ChatLocalAI
Enhanced
Direct integration with Langfuse tracing
LocalAI Setup
LocalAI is a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format.
To use ChatLocalAI within Flowise, follow the steps below:
-
git clone https://github.com/go-skynet/LocalAI -
cd LocalAI
3. ```bash
# copy your models to models/
cp your-model.bin models/For example:
Download one of the models from gpt4all.io
# Download gpt4all-j to models/
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-jIn the /models folder, you should be able to see the downloaded model in there:
 (1) (1).png)
Refer here for list of supported models.
-
docker compose up -d --pull always - Now API is accessible at localhost:8080
# Test API
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"ggml-gpt4all-j.bin","object":"model"}]}Flowise Setup
Drag and drop a new ChatLocalAI component to canvas:
.png)
Fill in the fields:
- Base Path: The base url from LocalAI such as http://localhost:8080/v1
- Model Name: The model you want to use. Note that it must be inside
/modelsfolder of LocalAI directory. For instance:ggml-gpt4all-j.bin
If you are running both Flowise and LocalAI on Docker, you might need to change the base path to http://host.docker.internal:8080/v1. For Linux based systems the default docker gateway should be used since host.docker.internal is not available: http://172.17.0.1:8080/v1
That’s it! For more information, refer to LocalAI docs.
Watch how you can use LocalAI on Flowise