Ask Chatbot

Streamlit web app providing a Large Language Model (LLM) chatbot with a custom knowledge base

Live Demo

Deployed to Streamlit Community Cloud ☁️
Conversation LLM chatbot chain only
For simplicity and privacy, the semantic search of personal or organizational documents to create a custom knowledge base for the LLM is available only as a local deployment feature
URL: https://ask-chatbot.streamlit.app

Extend the LLM chatbot with a custom knowledge base
Include the data you wish to upload to extend the LLM chatbot in the 'data' directory
Anticipates to load any .txt, .pdf, .csv, .docx, or .xlsx files found in the directory
Web scraping, see code for details
Data is persisted within a local ChromaDB vector store

Create a .streamlit folder in the 'src' directory and include the contents of the .streamlit.example
To initialize a virtual enviroment, navigate to the 'src' directory in the terminal and execute
```
$ python -m venv venv
```
Activate the virtual environment, on MacOS or Linux with
```
$ source venv/bin/activate
```
Install dependencies
```
$ pip install -r requirements.txt
```
Some LangChain packages may have hidden dependencies that require pip installation
Run the app
```
$ streamlit run app.py
```
Open your browser at http://localhost:8501
To deactivate the virtual environment
```
$ deactivate
```

LLM Conversation

Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
.streamlit.example		.streamlit.example
data		data
helpers		helpers
public		public
static		static
.gitignore		.gitignore
README.md		README.md
app.py		app.py
requirements.txt		requirements.txt