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convert_speeches.py

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+TARGET = ".data/speeches.vert.shuffled"
+
+import os
+import re
+from typing import Dict
+
+import jsonlines
+from tqdm import tqdm
+
+
+def process_vert_format(vert_content: str) -> Dict[str, str]:
+    doc_pattern = re.compile(r'<doc[^>]*>.*?</doc>', re.DOTALL)
+
+    # Pattern to match document boundaries and extract metadata
+    metadata_pattern = re.compile(
+        r'<doc id="([^"]*)"\s+speaker="([^"]*)"\s+year="([^"]*)"\s+date="([^"]*)"\s+title="([^"]*)"\s+office="([^"]*)"\s+occasion="([^"]*)"\s+medium="([^"]*)"\s+source="([^"]*)"\s+link="([^"]*)"\s+altsource="([^"]*)"\s+status="([^"]*)"\s+notes="([^"]*)">'
+    )
+
+    block_pattern = re.compile(r'<block[^>]*>.*?</block>', re.DOTALL)
+
+    # Pattern to remove whitespace before punctuation
+    ws_before_punct = re.compile(r'\s+([.,!?:;])')
+
+    # Find all documents
+    documents = re.findall(doc_pattern, vert_content)
+    processed_documents = {}
+
+    for doc in tqdm(documents):
+        # Extract metadata
+        metadata_match = re.search(metadata_pattern, doc)
+        if metadata_match:
+            doc_id = metadata_match.group(1)
+            speaker = metadata_match.group(2)
+            year = metadata_match.group(3)
+            date = metadata_match.group(4)
+            title = metadata_match.group(5)
+            office = metadata_match.group(6)
+            occasion = metadata_match.group(7)
+            medium = metadata_match.group(8)
+            source = metadata_match.group(9)
+            link = metadata_match.group(10)
+            altsource = metadata_match.group(11)
+            status = metadata_match.group(12)
+            notes = metadata_match.group(13)
+
+            metadata_str = (f"Řečník: {speaker}, "
+                            f"Rok: {year}, "
+                            f"Datum: {date}, "
+                            f"Název: {title}, "
+                            f"Úřad: {office}, "
+                            f"Příležitost: {occasion}, ")
+
+        else:
+            raise ValueError("Metadata not found in document")
+
+        for bid, block in enumerate(re.findall(block_pattern, doc)):
+            # remove tags from each line, and join text
+            tokens = [line.split("\t")[0].strip() for line in block.split("\n") if line.strip() != ""]
+            doc_text = " ".join(tokens)
+
+            # remove any text with <...> tag
+            doc_text = re.sub(r'<[^>]*>', '', doc_text)
+
+            # replace more than one space with one space
+            doc_text = re.sub(r'\s+', ' ', doc_text).strip()
+
+            # remove whitespace before ., !, ?
+            doc_text = re.sub(ws_before_punct, r'\1', doc_text)
+
+            # - sometimes lines in oral are empty? e.g. 08A009N // REMOVE THESE LINES
+            if doc_text.strip() == "":
+                continue
+
+            processed_documents[f"{doc_id}_{bid}"] = metadata_str + "\n" + doc_text
+
+    return processed_documents
+
+
+# Read the content from the file
+with open(TARGET, "r") as f:
+    vert_content = f.read()
+
+# Process the content
+processed_documents = process_vert_format(vert_content)
+
+# write all splits into same json file in  .data/hf_dataset/cnc_fictree/test.jsonl
+OF = ".data/hf_dataset/cnc_prez_prejavy/test.jsonl"
+os.makedirs(os.path.dirname(OF), exist_ok=True)
+with jsonlines.open(OF, "w") as writer:
+    for doc_id, doc in list(processed_documents.items()):
+        writer.write({"text": doc, "id": doc_id})