Qdrant is an open-source vector similarity search engine built for production-ready vector search applications.
It provides a convenient API to store, search, and manage vectors with additional payload data.
Obiguard provides a proxy to Qdrant, allowing you to use virtual keys and observability features.
from obiguard import Obiguardclient = Obiguard( obiguard_api_key="vk-obg***", # Your Obiguard virtual key custom_host="QDRANT_HOST" # Replace with your Qdrant host)response = client.post( url="https://xxxx-xxx-xxx-xx-xxxxxx.us-west-2-0.aws.cloud.qdrant.io", # Qdrant search endpoint, you can use any Qdrant endpoint)print(response)
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from obiguard import Obiguardclient = Obiguard( obiguard_api_key="vk-obg***", # Your Obiguard virtual key custom_host="QDRANT_HOST" # Replace with your Qdrant host)response = client.post( url="https://xxxx-xxx-xxx-xx-xxxxxx.us-west-2-0.aws.cloud.qdrant.io", # Qdrant search endpoint, you can use any Qdrant endpoint)print(response)
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from openai import OpenAIfrom obiguard import OBIGUARD_GATEWAY_URL, createHeadersopenai = OpenAI( api_key='QDRANT_API_KEY', base_url=OBIGUARD_GATEWAY_URL, default_headers=createHeaders( provider="qdrant", obiguard_api_key="vk-obg***", # Your Obiguard virtual key custom_host="QDRANT_HOST" # Replace with your Qdrant host ))response = openai.post( url="https://xxxx-xxx-xxx-xx-xxxxxx.us-west-2-0.aws.cloud.qdrant.io", # Qdrant search endpoint, You can use any Qdrant endpoint)print(response)