Agentic RAG with LanceDB

This example demonstrates how to implement Agentic RAG using LanceDB vector database with OpenAI embeddings, enabling the agent to search and retrieve relevant information dynamically.

Code

agentic_rag_lancedb.py

"""
1. Run: `pip install openai lancedb tantivy pypdf sqlalchemy agno` to install the dependencies
2. Run: `python cookbook/rag/04_agentic_rag_lancedb.py` to run the agent
"""

from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIChat
from agno.vectordb.lancedb import LanceDb, SearchType

knowledge = Knowledge(
    # Use LanceDB as the vector database and store embeddings in the `recipes` table
    vector_db=LanceDb(
        table_name="recipes",
        uri="tmp/lancedb",
        search_type=SearchType.vector,
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

knowledge.add_content(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"
)

agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    knowledge=knowledge,
    # Add a tool to search the knowledge base which enables agentic RAG.
    # This is enabled by default when `knowledge` is provided to the Agent.
    search_knowledge=True,
    markdown=True,
)
agent.print_response(
    "How do I make chicken and galangal in coconut milk soup", stream=True
)

Usage

1. Create a virtual environment

   Open the Terminal and create a python virtual environment.

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Install libraries

   pip install -U agno openai lancedb tantivy pypdf sqlalchemy
   
3. Export your OpenAI API key

   Mac/Linux

     export OPENAI_API_KEY="your_openai_api_key_here"
   
4. Create a Python file

   Create a Python file and add the above code.

   touch agentic_rag_lancedb.py
   
5. Run Agent

   Mac

   python agentic_rag_lancedb.py
   
6. Find All Cookbooks

   Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:

   Agno Cookbooks on GitHub