langchain/libs/community/langchain_community/document_loaders/whatsapp_chat.py
Bagatur ed58eeb9c5
community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
Moved the following modules to new package langchain-community in a backwards compatible fashion:

```
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
```

Moved the following to core
```
mv langchain/langchain/utils/json_schema.py core/langchain_core/utils
mv langchain/langchain/utils/html.py core/langchain_core/utils
mv langchain/langchain/utils/strings.py core/langchain_core/utils
cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py
rm langchain/langchain/utils/env.py
```

See .scripts/community_split/script_integrations.sh for all changes
2023-12-11 13:53:30 -08:00

66 lines
1.7 KiB
Python

import re
from pathlib import Path
from typing import List
from langchain_core.documents import Document
from langchain_community.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"
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 = ""
with open(p, encoding="utf8") as f:
lines = f.readlines()
message_line_regex = r"""
\[?
(
\d{1,4}
[\/.]
\d{1,2}
[\/.]
\d{1,4}
,\s
\d{1,2}
:\d{2}
(?:
:\d{2}
)?
(?:[\s_](?:AM|PM))?
)
\]?
[\s-]*
([~\w\s]+)
[:]+
\s
(.+)
"""
ignore_lines = ["This message was deleted", "<Media omitted>"]
for line in lines:
result = re.match(
message_line_regex, line.strip(), flags=re.VERBOSE | re.IGNORECASE
)
if result:
date, sender, text = result.groups()
if text not in ignore_lines:
text_content += concatenate_rows(date, sender, text)
metadata = {"source": str(p)}
return [Document(page_content=text_content, metadata=metadata)]