diff --git a/api/tests/unit_tests/core/rag/splitter/__init__.py b/api/tests/unit_tests/core/rag/splitter/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/api/tests/unit_tests/core/rag/splitter/test_text_splitter.py b/api/tests/unit_tests/core/rag/splitter/test_text_splitter.py
new file mode 100644
index 0000000000..7d246ac3cc
--- /dev/null
+++ b/api/tests/unit_tests/core/rag/splitter/test_text_splitter.py
@@ -0,0 +1,1908 @@
+"""
+Comprehensive test suite for text splitter functionality.
+
+This module provides extensive testing coverage for text splitting operations
+used in RAG (Retrieval-Augmented Generation) systems. Text splitters are crucial
+for breaking down large documents into manageable chunks while preserving context
+and semantic meaning.
+
+## Test Coverage Overview
+
+### Core Splitter Types Tested:
+1. **RecursiveCharacterTextSplitter**: Main splitter that recursively tries different
+   separators (paragraph -> line -> word -> character) to split text appropriately.
+
+2. **TokenTextSplitter**: Splits text based on token count using tiktoken library,
+   useful for LLM context window management.
+
+3. **EnhanceRecursiveCharacterTextSplitter**: Enhanced version with custom token
+   counting support via embedding models or GPT2 tokenizer.
+
+4. **FixedRecursiveCharacterTextSplitter**: Prioritizes a fixed separator before
+   falling back to recursive splitting, useful for structured documents.
+
+### Test Categories:
+
+#### Helper Functions (TestSplitTextWithRegex, TestSplitTextOnTokens)
+- Tests low-level splitting utilities
+- Regex pattern handling
+- Token-based splitting mechanics
+
+#### Core Functionality (TestRecursiveCharacterTextSplitter, TestTokenTextSplitter)
+- Initialization and configuration
+- Basic splitting operations
+- Separator hierarchy behavior
+- Chunk size and overlap handling
+
+#### Enhanced Splitters (TestEnhanceRecursiveCharacterTextSplitter, TestFixedRecursiveCharacterTextSplitter)
+- Custom encoder integration
+- Fixed separator prioritization
+- Character-level splitting with overlap
+- Multilingual separator support
+
+#### Metadata Preservation (TestMetadataPreservation)
+- Metadata copying across chunks
+- Start index tracking
+- Multiple document processing
+- Complex metadata types (strings, lists, dicts)
+
+#### Edge Cases (TestEdgeCases)
+- Empty text, single characters, whitespace
+- Unicode and emoji handling
+- Very small/large chunk sizes
+- Zero overlap scenarios
+- Mixed separator types
+
+#### Advanced Scenarios (TestAdvancedSplittingScenarios)
+- Markdown, HTML, JSON document splitting
+- Technical documentation
+- Code and mixed content
+- Lists, tables, quotes
+- URLs and email content
+
+#### Configuration Testing (TestSplitterConfiguration)
+- Custom length functions
+- Different separator orderings
+- Extreme overlap ratios
+- Start index accuracy
+- Regex pattern separators
+
+#### Error Handling (TestErrorHandlingAndRobustness)
+- Invalid inputs (None, empty)
+- Extreme parameters
+- Special characters (unicode, control chars)
+- Repeated separators
+- Empty separator lists
+
+#### Performance (TestPerformanceCharacteristics)
+- Chunk size consistency
+- Information preservation
+- Deterministic behavior
+- Chunk count estimation
+
+## Usage Examples
+
+```python
+# Basic recursive splitting
+splitter = RecursiveCharacterTextSplitter(
+    chunk_size=1000,
+    chunk_overlap=200,
+    separators=["\n\n", "\n", " ", ""]
+)
+chunks = splitter.split_text(long_text)
+
+# With metadata preservation
+documents = splitter.create_documents(
+    texts=[text1, text2],
+    metadatas=[{"source": "doc1.pdf"}, {"source": "doc2.pdf"}]
+)
+
+# Token-based splitting
+token_splitter = TokenTextSplitter(
+    encoding_name="gpt2",
+    chunk_size=500,
+    chunk_overlap=50
+)
+token_chunks = token_splitter.split_text(text)
+```
+
+## Test Execution
+
+Run all tests:
+    pytest tests/unit_tests/core/rag/splitter/test_text_splitter.py -v
+
+Run specific test class:
+    pytest tests/unit_tests/core/rag/splitter/test_text_splitter.py::TestRecursiveCharacterTextSplitter -v
+
+Run with coverage:
+    pytest tests/unit_tests/core/rag/splitter/test_text_splitter.py --cov=core.rag.splitter
+
+## Notes
+
+- Some tests are skipped if tiktoken library is not installed (TokenTextSplitter tests)
+- Tests use pytest fixtures for reusable test data
+- All tests follow Arrange-Act-Assert pattern
+- Tests are organized by functionality in classes for better organization
+"""
+
+import string
+from unittest.mock import Mock, patch
+
+import pytest
+
+from core.rag.models.document import Document
+from core.rag.splitter.fixed_text_splitter import (
+    EnhanceRecursiveCharacterTextSplitter,
+    FixedRecursiveCharacterTextSplitter,
+)
+from core.rag.splitter.text_splitter import (
+    RecursiveCharacterTextSplitter,
+    Tokenizer,
+    TokenTextSplitter,
+    _split_text_with_regex,
+    split_text_on_tokens,
+)
+
+# ============================================================================
+# Test Fixtures
+# ============================================================================
+
+
+@pytest.fixture
+def sample_text():
+    """Provide sample text for testing."""
+    return """This is the first paragraph. It contains multiple sentences.
+
+This is the second paragraph. It also has several sentences.
+
+This is the third paragraph with more content."""
+
+
+@pytest.fixture
+def long_text():
+    """Provide long text for testing chunking."""
+    return " ".join([f"Sentence number {i}." for i in range(100)])
+
+
+@pytest.fixture
+def multilingual_text():
+    """Provide multilingual text for testing."""
+    return "This is English. 这是中文。日本語です。한국어입니다。"
+
+
+@pytest.fixture
+def code_text():
+    """Provide code snippet for testing."""
+    return """def hello_world():
+    print("Hello, World!")
+    return True
+
+def another_function():
+    x = 10
+    y = 20
+    return x + y"""
+
+
+@pytest.fixture
+def markdown_text():
+    """
+    Provide markdown formatted text for testing.
+
+    This fixture simulates a typical markdown document with headers,
+    paragraphs, and code blocks.
+    """
+    return """# Main Title
+
+This is an introduction paragraph with some content.
+
+## Section 1
+
+Content for section 1 with multiple sentences. This should be split appropriately.
+
+### Subsection 1.1
+
+More detailed content here.
+
+## Section 2
+
+Another section with different content.
+
+```python
+def example():
+    return "code"
+```
+
+Final paragraph."""
+
+
+@pytest.fixture
+def html_text():
+    """
+    Provide HTML formatted text for testing.
+
+    Tests how splitters handle structured markup content.
+    """
+    return """<html>
+<head><title>Test</title></head>
+<body>
+<h1>Header</h1>
+<p>First paragraph with content.</p>
+<p>Second paragraph with more content.</p>
+<div>Nested content here.</div>
+</body>
+</html>"""
+
+
+@pytest.fixture
+def json_text():
+    """
+    Provide JSON formatted text for testing.
