mirror of
https://github.com/nomic-ai/gpt4all
synced 2024-11-02 09:40:42 +00:00
390994ea5e
Signed-off-by: Andriy Mulyar <andriy.mulyar@gmail.com>
72 lines
1.7 KiB
Markdown
72 lines
1.7 KiB
Markdown
# GPT4All REST API
|
|
This directory contains the source code to run and build docker images that run a FastAPI app
|
|
for serving inference from GPT4All models. The API matches the OpenAI API spec.
|
|
|
|
## Tutorial
|
|
|
|
### Starting the app
|
|
|
|
First build the FastAPI docker image. You only have to do this on initial build or when you add new dependencies to the requirements.txt file:
|
|
```bash
|
|
DOCKER_BUILDKIT=1 docker build -t gpt4all_api --progress plain -f gpt4all_api/Dockerfile.buildkit .
|
|
```
|
|
|
|
Then, start the backend with:
|
|
|
|
```bash
|
|
docker compose up --build
|
|
```
|
|
|
|
#### Spinning up your app
|
|
Run `docker compose up` to spin up the backend. Monitor the logs for errors in-case you forgot to set an environment variable above.
|
|
|
|
|
|
#### Development
|
|
Run
|
|
|
|
```bash
|
|
docker compose up --build
|
|
```
|
|
and edit files in the `api` directory. The api will hot-reload on changes.
|
|
|
|
You can run the unit tests with
|
|
|
|
```bash
|
|
make test
|
|
```
|
|
|
|
#### Viewing API documentation
|
|
|
|
Once the FastAPI ap is started you can access its documentation and test the search endpoint by going to:
|
|
```
|
|
localhost:80/docs
|
|
```
|
|
|
|
This documentation should match the OpenAI OpenAPI spec located at https://github.com/openai/openai-openapi/blob/master/openapi.yaml
|
|
|
|
|
|
#### Running inference
|
|
```python
|
|
import openai
|
|
openai.api_base = "http://localhost:4891/v1"
|
|
|
|
openai.api_key = "not needed for a local LLM"
|
|
|
|
|
|
def test_completion():
|
|
model = "gpt4all-j-v1.3-groovy"
|
|
prompt = "Who is Michael Jordan?"
|
|
response = openai.Completion.create(
|
|
model=model,
|
|
prompt=prompt,
|
|
max_tokens=50,
|
|
temperature=0.28,
|
|
top_p=0.95,
|
|
n=1,
|
|
echo=True,
|
|
stream=False
|
|
)
|
|
assert len(response['choices'][0]['text']) > len(prompt)
|
|
print(response)
|
|
```
|