diff --git a/docs/my-website/docs/index.md b/docs/my-website/docs/index.md
index 2921f860ef..6c687b6fee 100644
--- a/docs/my-website/docs/index.md
+++ b/docs/my-website/docs/index.md
@@ -1,3 +1,6 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
# LiteLLM - Getting Started
import QuickStart from '../src/components/QuickStart.js'
@@ -5,25 +8,120 @@ import QuickStart from '../src/components/QuickStart.js'
## **Call 100+ LLMs using the same Input/Output Format**
## Basic usage
+
+
+
+
+
+
```python
from litellm import completion
import os
-
## set ENV variables
os.environ["OPENAI_API_KEY"] = "sk-litellm-7_NPZhMGxY2GoHC59LgbDw" # [OPTIONAL] replace with your openai key
-os.environ["COHERE_API_KEY"] = "sk-litellm-7_NPZhMGxY2GoHC59LgbDw" # [OPTIONAL] replace with your cohere key
-messages = [{ "content": "Hello, how are you?","role": "user"}]
-
-# openai call
-response = completion(model="gpt-3.5-turbo", messages=messages)
-
-# cohere call
-response = completion("command-nightly", messages)
+response = completion(
+ model="gpt-3.5-turbo",
+ messages=[{ "content": "Hello, how are you?","role": "user"}]
+)
```
+
+
+
+```python
+from litellm import completion
+import os
+
+## set ENV variables
+os.environ["ANTHROPIC_API_KEY"] = "sk-litellm-7_NPZhMGxY2GoHC59LgbDw" # [OPTIONAL] replace with your openai key
+
+response = completion(
+ model="claude-2",
+ messages=[{ "content": "Hello, how are you?","role": "user"}]
+)
+```
+
+
+
+
+
+```python
+from litellm import completion
+import os
+
+# auth: run 'gcloud auth application-default'
+os.environ["VERTEX_PROJECT"] = "hardy-device-386718"
+os.environ["VERTEX_LOCATION"] = "us-central1"
+
+response = completion(
+ model="chat-bison",
+ messages=[{ "content": "Hello, how are you?","role": "user"}]
+)
+```
+
+
+
+
+
+```python
+from litellm import completion
+import os
+
+os.environ["HUGGINGFACE_API_KEY"] = "huggingface_api_key"
+
+# e.g. Call 'WizardLM/WizardCoder-Python-34B-V1.0' hosted on HF Inference endpoints
+response = completion(
+ model="huggingface/WizardLM/WizardCoder-Python-34B-V1.0",
+ messages=[{ "content": "Hello, how are you?","role": "user"}],
+ api_base="https://my-endpoint.huggingface.cloud"
+)
+
+print(response)
+```
+
+
+
+
+
+```python
+from litellm import completion
+import os
+
+## set ENV variables
+os.environ["AZURE_API_KEY"] = ""
+os.environ["AZURE_API_BASE"] = ""
+os.environ["AZURE_API_VERSION"] = ""
+
+# azure call
+response = completion(
+ "azure/",
+ messages = [{ "content": "Hello, how are you?","role": "user"}]
+)
+```
+
+
+
+
+
+
+```python
+from litellm import completion
+
+response = completion(
+ model="ollama/llama2",
+ messages = [{ "content": "Hello, how are you?","role": "user"}],
+ api_base="http://localhost:11434"
+)
+```
+
+
+
+
+
+
## Streaming
Same example from before. Just pass in `stream=True` in the completion args.