+
+    Tests splitting of structured data formats.
+    """
+    return """{
+    "name": "Test Document",
+    "content": "This is the main content",
+    "metadata": {
+        "author": "John Doe",
+        "date": "2024-01-01"
+    },
+    "sections": [
+        {"title": "Section 1", "text": "Content 1"},
+        {"title": "Section 2", "text": "Content 2"}
+    ]
+}"""
+
+
+@pytest.fixture
+def technical_text():
+    """
+    Provide technical documentation text.
+
+    Simulates API documentation or technical writing with
+    specific terminology and formatting.
+    """
+    return """API Endpoint: /api/v1/users
+
+Description: Retrieves user information from the database.
+
+Parameters:
+- user_id (required): The unique identifier for the user
+- include_metadata (optional): Boolean flag to include additional metadata
+
+Response Format:
+{
+    "user_id": "12345",
+    "name": "John Doe",
+    "email": "john@example.com"
+}
+
+Error Codes:
+- 404: User not found
+- 401: Unauthorized access
+- 500: Internal server error"""
+
+
+# ============================================================================
+# Test Helper Functions
+# ============================================================================
+
+
+class TestSplitTextWithRegex:
+    """
+    Test the _split_text_with_regex helper function.
+
+    This helper function is used internally by text splitters to split
+    text using regex patterns. It supports keeping or removing separators
+    and handles special regex characters properly.
+    """
+
+    def test_split_with_separator_keep(self):
+        """
+        Test splitting text with separator kept.
+
+        When keep_separator=True, the separator should be appended to each
+        chunk (except possibly the last one). This is useful for maintaining
+        document structure like paragraph breaks.
+        """
+        text = "Hello\nWorld\nTest"
+        result = _split_text_with_regex(text, "\n", keep_separator=True)
+        # Each line should keep its newline character
+        assert result == ["Hello\n", "World\n", "Test"]
+
+    def test_split_with_separator_no_keep(self):
+        """Test splitting text without keeping separator."""
+        text = "Hello\nWorld\nTest"
+        result = _split_text_with_regex(text, "\n", keep_separator=False)
+        assert result == ["Hello", "World", "Test"]
+
+    def test_split_empty_separator(self):
+        """Test splitting with empty separator (character by character)."""
+        text = "ABC"
+        result = _split_text_with_regex(text, "", keep_separator=False)
+        assert result == ["A", "B", "C"]
+
+    def test_split_filters_empty_strings(self):
+        """Test that empty strings and newlines are filtered out."""
+        text = "Hello\n\nWorld"
+        result = _split_text_with_regex(text, "\n", keep_separator=False)
+        # Empty strings between consecutive separators should be filtered
+        assert "" not in result
+        assert result == ["Hello", "World"]
+
+    def test_split_with_special_regex_chars(self):
+        """Test splitting with special regex characters in separator."""
+        text = "Hello.World.Test"
+        result = _split_text_with_regex(text, ".", keep_separator=False)
+        # The function escapes regex chars, so it should split correctly
+        # But empty strings are filtered, so we get the parts
+        assert len(result) >= 0  # May vary based on regex escaping
+        assert isinstance(result, list)
+
+
+class TestSplitTextOnTokens:
+    """Test the split_text_on_tokens function."""
+
+    def test_basic_token_splitting(self):
+        """Test basic token-based splitting."""
+
+        # Mock tokenizer
+        def mock_encode(text: str) -> list[int]:
+            return [ord(c) for c in text]
+
+        def mock_decode(tokens: list[int]) -> str:
+            return "".join([chr(t) for t in tokens])
+
+        tokenizer = Tokenizer(chunk_overlap=2, tokens_per_chunk=5, decode=mock_decode, encode=mock_encode)
+
+        text = "ABCDEFGHIJ"
+        result = split_text_on_tokens(text=text, tokenizer=tokenizer)
+
+        # Should split into chunks of 5 with overlap of 2
+        assert len(result) > 1
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_token_splitting_with_overlap(self):
+        """Test that overlap is correctly applied in token splitting."""
+
+        def mock_encode(text: str) -> list[int]:
+            return list(range(len(text)))
+
+        def mock_decode(tokens: list[int]) -> str:
+            return "".join([str(t) for t in tokens])
+
+        tokenizer = Tokenizer(chunk_overlap=2, tokens_per_chunk=5, decode=mock_decode, encode=mock_encode)
+
+        text = string.digits
+        result = split_text_on_tokens(text=text, tokenizer=tokenizer)
+
+        # Verify we get multiple chunks
+        assert len(result) >= 2
+
+    def test_token_splitting_short_text(self):
+        """Test token splitting with text shorter than chunk size."""
+
+        def mock_encode(text: str) -> list[int]:
+            return [ord(c) for c in text]
+
+        def mock_decode(tokens: list[int]) -> str:
+            return "".join([chr(t) for t in tokens])
+
+        tokenizer = Tokenizer(chunk_overlap=2, tokens_per_chunk=100, decode=mock_decode, encode=mock_encode)
+
+        text = "Short"
+        result = split_text_on_tokens(text=text, tokenizer=tokenizer)
+
+        # Should return single chunk for short text
+        assert len(result) == 1
+        assert result[0] == text
+
+
+# ============================================================================
+# Test RecursiveCharacterTextSplitter
+# ============================================================================
+
+
+class TestRecursiveCharacterTextSplitter:
+    """
+    Test RecursiveCharacterTextSplitter functionality.
+
+    RecursiveCharacterTextSplitter is the main text splitting class that
+    recursively tries different separators (paragraph -> line -> word -> character)
+    to split text into chunks of appropriate size. This is the most commonly
+    used splitter for general text processing.
+    """
+
+    def test_initialization(self):
+        """
+        Test splitter initialization with default parameters.
+
+        Verifies that the splitter is properly initialized with the correct
+        chunk size, overlap, and default separator hierarchy.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10)
+        assert splitter._chunk_size == 100
+        assert splitter._chunk_overlap == 10
+        # Default separators: paragraph, line, space, character
+        assert splitter._separators == ["\n\n", "\n", " ", ""]
+
+    def test_initialization_custom_separators(self):
+        """Test splitter initialization with custom separators."""
+        custom_separators = ["\n\n\n", "\n\n", "\n", " "]
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10, separators=custom_separators)
+        assert splitter._separators == custom_separators
+
+    def test_chunk_overlap_validation(self):
+        """Test that chunk overlap cannot exceed chunk size."""
+        with pytest.raises(ValueError, match="larger chunk overlap"):
+            RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=150)
+
+    def test_split_by_paragraph(self, sample_text):
+        """Test splitting text by paragraphs."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10)
+        result = splitter.split_text(sample_text)
+
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+        # Verify chunks respect size limit (with some tolerance for overlap)
+        assert all(len(chunk) <= 150 for chunk in result)
+
+    def test_split_by_newline(self):
+        """Test splitting by newline when paragraphs are too large."""
+        text = "Line 1\nLine 2\nLine 3\nLine 4\nLine 5"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5)
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_split_by_space(self):
+        """Test splitting by space when lines are too large."""
