AI Tutor Project Setup and Use

This project sets up a AI tutor using ChromaDB for vector storage and Large Language Model for processing responses.

Prerequisites

First, make sure Ollama is running in the background with Mistral model installed on your system

Install Required dependencies
Run following command,
```
pip3 install -r requirements.txt
```
If you get errors regarding modules not found while running the application install them with pip3 install MODULE_NAME.
Add Hugging Face Token
Create a .env file in the root directory and include your Hugging Face API key:
```
HF_API_KEY = "your_huggingface_api_key"
```
Populate Database
Run the following script to create a ChromaDB instance using Resource Version 3.xlsx:
```
python3 populate_database.py
```
Run the Application
Start the Flask server by executing:
```
python3 app.py
```
Access the Chatbot
Open your browser and go to:
```
http://127.0.0.1:5000
```
The chatbot should be up and running.

Happy AI Learning :)

Name		Name	Last commit message	Last commit date
Latest commit History 47 Commits
__pycache__		__pycache__
auth		auth
controllers		controllers
data		data
static		static
templates		templates
.DS_Store		.DS_Store
.gitignore		.gitignore
README.md		README.md
agentA_test_script.py		agentA_test_script.py
agentB_test_script.py		agentB_test_script.py
app.py		app.py
app_gemini.py		app_gemini.py
app_test.py		app_test.py
check_chromeDb.py		check_chromeDb.py
clear_redis_sessions.py		clear_redis_sessions.py
config.py		config.py
final_fast.mov		final_fast.mov
get_embedding_function.py		get_embedding_function.py
master_agent_test_script.py		master_agent_test_script.py
populate_database.py		populate_database.py
query_data.py		query_data.py
redis_test.py		redis_test.py
requirements.txt		requirements.txt
user cred.txt		user cred.txt
view_redis_sessions.py		view_redis_sessions.py