CSV Loader

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)