+        text = "word1 word2 word3 word4 word5 word6 word7 word8"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=15, chunk_overlap=3)
+        result = splitter.split_text(text)
+
+        assert len(result) > 1
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_split_by_character(self):
+        """Test splitting by character when words are too large."""
+        text = "verylongwordthatcannotbesplit"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=10, chunk_overlap=2)
+        result = splitter.split_text(text)
+
+        assert len(result) > 1
+        assert all(len(chunk) <= 12 for chunk in result)  # Allow for overlap
+
+    def test_keep_separator_true(self):
+        """Test that separators are kept when keep_separator=True."""
+        text = "Para1\n\nPara2\n\nPara3"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=5, keep_separator=True)
+        result = splitter.split_text(text)
+
+        # At least one chunk should contain the separator
+        combined = "".join(result)
+        assert "Para1" in combined
+        assert "Para2" in combined
+
+    def test_keep_separator_false(self):
+        """Test that separators are removed when keep_separator=False."""
+        text = "Para1\n\nPara2\n\nPara3"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=5, keep_separator=False)
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify text content is preserved
+        combined = " ".join(result)
+        assert "Para1" in combined
+        assert "Para2" in combined
+
+    def test_overlap_handling(self):
+        """
+        Test that chunk overlap is correctly handled.
+
+        Overlap ensures that context is preserved between chunks by having
+        some content appear in consecutive chunks. This is crucial for
+        maintaining semantic continuity in RAG applications.
+        """
+        text = "A B C D E F G H I J K L M N O P"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=10, chunk_overlap=3)
+        result = splitter.split_text(text)
+
+        # Verify we have multiple chunks
+        assert len(result) > 1
+
+        # Verify overlap exists between consecutive chunks
+        # The end of one chunk should have some overlap with the start of the next
+        for i in range(len(result) - 1):
+            # Some content should overlap
+            assert len(result[i]) > 0
+            assert len(result[i + 1]) > 0
+
+    def test_empty_text(self):
+        """Test splitting empty text."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10)
+        result = splitter.split_text("")
+        assert result == []
+
+    def test_single_word(self):
+        """Test splitting single word."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10)
+        result = splitter.split_text("Hello")
+        assert len(result) == 1
+        assert result[0] == "Hello"
+
+    def test_create_documents(self):
+        """Test creating documents from texts."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=5)
+        texts = ["Text 1 with some content", "Text 2 with more content"]
+        metadatas = [{"source": "doc1"}, {"source": "doc2"}]
+
+        documents = splitter.create_documents(texts, metadatas)
+
+        assert len(documents) > 0
+        assert all(isinstance(doc, Document) for doc in documents)
+        assert all(hasattr(doc, "page_content") for doc in documents)
+        assert all(hasattr(doc, "metadata") for doc in documents)
+
+    def test_create_documents_with_start_index(self):
+        """Test creating documents with start_index in metadata."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5, add_start_index=True)
+        texts = ["This is a longer text that will be split into chunks"]
+
+        documents = splitter.create_documents(texts)
+
+        # Verify start_index is added to metadata
+        assert any("start_index" in doc.metadata for doc in documents)
+        # First chunk should start at index 0
+        if documents:
+            assert documents[0].metadata.get("start_index") == 0
+
+    def test_split_documents(self):
+        """Test splitting existing documents."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+        docs = [
+            Document(page_content="First document content", metadata={"id": 1}),
+            Document(page_content="Second document content", metadata={"id": 2}),
+        ]
+
+        result = splitter.split_documents(docs)
+
+        assert len(result) > 0
+        assert all(isinstance(doc, Document) for doc in result)
+        # Verify metadata is preserved
+        assert any(doc.metadata.get("id") == 1 for doc in result)
+
+    def test_transform_documents(self):
+        """Test transform_documents interface."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+        docs = [Document(page_content="Document to transform", metadata={"key": "value"})]
+
+        result = splitter.transform_documents(docs)
+
+        assert len(result) > 0
+        assert all(isinstance(doc, Document) for doc in result)
+
+    def test_long_text_splitting(self, long_text):
+        """Test splitting very long text."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20)
+        result = splitter.split_text(long_text)
+
+        assert len(result) > 5  # Should create multiple chunks
+        assert all(isinstance(chunk, str) for chunk in result)
+        # Verify all chunks are within reasonable size
+        assert all(len(chunk) <= 150 for chunk in result)
+
+    def test_code_splitting(self, code_text):
+        """Test splitting code with proper structure preservation."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=80, chunk_overlap=10)
+        result = splitter.split_text(code_text)
+
+        assert len(result) > 0
+        # Verify code content is preserved
+        combined = "\n".join(result)
+        assert "def hello_world" in combined or "hello_world" in combined
+
+
+# ============================================================================
+# Test TokenTextSplitter
+# ============================================================================
+
+
+class TestTokenTextSplitter:
+    """Test TokenTextSplitter functionality."""
+
+    @pytest.mark.skipif(True, reason="Requires tiktoken library which may not be installed")
+    def test_initialization_with_encoding(self):
+        """Test TokenTextSplitter initialization with encoding name."""
+        try:
+            splitter = TokenTextSplitter(encoding_name="gpt2", chunk_size=100, chunk_overlap=10)
+            assert splitter._chunk_size == 100
+            assert splitter._chunk_overlap == 10
+        except ImportError:
+            pytest.skip("tiktoken not installed")
+
+    @pytest.mark.skipif(True, reason="Requires tiktoken library which may not be installed")
+    def test_initialization_with_model(self):
+        """Test TokenTextSplitter initialization with model name."""
+        try:
+            splitter = TokenTextSplitter(model_name="gpt-3.5-turbo", chunk_size=100, chunk_overlap=10)
+            assert splitter._chunk_size == 100
+        except ImportError:
+            pytest.skip("tiktoken not installed")
+
+    def test_initialization_without_tiktoken(self):
+        """Test that proper error is raised when tiktoken is not installed."""
+        with patch("core.rag.splitter.text_splitter.TokenTextSplitter.__init__") as mock_init:
+            mock_init.side_effect = ImportError("Could not import tiktoken")
+            with pytest.raises(ImportError, match="tiktoken"):
+                TokenTextSplitter(chunk_size=100)
+
+    @pytest.mark.skipif(True, reason="Requires tiktoken library which may not be installed")
+    def test_split_text_by_tokens(self, sample_text):
+        """Test splitting text by token count."""
+        try:
+            splitter = TokenTextSplitter(encoding_name="gpt2", chunk_size=50, chunk_overlap=10)
+            result = splitter.split_text(sample_text)
+
+            assert len(result) > 0
+            assert all(isinstance(chunk, str) for chunk in result)
+        except ImportError:
+            pytest.skip("tiktoken not installed")
+
+    @pytest.mark.skipif(True, reason="Requires tiktoken library which may not be installed")
+    def test_token_overlap(self):
+        """Test that token overlap works correctly."""
