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Ask AI
"""Run `pip install ddgs pgvector google.genai` to install dependencies."""
from agno.agent import Agent
from agno.db.postgres.postgres import PostgresDb
from agno.knowledge import PDFUrlKnowledgeBase
from agno.models.google import Gemini
from agno.tools.websearch import WebSearchTools
from agno.vectordb.pgvector import PgVector
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
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", db_url=db_url),
)
knowledge_base.load(recreate=True) # Comment out after first run
agent = Agent(
model=Gemini(id="gemini-2.0-flash-001"),
tools=[WebSearchTools()],
knowledge=knowledge_base,
# Store the memories and summary in a database
db=PostgresDb(db_url=db_url, memory_table="agent_memory"),
update_memory_on_run=True,
enable_session_summaries=True,
# This setting adds a tool to search the knowledge base for information
search_knowledge=True,
# This setting adds a tool to get chat history
read_chat_history=True,
# Add the previous chat history to the messages sent to the Model.
add_history_to_context=True,
# This setting adds 6 previous messages from chat history to the messages sent to the LLM
num_history_runs=6,
markdown=True,
)
agent.print_response("Whats is the latest AI news?")
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
pass
Run the Example
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Ask AI
# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/90_models/google/gemini
# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate
# Optiona: Run PgVector (needs docker)
./cookbook/scripts/run_pgvector.sh
python storage_and_memory.py