https://github.com/amjadraza/embedchain-streamlit-app
A Chat App built with embedchain and streamlit
https://github.com/amjadraza/embedchain-streamlit-app
deeplearning generativeai llms nlp-machine-learning python
Last synced: 4 months ago
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A Chat App built with embedchain and streamlit
- Host: GitHub
- URL: https://github.com/amjadraza/embedchain-streamlit-app
- Owner: amjadraza
- License: mit
- Created: 2023-06-27T09:05:55.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-02T19:01:20.000Z (over 1 year ago)
- Last Synced: 2024-08-13T07:07:57.035Z (8 months ago)
- Topics: deeplearning, generativeai, llms, nlp-machine-learning, python
- Language: Python
- Homepage: https://embedchain.streamlit.app/
- Size: 949 KB
- Stars: 41
- Watchers: 2
- Forks: 22
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - amjadraza/embedchain-streamlit-app - A Chat App built with embedchain and streamlit (Python)
README
📖 EmbedChain-Streamlit-Docker App Template
[](https://youtu.be/yJAWB13FhYQ)
[https://youtu.be/yJAWB13FhYQ](https://youtu.be/yJAWB13FhYQ)
## 🔧 Features
- Basic Skeleton App configured with `openai` API
- A ChatBot using embedchain and Streamlit
- Docker Support with Optimisation Cache etc
- Deployment on Streamlit Public Cloud
This repo contains an `main.py` file which has a template for a chatbot implementation.
## Example Input Data:
Select the number of Data Sources from slider and enter the details.
| Source | URL |
| -------- | ------- |
| youtube | https://www.youtube.com/watch?v=3qHkcs3kG44 |
| pdf_file |https://navalmanack.s3.amazonaws.com/Eric-Jorgenson_The-Almanack-of-Naval-Ravikant_Final.pdf |
| web | https://nav.al/feedback |
|qna_pair| "Who is Naval Ravikant?", "Naval Ravikant is an Indian-American entrepreneur and investor." |
**Question:** What unique capacity does Naval argue humans possess when it comes to understanding explanations or concepts?
## Adding your chain
To add your chain, you need to change the `load_chain` function in `main.py`.
Depending on the type of your chain, you may also need to change the inputs/outputs that occur later on.
## 💻 Running Locally
1. Clone the repository📂
```bash
git clone https://github.com/amjadraza/embedchain-streamlit-app.git
```
2. Install dependencies with [Poetry](https://python-poetry.org/) and activate virtual environment🔨
```bash
poetry install
poetry shell
```
3. Run the Streamlit server🚀
```bash
streamlit run demo_app/main.py
```
Run App using Docker
--------------------
This project includes `Dockerfile` to run the app in Docker container. In order to optimise the Docker Image
size and building time with cache techniques, I have follow tricks in below Article
https://medium.com/@albertazzir/blazing-fast-python-docker-builds-with-poetry-a78a66f5aed0
Build the docker container
``docker build . -t embedchain-streamlit-app:latest ``
To generate Image with `DOCKER_BUILDKIT`, follow below command
```DOCKER_BUILDKIT=1 docker build --target=runtime . -t embedchain-streamlit-app:latest```
1. Run the docker container directly
``docker run -d --name embedchain-streamlit-app -p 8080:8080 embedchain-streamlit-app:latest ``
2. Run the docker container using docker-compose (Recommended)
``docker-compose up``
Deploy App on Streamlit Public Cloud
------------------------------------
This app can be deployed on Streamlit Public Cloud using GitHub. Below is the Link to
Publicly deployed App
https://embedchain.streamlit.app/
## Report Feedbacks
As `embedchain-streamlit-app:latest` is a template project with minimal example. Report issues if you face any.
## DISCLAIMER
This is a template App, when using with openai_api key, you will be charged a nominal fee depending
on number of prompts etc.