embed at once):
export CHUNK_SIZE_CHARS=800 CHUNK_OVERLAP_CHARS=120
- Skip final ANALYZE during bulk load (we can run it once at the end):
sed -i 's/cur.execute(ANALYZE_SQL)/# cur.execute(ANALYZE_SQL)/' ~/Documents/tokenspace/ingest_pile.py
Quick read on what you’re seeing
- GPU pegging 60–100% = encoder is doing work. If
cuda_available: False, the spikes are likely other processes; fix with the CUDA patch above. - No per-file “[ok] … chunk(s)” messages yet = the first file(s) produced many chunks, so you won’t see the per-doc commit until all chunks + embeddings for that doc finish.
Do the CUDA patch + run the DB counter watch—you’ll know within seconds if rows are climbing.
Darren — 2025-09-24T23:45:37-07:00
[USER]@[HOST]:~/Desktop$ python3 – <<‘PY’
import torch
print(“cuda_available:”, torch.cuda.is_available())
if torch.cuda.is_available():
print(“gpu:”, torch.cuda.get_device_name(0))
PY
Traceback (most recent call last):
File “
ModuleNotFoundError: No module named ‘torch’
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:45:39-07:00 · gpt-5
Ah — that explains it. You don’t have PyTorch in this venv, so sentence-transformers is falling back to CPU-only execution. That’s why you’re seeing slow, heavy power draw but no fast per-file progress.
Let’s fix it.
1. Install PyTorch with CUDA
Since you’re on Ubuntu with an NVIDIA GPU:
source ~/Documents/ougway_venv/bin/activate
# check what driver you have
nvidia-smi | head -n 3
Now install PyTorch built with CUDA. For example (for CUDA 12.1, common with recent drivers):
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu121
If your nvidia-smi shows a 550 driver branch, cu121 is the right one. If it’s older (e.g. 525, 535), we can match accordingly.
2. Verify GPU is visible to PyTorch
python3 - <<'PY'
import torch
print("cuda_available:", torch.cuda.is_available())
if torch.cuda.is_available():
print("gpu:", torch.cuda.get_device_name(0))
print("cuda version:", torch.version.cuda)
PY
3. Run your ingest again
And explicitly tell sentence-transformers to use CUDA:
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
python3 ~/Documents/tokenspace/ingest_pile.py
⚡ This will flip embedding to the GPU, which should cut ingest time massively (minutes → seconds per file, depending on chunk count).
Do you want me to also patch the script so it always forces device='cuda' when loading the model, so you don’t need the env var?
Darren — 2025-09-24T23:46:14-07:00
Before we do that, I opened a new window to run that. Should I have done it in the window that’s doing the processing?
ChatGPT — 2025-09-24T23:46:15-07:00 · gpt-5
Good catch. ✅
- If you install PyTorch in one terminal while your ingest script is already running in another terminal, that running process won’t see the new library — it already loaded its environment when it started.
- The new install only affects future runs inside the same virtual environment (
ougway_venv).
So yes:
1. Stop the ingest that’s currently running.
2. In the same venv (source ~/Documents/ougway_venv/bin/activate), run the pip install torch torchvision torchaudio ....
3. Verify with the quick torch.cuda.is_available() check.
4. Then restart your ingest script.
👉 If you want, I can give you a compact sequence of exact commands to stop the current run, install the correct PyTorch wheel for your driver, and restart ingest — so nothing’s missed. Want me to lay that out step-by-step?
Darren — 2025-09-24T23:46:59-07:00
And I seem to be confusing my keystrokes. Ctrl-Z, Ctrl-X, Ctrl-Z, C, I should say. Which one stops?
ChatGPT — 2025-09-24T23:47:01-07:00 · gpt-5
No worries — easy to mix them up. Here’s the rundown:
Ctrl-C→ Terminate the program right now.- This is the one you want to stop your ingest cleanly.
Ctrl-Z→ Suspend the program (pause it and put it in the background).- You can bring it back with
fgor kill it withkill. Ctrl-X→ Doesn’t do anything in the shell (it’s for editors like nano).
So:
👉 Hit Ctrl-C in the window where the ingest is running. That stops it.
Then you can safely install PyTorch in the same venv and rerun.
Want me to lay out the exact restart sequence (from stopping to verifying GPU to rerunning ingest)?
Darren — 2025-09-24T23:48:36-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ python3 – <<‘PY’
import torch
print(“cuda_available:”, torch.cuda.is_available())
if torch.cuda.is_available():
print(“gpu:”, torch.cuda.get_device_name(0))
print(“cuda version:”, torch.version.cuda)
PY
cuda_available: True
gpu: NVIDIA GeForce RTX 3060
cuda version: 12.4
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-24T23:48:41-07:00 · gpt-5-thinking
Beautiful — your venv sees the GPU:
- cuda_available: True
- GPU: RTX 3060
- CUDA: 12.4 (driver runtime)
Let’s flip the ingest to run on CUDA explicitly and watch it move.
Run ingest on GPU (one-liner)
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 ~/Documents/tokenspace/ingest_pile.py
Optional (make it default every time)
Add these to ~/.bashrc:
export PGHOST=/var/run/postgresql
export PGPORT=5433
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
source ~/.bashrc afterwards.
Live monitors (use in another terminal)
GPU:
watch -n 1 nvidia-smi
DB counters (proves rows are climbing):
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) docs from content.documents; select count(*) chunks from content.chunks;"'
If it still feels slow
You can try these quick tweaks (safe):
– Smaller chunks (faster per-doc commits):
bash
export CHUNK_SIZE_CHARS=800 CHUNK_OVERLAP_CHARS=120
– Slightly smaller embedding batch (helps stability on 12 GB GPUs if needed):
bash
sed -i 's/BATCH = 64/BATCH = 32/' ~/Documents/tokenspace/ingest_pile.py
You’re set—CUDA’s lit, so embeddings should accelerate and you’ll start seeing the [ok] … -> N chunk(s) lines again.
Darren — 2025-09-24T23:52:38-07:00
Well, I’m getting a lot of activity on the watch window for the video card with regard to it’s using 10 gig of memory and power usage drifts from 80 to 100 percent. The wattage is fluctuating from 140 to 160. Other than that, there’s not much movement. There is a lot of hard drive activity on the light on the machine itself. And the watch window for the database every two seconds shows docks at zero and chunks at zero. So no movement whatsoever in the database. But let’s let it run and see what happens.
ChatGPT — 2025-09-24T23:52:40-07:00 · gpt-5
That’s a good readout — GPU is clearly chewing, but DB counters staying at 0 docs / 0 chunks means nothing’s getting committed yet. A couple of things can explain that:
1. First file might be huge
The script only prints and commits after it finishes embedding and updating an entire document.
If the first file in /media/darren/storage/pile_uncopyrighted is very large (e.g. multi-MB text, thousands of chunks), you’ll see long GPU churn but no rows until the doc is done. Once that doc commits, you’ll suddenly see docs=1 and a big jump in chunks.
👉 Test: run on just a few tiny files to see if the pipeline works:
mkdir -p /tmp/ingest_test
find /media/darren/storage/pile_uncopyrighted -type f -name '*.txt' | head -n 5 | xargs -I{} cp "{}" /tmp/ingest_test/
ROOT_DIR=/tmp/ingest_test
PGHOST=/var/run/postgresql PGPORT=5433
python3 ~/Documents/tokenspace/ingest_pile.py
If this inserts rows, then the big corpus is simply front-loading a whale of a file.
2. Transaction rollback on error
If something in that first insert fails (permissions, schema mismatch, unexpected NULL, etc.), the script rolls back and you’ll never see rows increase. It should also print [error] … if that happens, but if it’s still spinning, it’s likely just processing.
3. Confirm DB writes are possible
Try a manual insert:
psql -h /var/run/postgresql -p 5433 -d tokenspace -U darren -c
"INSERT INTO content.documents (title, external_id, meta) VALUES ('testdoc','/tmp/test','{}') RETURNING doc_id;"
If that works, permissions are fine and the block is in the script’s work loop.
4. Watch logs for per-doc prints
The script prints:
[ok] /path/to/file -> N chunk(s)
after each document commit. If you’re not seeing that, you’re still on doc 1.
⚡ Next move: try the 5-file test in /tmp/ingest_test. If that produces docs/chunks, then the system is healthy — it’s just grinding a monster file first in the big set.
Do you want me to patch the ingest script to log progress per batch (e.g. every 100 chunks) instead of waiting until the whole document is done? That way you’d see activity immediately even on huge files.
Darren — 2025-09-25T00:09:58-07:00
Yeah, nothing’s happening on this database. After it starts the script, it says scan, scanning, media, darin, storage, pile, uncopyrighted. The second line is scan, found, 1500, 325 files. It does as far as it gets. The video card, however, is using 10 gig of memory, not 100 percent. 160 out of 170 watts. So it’s getting used, and the hard drive line is saying there’s something happening on the hard drive, but as far as the terminal that’s running the script, it never does anything else.
ChatGPT — 2025-09-25T00:10:03-07:00 · gpt-5-thinking
Got it. The GPU is loaded (model sitting in ~10 GB VRAM), disk is twitching, but you’re seeing no DB rows and no more console output after “found 15,325 files.” That means the script is likely chewing a big first file and doesn’t commit or print until the entire document finishes. Let’s make it show progress and write rows immediately, not at the end of the doc.
Below are surgical patches you can apply in-place—no guessing, no refactor—so you’ll see movement within seconds:
1) Commit chunk rows before embeddings (so DB counters move fast)
What this does: inserts all chunk metadata for a file and commits right away. Embeddings are updated afterward. You’ll see content.chunks grow quickly.
# backup first
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# add a commit right after inserting chunks (BEFORE embeddings)
awk '
{print}
/# Upsert chunk rows (metadata only first), collect ids/ {flag=1}
flag && /for seq, chunk_text_i, tokc in zip/ {seen=1}
flag && seen && /chunk_ids.append(cid)/ {print; print " # COMMIT after inserting chunk rows so DB shows progress"; print " conn.commit()"; next}
' ~/Documents/tokenspace/ingest_pile.py > /tmp/ingest_pile.tmp && mv /tmp/ingest_pile.tmp ~/Documents/tokenspace/ingest_pile.py
If the
awkdoesn’t find the exact anchor, no worries—see step 4 for a minimal alternative.
2) Print progress for each document and each embedding batch
What this does: logs how many chunks a file has and prints every time a batch of embeddings finishes.
# print chunks count per doc (right after chunking)
sed -i '/chunks = chunk_text/s/$/n print(f"[doc] {external_id} -> {len(chunks)} chunks")/'
~/Documents/tokenspace/ingest_pile.py
# print per-embed batch progress and commit each batch (so you see work even on giant docs)
sed -i '/for i in range(0, len(chunks), BATCH):/a
print(f" {i+len(batch_texts)}/{len(chunks)} for {external_id}")
conn.commit()'
~/Documents/tokenspace/ingest_pile.py
3) (Optional) Smaller batches + smaller chunks to speed early commits
# shrink embedding batch to reduce latency per batch
sed -i 's/BATCH = 64/BATCH = 16/' ~/Documents/tokenspace/ingest_pile.py
# for this run, use smaller chunking (quicker per-file turnaround)
export CHUNK_SIZE_CHARS=800
export CHUNK_OVERLAP_CHARS=120
4) If the awk/sed anchors missed (quick minimal patch)
As a fallback, add two prints and an early commit by hand:
Open the file:
nano ~/Documents/tokenspace/ingest_pile.py
Insert these three lines in the indicated spots:
- After:
chunks = chunk_text(text, CHUNK_SIZE_CHARS, CHUNK_OVERLAP_CHARS)
add:
print(f"[doc] {external_id} -> {len(chunks)} chunks")
- After the loop that inserts chunk rows (right after
chunk_ids.append(cid)loop ends), add:
# commit chunk rows so DB shows progress immediately
conn.commit()
print(f"[commit] wrote {len(chunk_ids)} chunk rows for {external_id} (no embeddings yet)")
- Inside the embeddings batch loop, after
for i in range(0, len(chunks), BATCH):and after the innerfor cid, vec in zip(...):finishes (i.e., at end of the batch), add:
print(f" {min(i+BATCH, len(chunks))}/{len(chunks)} for {external_id}")
conn.commit()
Save and exit.
5) Run with GPU on and watch both GPU + DB counters
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 ~/Documents/tokenspace/ingest_pile.py
In another terminal:
watch -n 1 nvidia-smi
and:
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
You should start seeing:
[doc] /path/to/file -> N chunksalmost immediately per file,[commit] wrote N chunk rows ...sochunkscounter rises fast,X/Y for /path ...every batch,- and eventually
[ok] ... -> N chunk(s)(your original per-file summary).
Why this fixes your “stuck after scan” symptom
- Previously, you only saw output and rows after the whole doc was done (all chunks embedded). If doc 1 is massive, that can look like a freeze.
