diff --git a/requirements.txt b/requirements.txt
index db056ac..7e5c0e9 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,2 +1,3 @@
-streamlit
-langchain
+tiktoken==0.4.0
+langchain==0.0.222
+streamlit==1.25.0
diff --git a/splitter.py b/splitter.py
index becb08b..4e8661d 100644
--- a/splitter.py
+++ b/splitter.py
@@ -1,20 +1,21 @@
 import streamlit as st
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.text_splitter import RecursiveCharacterTextSplitter, CharacterTextSplitter
 
 
 # Streamlit UI
-st.title("Document Splitter")
-
-col1, col2 = st.columns([5, 5])
+st.title("Document Splitter Playground")
+st.info("Split a document into chunks using a `Document Splitter` with input `chunk_size` and `chunk_overlap`")
+col1, col2, col3 = st.columns([1, 1, 1])
 
 with col1:
-    chunk_size = st.number_input(min_value=1, label="Chunk Size", value=1000)
+    chunk_size = st.number_input(min_value=1, label="Chunk Size (Characters or Tokens)", value=1000)
 
+with col2:
     # Setting the max value of chunk_overlap based on chunk_size
     chunk_overlap = st.number_input(
         min_value=1,
         max_value=chunk_size - 1,
-        label="Chunk Overlap",
+        label="Chunk Overlap (Characters or Tokens)",
         value=int(chunk_size * 0.2),
     )
 
@@ -22,37 +23,74 @@ with col1:
     if chunk_overlap >= chunk_size:
         st.warning("Chunk Overlap should be less than Chunk Length!")
 
-with col2:
-    splitter = st.selectbox(
-        "Select a Document Splitter", ["RecursiveCharacterTextSplitter"]
+with col3:
+    splitter_choice = st.selectbox(
+        "Select a Document Splitter", ["Characters", "Recursive Characters", "Tokens"]
     )
 
-import_text = """```python
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+if splitter_choice == "Characters":
+    import_text = """```python
+    from langchain.text_splitter import CharacterTextSplitter
 
+    splitter = CharacterTextSplitter(
+        separator = " ", # Split character (default \\n\\n)
+        chunk_size={chunk_size}, # Measure chunk length by number of characters
+        chunk_overlap={chunk_overlap}
+    )
+    text = "foo bar"
+    splits = splitter.split_text(text)
+    """.format(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
 
-splitter = RecursiveCharacterTextSplitter(
-    chunk_size={chunk_size}, chunk_overlap={chunk_overlap}
-)
-text = "foo bar"
-splits = splitter.split_text(text)
-""".format(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
+elif splitter_choice == "Recursive Characters":
+    import_text = """```python
+    from langchain.text_splitter import RecursiveCharacterTextSplitter
+    # The default list of split characters is [\\n\\n, \\n, " ", ""]
+    # Tries to split on them in order until the chunks are small enough
+    # Keep paragraphs, sentences, words together as long as possible
+    splitter = RecursiveCharacterTextSplitter(
+        chunk_size={chunk_size}, 
+        chunk_overlap={chunk_overlap}
+    )
+    text = "foo bar"
+    splits = splitter.split_text(text)
+    """.format(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
+
+else: # Tokens
+    import_text = """```python
+    from langchain.text_splitter import CharacterTextSplitter
+
+    splitter = CharacterTextSplitter.from_tiktoken_encoder(
+        separator = " ", # Split character (default \\n\\n)
+        chunk_size={chunk_size}, # Measure chunk length by number of characters
+        chunk_overlap={chunk_overlap}
+    )
+    text = "foo bar"
+    splits = splitter.split_text(text)
+    """.format(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
 
 st.info(import_text)
 
-
 # Box for pasting document
 doc = st.text_area("Paste your document here:")
 
 # Split document button
 if st.button("Split Document"):
-    splitter = RecursiveCharacterTextSplitter(
-        chunk_size=chunk_size, chunk_overlap=chunk_overlap
-    )
+    # Choose splitter
+    if splitter_choice == "Characters":
+        splitter = CharacterTextSplitter(separator = " ", 
+                                         chunk_size=chunk_size, 
+                                         chunk_overlap=chunk_overlap)
+    elif splitter_choice == "Recursive Characters":
+        splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, 
+                                                  chunk_overlap=chunk_overlap)
+    else: # Tokens
+        splitter = CharacterTextSplitter.from_tiktoken_encoder(separator = " ",
+                                                               chunk_size=chunk_size,
+                                                               chunk_overlap=chunk_overlap)
+    # Split the document
     splits = splitter.split_text(doc)
 
     # Display the splits
-    st.subheader("Document Splits:")
     for idx, split in enumerate(splits, start=1):
         st.text_area(
             f"Split {idx}", split, height=200