LLM Lab

This project is an advanced laboratory environment that showcases various Artificial Intelligence (AI) and Natural Language Processing (NLP) applications. Comprising multiple submodules, the project is designed to demonstrate the capabilities and methods of AI. These submodules perform a variety of tasks, including text-based querying, image generation using generative models, embedding-based similarity calculation, interaction with external functions or APIs, and fine-tuning pre-trained models. Each submodule utilizes the latest AI technologies to explore and showcase the practical applications of modern NLP and AI techniques, providing a powerful environment for experimentation and development.

Subprojects

1. Image Generation with AI API

• Description: Generates images based on text descriptions provided by the user.
• Technologies: Hugging Face API, Stable Diffusion model.
• More Information: create_image_with_ai/readme.md

2. Embedding-Based Query with RAG

• Description: Compares user queries with texts in a database and generates the most appropriate response using the RAG (Retrieval-Augmented Generation) method.
• Technologies: Sentence Transformers, Groq API.
• More Information: embedding-based_query_with_RAG/readme.md

3. Embedding-Based Text Similarity Search and Visualization

• Description: Compares user queries with texts, calculates similarity scores, and visualizes the results.
• Technologies: Sentence Transformers, Matplotlib, Seaborn.
• More Information: embedding_base_search/readme.md

4. Function Calling with Groq

• Description: Demonstrates how to use the "function calling" feature of the Groq library to dynamically handle function calls from the model in a Python application.
• Technologies: Groq library, Python
• More Information: function_calling_with_groq/readme.md

5. Fine-Tuning with Groq

• Description: Demonstrates how to fine-tune models using the Groq library for specific tasks.
• Technologies: Groq library, Python
• More Information: fine_tunning_with_groq/readme.md

6. Job Search Demo

• Description: A job search application that allows users to search for job titles using a query. It combines a FastAPI backend and a React frontend.
• Technologies: FastAPI, React, FAISS, Sentence Transformers.
• More Information: job_search_demo/readme.md

7. Multi-Agent System

• Description: Automates the process of creating blog posts using multiple AI agents for planning, researching, writing, and reviewing.
• Technologies: Python, Groq API, httpx.
• More Information: multi_agent_system/readme.md