mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +00:00
66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
|
import datetime
|
||
|
import json
|
||
|
from typing import List
|
||
|
|
||
|
from langchain_core.documents import Document
|
||
|
|
||
|
from langchain_community.document_loaders.base import BaseLoader
|
||
|
|
||
|
|
||
|
def concatenate_rows(message: dict, title: str) -> str:
|
||
|
"""
|
||
|
Combine message information in a readable format ready to be used.
|
||
|
Args:
|
||
|
message: Message to be concatenated
|
||
|
title: Title of the conversation
|
||
|
|
||
|
Returns:
|
||
|
Concatenated message
|
||
|
"""
|
||
|
if not message:
|
||
|
return ""
|
||
|
|
||
|
sender = message["author"]["role"] if message["author"] else "unknown"
|
||
|
text = message["content"]["parts"][0]
|
||
|
date = datetime.datetime.fromtimestamp(message["create_time"]).strftime(
|
||
|
"%Y-%m-%d %H:%M:%S"
|
||
|
)
|
||
|
return f"{title} - {sender} on {date}: {text}\n\n"
|
||
|
|
||
|
|
||
|
class ChatGPTLoader(BaseLoader):
|
||
|
"""Load conversations from exported `ChatGPT` data."""
|
||
|
|
||
|
def __init__(self, log_file: str, num_logs: int = -1):
|
||
|
"""Initialize a class object.
|
||
|
|
||
|
Args:
|
||
|
log_file: Path to the log file
|
||
|
num_logs: Number of logs to load. If 0, load all logs.
|
||
|
"""
|
||
|
self.log_file = log_file
|
||
|
self.num_logs = num_logs
|
||
|
|
||
|
def load(self) -> List[Document]:
|
||
|
with open(self.log_file, encoding="utf8") as f:
|
||
|
data = json.load(f)[: self.num_logs] if self.num_logs else json.load(f)
|
||
|
|
||
|
documents = []
|
||
|
for d in data:
|
||
|
title = d["title"]
|
||
|
messages = d["mapping"]
|
||
|
text = "".join(
|
||
|
[
|
||
|
concatenate_rows(messages[key]["message"], title)
|
||
|
for idx, key in enumerate(messages)
|
||
|
if not (
|
||
|
idx == 0
|
||
|
and messages[key]["message"]["author"]["role"] == "system"
|
||
|
)
|
||
|
]
|
||
|
)
|
||
|
metadata = {"source": str(self.log_file)}
|
||
|
documents.append(Document(page_content=text, metadata=metadata))
|
||
|
|
||
|
return documents
|