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Feb 25, 2024
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(docs) using openai compatible endpoints #2189

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53 changes: 24 additions & 29 deletions docs/my-website/docs/providers/openai_compatible.md
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Expand Up @@ -6,42 +6,37 @@ To call models hosted behind an openai proxy, make 2 changes:

2. **Do NOT** add anything additional to the base url e.g. `/v1/embedding`. LiteLLM uses the openai-client to make these calls, and that automatically adds the relevant endpoints.

## Usage

## Usage - completion
```python
import litellm
from litellm import embedding
litellm.set_verbose = True
import os


litellm_proxy_endpoint = "http://0.0.0.0:8000"
bearer_token = "sk-1234"

CHOSEN_LITE_LLM_EMBEDDING_MODEL = "openai/GPT-J 6B - Sagemaker Text Embedding (Internal)"

litellm.set_verbose = False

print(litellm_proxy_endpoint)



response = embedding(

model = CHOSEN_LITE_LLM_EMBEDDING_MODEL, # add `openai/` prefix to model so litellm knows to route to OpenAI

api_key=bearer_token,

api_base=litellm_proxy_endpoint, # set API Base of your Custom OpenAI Endpoint

input=["good morning from litellm"],

api_version='2023-07-01-preview'

response = litellm.completion(
model="openai/mistral, # add `openai/` prefix to model so litellm knows to route to OpenAI
api_key="sk-1234", # api key to your openai compatible endpoint
api_base="http://0.0.0.0:8000", # set API Base of your Custom OpenAI Endpoint
messages=[
{
"role": "user",
"content": "Hey, how's it going?",
}
],
)
print(response)
```

print('================================================')
## Usage - embedding

print(len(response.data[0]['embedding']))
```python
import litellm
import os

response = litellm.embedding(
model="openai/GPT-J", # add `openai/` prefix to model so litellm knows to route to OpenAI
api_key="sk-1234", # api key to your openai compatible endpoint
api_base="http://0.0.0.0:8000", # set API Base of your Custom OpenAI Endpoint
input=["good morning from litellm"]
)
print(response)
```