LLM Agent Gmail Parser Better RAG 📧🤖

Problem Addressed

Indexing emails to use with RAG applications or to extract relevant knowledge has its challenges, such as:

• A lot of noise and garbage in the text
• Dealing with email threads

Solution

In this project, I experimented with various prompt techniques to extract the most important information from emails while addressing the problems stated above. I found that a report-style summary works better than just asking for a summary, as the latter tends to lose a lot of important information.

Key Points 🌟

• Noise Reduction: Implemented techniques to filter out irrelevant information and focus on key content.
• Thread Handling: Developed methods to accurately parse and summarize email threads.
• Report-Style Summaries: Discovered that report-style summaries retain more essential information compared to generic summaries.
• Prompt Engineering: Experimented with different prompt structures to enhance the extraction of valuable insights.