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Business Professionals: Individuals needing quick access to email communications for scheduling or information retrieval.
Project Managers: Those who require organized and timely responses regarding team communications.
Developers: Tech-savvy users interested in integrating Telegram with email querying capabilities.
Data Analysts: Users who need to analyze email data trends and insights efficiently.
General Users: Anyone looking for a convenient way to manage their email queries through a chatbot interface.

Accessing relevant email information can be time-consuming and cumbersome.
Users often struggle to retrieve specific email details related to upcoming events or tasks.
This workflow automates the process of querying emails, providing instant responses through a Telegram bot, thus saving time and increasing productivity.

Step 1: Triggered by Telegram - The workflow starts when a user sends a message to the Telegram bot.
Step 2: Session Management - A unique session ID is generated to track the conversation context.
Step 3: Message Processing - The workflow checks if the message is coming from Telegram and processes it accordingly.
Step 4: AI Processing - The user's query is sent to an AI agent, which determines whether to search through structured SQL or vectorized email data.
Step 5: Data Retrieval - The workflow queries either the Postgres database for structured data or the PGVector store for semantic searches based on the user's request.
Step 6: Response Formatting - The retrieved information is formatted for clarity and conciseness before sending it back to the user.
Step 7: Batch Responses - If there are multiple responses, they are split into manageable chunks and sent to the user in batches to ensure readability.

e-mail Chatbot with both semantic and structured RAG, using Telegram and Pgvector