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Langchain Cohere Qdrant Retrieval

screenshot of Langchain Cohere Qdrant Retrieval

This is a template retrieval repo to create a Flask api server using LangChain with Cohere embeddings and Qdrant Vector Database

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Product Analysis: langchain-cohere-qdrant-retrieval

Overview

LangChain-Cohere-Qdrant-Retrieval is a template retrieval repository aimed at creating a Flask API server. The server utilizes LangChain, allowing users to search in over 100 languages using Cohere embeddings and the Qdrant Vector Database. This repository provides instructions on how to install and set up the necessary dependencies and environment variables.

Features

  • Flask API Server: Create a Flask API server to host the LangChain-Cohere-Qdrant-Retrieval functionality.
  • PDF Search: Accept PDF files and enable search functionality across a wide range of languages.
  • Cohere Embeddings: Utilize Cohere embeddings to enhance the search capabilities of the application.
  • Qdrant Vector Database: Use the Qdrant Vector Database to store and retrieve vectors for efficient searching.

Summary

The LangChain-Cohere-Qdrant-Retrieval repository allows users to create a Flask API server capable of searching PDF files in multiple languages. By leveraging the power of Cohere embeddings and the Qdrant Vector Database, users can efficiently search for information across a wide range of languages. The installation guide provides step-by-step instructions to set up the necessary dependencies and environment variables.