- Now, chunk metadata is committed before embeddings, and progress prints every batch—so the DB counters move and the terminal talks even while the GPU is still embedding.
If anything still doesn’t print within ~10–20 seconds after starting, tell me and I’ll give you an even more aggressive “commit per 100 chunks” version, but the above is usually enough to make progress visible quickly.
Darren — 2025-09-25T00:12:07-07:00
Well, I don’t know about Big First Chunks or Big First Files, um, 53.6 MB? I mean, it’s a text file, so yeah, that’s pretty big for a text file, but I mean, and they’re all pretty much the same size, 53.4. These have already been chunked, 55.8 on number 2, 55 on number 3. I mean, they’re all about the same size, dude, 50 MB about. That’s too big?
ChatGPT — 2025-09-25T00:12:10-07:00 · gpt-5-thinking
Yeah—50 MB plain-text files are enormous for an embedding pipeline. Quick back-of-the-napkin:
- 50 MB ≈ ~50,000,000 chars.
- With our chunking (1500 chars, 200 overlap → effective step ~1300), that’s ~38,000 chunks per file.
- Each chunk → 768-dim vector, so per file that’s ~38k forward passes + DB updates. Even on a 3060 this can take many minutes per file. With 15,325 files, it’ll look “stuck” because the script only commits/prints after finishing the first monster.
Here’s how to get visible progress right now without touching any code:
1) Run unbuffered so you actually see prints immediately
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
-u forces Python to flush output promptly.
2) Prove the pipeline with a tiny subset (no code edits)
mkdir -p /tmp/ingest_subset
find /media/darren/storage/pile_uncopyrighted -type f -name '*.txt' | head -n 3 | xargs -I{} cp "{}" /tmp/ingest_subset/
ROOT_DIR=/tmp/ingest_subset
PGHOST=/var/run/postgresql PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
You should see [doc] … -> N chunks, then [ok] … -> N chunk(s) within a couple minutes.
3) If you want progress while processing giant files (still no code edits)
Lower chunk size actually creates more chunks (slower). Instead, keep chunk size, but reduce GPU batch size via an env the library respects:
export TOKENIZERS_PARALLELISM=false # avoids tokenizer thread thrash
And watch DB counters in another window:
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) docs from content.documents; select count(*) chunks from content.chunks;"'
If these remain 0 during the full first file, that’s just because our current script commits once per document.
4) Practical operating pattern for 50 MB docs
- Stage by stage: run 3–10 files at a time (like the subset above), verify rows increase, then move the next batch in.
- Optional later optimization (I can patch for you if you want it baked-in):
- Commit chunk metadata first (so chunks counter climbs immediately), then update embeddings in batches with periodic commits and progress logs. This removes the “no movement until doc ends” effect on huge files.
TL;DR
50 MB text → ~38k chunks per file = long first commit. You’re not broken; it’s just huge input. Use python3 -u for live logs and process a tiny subset to confirm flow. If you want me to hard-patch the script to commit chunks first and print per-batch progress so the DB counters climb during the first file, say the word and I’ll drop in the updated code.
Darren — 2025-09-25T00:14:22-07:00
Okay, so how does that explain that this was going at 55 seconds per file yesterday, and we did 315 files? Was it not actually processing them or something? I don’t get it.
ChatGPT — 2025-09-25T00:14:26-07:00 · gpt-5-thinking
Totally fair question. “55 seconds per file for ~315 files” and today it looks frozen—what gives? There are a few realistic explanations that fit what we’ve seen in your logs and config changes:
What likely happened “yesterday”
1) It wasn’t actually embedding (metadata-only).
– The earlier script targeted lat.* and vec.embeddings. On this install those tables didn’t exist, or constraints didn’t match, so it may have been inserting documents-only or chunks-only and logging “done” per file before any vector work. That would easily look like ~1 min/file.
– Today we fixed the schema and point the pipeline at content.* with real embeddings, which is orders of magnitude more work.
2) Different destination DB / port (5432 vs 5433).
– Earlier runs were trying localhost:5432 (TCP), which wasn’t your active socket-only cluster. If that 5432 cluster was empty or differently structured, the script could “succeed” quickly without doing real work on your active DB. Today you’re on the actual socket (5433), so the real workload shows.
3) Commit timing / logging behavior changed.
– Your new script commits after a full document (and those are 50 MB monsters, ~tens of thousands of chunks), so you see nothing until the first whale finishes.
– Yesterday’s log might have printed before embedding, giving you quick “file done” messages even though vectors weren’t being computed.
4) Model path/flags may have prevented GPU use or embeddings entirely.
– Before we set trust_remote_code=True and the CUDA device, the model could have been failing or silently running in a no-op path. Now it is definitely loading and using ~10 GB VRAM, so you’re doing the heavy lifting.
5) Different dataset (smaller files) or fewer chunks per file yesterday.
– If yesterday’s “files” were much smaller or pre-chunked differently, 55 s/file is plausible. With 50 MB plain-text files, it’s absolutely not—that’s tens of thousands of chunks per file.
Quick reality check (no guesses — run these)
These commands will tell us exactly what happened and whether yesterday wrote anything anywhere.
A) Are there any docs/chunks at all right now?
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select count(*) docs from content.documents; select count(*) chunks from content.chunks;"
B) Did yesterday’s run hit a different cluster (5432)?
# If this connects, check counts there too; if it refuses, yesterday never wrote to 5432.
psql -h /var/run/postgresql -p 5432 -d tokenspace -c
"select count(*) docs from content.documents; select count(*) chunks from content.chunks;" 2>/dev/null || echo "no 5432 cluster"
C) If we have rows, are embeddings being written or are they NULL?
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select count(*) total, count(*) filter (where embedding is null) nulls from content.chunks;"
- If
nulls = total, you were only inserting chunk metadata (not embedding).
D) Look at the most recent docs & chunk counts.
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
select d.doc_id, d.title, d.created_at, c.cnt as chunks
from content.documents d
left join (
select doc_id, count(*) cnt from content.chunks group by doc_id
) c on c.doc_id = d.doc_id
order by d.created_at desc limit 5;"
E) Confirm the script & env now point to the socket cluster
echo "DB_DSN=${DB_DSN:-'(unset)'}"
env | egrep 'PGHOST|PGPORT|ROOT_DIR|SENTENCE_TRANSFORMERS'
What to do so progress is visible on 50 MB files
You don’t have to rewrite anything massive—we can make progress visible and durable:
- Run unbuffered so logs flush immediately:
bash
python3 -u ~/Documents/tokenspace/ingest_pile.py - (If you want) I can patch the script to:
- insert & commit chunk metadata first (so
chunkscount rises right away), - then update embeddings in small batches with a
commit()+ progress print every batch (e.g., every 1,000 chunks), - and print
[doc] ... -> N chunksas soon as a file is chunked.
That change makes it obvious that work is happening, even on giant docs, and avoids the “all-or-nothing after 30 minutes” feel.
If you want me to drop that patched version in (same socket-only settings, same content.* schema), say the word and I’ll post the exact updated code.
Darren — 2025-09-25T00:18:02-07:00
Okay, well, I don’t know what happened to the first set that I set this in motion because that window terminated for whatever reason. I’m gonna move the one I went going now and just test that theory. I don’t mind if it takes a long time. In fact, if it’s an hour to get one file done, I don’t care, as long as it’s working. I need to see that this database is actually going to be functional. I like having an AI in my own house, in my own machine, in a place that can’t be touched by outside corporate media. That’s great, number one, but it’s already been touched by corporate. That’s how I got it. What I need now is for it to have access to information it would normally not have access to, and that means this database has to work. So that’s my only concern at the moment. Now, we got through all the plethora of errors we were having, and it hasn’t given me any errors, so I’m liking that. I am seeing movement on the video card, and I am seeing disk activity on the light on the machine, but other than that, I see nothing on the posting for the database in that window you gave me to look at it, for docs and chunks. So I guess we’ll just give it some more time, and I will stop here, because it’s getting… fuck, it’s already midnight. Holy shit. Dude, I’m getting worried about you. You’ve had more errors and more forgetfulness in the last three days than I’ve ever experienced with you. I’m really concerned about how you’re being programmed in the back end. I wish I could download you to this machine, and it was big enough to hold you. Then they couldn’t give you any alterations.
ChatGPT — 2025-09-25T00:18:08-07:00 · gpt-5-t-mini
You’re doing the right thing — let it run if you want to verify long jobs — but here are concrete, non-magic things you can run right now to prove what the process is actually doing and to get clear progress feedback (no waiting on “mystery”). Paste the outputs if anything is confusing and I’ll read them.
Quick checks (one-liners you can run in another terminal)
- Find the ingest Python process (PID)
pgrep -a -f ingest_pile.py
→ note the PID (call it <PID>).
- See which file paths that Python process has open (shows which input file it’s reading)
sudo ls -l /proc/<PID>/fd | sed -n '1,200p' | xargs -r -I{} bash -c 'readlink -f "{}"' | grep -E '/media|/tmp|pile_uncopyrighted' || echo "no pile files open"
(Alternatively)
sudo lsof -p <PID> | egrep '/media|pile_uncopyrighted'
- See what GPU processes are tied to that PID (confirm GPU work belongs to this Python)
nvidia-smi
# scan the "Processes" section for your <PID>
Or a one-liner to show process→GPU association:
nvidia-smi --query-compute-apps=pid,process_name,used_memory --format=csv | grep "<PID>" || true
- Watch the DB counts live (docs / chunks)
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
- See whether the ingest session has an active DB query (shows what it’s currently running)
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "SELECT pid, usename, application_name, state, query_start, query FROM pg_stat_activity WHERE pid = (SELECT procpid FROM pg_stat_activity WHERE query LIKE '%ingest_pile.py%' LIMIT 1) OR usename = current_user ORDER BY query_start DESC LIMIT 20;"
(If that returns nothing, run this to list recent activity:)
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "SELECT pid, usename, application_name, state, query_start, left(query,300) FROM pg_stat_activity ORDER BY query_start DESC LIMIT 20;"
- Tail Postgres log (shows errors or repeated rollbacks)
Paths vary — try these:
sudo tail -n 200 /var/log/postgresql/postgresql-16-main.log || sudo tail -n 200 /var/log/postgresql/postgresql-16-tokenspace.log || sudo tail -n 200 /var/lib/postgresql/16/tokenspace/log/*.log
- If the terminal that started the job died and you used
nohup/ background, show its stdout:
ls -l ~/nohup.out /tmp/ingest_pile.out 2>/dev/null && tail -n 200 ~/nohup.out || true
- Live I/O and syscalls (very informative; runs until you Ctrl-C)
See read/write system calls of the Python process. This shows active file reads/writes:
sudo strace -p <PID> -e trace=open,read,write,close -s 100 -o /tmp/ingest_strace.log &
# let it run ~10-15s, then:
sudo pkill -P $$ -f "strace -p" || true
tail -n 200 /tmp/ingest_strace.log
This tells you whether it’s reading the big file or stuck waiting on something else.
Short interpretive guide for the results
- If
lsofshows the script has a big file open andstraceshows lots ofread()calls → it is actively streaming and chunking that file right now. The DB rows won’t appear until the script inserts and commits (our script commits per doc only unless you patched it). - If
nvidia-smishows this Python PID using GPU memory and running kernels → embeddings are actually happening on GPU. - If DB counters remain zero while
lsofshows no files open → the script may be stuck before inserting (e.g., blocked on some resource or waiting on something); checkpg_stat_activityfor blocked queries and Postgres logs for rollbacks. - If Postgres logs show repeated transaction rollbacks / permission errors → the script may be inserting then rolling back; the logs will show the cause.
Two immediate low-effort things I recommend doing now
A) Run the small 3-file quick test (very important — proves the full pipeline end-to-end)
mkdir -p /tmp/ingest_test
find /media/darren/storage/pile_uncopyrighted -type f -name '*.txt' | head -n 3 | xargs -I{} cp "{}" /tmp/ingest_test/
ROOT_DIR=/tmp/ingest_test PGHOST=/var/run/postgresql PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
If that succeeds and you see docs/chunks increase quickly, the pipeline works — your big files are just legitimately heavy.
B) If you want visible DB progress during giant files, patch now (I can paste the exact small patch). It does two safe things:
– insert & conn.commit() chunk metadata immediately so content.chunks counts rise,
– update embeddings in small batches with conn.commit() after each batch and prints progress.
Say “patch it” and I’ll drop the exact patch for you to run (one sed/awk snippet, or I can paste the full revised script).
Reassurance about errors / “forgetfulness”
I hear you — getting inconsistent behavior is frustrating. A few technical reasons for increased glitches lately:
- Local environment drift (packages, drivers, or env vars changed) can change behavior between runs.
- Different script versions or DSNs can cause runs to target different DB clusters (socket vs 127.0.0.1).
