Unix socket database setup — Part 1

Good—now we can see exactly what’s happening:

• vec doesn’t exist → grant/owner lines for it fail.
• A sequence like lat.cells_cell_id_seq is 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.embeddings hasn’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.

Good—now we’re past sockets/auth and hitting DDL: your script assumes the schemas/tables already exist:

• lat.documents
• lat.chunks
• vec.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’s dims accordingly.

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:oogway@/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.

You’re right to pause. The schema you ran is the unified TokenSpace schema, which uses:

• content.documents / content.chunks (with the embedding column in content.chunks)
• token.*, cog.*, and lat.* for lattice/topology (no lat.documents / lat.chunks tables) fileciteturn1file0

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, no lat.chunks, and no separate vec.embeddings table in this design. Creating them would diverge from your source of truth. fileciteturn1file0

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.

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=5433
• ROOT_DIR = /mnt/storage/pile_uncopyrighted
• MODEL_DIR = /mnt/storage/models/noemic-embed-768
• CHUNK_SIZE_CHARS=1500, CHUNK_OVERLAP_CHARS=200
• It never creates new tables—only uses content.documents and content.chunks and updates embedding in the chunk row.
• If the scan shows 0 files, drop a couple .txt/.md files under /mnt/storage/pile_uncopyrighted/ and rerun.

If anything barks, paste the exact error text and I’ll hand you the single-line fix.

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?

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.

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?

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?

Yep — the script is doing an ON CONFLICT upsert, but your schema doesn’t have the matching UNIQUE constraints yet:

• content.documents needs a UNIQUE constraint on external_id (since we upsert by it).
• content.chunks needs 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.

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.

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.

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.

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?

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?

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 fg or kill it with kill.
• 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)?