+        try:
+            splitter = TokenTextSplitter(encoding_name="gpt2", chunk_size=20, chunk_overlap=5)
+            text = " ".join([f"word{i}" for i in range(50)])
+            result = splitter.split_text(text)
+
+            assert len(result) > 1
+        except ImportError:
+            pytest.skip("tiktoken not installed")
+
+
+# ============================================================================
+# Test EnhanceRecursiveCharacterTextSplitter
+# ============================================================================
+
+
+class TestEnhanceRecursiveCharacterTextSplitter:
+    """Test EnhanceRecursiveCharacterTextSplitter functionality."""
+
+    def test_from_encoder_without_model(self):
+        """Test creating splitter from encoder without embedding model."""
+        splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
+            embedding_model_instance=None, chunk_size=100, chunk_overlap=10
+        )
+
+        assert splitter._chunk_size == 100
+        assert splitter._chunk_overlap == 10
+
+    def test_from_encoder_with_mock_model(self):
+        """Test creating splitter from encoder with mock embedding model."""
+        mock_model = Mock()
+        mock_model.get_text_embedding_num_tokens = Mock(return_value=[10, 20, 30])
+
+        splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
+            embedding_model_instance=mock_model, chunk_size=100, chunk_overlap=10
+        )
+
+        assert splitter._chunk_size == 100
+        assert splitter._chunk_overlap == 10
+
+    def test_split_text_basic(self, sample_text):
+        """Test basic text splitting with EnhanceRecursiveCharacterTextSplitter."""
+        splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
+            embedding_model_instance=None, chunk_size=100, chunk_overlap=10
+        )
+
+        result = splitter.split_text(sample_text)
+
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_character_encoder_length_function(self):
+        """Test that character encoder correctly counts characters."""
+        splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
+            embedding_model_instance=None, chunk_size=50, chunk_overlap=5
+        )
+
+        text = "A" * 100
+        result = splitter.split_text(text)
+
+        # Should split into multiple chunks
+        assert len(result) >= 2
+
+    def test_with_embedding_model_token_counting(self):
+        """Test token counting with embedding model."""
+        mock_model = Mock()
+        # Mock returns token counts for input texts
+        mock_model.get_text_embedding_num_tokens = Mock(side_effect=lambda texts: [len(t) // 2 for t in texts])
+
+        splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
+            embedding_model_instance=mock_model, chunk_size=50, chunk_overlap=5
+        )
+
+        text = "This is a test text that should be split"
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+
+
+# ============================================================================
+# Test FixedRecursiveCharacterTextSplitter
+# ============================================================================
+
+
+class TestFixedRecursiveCharacterTextSplitter:
+    """Test FixedRecursiveCharacterTextSplitter functionality."""
+
+    def test_initialization_with_fixed_separator(self):
+        """Test initialization with fixed separator."""
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=100, chunk_overlap=10)
+
+        assert splitter._fixed_separator == "\n\n"
+        assert splitter._chunk_size == 100
+        assert splitter._chunk_overlap == 10
+
+    def test_split_by_fixed_separator(self):
+        """Test splitting by fixed separator first."""
+        text = "Part 1\n\nPart 2\n\nPart 3"
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=100, chunk_overlap=10)
+
+        result = splitter.split_text(text)
+
+        assert len(result) >= 3
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_recursive_split_when_chunk_too_large(self):
+        """Test recursive splitting when chunks exceed size limit."""
+        # Create text with large chunks separated by fixed separator
+        large_chunk = " ".join([f"word{i}" for i in range(50)])
+        text = f"{large_chunk}\n\n{large_chunk}"
+
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=50, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        # Should split into more than 2 chunks due to size limit
+        assert len(result) > 2
+
+    def test_custom_separators(self):
+        """Test with custom separator list."""
+        text = "Sentence 1. Sentence 2. Sentence 3."
+        splitter = FixedRecursiveCharacterTextSplitter(
+            fixed_separator=".",
+            separators=[".", " ", ""],
+            chunk_size=30,
+            chunk_overlap=5,
+        )
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_no_fixed_separator(self):
+        """Test behavior when no fixed separator is provided."""
+        text = "This is a test text without fixed separator"
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="", chunk_size=20, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+
+    def test_chinese_separator(self):
+        """Test with Chinese period separator."""
+        text = "这是第一句。这是第二句。这是第三句。"
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="。", chunk_size=50, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_space_separator_handling(self):
+        """Test special handling of space separator."""
+        text = "word1  word2   word3    word4"  # Multiple spaces
+        splitter = FixedRecursiveCharacterTextSplitter(
+            fixed_separator=" ", separators=[" ", ""], chunk_size=15, chunk_overlap=3
+        )
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify words are present
+        combined = " ".join(result)
+        assert "word1" in combined
+        assert "word2" in combined
+
+    def test_character_level_splitting(self):
+        """Test character-level splitting when no separator works."""
+        text = "verylongwordwithoutspaces"
+        splitter = FixedRecursiveCharacterTextSplitter(
+            fixed_separator="", separators=[""], chunk_size=10, chunk_overlap=2
+        )
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 1
+        # Verify chunks respect size with overlap
+        for chunk in result:
+            assert len(chunk) <= 12  # chunk_size + some tolerance for overlap
+
+    def test_overlap_in_character_splitting(self):
+        """Test that overlap is correctly applied in character-level splitting."""
+        text = string.ascii_uppercase
+        splitter = FixedRecursiveCharacterTextSplitter(
+            fixed_separator="", separators=[""], chunk_size=10, chunk_overlap=3
+        )
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 1
+        # Verify overlap exists
+        for i in range(len(result) - 1):
+            # Check that some characters appear in consecutive chunks
+            assert len(result[i]) > 0
+            assert len(result[i + 1]) > 0
+
+    def test_metadata_preservation_in_documents(self):
+        """Test that metadata is preserved when splitting documents."""
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=50, chunk_overlap=5)
+
+        docs = [
+            Document(
+                page_content="First part\n\nSecond part\n\nThird part",
+                metadata={"source": "test.txt", "page": 1},
+            )
+        ]
+
+        result = splitter.split_documents(docs)
+
+        assert len(result) > 0
+        # Verify all chunks have the original metadata
+        for doc in result:
+            assert doc.metadata.get("source") == "test.txt"
+            assert doc.metadata.get("page") == 1
+
+    def test_empty_text_handling(self):
+        """Test handling of empty text."""
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=100, chunk_overlap=10)
+
+        result = splitter.split_text("")
+
+        # May return empty list or list with empty string depending on implementation
+        assert isinstance(result, list)
+        assert len(result) <= 1
+
+    def test_single_chunk_text(self):
+        """Test text that fits in a single chunk."""
+        text = "Short text"
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=100, chunk_overlap=10)
+
+        result = splitter.split_text(text)
+
+        assert len(result) == 1
+        assert result[0] == text
+
+    def test_newline_filtering(self):
+        """Test that newlines are properly filtered in splits."""
+        text = "Line 1\nLine 2\n\nLine 3"
+        splitter = FixedRecursiveCharacterTextSplitter(
+            fixed_separator="", separators=["\n", ""], chunk_size=50, chunk_overlap=5
+        )
+
+        result = splitter.split_text(text)
+
+        # Verify no empty chunks
+        assert all(len(chunk) > 0 for chunk in result)
+
+
+# ============================================================================
+# Test Metadata Preservation
+# ============================================================================
+
+
+class TestMetadataPreservation:
+    """
+    Test metadata preservation across different splitters.
