This summary of the video was created by an AI. It might contain some inaccuracies.
00:00:00 – 00:13:45
Billy from Generative Labs provides an extensive tutorial on building and deploying a stable diffusion API using Runpod serverless infrastructure. Key steps include setting up a Runpod account, Docker, Git, Postman, and downloading models. Viewers are guided through cloning a serverless worker template from GitHub, moving models to the correct directories, modifying the Docker file for model naming, and configuring the Handler file to support various API functionalities like text-to-image and image-to-image. The tutorial also covers the creation and deployment of a Docker image, setting up a serverless endpoint, adjusting container disk size, and obtaining an API key. Api key setup in Postman is explained, including asynchronous and synchronous job handling. A deep dive on using the "get models" API and specifying model checkpoints demonstrates generating and visualizing images. The tutorial concludes with a small prompt modification and getting stable diffusion options. Viewers are encouraged to engage with the video by liking, subscribing, and commenting.
00:00:00
In this part of the video, Billy from Generative Labs provides a detailed tutorial on creating a stable diffusion API using Runpod serverless. Key actions include setting up prerequisites such as a Runpod account, Docker, Git, Postman, and downloading custom models. Billy guides viewers through cloning a serverless worker template from GitHub, moving custom models into the correct directories, and modifying the Docker file for model naming. The Handler file is discussed, showing modifications made to support multiple stable diffusion APIs, including text to image and image to image functionalities.
00:03:00
In this part of the video, the speaker explains how to build and deploy a Docker image. First, they describe using the `docker build` and `tag` commands to create the image and then using the `docker push` command to upload it to Docker Hub. Next, they guide creating a serverless endpoint using Run Pod by creating a template that references the Docker image and adjusting the container disk size for large models. The speaker then details how to create a new endpoint, specify worker parameters, and note the endpoint ID for future use with Postman. Finally, they mention the necessity of obtaining an API key.
00:06:00
In this segment of the video, viewers are guided on how to set up and use API keys in Postman. After creating and securely storing an API key, an imported Postman configuration file simplifies the process. The configuration includes four types of requests: running jobs asynchronously, running async jobs with a webhook, running synchronous jobs, and checking the status of a running job. The video focuses on setting up a job to run asynchronously using the Stable Diffusion API. Viewers are instructed on how to invoke an API, retrieve and use a job ID to check the status, and visualize the resulting image within Postman. The segment concludes by comparing async requests with synchronous ones, noting that sync requests wait for completion before returning a response.
00:09:00
In this segment of the video, the presenter demonstrates changing the API name to “get models” and mentions that the response payload has two models available, “model safe tensor” and “model 2 safe tensor.” They show copying the full string of “model 2 safe tensor” and pasting it as the value for the “SD model checkpoint” key in the request body. After issuing the request again, a photo-realistic image of a girl at the beach is displayed, verifying the specified model was used by checking the “St model hash” key in the response payload. The presenter then explains copying the Base 64 encoded image to make an image-to-image request, highlighting the addition of a new key named “init images,” which takes an array of Base 64 encoded strings.
00:12:00
In this part of the video, the presenter makes a small modification to the prompt by changing the hair color and demonstrates how to get a list of the current stable diffusion options by altering the API name to ‘get options’. The tutorial concludes with a call to action for viewers to like the video, subscribe to the channel for more tutorials, and leave comments with questions or suggestions for future content.