Files
t6_mem0/embedchain/chunkers/base_chunker.py
2023-07-15 19:41:55 +05:30

50 lines
1.4 KiB
Python

import hashlib
class BaseChunker:
def __init__(self, text_splitter):
"""Initialize the chunker."""
self.text_splitter = text_splitter
def create_chunks(self, loader, src):
"""
Loads data and chunks it.
:param loader: The loader which's `load_data` method is used to create
the raw data.
:param src: The data to be handled by the loader. Can be a URL for
remote sources or local content for local loaders.
"""
documents = []
ids = []
idMap = {}
datas = loader.load_data(src)
metadatas = []
for data in datas:
content = data["content"]
meta_data = data["meta_data"]
url = meta_data["url"]
chunks = self.get_chunks(content)
for chunk in chunks:
chunk_id = hashlib.sha256((chunk + url).encode()).hexdigest()
if idMap.get(chunk_id) is None:
idMap[chunk_id] = True
ids.append(chunk_id)
documents.append(chunk)
metadatas.append(meta_data)
return {
"documents": documents,
"ids": ids,
"metadatas": metadatas,
}
def get_chunks(self, content):
"""
Returns chunks using text splitter instance.
Override in child class if custom logic.
"""
return self.text_splitter.split_text(content)