This sample demonstrates a sequential multi-agent pipeline for generating marketing copy from a product description.
The workflow showcases:
- Sequential Agent Pipeline: Three agents work in sequence, each building on the previous output
- Role-Based Agents: Each agent has a distinct responsibility
- Content Transformation: Raw product info transforms into polished marketing copy
Product Description
|
v
AnalystAgent --> Key features, audience, USPs
|
v
WriterAgent --> Draft marketing copy
|
v
EditorAgent --> Polished final copy
|
v
Final Output
| Agent | Role |
|---|---|
| AnalystAgent | Identifies key features, target audience, and unique selling points |
| WriterAgent | Creates compelling marketing copy (~150 words) |
| EditorAgent | Polishes grammar, clarity, tone, and formatting |
# Run the demonstration with mock responses
python main.pyAn eco-friendly stainless steel water bottle that keeps drinks cold for 24 hours.
For production use, configure these agents in Azure AI Foundry:
Instructions: You are a marketing analyst. Given a product description, identify:
- Key features
- Target audience
- Unique selling points
Instructions: You are a marketing copywriter. Given a block of text describing
features, audience, and USPs, compose a compelling marketing copy (like a
newsletter section) that highlights these points. Output should be short
(around 150 words), output just the copy as a single text block.
Instructions: You are an editor. Given the draft copy, correct grammar,
improve clarity, ensure consistent tone, give format and make it polished.
Output the final improved copy as a single text block.