> ## 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.

# CSV Loader

> Load CSV files with flexible row handling and content synthesis

## Overview

CSV loader processes CSV files with options to create documents per row, per chunk, or as a single document. Supports column filtering and flexible content formatting.

**Loader Class:** `CSVLoader`

**Config Class:** `CSVLoaderConfig`

## Install

<Note>
  Install the CSV loader optional dependency group:

  ```bash theme={null}
  uv pip install "upsonic[csv-loader]"
  ```
</Note>

## Examples

```python theme={null}
from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders.csv import CSVLoader
from upsonic.loaders.config import CSVLoaderConfig
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.text_splitter.recursive import RecursiveChunker, RecursiveChunkingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode

# Configure loader for per-row documents
loader_config = CSVLoaderConfig(
    split_mode="per_row",
    content_synthesis_mode="concatenated",
    include_columns=["name", "description"]
)
loader = CSVLoader(loader_config)

# Setup KnowledgeBase
embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
chunker = RecursiveChunker(RecursiveChunkingConfig())
vectordb = ChromaProvider(ChromaConfig(
    collection_name="csv_data",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))

kb = KnowledgeBase(
    sources=["data.csv"],
    embedding_provider=embedding,
    vectordb=vectordb,
    loaders=[loader],
    splitters=[chunker]
)

# Query with Agent
agent = Agent("anthropic/claude-sonnet-4-5")
task = Task("Find products matching 'laptop'", context=[kb])
result = agent.do(task)
print(result)
```

## Parameters

| Parameter | Type | Description | Default | Source |
| - | - | - | - | - |
| `encoding` | `str \| None` | File encoding (auto-detected if None) | None | Base |
| `error_handling` | `"ignore" \| "warn" \| "raise"` | How to handle loading errors | "warn" | Base |
| `include_metadata` | `bool` | Whether to include file metadata | True | Base |
| `custom_metadata` | `dict` | Additional metadata to include | {} | Base |
| `max_file_size` | `int \| None` | Maximum file size in bytes | None | Base |
| `skip_empty_content` | `bool` | Skip documents with empty content | True | Base |
| `content_synthesis_mode` | `"concatenated" \| "json"` | How to create document content from rows | "concatenated" | Specific |
| `split_mode` | `"single_document" \| "per_row" \| "per_chunk"` | How to split CSV into documents | "single\_document" | Specific |
| `rows_per_chunk` | `int` | Number of rows per document (for per\_chunk mode) | 100 | Specific |
| `include_columns` | `list[str] \| None` | Only include these columns | None | Specific |
| `exclude_columns` | `list[str] \| None` | Exclude these columns | None | Specific |
| `delimiter` | `str` | CSV delimiter | "," | Specific |
| `quotechar` | `str` | CSV quote character | '"' | Specific |
| `has_header` | `bool` | Whether CSV has a header row | True | Specific |


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