PGVector

pip install "upsonic[rag]"

from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings.openai_provider import OpenAIEmbeddingProvider
from upsonic.vectordb import PgvectorProvider, PgVectorConfig, HNSWIndexConfig
from pydantic import SecretStr

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

# Create PGVector configuration
config = PgVectorConfig(
    collection_name="my_collection",
    vector_size=1536,
    connection_string=SecretStr("postgresql://user:password@localhost/dbname"),
    schema_name="public",
    index=HNSWIndexConfig(m=16, ef_construction=200)
)
vectordb = PgvectorProvider(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="Search the database",
    context=[kb]
)
result = agent.do(task)