Update 12 - OpenAI API.md

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## OpenAI compatible API
This project includes an API compatible with multiple OpenAI endpoints, including Chat and Completions.
The main API for this project is meant to be a drop-in replacement to the OpenAI API, including Chat and Completions endpoints.
If you did not use the one-click installers, you may need to install the requirements first:
@ -12,8 +12,8 @@ pip install -r extensions/openai/requirements.txt
Add `--extensions openai` to your command-line flags.
* To create a public Cloudflare URL, add the `--public-api` flag.
* To listen on your local network, add the `--listen` flag.
* To create a public Cloudflare URL, also add the `--public-api` flag.
* To listen on your local network, also add the `--listen` flag.
* To change the port, which is 5000 by default, use `--port 1234` (change 1234 to your desired port number).
* To use SSL, add `--ssl-keyfile key.pem --ssl-certfile cert.pem`. Note that it doesn't work with `--public-api`.
@ -33,7 +33,7 @@ The following environment variables can be used (they take precendence over ever
#### Persistent settings with `settings.yaml`
You can also set default values by adding these lines to your `settings.yaml` file:
You can also set the following variables in your `settings.yaml` file:
```
openai-embedding_device: cuda
@ -44,6 +44,106 @@ openai-debug: 1
### Examples
For the documentation with all the parameters, consult `http://127.0.0.1:5000/docs` or the [typing.py](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/openai/typing.py) file.
The official examples in the [OpenAI documentation](https://platform.openai.com/docs/api-reference) should also work, and the same parameters apply (although the API here has more optional parameters).
#### Completions
```shell
curl http://127.0.0.1:5000/v1/completions \
-H "Content-Type: application/json" \
-d '{
"prompt": "This is a cake recipe:\n\n1.",
"max_tokens": 200,
"temperature": 1,
"top_p": 0.9,
"seed": 10
}'
```
#### Chat completions
Works best with instruction-following models. If the "instruction_template" variable is not provided, it will be guessed automatically based on the model name using the regex patterns in `models/config.yaml`.
```shell
curl http://127.0.0.1:5000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"messages": [
{
"role": "user",
"content": "Hello!"
}
],
"mode": "instruct",
"instruction_template": "Alpaca"
}'
```
#### Chat completions with characters
```shell
curl http://127.0.0.1:5000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"messages": [
{
"role": "user",
"content": "Hello! Who are you?"
}
],
"mode": "chat",
"character": "Example"
}'
```
#### SSE streaming
```shell
curl http://127.0.0.1:5000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"messages": [
{
"role": "user",
"content": "Hello!"
}
],
"mode": "instruct",
"instruction_template": "Alpaca",
"stream": true
}'
```
#### Python chat example
```python
import requests
url = "http://127.0.0.1:5000/v1/chat/completions"
headers = {
"Content-Type": "application/json"
}
history = []
while True:
user_message = input("> ")
history.append({"role": "user", "content": user_message})
data = {
"mode": "chat",
"character": "Example",
"messages": history
}
response = requests.post(url, headers=headers, json=data, verify=False)
assistant_message = response.json()['choices'][0]['message']['content']
history.append({"role": "assistant", "content": assistant_message})
print(assistant_message)
```
### Client Application Setup