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Langchain Cohere Qdrant Doc Retrieval

screenshot of Langchain Cohere Qdrant Doc Retrieval

This Flask backend API takes a document in multiple formats and allows you to perform semantic search using Langchain, Cohere and Qdrant.

Github

Overview

The LangChain-Cohere-Qdrant document retrieval system is a powerful Flask backend API designed to streamline the way you manage and search documents. With support for a variety of file formats including text files, presentations, images, and more, it leverages the Cohere Multilingual API to facilitate semantic searches in over 100 languages. This makes it an excellent tool for developers looking to implement robust document management and retrieval systems in their applications.

By using the Qdrant vector database to store embeddings, this API ensures that your searches are not only fast but also semantically relevant, improving the quality of search results. Whether you are building an advanced search application or enhancing existing document functionalities, this API provides a scalable and effective solution.

Features

  • Multilingual Support: Seamlessly perform semantic searches in over 100 languages thanks to the integrated Cohere Multilingual API.

  • Multiple File Format Compatibility: Accepts a variety of document types such as .txt, .docx, .pptx, .jpg, .png, .eml, .html, and .pdf, making it versatile for different use cases.

  • Vector Database Integration: Utilizes Qdrant for storing embeddings, allowing for efficient and accurate search functionality.

  • User-Friendly Setup: Easy installation process on macOS/Linux with clear steps for setting up the environment and dependencies.

  • Accessible API Endpoints: Provides straightforward API routes for embedding and retrieval operations, enabling easy integration with any frontend application.

  • Configuration Flexibility: Offers customizable settings through environment variables, allowing users to tailor the application to their specific needs.

  • Support for Frontend Connectivity: Designed to work smoothly with frontend applications, making it a convenient choice for developers looking to enhance user interaction.

  • Open for Exploration: Users are encouraged to explore and modify the code to suit their requirements, fostering a spirit of innovation and customization.