PineconeDB

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

from phi.agent import Agent
from phi.knowledge.pdf import PDFUrlKnowledgeBase
from phi.vectordb.pineconedb import PineconeDB

api_key = os.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://phi-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
vector_db=vector_db,
)

# Comment out after first run

knowledge_base.load(recreate=False, upsert=True)

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

    agent = Agent(
        run_id=run_id,
        user_id=user,
        knowledge_base=knowledge_base,
        use_tools=True,
        show_tool_calls=True,
        debug_mode=True,
        # Uncomment the following line to use traditional RAG
        # add_references_to_prompt=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)