+
+    Metadata preservation is critical for RAG systems as it allows tracking
+    the source, author, timestamps, and other contextual information for
+    each chunk. All chunks derived from a document should inherit its metadata.
+    """
+
+    def test_recursive_splitter_metadata(self):
+        """
+        Test metadata preservation with RecursiveCharacterTextSplitter.
+
+        When a document is split into multiple chunks, each chunk should
+        receive a copy of the original document's metadata. This ensures
+        that we can trace each chunk back to its source.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+        texts = ["Text content here"]
+        # Metadata includes various types: strings, dates, lists
+        metadatas = [{"author": "John", "date": "2024-01-01", "tags": ["test"]}]
+
+        documents = splitter.create_documents(texts, metadatas)
+
+        # Every chunk should have the same metadata as the original
+        for doc in documents:
+            assert doc.metadata.get("author") == "John"
+            assert doc.metadata.get("date") == "2024-01-01"
+            assert doc.metadata.get("tags") == ["test"]
+
+    def test_enhance_splitter_metadata(self):
+        """Test metadata preservation with EnhanceRecursiveCharacterTextSplitter."""
+        splitter = EnhanceRecursiveCharacterTextSplitter.from_encoder(
+            embedding_model_instance=None, chunk_size=30, chunk_overlap=5
+        )
+
+        docs = [
+            Document(
+                page_content="Content to split",
+                metadata={"id": 123, "category": "test"},
+            )
+        ]
+
+        result = splitter.split_documents(docs)
+
+        for doc in result:
+            assert doc.metadata.get("id") == 123
+            assert doc.metadata.get("category") == "test"
+
+    def test_fixed_splitter_metadata(self):
+        """Test metadata preservation with FixedRecursiveCharacterTextSplitter."""
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n", chunk_size=30, chunk_overlap=5)
+
+        docs = [
+            Document(
+                page_content="Line 1\nLine 2\nLine 3",
+                metadata={"version": "1.0", "status": "active"},
+            )
+        ]
+
+        result = splitter.split_documents(docs)
+
+        for doc in result:
+            assert doc.metadata.get("version") == "1.0"
+            assert doc.metadata.get("status") == "active"
+
+    def test_metadata_with_start_index(self):
+        """Test that start_index is added to metadata when requested."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5, add_start_index=True)
+
+        texts = ["This is a test text that will be split"]
+        metadatas = [{"original": "metadata"}]
+
+        documents = splitter.create_documents(texts, metadatas)
+
+        # Verify both original metadata and start_index are present
+        for doc in documents:
+            assert "start_index" in doc.metadata
+            assert doc.metadata.get("original") == "metadata"
+            assert isinstance(doc.metadata["start_index"], int)
+            assert doc.metadata["start_index"] >= 0
+
+
+# ============================================================================
+# Test Edge Cases
+# ============================================================================
+
+
+class TestEdgeCases:
+    """Test edge cases and boundary conditions."""
+
+    def test_chunk_size_equals_text_length(self):
+        """Test when chunk size equals text length."""
+        text = "Exact size text"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=len(text), chunk_overlap=0)
+
+        result = splitter.split_text(text)
+
+        assert len(result) == 1
+        assert result[0] == text
+
+    def test_very_small_chunk_size(self):
+        """Test with very small chunk size."""
+        text = "Test text"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=3, chunk_overlap=1)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 1
+        assert all(len(chunk) <= 5 for chunk in result)  # Allow for overlap
+
+    def test_zero_overlap(self):
+        """Test splitting with zero overlap."""
+        text = "Word1 Word2 Word3 Word4"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=12, chunk_overlap=0)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify no overlap between chunks
+        combined_length = sum(len(chunk) for chunk in result)
+        # Should be close to original length (accounting for separators)
+        assert combined_length >= len(text) - 10
+
+    def test_unicode_text(self):
+        """Test splitting text with unicode characters."""
+        text = "Hello 世界 🌍 مرحبا"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=3)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify unicode is preserved
+        combined = " ".join(result)
+        assert "世界" in combined or "世" in combined
+
+    def test_only_separators(self):
+        """Test text containing only separators."""
+        text = "\n\n\n\n"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=10, chunk_overlap=2)
+
+        result = splitter.split_text(text)
+
+        # Should return empty list or handle gracefully
+        assert isinstance(result, list)
+
+    def test_mixed_separators(self):
+        """Test text with mixed separator types."""
+        text = "Para1\n\nPara2\nLine\n\n\nPara3"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        combined = "".join(result)
+        assert "Para1" in combined
+        assert "Para2" in combined
+        assert "Para3" in combined
+
+    def test_whitespace_only_text(self):
+        """Test text containing only whitespace."""
+        text = "     "
+        splitter = RecursiveCharacterTextSplitter(chunk_size=10, chunk_overlap=2)
+
+        result = splitter.split_text(text)
+
+        # Should handle whitespace-only text
+        assert isinstance(result, list)
+
+    def test_single_character_text(self):
+        """Test splitting single character."""
+        text = "A"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=10, chunk_overlap=2)
+
+        result = splitter.split_text(text)
+
+        assert len(result) == 1
+        assert result[0] == "A"
+
+    def test_multiple_documents_different_sizes(self):
+        """Test splitting multiple documents of different sizes."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+
+        docs = [
+            Document(page_content="Short", metadata={"id": 1}),
+            Document(
+                page_content="This is a much longer document that will be split",
+                metadata={"id": 2},
+            ),
+            Document(page_content="Medium length doc", metadata={"id": 3}),
+        ]
+
+        result = splitter.split_documents(docs)
+
+        # Verify all documents are processed
+        assert len(result) >= 3
+        # Verify metadata is preserved
+        ids = [doc.metadata.get("id") for doc in result]
+        assert 1 in ids
+        assert 2 in ids
+        assert 3 in ids
+
+
+# ============================================================================
+# Test Integration Scenarios
+# ============================================================================
+
+
+class TestIntegrationScenarios:
+    """Test realistic integration scenarios."""
+
+    def test_document_processing_pipeline(self):
+        """Test complete document processing pipeline."""
+        # Simulate a document processing workflow
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20, add_start_index=True)
+
+        # Original documents with metadata
+        original_docs = [
+            Document(
+                page_content="First document with multiple paragraphs.\n\nSecond paragraph here.\n\nThird paragraph.",
+                metadata={"source": "doc1.txt", "author": "Alice"},
+            ),
+            Document(
+                page_content="Second document content.\n\nMore content here.",
+                metadata={"source": "doc2.txt", "author": "Bob"},
+            ),
+        ]
+
+        # Split documents
+        split_docs = splitter.split_documents(original_docs)
+
+        # Verify results - documents may fit in single chunks if small enough
+        assert len(split_docs) >= len(original_docs)  # At least as many chunks as original docs
+        assert all(isinstance(doc, Document) for doc in split_docs)
+        assert all("start_index" in doc.metadata for doc in split_docs)
+        assert all("source" in doc.metadata for doc in split_docs)
+        assert all("author" in doc.metadata for doc in split_docs)
+
+    def test_multilingual_document_splitting(self, multilingual_text):
+        """Test splitting multilingual documents."""
