from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode
# Create embedding provider
embedding = OpenAIEmbedding(OpenAIEmbeddingConfig(
model_name="text-embedding-3-small",
batch_size=100
))
# Setup KnowledgeBase
vectordb = ChromaProvider(ChromaConfig(
collection_name="openai_docs",
vector_size=1536,
connection=ConnectionConfig(mode=Mode.IN_MEMORY)
))
kb = KnowledgeBase(
sources=["document.txt"],
embedding_provider=embedding,
vectordb=vectordb
)
# Query with Agent
agent = Agent("openai/gpt-4o")
task = Task("What is this document about?", context=[kb])
result = agent.do(task)
print(result)