Pinecone Agent Knowledge

Setup

Follow the instructions in the Pinecone Setup Guide to get started quickly with Pinecone.

pip install pinecone

We do not yet support Pinecone v6.x.x. We are actively working to achieve compatibility. In the meantime, we recommend using Pinecone v5.4.2 for the best experience.

Example

agent_with_knowledge.py

import os
import typer
from typing import Optional
from rich.prompt import Prompt

from agno.agent import Agent
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.vectordb.pineconedb import PineconeDb

api_key = os.getenv("PINECONE_API_KEY")
index_name = "thai-recipe-hybrid-search"

vector_db = PineconeDb(
    name=index_name,
    dimension=1536,
    metric="cosine",
    spec={"serverless": {"cloud": "aws", "region": "us-east-1"}},
    api_key=api_key,
    use_hybrid_search=True,
    hybrid_alpha=0.5,
)

knowledge_base = PDFUrlKnowledgeBase(
    urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=vector_db,
)

def pinecone_agent(user: str = "user"):
    run_id: Optional[str] = None

    agent = Agent(
        run_id=run_id,
        user_id=user,
        knowledge=knowledge_base,
        show_tool_calls=True,
        debug_mode=True,
    )

    if run_id is None:
        run_id = agent.run_id
        print(f"Started Run: {run_id}\n")
    else:
        print(f"Continuing Run: {run_id}\n")

    while True:
        message = Prompt.ask(f"[bold] :sunglasses: {user} [/bold]")
        if message in ("exit", "bye"):
            break
        agent.print_response(message)

if __name__ == "__main__":
    # Comment out after first run
    knowledge_base.load(recreate=True, upsert=True)

    typer.run(pinecone_agent)

Async Support ⚡

Pinecone also supports asynchronous operations, enabling concurrency and leading to better performance.

async_pinecone.py

import asyncio
from os import getenv

from agno.agent import Agent
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.vectordb.pineconedb import PineconeDb

api_key = getenv("PINECONE_API_KEY")
index_name = "thai-recipe-index"

vector_db = PineconeDb(
    name=index_name,
    dimension=1536,
    metric="cosine",
    spec={"serverless": {"cloud": "aws", "region": "us-east-1"}},
    api_key=api_key,
)

knowledge_base = PDFUrlKnowledgeBase(
    urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=vector_db,
)

agent = Agent(
    knowledge=knowledge_base,
    # 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,
)

if __name__ == "__main__":
    # Comment out after first run
    asyncio.run(knowledge_base.aload(recreate=False, upsert=True))

    # Create and use the agent
    asyncio.run(agent.aprint_response("How to make Tom Kha Gai", markdown=True))

Use aload() and aprint_response() methods with asyncio.run() for non-blocking operations in high-throughput applications.

PineconeDb Params

Parameter	Type	Default	Description
name	str	-	The name of the Pinecone index
dimension	int	-	The dimension of the embeddings
spec	Union[Dict, ServerlessSpec, PodSpec]	-	The index spec
embedder	Optional[Embedder]	None	Embedder instance for creating embeddings (defaults to OpenAIEmbedder if not provided)
metric	Optional[str]	"cosine"	The metric used for similarity search
additional_headers	Optional[Dict[str, str]]	None	Additional headers to pass to the Pinecone client
pool_threads	Optional[int]	1	The number of threads to use for the Pinecone client
namespace	Optional[str]	None	The namespace for the Pinecone index
timeout	Optional[int]	None	The timeout for Pinecone operations
index_api	Optional[Any]	None	The Index API object
api_key	Optional[str]	None	The Pinecone API key
host	Optional[str]	None	The Pinecone host
config	Optional[Config]	None	The Pinecone config
use_hybrid_search	bool	False	Whether to use hybrid search
hybrid_alpha	float	0.5	The alpha value for hybrid search

Developer Resources

• View Cookbook (Sync)
• View Cookbook (Async)