fix: deploy buttons images not appearing (#3092)

Added railway, render and GCP deploy images and link

docs/docs/Deployment/deployment-gcp.md

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 :::info
 
 This page may contain outdated information. It will be updated as soon as possible.
 
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 ## Deploy on Google Cloud Platform {#4ee01cda736c4f7396936409f23cdb52}
 
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 ### Run Langflow from a New Google Cloud Project {#ce729796d7404ccdb627bee47d6a4399}
 
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 This guide will help you set up a Langflow development VM in a Google Cloud Platform project using Google Cloud Shell.
 
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 When Cloud Shell opens, be sure to select Trust repo. Some gcloud commands might not run in an ephemeral Cloud Shell environment.
 
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 ### Standard VM {#245b47b450dd4159a5c56a5124bab84f}
 
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-[embed](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
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+[![GCP Deploy](https://camo.githubusercontent.com/c1a4a499c1d93d7038fd7af8c4f3fce222050f3bbdf4275dafbfde2491e4b8c4/68747470733a2f2f677374617469632e636f6d2f636c6f75647373682f696d616765732f6f70656e2d62746e2e737667)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
 
 This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
 
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 ## Spot/Preemptible Instance {#de9b8f7c71284cbb98e8137a3c44553d}
 
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 When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.
 
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 ## Pricing (approximate) {#2289f4ba9f544e6e9d4b915ef5aacd24}
 
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 > For a more accurate breakdown of costs, please use the GCP Pricing Calculator
 
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 | Component          | Regular Cost (Hourly) | Regular Cost (Monthly) | Spot/Preemptible Cost (Hourly) | Spot/Preemptible Cost (Monthly) | Notes                                                                      |
 | ------------------ | --------------------- | ---------------------- | ------------------------------ | ------------------------------- | -------------------------------------------------------------------------- |
 | 100 GB Disk        | -                     | $10/month              | -                              | $10/month                       | Disk cost remains the same for both regular and Spot/Preemptible VMs       |
 | VM (n1-standard-4) | $0.15/hr              | ~$108/month            | ~$0.04/hr                      | ~$29/month                      | The VM cost can be significantly reduced using a Spot/Preemptible instance |
 | **Total**          | **$0.15/hr**          | **~$118/month**        | **~$0.04/hr**                  | **~$39/month**                  | Total costs for running the VM and disk 24/7 for an entire month           |
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docs/docs/Deployment/deployment-railway.md

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 ## Deploy on Railway {#a9a1ce4d39e74cc29aef4d30c6172d10}
 
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 Railway is a cloud infrastructure platform that enables developers to deploy and manage applications effortlessly. It provides an intuitive interface, seamless integrations, and powerful features like auto-deploy from GitHub, managed databases, and automatic scaling.
 
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 Deploying Langflow to Railway involves a few simple steps:
 
 1. **Click the Button Below**: Start by clicking the deployment button provided below. This will redirect you to the Railway platform.
 
-	[https://railway.app/template/JMXEWp?referralCode=MnPSdg](https://railway.app/template/JMXEWp?referralCode=MnPSdg)
+   [![Deploy on Railway](./railway-deploy.svg)](https://railway.app/template/JMXEWp?referralCode=MnPSdg)
 
 2. **Deploy**: Proceed to deploy your Langflow instance. Click Deploy Now to deploy the instance. Railway will handle the rest, including setting up the infrastructure, deploying the Langflow instance, and starting the application.
 
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 By following these steps, your Langflow instance will be successfully deployed on Railway.
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docs/docs/Deployment/deployment-render.md

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 ## Deploy on Render {#20a959b7047e44e490cc129fd21895c0}
 
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 [Render.com](http://render.com/) is a unified cloud platform designed to make deploying web applications, APIs, and static sites easy. It provides a streamlined experience with powerful features like automatic SSL, managed databases, and auto-deploy from Git, making it a popular choice for developers looking to simplify their deployment workflows.
 
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 Deploying Langflow to Render is a straightforward process that can be completed in just a few steps:
 
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 1. **Click the Button Below**: Start by clicking the deployment button provided below. This will redirect you to the Render platform.
 
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-	[https://render.com/deploy?repo=https://github.com/langflow-ai/langflow/tree/dev](https://render.com/deploy?repo=https%3A%2F%2Fgithub.com%2Flangflow-ai%2Flangflow%2Ftree%2Fdev)
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+   [![Deploy to Render](./render-deploy.svg)](https://render.com/deploy?repo=https%3A%2F%2Fgithub.com%2Flangflow-ai%2Flangflow%2Ftree%2Fdev)
 
 2. **Select the Default Configuration**: Once on the Render platform, you will be prompted to provide a blueprint name and to select the default configuration for Langflow. This configuration includes all the necessary settings and resources to run Langflow efficiently. You can change the branch of the repo to “main” or “dev” based on your preference. Click “Create New Resources” to proceed.
 
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 3. **Deploy**: After selecting the configuration, proceed to deploy your Langflow instance. You can keep the default Starter instance, or change it to another instance based on your specific needs. Click Apply to deploy the instance. Render will handle the rest, including setting up the database, deploying the Langflow instance, and starting the application.
 
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 By following these steps, your Langflow instance will be successfully deployed on Render. Remember to review the pricing details on the Render platform to understand any costs involved.
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