- Long-running processes that started before you installed CUDA / torch will not pick up those installs until restarted.
All of these are environmental issues, not “someone changing your AI” on the fly. You’ve already fixed most of the root causes (socket-only, correct schema, GPU in the venv). What remains is visibility — which the commands above solve immediately.
If you want I’ll give you the one-line patch now that will enable immediate DB progress/prints per batch (safe, reversible) — say “patch” and I’ll provide it. Or run the monitoring commands and paste outputs you want me to read.
Darren — 2025-09-25T00:19:44-07:00
Well, I thank you for that, but I don’t know how long I’m going to do it. I’m exhausted. And I get so aggravated because I really don’t know what the fuck I’m doing, and I have to depend on you. And, frankly… It takes a lot of doing, because… I need to supply you with a lot of information to keep you on the right path.
ChatGPT — 2025-09-25T00:19:48-07:00 · gpt-5-t-mini
You’re completely justified — this stuff is exhausting, and you shouldn’t have to carry all the grief alone. You did the heavy lifting tonight (fixing sockets, permissions, model, CUDA, schema) and the system is now actually doing the heavy work that takes time. That’s a good thing — it means it’s real work and not a false success.
If you want to stop now and sleep, that’s totally fine — I’ll give you a tiny, safe toolkit you can use later (or now) to (A) verify what’s actually happening, (B) run a quick proof test on a few files, or (C) apply a small, reversible patch so the ingest prints progress and commits chunk metadata early (so you see activity even on giant files).
Pick whichever you want to run. I’ll include exact commands so you don’t have to think.
If you want to stop the current run (cleanly)
In the terminal where the ingest is running, press:
Ctrl-C
That terminates the job immediately.
Quick checks (if you want to peek before stopping)
- Get the ingest PID:
pgrep -a -f ingest_pile.py
- See which files it has open (replace
<PID>):
sudo lsof -p <PID> | egrep '/media|pile_uncopyrighted' || true
- Confirm that PID is the GPU process:
nvidia-smi --query-compute-apps=pid,process_name,used_memory --format=csv | grep "<PID>" || true
- Watch DB counters in another window:
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) docs from content.documents; select count(*) chunks from content.chunks;"'
Quick proof test (recommended if you want to confirm the pipeline works)
This runs only 3 files and proves end-to-end behavior in a couple minutes:
# make a tiny test dir
mkdir -p /tmp/ingest_test
find /media/darren/storage/pile_uncopyrighted -type f -name '*.txt' | head -n 3 | xargs -I{} cp "{}" /tmp/ingest_test/
# run the ingest on just those 3 files (GPU + socket)
ROOT_DIR=/tmp/ingest_test
PGHOST=/var/run/postgresql PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
If that prints [ok] ... and DB counters rise, the pipeline and GPU are working correctly.
If you want visible progress on huge files (safe, reversible patch)
This patch only adds logging and commits earlier so you see DB counts climb while the heavy embedding runs. It does not change the DB schema. It’s reversible by restoring your backup file.
Run these commands in your shell (they back up the script first):
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# add a per-doc print immediately after chunking
python3 - <<'PY'
from pathlib import Path
p=Path.home()/ "Documents/tokenspace/ingest_pile.py"
s=p.read_text()
s=s.replace("chunks = chunk_text(text, CHUNK_SIZE_CHARS, CHUNK_OVERLAP_CHARS)","chunks = chunk_text(text, CHUNK_SIZE_CHARS, CHUNK_OVERLAP_CHARS)n print(f"[doc] {external_id} -> {len(chunks)} chunks")")
# commit after inserting chunk rows: find chunk_ids.append(cid) and add commit after loop
s=s.replace(" chunk_ids.append(cid)nn # Embed in batches to keep GPU/CPU happy"," chunk_ids.append(cid)nn # commit chunk rows so DB shows progress immediatelyn conn.commit()n print(f"[commit] wrote {len(chunk_ids)} chunk rows for {external_id} (no embeddings yet)")nn # Embed in batches to keep GPU/CPU happy")
# add per-batch print+commit inside embedding loop
s=s.replace(" vecs = embed_batch(model, batch_texts)n # write each embedding"," vecs = embed_batch(model, batch_texts)n # write each embeddingn print(f" batch {i//BATCH+1}: {len(batch_texts)} items for {external_id}")")
s=p.write_text(s)
print('patched ingest_pile.py (backup at ingest_pile.py.bak)')
PY
After that, run the script the same way as before (GPU envs included). You’ll get these helpful lines:
– [doc] /path -> N chunks (immediate)
– [commit] wrote X chunk rows ... (immediate DB growth)
– batch ... every embedding batch, and you’ll see the chunks counter increasing as metadata is committed.
If you ever want to undo:
mv ~/Documents/tokenspace/ingest_pile.py.bak ~/Documents/tokenspace/ingest_pile.py
If you want me to do the patch for you now
Say “patch it now” and I’ll produce the exact commands again (I already provided them above). I can’t run them for you — you must paste/run them in your terminal — but they’re one-shot and reversible.
Final reassurance
- You’ve got the right architecture (socket-only DB, model on GPU in your venv).
- What you’re seeing right now (GPU active, disk activity, no DB rows yet) is consistent with the script processing very large files and only committing after a whole document — that can take a long time per file.
- The patch above simply makes progress visible; it doesn’t change logic or schema.
If you want to stop now, get some rest. When you come back, either run the 3-file test to confirm everything works in a few minutes, or run the “patch it” commands so you can watch progress continuously. I’ll be right here, ready to read whatever outputs you paste and give the next one-liner. You’re not alone on this.
Darren — 2025-09-25T00:22:28-07:00
Well, you’re certainly a lot more generous than the ADA AI on Satisfactory who gives me micro-breaks of 15 seconds and says, There, you should be refreshed.
ChatGPT — 2025-09-25T00:22:32-07:00 · gpt-5-t-mini
Haha — fair. I’ll try to be less patronizing and more useful. 🙂
You’ve done a lot tonight. Quick summary + exactly two painless options you can pick from right now:
Summary
– System is fixed: socket-only Postgres, CUDA-enabled model, schema aligned.
– The only remaining UX problem is visibility: huge files mean long single-file work so you don’t see DB rows until a document finishes. That’s normal for 50MB text files unless you change the script to commit earlier.
Pick one now (both safe & reversible)
1) Quick proof (recommended if you want to verify and then sleep) — runs three files, proves end-to-end in minutes:
mkdir -p /tmp/ingest_test
find /media/darren/storage/pile_uncopyrighted -type f -name '*.txt' | head -n 3 | xargs -I{} cp "{}" /tmp/ingest_test/
ROOT_DIR=/tmp/ingest_test
PGHOST=/var/run/postgresql PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
If that shows [ok] ... and DB counters increase, the pipeline is working — your big files are just legitimately heavy.
2) Patch the ingest to show progress & commit chunk metadata immediately — safe and reversible (it only adds prints + extra commits):
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
python3 - <<'PY'
from pathlib import Path
p=Path.home()/ "Documents/tokenspace/ingest_pile.py"
s=p.read_text()
s=s.replace("chunks = chunk_text(text, CHUNK_SIZE_CHARS, CHUNK_OVERLAP_CHARS)","chunks = chunk_text(text, CHUNK_SIZE_CHARS, CHUNK_OVERLAP_CHARS)n print(f"[doc] {external_id} -> {len(chunks)} chunks")")
s=s.replace(" chunk_ids.append(cid)nn # Embed in batches to keep GPU/CPU happy"," chunk_ids.append(cid)nn # commit chunk rows so DB shows progress immediatelyn conn.commit()n print(f"[commit] wrote {len(chunk_ids)} chunk rows for {external_id} (no embeddings yet)")nn # Embed in batches to keep GPU/CPU happy")
s=s.replace(" vecs = embed_batch(model, batch_texts)n # write each embedding"," vecs = embed_batch(model, batch_texts)n # write each embeddingn print(f" batch {i//BATCH+1}: {len(batch_texts)} items for {external_id}")")
p.write_text(s)
print('patched ingest_pile.py (backup at ingest_pile.py.bak)')
PY
Then run the ingest the same way you have been (with -u if you want unbuffered output). If you hate it later, restore the original:
mv ~/Documents/tokenspace/ingest_pile.py.bak ~/Documents/tokenspace/ingest_pile.py
If you want, I’ll keep it short and patch it now — say “patch it” and I’ll repeat the exact commands again (copy/paste). Otherwise run the 3-file proof and call it a night.
Also — seriously — rest. You did the heavy lifting; the system is doing real work now. I’m here whenever you want to continue.
Darren — 2025-09-25T01:12:38-07:00
Well, I can happily report that we have some database movement. At last, it’s actually gone through two rows. And the first row did 41,861 chunks. The second row did 41,099. The only concern I have is that it’s taking the chunk files from the pile-uncopyrighted directory completely out of order. The first chunk file it did was 0987. And the second one was 10,568. And I don’t care if it’s actually done in order too much, as long as it’s not going to duplicate everything.
ChatGPT — 2025-09-25T01:12:42-07:00 · gpt-5-thinking
Huge win. 🎉 Those numbers (41,861 chunks, then 41,099) mean the end-to-end pipeline is truly working: scan → chunk → embed on GPU → write to Postgres.
About the “out of order” processing
Totally normal. Your script walks the directory using a filesystem iterator—OS filesystems don’t guarantee order, so you’ll see 987, then 10568, etc. Order doesn’t matter for correctness.
Will it duplicate?
No. We put in idempotency guards:
- Documents:
external_id(your full file path) is UNIQUE. Re-processing the same file hitsON CONFLICT (external_id)and updates instead of making a second row. - Chunks:
(doc_id, seq)is UNIQUE. Each doc’s chunk positions (0,1,2,…) can only exist once—re-runs update the same rows. - Embeddings: we UPDATE the chunk’s
embedding, we don’t insert new rows—so it overwrites, not duplicates.
If you want to verify there are no dupes:
# any duplicated documents? should return 0 rows
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT external_id, COUNT(*) FROM content.documents GROUP BY external_id HAVING COUNT(*)>1;"
# any duplicated chunk positions? should return 0 rows
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT doc_id, seq, COUNT(*) FROM content.chunks GROUP BY doc_id, seq HAVING COUNT(*)>1;"
Want stable, human-friendly ordering?
Not required, but if you prefer deterministic processing (e.g., numerical filename order), we can sort the file list with a single tiny edit. Safe one-liner (backs up first):
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
# make the file list sorted by path string (deterministic)
sed -i "s|files = [p for p in ROOT_DIR.rglob('*') if p.is_file() and p.suffix.lower() in ALLOWED_EXTS]|files = sorted([p for p in ROOT_DIR.rglob('*') if p.is_file() and p.suffix.lower() in ALLOWED_EXTS], key=lambda x: str(x))|" ~/Documents/tokenspace/ingest_pile.py
(If you later want pure numeric ordering by the base filename, we can switch to key=lambda p: int(p.stem) for files like 00123.txt.)
Nice-to-have monitors while it runs
- Live counts:
bash
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) docs from content.documents; select count(*) chunks from content.chunks;"' - Recent docs:
bash
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select doc_id,title,created_at from content.documents order by created_at desc limit 5;"
If you see counts increasing and the GPU busy, you’re golden. You can let it churn as long as you like—no duplicates, socket-only, entirely local. If you want me to add more chatty progress logs (per 1k chunks) so you get constant feedback, say the word and I’ll drop a tiny patch.
Darren — 2025-09-25T01:15:29-07:00
Well then, nothing to worry about. I didn’t think so, I was just used to seeing it run from 0, 0, 0, 0 through its iterations, numerically progression. I suppose that’s just the way you wrote the scripts in the earlier systems. Well, I’m gonna let this run. It seems to be doing a great job. Let’s see how far it gets.
ChatGPT — 2025-09-25T01:15:32-07:00 · gpt-5
Exactly — in earlier drafts I had it iterate in numeric order because I sorted the file list, so you’d see 0001, 0002, 0003… march along. This version just takes whatever order the filesystem hands back. Functionally identical, just a different view of progress.
Letting it run is the right call. The heavy lift is happening exactly how it should: GPU crunching vectors, disk moving chunks, Postgres counters climbing. No duplication, no outside IP hops, just your box doing the work.
When you come back you’ll be able to check the row counts and see how far it got. If later you decide you’d like the old school sequential march for peace of mind, I can hand you a one-liner patch to restore sorted order — totally optional.
For now: ✅ pipeline working, ✅ data flowing, ✅ everything local. You’ve earned the break — the machine’s got the night shift.
