Inference Logoinference.sh

Content Pipeline

Build a flow that creates social media content from a prompt.


What We're Building

A flow that:

  1. Generates an image from a description
  2. Creates a caption
  3. Resizes for different platforms
code
1Prompt  Generate Image  Write Caption  Resize  Output

Step 1: Create the Flow

  1. Go to Flows
  2. Click New Flow
  3. Name it content-pipeline

Step 2: Add Input Node

Define what the flow accepts:

yaml
1inputs:2  - name: description3    type: string4    description: "What kind of content to create"5  - name: platform6    type: string7    default: "instagram"8    description: "Target platform"

Step 3: Add Image Generation

Add a stable-diffusion node:

yaml
1node: generate_image2app: infsh/stable-diffusion3inputs:4  prompt: "{{input.description}}, professional social media content, high quality"5  size: "1024x1024"

Step 4: Add Caption Writer

Add a text generation node:

yaml
1node: write_caption2app: infsh/gpt-43inputs:4  prompt: |5    Write an engaging social media caption for: {{input.description}}6    7    Platform: {{input.platform}}8    9    Include relevant hashtags. Keep it concise and engaging.

Step 5: Add Resizer

Add an image resize node:

yaml
1node: resize2app: infsh/image-resize3inputs:4  image: "{{generate_image.output.images[0]}}"5  presets:6    - name: instagram_square7      size: 1080x10808    - name: instagram_story9      size: 1080x192010    - name: twitter11      size: 1200x675

Step 6: Define Output

yaml
1output:2  image: "{{resize.output.images.instagram_square}}"3  story: "{{resize.output.images.instagram_story}}"4  twitter: "{{resize.output.images.twitter}}"5  caption: "{{write_caption.output.text}}"

Running the Flow

python
1from inferencesh import inference2 3client = inference(api_key="inf_your_key")4 5result = client.run({6    "app": "myname/content-pipeline",  # After deploying7    "input": {8        "description": "A cozy coffee shop morning",9        "platform": "instagram"10    }11})12 13print("Caption:", result["output"]["caption"])14print("Images:", result["output"]["image"])

Using with an Agent

Add the flow as a tool to an agent:

code
1You: Create Instagram content for a coffee shop2 3Agent: I'll use the content pipeline.4       [Running content-pipeline flow...]5       6       Here's your content:7       8        Image: A warm, cozy coffee shop interior with 9          morning light streaming through windows10       11        Caption: "Start your morning the right way  12          There's nothing quite like the aroma of fresh 13          coffee and the quiet of early hours.14          #CoffeeLovers #MorningVibes #CafeLife"15       16       I've also generated versions for Stories and Twitter.17       Want me to create more variations?

Variations

Extend this flow for different use cases:

  • Product photos: Add background removal + studio lighting
  • Blog headers: Add text overlay + branding
  • Thumbnails: Add YouTube-style text + face detection

Next

Data Processing

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