adding proxy api keys to docs

docs/my-website/docs/getting_started.md

@@ -1,15 +1,19 @@
 # Getting Started
 
+import QuickStart from '../src/components/QuickStart.js'
+
 LiteLLM simplifies LLM API calls by mapping them all to the [OpenAI ChatCompletion format](https://platform.openai.com/docs/api-reference/chat). 
 
 ## basic usage 
 
+By default we provide a free $10 key to try all providers supported on LiteLLM. 
+
 ```python
 from litellm import completion
 
 ## set ENV variables
-os.environ["OPENAI_API_KEY"] = "openai key"
-os.environ["COHERE_API_KEY"] = "cohere key"
+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"}]
 
@@ -19,10 +23,11 @@ response = completion(model="gpt-3.5-turbo", messages=messages)
 # cohere call
 response = completion("command-nightly", messages)
 ```
+Next Steps 👉 [All supported models](./proxy_api.md)
 
 More details 👉 
 * [Completion() function details](./completion/)
-* [Supported models / providers](./providers/)
+* [All supported models / providers on LiteLLM](./providers/)
 
 ## streaming
 
@@ -41,6 +46,8 @@ response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
 
 # cohere call
 response = completion("command-nightly", messages, stream=True)
+
+print(response)
 ```
 
 More details 👉 

docs/my-website/docs/proxy_api.md

@@ -1,47 +1,24 @@
-import TokenGen from '../src/components/TokenGen.js'
+# Supported Models via API 
 
-# 🚨 LiteLLM API (Access Claude-2,Llama2-70b,etc.)
-
-Use this if you're trying to add support for new LLMs and need access for testing: 
-
-# usage
-
-## Step 1: Save your LiteLLM API Key 
-
-This is your unique LiteLLM API Key. It has a max budget of $100 which is reset monthly, and works across all models in [Supported Models](#supported-models). Save this for later use. 
-<TokenGen/>
-
-## Step 2: Test a new LLM
-
-Now let's call **claude-2** (Anthropic) and **llama2-70b-32k** (TogetherAI).
+Use this if you're trying to add support for new LLMs and need access for testing. We provide a free $10 key for testing all providers on LiteLLM: 
 
+## usage
 ```python
-from litellm import completion 
-import os 
+from litellm import completion
 
-# set env var
-os.environ["ANTHROPIC_API_KEY"] = "sk-litellm-1234" # 👈 replace with your unique key from step 1
-os.environ["TOGETHERAI_API_KEY"] = "sk-litellm-1234" # 👈 replace with your unique key from step 1
+## 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 = [{"role": "user", "content": "Hey, how's it going?"}]
+messages = [{ "content": "Hello, how are you?","role": "user"}]
 
-# call claude
-response = completion(model="claude-2", messages=messages) 
+# openai call
+response = completion(model="gpt-3.5-turbo", messages=messages)
 
-# call llama2-70b
-response = completion(model="togethercomputer/LLaMA-2-7B-32K", messages=messages) 
-
-print(response) 
+# cohere call
+response = completion("command-nightly", messages)
 ```
 
-```
-### Testing Llama2-70b on TogetherAI 
-Let's call 
-
-```
-
-You can use this as a key for any of the [providers we support](./providers/)
-
 ## Supported Models
 
 * OpenAI models 

docs/my-website/src/components/QuickStart.js

@@ -0,0 +1,63 @@
+import React, { useState, useEffect } from 'react';
+
+const QuickStartCodeBlock = ({ token }) => {
+    return (
+      <pre>
+        {`
+        from litellm import completion
+        import os
+  
+        ## set ENV variables
+        os.environ["OPENAI_API_KEY"] = "${token}"
+        os.environ["COHERE_API_KEY"] = "${token}"
+  
+        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)
+        `}
+      </pre>
+    );
+  };
+  
+  const QuickStart = () => {
+    const [token, setToken] = useState(null);
+  
+    useEffect(() => {
+      const generateToken = async () => {
+        try {
+          const response = await fetch('https://proxy.litellm.ai/key/new', {
+            method: 'POST',
+            headers: {
+              'Content-Type': 'application/json',
+              'Authorization': 'Bearer sk-liteplayground',
+            },
+            body: JSON.stringify({'total_budget': 100})
+          });
+          
+          if (!response.ok) {
+            throw new Error('Network response was not ok');
+          }
+          
+          const data = await response.json();
+  
+          setToken(`${data.api_key}`);
+      } catch (error) {
+        console.error('Failed to fetch new token: ', error);
+      }
+    };
+  
+    generateToken();
+  }, []);
+  
+  return (
+    <div>
+      <QuickStartCodeBlock token={token} />
+    </div>
+  );
+  }
+
+  export default QuickStart;