Model Catalog Migration 8/9: Extended LLM Provider Integrations

integrations/llms/ai21.mdx

@@ -30,13 +30,13 @@ print(response.choices[0].message.content)
 ```
 
 ```js Javascript icon="square-js"
-        import Portkey from 'portkey-ai'
+import Portkey from 'portkey-ai'
 
 // 1. Install: npm install portkey-ai
 // 2. Add @ai21 provider in model catalog
 // 3. Use it:
 
-        const portkey = new Portkey({
+const portkey = new Portkey({
     apiKey: "PORTKEY_API_KEY"
 })
 
@@ -48,7 +48,7 @@ const response = await portkey.chat.completions.create({
 console.log(response.choices[0].message.content)
 ```
 
-```python OpenAI Py icon="openai"
+```python OpenAI Py icon="python"
 from openai import OpenAI
 from portkey_ai import PORTKEY_GATEWAY_URL
 
@@ -69,7 +69,7 @@ response = client.chat.completions.create(
 print(response.choices[0].message.content)
         ```
 
-```js OpenAI JS icon="openai"
+```js OpenAI JS icon="square-js"
 import OpenAI from "openai"
 import { PORTKEY_GATEWAY_URL } from "portkey-ai"
 

integrations/llms/anthropic.mdx

@@ -63,7 +63,7 @@ const response = await portkey.chat.completions.create({
 console.log(response.choices[0].message.content)
 ```
 
-```python OpenAI Py icon="openai"
+```python OpenAI Py icon="python"
 from openai import OpenAI
 from portkey_ai import PORTKEY_GATEWAY_URL
 
@@ -85,7 +85,7 @@ response = client.chat.completions.create(
 print(response.choices[0].message.content)
 ```
 
-```js OpenAI JS icon="openai"
+```js OpenAI JS icon="square-js"
 import OpenAI from "openai"
 import { PORTKEY_GATEWAY_URL } from "portkey-ai"
 

integrations/llms/anyscale-llama2-mistral-zephyr.mdx

@@ -45,7 +45,7 @@ const response = await portkey.chat.completions.create({
 console.log(response.choices[0].message.content)
 ```
 
-```python OpenAI Py icon="openai"
+```python OpenAI Py icon="python"
 from openai import OpenAI
 from portkey_ai import PORTKEY_GATEWAY_URL
 
@@ -66,7 +66,7 @@ response = client.chat.completions.create(
 print(response.choices[0].message.content)
 ```
 
-```js OpenAI JS icon="openai"
+```js OpenAI JS icon="square-js"
 import OpenAI from "openai"
 import { PORTKEY_GATEWAY_URL } from "portkey-ai"
 

integrations/llms/cerebras.mdx

@@ -1,107 +1,153 @@
 ---
 title: "Cerebras"
+description: "Integrate Cerebras models with Portkey's AI Gateway"
 ---
 
-Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including the models hosted on [Cerebras Inference API](https://cerebras.ai/inference).
+Portkey provides a robust and secure gateway to integrate various Large Language Models (LLMs) into applications, including [Cerebras Inference API](https://cerebras.ai/inference).
 
-<Note>
-Provider Slug: `cerebras`
-</Note>
+With Portkey, take advantage of features like fast AI gateway access, observability, prompt management, and more, while securely managing API keys through [Model Catalog](/product/model-catalog).
 
-## Portkey SDK Integration with Cerebras
+## Quick Start
 
-Portkey provides a consistent API to interact with models from various providers. To integrate Cerebras with Portkey:
+Get Cerebras working in 3 steps:
 
-### 1\. Install the Portkey SDK
-<Tabs>
-    <Tab title="NodeJS">
-        ```sh
-        npm install --save portkey-ai
-        ```
-    </Tab>
-    <Tab title="Python">
-        ```sh
-        pip install portkey-ai
-        ```
-    </Tab>
+<CodeGroup>
+```python Python icon="python"
+from portkey_ai import Portkey
 
-  </Tabs>
+# 1. Install: pip install portkey-ai
+# 2. Add @cerebras provider in model catalog
+# 3. Use it:
 
+portkey = Portkey(api_key="PORTKEY_API_KEY")
 
+response = portkey.chat.completions.create(
+    model="@cerebras/llama3.1-8b",
+    messages=[{"role": "user", "content": "Say this is a test"}]
+)
 
-### 2\. Initialize Portkey with Cerebras
+print(response.choices[0].message.content)
+```
 
-To use Cerebras with Portkey, get your API key from [here](https://cerebras.ai/inference), then add it to Portkey to create the virtual key.
-<Tabs>
-    <Tab title="NodeJS SDK">
-        ```js
-        import Portkey from 'portkey-ai'
+```js Javascript icon="square-js"
+import Portkey from 'portkey-ai'
 
-        const portkey = new Portkey({
-            apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
-            provider:"@CEREBRAS_PROVIDER" // Your Cerebras Inference virtual key
-        })
-        ```
-    </Tab>
-    <Tab title="Python SDK">
-        ```py
-        from portkey_ai import Portkey
-
-        portkey = Portkey(
-            api_key ="PORTKEY_API_KEY",  # Replace with your Portkey API key
-            provider="@CEREBRAS_PROVIDER" # Your Cerebras Inference virtual key
-        )
-        ```
-    </Tab>
+// 1. Install: npm install portkey-ai
+// 2. Add @cerebras provider in model catalog
+// 3. Use it:
+
+const portkey = new Portkey({
+    apiKey: "PORTKEY_API_KEY"
+})
 
-  </Tabs>
+const response = await portkey.chat.completions.create({
+    model: "@cerebras/llama3.1-8b",
+    messages: [{ role: "user", content: "Say this is a test" }]
+})
 
+console.log(response.choices[0].message.content)
+        ```
 
