README.md

metadata

title: Sales Email Generator
license: mit
sdk: gradio
emoji: 💻
colorFrom: blue
colorTo: gray
app_file: app.py

Smart Sales Email Generator

An AI-powered tool that generates contextual and professional follow-up emails based on previous customer interactions, using RAG, sentiment analysis and quality scoring.

AI Tools & Technologies

• RAG (Retrieval Augmented Generation) Implementation:
  • Vector Store: ChromaDB for email template storage
  • Embeddings: HuggingFace Sentence Transformers
  • Similarity Search for context retrieval
• LangChain for orchestrating the RAG pipeline
• Hugging Face Transformers for sentiment analysis
• DeepSeek model for email generation
• Gradio for the interactive web interface
• Transformers pipeline for NLP tasks

Key Features

• RAG-powered contextual email generation
• Retrieval of similar past interactions
• Automated sentiment analysis for tone detection
• Customizable urgency levels and situation types
• Real-time email quality scoring
• Multiple pre-built templates for common scenarios
• Context-aware response generation

Technical Skills Demonstrated

• RAG System Implementation
• Vector Database Management
• Embedding Generation
• Natural Language Processing (NLP)
• Large Language Model (LLM) integration
• Prompt engineering
• API integration (Hugging Face Hub)
• Web application development
• Machine Learning model deployment
• GPU acceleration support
• Error handling and input validation

Architecture

• RAG Components:
  • Vector Store for template storage
  • Embedding model for text vectorization
  • Similarity search for context retrieval
• Language Models:
  • DeepSeek for generation
  • BERT-based model for sentiment analysis
• Interface:
  • Gradio for web UI
  • Real-time processing

Use Cases

• Customer Service Follow-ups
• Complaint Resolution
• Service Issue Communication
• Payment Dispute Handling
• Product Query Responses
• General Business Communication

How to Use

1. Enter the previous customer interaction
2. Select the situation type from available options
3. Choose tone (optional - will be automatically detected)
4. Set urgency level (High/Medium/Low)
5. Submit to generate a professional follow-up email with quality score

Development Stack

• Python 3.x
• LangChain Framework
• ChromaDB
• HuggingFace Transformers
• Gradio UI Framework
• CUDA support for GPU acceleration

Future Enhancements

• Enhanced RAG capabilities
• Expanded template database
• Response time optimization
• Direct email system integration
• Analytics and tracking capabilities
• Enhanced scoring system

License

MIT License

Author

[Tobi Ajibola]