feat: image-input, renamed "prompt" to "workflow", added "REFRESH_WOR…

…KER" (#14) * feat: renamed "prompt" to "workflow" BREAKING, added the input param "images" to upload images into Comfy * docs: how to activate the virtual env * feat: added "REFRESH_WORKER", improved "upload_images" * docs: added "API specification", update "config" * feat: pin runpod to 1.3.6
blib-la · Dec 2, 2023 · 5f5e390 · 5f5e390
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diff --git a/README.md b/README.md
@@ -15,6 +15,10 @@
 - [Config](#config)
   * [Upload image to AWS S3](#upload-image-to-aws-s3)
 - [Use the Docker image on RunPod](#use-the-docker-image-on-runpod)
+- [API specification](#api-specification)
+  * [JSON Payload Structure](#json-payload-structure)
+  * [Fields](#fields)
+    + ["input.images" details](#inputimages-details)
 - [Interact with your RunPod API](#interact-with-your-runpod-api)
   * [Health status](#health-status)
   * [Generate an image](#generate-an-image)
@@ -24,7 +28,6 @@
 - [Local testing](#local-testing)
   * [Setup](#setup)
     + [Setup for Windows](#setup-for-windows)
-  * [Activate virtual env](#activate-virtual-env)
   * [Test: handler](#test-handler)
   * [Test: docker image](#test-docker-image)
 - [Automatically deploy to Docker hub with Github Actions](#automatically-deploy-to-docker-hub-with-github-actions)
@@ -43,6 +46,7 @@
 ## Features
 
 - Run any [ComfyUI](https://github.com/comfyanonymous/ComfyUI) workflow to generate an image
+- Provide input images as base64-encoded string
 - Generated image is either:
   - Returned as base64-encoded string (default)
   - Uploaded to AWS S3 ([if AWS S3 is configured](#upload-image-to-aws-s3))
@@ -57,6 +61,10 @@
 
 ## Config
 
+| Environment Variable | Description                                                                  | Default |
+| -------------------- | ---------------------------------------------------------------------------- | ------- |
+| `REFRESH_WORKER`     | When you want stop the worker after each finished job to have a clean state. | `false` |
+
 ### Upload image to AWS S3
 
 This is only needed if you want to upload the generated picture to AWS S3. If you don't configure this, your image will be exported as base64-encoded string.
@@ -97,6 +105,44 @@ This is only needed if you want to upload the generated picture to AWS S3. If yo
 - Click `deploy`
 - Your endpoint will be created, you can click on it to see the dashboard
 
+## API specification
+
+The following is the required structure and format for requests made to the API. 
+
+### JSON Payload Structure
+
+```json
+{
+  "input": {
+    "workflow": {},
+    "images": [
+      {
+        "name": "example_image_name.png",
+        "image": "base64_encoded_string"
+      }
+    ]
+  }
+}
+```
+
+### Fields
+
+| Field Path       | Type   | Required | Description                                       |
+| ---------------- | ------ | -------- | ------------------------------------------------- |
+| `input`          | Object | Yes      | The top-level object containing the request data. |
+| `input.workflow` | Object | Yes      | Contains the ComfyUI workflow configuration.      |
+| `input.images`   | Array  | No       | An array of images.                               |
+
+
+#### "input.images" details
+
+| Field Name | Type   | Required | Description                                                                              |
+| ---------- | ------ | -------- | ---------------------------------------------------------------------------------------- |
+| `name`     | String | No       | The name of the image. Please use the same name in your workflow to reference the image. |
+| `image`    | String | No       | A base64 encoded string of the image.                                                    |
+
+
+
 ## Interact with your RunPod API
 
 - In the [User Settings](https://www.runpod.io/console/serverless/user/settings) click on `API Keys` and then on the `API Key` button
@@ -105,6 +151,8 @@ This is only needed if you want to upload the generated picture to AWS S3. If yo
   - Replace `<api_key>` with your key
   - Replace `<endpoint_id>` with the ID of the endpoint, you find that when you click on your endpoint, it's part of the URLs shown at the bottom of the first box
 
+
+
 ### Health status
 
 ```bash
@@ -113,16 +161,16 @@ curl -H "Authorization: Bearer <api_key>" https://api.runpod.ai/v2/<endpoint_id>
 
 ### Generate an image
 
-You can ether create a new job async by using /run or a sync by using runsync. The example here is using a sync job and waits until the response is delivered.
+You can either create a new job async by using `/run` or a sync by using runsync. The example here is using a sync job and waits until the response is delivered.
 
-The API expects a JSON in this form, where `prompt` is the [workflow from ComfyUI, exported as JSON](#how-to-get-the-workflow-from-comfyui):
+The API expects a JSON in this form, where `workflow` is the [workflow from ComfyUI, exported as JSON](#how-to-get-the-workflow-from-comfyui):
 