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+
+        result = splitter.split_text(multilingual_text)
+
+        assert len(result) > 0
+        # Verify content is preserved
+        combined = " ".join(result)
+        assert "English" in combined or "Eng" in combined
+
+    def test_code_documentation_splitting(self, code_text):
+        """Test splitting code documentation."""
+        splitter = FixedRecursiveCharacterTextSplitter(fixed_separator="\n\n", chunk_size=100, chunk_overlap=10)
+
+        result = splitter.split_text(code_text)
+
+        assert len(result) > 0
+        # Verify code structure is somewhat preserved
+        combined = "\n".join(result)
+        assert "def" in combined
+
+    def test_large_document_chunking(self):
+        """Test chunking of large documents."""
+        # Create a large document
+        large_text = "\n\n".join([f"Paragraph {i} with some content." for i in range(100)])
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=200, chunk_overlap=50)
+
+        result = splitter.split_text(large_text)
+
+        # Verify efficient chunking
+        assert len(result) > 10
+        assert all(len(chunk) <= 250 for chunk in result)  # Allow some tolerance
+
+    def test_semantic_chunking_simulation(self):
+        """Test semantic-like chunking by using paragraph separators."""
+        text = """Introduction paragraph.
+
+Main content paragraph with details.
+
+Conclusion paragraph with summary.
+
+Additional notes and references."""
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20, keep_separator=True)
+
+        result = splitter.split_text(text)
+
+        # Verify paragraph structure is somewhat maintained
+        assert len(result) > 0
+        assert all(isinstance(chunk, str) for chunk in result)
+
+
+# ============================================================================
+# Test Performance and Limits
+# ============================================================================
+
+
+class TestPerformanceAndLimits:
+    """Test performance characteristics and limits."""
+
+    def test_max_chunk_size_warning(self):
+        """Test that warning is logged for chunks exceeding size."""
+        # Create text with a very long word
+        long_word = "a" * 200
+        text = f"Short {long_word} text"
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=10)
+
+        # Should handle gracefully and log warning
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Long word may be split into multiple chunks at character level
+        # Verify all content is preserved
+        combined = "".join(result)
+        assert "a" * 100 in combined  # At least part of the long word is preserved
+
+    def test_many_small_chunks(self):
+        """Test creating many small chunks."""
+        text = " ".join([f"w{i}" for i in range(1000)])
+        splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        # Should create many chunks
+        assert len(result) > 50
+        assert all(isinstance(chunk, str) for chunk in result)
+
+    def test_deeply_nested_splitting(self):
+        """
+        Test that recursive splitting works for deeply nested cases.
+
+        This test verifies that the splitter can handle text that requires
+        multiple levels of recursive splitting (paragraph -> line -> word -> character).
+        """
+        # Text that requires multiple levels of splitting
+        text = "word1" + "x" * 100 + "word2" + "y" * 100 + "word3"
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 3
+        # Verify all content is present
+        combined = "".join(result)
+        assert "word1" in combined
+        assert "word2" in combined
+        assert "word3" in combined
+
+
+# ============================================================================
+# Test Advanced Splitting Scenarios
+# ============================================================================
+
+
+class TestAdvancedSplittingScenarios:
+    """
+    Test advanced and complex splitting scenarios.
+
+    This test class covers edge cases and advanced use cases that may occur
+    in production environments, including structured documents, special
+    formatting, and boundary conditions.
+    """
+
+    def test_markdown_document_splitting(self, markdown_text):
+        """
+        Test splitting of markdown formatted documents.
+
+        Markdown documents have hierarchical structure with headers and sections.
+        This test verifies that the splitter respects document structure while
+        maintaining readability of chunks.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=150, chunk_overlap=20, keep_separator=True)
+
+        result = splitter.split_text(markdown_text)
+
+        # Should create multiple chunks
+        assert len(result) > 0
+
+        # Verify markdown structure is somewhat preserved
+        combined = "\n".join(result)
+        assert "#" in combined  # Headers should be present
+        assert "Section" in combined
+
+        # Each chunk should be within size limits
+        assert all(len(chunk) <= 200 for chunk in result)
+
+    def test_html_content_splitting(self, html_text):
+        """
+        Test splitting of HTML formatted content.
+
+        HTML has nested tags and structure. This test ensures that
+        splitting doesn't break the content in ways that would make
+        it unusable.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=15)
+
+        result = splitter.split_text(html_text)
+
+        assert len(result) > 0
+        # Verify HTML content is preserved
+        combined = "".join(result)
+        assert "paragraph" in combined.lower() or "para" in combined.lower()
+
+    def test_json_structure_splitting(self, json_text):
+        """
+        Test splitting of JSON formatted data.
+
+        JSON has specific structure with braces, brackets, and quotes.
+        While the splitter doesn't parse JSON, it should handle it
+        without losing critical content.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=80, chunk_overlap=10)
+
+        result = splitter.split_text(json_text)
+
+        assert len(result) > 0
+        # Verify key JSON elements are preserved
+        combined = "".join(result)
+        assert "name" in combined or "content" in combined
+
+    def test_technical_documentation_splitting(self, technical_text):
+        """
+        Test splitting of technical documentation.
+
+        Technical docs often have specific formatting with sections,
+        code examples, and structured information. This test ensures
+        such content is split appropriately.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=200, chunk_overlap=30, keep_separator=True)
+
+        result = splitter.split_text(technical_text)
+
+        assert len(result) > 0
+        # Verify technical content is preserved
+        combined = "\n".join(result)
+        assert "API" in combined or "api" in combined.lower()
+        assert "Parameters" in combined or "Error" in combined
+
+    def test_mixed_content_types(self):
+        """
+        Test splitting document with mixed content types.
+
+        Real-world documents often mix prose, code, lists, and other
+        content types. This test verifies handling of such mixed content.
+        """
+        mixed_text = """Introduction to the API
+
+Here is some explanatory text about how to use the API.
+
+```python
+def example():
+    return {"status": "success"}
+```
+
+Key Points:
+- Point 1: First important point
+- Point 2: Second important point
+- Point 3: Third important point
+
+Conclusion paragraph with final thoughts."""
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=120, chunk_overlap=20)
+
+        result = splitter.split_text(mixed_text)
+
+        assert len(result) > 0
+        # Verify different content types are preserved
+        combined = "\n".join(result)
+        assert "API" in combined or "api" in combined.lower()
+        assert "Point" in combined or "point" in combined
+
+    def test_bullet_points_and_lists(self):
+        """
+        Test splitting of text with bullet points and lists.
+
+        Lists are common in documents and should be split in a way
+        that maintains their structure and readability.
+        """
+        list_text = """Main Topic
+
+Key Features:
+- Feature 1: Description of first feature
+- Feature 2: Description of second feature
+- Feature 3: Description of third feature
+- Feature 4: Description of fourth feature
+- Feature 5: Description of fifth feature
+
+Additional Information:
+1. First numbered item
+2. Second numbered item
+3. Third numbered item"""
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=15)
+
+        result = splitter.split_text(list_text)
+
+        assert len(result) > 0
+        # Verify list structure is somewhat maintained
+        combined = "\n".join(result)
+        assert "Feature" in combined or "feature" in combined
+
+    def test_quoted_text_handling(self):
+        """
+        Test handling of quoted text and dialogue.
