Add spliter type param

Signed-off-by: shiyu22 <shiyu.chen@zilliz.com>

README.md

@@ -46,9 +46,13 @@ Create the operator via the following factory method
 
 **Parameters:**
 
-​	***chunk_size***: int
+​	***type***: str
 
-​	The size of each chunk, defaults to 300.
+​	The type of spliter, defaults to 'RecursiveCharacter'. You can set this parameter in ['[RecursiveCharacter](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/recursive_text_splitter.html)', '[Markdown](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/markdown.html)', '[PythonCode](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/python.html)', '[Character](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/character_text_splitter.html#)', '[NLTK](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/nltk.html)', '[Spacy](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/spacy.html)', '[Tiktoken](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/tiktoken_splitter.html)', '[HuggingFace](https://python.langchain.com/en/latest/modules/indexes/text_splitters/examples/huggingface_length_function.html)'].
+
+​    ***chunk_size***: int
+
+​	The maximum size of chunk, defaults to 300.
 
 <br />
 

requirements.txt

@@ -1 +1,4 @@
 langchain>=0.0.151
+transformers
+tiktoken
+spacy

spliter.py

@@ -1,15 +1,45 @@
 from towhee.operator import PyOperator
 from typing import List
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.text_splitter import (
+    RecursiveCharacterTextSplitter, 
+    MarkdownTextSplitter, 
+    PythonCodeTextSplitter,
+    CharacterTextSplitter,
+    NLTKTextSplitter,
+    SpacyTextSplitter,
+    TokenTextSplitter,
+    )
 
 
 class TextSpliter(PyOperator):
     '''Split data into a list.'''
-    def __init__(self, chunk_size: int = 300):
+    def __init__(self, type: str = 'RecursiveCharacter', chunk_size: int = 300, **kwargs):
         super().__init__()
-        self.splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size)
+        self.type = type
+        if self.type == 'RecursiveCharacter':
+            self.splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'Markdown':
+            self.splitter = MarkdownTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'PythonCode':
+            self.splitter = PythonCodeTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'Character':
+            self.splitter = CharacterTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'NLTK':
+            self.splitter = NLTKTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'Spacy':
+            self.splitter = SpacyTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'Tiktoken':
+            self.splitter = TokenTextSplitter(chunk_size=chunk_size, **kwargs)
+        elif self.type == 'HuggingFace':
+            if 'tokenizer' not in kwargs:
+                from transformers import GPT2TokenizerFast
+                kwargs['tokenizer'] = GPT2TokenizerFast.from_pretrained("gpt2")
+            self.splitter = CharacterTextSplitter.from_huggingface_tokenizer(chunk_size=chunk_size, **kwargs)
+        else:
+            raise ValueError("Invalid type. You need choose in ['RecursiveCharacter', 'Markdown', 'PythonCode' \
+                             'Character', 'NLTK', 'Spacy', 'Tiktoken', 'HuggingFace'].")
+        
 
     def __call__(self, data: str) -> List[str]:
-        texts = self.splitter.create_documents([data])
-        docs = self.splitter.split_documents(texts)
-        return [str(doc.page_content) for doc in docs]
+        texts = self.splitter.split_text(data)
+        return texts