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Michael Ikehi 6fd7213076 feat: Initial implementation of Marketing Assistant AI for Adriana James
- Set up FastAPI backend with modular structure:

  - main.py for API routing

  - copywriter.py for AI-powered content generation using Cohere

  - embeddings.py for generating and reranking content embeddings

  - vector_store.py for FAISS-based similarity search

  - brand_style.py for managing brand tone, taboo words, and preferred terms

  - config.py for managing environment and application settings

- Configured RESTful API endpoints: /generate-copy, /brand-style, /training-data, /improve-content, /analyze-content

- Created frontend with vanilla HTML, CSS, and JS (index.html, styles.css, app.js)

- Integrated brand style management for tone, voice, taboo words, and terminology

- Implemented vector search for referencing similar historical content

- Enabled training data input to improve future AI output

- Added environment variable support for API keys and model configs

- Structured data storage with local JSON and DB files

- Added developer documentation, API reference, and project setup instructions

This commit provides the foundation for a full-stack, AI-driven content creation platform that ensures brand consistency, speeds up marketing workflows, and supports iterative improvement over time.
2025-04-17 08:50:12 +01:00

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fastapi
uvicorn
pydantic
python-dotenv
httpx
faiss-cpu
numpy==1.26.2
pandas
cohere
python-multipart
SQLAlchemy
databases
aiosqlite
loguru
tenacity