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docs/my-website/docs/debugging/hosted_debugging.md
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import Image from '@theme/IdealImage'; import Image from '@theme/IdealImage';
# LiteLLM Client: Debug Logs + Instant LLM Deploys # LiteLLM Client: 1-Click Deploy LLMs + Debug Logs
LiteLLM offers a UI to: LiteLLM offers a UI to:
* 1-Click Deploy LLMs - the client stores your api keys + model configurations * 1-Click Deploy LLMs - the client stores your api keys + model configurations
* Debug your Call Logs * Debug your Call Logs
@ -8,7 +8,9 @@ LiteLLM offers a UI to:
<Image img={require('../../img/dashboard.png')} alt="Dashboard" /> <Image img={require('../../img/dashboard.png')} alt="Dashboard" />
## Getting Started ## Getting Started
1 Step: <a target="_blank" href="https://colab.research.google.com/github/https://colab.research.google.com/drive/1y2ChqxJOwEByThibxYMEpY5P6_RTNjj4?usp=sharing">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
* Make a `litellm.completion()` call 👉 get your debugging dashboard * Make a `litellm.completion()` call 👉 get your debugging dashboard
Example Code: Regular `litellm.completion()` call: Example Code: Regular `litellm.completion()` call:
@ -23,6 +25,7 @@ All `completion()` calls print with a link to your session dashboard
<Image img={require('../../img/dash_output.png')} alt="Dashboard" /> <Image img={require('../../img/dash_output.png')} alt="Dashboard" />
Example Output from litellm completion Example Output from litellm completion
```bash ```bash
Here's your LiteLLM Dashboard 👉 https://admin.litellm.ai/88911906-d786-44f2-87c7-9720e6031b45 Here's your LiteLLM Dashboard 👉 https://admin.litellm.ai/88911906-d786-44f2-87c7-9720e6031b45
@ -38,12 +41,7 @@ Here's your LiteLLM Dashboard 👉 https://admin.litellm.ai/88911906-d786-44f2-8
Once created, your dashboard is viewable at - `admin.litellm.ai/<your_email>` [👋 Tell us if you need better privacy controls](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version?month=2023-08) Once created, your dashboard is viewable at - `admin.litellm.ai/<your_email>` [👋 Tell us if you need better privacy controls](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version?month=2023-08)
See our live dashboard 👉 [admin.litellm.ai](https://admin.litellm.ai/) See our live dashboard 👉 [admin.litellm.ai](https://admin.litellm.ai/)
## Usage
### Requirements
1. **Needs litellm>=0.1.438***
2. Set `litellm.email` account. You can set your user email in 2 ways.
- By setting it on the module - `litellm.email=<your_email>`.
- By setting it as an environment variable - `os.environ["LITELLM_EMAIL"] = "your_email"`.
## Code Setup ## Code Setup
```python ```python
@ -54,16 +52,19 @@ litellm.email = "test_email@test.com"
``` ```
## Using LiteLLM Dashboard - Add New LLMs ## LiteLLM Dashboard - 1-Click Deploy LLMs
LiteLLM allows you to add a new model using the liteLLM Dashboard LiteLLM allows you to add a new model using the liteLLM Dashboard
Go to `admin.litellm.ai/<your_email>`
Navigate to the 'Add New LLM' Section Navigate to the 'Add New LLM' Section
<Image img={require('../../img/add_model.png')} alt="Dashboard" /> <Image img={require('../../img/add_model.png')} alt="Dashboard" />
- Select Provider - Select Provider
- Select your LLM - Select your LLM
- Add your LLM Key - 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 ### Using your new LLM - Completion() with the LiteLLM Dashboard
```python ```python
from litellm import embedding, completion from litellm import embedding, completion
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response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}]) response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
``` ```
## Using LiteLLM Dashboard - Debug your Call Logs
```python
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"}])
```
See your Logs below