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Merge remote-tracking branch 'origin/hybrid-cloud-dev' into hybrid-cloud-dev
# Conflicts: # qdrant-landing/content/documentation/examples/rag-contract-management-stackit-aleph-alpha.md # qdrant-landing/content/documentation/examples/recommendation-system-ovhcloud.md
This commit is contained in:
Kacper Łukawski
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---
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title: Chat With Product PDF Manuals Using Hybrid Search
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weight: 27
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preview_image: /blog/hybrid-cloud-llamaindex/hybrid-cloud-llamaindex-tutorial.png
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aliases:
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- /documentation/tutorials/hybrid-search-llamaindex-jinaai/
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---
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---
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title: RAG System for Employee Onboarding
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weight: 30
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preview_image: /blog/hybrid-oracle-cloud-infrastructure/hybrid-cloud-oracle-cloud-infrastructure-tutorial.png
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aliases:
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- /documentation/tutorials/natural-language-search-oracle-cloud-infrastructure-cohere-langchain/
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---
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Technological advancements have made it possible to interact with websites using natural language. This tutorial will
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guide you through the process of integrating [Cohere](https://cohere.com/)'s language models with Qdrant to enable
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natural language search on your documentation. We are going to use [Langchain](https://langchain.com/) as an
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natural language search on your documentation. We are going to use [LangChain](https://langchain.com/) as an
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orchestrator. Everything will be hosted on [Oracle Cloud Infrastructure (OCI)](https://www.oracle.com/cloud/), so you
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can scale your application as needed, and do not send your data to third parties. That is especially important when you
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are working with confidential or sensitive data.
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---
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title: Private Chatbot for Interactive Learning
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weight: 23
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preview_image: /blog/hybrid-cloud-red-hat-openshift/hybrid-cloud-red-hat-openshift-tutorial.png
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aliases:
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- /documentation/tutorials/rag-chatbot-red-hat-openshift-haystack/
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---
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---
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title: Blog-Reading RAG Chatbot
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weight: 35
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preview_image: /blog/hybrid-cloud-scaleway/hybrid-cloud-scaleway-tutorial.png
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aliases:
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- /documentation/tutorials/rag-chatbot-scaleway/
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---
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- **LLM:** GPT-3.5, developed by OpenAI is utilized as the generator for producing answers.
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- **Framework:** [LangChain](https://www.langchain.com/) for extensive RAG capabilities.
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## Deploying Qdrant Hybrid Cloud on Scaleway
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[Scaleway Kapsule](https://www.scaleway.com/en/kubernetes-kapsule/) and [Kosmos](https://www.scaleway.com/en/kubernetes-kosmos/) are managed Kubernetes services from [Scaleway](https://www.scaleway.com/en/). They abstract away the complexities of managing and operating a Kubernetes cluster. The primary difference being, Kapsule clusters are composed solely of Scaleway Instances. Whereas, a Kosmos cluster is a managed multi-cloud Kubernetes engine that allows you to connect instances from any cloud provider to a single managed Control-Plane.
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1. To start using managed Kubernetes on Scaleway, follow the [platform-specific documentation](/documentation/hybrid-cloud/platform-deployment-options/#scaleway).
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2. Once your Kubernetes clusters are up, [you can begin deploying Qdrant Hybrid Cloud](/documentation/hybrid-cloud/).
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## Prerequisites
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To prepare the environment for working with Qdrant and related libraries, it's necessary to install all required Python packages. This can be done using Poetry, a tool for dependency management and packaging in Python. The code snippet imports various libraries essential for the tasks ahead, including `bs4` for parsing HTML and XML documents, `langchain` and its community extensions for working with language models and document loaders, and `Qdrant` for vector storage and retrieval. These imports lay the groundwork for utilizing Qdrant alongside other tools for natural language processing and machine learning tasks.
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---
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title: Private RAG Information Extraction Engine
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weight: 32
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preview_image: /blog/hybrid-cloud-vultr/hybrid-cloud-vultr-tutorial.png
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aliases:
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- /documentation/tutorials/rag-chatbot-vultr-dspy-ollama/
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---
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## Configuring the environment
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## CDeploying Qdrant Hybrid Cloud on Vultr
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All the services we are going to use in this tutorial will be running on [Vultr Kubernetes
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Engine](https://www.vultr.com/kubernetes/). That gives us a lot of flexibility in terms of scaling and managing the
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resources. Before we go further, make sure you have a Vultr account and a Kubernetes cluster running. Please follow the
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[official documentation](https://docs.vultr.com/vultr-kubernetes-engine) to get everything up and running.
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Engine](https://www.vultr.com/kubernetes/). That gives us a lot of flexibility in terms of scaling and managing the resources. Vultr manages the control plane and worker nodes and provides integration with other managed services such as Load Balancers, Block Storage, and DNS.
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1. To start using managed Kubernetes on Vultr, follow the [platform-specific documentation](/documentation/hybrid-cloud/platform-deployment-options/#vultr).
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2. Once your Kubernetes clusters are up, [you can begin deploying Qdrant Hybrid Cloud](/documentation/hybrid-cloud/).
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### Installing the necessary packages
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---
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title: Region-Specific Contract Management System
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weight: 28
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preview_image: /blog/hybrid-cloud-aleph-alpha/hybrid-cloud-aleph-alpha-tutorial.png
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aliases:
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- /documentation/tutorials/rag-contract-management-stackit-aleph-alpha/
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---
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Companies want their data to be kept and processed within specific geographical boundaries. For that reason, this RAG-centric tutorial focuses on dealing with a region-specific cloud provider. You will set up a contract management system using [Aleph Alpha's](https://aleph-alpha.com/) embeddings and LLM. You will host everything on [STACKIT](https://www.stackit.de/), a German business cloud provider. On this platform, you will run Qdrant Hybrid Cloud as well as the rest of your RAG application. This setup will ensure that your data is stored and processed in Germany.
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[//]: # (TODO: add link to Qdrant Hybrid Cloud above)
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## Components
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---
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title: Question-Answering System for AI Customer Support
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weight: 26
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preview_image: /blog/hybrid-cloud-airbyte/hybrid-cloud-airbyte-tutorial.png
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aliases:
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- /documentation/tutorials/rag-customer-support-cohere-airbyte-aws/
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---
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---
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title: Movie Recommendation System
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weight: 34
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preview_image: /blog/hybrid-cloud-ovhcloud/hybrid-cloud-ovhcloud-tutorial.png
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aliases:
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- /documentation/tutorials/recommendation-system-ovhcloud/
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---
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@@ -26,6 +27,13 @@ In this tutorial, you will build a mechanism that recommends movies based on def
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## Deploying Qdrant Hybrid Cloud on OVHcloud
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[Service Managed Kubernetes](https://www.ovhcloud.com/en-in/public-cloud/kubernetes/), powered by OVH Public Cloud Instances, a leading European cloud provider. With OVHcloud Load Balancers and disks built in. OVHcloud Managed Kubernetes provides high availability, compliance, and CNCF conformance, allowing you to focus on your containerized software layers with total reversibility.
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1. To start using managed Kubernetes on OVHcloud, follow the [platform-specific documentation](/documentation/hybrid-cloud/platform-deployment-options/#ovhcloud).
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2. Once your Kubernetes clusters are up, [you can begin deploying Qdrant Hybrid Cloud](/documentation/hybrid-cloud/).
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## Prerequisites
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Download and unzip the MovieLens dataset:
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