Files
pipecat/examples/simple-chatbot
Aleix Conchillo Flaqué 7e39d9ad3d introduce input/output audio and image frames
We now distinguish between input and output audio and image frames. We introduce
`InputAudioRawFrame`, `OutputAudioRawFrame`, `InputImageRawFrame` and
`OutputImageRawFrame` (and other subclasses of those). The input frames usually
come from an input transport and are meant to be processed inside the pipeline
to generate new frames. However, the input frames will not be sent through an
output transport. The output frames can also be processed by any frame processor
in the pipeline and they are allowed to be sent by the output transport.
2024-09-19 23:11:03 -07:00
..
2024-05-13 17:09:46 +01:00
2024-05-13 17:09:46 +01:00
2024-05-13 17:09:46 +01:00
2024-05-13 17:09:46 +01:00
2024-05-13 17:09:46 +01:00

Simple Chatbot

This app connects you to a chatbot powered by GPT-4, complete with animations generated by Stable Video Diffusion.

See a video of it in action: https://x.com/kwindla/status/1778628911817183509

And a quick video walkthrough of the code: https://www.loom.com/share/13df1967161f4d24ade054e7f8753416

The first time, things might take extra time to get started since VAD (Voice Activity Detection) model needs to be downloaded.

Get started

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

cp env.example .env # and add your credentials

Run the server

python server.py

Then, visit http://localhost:7860/start in your browser to start a chatbot session.

Build and test the Docker image

docker build -t chatbot .
docker run --env-file .env -p 7860:7860 chatbot