from agno.agent import Agent from agno.document.chunking.fixed import FixedSizeChunking from agno.knowledge.pdf_url import PDFUrlKnowledgeBase from agno.vectordb.pgvector import PgVector db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai" knowledge_base = PDFUrlKnowledgeBase( urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"], vector_db=PgVector(table_name="recipes_fixed_size_chunking", db_url=db_url), chunking_strategy=FixedSizeChunking(), ) knowledge_base.load(recreate=False) # Comment out after first run agent = Agent( knowledge_base=knowledge_base, search_knowledge=True, ) agent.print_response("How to make Thai curry?", markdown=True)
chunk_size
int
5000
overlap
0
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