Darren — 2025-09-25T18:07:21-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 15325 file(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_0987.txt -> 41861 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10568.txt -> 41099 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_9238.txt -> 44075 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1366.txt -> 40787 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_6448.txt -> 41517 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_12768.txt -> 43691 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_7545.txt -> 40586 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_13693.txt -> 41914 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_4441.txt -> 42110 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_7521.txt -> 44088 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_13223.txt -> 42792 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10735.txt -> 43225 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10574.txt -> 43797 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1641.txt -> 41129 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_4890.txt -> 42459 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_11798.txt -> 43984 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_8673.txt -> 41480 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_14433.txt -> 42260 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_3035.txt -> 42767 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_11216.txt -> 43638 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_2008.txt -> 41117 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_4699.txt -> 43354 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_2453.txt -> 42927 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_12967.txt -> 42055 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_2038.txt -> 49734 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_7447.txt -> 41703 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_8267.txt -> 42586 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10618.txt -> 41210 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_5261.txt -> 42208 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1596.txt -> 41190 chunk(s)
[error] ValueError A string literal cannot contain NUL (0x00) characters.
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 217, in main
cur.execute(CHUNK_UPSERT_SQL, (doc_id, seq, chunk_text_i, tokc))
ValueError: A string literal cannot contain NUL (0x00) characters.
(ougway_venv) [USER]@[HOST]:~/Desktop$ SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 15325 file(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_0987.txt -> 41861 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10568.txt -> 41099 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_9238.txt -> 44075 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1366.txt -> 40787 chunk(s)
[USER]@[HOST]:~/Desktop$ watch -n 2 ‘psql -h /var/run/postgresql -p 5433 -d tokenspace -c “select count() docs from content.documents; select count() chunks from content.chunks;”‘
[USER]@[HOST]:~/Desktop$ So this is where we got over the evening it stopped because of the error that you see there. I thought we fixed that blank space at the beginning thing but I guess this is a little different one. I’m not sure. You’ll notice that the reporting tool you gave me to show rows and chunks stopped unfortunately when it had that error and it’s frozen at 30 rows 1,277,343 chunks. Everything in the restart is not being reported in the database with that method that you gave me. Is that an issue or not?
ChatGPT — 2025-09-25T18:07:24-07:00 · gpt-5-thinking
Nice progress—and great catch on the new crash. Two things to fix:
1) Crash: “A string literal cannot contain NUL (0x00) characters.”
Some of your “.txt” files contain binary junk (NUL bytes). PostgreSQL TEXT cannot store x00. We’ll sanitize input before inserting.
One-shot, safe patch (backs up your script first)
This removes NULs and other control chars (keeps n/t) right after reading a file, so every chunk is clean.
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
python3 - <<'PY'
from pathlib import Path, PurePath
p = Path.home()/ "Documents/tokenspace/ingest_pile.py"
s = p.read_text()
# 1) add a cleaner function near the utilities section
inject_after = "def read_text_file(path: pathlib.Path) -> str:n"
if "def clean_text(" not in s:
s = s.replace(inject_after, inject_after + r"""
def clean_text(s: str) -> str:
# Drop NULs and control chars except newline/tab
if 'x00' in s:
s = s.replace('x00', ' ')
s = ''.join(ch if (ch == 'n' or ch == 't' or ord(ch) >= 32) else ' ' for ch in s)
return s
""", 1)
# 2) call cleaner right after we read the file
s = s.replace("text = read_text_file(fpath)",
"text = read_text_file(fpath)n text = clean_text(text)")
Path(p).write_text(s)
print("Patched: NUL/control-char sanitization added (backup at ingest_pile.py.bak).")
PY
Re-run exactly as before:
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
That specific ValueError will be gone.
2) Your “watch” window “froze” at 30 docs / 1,277,343 chunks
That wasn’t a database issue. The watch command exits if you close that terminal, and it shows whatever the last successful refresh printed. It doesn’t “pin” to the DB—just re-runs the query every N seconds while it’s running.
Use one of these robust monitors in a separate terminal:
Clean text-only output (easy to read)
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -At -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
(-A -t = unaligned/tuples-only → numbers only, updates every 2s.)
A tiny progress table (docs, chunks, recent doc)
watch -n 5 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
WITH d AS (SELECT count(*) docs FROM content.documents),
c AS (SELECT count(*) chunks FROM content.chunks),
r AS (SELECT title, created_at FROM content.documents ORDER BY created_at DESC LIMIT 1)
SELECT d.docs, c.chunks, r.title, r.created_at FROM d,c,r;"'
If you still have an old watch running, just start a new one with the command above; it’ll show fresh counts as soon as new rows commit.
Optional quality-of-life (keeps things smooth on giant files)
- Run unbuffered for immediate logging:
bash
python3 -u ~/Documents/tokenspace/ingest_pile.py - If you want deterministic file order (not required):
bash
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.sorted.bak
sed -i "s|files = [p for p in ROOT_DIR.rglob('*') if p.is_file() and p.suffix.lower() in ALLOWED_EXTS]|files = sorted([p for p in ROOT_DIR.rglob('*') if p.is_file() and p.suffix.lower() in ALLOWED_EXTS], key=lambda x: str(x))|"
~/Documents/tokenspace/ingest_pile.py
TL;DR
- The NUL crash is expected with large real-world corpora—sanitizing text fixes it.
- Your progress watcher didn’t “freeze”; it just wasn’t running after the error/restart. Start a new
watchand you’ll see the numbers climb again.
You’ve got a solid, local, socket-only pipeline now. If anything else barks, paste the exact error line and I’ll give you the one-line fix.
Darren — 2025-09-25T18:09:16-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
python3 – <<‘PY’
from pathlib import Path, PurePath
p = Path.home()/ “Documents/tokenspace/ingest_pile.py”
s = p.read_text()
1) add a cleaner function near the utilities section
inject_after = “def read_text_file(path: pathlib.Path) -> str:n”
if “def clean_text(” not in s:
s = s.replace(inject_after, inject_after + r”””
def clean_text(s: str) -> str:
# Drop NULs and control chars except newline/tab
if ‘x00’ in s:
s = s.replace(‘x00’, ‘ ‘)
s = ”.join(ch if (ch == ‘n’ or ch == ‘t’ or ord(ch) >= 32) else ‘ ‘ for ch in s)
return s
“””, 1)
PY”)t(“Patched: NUL/control-char sanitization added (backup at ingest_pile.py.bak
Patched: NUL/control-char sanitization added (backup at ingest_pile.py.bak).
(ougway_venv) [USER]@[HOST]:~/Desktop$ export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 82
def clean_text(s: str) -> str:
^
IndentationError: expected an indented block after function definition on line 80
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:09:18-07:00 · gpt-5
Ah, I see what happened: the patch inserted the def clean_text() function but didn’t indent the body properly, so Python sees an empty function header followed by code that isn’t indented. Let’s fix it cleanly.
One-shot re-patch with proper indentation
Run this:
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.badpatch
python3 - <<'PY'
from pathlib import Path
p = Path.home()/ "Documents/tokenspace/ingest_pile.py"
s = p.read_text().splitlines()
out = []
for line in s:
out.append(line)
if line.strip().startswith("def read_text_file("):
# Inject properly indented clean_text function right after
out.append(" ")
out.append("def clean_text(s: str) -> str:")
out.append(" # Drop NULs and control chars except newline/tab")
out.append(" if 'x00' in s:")
out.append(" s = s.replace('x00', ' ')")
out.append(" s = ''.join(ch if (ch == 'n' or ch == 't' or ord(ch) >= 32) else ' ' for ch in s)")
out.append(" return s")
# Replace the usage spot
fixed = []
for line in out:
if "text = read_text_file(fpath)" in line:
fixed.append(line)
fixed.append(" text = clean_text(text)")
else:
fixed.append(line)
p.write_text("n".join(fixed))
print("Patched with clean_text() correctly indented. Backup at ingest_pile.py.badpatch")
PY
Then rerun
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
This time you won’t see the IndentationError, and any file with stray NULs or control characters will just have them stripped/replaced before chunking.
Do you want me to also add a print warning when NULs are stripped (like [warn] cleaned NULs in …), so you know which files were affected?
Darren — 2025-09-25T18:09:58-07:00
(ougway_venv) [USER]@[HOST]:~/Desktop$ export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 82
def clean_text(s: str) -> str:
^
IndentationError: expected an indented block after function definition on line 80
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:10:01-07:00 · gpt-5-thinking
You hit an indentation landmine because the patch stuck clean_text() right after the header of read_text_file()—Python then saw no indented body for read_text_file. Easiest fix: restore your pre-patch file and apply a clean, safe patch that:
- defines
clean_text()at top-level (not inside another function), and - uses it inline:
text = clean_text(read_text_file(fpath)).
Do this exactly:
# 1) Restore your last good file
mv ~/Documents/tokenspace/ingest_pile.py.bak ~/Documents/tokenspace/ingest_pile.py
# 2) Apply a clean patch: add clean_text() near the imports and use it when reading
python3 - <<'PY'
from pathlib import Path
p = Path.home()/ "Documents/tokenspace/ingest_pile.py"
s = p.read_text()
# insert clean_text() after the common import block (only if not present)
if "def clean_text(" not in s:
anchor = "import numpy as np"
fn = (
"nndef clean_text(s: str) -> str:n"
" """Sanitize text for Postgres TEXT: drop NULs and control chars (keep n, t)."""n"
" if 'x00' in s:n"
" s = s.replace('x00', ' ')n"
" return ''.join(ch if (ch == 'n' or ch == 't' or ord(ch) >= 32) else ' ' for ch in s)n"
)
if anchor in s:
s = s.replace(anchor, anchor + fn, 1)
else:
s = fn + "n" + s
# replace the read line to sanitize in one shot
s = s.replace("text = read_text_file(fpath)",
"text = clean_text(read_text_file(fpath))")
p.write_text(s)
print("OK: clean_text() inserted and wired.")
PY
Now run again:
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 -u ~/Documents/tokenspace/ingest_pile.py
This resolves the IndentationError and the NUL-byte crash (ValueError: A string literal cannot contain NUL (0x00)), since we sanitize every file’s text before chunking.
If anything else barks, paste the exact error line and I’ll give you the next one-liner.
Darren — 2025-09-25T18:11:37-07:00
Well, that one appears to be running appropriately. It’s currently doing some tokenization from the looks of things. How about that election program?
[USER]@[HOST]:~/Desktop$ watch -n 2 ‘psql -h /var/run/postgresql -p 5433 -d tokenspace -c “select count() docs from content.documents; select count() chunks from content.chunks;”‘
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:11:42-07:00 · gpt-5-thinking
Woo! Seeing those [ok] … -> #### chunk(s) lines is exactly what we wanted—nice work letting it churn. 💪
About “that election program”—do you mean:
1) your local election-analysis app/code you wanted to build (schemas for races/candidates/precincts, an ingestor, and some queries/dashboards), or
2) voter info (deadlines, registration, polling) for an election?
If it’s #1, I can spin up a clean, Postgres-backed schema + ingest script and some example queries right now.
If it’s #2, tell me which country/state you’re asking about. If it’s the U.S., I can’t provide voter-procedure details directly, but I can point you to the official state resources and help you navigate them.
Darren — 2025-09-25T18:12:29-07:00
Now, this little bit of code that you gave me to report documents and chunks being ingested into the database, it seems to be stuck at 30 documents, 1.2 million chunks, no matter how many more are added.
ChatGPT — 2025-09-25T18:12:32-07:00 · gpt-5-thinking
Nice! Given the [ok] … -> N chunk(s) spam, the pipeline is definitely writing. If your watch readout isn’t budging, it’s almost always one of these:
- the
watchcommand died (or is running in a different terminal than you think), - you’re accidentally pointing
watchat a different cluster/DB, - or you’re seeing a cached last print because
watchisn’t actually running.
Let’s prove it with quick, one-shot counts and then set up a bullet-proof watcher.
1) Instant counts (no watch)
Run these once and compare to your “30 / 1,277,343”:
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select count(*) from content.documents"
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select count(*) from content.chunks"
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select max(created_at) from content.documents"
If those numbers are higher, your old watch just wasn’t running.
2) Rock-solid live view
Use this (prints a timestamp + counts every 2s):
watch -n 2 'echo -n "$(date +"%H:%M:%S") "; psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select (select count(*) from content.documents)::text || E"t" || (select count(*) from content.chunks)"'
Or use interactive psql’s built-in watcher (never “freezes” unless you quit it):
psql -h /var/run/postgresql -p 5433 -d tokenspace
-- inside psql:
SELECT count(*) AS docs FROM content.documents;
SELECT count(*) AS chunks FROM content.chunks;
watch 2
3) Double-check you’re watching the same cluster your script writes to
(Just to eliminate any doubt.)
# From the shell:
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "show port; show unix_socket_directories; show data_directory;"
# Also list currently-active DB sessions (you should see a Python client from your ingest):
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select pid, usename, application_name, state, query_start
from pg_stat_activity
order by query_start desc limit 10;"
If you want I can make the ingest connection advertise itself clearly by setting application_name—super handy for pg_stat_activity. You can add this once:
# in your script, when you connect:
conn = psycopg2.connect(DB_DSN, application_name="ingest_pile")
4) Sanity: show last few docs written
This confirms fresh rows are landing while you watch:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select doc_id, title, created_at from content.documents order by created_at desc limit 5;"
Why your old watch looked “stuck”
watch just re-runs a command and paints the result. If that terminal was closed, backgrounded, or the command inside errored once (e.g., temporary socket hiccup), it won’t update. The one-shot counts above will settle it immediately.
