> ## Documentation Index
> Fetch the complete documentation index at: https://docs.phidata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# PgVector

<CodeGroup>
  ```python agent.py theme={null}
  from phi.agent import Agent
  from phi.storage.agent.postgres import PgAgentStorage
  from phi.knowledge.pdf import PDFUrlKnowledgeBase
  from phi.vectordb.pgvector import PgVector2

  db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

  agent = Agent(
  storage=PgAgentStorage(table_name="recipe_agent", db_url=db_url),
  knowledge_base=PDFUrlKnowledgeBase(
  urls=["https://phi-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
  vector_db=PgVector2(collection="recipe_documents", db_url=db_url),
  ), # Show tool calls in the response
  show_tool_calls=True, # Enable the agent to search the knowledge base
  search_knowledge=True, # Enable the agent to read the chat history
  read_chat_history=True,
  )

  # Comment out after first run

  agent.knowledge_base.load(recreate=False) # type: ignore

  agent.print_response("How do I make pad thai?", markdown=True)

  ```
</CodeGroup>

## PgVectorDb Params

<Snippet file="vectordb_pgvector_params.mdx" />