> ## Documentation Index
> Fetch the complete documentation index at: https://docs.upsonic.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Agentic Splitter

> Split documents using AI agents for cognitive processing

## Overview

Agentic splitter uses AI agents to extract atomic propositions, group them into coherent topics, and create semantically meaningful chunks. Features comprehensive caching, quality validation, error handling with fallbacks, and rich metadata enrichment.

**Splitter Class:** `AgenticChunker`

**Config Class:** `AgenticChunkingConfig`

## Dependencies

Requires a pre-configured Agent instance for cognitive processing.

## Examples

```python theme={null}
from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders.text import TextLoader
from upsonic.loaders.config import TextLoaderConfig
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.text_splitter.agentic import AgenticChunker, AgenticChunkingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode

# Create agent for cognitive processing
agent = Agent("anthropic/claude-sonnet-4-5")

# Configure splitter
splitter_config = AgenticChunkingConfig(
    chunk_size=512,
    chunk_overlap=50,
    max_agent_retries=3,
    enable_proposition_caching=True
)
splitter = AgenticChunker(agent, splitter_config)

# Setup KnowledgeBase
loader = TextLoader(TextLoaderConfig())
embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
vectordb = ChromaProvider(ChromaConfig(
    collection_name="agentic_docs",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))

kb = KnowledgeBase(
    sources=["document.txt"],
    embedding_provider=embedding,
    vectordb=vectordb,
    loaders=[loader],
    splitters=[splitter]
)

# Query with Agent
query_agent = Agent("anthropic/claude-sonnet-4-5")
task = Task("What are the main propositions?", context=[kb])
result = query_agent.do(task)
print(result)
```

## Parameters

| Parameter                       | Type                   | Description                               | Default | Source   |
| ------------------------------- | ---------------------- | ----------------------------------------- | ------- | -------- |
| `chunk_size`                    | `int`                  | Target size of each chunk                 | 1024    | Base     |
| `chunk_overlap`                 | `int`                  | Overlapping units between chunks          | 200     | Base     |
| `min_chunk_size`                | `int \| None`          | Minimum size for a chunk                  | None    | Base     |
| `length_function`               | `Callable[[str], int]` | Function to measure text length           | `len`   | Base     |
| `strip_whitespace`              | `bool`                 | Strip leading/trailing whitespace         | False   | Base     |
| `max_agent_retries`             | `int`                  | Maximum retries for agent calls           | 3       | Specific |
| `min_proposition_length`        | `int`                  | Minimum length for valid propositions     | 20      | Specific |
| `max_propositions_per_chunk`    | `int`                  | Maximum propositions in a chunk           | 15      | Specific |
| `min_propositions_per_chunk`    | `int`                  | Minimum propositions to form a chunk      | 3       | Specific |
| `enable_proposition_caching`    | `bool`                 | Cache proposition extraction results      | True    | Specific |
| `enable_topic_caching`          | `bool`                 | Cache topic assignment results            | True    | Specific |
| `enable_refinement_caching`     | `bool`                 | Cache topic refinement results            | True    | Specific |
| `enable_proposition_validation` | `bool`                 | Validate proposition quality              | True    | Specific |
| `enable_topic_optimization`     | `bool`                 | Optimize topic assignments                | True    | Specific |
| `enable_coherence_scoring`      | `bool`                 | Score chunk coherence                     | True    | Specific |
| `fallback_to_recursive`         | `bool`                 | Fallback to recursive chunking on failure | True    | Specific |
| `include_proposition_metadata`  | `bool`                 | Include proposition-level metadata        | True    | Specific |
| `include_topic_scores`          | `bool`                 | Include topic coherence scores            | True    | Specific |
| `include_agent_metadata`        | `bool`                 | Include agent processing metadata         | True    | Specific |