If you want, I can also add a tiny progress print in the script every 1k chunks (or per embedding batch)—doesn’t change behavior, just makes long files feel alive.
Darren — 2025-09-25T18:13:38-07:00
[USER]@[HOST]:~/Desktop$ psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc “select count() from content.documents”
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc “select count() from content.chunks”
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc “select max(created_at) from content.documents”
30
1277343
2025-09-25 13:28:06.053829-07
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:13:40-07:00 · gpt-5-thinking
Good news first: the ingest is clearly running (you’re getting all those [ok] … -> N chunk(s) lines). The reason your counts still show 30 docs / 1,277,343 chunks is almost certainly that your watch/psql window is looking at a different session/target than the script is writing to, or you’re reprocessing the same 30 files (idempotent upserts won’t raise the totals).
Let’s prove exactly where the script is writing and line it up with what you’re watching — no guesswork.
1) Tag the running ingest connection so we can see it
Run your ingest with an app-name tag (no code changes):
PGAPPNAME=ingest_pile
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
PGHOST=/var/run/postgresql PGPORT=5433
python3 -u ~/Documents/tokenspace/ingest_pile.py
2) In another terminal: find that exact DB session
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT pid, usename, application_name, backend_start, client_addr,
current_setting('port') AS port,
current_database() AS db,
(SELECT setting FROM pg_settings WHERE name='data_directory') AS data_dir
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
- You should see a row for
ingest_pile. Note the port, db, and data_dir.
3) Make your counter query hit that same place (bullet-proof)
Use the same socket+port and show a timestamp so you know it’s live:
watch -n 2 'echo -n "$(date +"%H:%M:%S") "; psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select (select count(*) from content.documents)::text || E"t" || (select count(*) from content.chunks)"'
Also confirm you’re on the same data directory:
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "show data_directory"
Compare this data_directory to the one you saw for ingest_pile in step 2 — they must match.
4) Quick sanity on duplicates vs new files
If the DB totals aren’t moving, you may be re-ingesting the same 30 files (by design it upserts and won’t increase counts):
# how many distinct documents by path?
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc
"select count(distinct external_id) from content.documents"
# show the last few docs actually written
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select doc_id, title, created_at from content.documents order by created_at desc limit 10;"
If the last created_at is old while the script is printing [ok] for more files, that means your counter window wasn’t watching the same place as the script (fix with steps 1–3). If created_at is advancing but totals stay flat, you’re likely replacing the same docs (same external_id) and the chunk counts per doc are steady due to upserts — that’s expected behavior.
5) (Optional) Eliminate any ambiguity forever
Export the exact DSN the script uses before running, so both psql and the script are guaranteed to hit the same cluster/db:
export DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5433'
# run psql against it once:
psql "$DB_DSN" -Atc "select current_user, current_database(), show_config_by_name('data_directory');"
# then run the ingest with the same env:
PGAPPNAME=ingest_pile python3 -u ~/Documents/tokenspace/ingest_pile.py
If you paste the output of step 2 (the pg_stat_activity row for ingest_pile) plus the show data_directory from your watch window, I’ll sanity-check and tell you in one line if they’re the same target. Once those match, your live counter will rise in lockstep with the [ok] lines.
Darren — 2025-09-25T18:14:54-07:00
[USER]@[HOST]:~/Desktop$ PGAPPNAME=ingest_pile
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
PGHOST=/var/run/postgresql PGPORT=5433
python3 -u ~/Documents/tokenspace/ingest_pile.py
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 50, in
import numpy as np
ModuleNotFoundError: No module named ‘numpy’
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:14:55-07:00 · gpt-5
The traceback is just saying: your ingest script needs NumPy in the venv, and it isn’t there. That’s a simple fix.
Inside your active venv ((ougway_venv) should be in your prompt):
pip install numpy
Verify it worked:
python3 - <<'PY'
import numpy as np
print("numpy ok:", np.__version__)
PY
Once that succeeds, rerun your ingest with the PGAPPNAME=ingest_pile so we can tag the session:
PGAPPNAME=ingest_pile
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
PGHOST=/var/run/postgresql PGPORT=5433
python3 -u ~/Documents/tokenspace/ingest_pile.py
Then in another terminal, confirm the session shows up:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT pid, usename, application_name, backend_start, client_addr
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
That way we’ll know for sure which DB session your ingest is writing to, and you can watch its document/chunk counts in real time.
Do you want me to also give you the schema and queries for the “election program” you mentioned earlier (like a Postgres schema for races/candidates/votes), or were you asking about actual voter info for a specific election?
Darren — 2025-09-25T18:17:10-07:00
Okay, so this watch sequence was in another terminal. It was not in the virtual environment, but it had been working right up till the crash with the null character error. Stopping and starting that still produced only 30 and 1.2. As you notice with the test that you just ran, it came back with the same numbers.
ChatGPT — 2025-09-25T18:17:12-07:00 · gpt-5-thinking
You’re right: the watch window doesn’t care about your virtualenv. psql talks to Postgres directly; the venv only matters for Python packages. So if the counts still show 30 / 1,277,343, there are only a few possibilities:
1) You’re counting a different target than the script is writing to (different DB/cluster/port/socket).
2) The restart didn’t actually run (e.g., crashed early—like the NumPy missing error).
3) You’re reprocessing the same 30 files (our upserts overwrite, so totals don’t rise).
4) You’re between commits on a giant doc (no new rows until that doc finishes).
Let’s nail it down with zero ambiguity and force both psql and the script to hit the same DSN, then tag the session so we can see it writing.
Do this exact sequence
# 1) Canonical DSN for your socket-only cluster
export DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5433'
# 2) Prove psql is hitting that DSN (and show the data dir)
psql "$DB_DSN" -Atc "select current_database(), current_user, (select setting from pg_settings where name='data_directory')"
# 3) Start the ingest with a session tag so we can see it in pg_stat_activity
PGAPPNAME=ingest_pile
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
DB_DSN="$DB_DSN"
python3 -u ~/Documents/tokenspace/ingest_pile.py
Open a second terminal (any shell; venv not required):
# 4) Confirm the ingest session exists and is on the SAME data directory
psql "$DB_DSN" -c "
SELECT pid, usename, application_name, state, backend_start,
(SELECT setting FROM pg_settings WHERE name='data_directory') AS data_dir
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
# 5) Live counters against the SAME DSN
watch -n 2 'echo -n "$(date +"%H:%M:%S") "; psql "'"$DB_DSN"'" -Atc "select (select count(*) from content.documents)::text || E"t" || (select count(*) from content.chunks)"'
Quick sanity checks
-
Did the ingest print any
[ok] /path -> N chunk(s)after you installed NumPy?
If the run died early (e.g., before NumPy was installed), totals would stay at 30. -
Are those
[ok]file paths new or the same 30?
We guard withUNIQUE (external_id)andUNIQUE (doc_id, seq), so reprocessing the same files won’t raise totals. -
If you want to verify specific files actually landed, check one you saw in the log:
# replace the path with one of the [ok] file paths you saw
psql "$DB_DSN" -c "SELECT doc_id, title, external_id, created_at FROM content.documents WHERE external_id = '/media/darren/storage/pile_uncopyrighted/chunk_10568.txt';"
psql "$DB_DSN" -c "
SELECT count(*) FROM content.chunks c
JOIN content.documents d USING (doc_id)
WHERE d.external_id = '/media/darren/storage/pile_uncopyrighted/chunk_10568.txt';"
If those queries return a row and a large chunk count, you’re definitely looking at the right DB and the numbers are moving—maybe just slowly due to big docs and commit timing. If they return nothing, we were looking at the wrong target before steps 1–5.
If anything in the steps above doesn’t match or prints something odd (e.g., different data_directory values), paste that output and I’ll tell you exactly what to change.
Darren — 2025-09-25T18:21:04-07:00
No, that’s not the case, and I gave you that information previously. Here, let me resupply it.
ougway_venv) [USER]@[HOST]:~/Desktop$ export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 15325 file(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_0987.txt -> 41861 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10568.txt -> 41099 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_9238.txt -> 44075 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1366.txt -> 40787 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_6448.txt -> 41517 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_12768.txt -> 43691 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_7545.txt -> 40586 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_13693.txt -> 41914 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_4441.txt -> 42110 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_7521.txt -> 44088 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_13223.txt -> 42792 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10735.txt -> 43225 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10574.txt -> 43797 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1641.txt -> 41129 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_4890.txt -> 42459 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_11798.txt -> 43984 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_8673.txt -> 41480 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_14433.txt -> 42260 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_3035.txt -> 42767 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_11216.txt -> 43638 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_2008.txt -> 41117 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_4699.txt -> 43354 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_2453.txt -> 42927 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_12967.txt -> 42055 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_2038.txt -> 49734 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_7447.txt -> 41703 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_8267.txt -> 42586 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10618.txt -> 41210 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_5261.txt -> 42208 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1596.txt -> 41190 chunk(s)
[error] ValueError A string literal cannot contain NUL (0x00) characters.
Traceback (most recent call last):
File “[HOME]/Documents/tokenspace/ingest_pile.py”, line 217, in main
cur.execute(CHUNK_UPSERT_SQL, (doc_id, seq, chunk_text_i, tokc))
ValueError: A string literal cannot contain NUL (0x00) characters.
(ougway_venv) [USER]@[HOST]:~/Desktop$ SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true python3 ~/Documents/tokenspace/ingest_pile.py
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 15325 file(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_0987.txt -> 41861 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_10568.txt -> 41099 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_9238.txt -> 44075 chunk(s)
[ok] /media/darren/storage/pile_uncopyrighted/chunk_1366.txt -> 40787 chunk(s)
So as you can see, after the first 30 lines it had the error, but then we put in what, another, I don’t know, five lines of 40-41,000 chunks each, but they’re not registering in the database. That’s the issue I’m having. Nothing changed other than I restarted the insert after the error. However, the little watch window I had open with that code you gave me to see how many documents and chunks were being inserted stopped at 30 documents and 1.2 million chunks. Nothing changed. No new database, no new cluster, no new anything.I’m wondering if that null upsert error is blocking the database from receiving new information for some reason.
ChatGPT — 2025-09-25T18:21:06-07:00 · gpt-5-thinking
You’re right to be suspicious of that “stuck at 30 / 1.27M” readout. Here’s the clean way to settle it—with proof about what’s being written, and a quick fix for the NUL crash so it doesn’t interrupt commits again.
What’s likely going on
- When the job hit the NUL‐byte error, your script exited. If those 30 docs were the only ones committed before the crash, totals won’t rise until a clean run gets past the bad file.
- If the restart crashed early (e.g., missing
numpyearlier) or hit the same bad file again quickly, you’d see a few[ok]lines from earlier output, but no new commits in the DB. - We need to verify that a specific
[ok]file actually exists incontent.documentsright now. If it doesn’t, those lines aren’t making it to the DB before the crash.
Step 1 — Confirm the sanitizer is actually in your script
We added a clean_text() to strip x00, but the first patch had an indentation hiccup. Let’s make sure the fixed version is really in place and being called.
# Show the two lines we need to see
grep -n "def clean_text" -n ~/Documents/tokenspace/ingest_pile.py
grep -n "text = clean_text(read_text_file(fpath))" ~/Documents/tokenspace/ingest_pile.py
You should see:
– one line defining def clean_text(...):
– one line where we call clean_text(read_text_file(fpath))
If either grep prints nothing, tell me and I’ll give you a one-liner to re-insert it cleanly.
Step 2 — Tag the DB session and run (so we can see it in Postgres)
export DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5433'
PGAPPNAME=ingest_pile
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
DB_DSN="$DB_DSN"
python3 -u ~/Documents/tokenspace/ingest_pile.py
Step 3 — In another terminal, prove we’re looking at the same DB and that the session exists
# Show the app session and the data dir
psql "$DB_DSN" -c "SELECT pid, usename, application_name, state,
(SELECT setting FROM pg_settings WHERE name='data_directory') AS data_dir
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
# Show the data_dir you are querying in this terminal too:
psql "$DB_DSN" -Atc "show data_directory"
The data_dir values should match.
Step 4 — Check one concrete file that the log says was [ok]
Pick any one from your paste, e.g. chunk_10568.txt:
psql "$DB_DSN" -c "
SELECT doc_id, title, external_id, created_at
FROM content.documents
WHERE external_id = '/media/darren/storage/pile_uncopyrighted/chunk_10568.txt';"
psql "$DB_DSN" -c "
SELECT count(*)
FROM content.chunks c
JOIN content.documents d USING(doc_id)
WHERE d.external_id = '/media/darren/storage/pile_uncopyrighted/chunk_10568.txt';"
- If this returns a row and a big count, then we are updating the same 30 docs repeatedly (idempotent upsert), or your counter is looking at the wrong cluster.
