talk-to-your-docs / whatsapp_chat_custom.py
arslan-ahmed's picture
initial push
85c4fe0
# created custom class for WhatsAppChatLoader - because original langchain one isnt working
import re
from pathlib import Path
from typing import List
from langchain.docstore.document import Document
from langchain.document_loaders.base import BaseLoader
def concatenate_rows(date: str, sender: str, text: str) -> str:
"""Combine message information in a readable format ready to be used."""
return f"{sender} on {date}: {text}\n\n"
# def concatenate_rows(date: str, sender: str, text: str) -> str:
# """Combine message information in a readable format ready to be used."""
# return f"{text}\n"
class WhatsAppChatLoader(BaseLoader):
"""Load `WhatsApp` messages text file."""
def __init__(self, path: str):
"""Initialize with path."""
self.file_path = path
def load(self) -> List[Document]:
"""Load documents."""
p = Path(self.file_path)
text_content = ""
ignore_lines = ["This message was deleted", "<Media omitted>"]
#########################################################################################
# original code from langchain replaced with this code
#########################################################################################
# use https://whatstk.streamlit.app/ to get CSV
import pandas as pd
df = pd.read_csv(p)[['date', 'username', 'message']]
for i,row in df.iterrows():
date = row['date']
sender = row['username']
text = row['message']
if not any(x in text for x in ignore_lines):
text_content += concatenate_rows(date, sender, text)
metadata = {"source": str(p)}
return [Document(page_content=text_content.strip(), metadata=metadata)]