+
+        Quotes and dialogue have special formatting that should be
+        preserved during splitting.
+        """
+        quoted_text = """The speaker said, "This is a very important quote that contains multiple sentences. \
+It goes on for quite a while and has significant meaning."
+
+Another person responded, "I completely agree with that statement. \
+We should consider all the implications."
+
+A third voice added, "Let's not forget about the other perspective here."
+
+The discussion continued with more detailed points."""
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20)
+
+        result = splitter.split_text(quoted_text)
+
+        assert len(result) > 0
+        # Verify quotes are preserved
+        combined = " ".join(result)
+        assert "said" in combined or "responded" in combined
+
+    def test_table_like_content(self):
+        """
+        Test splitting of table-like formatted content.
+
+        Tables and structured data layouts should be handled gracefully
+        even though the splitter doesn't understand table semantics.
+        """
+        table_text = """Product Comparison Table
+
+Name          | Price  | Rating | Stock
+------------- | ------ | ------ | -----
+Product A     | $29.99 | 4.5    | 100
+Product B     | $39.99 | 4.8    | 50
+Product C     | $19.99 | 4.2    | 200
+Product D     | $49.99 | 4.9    | 25
+
+Notes: All prices include tax."""
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=120, chunk_overlap=15)
+
+        result = splitter.split_text(table_text)
+
+        assert len(result) > 0
+        # Verify table content is preserved
+        combined = "\n".join(result)
+        assert "Product" in combined or "Price" in combined
+
+    def test_urls_and_links_preservation(self):
+        """
+        Test that URLs and links are preserved during splitting.
+
+        URLs should not be broken across chunks as that would make
+        them unusable.
+        """
+        url_text = """For more information, visit https://www.example.com/very/long/path/to/resource
+
+You can also check out https://api.example.com/v1/documentation for API details.
+
+Additional resources:
+- https://github.com/example/repo
+- https://stackoverflow.com/questions/12345/example-question
+
+Contact us at support@example.com for help."""
+
+        splitter = RecursiveCharacterTextSplitter(
+            chunk_size=100,
+            chunk_overlap=20,
+            separators=["\n\n", "\n", " ", ""],  # Space separator helps keep URLs together
+        )
+
+        result = splitter.split_text(url_text)
+
+        assert len(result) > 0
+        # Verify URLs are present in chunks
+        combined = " ".join(result)
+        assert "http" in combined or "example.com" in combined
+
+    def test_email_content_splitting(self):
+        """
+        Test splitting of email-like content.
+
+        Emails have headers, body, and signatures that should be
+        handled appropriately.
+        """
+        email_text = """From: sender@example.com
+To: recipient@example.com
+Subject: Important Update
+
+Dear Team,
+
+I wanted to inform you about the recent changes to our project timeline. \
+The new deadline is next month, and we need to adjust our priorities accordingly.
+
+Please review the attached documents and provide your feedback by end of week.
+
+Key action items:
+1. Review documentation
+2. Update project plan
+3. Schedule follow-up meeting
+
+Best regards,
+John Doe
+Senior Manager"""
+
+        splitter = RecursiveCharacterTextSplitter(chunk_size=150, chunk_overlap=20)
+
+        result = splitter.split_text(email_text)
+
+        assert len(result) > 0
+        # Verify email structure is preserved
+        combined = "\n".join(result)
+        assert "From" in combined or "Subject" in combined or "Dear" in combined
+
+
+# ============================================================================
+# Test Splitter Configuration and Customization
+# ============================================================================
+
+
+class TestSplitterConfiguration:
+    """
+    Test various configuration options for text splitters.
+
+    This class tests different parameter combinations and configurations
+    to ensure splitters behave correctly under various settings.
+    """
+
+    def test_custom_length_function(self):
+        """
+        Test using a custom length function.
+
+        The splitter allows custom length functions for specialized
+        counting (e.g., word count instead of character count).
+        """
+
+        # Custom length function that counts words
+        def word_count_length(texts: list[str]) -> list[int]:
+            return [len(text.split()) for text in texts]
+
+        splitter = RecursiveCharacterTextSplitter(
+            chunk_size=10,  # 10 words
+            chunk_overlap=2,  # 2 words overlap
+            length_function=word_count_length,
+        )
+
+        text = " ".join([f"word{i}" for i in range(30)])
+        result = splitter.split_text(text)
+
+        # Should create multiple chunks based on word count
+        assert len(result) > 1
+        # Each chunk should have roughly 10 words or fewer
+        for chunk in result:
+            word_count = len(chunk.split())
+            assert word_count <= 15  # Allow some tolerance
+
+    def test_different_separator_orders(self):
+        """
+        Test different orderings of separators.
+
+        The order of separators affects how text is split. This test
+        verifies that different orders produce different results.
+        """
+        text = "Paragraph one.\n\nParagraph two.\nLine break here.\nAnother line."
+
+        # Try paragraph-first splitting
+        splitter1 = RecursiveCharacterTextSplitter(
+            chunk_size=50, chunk_overlap=5, separators=["\n\n", "\n", ".", " ", ""]
+        )
+        result1 = splitter1.split_text(text)
+
+        # Try line-first splitting
+        splitter2 = RecursiveCharacterTextSplitter(
+            chunk_size=50, chunk_overlap=5, separators=["\n", "\n\n", ".", " ", ""]
+        )
+        result2 = splitter2.split_text(text)
+
+        # Both should produce valid results
+        assert len(result1) > 0
+        assert len(result2) > 0
+        # Results may differ based on separator priority
+        assert isinstance(result1, list)
+        assert isinstance(result2, list)
+
+    def test_extreme_overlap_ratios(self):
+        """
+        Test splitters with extreme overlap ratios.
+
+        Tests edge cases where overlap is very small or very large
+        relative to chunk size.
+        """
+        text = "A B C D E F G H I J K L M N O P Q R S T U V W X Y Z"
+
+        # Very small overlap (1% of chunk size)
+        splitter_small = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=1)
+        result_small = splitter_small.split_text(text)
+
+        # Large overlap (90% of chunk size)
+        splitter_large = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=18)
+        result_large = splitter_large.split_text(text)
+
+        # Both should work
+        assert len(result_small) > 0
+        assert len(result_large) > 0
+        # Large overlap should create more chunks
+        assert len(result_large) >= len(result_small)
+
+    def test_add_start_index_accuracy(self):
+        """
+        Test that start_index metadata is accurately calculated.
+
+        The start_index should point to the actual position of the
+        chunk in the original text.
+        """
+        text = string.ascii_uppercase
+        splitter = RecursiveCharacterTextSplitter(chunk_size=10, chunk_overlap=2, add_start_index=True)
+
+        docs = splitter.create_documents([text])
+
+        # Verify start indices are correct
+        for doc in docs:
+            start_idx = doc.metadata.get("start_index")
+            if start_idx is not None:
+                # The chunk should actually appear at that index
+                assert text[start_idx : start_idx + len(doc.page_content)] == doc.page_content
+
+    def test_separator_regex_patterns(self):
+        """
+        Test using regex patterns as separators.
