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#

# Source code for langchain.document_loaders.telegram

    """Loader that loads Telegram chat json dump."""
    import json
    from pathlib import Path
    from typing import List

    from langchain.docstore.document import Document
    from langchain.document_loaders.base import BaseLoader

    def concatenate_rows(row: dict) -> str:
        """Combine message information in a readable format ready to be used."""
        date = row["date"]
        sender = row["from"]
        text = row["text"]
        return f"{sender} on {date}: {text}\n\n"

    class TelegramChatLoader(BaseLoader):
        """Loader that loads Telegram chat json directory dump."""

        def __init__(self, path: str):
            """Initialize with path."""
            self.file_path = path

        def load(self) -> List[Document]:
            """Load documents."""
            try:
                import pandas as pd
            except ImportError:
                raise ValueError(
                    "pandas is needed for Telegram loader, "
                    "please install with `pip install pandas`"
                )
            p = Path(self.file_path)

            with open(p, encoding="utf8") as f:
                d = json.load(f)

            normalized_messages = pd.json_normalize(d["messages"])
            df_normalized_messages = pd.DataFrame(normalized_messages)

            # Only keep plain text messages (no services, links, hashtags, code, bold...)
            df_filtered = df_normalized_messages[
                (df_normalized_messages.type == "message")
                & (df_normalized_messages.text.apply(lambda x: type(x) == str))
            ]

            df_filtered = df_filtered[["date", "text", "from"]]

            text = df_filtered.apply(concatenate_rows, axis=1).str.cat(sep="")

            metadata = {"source": str(p)}

            return [Document(page_content=text, metadata=metadata)]