 ```json
 {
   "input": {
-    "prompt": {
+    "workflow": {
       // ComfyUI workflow
-    }
+    },
   }
 }
 ```
@@ -132,7 +180,7 @@ Please also take a look at the [test_input.json](./test_input.json) to see how t
 #### Example request with cURL
 
 ```bash
-curl -X POST -H "Authorization: Bearer <api_key>" -H "Content-Type: application/json" -d '{"input":{"prompt":{"3":{"inputs":{"seed":1337,"steps":20,"cfg":8,"sampler_name":"euler","scheduler":"normal","denoise":1,"model":["4",0],"positive":["6",0],"negative":["7",0],"latent_image":["5",0]},"class_type":"KSampler"},"4":{"inputs":{"ckpt_name":"sd_xl_base_1.0.safetensors"},"class_type":"CheckpointLoaderSimple"},"5":{"inputs":{"width":512,"height":512,"batch_size":1},"class_type":"EmptyLatentImage"},"6":{"inputs":{"text":"beautiful scenery nature glass bottle landscape, , purple galaxy bottle,","clip":["4",1]},"class_type":"CLIPTextEncode"},"7":{"inputs":{"text":"text, watermark","clip":["4",1]},"class_type":"CLIPTextEncode"},"8":{"inputs":{"samples":["3",0],"vae":["4",2]},"class_type":"VAEDecode"},"9":{"inputs":{"filename_prefix":"ComfyUI","images":["8",0]},"class_type":"SaveImage"}}}}' https://api.runpod.ai/v2/<endpoint_id>/runsync
+curl -X POST -H "Authorization: Bearer <api_key>" -H "Content-Type: application/json" -d '{"input":{"workflow":{"3":{"inputs":{"seed":1337,"steps":20,"cfg":8,"sampler_name":"euler","scheduler":"normal","denoise":1,"model":["4",0],"positive":["6",0],"negative":["7",0],"latent_image":["5",0]},"class_type":"KSampler"},"4":{"inputs":{"ckpt_name":"sd_xl_base_1.0.safetensors"},"class_type":"CheckpointLoaderSimple"},"5":{"inputs":{"width":512,"height":512,"batch_size":1},"class_type":"EmptyLatentImage"},"6":{"inputs":{"text":"beautiful scenery nature glass bottle landscape, , purple galaxy bottle,","clip":["4",1]},"class_type":"CLIPTextEncode"},"7":{"inputs":{"text":"text, watermark","clip":["4",1]},"class_type":"CLIPTextEncode"},"8":{"inputs":{"samples":["3",0],"vae":["4",2]},"class_type":"VAEDecode"},"9":{"inputs":{"filename_prefix":"ComfyUI","images":["8",0]},"class_type":"SaveImage"}}}}' https://api.runpod.ai/v2/<endpoint_id>/runsync
 
 # Response with AWS S3 bucket configuration
 # {"delayTime":2188,"executionTime":2297,"id":"sync-c0cd1eb2-068f-4ecf-a99a-55770fc77391-e1","output":{"message":"https://bucket.s3.region.amazonaws.com/10-23/sync-c0cd1eb2-068f-4ecf-a99a-55770fc77391-e1/c67ad621.png","status":"success"},"status":"COMPLETED"}
@@ -150,7 +198,7 @@ curl -X POST -H "Authorization: Bearer <api_key>" -H "Content-Type: application/
   - Close the `Settings`
 - In the menu, click on the `Save (API Format)` button, which will download a file named `workflow_api.json`
 
-You can now take the content of this file and put it into your `prompt` when interacting with the API.
+You can now take the content of this file and put it into your `workflow` when interacting with the API.
 
 ## Build the image
 
@@ -166,6 +214,7 @@ Both tests will use the data from [test_input.json](./test_input.json), so make
 
 - Make sure you have Python >= 3.10
 - Create a virtual environment: `python -m venv venv`
+- Activate the virtual environment: `.\venv\Scripts\activate` (Windows) or `source ./venv/bin/activate` (Mac / Linux)
 - Install the dependencies: `pip install -r requirements.txt`
 
 #### Setup for Windows
@@ -188,10 +237,6 @@ To run the Docker image on Windows, we need to have WSL2 and a Linux distro (lik
 
 - Add your user to the `docker` group, so that you can use Docker without `sudo`: `sudo usermod -aG docker $USER`
 
-### Activate virtual env
-
-`.\venv\Scripts\activate`
-
 ### Test: handler
 
 - Run all tests: `python -m unittest discover`

diff --git a/requirements.txt b/requirements.txt
@@ -1 +1 @@
-runpod
+runpod==1.3.6