import typer
from typing import Optional
from os import getenv
from sqlalchemy.engine import create_engine
from bitca.assistant import Assistant
from bitca.knowledge.pdf import PDFUrlKnowledgeBase
from bitca.vectordb.singlestore import S2VectorDb
USERNAME = getenv("SINGLESTORE_USERNAME")
PASSWORD = getenv("SINGLESTORE_PASSWORD")
HOST = getenv("SINGLESTORE_HOST")
PORT = getenv("SINGLESTORE_PORT")
DATABASE = getenv("SINGLESTORE_DATABASE")
SSL_CERT = getenv("SINGLESTORE_SSL_CERT", None)
db_url = f"mysql+pymysql://{USERNAME}:{PASSWORD}@{HOST}:{PORT}/{DATABASE}?charset=utf8mb4"
if SSL_CERT:
db_url += f"&ssl_ca={SSL_CERT}&ssl_verify_cert=true"
db_engine = create_engine(db_url)
knowledge_base = PDFUrlKnowledgeBase(
urls=["https://bitca-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
vector_db=S2VectorDb(
collection="recipes",
db_engine=db_engine,
schema=DATABASE,
),
)
# Comment out after first run
knowledge_base.load(recreate=False)
def pdf_assistant(user: str = "user"):
run_id: Optional[str] = None
assistant = Assistant(
run_id=run_id,
user_id=user,
knowledge_base=knowledge_base,
use_tools=True,
show_tool_calls=True,
# Uncomment the following line to use traditional RAG
# add_references_to_prompt=True,
)
if run_id is None:
run_id = assistant.run_id
print(f"Started Run: {run_id}\n")
else:
print(f"Continuing Run: {run_id}\n")
while True:
assistant.cli_app(markdown=True)
if __name__ == "__main__":
typer.run(pdf_assistant)
