Reference: Medium post

BentoChain is a 🦜️🔗 LangChain deployment example using 🍱 BentoML inspired by langchain-gradio-template. This example demonstrates how to create a voice chatbot using the OpenAI API, Transformers speech models, Gradio, and BentoML. The chatbot takes input from a microphone, which is then converted into text using a speech recognition model.

The chatbot responds to the user's input with text, which can be played back to the user using a text-to-speech model.

🐳 Containerizes LangChain applications as standard OCI images.

🎱 Generates OpenAPI and gRPC endpoints automatically.

☁️ Deploys models as microservices running on the most optimal hardware and scaling independently.

Install Python dependencies.

poetry install
poetry shell

Create SSL certificate and key (this helps establish an HTTPS connexion that is needed to allow using the microphone on modern browers)

mkdir ssl
cd ssl
openssl req -x509 -newkey rsa:4096 -keyout key.pem -out cert.pem -sha256 -days 365 -nodes

Download and save speech recognition and text-to-speech models.

python train.py

Start the application locally.

bentoml serve service:svc --reload --ssl-certfile ssl/cert.pem --ssl-keyfile ssl/key.pem

Visit http://0.0.0.0:3000 for an OpenAPI Swagger page and http://0.0.0.0:3000/chatbot for a Gradio UI for the chatbot.

Build application into a distributable Bento artifact.

bentoml build

Containerize the application as an OCI image. This step requires Docker running.

bentoml containerize voicegpt:ahbt5xwxqsivkcvj

Run in Docker container.

docker run -it --rm -p 3333:3000 voicegpt:ahbt5xwxqsivkcvj serve --production

Push to yatai

bentoml push voicegpt:ahbt5xwxqsivkcvj