YAML Loader - Upsonic AI

Overview

YAML loader processes YAML files using jq-style queries to split documents and extract content. Supports multiple document files, metadata flattening, and flexible content synthesis modes. Loader Class: YAMLLoader Config Class: YAMLLoaderConfig

Install

Install the YAML loader optional dependency group:

uv pip install "upsonic[yaml-loader]"

Examples

from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders.yaml import YAMLLoader
from upsonic.loaders.config import YAMLLoaderConfig
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.text_splitter.recursive import RecursiveChunker, RecursiveChunkingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode

# Configure loader
loader_config = YAMLLoaderConfig(
    split_by_jq_query=".articles[]",
    content_synthesis_mode="smart_text",
    metadata_jq_queries={"author": ".author", "date": ".published"}
)
loader = YAMLLoader(loader_config)

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

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

# Query with Agent
agent = Agent("anthropic/claude-sonnet-4-5")
task = Task("Find articles about machine learning", 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
`split_by_jq_query`	`str`	jq query to select document objects	”.”	Specific
`handle_multiple_docs`	`bool`	Process multiple documents separated by ’---‘	True	Specific
`content_synthesis_mode`	`"canonical_yaml" \| "json" \| "smart_text"`	Content format	”canonical_yaml”	Specific
`yaml_indent`	`int`	Indentation level for YAML output	2	Specific
`json_indent`	`int \| None`	Indentation level for JSON output	2	Specific
`flatten_metadata`	`bool`	Flatten nested structure into metadata	True	Specific
`metadata_jq_queries`	`dict[str, str] \| None`	Map metadata keys to jq queries	None	Specific

​Overview

​Install

​Examples

​Parameters

Overview

Install

Examples

Parameters