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2 changes: 1 addition & 1 deletion docs/api-reference/openapi.json

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263 changes: 75 additions & 188 deletions docs/documentation/configuration/ingestion/parsing_and_chunking.mdx
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---
title: 'Parsing & Chunking'
description: 'Learn how to configure document chunking in your R2R deployment'
---
## Parsing & Chunking

## Parsing
R2R supports different parsing and chunking providers to extract text from various document formats and break it down into manageable pieces for efficient processing and retrieval.

R2R supports different parsing providers to extract text from various document formats. To configure the parsing provider:
To configure the parsing and chunking settings, update the `[ingestion]` section in your `r2r.toml` file:

```toml example r2r.toml
[parsing]
provider = "unstructured_local" # | rag | unstructured_api
excluded_parsers = ["mp4"]
```
Available providers:
- `r2r`: Default offering for `light` installations, a simple and lightweight parser included in R2R.
- `unstructured_local`: Default offering for `full` installations, makes use of open source Unstructured package.
- `unstructured_api`: Cloud offering of Unstructured

### Supported File Types

**R2R supports parsing for the following file types:**

- BMP (Bitmap Image)
- CSV (Comma-Separated Values)
- DOC (Microsoft Word Document)
- DOCX (Microsoft Word Document)
- EML (Electronic Mail)
- EPUB (Electronic Publication)
- GIF (Graphics Interchange Format)
- HEIC (High-Efficiency Image Format)
- HTM (HyperText Markup)
- HTML (HyperText Markup Language)
- JPEG (Joint Photographic Experts Group)
- JPG (Joint Photographic Experts Group)
- JSON (JavaScript Object Notation)
- MD (Markdown)
- MSG (Microsoft Outlook Message)
- MP3 (MPEG Audio Layer III)
- MP4 (MPEG-4 Part 14)
- ODT (Open Document Text)
- ORG (Org Mode)
- PDF (Portable Document Format)
- P7S (PKCS#7)
- PNG (Portable Network Graphics)
- PPT (PowerPoint)
- PPTX (Microsoft PowerPoint Presentation)
- RST (reStructured Text)
- RTF (Rich Text Format)
- SVG (Scalable Vector Graphics)
- TSV (Tab-Separated Values)
- TXT (Plain Text)
- XLS (Microsoft Excel Spreadsheet)
- XLSX (Microsoft Excel Spreadsheet)
- XML (Extensible Markup Language)
- TIFF (Tagged Image File Format)
- MP4 (MPEG-4 Part 14)

<Note> Parsing providers for an R2R system cannot be configured at runtime and are instead configured server side. </Note>

**Refer to the [Unstructured documentation](https://docs.unstructured.io/welcome) for details about their ingestion capabilities and limitations.**

## Chunking

R2R uses chunking to break down parsed documents into smaller, manageable pieces for efficient processing and retrieval. Configure the chunking settings in `r2r.toml`:

```toml r2r.toml
[chunking]
provider = "unstructured_local"
strategy = "auto"
chunking_strategy = "by_title"
new_after_n_chars = 512
max_characters = 1_024
combine_under_n_chars = 128
overlap = 20
```toml
[ingestion]
provider = "r2r" # or "unstructured_local" or "unstructured_api"
# ... provider-specific settings ...
```

Key chunking configuration options:

- `provider`: The chunking provider (defaults to "r2r").

**For R2R:**
- `chunking_strategy`: The chunking method ("recursive").
- `chunk_size`: The target size for each chunk.
- `chunk_overlap`: The number of characters to overlap between chunks.
- `excluded_parsers`: List of parsers to exclude (e.g., ["mp4"]).

**For Unstructured:**
- `strategy`: The overall chunking strategy ("auto", "fast", or "hi_res").
- `chunking_strategy`: The specific chunking method ("by_title" or "basic").
- `new_after_n_chars`: Soft maximum size for a chunk.
- `max_characters`: Hard maximum size for a chunk.
- `combine_under_n_chars`: Minimum size for combining small sections.
- `overlap`: Number of characters to overlap between chunks.

## Supported Providers

<Tabs>
<Tab title="Unstructured Local">
```python
# Ensure unstructured is installed
# Refer to the full installation docs here - [https://r2r-docs.sciphi.ai/introduction/documentation/installation/full/docker]

