> ## 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.

# JSON Loader

> Load JSON and JSONL files with flexible record extraction

## Overview

JSON loader processes JSON and JSONL files with support for single or multi-document extraction using JQ queries. Flexible content and metadata mapping for structured data.

**Loader Class:** `JSONLoader`

**Config Class:** `JSONLoaderConfig`

## Install

<Note>
  Install the JSON loader optional dependency group:

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

## Examples

```python theme={null}
from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders.json import JSONLoader
from upsonic.loaders.config import JSONLoaderConfig
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 multi-document extraction
loader_config = JSONLoaderConfig(
    mode="multi",
    record_selector=".articles[]",
    content_mapper=".title + ' ' + .body",
    metadata_mapper={"author": ".author", "date": ".published"}
)
loader = JSONLoader(loader_config)

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

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

# Query with Agent
agent = Agent("anthropic/claude-sonnet-4-5")
task = Task("Find articles about AI", 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 |
| `mode` | `"single" \| "multi"` | Processing mode | "single" | Specific |
| `record_selector` | `str \| None` | JQ query to select records (required for multi) | None | Specific |
| `content_mapper` | `str` | JQ query to extract content | "." | Specific |
| `metadata_mapper` | `dict[str, str] \| None` | Map metadata keys to JQ queries | None | Specific |
| `content_synthesis_mode` | `"json" \| "text"` | Format for extracted content | "json" | Specific |
| `json_lines` | `bool` | File is in JSON Lines format | False | Specific |


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