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https://github.com/rexsimiloluwah/streamlit-llm-apps

LLM Applications built using Streamlit, LangChain, and OpenAI API
https://github.com/rexsimiloluwah/streamlit-llm-apps

langchain llm openai streamlit

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LLM Applications built using Streamlit, LangChain, and OpenAI API

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README

        

# LLM Apps using Streamlit and LangChain

## Introduction

This repository showcases a suite of experimental LLM applications built using Streamlit.

## Uses

- Streamlit (UI)
- LangChain
- OpenAI API (`gpt-3.5-turbo`)

## Run the App

### Clone the Repository

```bash
$ git clone github.com/rexsimiloluwah/streamlit-llm-apps
$ cd streamlit-llm-apps
```

### Install the dependencies

You can advisably create a virtual environment

```bash
$ pip install -r requirements.txt
```

## Run the app

```bash
$ streamlit run src/main.py

# Using make
$ make run-app
```

## Example Applications

### 1. Simple Document QA App

This application enables you to perform question-answering over your PDF document. It uses the `RetrievalQA` chain and the in-memory `DocArray` vector store provided by LangChain.

Simple Document QA App Screenshot
Simple Document QA App Example Screenshot

### 2. Web Page QA App

This application enables you to perform question-answering over content loaded from a web page. It similarly uses the `RetrievalQA` chain and the in-memory `DocArray` vector store provided by LangChain.

Web Page QA App Screenshot
Web Page QA App Example Screenshot

### 3. Document Chat App

This application enables you to chat over your PDF document. It uses the `ConversationalRetrievalChain` chain and the in-memory `DocArray` vector store provided by LangChain. The memory is managed externally.

Document Chat App Screenshot
Document Chat App Example Screenshot