Qdrant

pip install "upsonic[rag]"

from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings.openai_provider import OpenAIEmbeddingProvider
from upsonic.vectordb import QdrantProvider, QdrantConfig, ConnectionConfig, Mode, HNSWIndexConfig

# Setup embedding provider
embedding = OpenAIEmbeddingProvider(api_key="your-api-key")

# Embedded mode
config = QdrantConfig(
    collection_name="my_collection",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.EMBEDDED, db_path="./qdrant_db"),
    index=HNSWIndexConfig(m=16, ef_construction=200),
    on_disk_payload=False
)
vectordb = QdrantProvider(config)

# Create knowledge base
kb = KnowledgeBase(
    sources="document.pdf",
    embedding_provider=embedding,
    vectordb=vectordb
)

# Use with Agent
agent = Agent("openai/gpt-4o")
task = Task(
    description="Find relevant information",
    context=[kb]
)
result = agent.do(task)