from upsonic import Agent, Task, KnowledgeBase
from upsonic.loaders import HTMLLoader, HTMLLoaderConfig
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 = HTMLLoaderConfig(
extract_text=True,
extract_tables=True,
table_format="markdown",
include_links=True
)
loader = HTMLLoader(loader_config)
# Setup KnowledgeBase
embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())
chunker = RecursiveChunker(RecursiveChunkingConfig())
vectordb = ChromaProvider(ChromaConfig(
collection_name="html_docs",
vector_size=1536,
connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))
kb = KnowledgeBase(
sources=["https://example.com/article"],
embedding_provider=embedding,
vectordb=vectordb,
loaders=[loader],
splitters=[chunker]
)
# Query with Agent
agent = Agent("openai/gpt-4o")
task = Task("Summarize the article", context=[kb])
result = agent.do(task)
print(result)