Move LLM-related components into LLM module (#74)

* Move splitter into indexing module
* Rename post_processing module to parsers
* Migrate LLM-specific composite pipelines into llms module

This change moves the `splitters` module into `indexing` module. The `indexing` module will be created soon, to house `indexing`-related components.

This change renames `post_processing` module into `parsers` module. Post-processing is a generic term which provides very little information. In the future, we will add other extractors into the `parser` module, like Metadata extractor...

This change migrates the composite elements into `llms` module. These elements heavily assume that the internal nodes are llm-specific. As a result, migrating these elements into `llms` module will make them more discoverable, and simplify code base structure.

knowledgehub/indexing/splitters.py

@@ -0,0 +1,70 @@
+from typing import Any, List, Sequence, Type
+
+from llama_index.node_parser import (
+    SentenceWindowNodeParser as LISentenceWindowNodeParser,
+)
+from llama_index.node_parser import SimpleNodeParser as LISimpleNodeParser
+from llama_index.node_parser.interface import NodeParser
+from llama_index.text_splitter import TokenTextSplitter
+
+from ..base import BaseComponent, Document
+
+__all__ = ["TokenTextSplitter"]
+
+
+class LINodeParser(BaseComponent):
+    _parser_class: Type[NodeParser]
+
+    def __init__(self, *args, **kwargs):
+        if self._parser_class is None:
+            raise AttributeError(
+                "Require `_parser_class` to set a NodeParser class from LlamarIndex"
+            )
+        self._parser = self._parser_class(*args, **kwargs)
+        super().__init__()
+
+    def __setattr__(self, name: str, value: Any) -> None:
+        if name.startswith("_") or name in self._protected_keywords():
+            return super().__setattr__(name, value)
+
+        return setattr(self._parser, name, value)
+
+    def __getattr__(self, name: str) -> Any:
+        return getattr(self._parser, name)
+
+    def get_nodes_from_documents(
+        self,
+        documents: Sequence[Document],
+        show_progress: bool = False,
+    ) -> List[Document]:
+        documents = self._parser.get_nodes_from_documents(
+            documents=documents, show_progress=show_progress
+        )
+        # convert Document to new base class from kotaemon
+        converted_documents = [Document.from_dict(doc.to_dict()) for doc in documents]
+        return converted_documents
+
+    def run(
+        self,
+        documents: Sequence[Document],
+        show_progress: bool = False,
+    ) -> List[Document]:
+        return self.get_nodes_from_documents(
+            documents=documents, show_progress=show_progress
+        )
+
+
+class SimpleNodeParser(LINodeParser):
+    _parser_class = LISimpleNodeParser
+
+    def __init__(self, *args, **kwargs):
+        chunk_size = kwargs.pop("chunk_size", 512)
+        chunk_overlap = kwargs.pop("chunk_overlap", 0)
+        kwargs["text_splitter"] = TokenTextSplitter(
+            chunk_size=chunk_size, chunk_overlap=chunk_overlap
+        )
+        super().__init__(*args, **kwargs)
+
+
+class SentenceWindowNodeParser(LINodeParser):
+    _parser_class = LISentenceWindowNodeParser