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split_slide.py

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+import json
+import nltk
+from nltk.tokenize import sent_tokenize, word_tokenize
+
+
+# nltk.download('punkt')
+
+
+def split_content_by_tokens(data, max_tokens=200):
+    """
+    Splits content into chunks of approximately max_tokens, respecting sentence boundaries.
+
+    Args:
+        data (list): List of dictionaries containing "page_number" and "content".
+        max_tokens (int): Maximum number of tokens per chunk.
+
+    Returns:
+        list: A new list of dictionaries with split content.
+    """
+    processed_data = []
+    chunk_id = 1
+    prev_page = -1
+    current_chunk = []
+    current_token_count = 0
+
+    for record in data:
+        page_number = record.get("page_number")
+        content = record.get("content", "")
+
+        if prev_page == -1:
+            prev_page = page_number
+        elif prev_page != page_number:  # not the same page
+            if current_chunk:
+                processed_data.append({
+                    "id": chunk_id,
+                    "page_number": prev_page,
+                    "content": " ".join(current_chunk),
+                    "type": "slide"
+                })
+                chunk_id += 1
+                current_chunk = []
+                current_token_count = 0
+                prev_page = page_number
+
+        # Tokenize content into sentences
+        sentences = sent_tokenize(content)
+
+        for sentence in sentences:
+            sentence_tokens = word_tokenize(sentence)
+            sentence_length = len(sentence_tokens)
+
+            # Check if adding this sentence exceeds the token limit
+            if current_token_count + sentence_length > max_tokens:
+                # Save the current chunk
+                if current_chunk:
+                    processed_data.append({
+                        "id": chunk_id,
+                        "page_number": page_number,
+                        "content": " ".join(current_chunk),
+                        "type": "slide"
+                    })
+                    chunk_id += 1
+                # Start a new chunk
+                current_chunk = []
+                current_token_count = 0
+
+            # Add the current sentence to the chunk
+            current_chunk.append(sentence)
+            current_token_count += sentence_length
+
+    # Save the last chunk
+    if current_chunk:
+        processed_data.append({
+            "id": chunk_id+1,
+            "page_number": prev_page,
+            "content": " ".join(current_chunk),
+            "type": "slide"
+        })
+
+    return processed_data
+
+
+if __name__ == "__main__":
+    # Load your JSON file
+    input_file = "/Users/yuchenhua/Coding/pdf/1121ppt.json"
+    output_file = "1121_ppt.json"
+
+    with open(input_file, 'r') as f:
+        data = json.load(f)
+
+    # Process the data
+    split_data = split_content_by_tokens(data)
+
+    # Save the processed data to a new JSON file
+    with open(output_file, 'w') as f:
+        json.dump(split_data, f, indent=4)
+
+    print(f"Processed content has been saved to {output_file}")