Buildsilver script suppors reservoir sampling so it can sample 100M+ …

…paths now efficiently

pdelfin/silver_data/buildsilver.py

@@ -6,7 +6,6 @@
 import argparse
 import boto3
 import json
-from openai import OpenAI
 from pypdf import PdfReader
 from tqdm import tqdm
 from typing import Generator
@@ -31,8 +30,6 @@ def _build_prompt(base_text: str) -> str:
         f"RAW_TEXT_START\n{base_text}\nRAW_TEXT_END"
     )
 
-# Initialize OpenAI client
-openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 pdf_filter = PdfFilter()
 
 def build_page_query(local_pdf_path: str, pretty_pdf_path: str, page: int) -> dict:
@@ -145,30 +142,68 @@ def main():
     parser.add_argument("--first_n_pages", type=int, default=0, help="Always sample the first N pages of each PDF.")
     parser.add_argument("--max_sample_pages", type=int, default=15, help="Max number of pages to sample per PDF.")
     parser.add_argument("--output", type=str, default="openai_batch_data", help="Output destination")
+    parser.add_argument("--reservoir_size", type=int, default=None,
+                        help="Size of the reservoir for sampling paths. Defaults to 10x num_sample_docs.")
     args = parser.parse_args()
 
-    # Load PDF paths from glob or path_list
+    # Set default reservoir_size if not provided
+    if args.reservoir_size is None:
+        args.reservoir_size = 10 * args.num_sample_docs
+
+    # Initialize reservoir sampling variables
     pdf_paths = []
+    n = 0  # Total number of items seen
+
+    # Load PDF paths from glob or path_list using reservoir sampling
     if args.glob_path:
         if args.glob_path.startswith("s3://"):
-            # Handle S3 globbing using boto3
+            # Handle S3 globbing using boto3 with pagination
             parsed = urlparse(args.glob_path)
             s3 = boto3.client('s3')
             bucket_name = parsed.netloc
             prefix = os.path.dirname(parsed.path.lstrip('/')) + "/"
-            response = s3.list_objects_v2(Bucket=bucket_name, Prefix=prefix)
-            for obj in response.get('Contents', []):
-                if obj['Key'].endswith('.pdf'):
-                    pdf_paths.append(f"s3://{bucket_name}/{obj['Key']}")
+            paginator = s3.get_paginator('list_objects_v2')
+            page_iterator = paginator.paginate(Bucket=bucket_name, Prefix=prefix)
+
+            for page in page_iterator:
+                for obj in page.get('Contents', []):
+                    if obj['Key'].endswith('.pdf'):
+                        n += 1
+                        path = f"s3://{bucket_name}/{obj['Key']}"
+                        if len(pdf_paths) < args.reservoir_size:
+                            pdf_paths.append(path)
+                        else:
+                            s = random.randint(1, n)
+                            if s <= args.reservoir_size:
+                                pdf_paths[s - 1] = path
         else:
-            # Handle local globbing
-            pdf_paths = glob.glob(args.glob_path)
+            # Handle local globbing using glob.iglob()
+            for path in glob.iglob(args.glob_path, recursive=True):
+                n += 1
+                if len(pdf_paths) < args.reservoir_size:
+                    pdf_paths.append(path)
+                else:
+                    s = random.randint(1, n)
+                    if s <= args.reservoir_size:
+                        pdf_paths[s - 1] = path
     elif args.path_list:
         with open(args.path_list, 'r') as f:
-            pdf_paths = [line.strip() for line in f]
-
+            for line in f:
+                n += 1
+                path = line.strip()
+                if len(pdf_paths) < args.reservoir_size:
+                    pdf_paths.append(path)
+                else:
+                    s = random.randint(1, n)
+                    if s <= args.reservoir_size:
+                        pdf_paths[s - 1] = path
+
+    # Shuffle the reservoir
     random.shuffle(pdf_paths)
 
+    print(f"Loaded and shuffled {len(pdf_paths)} paths to use.")
+
+    # Rest of the code remains the same
     cur_file_num = 0
     output_dir = args.output
     max_file_size = 99 * 1024 * 1024  # 99MB in bytes
@@ -184,7 +219,7 @@ def main():
     # Counter to track PDFs that produce at least one output
     pdfs_with_output = 0
 
-   # Using ThreadPoolExecutor to process files concurrently
+    # Using ThreadPoolExecutor to process files concurrently
     with ThreadPoolExecutor(max_workers=60) as executor:
         futures = []