YAML Loader

pip install "upsonic[loaders]"

from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders import YAMLLoader, YAMLLoaderConfig
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.text_splitter 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("openai/gpt-4o")
task = Task("Find articles about machine learning", context=[kb])
result = agent.do(task)
print(result)