backps

docker.sh

@@ -7,9 +7,7 @@ up () {
     --detach \
     --name cp2-pg \
     --restart unless-stopped \
-    --env POSTGRES_DB=cavepediav2_db \
+    --env-file $HOME/scripts-private/lech/cavepedia-v2/cp2-pg.env \
-    --env POSTGRES_PASSWORD=cavepediav2_pw \
-    --env POSTGRES_USER=cavepediav2_user \
     --volume /mammoth/cp2/cp2-pg/data:/var/lib/postgresql/data:rw \
     --publish 127.0.0.1:4010:5432 \
     --network pew-net \

poller/getobject.py

@@ -0,0 +1,53 @@
+from pgvector.psycopg import register_vector, Bit
+from psycopg.rows import dict_row
+from urllib.parse import unquote
+from pypdf import PdfReader, PdfWriter
+import anthropic
+import cohere
+import dotenv
+import datetime
+import io
+import json
+import minio
+import numpy as np
+import os
+import psycopg
+import time
+import logging
+from pythonjsonlogger.json import JsonFormatter
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+logHandler = logging.StreamHandler()
+formatter = JsonFormatter("{asctime}{message}", style="{")
+logHandler.setFormatter(formatter)
+logger.addHandler(logHandler)
+
+#####
+
+dotenv.load_dotenv('/home/paul/scripts-private/lech/cavepedia-v2/poller.env')
+
+COHERE_API_KEY = os.getenv('COHERE_API_KEY')
+MINIO_ACCESS_KEY = os.getenv('MINIO_ACCESS_KEY')
+MINIO_SECRET_KEY = os.getenv('MINIO_SECRET_KEY')
+
+s3 = minio.Minio(
+    's3.bigcavemaps.com',
+    access_key=MINIO_ACCESS_KEY,
+    secret_key=MINIO_SECRET_KEY,
+    region='kansascity',
+)
+
+def getobject():
+    bucket = 'cavepedia-v2'
+    key = 'public/var/fyi/VAR-FYI 1982-01.pdf'
+    with s3.get_object(bucket, key) as obj:
+        with open('/tmp/file.pdf', 'wb') as f:
+            while True:
+                chunk = obj.read(1024)
+                if not chunk:
+                    break
+                f.write(chunk)
+
+if __name__ == '__main__':
+    getobject()

poller/main.py

@@ -47,9 +47,8 @@ conn = psycopg.connect(
     row_factory=dict_row,
 )
 
-BACKOFF = False
-
 ## init
+# events table is created by minio up creation of event destination
 def create_tables():
     commands = (
         "CREATE EXTENSION IF NOT EXISTS vector",
@@ -73,10 +72,11 @@ def split_pdfs():
 
     for row in rows:
         with conn.cursor() as cur:
-            for record in row['event_data']['Records']:
+            for record in row['value']['Records']:
                 bucket = record['s3']['bucket']['name']
                 key = record['s3']['object']['key']
                 key = unquote(key)
+                key = key.replace('+',' ')
 
                 logger.info(f'SPLITTING bucket: {bucket}, key: {key}')
 
@@ -100,10 +100,10 @@ def split_pdfs():
                         with io.BytesIO() as bs:
                             writer.write(bs)
                             bs.seek(0)
-                            s3.put_object('cavepedia-v2-pages', f'{key}/page-{i}.pdf', bs, len(bs.getvalue()))
+                            s3.put_object(f'{bucket}-pages', f'{key}/page-{i + 1}.pdf', bs, len(bs.getvalue()))
-                        cur.execute('INSERT INTO embeddings (bucket, key) VALUES (%s, %s);', (f'{bucket}-pages', f'{key}/page-{i}.pdf'))
+                        cur.execute('INSERT INTO embeddings (bucket, key) VALUES (%s, %s);', (f'{bucket}-pages', f'{key}/page-{i + 1}.pdf'))
 
-            cur.execute('DELETE FROM events WHERE event_time = %s', (row['event_time'],))
+            cur.execute('DELETE FROM events WHERE key = %s', (row['key'],))
         conn.commit()
 
 ## processing
@@ -137,42 +137,31 @@ def ocr(bucket, key):
     return message
 
 def process_events():
-    rows = conn.execute('SELECT * FROM embeddings WHERE embedding IS NULL')
+    rows = conn.execute("SELECT COUNT(*) FROM embeddings WHERE embedding IS NULL")
+    row = rows.fetchone()
+    logger.info(f'Found {row["count"]} ready to be processed')
+
+    rows = conn.execute("SELECT * FROM embeddings WHERE embedding IS NULL")
 
     for row in rows:
         bucket = row['bucket']
         key = row['key']
         logger.info(f'PROCESSING bucket: {bucket}, key: {key}')
 
-        # tier 1 limit: 4k tokens/min
+        ## claude 4 sonnet ##
-        # single pdf = 2-3k tokens
+        # tier 1 limit: 8k tokens/min
-        max_retries = 5
+        # tier 2: enough
-        retry_delay = 30
+        # single pdf page: up to 2k tokens
-        for attempt in range(max_retries):
         try:
             ai_ocr = ocr(bucket, key)
             text = ai_ocr.content[0].text
-                text = text.replace('\n',' ')
 
             embedding=embed(text, 'search_document')
             conn.execute('UPDATE embeddings SET content = %s, embedding = %s::vector WHERE bucket = %s AND key = %s;', (text, embedding, bucket, key))
             conn.commit()
-                break
-            except anthropic.APIStatusError as e:
-                if e.type == 'overloaded_error':
-                    if attempt < max_retries - 1:
-                        sleep_time = retry_delay * (2 ** attempt)
-                        logger.info(f"Overload error. Retrying in {sleep_time:.2f} seconds...")
-                        time.sleep(sleep_time)
-                    else:
-                        logger.info('Max retries reached.')
-                        raise
-                else:
-                    raise
         except Exception as e:
             logger.error(f"An unexpected error occurred: {e}")
-                BACKOFF = True
+            return True
-                break
 
 ### embeddings
 def embed(text, input_type):
@@ -198,9 +187,10 @@ if __name__ == '__main__':
         BACKOFF = False
 
         split_pdfs()
-        process_events()
+        BACKOFF = process_events()
 
         if BACKOFF:
-            logger.info('BACKOFF')
+            logger.info('backoff detected, sleeping an extra 5 minutes')
-            time.sleep(10 * 60)
+            time.sleep(5 * 60)
+        logger.info('sleeping 5 minutes')
         time.sleep(5 * 60)

poller/search.py

@@ -36,7 +36,7 @@ def embed(text, input_type):
     return resp.embeddings.float[0]
 
 def search():
-    query = 'tazwell county caves'
+    query = 'links trip with not more than 2 people'
     query_embedding = embed(query, 'search_query')
 
     rows = conn.execute('SELECT * FROM embeddings ORDER BY embedding <=> %s::vector LIMIT 5', (query_embedding,)).fetchall()