aws-wechat-article-writing

To generate a WeChat article draft, provide a topic or outline file. The AI merges constraints from config.yaml and article.yaml, reads product references, and outputs a complete draft using the configured model.

Yes, you can use DeepSeek, OpenAI, Claude, Qwen, or Gemini models for WeChat article writing. You must configure the backend by setting the base_url, model, and provider credentials.

The best way to rewrite and polish WeChat article content is using an AI workflow that applies style constraints from config.yaml and integrates business references to refine the text.

Yes, you need YAML configuration files. The workflow requires a configured writing model and merges constraints from .aws-article/config.yaml and article.yaml to govern the drafting process.

To continue writing from an existing draft, the AI reads your current content and utilizes the configured LLM backend to generate subsequent text while adhering to merged YAML constraints and product references.

To include business references when generating WeChat article drafts, place materials in the .aws-article/products directory. The AI reads these references to enrich and inform the generated content.