Qdrant

pip install "praisonai[tools]"

export QDRANT_URL=http://localhost:6333
export QDRANT_API_KEY=your_api_key  # Optional for cloud

from praisonai_tools import QdrantTool

# Initialize
qdrant = QdrantTool(url="http://localhost:6333")

# Search
results = qdrant.search("products", query_vector=[0.1, 0.2, ...], limit=5)
print(results)

from praisonaiagents import Agent
from praisonai_tools import QdrantTool

qdrant = QdrantTool(url="http://localhost:6333")

agent = Agent(
    name="SearchAgent",
    instructions="You perform semantic search using Qdrant.",
    tools=[qdrant]
)

response = agent.chat("Find similar products to item 123")
print(response)

from praisonai_tools import QdrantTool

qdrant = QdrantTool(url="http://localhost:6333")
results = qdrant.search("documents", query_vector=[0.1, 0.2, 0.3], limit=5)

qdrant.upsert("documents", [
    {"id": 1, "vector": [0.1, 0.2, 0.3], "payload": {"text": "Hello"}}
])

qdrant.create_collection("my_collection", vector_size=384)

docker run -d --name qdrant \
    -p 6333:6333 \
    qdrant/qdrant