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@ -234,19 +234,35 @@ node index.js
- **GET** `/props`: Return the required assistant name and anti-prompt to generate the prompt in case you have specified a system prompt for all slots.
- **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only ChatML-tuned models, such as Dolphin, OpenOrca, OpenHermes, OpenChat-3.5, etc can be used with this endpoint. Compared to `api_like_OAI.py` this API implementation does not require a wrapper to be served.
- **POST** `/v1/chat/completions`: OpenAI-compatible Chat Completions API. Given a ChatML-formatted json description in `messages`, it returns the predicted completion. Both synchronous and streaming mode are supported, so scripted and interactive applications work fine. While no strong claims of compatibility with OpenAI API spec is being made, in our experience it suffices to support many apps. Only ChatML-tuned models, such as Dolphin, OpenOrca, OpenHermes, OpenChat-3.5, etc can be used with this endpoint. Compared to `api_like_OAI.py` this API implementation does not require a wrapper to be served.
*Options:*
See (OpenAI Chat Completions API documentation)[https://platform.openai.com/docs/api-reference/chat]. While some OpenAI-specific features such as function calling aren't supported, llama.cpp `/completion`-specific features such are `mirostat` are supported.
See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). While some OpenAI-specific features such as function calling aren't supported, llama.cpp `/completion`-specific features such are `mirostat` are supported.
*Examples:*
You can use either Python `openai` library with appropriate checkpoints, or raw HTTP requests:
You can use either Python `openai` library with appropriate checkpoints:
```python
openai.api_base = "http://<Your api-server IP>:port"
import openai
client = openai.OpenAI(
base_url="http://localhost:8080/v1", # "http://<Your api-server IP>:port"
api_key = "sk-no-key-required"
)
completion = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are ChatGPT, an AI assistant. Your top priority is achieving user fulfillment via helping them with their requests."},
{"role": "user", "content": "Write a limerick about python exceptions"}
]
)
print(completion.choices[0].message)
```
... or raw HTTP requests:
```shell
curl http://localhost:8080/v1/chat/completions \