From ff482f2eb978d6f61b650fc676ced7e451377b62 Mon Sep 17 00:00:00 2001 From: ishaan-jaff Date: Tue, 7 Nov 2023 12:16:29 -0800 Subject: [PATCH] (docs) proxy server --- docs/my-website/docs/simple_proxy.md | 73 +++++++++++++++------------- 1 file changed, 38 insertions(+), 35 deletions(-) diff --git a/docs/my-website/docs/simple_proxy.md b/docs/my-website/docs/simple_proxy.md index c51a633e00..d594737fe4 100644 --- a/docs/my-website/docs/simple_proxy.md +++ b/docs/my-website/docs/simple_proxy.md @@ -180,7 +180,15 @@ $ litellm --model command-nightly -# [TUTORIAL] LM-Evaluation Harness with TGI +### Server Endpoints +- POST `/chat/completions` - chat completions endpoint to call 100+ LLMs +- POST `/completions` - completions endpoint +- POST `/embeddings` - embedding endpoint for Azure, OpenAI, Huggingface endpoints +- GET `/models` - available models on server + +## Advanced + +### [TUTORIAL] LM-Evaluation Harness with TGI Evaluate LLMs 20x faster with TGI via litellm proxy's `/completions` endpoint. @@ -208,12 +216,33 @@ $ python3 main.py \ ``` -## Endpoints: -- `/chat/completions` - chat completions endpoint to call 100+ LLMs -- `/embeddings` - embedding endpoint for Azure, OpenAI, Huggingface endpoints -- `/models` - available models on server +### Caching +#### Control caching per completion request +Caching can be switched on/off per /chat/completions request +- Caching on for completion - pass `caching=True`: + ```shell + curl http://0.0.0.0:8000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-3.5-turbo", + "messages": [{"role": "user", "content": "write a poem about litellm!"}], + "temperature": 0.7, + "caching": true + }' + ``` +- Caching off for completion - pass `caching=False`: + ```shell + curl http://0.0.0.0:8000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-3.5-turbo", + "messages": [{"role": "user", "content": "write a poem about litellm!"}], + "temperature": 0.7, + "caching": false + }' + ``` -## Set Custom Prompt Templates +### Set Custom Prompt Templates LiteLLM by default checks if a model has a [prompt template and applies it](./completion/prompt_formatting.md) (e.g. if a huggingface model has a saved chat template in it's tokenizer_config.json). However, you can also set a custom prompt template on your proxy in the `config.yaml`: @@ -240,7 +269,7 @@ model_list: $ litellm --config /path/to/config.yaml ``` -## Multiple Models +### Multiple Models If you have 1 model running on a local GPU and another that's hosted (e.g. on Runpod), you can call both via the same litellm server by listing them in your `config.yaml`. @@ -282,7 +311,7 @@ completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"rol print(completion.choices[0].message.content) ``` -## Save Model-specific params (API Base, API Keys, Temperature, etc.) +### Save Model-specific params (API Base, API Keys, Temperature, etc.) Use the [router_config_template.yaml](https://github.com/BerriAI/litellm/blob/main/router_config_template.yaml) to save model-specific information like api_base, api_key, temperature, max_tokens, etc. **Step 1**: Create a `config.yaml` file @@ -305,7 +334,7 @@ model_list: ```shell $ litellm --config /path/to/config.yaml ``` -## Model Alias +### Model Alias Set a model alias for your deployments. @@ -321,32 +350,6 @@ model_list: api_key: your_huggingface_api_key # [OPTIONAL] if deployed on huggingface inference endpoints api_base: your_api_base # url where model is deployed ``` -## Advanced -### Caching -#### Control caching per completion request -Caching can be switched on/off per /chat/completions request -- Caching on for completion - pass `caching=True`: - ```shell - curl http://0.0.0.0:8000/v1/chat/completions \ - -H "Content-Type: application/json" \ - -d '{ - "model": "gpt-3.5-turbo", - "messages": [{"role": "user", "content": "write a poem about litellm!"}], - "temperature": 0.7, - "caching": true - }' - ``` -- Caching off for completion - pass `caching=False`: - ```shell - curl http://0.0.0.0:8000/v1/chat/completions \ - -H "Content-Type: application/json" \ - -d '{ - "model": "gpt-3.5-turbo", - "messages": [{"role": "user", "content": "write a poem about litellm!"}], - "temperature": 0.7, - "caching": false - }' - ```