# Set 'provider = "unstructured_local"' for `ingestion` in `my_r2r.toml`.
r2r serve --config-path=my_r2r.toml
```
### Supported Providers

R2R offers two main parsing and chunking providers:

1. **R2R (default for 'light' installation)**:
- Uses R2R's built-in parsing and chunking logic.
- Supports a wide range of file types, including TXT, JSON, HTML, PDF, DOCX, PPTX, XLSX, CSV, Markdown, images, audio, and video.
- Configuration options:
```toml
[ingestion]
provider = "r2r"
chunking_strategy = "recursive"
chunk_size = 1_024
chunk_overlap = 512
excluded_parsers = ["mp4"]
```
- `chunking_strategy`: The chunking method ("recursive").
- `chunk_size`: The target size for each chunk.
- `chunk_overlap`: The number of characters to overlap between chunks.
- `excluded_parsers`: List of parsers to exclude (e.g., ["mp4"]).

2. **Unstructured (default for 'full' installation)**:
- Leverages Unstructured's open-source ingestion platform.
- Provides more advanced parsing capabilities.
- Configuration options:
```toml
[ingestion]
provider = "unstructured_local"
strategy = "auto"
chunking_strategy = "by_title"
new_after_n_chars = 512
max_characters = 1_024
combine_under_n_chars = 128
overlap = 20
```
- `strategy`: The overall chunking strategy ("auto", "fast", or "hi_res").
- `chunking_strategy`: The specific chunking method ("by_title" or "basic").
- `new_after_n_chars`: Soft maximum size for a chunk.
- `max_characters`: Hard maximum size for a chunk.
- `combine_under_n_chars`: Minimum size for combining small sections.
- `overlap`: Number of characters to overlap between chunks.

This is the default `full` provider, using the open-source Unstructured library for local processing.
</Tab>

<Tab title="Unstructured API">
```python
export UNSTRUCTURED_API_KEY=your_unstructured_api_key
export UNSTRUCTURED_API_URL=your_unstructured_api_url
# .. set other environment variables

# Optional - Update default provider
# Set 'provider = "unstructured_api"' for `ingestion` in `my_r2r.toml`.
r2r serve --config-path=my_r2r.toml
```
### Supported File Types

Uses the Unstructured platform API for chunking, which may offer additional features or performance benefits.
</Tab>
Both R2R and Unstructured providers support parsing a wide range of file types, including:

<Tab title="R2R">
```python
# No additional setup required
- TXT, JSON, HTML, PDF, DOCX, PPTX, XLSX, CSV, Markdown, images (BMP, GIF, HEIC, JPEG, JPG, PNG, SVG, TIFF), audio (MP3), video (MP4), and more.

# Optional - Update default provider
# Set 'provider = "r2r"' for `ingestion` in `my_r2r.toml`.
r2r serve --config-path=my_r2r.toml
```
This is the default `light` provider, using the open-source R2R library for local processing.
Refer to the [Unstructured documentation](https://docs.unstructured.io/welcome) for more details on their ingestion capabilities and limitations.

</Tab>
</Tabs>
### Configuring Parsing & Chunking

### Advanced Configuration Options
To configure parsing and chunking settings, update the `[ingestion]` section in your `r2r.toml` file with the desired provider and its specific settings.

When using the Unstructured chunking provider, you can specify additional parameters in the configuration file:
For example, to use the R2R provider with custom chunk size and overlap:

```toml
[ingestion]
provider = "unstructured_local"
strategy = "auto" # "auto", "fast", or "hi_res"
chunking_strategy = "by_title" # "by_title" or "basic"

# Core chunking parameters
combine_under_n_chars = 128
max_characters = 500
new_after_n_chars = 1500
overlap = 0

# Additional chunking options
coordinates = false
encoding = "utf-8"
extract_image_block_types = [] # List of image block types to extract
gz_uncompressed_content_type = null
hi_res_model_name = null
include_orig_elements = true
include_page_breaks = false

languages = [] # List of languages to consider
multipage_sections = true
ocr_languages = [] # List of languages for OCR
output_format = "application/json"
overlap_all = false
pdf_infer_table_structure = true

