2.6 KiB
import Image from '@theme/IdealImage';
LiteLLM Client: 1-Click Deploy LLMs + Debug Logs
LiteLLM offers a UI to:
- 1-Click Deploy LLMs - the client stores your api keys + model configurations
- Debug your Call Logs
<Image img={require('../../img/dashboard.png')} alt="Dashboard" />
Getting Started
- Make a
litellm.completion()call 👉 get your debugging dashboard
Example Code: Regular litellm.completion() call:
from litellm import completion
messages = [{ "content": "Hello, how are you?" ,"role": "user"}]
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
Completion() Output with dashboard
All completion() calls print with a link to your session dashboard
<Image img={require('../../img/dash_output.png')} alt="Dashboard" />
Example Output from litellm completion
Here's your LiteLLM Dashboard 👉 https://admin.litellm.ai/88911906-d786-44f2-87c7-9720e6031b45
<OpenAIObject chat.completion id=chatcmpl-7r6LtlUXYYu0QayfhS3S0OzroiCel at 0x7fb307375030> JSON: {
"id": "chatcmpl-7r6LtlUXYYu0QayfhS3S0OzroiCel",
"object": "chat.completion",
"created": 1692890157,
"model": "gpt-3.5-turbo-0613",
..............
Once created, your dashboard is viewable at - admin.litellm.ai/<your_email> 👋 Tell us if you need better privacy controls
See our live dashboard 👉 admin.litellm.ai
Code Setup
import litellm
## Setup for activating / using the litellm dashboard
litellm.email = "test_email@test.com"
LiteLLM Dashboard - 1-Click Deploy LLMs
LiteLLM allows you to add a new model using the liteLLM Dashboard
Navigate to the 'Add New LLM' Section <Image img={require('../../img/add_model.png')} alt="Dashboard" />
- Select Provider
- Select your LLM
- Add your LLM Key
LiteLLM Dashboard - Debug Logs
All your completion() and embedding() call logs are available on admin.litellm.ai/<your-token>
See your Logs below
Using your new LLM - Completion() with the LiteLLM Dashboard
from litellm import embedding, completion
# keys set in admin.litellm.ai/<your_email> or .env OPENAI_API_KEY
messages = [{ "content": "Hello, how are you?" ,"role": "user"}]
# openai call
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])