ASK MY CV: Creating a Powerful AI-Driven Telegram Bot to Answer CV Queries: A Comprehensive Guide Project Overview

Creating a Powerful AI-Driven Telegram Bot to Answer CV Queries: A Comprehensive Guide

Project Overview

This project involves creating a Telegram bot, deployed on AWS Lambda, that can process user queries related to a CV using advanced AI techniques. The bot, accessible at https://t.me/pirahansiahbot, references a pre-existing text file to provide accurate and detailed responses. The bot is enhanced through several key processes, including dataset collection, fine-tuning of models, and the implementation of advanced AI techniques.

Key Technologies and Processes

1. Dataset Collection and Preparation:
2. Model Optimization and Fine-Tuning:
3. AWS Lambda Integration:
4. Telegram Bot Development:

Steps:

• Created a custom dataset for fine-tuning the ChatGPT model based on the OpenAI chat completions guide.
• Uploaded the dataset to OpenAI's storage for model fine-tuning.
• Fine-tuned the model using the "gpt-4o-mini-2024-07-18" as the base.
• Developed an AWS Lambda function to facilitate communication between a Telegram bot and the fine-tuned ChatGPT model.
• Set up an API Gateway to enable communication between AWS Lambda, the Telegram bot, and ChatGPT.
• Created and activated a Telegram bot, using the setWebhook API to connect it with the AWS Lambda function.

Project Structure

• lambda_function.py: The core script that manages Telegram messages, processes the CV content, and generates AI-powered responses.
• Telegram Bot: The bot, available at https://t.me/pirahansiahbot, serves as the interface for users to interact and query the CV content.

Implementation Details

1. Dataset Creation and Fine-Tuning

• Dataset Collection: I compiled a comprehensive dataset that reflects my professional experience, skills, and achievements. This dataset was crucial for training the model to respond accurately to CV-related queries.
• Data Augmentation: Various data augmentation techniques were applied to ensure that the dataset was diverse and robust, enhancing the model's ability to generalize.
• Fine-Tuning GPT-4 Mini: The model was fine-tuned using gpt4mini-0-july2024, with careful optimization of hyperparameters to ensure the best performance. The fine-tuning process was iterative, involving multiple rounds of testing and adjustments.

2. AWS Lambda Setup and Custom Layers

• Package Layers: I created custom AWS Lambda layers to handle OpenAI API requests, Telegram bot interactions, and file system operations. These layers streamline the development process and ensure that the Lambda function can efficiently manage all necessary tasks.
• File Handling: The CV content is stored within the Lambda environment, and the content is loaded into memory at the start of each function execution for quick access during queries.

3. Telegram Bot Integration

• Message Handling: The bot uses the Telegram API to receive and respond to user messages. It processes both text queries and file uploads, responding based on the content stored in Lambda.
• AI-Driven Responses: The bot, available at https://t.me/pirahansiahbot, leverages the fine-tuned GPT-4 Mini model to generate responses that are contextually relevant and directly based on my CV. This makes the bot an effective tool for answering questions about my professional background.

4. Fine-Tuning and Optimization

• Hyperparameter Tuning: Extensive hyperparameter tuning was performed to optimize the model's performance. This involved adjusting learning rates, batch sizes, and other critical parameters to maximize the accuracy and relevance of the responses.
• Model Validation: The model was rigorously tested against a variety of queries to ensure that it could handle a wide range of questions related to my CV.

Conclusion

This project showcases the power of integrating AI with serverless computing to create a highly functional and responsive Telegram bot. By leveraging AWS Lambda, OpenAI's fine-tuned GPT-4 Mini model, and a well-structured dataset, I have developed a bot that can accurately answer any question related to my CV. The project, accessible at https://t.me/pirahansiahbot, demonstrates expertise in dataset preparation, model optimization, and serverless architecture, making it a valuable addition to any professional portfolio.

Hashtags:

#AIPoweredBot #TelegramBot #AWSLambda #OpenAI #Serverless #GPT4Mini #FineTuning #DataAugmentation #ModelOptimization #CVAssistant #ChatGPT