qdrant-client and Basic-Qdrant-Upload-and-Search-Example
The official Python client library provides the SDK needed to interact with Qdrant, while the example code demonstrates practical implementation patterns for that client in AI chatbot applications, making them complements rather than competitors.
About qdrant-client
qdrant/qdrant-client
Python client for Qdrant vector search engine
Provides type-safe bindings for all Qdrant API methods with dual REST and gRPC transports, plus a local in-memory or disk-persisted mode for development without a server. Built-in embedding inference via FastEmbed (CPU/GPU) or Qdrant Cloud models enables end-to-end vector workflows in a single client, simplifying document upload and semantic search operations. Supports both synchronous and asynchronous request patterns with helper methods like `upload_collection` that handle chunking and batch operations automatically.
About Basic-Qdrant-Upload-and-Search-Example
libraryofcelsus/Basic-Qdrant-Upload-and-Search-Example
Example code on how to upload and search a Qdrant Vector Database for Ai Chatbot Retrieval Frameworks
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