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58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
"""Loader that loads Facebook chat json dump."""
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import datetime
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import json
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from pathlib import Path
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from typing import List
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from langchain.docstore.document import Document
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from langchain.document_loaders.base import BaseLoader
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def concatenate_rows(row: dict) -> str:
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"""Combine message information in a readable format ready to be used."""
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sender = row["sender_name"]
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text = row["content"]
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date = datetime.datetime.fromtimestamp(row["timestamp_ms"] / 1000).strftime(
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"%Y-%m-%d %H:%M:%S"
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)
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return f"{sender} on {date}: {text}\n\n"
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class FacebookChatLoader(BaseLoader):
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"""Loader that loads Facebook messages json directory dump."""
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def __init__(self, path: str):
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"""Initialize with path."""
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self.file_path = path
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def load(self) -> List[Document]:
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"""Load documents."""
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try:
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import pandas as pd
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except ImportError:
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raise ValueError(
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"pandas is needed for Facebook chat loader, "
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"please install with `pip install pandas`"
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)
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p = Path(self.file_path)
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with open(p, encoding="utf8") as f:
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d = json.load(f)
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normalized_messages = pd.json_normalize(d["messages"])
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df_normalized_messages = pd.DataFrame(normalized_messages)
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# Only keep plain text messages
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# (no services, nor links, hashtags, code, bold ...)
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df_filtered = df_normalized_messages[
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(df_normalized_messages.content.apply(lambda x: type(x) == str))
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]
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df_filtered = df_filtered[["timestamp_ms", "content", "sender_name"]]
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text = df_filtered.apply(concatenate_rows, axis=1).str.cat(sep="")
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metadata = {"source": str(p)}
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return [Document(page_content=text, metadata=metadata)]
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