similarity_threshold = null
skip_infer_table_types = [] # List of table types to skip inference
split_pdf_concurrency_level = 5
split_pdf_page = true
starting_page_number = null
unique_element_ids = false
xml_keep_tags = false
provider = "r2r"
chunking_strategy = "recursive"
chunk_size = 2_048
chunk_overlap = 256
excluded_parsers = ["mp4"]
```

These options allow fine-tuning of the chunking process for specific document types or requirements. Refer to the Unstructured [documentation here](https://docs.unstructured.io/open-source/core-functionality/chunking) for more details on the available settings.

### Runtime Configuration

The chunking configuration can be specified at runtime with the [`ingest_files`](/api-reference/endpoint/ingest_files) endpoint, allowing dynamic adjustment of chunking parameters based on the input documents or specific use cases.
Or, to use the Unstructured provider with a specific chunking strategy and character limits:

### Combining Chunking with Other R2R Components

Chunking is a crucial part of the document processing pipeline in R2R. It works in conjunction with other components such as parsing, embedding, and retrieval. For example:

```python
response = client.ingest_files(
file_paths=["document.pdf"],
ingestion_config={
"provider": "unstructured_local",
"chunking_strategy": "by_title",
"max_characters": 1000
},
embedding_config={...},
# ... other configurations
)
```toml
[ingestion]
provider = "unstructured_local"
strategy = "hi_res"
chunking_strategy = "basic"
new_after_n_chars = 1_000
max_characters = 2_000
combine_under_n_chars = 256
overlap = 50
```

For more detailed information on configuring chunking and other ingestion settings, please refer to the [Ingestion Configuration documentation](/documentation/configuration/ingestion/overview).

## Next Steps
Adjust the settings based on your specific requirements and the characteristics of your input documents.

To learn more about configuring other components of R2R, explore the following pages:
### Next Steps

- [Embedding Configuration](/documentation/configuration/ingestion/embedding)
- [Knowledge Graph Configuration](/documentation/configuration/knowledge-graph/overview)
- [Retrieval Configuration](/documentation/configuration/retrieval/overview)
- Learn more about [Embedding Configuration](/documentation/configuration/ingestion/embedding).
- Explore [Knowledge Graph Configuration](/documentation/configuration/knowledge-graph/overview).
- Check out [Retrieval Configuration](/documentation/configuration/retrieval/overview).
12 changes: 6 additions & 6 deletions py/core/main/api/data/retrieval_router_openapi.yml
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Expand Up @@ -12,7 +12,7 @@ search:
query="Who is Aristotle?",
vector_search_settings={
"use_vector_search": True,
"filters": {"document_id": {"eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"filters": {"document_id": {"$eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"search_limit": 20,
"use_hybrid_search": True
},
Expand Down Expand Up @@ -42,7 +42,7 @@ search:
"query": "Who is Aristotle?",
"vector_search_settings": {
"use_vector_search": true,
"filters": {"document_id": {"eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"filters": {"document_id": {"$eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"search_limit": 20,
"use_hybrid_search": true
},
Expand Down Expand Up @@ -83,7 +83,7 @@ rag:
query="Who is Aristotle?",
vector_search_settings={
"use_vector_search": True,
"filters": {"document_id": {"eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"filters": {"document_id": {"$eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"search_limit": 20,
"use_hybrid_search": True
},
Expand Down Expand Up @@ -118,7 +118,7 @@ rag:
"query": "Who is Aristotle?",
"vector_search_settings": {
"use_vector_search": true,
"filters": {"document_id": {"eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"filters": {"document_id": {"$eq": "3e157b3a-8469-51db-90d9-52e7d896b49b"}},
"search_limit": 20,
"use_hybrid_search": True
},
Expand Down Expand Up @@ -173,7 +173,7 @@ agent:
],
vector_search_settings={
"use_vector_search": True,
"filters": {"document_id": {"eq": "5e157b3a-8469-51db-90d9-52e7d896b49b"}},
"filters": {"document_id": {"$eq": "5e157b3a-8469-51db-90d9-52e7d896b49b"}},
"search_limit": 20,
"use_hybrid_search": True
},
Expand All @@ -197,7 +197,7 @@ agent:
],
"vector_search_settings": {
"use_vector_search": true,
"filters": {"document_id": {"eq": "5e157b3a-8469-51db-90d9-52e7d896b49b"}},
"filters": {"document_id": {"$eq": "5e157b3a-8469-51db-90d9-52e7d896b49b"}},
"search_limit": 20,
"use_hybrid_search": true
},
Expand Down

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