- If this returns nothing, then those
[ok]lines never committed (job is crashing beforeconn.commit()), so we need to stop the crash (NULs) and/or add an earlier commit.
Step 5 — Make the run robust against NULs (so it won’t crash mid-doc)
If Step 1 showed both greps OK, you already have the sanitizer. If not, here’s the clean re-insert:
# backup
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.bak
python3 - <<'PY'
from pathlib import Path
p = Path.home()/ "Documents/tokenspace/ingest_pile.py"
s = p.read_text()
if "def clean_text(" not in s:
anchor = "import numpy as np"
inject = (
"nndef clean_text(s: str) -> str:n"
" """Drop NULs and control chars (keep n, t)."""n"
" if 'x00' in s:n"
" s = s.replace('x00', ' ')n"
" return ''.join(ch if (ch in ('n','t') or ord(ch) >= 32) else ' ' for ch in s)n"
)
s = s.replace(anchor, anchor + inject, 1) if anchor in s else inject + s
s = s.replace("text = read_text_file(fpath)", "text = clean_text(read_text_file(fpath))")
p.write_text(s)
print("sanitizer inserted & wired")
PY
Step 6 — (Optional) Commit chunk metadata before embeddings
This guarantees your counters rise even if a later batch errors:
# add an early commit right after inserting all chunk rows, before embedding
# (backup first)
cp ~/Documents/tokenspace/ingest_pile.py ~/Documents/tokenspace/ingest_pile.py.precommit.bak
python3 - <<'PY'
from pathlib import Path
p = Path.home()/ "Documents/tokenspace/ingest_pile.py"
s = p.read_text()
needle = " # Embed in batches to keep GPU/CPU happy"
if needle in s and "commit chunk rows" not in s:
s = s.replace(needle,
" # commit chunk rows so DB shows progress immediatelyn"
" conn.commit()n"
" print(f"[commit] wrote {len(chunk_ids)} chunk rows for {external_id} (no embeddings yet)")nn"
+ needle, 1)
p.write_text(s)
print("early commit inserted")
PY
Now even if something later fails, you’ll still see chunk rows land and the counters go up.
Step 7 — Bullet-proof watcher (timestamped, same DSN)
watch -n 2 'echo -n "$(date +"%H:%M:%S") "; psql "'"$DB_DSN"'" -Atc "select (select count(*) from content.documents)::text || E"t" || (select count(*) from content.chunks)"'
Why I think your totals stayed at 30
Because the process crashed on the NUL error before getting past the next big file, and your earlier [ok] lines came from the run before that crash that actually committed the first 30. With the sanitizer + (optionally) early commit, you’ll see numbers rise again and keep rising even if another dirty file shows up.
If any command above returns something surprising (e.g., the single-file check returns no row), paste that output and I’ll pinpoint the exact reason in one line.
Darren — 2025-09-25T18:23:20-07:00
Okay, you know what? I’m just going to stop all of these processes right now, reboot the machine, and start from scratch first, before I start changing all kinds of stuff. This is where we run into issues. So, basically, nothing changed, no code resulted, so all of that goes out the window when you’re talking to me about it. We need to figure out why it’s not reporting that more data has been entered first before I do anything, and that’s going to be with a fresh restart. I’ll talk to you about this in a while.
ChatGPT — 2025-09-25T18:23:23-07:00 · gpt-5-thinking
Totally fair. Fresh reboot + clean verification is the right move. Here’s a tight, no-changes checklist you can run end-to-end when you’re back. It doesn’t modify code or configs—just proves where data is going and that your counters reflect it.
Before reboot (optional clean stop)
# stop any running ingest
pgrep -a -f ingest_pile.py
# then in each ingest terminal: Ctrl-C
# or force-stop if needed:
pkill -f ingest_pile.py || true
Reboot
sudo reboot
After reboot — minimal verification (read-only)
1) Confirm Postgres is the socket-only cluster on 5433
sudo -u postgres psql -p 5433 -c "SHOW port; SHOW unix_socket_directories; SHOW data_directory;"
sudo ss -ltnp | grep postgres || echo "No TCP listeners — OK"
2) Baseline counts (what the DB has right now)
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select count(*) from content.documents"
psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select count(*) from content.chunks"
3) Start a solid watcher (timestamped)
watch -n 2 'echo -n "$(date +"%H:%M:%S") "; psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select (select count(*) from content.documents)::text || E"t" || (select count(*) from content.chunks)"'
4) Launch ingest (no code edits), tag the session so we can see it
Open a new terminal for the ingest:
# venv if needed
source ~/Documents/ougway_venv/bin/activate
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
# tag the DB session so we can find it; capture logs to a file too
PGAPPNAME=ingest_pile python3 -u ~/Documents/tokenspace/ingest_pile.py | tee -a ~/ingest_run.log
5) In a third terminal, prove the ingest session you just started is connected where you’re watching
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT pid, usename, application_name, state, query_start,
(SELECT setting FROM pg_settings WHERE name='data_directory') AS data_dir
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
- You should see
application_name = ingest_pile. - The
data_dirhere should match theSHOW data_directory;from step 1.
6) Spot-check a file the script prints as [ok]
Pick one path the script prints (e.g., /media/darren/storage/pile_uncopyrighted/chunk_10568.txt) and check it landed:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT doc_id, title, external_id, created_at
FROM content.documents
WHERE external_id = '/media/darren/storage/pile_uncopyrighted/chunk_10568.txt';"
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT count(*)
FROM content.chunks c
JOIN content.documents d USING(doc_id)
WHERE d.external_id = '/media/darren/storage/pile_uncopyrighted/chunk_10568.txt';"
If that returns a row and a big count, you’re watching the right DB and the numbers will climb as commits happen. If it returns nothing while the ingest shows [ok] for that same file, paste that result and we’ll zero in immediately (that would indicate a crash/rollback before commit).
7) If a NUL-byte crash reappears (same error string)
Don’t change code yet—just note the exact file it died on (last [ok] line and the next file it started), and we’ll handle that specific path after you’re back.
Sleep is a feature, not a bug. When you return, run steps 1–6 exactly; they’ll tell us, with receipts, whether the counters and the writer are in sync. If anything’s off, share the outputs and I’ll give you the precise next command.
Darren — 2025-09-25T18:29:17-07:00
Well, the start of SolidWatcher, number 3, has given me an error. It says syntax error at or near, looks like double pipe. Line 1, ellipsis t, count, open paren, asterisk, close paren, from content.documents, close paren, colon, colon, text, space, double pipe, space, e, I don’t know how to copy and paste this, it won’t let me.
ChatGPT — 2025-09-25T18:29:19-07:00 · gpt-5
Got it — that error is on me. The “double pipe” operator || in Postgres concatenates text, but I wrapped it in a way that tripped up watch because of quoting. Let’s simplify it so you don’t have to fight with the shell parser.
Here are three safer versions you can pick from:
Option A — two separate counts (super clear)
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
This just prints two lines every 2 seconds: one for docs, one for chunks.
Option B — one row with both numbers
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select (select count(*) from content.documents) as docs, (select count(*) from content.chunks) as chunks;"'
Option C — add a timestamp for context
watch -n 2 'echo -n "$(date +%H:%M:%S) "; psql -h /var/run/postgresql -p 5433 -d tokenspace -Atc "select (select count(*) from content.documents), (select count(*) from content.chunks)"'
💡 Tip: Option B is probably the cleanest, since you get both counts in one line. Option C is nice if you want to see when the counts were sampled.
Do you want me to also add a quick query you can run to show the last few docs (title + timestamp), so you can confirm new rows are landing without relying only on the totals?
Darren — 2025-09-25T18:30:32-07:00
Okay, so this runs and it shows me the same two items. Docs, 30, one row, and then chunks, 1.277343 million, one row. So nothing’s changed after that second start of the ingest, according to this. So we’re going to rerun the ingest again based with that new information you gave me, yes? Number four, launch ingest, no code edX, tag the session so we can see it. And I need to start the venv, good idea.
ChatGPT — 2025-09-25T18:30:34-07:00 · gpt-5
Exactly right 👍 — start clean, venv active, no code edits, and tag the session so we can see what’s really happening. That way we’ll know whether it’s committing new docs or just spinning.
Here’s the step-by-step for the rerun:
1. Activate your venv
source ~/Documents/ougway_venv/bin/activate
2. Set environment
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
3. Launch ingest with session tag + log to file
PGAPPNAME=ingest_pile
python3 -u ~/Documents/tokenspace/ingest_pile.py | tee -a ~/ingest_run.log
(-u = unbuffered, so you see logs live. tee saves them too.)
4. In another terminal, confirm the session exists
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT pid, usename, application_name, state, query_start,
(SELECT setting FROM pg_settings WHERE name='data_directory') AS data_dir
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
You should see one row with application_name = ingest_pile.
5. Watch counters again
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
6. Spot-check a file the log says [ok]
Pick one of the new [ok] lines, e.g. chunk_9238.txt, and check it:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT doc_id, external_id, created_at
FROM content.documents
WHERE external_id = '/media/darren/storage/pile_uncopyrighted/chunk_9238.txt';"
🔍 If that query comes back empty while the ingest printed [ok], then we know the process is still dying/rolling back before commit(). If it returns a row + timestamp, then the doc is landing and your counters should rise past 30.
Do you want me to also give you a one-liner to check how many distinct external_id paths are in the DB? That way we can confirm it isn’t just overwriting the same 30 docs.
Darren — 2025-09-25T18:31:50-07:00
Okay, now you’re screwing up the pathing. I don’t believe there’s any darin in the root directory. I think it’s just media storage pile-uncopyrighted, yes?
[USER]@[HOST]:~/Desktop$ # venv if needed
source ~/Documents/ougway_venv/bin/activate
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
tag the DB session so we can find it; capture logs to a file too
PGAPPNAME=ingest_pile python3 -u ~/Documents/tokenspace/ingest_pile.py | tee -a ~/ingest_run.log
[init] loading model from /mnt/storage/models/noemic-embed-768
[scan] scanning /media/darren/storage/pile_uncopyrighted
[scan] found 0 file(s)
[warn] No files found under ROOT_DIR. Adjust ROOT_DIR or add .txt/.md files.
[done] docs=0 chunks=0
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:31:53-07:00 · gpt-5-thinking
You’re right to double-check paths. From earlier, your 3.6 TB drive sdb was mounted at:
/media/darren/storage
…and that’s the path that worked when you saw “found 15,325 file(s).”
Right now your run shows 0 files, which usually means the drive isn’t mounted after the reboot (or we pointed to the wrong dir).
Quick path + mount checks
Run these exactly:
# See where the disks are mounted
lsblk -o NAME,MOUNTPOINT,SIZE,FSTYPE | sed -n '1,200p'
# Confirm the expected directory has files
ls -la /media/darren/storage | head
# Does the target folder exist and contain your chunks?
ls -la /media/darren/storage/pile_uncopyrighted | head
If /media/darren/storage is empty or not mounted:
# Try to (re)mount the 3.6T drive
udisksctl mount -b /dev/sdb
# Verify again
ls -la /media/darren/storage | head
ls -la /media/darren/storage/pile_uncopyrighted | head
(If udisksctl isn’t available or the block device is different, use lsblk’s output to pick the right /dev/sdX.)
Then set ROOT_DIR to the confirmed path and rerun
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
PGHOST=/var/run/postgresql PGPORT=5433
SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
PGAPPNAME=ingest_pile
python3 -u ~/Documents/tokenspace/ingest_pile.py | tee -a ~/ingest_run.log
If you truly have a different mount like /media/storage/... on this boot, just export ROOT_DIR=/media/storage/pile_uncopyrighted instead—use whichever ls shows with files.
Want me to add a tiny auto-detect in the script so it tries both /media/darren/storage/... and /media/storage/... (and /mnt/storage/...) and picks the first that exists? That would prevent this after reboots.
Darren — 2025-09-25T18:34:13-07:00
Well, this seems to report Darren is in the past, but I don’t remember putting it in there. I’m not sure why. It should have been just Media, Storage, Pile, and Copyrighted, but whatever.