+```python OpenAI Py icon="python"
+from openai import OpenAI
+from portkey_ai import PORTKEY_GATEWAY_URL
+
+# 1. Install: pip install openai portkey-ai
+# 2. Add @cerebras provider in model catalog
+# 3. Use it:
+
+client = OpenAI(
+    api_key="PORTKEY_API_KEY",  # Portkey API key
+    base_url=PORTKEY_GATEWAY_URL
+)
+
+response = client.chat.completions.create(
+    model="@cerebras/llama3.1-8b",
+    messages=[{"role": "user", "content": "Say this is a test"}]
+)
+
+print(response.choices[0].message.content)
+```
+
+```js OpenAI JS icon="square-js"
+import OpenAI from "openai"
+import { PORTKEY_GATEWAY_URL } from "portkey-ai"
+
+// 1. Install: npm install openai portkey-ai
+// 2. Add @cerebras provider in model catalog
+// 3. Use it:
+
+const client = new OpenAI({
+    apiKey: "PORTKEY_API_KEY",  // Portkey API key
+    baseURL: PORTKEY_GATEWAY_URL
+})
+
+const response = await client.chat.completions.create({
+    model: "@cerebras/llama3.1-8b",
+    messages: [{ role: "user", content: "Say this is a test" }]
+})
+
+console.log(response.choices[0].message.content)
+```
+
+```sh cURL icon="square-terminal"
+# 1. Add @cerebras provider in model catalog
+# 2. Use it:
+
+curl https://api.portkey.ai/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
+  -d '{
+    "model": "@cerebras/llama3.1-8b",
+    "messages": [
+      { "role": "user", "content": "Say this is a test" }
+    ]
+  }'
+```
+</CodeGroup>
 
+<Note>
+**Tip:** You can also set `provider="@cerebras"` in `Portkey()` and use just `model="llama3.1-8b"` in the request.
+</Note>
 
-### 3\. Invoke Chat Completions
-<Tabs>
-    <Tab title="NodeJS SDK">
-        ```js
-        const chatCompletion = await portkey.chat.completions.create({
-            messages: [{ role: 'user', content: 'Say this is a test' }],
-            model: 'llama3.1-8b',
-        });
+## Add Provider in Model Catalog
 
-        console.log(chatCompletion.choices);
-        ```
-    </Tab>
-    <Tab title="Python SDK">
-        ```python
-        completion = portkey.chat.completions.create(
-            messages= [{ "role": 'user', "content": 'Say this is a test' }],
-            model= 'llama3.1-8b'
-        )
-
-        print(completion)
-        ```
-    </Tab>
+1. Go to [**Model Catalog → Add Provider**](https://app.portkey.ai/model-catalog/providers)
+2. Select **Cerebras**
+3. Choose existing credentials or create new by entering your [Cerebras API key](https://cerebras.ai/inference)
+4. Name your provider (e.g., `cerebras-prod`)
 
-  </Tabs>
+<Card title="Complete Setup Guide →" href="/product/model-catalog">
+  See all setup options, code examples, and detailed instructions
+</Card>
 
 ---
 
 ## Supported Models
 
-Cerebras currently supports `Llama-3.1-8B` and `Llama-3.1-70B`. You can find more info here:
-<Info>
-[![Logo](/images/llms/apple-touch-icon.png)Overview - Starter KitStarter Kit](https://inference-docs.cerebras.ai/introduction)
-</Info>
-## Next Steps
-
-The complete list of features supported in the SDK are available on the link below.
-
-<Card title="SDK" href="/api-reference/sdk">
+<Card title="Cerebras Models" icon="list" href="https://inference-docs.cerebras.ai/introduction">
+  View all available models and documentation
 </Card>
 
-You'll find more information in the relevant sections:
+## Next Steps
 
-1. [Add metadata to your requests](/product/observability/metadata)
-2. [Add gateway configs to your Cerebras](/product/ai-gateway/configs)[ requests](/product/ai-gateway/configs)
-3. [Tracing Cerebras requests](/product/observability/traces)
-4. [Setup a fallback from OpenAI to Cerebras](/product/ai-gateway/fallbacks)
+<CardGroup cols={2}>
+  <Card title="Add Metadata" icon="tags" href="/product/observability/metadata">
+    Add metadata to your Cerebras requests
+  </Card>
+  <Card title="Gateway Configs" icon="gear" href="/product/ai-gateway/configs">
+    Add gateway configs to your Cerebras requests
+  </Card>
+  <Card title="Tracing" icon="chart-line" href="/product/observability/traces">
+    Trace your Cerebras requests
+  </Card>
+  <Card title="Fallbacks" icon="arrow-rotate-left" href="/product/ai-gateway/fallbacks">
+    Setup fallback from OpenAI to Cerebras
+  </Card>
+</CardGroup>
+
+For complete SDK documentation:
+
+<Card title="SDK Reference" icon="code" href="/api-reference/sdk/list">
+  Complete Portkey SDK documentation
+</Card>