Pinecone Agent Knowledge

Setup

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

​Example

agent_with_knowledge.py

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

from bitca.agent import Agent
from bitca.knowledge.pdf import PDFUrlKnowledgeBase
from bitca.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://bitca-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=vector_db,
)

# Comment out after first run
knowledge_base.load(recreate=True, upsert=True)


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__":
    typer.run(pinecone_agent)

​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