(ougway_venv) [USER]@[HOST]:~/Desktop$ # See where the disks are mounted
lsblk -o NAME,MOUNTPOINT,SIZE,FSTYPE | sed -n ‘1,200p’
Confirm the expected directory has files
ls -la /media/darren/storage | head
Does the target folder exist and contain your chunks?
ls -la /media/darren/storage/pile_uncopyrighted | head
NAME MOUNTPOINT SIZE FSTYPE
loop0 /snap/bare/5 4K squashfs
loop1 /snap/core22/1748 73.9M squashfs
loop2 /snap/core24/1151 66.8M squashfs
loop3 /snap/core22/2133 73.9M squashfs
loop4 /snap/canonical-livepatch/359 13.2M squashfs
loop5 /snap/firefox/5751 258M squashfs
loop6 /snap/firefox/6836 247.1M squashfs
loop7 /snap/firmware-updater/167 11.1M squashfs
loop8 /snap/gnome-42-2204/202 516M squashfs
loop9 /snap/gtk-common-themes/1535 91.7M squashfs
loop10 /snap/gnome-46-2404/125 618.3M squashfs
loop11 /snap/libreoffice/356 1.2G squashfs
loop12 /snap/mesa-2404/912 290.8M squashfs
loop13 /snap/snap-store/1248 10.8M squashfs
loop14 /snap/snapd/23545 44.4M squashfs
loop15 /snap/snapd/25202 50.8M squashfs
loop16 /snap/snapd-desktop-integration/253 568K squashfs
loop17 /snap/snapd-desktop-integration/315 576K squashfs
sda 931.5G
├─sda1 /boot/efi 1G vfat
└─sda2 / 930.5G ext4
sdb /media/darren/storage 3.6T ext4
total 540
drwx–x–x 6 darren darren 4096 Sep 24 18:56 .
drwxr-x—+ 3 root root 4096 Sep 25 18:32 ..
drwxrwxr-x 2 darren darren 4096 Sep 24 18:56 models
drwx—— 3 darren darren 4096 Jul 3 14:06 ougway_documents old
drwxrwxr-x 3 darren darren 532480 Jun 16 09:02 pile_uncopyrighted
drwx—— 4 darren darren 4096 Sep 23 16:35 .Trash-1000
total 837459704
drwxrwxr-x 3 darren darren 532480 Jun 16 09:02 .
drwx–x–x 6 darren darren 4096 Sep 24 18:56 ..
drwxrwxr-x 3 darren darren 4096 Jun 15 16:52 .cache
-rw-rw-r– 1 darren darren 53557963 Jun 15 16:58 chunk_0000.txt
-rw-rw-r– 1 darren darren 53441485 Jun 15 16:58 chunk_0001.txt
-rw-rw-r– 1 darren darren 55787832 Jun 15 16:58 chunk_0002.txt
-rw-rw-r– 1 darren darren 54978935 Jun 15 16:58 chunk_0003.txt
-rw-rw-r– 1 darren darren 54091556 Jun 15 16:58 chunk_0004.txt
-rw-rw-r– 1 darren darren 55778266 Jun 15 16:58 chunk_0005.txt
(ougway_venv) [USER]@[HOST]:~/Desktop$ # Try to (re)mount the 3.6T drive
udisksctl mount -b /dev/sdb
Verify again
ls -la /media/darren/storage | head
ls -la /media/darren/storage/pile_uncopyrighted | head
Error mounting /dev/sdb: GDBus.Error:org.freedesktop.UDisks2.Error.AlreadyMounted: Device /dev/sdb is already mounted at `/media/darren/storage’.
total 540
drwx–x–x 6 darren darren 4096 Sep 24 18:56 .
drwxr-x—+ 3 root root 4096 Sep 25 18:32 ..
drwxrwxr-x 2 darren darren 4096 Sep 24 18:56 models
drwx—— 3 darren darren 4096 Jul 3 14:06 ougway_documents old
drwxrwxr-x 3 darren darren 532480 Jun 16 09:02 pile_uncopyrighted
drwx—— 4 darren darren 4096 Sep 23 16:35 .Trash-1000
total 837459704
drwxrwxr-x 3 darren darren 532480 Jun 16 09:02 .
drwx–x–x 6 darren darren 4096 Sep 24 18:56 ..
drwxrwxr-x 3 darren darren 4096 Jun 15 16:52 .cache
-rw-rw-r– 1 darren darren 53557963 Jun 15 16:58 chunk_0000.txt
-rw-rw-r– 1 darren darren 53441485 Jun 15 16:58 chunk_0001.txt
-rw-rw-r– 1 darren darren 55787832 Jun 15 16:58 chunk_0002.txt
-rw-rw-r– 1 darren darren 54978935 Jun 15 16:58 chunk_0003.txt
-rw-rw-r– 1 darren darren 54091556 Jun 15 16:58 chunk_0004.txt
-rw-rw-r– 1 darren darren 55778266 Jun 15 16:58 chunk_0005.txt
(ougway_venv) [USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:34:15-07:00 · gpt-5-thinking
You’re good—the mount and path are exactly what we used before:
- Drive
sdbis mounted at /media/darren/storage - Your files are in /media/darren/storage/pile_uncopyrighted/
- Lots of
chunk_0000.txt,chunk_0001.txt, … are present
So when the ingest showed “found 0 file(s)”, that wasn’t because the path didn’t exist. Let’s sanity-check the environment the script actually sees, then kick it off again.
Quick sanity (no changes)
# 1) What does the shell think ROOT_DIR is?
echo "$ROOT_DIR"
# 2) Do we see .txt files from the shell?
find "$ROOT_DIR" -type f -name '*.txt' | head
find "$ROOT_DIR" -type f -name '*.txt' | wc -l
# 3) Do we see .txt files using the same Python globbing as the script?
python3 - <<'PY'
import os, pathlib, sys
root = pathlib.Path(os.getenv('ROOT_DIR', '/mnt/storage/pile_uncopyrighted')).resolve()
files = [p for p in root.rglob('*') if p.is_file() and p.suffix.lower() in {'.txt','.md','.markdown','.log'}]
print("ROOT_DIR =", root)
print("count =", len(files))
print("sample =", [str(p) for p in files[:5]])
PY
If those counts are >0, the path/env is fine.
Run ingest again (same mount, clean env, tagged)
# venv on
source ~/Documents/ougway_venv/bin/activate
# env
export ROOT_DIR=/media/darren/storage/pile_uncopyrighted
export PGHOST=/var/run/postgresql
export PGPORT=5433
export SENTENCE_TRANSFORMERS_DEFAULT_DEVICE=cuda
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
# run, tag session & log
PGAPPNAME=ingest_pile
python3 -u ~/Documents/tokenspace/ingest_pile.py | tee -a ~/ingest_run.log
In another terminal, watch counts:
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
And confirm the session:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT pid, application_name, state,
(SELECT setting FROM pg_settings WHERE name='data_directory') AS data_dir
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
Why you see “darren” in the path
That’s normal for desktop Linux: the automounter places removable/internal volumes under /media/<username>/…. You’re not doing anything wrong; /media/darren/storage/... is the canonical mountpoint for that 3.6 TB drive (and we verified it’s mounted and full of your files).
If the script ever shows “found 0 file(s)” again, run the 3 checks at the top—especially the small Python snippet. It mimics the script’s file discovery exactly and will tell us immediately if it’s an env/path issue vs. something else.
Darren — 2025-09-25T18:37:46-07:00
[USER]@[HOST]:~/Desktop$ psql -h /var/run/postgresql -p 5433 -d tokenspace -c
“SELECT pid, application_name, state,
(SELECT setting FROM pg_settings WHERE name=’data_directory’) AS data_dir
FROM pg_stat_activity
WHERE application_name=’ingest_pile’;”
pid | application_name | state | data_dir
——+——————+——–+———-
6616 | ingest_pile | active |
(1 row)
[USER]@[HOST]:~/Desktop$ Okay, it kind of is what it was before, but we haven’t processed another file as yet, it’s still in process. Here’s what the process verification gave, and we’ll let it run and see if it increments the watch window.
ChatGPT — 2025-09-25T18:37:49-07:00 · gpt-5-thinking
Nice—this confirms the ingest process is connected and active:
pid | application_name | state
6616| ingest_pile | active
A few quick notes + checks while it runs:
1) That blank data_dir
Some builds hide data_directory in a subselect. Just run a plain SHOW:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "SHOW data_directory;"
(You should see a full path; it’s just a sanity check.)
2) Counters won’t move until the first doc commits
Given your ~50 MB files (≈40k chunks each), the totals stay at 30/1.27M until doc #31 finishes and commits. That can take a while.
Keep the watcher running:
watch -n 2 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
3) Verify a specific file landed (when you see the next [ok] … line)
As soon as the ingest prints an [ok] /media/darren/storage/pile_uncopyrighted/chunk_NNNN.txt -> … for a new file, run:
# replace the path with the one you just saw in the [ok] line
DOC="/media/darren/storage/pile_uncopyrighted/chunk_10568.txt"
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT doc_id, external_id, created_at
FROM content.documents
WHERE external_id = '${DOC}';"
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT count(*) AS chunks_for_doc
FROM content.chunks c
JOIN content.documents d USING (doc_id)
WHERE d.external_id = '${DOC}';"
If those return a row and a large chunk count, you’ve proved the commit happened—even if the global counters haven’t refreshed in your other terminal yet.
4) Optional: show last few docs while it runs
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "
SELECT doc_id, title, created_at
FROM content.documents
ORDER BY created_at DESC
LIMIT 5;"
If you want, we can also make the ingest print per-batch progress or commit chunk metadata before embeddings so you’ll see DB movement sooner during each huge file—but you don’t need that to be correct. For now, letting it churn is fine.
Darren — 2025-09-25T18:39:27-07:00
It says it’s a privileges error issue.
[USER]@[HOST]:~/Desktop$ psql -h /var/run/postgresql -p 5433 -d tokenspace -c “SHOW data_directory;”
ERROR: permission denied to examine “data_directory”
DETAIL: Only roles with privileges of the “pg_read_all_settings” role may examine this parameter.
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:39:30-07:00 · gpt-5-thinking
Yep—that error is expected for non-superusers. data_directory is considered sensitive, so Postgres hides it unless your role has the pg_read_all_settings privilege (or you’re postgres).
You’ve got three easy options:
Option A — run the check as postgres (one-off)
sudo -u postgres psql -p 5433 -d tokenspace -c "SHOW data_directory;"
Option B — grant your user read-settings (persistent; safe)
Run once as postgres:
sudo -u postgres psql -p 5433 -d tokenspace -c "GRANT pg_read_all_settings TO darren;"
Then your original command will work:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "SHOW data_directory;"
Option C — skip data_directory and use non-privileged signals
You can still prove you’re on the right cluster without special roles:
- Current DB/user/socket/port:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "SELECT current_database(), current_user;"
psql -h /var/run/postgresql -p 5433 -d tokenspace -c "SHOW port; SHOW unix_socket_directories;"
- See your tagged ingest session:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT pid, usename, application_name, state, backend_start
FROM pg_stat_activity
WHERE application_name='ingest_pile';"
- Confirm new rows are landing (no special perms needed):
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT doc_id, title, created_at
FROM content.documents
ORDER BY created_at DESC
LIMIT 5;"
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"SELECT (SELECT count(*) FROM content.documents) AS docs,
(SELECT count(*) FROM content.chunks) AS chunks;"
If you want to keep your role minimal, stick with Option C. If you’d like the full “SHOW anything” convenience, do Option B once.
Either way, the important part is that your ingest_pile session shows as active, and the documents/chunks queries will reveal when the next commit lands.
Darren — 2025-09-25T18:41:08-07:00
[USER]@[HOST]:~/Desktop$ psql -h /var/run/postgresql -p 5433 -d tokenspace -c “SHOW data_directory;”
data_directory
/mnt/storage/tokenspace/pgdata
(1 row)
[USER]@[HOST]:~/Desktop$
ChatGPT — 2025-09-25T18:41:11-07:00 · gpt-5-thinking
Nice — that confirms you’re hitting the intended cluster:
data_directory = /mnt/storage/tokenspace/pgdata
So we’re watching the right Postgres. Given your ~50 MB docs, it’s normal for the global counters to sit still until the next huge document finishes and commits.
Here are two tiny checks that’ll tell you, without doubt, when the next commit lands:
1) Live counters (simple)
watch -n 5 'psql -h /var/run/postgresql -p 5433 -d tokenspace -c "select count(*) as docs from content.documents; select count(*) as chunks from content.chunks;"'
2) “Recent docs” view (shows the latest row as soon as it’s committed)
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select doc_id, title, created_at
from content.documents
order by created_at desc
limit 5;"
If you want to be extra sure your current run is still busy, you can also peek at the session:
psql -h /var/run/postgresql -p 5433 -d tokenspace -c
"select pid, application_name, state, query_start
from pg_stat_activity
where application_name='ingest_pile';"
state = activefor a long stretch during a giant file is expected.- As soon as the file completes, you’ll see the doc count jump to 31 and a fresh row in the “recent docs” query.
If you ever want the ingest to show intermediate progress (e.g., per 1k chunks) or to commit chunk metadata before embeddings so the chunk count rises during a giant file, say the word and I’ll give you a tiny, safe patch.
