Integrations
Qdrant Integration
Examples
- Introduction
- Agents
- Models
- Integrations
- Agent Teams
- Use Cases
How To
Integrations
Qdrant Integration
Example
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.qdrant import Qdrant
api_key = os.getenv("QDRANT_API_KEY")
qdrant_url = os.getenv("QDRANT_URL")
collection_name = "thai-recipe-index"
vector_db = Qdrant(
collection=collection_name,
url=qdrant_url,
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=True, upsert=True)
def qdrant_agent(user: str = "user"):
run_id: Optional[str] = None
agent = Agent(
run_id=run_id,
user_id=user,
knowledge_base=knowledge_base,
tool_calls=True,
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(qdrant_agent)
Usage
1
Create a virtual environment
Open the Terminal
and create a python virtual environment.
2
Install libraries
pip install -U qdrant-client pypdf openai phidata
3
Run Qdrant Agent
Information
- View on Github
On this page