​
代码

cookbook/agent_concepts/knowledge/vector_dbs/mongo_db/mongo_db_hybrid_search.py
import typer
from agno.agent import Agent
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.vectordb.mongodb import MongoDb
from agno.vectordb.search import SearchType
from rich.prompt import Prompt

# MongoDB Atlas 连接字符串
"""
示例连接字符串：
"mongodb_srv://<username>:<password>@cluster0.mongodb.net/?retryWrites=true&w=majority"
"mongodb://localhost:27017/agno?authSource=admin"
"""
mdb_connection_string = "mongodb_srv://<username>:<password>@cluster0.mongodb.net/?retryWrites=true&w=majority"

vector_db = MongoDb(
    collection_name="recipes",
    db_url=mdb_connection_string,
    search_index_name="recipes",
    search_type=SearchType.hybrid
)

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

def mongodb_agent(user: str = "user"):
    agent = Agent(
        user_id=user,
        knowledge=knowledge_base,
        search_knowledge=True,
    )

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


if __name__ == "__main__":
    # 首次运行时注释掉
    knowledge_base.load(recreate=True)

    typer.run(mongodb_agent)

​
用法

1

创建虚拟环境

打开 Terminal 并创建一个 python 虚拟环境。

python3 -m venv .venv
source .venv/bin/activate
2

设置您的 API 密钥

export OPENAI_API_KEY=xxx
3

安装库

pip install -U pymongo tantivy pypdf openai agno
4

运行 Agent

python cookbook/agent_concepts/knowledge/vector_dbs/mongo_db/mongo_db_hybrid_search.py