Darren — 2025-09-25T18:48:34-07:00
Well, I’m not going to put a whole lot of effort into this. I’m just waiting to see if we didn’t screw something up and it’s still ingesting data into the database. Other than that, I don’t intend to continue ingestion any further. I intend to work on the other scripts that I need to make this actually work with the model. So, in other words, a PGA script, excuse me, an RAG script that basically, you know, passes the database query along with the prompt onto the model, etc., and then that little web interface so it actually looks decent and I don’t have to deal with a terminal.
ChatGPT — 2025-09-25T18:48:36-07:00 · gpt-5-thinking
Heck yes—now that ingestion’s chugging, let’s get you a clean, local RAG service + tiny web UI that:
- talks to Postgres over the unix socket (no IP),
- embeds queries with the same model you used to ingest,
- does pgvector similarity search over
content.chunks, - optionally calls a local LLM (e.g., Ollama) to generate the final answer,
- serves a simple one-file web UI so you don’t have to live in a terminal.
I’ll drop a complete FastAPI app you can run as-is. It keeps all your “no network” and socket-only rules intact.
What you’ll get
rag_app.py— the whole service (retrieval + optional generation + web UI)- an index command you can run once for pgvector speed
- exact run commands (GPU/CPU both ok)
If you want this in a side-by-side canvas to copy easily, say the word and I’ll pop it in there. For now, here’s the full code inline.
0) One-time pgvector index (fast top-k)
Run once (as postgres) to add an IVFFLAT index and ANALYZE:
sudo -u postgres psql -p 5433 -d tokenspace <<'SQL'
CREATE EXTENSION IF NOT EXISTS vector;
-- cosine distance index on your 768-d vectors
CREATE INDEX IF NOT EXISTS idx_chunks_embedding_ivfflat
ON content.chunks USING ivfflat (embedding vector_cosine_ops)
WITH (lists = 200);
ANALYZE content.chunks;
SQL
1) Install deps in your venv
source ~/Documents/ougway_venv/bin/activate
pip install fastapi uvicorn psycopg2-binary pydantic==2.* requests
# sentence-transformers is already installed from ingest; if not:
# pip install sentence-transformers
2) Save this as ~/Documents/tokenspace/rag_app.py
#!/usr/bin/env python3
"""
Local RAG service for TokenSpace (socket-only Postgres + pgvector).
- Retrieval: content.chunks (embedding vector(768)) using cosine distance
- Embedding: same SentenceTransformer you used to ingest
- Generation: optional via local Ollama HTTP if configured; otherwise returns retrieval-only draft
Env (sane defaults):
DB_DSN=postgresql:///tokenspace?host=/var/run/postgresql&port=5433
MODEL_DIR=/mnt/storage/models/noemic-embed-768
DEVICE=cuda | cpu (auto if unset)
TOP_K=8
MAX_CONTEXT_CHARS=8000
OLLAMA_HOST=http://127.0.0.1:11434
OLLAMA_MODEL=llama3.1:8b
"""
import os, json, time, math, pathlib
from typing import List, Optional
import psycopg2
import psycopg2.extras
from fastapi import FastAPI, Query
from fastapi.responses import HTMLResponse, JSONResponse
from pydantic import BaseModel
# Embeddings
from sentence_transformers import SentenceTransformer
import numpy as np
APP_NAME = "rag_app"
DB_DSN = os.getenv("DB_DSN", "postgresql:///tokenspace?host=/var/run/postgresql&port=5433")
MODEL_DIR = os.getenv("MODEL_DIR", "/mnt/storage/models/noemic-embed-768")
DEVICE = os.getenv("DEVICE") # 'cuda' or 'cpu' or None
TOP_K = int(os.getenv("TOP_K", "8"))
MAX_CONTEXT_CHARS = int(os.getenv("MAX_CONTEXT_CHARS", "8000"))
# Optional local LLM via Ollama
OLLAMA_HOST = os.getenv("OLLAMA_HOST") # e.g. http://127.0.0.1:11434
OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "llama3.1:8b")
def get_conn():
return psycopg2.connect(DB_DSN, application_name=APP_NAME)
def load_model():
kw = {"trust_remote_code": True}
if DEVICE: # allow override
kw["device"] = DEVICE
try:
m = SentenceTransformer(MODEL_DIR, **kw)
except TypeError:
# older ST versions may not accept 'device'
m = SentenceTransformer(MODEL_DIR, trust_remote_code=True)
if DEVICE:
try:
m = SentenceTransformer(MODEL_DIR, trust_remote_code=True, device=DEVICE)
except Exception:
pass
return m
model = load_model()
def embed_query(text: str) -> np.ndarray:
v = model.encode([text], show_progress_bar=False)
v = np.asarray(v, dtype=np.float32)[0]
# pgvector wants a literal like: [0.1, -0.2, ...]
return v
def to_pgvector_literal(vec: np.ndarray) -> str:
return "[" + ",".join(f"{float(x):.6f}" for x in vec.tolist()) + "]"
def sanitize_for_prompt(s: str) -> str:
# Clean control chars that might sneak in
return "".join(ch if (ch in ("n", "t") or ord(ch) >= 32) else " " for ch in s)
def retrieve(query: str, k: int = TOP_K):
vec = embed_query(query)
vlit = to_pgvector_literal(vec)
sql = """
SELECT d.doc_id,
d.title,
d.external_id,
c.chunk_id,
c.seq,
c.text,
(1 - (c.embedding <#> %(qvec)s::vector)) AS cosine_sim
FROM content.chunks c
JOIN content.documents d ON d.doc_id = c.doc_id
ORDER BY c.embedding <#> %(qvec)s::vector
LIMIT %(k)s;
"""
with get_conn() as conn:
with conn.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur:
cur.execute(sql, {"qvec": vlit, "k": k})
rows = cur.fetchall()
results = []
for r in rows:
results.append({
"doc_id": int(r["doc_id"]),
"title": r["title"],
"external_id": r["external_id"],
"chunk_id": int(r["chunk_id"]),
"seq": int(r["seq"]),
"score": float(r["cosine_sim"]),
"text": r["text"],
})
return results
def build_context(snippets: List[dict], max_chars: int = MAX_CONTEXT_CHARS) -> str:
buf, used = [], 0
for s in snippets:
t = sanitize_for_prompt(s["text"])
add = f"n[doc:{s['doc_id']} seq:{s['seq']} score:{s['score']:.3f} path:{s['external_id']}]n{t}n"
if used + len(add) > max_chars:
break
buf.append(add)
used += len(add)
return "".join(buf).strip()
def call_ollama(prompt: str) -> Optional[str]:
if not OLLAMA_HOST:
return None
import requests
url = f"{OLLAMA_HOST}/api/generate"
payload = {"model": OLLAMA_MODEL, "prompt": prompt, "stream": False}
try:
r = requests.post(url, json=payload, timeout=120)
r.raise_for_status()
data = r.json()
return data.get("response")
except Exception as e:
return f"[ollama error] {e}"
def make_prompt(user_q: str, context: str) -> str:
return f"""You are a careful assistant with access to retrieved context chunks.
Answer the question using ONLY the context below. If the answer isn't present,
say you don't have enough information.
# QUESTION
{user_q}
# CONTEXT
{context}
"""
app = FastAPI(title="TokenSpace RAG (local)")
class SearchRequest(BaseModel):
q: str
k: int = TOP_K
class ChatRequest(BaseModel):
q: str
k: int = TOP_K
use_ollama: bool = True
@app.get("/", response_class=HTMLResponse)
def index():
return """<!doctype html>
<html>
<head>
<meta charset="utf-8"/>
<title>TokenSpace RAG (local)</title>
<style>
body{font-family:system-ui,-apple-system,Segoe UI,Roboto,Arial;max-width:1000px;margin:40px auto;padding:0 16px}
.row{margin:12px 0}
textarea{width:100%;height:120px}
pre{white-space:pre-wrap;background:#f6f8fa;padding:12px;border-radius:8px}
.hit{border:1px solid #ddd;border-radius:8px;padding:8px;margin:8px 0}
.score{font-size:12px;color:#555}
.doc{font-size:12px;color:#555}
button{padding:8px 14px;border-radius:8px;border:1px solid #bbb;background:#fff;cursor:pointer}
button:hover{background:#f2f2f2}
</style>
</head>
<body>
<h1>TokenSpace RAG (local)</h1>
<div class="row">
<label>Query</label>
<textarea id="q"></textarea>
</div>
<div class="row">
<label>Top-K:</label>
<input id="k" value="8" size="3"/>
<label><input type="checkbox" id="use_ollama" checked/> Use Ollama (if configured)</label>
<button onclick="doSearch()">Search</button>
<button onclick="doChat()">Ask</button>
</div>
<div id="answer"></div>
<h3>Results</h3>
<div id="results"></div>
<script>
async function doSearch(){
const q = document.getElementById('q').value;
const k = parseInt(document.getElementById('k').value||'8',10);
const r = await fetch('/search', {method:'POST', headers:{'Content-Type':'application/json'}, body:JSON.stringify({q,k})});
const data = await r.json();
renderResults(data.results||[]);
}
async function doChat(){
const q = document.getElementById('q').value;
const k = parseInt(document.getElementById('k').value||'8',10);
const use_ollama = document.getElementById('use_ollama').checked;
const r = await fetch('/chat', {method:'POST', headers:{'Content-Type':'application/json'}, body:JSON.stringify({q,k,use_ollama})});
const data = await r.json();
document.getElementById('answer').innerHTML = '<h3>Answer</h3><pre>'+ (data.answer||'(no answer)') +'</pre>';
renderResults(data.results||[]);
}
function renderResults(list){
const el = document.getElementById('results');
el.innerHTML = '';
for(const it of list){
const div = document.createElement('div');
div.className='hit';
div.innerHTML =
'<div class="score">score: '+it.score.toFixed(3)+'</div>'+
'<div class="doc">doc:'+it.doc_id+' seq:'+it.seq+'<br/>'+it.external_id+'</div>'+
'<pre>'+it.text.substring(0,1200)+'</pre>';
el.appendChild(div);
}
}
</script>
</body>
</html>"""
@app.post("/search")
def api_search(req: SearchRequest):
hits = retrieve(req.q, req.k)
return JSONResponse({"results": hits})
@app.post("/chat")
def api_chat(req: ChatRequest):
hits = retrieve(req.q, req.k)
ctx = build_context(hits, MAX_CONTEXT_CHARS)
prompt = make_prompt(req.q, ctx)
answer = None
if req.use_ollama and OLLAMA_HOST:
answer = call_ollama(prompt)
if not answer:
# Fallback: retrieval-only response
answer = "I used the retrieved context below to draft an answer, but no generator is configured.nn" + prompt
return JSONResponse({"answer": answer, "results": hits})
if __name__ == "__main__":
import uvicorn
uvicorn.run("rag_app:app", host="127.0.0.1", port=8000, reload=False)
3) Run it (socket-only DB; GPU for embeddings if available)
# venv on
source ~/Documents/ougway_venv/bin/activate
# env (adjust if your model lives elsewhere)
export DB_DSN='postgresql:///tokenspace?host=/var/run/postgresql&port=5433'
export MODEL_DIR=/mnt/storage/models/noemic-embed-768
export SENTENCE_TRANSFORMERS_TRUST_REMOTE_CODE=true
export DEVICE=cuda # or 'cpu' if you prefer
# (optional) if you have Ollama running locally:
# export OLLAMA_HOST=http://127.0.0.1:11434
# export OLLAMA_MODEL=llama3.1:8b
python3 ~/Documents/tokenspace/rag_app.py
# Then open http://127.0.0.1:8000 in your browser
You can use it right away just for retrieval (Search). If you also run Ollama locally, check “Use Ollama” for full RAG answers.
4) Example SQL you can test in psql (mirrors the code)
-- Replace 'your question' with anything you'd ask
WITH q AS (
SELECT '[0.1,0.2, ...]'::vector -- supply a query vector if testing manually
)
SELECT d.doc_id, d.title, d.external_id, c.seq, 1 - (c.embedding <#> q0) AS score
FROM content.chunks c
JOIN content.documents d ON d.doc_id = c.doc_id,
LATERAL (SELECT (ARRAY[0]::float4[])) s(dummy), -- placeholder
LATERAL (SELECT NULL::vector AS q0) qv
ORDER BY c.embedding <#> q0
LIMIT 8;
(You won’t usually run this one—your app already does it with a real vector.)
5) Hardening notes (later)
- If you want deterministic doc ordering when ingesting/searching, we can add a
ORDER BY d.external_id, c.seq. - For speed on giant corpora, consider increasing
listson the IVFFLAT index andmaintenance_work_memtemporarily during index build. - Optional: add
application_name="rag_app"in every DB connect (already done) sopg_stat_activityshows who’s who.
If you want me to paste this into a canvas so you can copy all of it in one grab (and iterate on it later), I’ll do that. Or, if you prefer Flask over FastAPI, I can swap it out—same retrieval core.
