Skip to content

dockersamples/genai-chatbot

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Video Analysis and Transcription ChatBot using Docker GenAI Stack

The application is a chatbot that can answer questions from a video. Additionally, it provides timestamps from the video that can help you to find the sources used to answer your question.

Getting Started

Clone the repository

git clone https://github.com/dockersamples/docker-genai.git

Specify your API keys

In the /docker-genai directory, create a text file called .env and specify your API keys inside. The following is the contents of the .env.example file that you can refer to as an example.

#-------------------------------------------------------------
# OpenAI
#-------------------------------------------------------------
OPENAI_TOKEN=your-api-key # Replace your-api-key with your personal API key

#-------------------------------------------------------------
# Pinecone
#--------------------------------------------------------------
PINECONE_TOKEN=your-api-key # Replace your-api-key with your personal API key

Build and Run the application

 docker compose up --build

Docker Compose builds and runs the application based on the services defined in the docker-compose.yaml file. When the application is running, you'll see the logs of 2 services in the terminal. In the logs, you'll see the services are exposed on ports 8503 and 8504. The two services are complementary to each other. The yt-whisper service is running on port 8503. This service feeds the Pinecone database with videos that you want to archive in your knowledge database. The following section explores this service.

Open a browser and access the yt-whisper service at http://localhost:8503 .

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 76.3%
  • Dockerfile 20.4%
  • Shell 3.3%