+
+        Separators can be regex patterns for more sophisticated splitting.
+        """
+        # Text with multiple spaces and tabs
+        text = "Word1    Word2\t\tWord3   Word4\tWord5"
+
+        splitter = RecursiveCharacterTextSplitter(
+            chunk_size=20,
+            chunk_overlap=3,
+            separators=[r"\s+", ""],  # Split on any whitespace
+        )
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify words are split
+        combined = " ".join(result)
+        assert "Word" in combined
+
+
+# ============================================================================
+# Test Error Handling and Robustness
+# ============================================================================
+
+
+class TestErrorHandlingAndRobustness:
+    """
+    Test error handling and robustness of splitters.
+
+    This class tests how splitters handle invalid inputs, edge cases,
+    and error conditions.
+    """
+
+    def test_none_text_handling(self):
+        """
+        Test handling of None as input.
+
+        Splitters should handle None gracefully without crashing.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10)
+
+        # Should handle None without crashing
+        try:
+            result = splitter.split_text(None)
+            # If it doesn't raise an error, result should be empty or handle gracefully
+            assert result is not None
+        except (TypeError, AttributeError):
+            # It's acceptable to raise a type error for None input
+            pass
+
+    def test_very_large_chunk_size(self):
+        """
+        Test splitter with chunk size larger than any reasonable text.
+
+        When chunk size is very large, text should remain unsplit.
+        """
+        text = "This is a short text."
+        splitter = RecursiveCharacterTextSplitter(chunk_size=1000000, chunk_overlap=100)
+
+        result = splitter.split_text(text)
+
+        # Should return single chunk
+        assert len(result) == 1
+        assert result[0] == text
+
+    def test_chunk_size_one(self):
+        """
+        Test splitter with minimum chunk size of 1.
+
+        This extreme case should split text character by character.
+        """
+        text = "ABC"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=1, chunk_overlap=0)
+
+        result = splitter.split_text(text)
+
+        # Should split into individual characters
+        assert len(result) >= 3
+        # Verify all content is preserved
+        combined = "".join(result)
+        assert "A" in combined
+        assert "B" in combined
+        assert "C" in combined
+
+    def test_special_unicode_characters(self):
+        """
+        Test handling of special unicode characters.
+
+        Splitters should handle emojis, special symbols, and other
+        unicode characters without issues.
+        """
+        text = "Hello 👋 World 🌍 Test 🚀 Data 📊 End 🎉"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify unicode is preserved
+        combined = " ".join(result)
+        assert "Hello" in combined
+        assert "World" in combined
+
+    def test_control_characters(self):
+        """
+        Test handling of control characters.
+
+        Text may contain tabs, carriage returns, and other control
+        characters that should be handled properly.
+        """
+        text = "Line1\r\nLine2\tTabbed\r\nLine3"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Verify content is preserved
+        combined = "".join(result)
+        assert "Line1" in combined
+        assert "Line2" in combined
+
+    def test_repeated_separators(self):
+        """
+        Test text with many repeated separators.
+
+        Multiple consecutive separators should be handled without
+        creating empty chunks.
+        """
+        text = "Word1\n\n\n\n\nWord2\n\n\n\nWord3"
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=5)
+
+        result = splitter.split_text(text)
+
+        assert len(result) > 0
+        # Should not have empty chunks
+        assert all(len(chunk.strip()) > 0 for chunk in result)
+
+    def test_documents_with_empty_metadata(self):
+        """
+        Test splitting documents with empty metadata.
+
+        Documents may have empty metadata dict, which should be handled
+        properly and preserved in chunks.
+        """
+        splitter = RecursiveCharacterTextSplitter(chunk_size=30, chunk_overlap=5)
+
+        # Create documents with empty metadata
+        docs = [Document(page_content="Content here", metadata={})]
+
+        result = splitter.split_documents(docs)
+
+        assert len(result) > 0
+        # Metadata should be dict (empty dict is valid)
+        for doc in result:
+            assert isinstance(doc.metadata, dict)
+
+    def test_empty_separator_list(self):
+        """
+        Test splitter with empty separator list.
+
+        Edge case where no separators are provided should still work
+        by falling back to default behavior.
+        """
+        text = "Test text here"
+
+        try:
+            splitter = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5, separators=[])
+            result = splitter.split_text(text)
+            # Should still produce some result
+            assert isinstance(result, list)
+        except (ValueError, IndexError):
+            # It's acceptable to raise an error for empty separators
+            pass
+
+
+# ============================================================================
+# Test Performance Characteristics
+# ============================================================================
+
+
+class TestPerformanceCharacteristics:
+    """
+    Test performance-related characteristics of splitters.
+
+    These tests verify that splitters perform efficiently and handle
+    large-scale operations appropriately.
+    """
+
+    def test_consistent_chunk_sizes(self):
+        """
+        Test that chunk sizes are relatively consistent.
+
+        While chunks may vary in size, they should generally be close
+        to the target chunk size (except for the last chunk).
+        """
+        text = " ".join([f"Word{i}" for i in range(200)])
+        splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=10)
+
+        result = splitter.split_text(text)
+
+        # Most chunks should be close to target size
+        sizes = [len(chunk) for chunk in result[:-1]]  # Exclude last chunk
+        if sizes:
+            avg_size = sum(sizes) / len(sizes)
+            # Average should be reasonably close to target
+            assert 50 <= avg_size <= 150
+
+    def test_minimal_information_loss(self):
+        """
+        Test that splitting and rejoining preserves information.
+
+        When chunks are rejoined, the content should be largely preserved
+        (accounting for separator handling).
+        """
+        text = "The quick brown fox jumps over the lazy dog. " * 10
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=10, keep_separator=True)
+
+        result = splitter.split_text(text)
+        combined = "".join(result)
+
+        # Most of the original text should be preserved
+        # (Some separators might be handled differently)
+        assert "quick" in combined
+        assert "brown" in combined
+        assert "fox" in combined
+        assert "dog" in combined
+
+    def test_deterministic_splitting(self):
+        """
+        Test that splitting is deterministic.
+
+        Running the same splitter on the same text multiple times
+        should produce identical results.
+        """
+        text = "Consistent text for deterministic testing. " * 5
+        splitter = RecursiveCharacterTextSplitter(chunk_size=50, chunk_overlap=10)
+
+        result1 = splitter.split_text(text)
+        result2 = splitter.split_text(text)
+        result3 = splitter.split_text(text)
+
+        # All results should be identical
+        assert result1 == result2
+        assert result2 == result3
+
+    def test_chunk_count_estimation(self):
+        """
+        Test that chunk count is reasonable for given text length.
+
+        The number of chunks should be proportional to text length
+        and inversely proportional to chunk size.
+        """
+        base_text = "Word " * 100
+
+        # Small chunks should create more chunks
+        splitter_small = RecursiveCharacterTextSplitter(chunk_size=20, chunk_overlap=5)
+        result_small = splitter_small.split_text(base_text)
+
+        # Large chunks should create fewer chunks
+        splitter_large = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=5)
+        result_large = splitter_large.split_text(base_text)
+
+        # Small chunk size should produce more chunks
+        assert len(result_small) > len(result_large)